assig 3

attached

Assignment Overview: This semester, you will write a series of five papers, with each paper building on (and sometimes reusing) material from prior papers. To make sure your first paper (Paper I: Literature Review) provides a good foundation for subsequent papers, this “Read Aloud Assignment” focuses on helping you know
what to write and
how to write it. Grading is pass / fail: Just make sure to complete all four steps below to earn all assignment points. You will also have a good start on your first paper!

Don't use plagiarized sources. Get Your Custom Essay on

assig 3

Just from $13/Page

Order Essay

For this “Read Aloud Assignment”, I want you to complete four steps (see the Assignment #3 instructions for more details)

Step One: I want you to upload your
first full page of Paper I. Submit your one-page document by uploading the paper file to Canvas.

Step Two: I want you to read your page aloud to another person. Then have your reader complete the six “Questions For Your Listener” survey

Step Four: Finally, you will rate several statements about your own writing

Lecture and Lab Presentations:

The main
lecture content this week is Chapter E (CCP) and Chapter 7 (Salkind), both on developing research ideas. Please note that the order of the class lecture material for the Salkind textbook may differ from the order of chapters in that book, so make sure to keep an eye on the syllabus so you know which chapters we are covering each week. Both Chapter B and Chapter 7 talk about research hypotheses, where will discuss the components needed for a good research hypothesis. That is, it is a very specific statement that predicts outcomes, often by comparison to control groups.

Your Week Two
lab presentation focuses on your
Social Loafing (Loafing) study predictions. Read all presentations early so you don’t fall behind. A quick note: As you read the lab material, look at the hypothesis for your
Social Loafing study and see if it meets all of the requirements for a good hypothesis presented in your lecture material!

Papers:

You should be working on your first paper by now.
Paper I: Study One Literature Review will be due
Monday, September 19th. There are example papers, instructions, grade rubrics, and a checklist available online to help you with this paper, but it is important to get an early start on it! I talk about the paper a lot more in the lab powerpoint presentations, so make sure you know what goes into this paper. I’ll highlight a few of those elements below, but your best bet is to review the materials online right now to make sure you have a good start on the paper.

1. Look over the instructions and the example papers carefully and make sure you follow those requirements. Your title page should be in APA format (including proper headers, page numbers, and title elements). Note that all class materials were revised right before this semester session to accommodate the new 7th Edition of the American Psychological Association Publication Manual. If you look at the example papers, you’ll find that they align with the 7th edition now, as does the APA formatting powerpoint presentation. I also included an example paper published by the APA with additional notes in case you would like to see yet another example.

2. I STRONGLY recommend you watch the APA formatting video. You can find it by clicking

https://www.youtube.com/watch?v=Mrh5OC3T6dc (Links to an external site.)

It takes 10 minutes and will save you a lot of headaches in the future if you learn how to format early in the semester!

3. I want to give you some hints about the paper. Make sure your title page is PERFECT. It has very specific standards, and we will mark off a point for each error. Your second page starts the main body of your paper. There are some important APA format aspects here as well (the header is a little different, but you repeat your title).The main paper starts broadly and narrows toward the end. That is, I suggest giving an overview of
Social Loafing early, defining the concept. Then discuss five studies in this area, all the time narrowing down as you near the end of the paper. Your hypothesis comes at the end of the paper. I gave this hypothesis to you in your experimenter script, so feel free to copy and paste it. The pages leading up to that hypothesis, though, should be your own work, and they should help support your hypotheses. Finally, your references start on their own page, with a lot of APA format requirements here. Review the APA formatting lecture to make sure you reference correctly.

4. My best piece of advice for this paper is to write it as if your reader knows nothing about
Social Loafing, but also write it as if they do know about research methods. Your APA formatting should be perfect, as your reader will be familiar with the general organization of an empirical APA research report, but you have to “teach them” about
Social Loafing in your literature review. Don’t assume they know a lot about the topic – YOU will educate them on it. When I submit my own papers to journals, I have to do the same thing – the editors know a lot about psychology but not always a lot about my specific topic. Potential journal readers are the same way. Thus
my audience is APA knowledgeable but not necessarily topic-knowledgeable. Keep that in mind as you write your papers. In addition, there is a checklist on Canvas that walks you through each segment of the paper. If you can check “YES” to all items on the checklist then you have a great chance of getting a good paper grade. The checklist highlights both content as well as APA style. You’ll find a similar checklist for all papers in this course. I highly suggest you use them!

Discussions:

None this week!

Assignments:

Assignment #3 (Read Aloud Assignment). There are a few different “due dates” for Assignment #3, though the official Canvas-based due date is
Sunday, September 11th. For Assignment #3, you need to write the first page of your literature review for Paper I, and you need to write it quickly! One of our course goals is to help you write clearly, thoughtfully, and properly in APA format. To accomplish this, we designed this Assignment #3, which asks you to first write your first page for Paper I and then
read that whole page out loud to another person of your choosing (classmate, friend, family member, etc.). Because your official Assignment #3 deadline is
September 11th, I recommend having the first page written no later than
Friday and then reading it aloud to another person by
Saturday. That will give you time to work on the question associated with Assignment #3 so that you can turn it in on
Sunday).

Note #1: See the assignment instructions for more information, but my hope is that you will learn that reading your writing aloud is a great tool for making sure it is clear and precise. You will get some feedback on your paper from your listener, and you will provide ratings about your experience in Canvas. Make sure to carefully read the assignment instructions
now so that you will be ready to submit it on Sunday.

Note #2: If the person you recruit to listen to your “read aloud” assignment will be one of your participants, then make sure to have them complete your survey (for Assignment #4) before you read them the first page of your paper. You are welcome to have them do both, but you don’t want them to learn about your study by listening to your read aloud assignment before they participate in the study.

image1

Read Aloud Assignment #3

For this “Read Aloud Assignment”, I want you to complete four steps.

Step One: I want you to upload your
first full page of Paper I (the introductory paragraph and second paragraph, both double-spaced and consisting of around 300 to 350 words total). This page does not need to be the final version that you will use for Paper I, but make sure to proofread it carefully for both content and writing quality. While you should refer to the “Paper I: Literature Review Instructions” for specific guidance about the content required for this paper, I only need you to focus on the
first full page for this “Read Aloud Assignment”.

Question 1: Submit your one-page document by uploading the paper file to Canvas.

Step Two: I want you to read your page aloud to another person. This can be anyone you want, including other class members, other students at FIU, your family, a friend, etc. Then have your reader complete the “Questions For Your Listener” survey below so they can give you some feedback on your writing and paper content.
Note: The “Listener” can be same person who served as one of your three study participants, but they must have already completed the study if you want them to be the “Listener” for this assignment.

After reading your paper aloud to your listener, ask them to rate the following six statements (Questions 2 through 7) about your paper on a scale ranging from 1 (Strongly Disagree) to 7 (Strongly Agree). Transfer their ratings to the electronic version of this survey assignment in Canvas. Feel free to ask your listener for clarification if their responses surprise you, as their feedback may give you some good insight into how to revise your paper before your formal Paper I submission.

Questions For Your Listener										Rating (1 to 7)
2. The introductory paragraph provides a clear description of the purpose and topic of the paper
3. The paper has a nice flow, with smooth transitions between sentences as well as between the introductory paragraph and the second paragraph
4. The second paragraph (which most likely focuses on describing a prior study or studies on the same topic) seems to lack the detail that I need to fully understand that prior study
5. Although I am only listening to the student author as they read me their paper, I feel like the paper needs additional proofreading
6. The student author does a good job supporting factual claims by citing other authors/studies
7. I feel like I have a good understanding of the topic the author discussed in this paper

Step Three: To make sure you have a good grasp of your study hypotheses, I want you to tell your reader what your study is about
in your own words and then ask them whether the first page of your paper does a good job setting up or leading into those hypotheses (
Feel free to refer to the study debriefing statement for information about the study predictions, but avoid simply reading that debriefing statement to your listener. Instead, summarize the study in your own words). Then have your listener describe back to you what your study is about. Based on their responses back to you, rate the statements below on a scale ranging from 1 (Strongly Disagree) to 7 (Strongly Agree). Transfer those ratings to the survey in Canvas.

Rating (1 to 7)

Questions For You (The Author)

8. My listener accurately described my study hypotheses

9. My listener seems confused about my study design

Step Four: Now I want YOU to rate the following statements about your writing and the content of your one-page “Read Aloud Assignment” on a scale ranging from 1 (Strongly Disagree) to 7 (Strongly Agree). Transfer YOUR ratings to the survey in Canvas.

Questions For You (The Author)

Rating (1 to 7)

10. I feel my introductory paragraph adequately describes what my paper is about.

11. I think I can do a better job making sure that my paper flows well, with smoother transitions between sentences and between paragraphs

12. I think I need more detail when describing prior research so that I can better discuss what the prior research did and what they found.

13. Reading my paper aloud helped me figure out which sentences / passages need additional proofreading attention

14. Reading my paper aloud helped me figure out where I need to better cite resources to support my factual claims.

15. I feel like I have a good idea about how to improve my writing before I turn in the final draft of Paper I.

This article was downloaded by: [5.198.138.130] On: 28 May 2022, At: 10:40
Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
INFORMS is located in Maryland, USA

Management Science

Publication details, including instructions for authors and subscription information:
http://pubsonline.informs.org

Working Harder or Hardly Working? Posting Performance
Eliminates Social Loafing and Promotes Social Laboring in
Workgroups
Robert B. Lount Jr., Steffanie L. Wilk

To cite this article:
Robert B. Lount Jr., Steffanie L. Wilk (2014) Working Harder or Hardly Working? Posting Performance Eliminates Social Loafing
and Promotes Social Laboring in Workgroups. Management Science 60(5):

1098

-1106. https://doi.org/10.1287/mnsc.2013.1820

Full terms and conditions of use: https://pubsonline.informs.org/Publications/Librarians-Portal/PubsOnLine-Terms-and-
Conditions

This article may be used only for the purposes of research, teaching, and/or private study. Commercial use
or systematic downloading (by robots or other automatic processes) is prohibited without explicit Publishe

approval, unless otherwise noted. For more information, contact permissions@informs.org.

The Publisher does not warrant or guarantee the article’s accuracy, completeness, merchantability, fitness
for a particular purpose, or non-infringement. Descriptions of, or references to, products or publications, or
inclusion of an advertisement in this article, neither constitutes nor implies a guarantee, endorsement, or
support of claims made of that product, publication, or service.

Please scroll down for article—it is on subsequent pages

With 12,500 members from nearly 90 countries, INFORMS is the largest international association of operations research (O.R.)
and analytics professionals and students. INFORMS provides unique networking and learning opportunities for individual
professionals, and organizations of all types and sizes, to better understand and use O.R. and analytics tools and methods to
transform strategic visions and achieve better outcomes.
For more information on INFORMS, its publications, membership, or meetings visit http://www.informs.org

http://pubsonline.informs.org

https://doi.org/10.1287/mnsc.2013.1820

https://pubsonline.informs.org/Publications/Librarians-Portal/PubsOnLine-Terms-and-Conditions

http://www.informs.org

MANAGEMENT SCIENCE
Vol. 60, No. 5, May 2014, pp. 1098–1106
ISSN 0025-1909 (print) � ISSN 1526-5501 (online) http://dx.doi.org/10.1287/mnsc.2013.1820

Working Harder or Hardly Working?

Posting

Performance Eliminates Social Loafing and
Promotes Social Laboring in Workgroups

Robert B. Lount Jr., Steffanie L. Wilk
Department of Management and Human Resources, Fisher College of Business, Ohio State University,

Columbus, Ohio 43210 {lount@fisher.osu.edu, wilk@fisher.osu.edu}

The current paper examines how posting performance—an act that triggers increased social comparisons
between workers—influences employees’ motivation when working in groups. In the study, posting

employee performance moderated the relationship between groupwork and employee motivation. When indi-
vidual performance was publicly posted in the workplace, employees working in a group performed better than
when working alone (i.e., social laboring); however, when individual performance was not posted, employees
working in a group performed worse than when working alone (i.e., social loafing). The findings shed light on
how social comparisons can have positive implications for employee performance in groups.

Keywords : organizational studies; effectiveness performance; motivation; productivity
History : Received September 14, 2011; accepted August 6, 2013, by Jesper Sørensen, organizations. Published

online in Articles in Advance January 2, 2014.

Introduction
Despite the widespread use of groups and teams in
organizations to perform both routine and specialized
tasks, concerns have long been raised that working in
a group has the potential to harm individual motiva-
tion. Numerous studies have documented that when
inputs are pooled together, group members experi-
ence a diffusion of responsibility where individuals
reduce their effort and become less productive com-
pared with when they work alone (for a review, see
Karau and Williams 1993); this phenomenon is often
referred to as social loafing or free riding. Although
social loafing is often described as a potential mal-
ady that can harm motivation when individuals work
in groups (Hackman 2002, Kerr and Tindale 2004), in
recent years, researchers have increasingly begun to
document instances of social laboring—when work-
ing in a group can lead individuals to increase their
effort and be more productive compared with individ-
uals working alone (for reviews, see Kerr and Hertel
2011, Larson 2010, Weber and Hertel 2007). Consid-
ering the frequency with which employees work in
groups, it is both practically and theoretically impor-
tant to help shed light on features in the workplace
that not only help to eliminate social loafing but also
may promote social laboring.

In the current paper, we examine how having
performance publicly compared with others in the
workplace affects employee motivation when indi-
viduals work in groups. We argue that when social

comparison processes become salient via the pres-
ence of posting performance, employees working in
groups will increase their motivation (i.e., social labor-
ing); however, when social comparison processes are
minimized via the absence of posting performance,
employees working in groups will be inclined to
reduce their task motivation (i.e., social loafing). We
test our predictions in a call center where employees
performed their work either alone or as a member
of a temporary workgroup. The setting allowed us to
directly examine how posting performance relates to
both social loafing and social laboring when employ-
ees worked in groups compared with when they
worked alone.

Social Bases of Motivation in Workgroups
For more than a century, scholars have documented
that working in a group can affect individuals’ levels
of task motivation (Köhler 1926, Ringelmann 1913).1

The positive or negative impact of working with
others on task motivation has been attributed to
two main psychological mechanisms: (1) perceived
instrumentality and (2) social comparison processes.
Whereas the former affects effort through an individ-
ual’s assessment of how necessary his or her con-
tribution is for the group to accomplish its task,
the latter affects effort through influencing the value

1 We define a group as two or more individuals whose inputs are
pooled together toward a common goal (Williams 2010).

1098

Lount and Wilk: Working Harder or Hardly Working?
Management Science 60(5), pp. 1098–1106, © 2014 INFORMS 1099

individuals place on how they perform relative to
other group members.

Research supporting social comparison theory
(Festinger 1954) has documented that individuals
generally prefer to compare favorably against others
(for reviews, see Buunk and Gibbons 2007, Suls and
Wheeler 2000). When performance comparisons are
made salient among group members, individual effort
can be influenced by the value that individuals place
on how their performance is evaluated by others in
the group, as well as by themselves. Given that indi-
viduals generally desire to be seen as valued mem-
bers of the groups to which they belong (Hogg 1996),
making performance comparisons salient allows indi-
viduals to both demonstrate and evaluate their rela-
tive value to the group (Harkins and Szymanski 1989).
Additionally, when individuals work together on a
shared task, concerns over being seen as the weakest
link, or the group member who is responsible for low-
ered performance, can fuel individual effort in groups
(Hertel et al. 2000). Moreover, providing explicit com-
parisons can increase competition, where individu-
als work harder in an effort to outperform others
(Lount and Phillips 2007). Taken together, when per-
formance comparisons are made salient in groups,
individuals can feel increasingly accountable for their
contributions; the comparisons lead individuals to
place increased value on performing well so that they
can be seen favorably. Accordingly, researchers have
argued that increasing the salience of performance
comparisons can help not only eliminate social loafing
(e.g., Karau and Williams 1993, Williams et al. 1981)
but also promote social laboring in groups (e.g., Kerr
et al. 2005, Lount et al. 2008).

Although promoting performance comparisons
within groups has the potential to improve effort, the
motivational potential of such performance compar-
isons depends on the perceived similarity of those
being compared (e.g., Festinger 1954, Harkins 1987,
Sanders et al. 1978). Within groups, comparisons with
others who are working on an identical task provide
information about group members’ relative abilities
and contributions, making performance comparisons
particularly relevant and increasing their motivational
potential (Suls et al. 2002). For instance, Harkins
(1987) documented that the task motivation of coac-
tors (i.e., individuals who work near one another but
who do not have a shared outcome) was larger when
they anticipated having their performance compared
with another person who was working on an identical
task (i.e., generating as many uses as possible for the
same object) compared with when they anticipated
being compared with someone performing a dissimi-
lar task (i.e., generating as many uses as possible for
a different object).

Although working alongside group members per-
forming an identical task has the potential to increase

motivation via social comparison processes, working
on a task identical to one’s teammates’ paradoxi-
cally also has the potential to harm individual moti-
vation and promote social loafing. Namely, working
on an identical task can lead individuals to lower
the perceived importance of their own contributions.
In other words, perceived instrumentality can be
harmed because individuals become aware that they
are not solely responsible for the performance on
the assigned task and that other group members can
make up for any one individual’s low performance
(Kerr 1983). Supporting the possibility that motivation
is harmed when individuals perform a task identical
to that of their teammates, Karau and Williams’ (1993)
meta-analysis on motivation in groups documented
social loafing effects to occur when group members
worked on identical tasks, whereas individual moti-
vation was not harmed when teammates worked
on different tasks. Taken together, basic research on
individual motivation in groups highlights that both
social comparison processes and concerns about per-
ceived instrumentality play a critical role in influenc-
ing effort when working on a task identical to one’s
teammates’ (Kerr et al. 2007, Hertel et al. 2008). As
such, when teammates perform the same task as one
another, understanding how to structure groupwork
to avoid the potential negative effects of decreased
perceptions of instrumentality will likely depend on
the how social comparison processes are affected by
the broader organizational context.

Whereas prior research has found evidence of social
loafing in the laboratory (for reviews, see Karau and
Williams 1993, Rutte 2003) and in simulated work
environments (e.g., Early 1989, Erev et al. 1993),
the degree to which such findings necessarily cor-
respond or predict the behavior of employees in
workgroups is unclear. Moreover, doubts have been
raised as to whether social loafing will necessarily
even occur among employees (e.g., Erez and Somech
1996) because there are a number of features present
in the workplace that may deter the propensity to
reduce task motivation when working with others
(e.g., desire for organization to perform well, poten-
tial for promotion, concerns over being laid off). To
date, the most frequently cited evidence of loafing
in organizational workgroups comes from survey-
based studies that have examined perceptions of loaf-
ing (e.g., George 1992, Liden et al. 2004). Perceptions
of loafing—although tapping into beliefs about group-
oriented behaviors (e.g., letting others do more of the
work)—do not necessarily reflect actual changes in
behavior (i.e., motivation losses) caused by working
on a shared task. Additionally, building on recent doc-
umentations of social laboring obtained from labora-
tory studies (e.g., Kerr and Hertel 2011) and in team
sports (e.g., Hüffmeier and Hertel 2012), it has been

Lount and Wilk: Working Harder or Hardly Working?
1100 Management Science 60(5), pp. 1098–1106, © 2014 INFORMS

suggested that the social setting may be structured
not only to eliminate social loafing but also to pro-
mote social laboring when employees work in groups
(van Dick et al. 2009).

We argue below that posting employee perfor-
mance in the workplace—an action that can help to
activate social comparison processes—constitutes a
critical component of the work context that can help
to eliminate social loafing and promote social laboring
when individuals work in groups.

The Current Study
The practice of posting performance is common in
many workplace settings and typically takes the form
of a manager posting one or more characteristics of
an individual’s performance in view of his or her
coworkers. Posting performance highlights that the
organization is aware of and cares about performance,
and it can signal to employees that they should also
care (Nordstrom et al. 1991). Prior work has shown
that employees perform better when they receive
feedback from management that allows them to com-
pare their performance to that of others (Blanes i
Vidal and Nossol 2011). Posting performance can
facilitate a culture of comparison, where performance
comparisons are a salient and relevant feature of
the workplace. Despite the potential for posting per-
formance to increase employee effort, the motiva-
tional benefits of the comparisons will likely depend
on against whom one is being compared (Festinger
1954, Harkins 1987). That is, whereas posting per-
formance may promote social comparison processes
in certain work settings (e.g., when coworkers per-
form identical tasks), they may not necessarily elicit
such processes when comparisons are deemed less
relevant (e.g., when coworkers perform dissimilar
tasks).

In the current study, we sought to examine how
performance posting would impact the relationship
between groupwork and employee motivation when
teammates worked on an identical task. Namely,
although working on a task identical to one’s team-
mates’ can harm individual motivation via reducing
perceptions of instrumentality, working under con-
ditions that heighten comparison processes may not
only be sufficient to eliminate the tendency reduce
one’s inputs but also promote the desire to per-
form especially well. Consistent with the expectation
that settings that make comparisons especially salient
should lead individuals to be driven to compare
favorably, we predicted that posting performance
would moderate the relationship between groupwork
and individual task motivation. When performance
was posted in the office, we expected social labor-
ing to occur (i.e., increased performance of employees
working in groups compared with when they work

alone). However, when performance was not posted,
we expected that a reduction in perceived instrumen-
tality would promote social loafing (i.e., decreased
performance of employees working in groups com-
pared with working alone).

To test our predictions in the workplace, it was nec-
essary to examine the performance of employees when
working alone compared with when they worked in
a group, and we examine whether performance in
these contexts differed as a function performance post-
ing. Accordingly, we examined the performance of
employees working at a call center who performed the
task of recruiting people to participate in a focus group
either alone or with other employees recruiting people
for the same focus group.2 While working in a group,
an employee’s number of recruits was pooled with
that of other group members, thereby creating out-
come interdependence among group members. The
basic nature of an individual’s work did not differ
while working alone or as a member of a group
because employees sat in a cubicle making phone calls
in both situations, providing us with an opportunity
to compare employee performance across these two
types of work settings.3

The study was conducted over a 12-week period,
6 weeks during which the company posted employee
performance weekly and 6 weeks during which the
company did not post employee performance. Across
these 12 weeks, employees were assigned, on a daily
basis, to work alone or with others completing the
same task.

Method
Organizational Setting
FocusCo (a pseudonym) is an organization that con-
ducts focus groups for clients. Focus groups are
used to test market products or product marketing
campaigns. Clients would contract with FocusCo to
recruit individuals, run the focus groups, and report

2 By alone, we simply mean that the individual does not have
interdependence with others. The current work environment (i.e.,
employees working at cubicles side by side) helps controls for
many of the psychological effects (e.g., arousal) attributable to
working in the presence of others that can affect individual perfor-
mance (Aiello and Douthitt 2001, Cottrell et al. 1968).
3 To argue that a process loss or gain in a group has occurred,
one needs to compare performance against a baseline (Hill 1982,
Tindale and Larson 1992). In the current study, the presence of
an individual baseline enabled us to examine whether employees
exert different levels of effort when they work in groups compared
with when they work alone. Given that the basic nature of the task
did not change when individuals worked alone or as a member
of a group, positive/negative changes in individual performance
across these two work arrangements should largely be attributable
to motivation gains/losses instead of coordination gains/losses
(Larson and Schaumann 1993, Steiner 1972).

Lount and Wilk: Working Harder or Hardly Working?
Management Science 60(5), pp. 1098–1106, © 2014 INFORMS 1101

back with results. Our data come from call center
employees responsible for recruiting individuals for
these focus groups. Employees contacted prospective
focus group members from a list of phone numbers
provided by the organization.

For each client project, a profile was created for
requested focus group members. The employees
were responsible for calling and quizzing prospec-
tive group members on the characteristics of the pro-
file (e.g., age, sex, exposure to a particular product,
user of a particular product). Although projects gener-
ally required similar participant characteristics, there
was variation depending on the project, making some
focus groups more time consuming to recruit par-
ticipants for than others. As such, managers gener-
ally kept track of project assignments to minimize
the chance that certain employees were regularly
assigned to more or less difficult projects than others
across time.

Before making phone calls, employees began each
new project by carefully studying the profile require-
ments. While on the phone, based on the responses
of the prospective focus group member, the employee
would determine whether he or she fit the profile. If
so, the employee would provide this individual with
information about the place and time of the focus
group and encourage him or her to attend. If the
recruit was able and willing to participate, this would
be considered a successful recruit for the employee.
However, if the responses provided indicated that the
prospective focus group member was not appropriate
for the project, the employee would end the call and
then proceed to the next call.

Employees worked on only one project at a time.
Each project had a quota to be met, and depending on
how managers assigned projects that day, individuals
worked either alone or simultaneously with others to
meet the quota. Assignment to whether one worked
alone or in a group was largely random, with some
oversight from managers with regard to workflow
scheduling. In any given week, employees would be
assigned to multiple projects, working either alone or
with others on a project. The project was considered
complete when the number of recruits met the quota,
which could take anywhere from less than a day to
several days.

Even though projects were of generally short dura-
tion, working together with one or more others cre-
ated a sense of group membership. When a project
was assigned to more than one person, the man-
ager met with the employees who were to be work-
ing on the same project, explained the project and
their joint goal, and encouraged them to keep track
of recruits among themselves to make sure they met
the quota and did not recruit too many participants.
As we observed in our site visits, employees did this

by informing each other of a successful recruit or
by checking in with one another throughout the day
to determine how many recruits had been achieved.
Moreover, group members tended to talk about “our
project” rather than “my project.” Management rein-
forced the group nature of the work by making the
entire group accountable for reaching the quota and
requiring all group members to continue to work on
that project until the quota was met. If an employee’s
recruit was discovered to be unqualified, the entire
group, not just the employee who recruited the par-
ticipant, would have to return to work on the project
until the quota was met, even if that meant putting
their newly assigned project on hold.

It was also observed in our site visits that, given
the high number of rejections employees faced when
making phone calls to recruit focus group members,
it was viewed as a positive event to complete a quota.
In addition, the time transitioning from one project to
the next provided an opportunity for a break from the
phones. Given the taxing nature of constantly talking,
team members who helped reach the quota were gen-
erally viewed favorably by their teammates.

We examined performance of employees across
12 weeks. For six consecutive weeks, individual per-
formance was posted at the end of each week in
a prominent spot in the office. At the end of the
six weeks with posting, the performance list was
removed from the office and the manager informed
employees that performance would no longer be
posted. Thus, performance data during the “post-
ing period” began the first day employees were
exposed to the performance list, and performance
data during the “no-posting period” began the first
day employees worked in the absence of the perfor-
mance list.4 The call center manager provided few
details to the employees about the posting or why it
was removed. The information posted included the
employee’s name, the number of people recruited for
focus groups that week, and the number of hours he
or she worked that week. The FocusCo primary per-
formance metric, recruits per hours worked, was also
clearly visible. The list was ordered sequentially on
the basis of employee performance, with the top per-
former’s information listed first.

4 The decision to have the first six weeks be the posting time period
and have the six weeks following be the no-posting period was
made for two reasons. First, managers wanted time to set up the
posting system and used the week preceding January 1 (i.e., when
the call center is closed) to do so. Second, the call center did not
want to compare performance during the holiday season (i.e., six
weeks preceding January 1) with performance following the holi-
days to avoid “holiday effects” because management believed that
people may be less interested in participating in focus groups dur-
ing the holidays.

Lount and Wilk: Working Harder or Hardly Working?
1102 Management Science 60(5), pp. 1098–1106, © 2014 INFORMS

Sample
For our analyses, we use data provided by the orga-
nization for all call center employees and projects
within the 12-week period noted above. The call cen-
ter organization was small and varied from around
20 to 25 employees. We created a sample to include
only employees who were in both the posting and
no-posting period for a final count of 21 employ-
ees (90% female with average tenure of 2.3 years).
Although the number of respondents is small, it is
consistent with other experience sampling studies
(e.g., 27 participants in Ilies and Judge 2002, 18 par-
ticipants in Totterdell and Holman 2003). From these
employees we obtained 737 observations across the
12 weeks, where each observation included perfor-
mance data for a particular project on a given day for
a particular employee. We focus on the project level
as employees would sometimes work on more than
one project in a given workday.

Measures

Recruits per Hour. The dependent variable is
FocusCo’s primary measure of productivity, the num-
ber of recruits per hour worked for each employee.
This was calculated for each day for each project
on which an employee was working. Given that the
task is easily learned and performance is determined
largely by persistence, consistent with other research
examining task motivation among call center workers
(e.g., Grant 2008), the number of recruits per hour the
employee obtained was operationalized as a behav-
ioral indication of effort.

Posting. A dichotomous variable (0 = no posting,
1 = posting) was created to indicate whether FocusCo
was posting or not during the time period.

Groupwork. We calculated the number of other
employees who were assigned the same project on the
same shift on the same day. There were either two,
three, or four people working on the same project
on the same shift, with the majority being two per
project per shift. We created a dichotomous variable
where 0 indicates the person was working alone on
this particular project that day and on that shift and a
1 indicates that the person was working with at least
one other person on this particular project that day
and that shift. Dichotomizing groupwork (0 = alone,
1 = group) is consistent with prior work showing that
the distinction between working alone versus work-
ing with at least one other person is a critical one
in distinguishing between individual and group con-
texts (Latané et al. 1979, Williams 2010).

Controls. We also controlled for the number of
days a person had been working on the cur-
rent project or task because research has shown
that experience can influence performance (Quinones
et al. 1995).

Analysis
Data were structured so that each line of data was
a separate project/day/person combination (thus,
projects were nested within days, which were nested
within person). Because of the nested nature of the
data, we chose to use hierarchical linear model-
ing (HLM) to account for the dependence among
the observations (Raudenbush and Bryk 2002). HLM
accounts for bias associated with dependence among
observations that occurs when data are nested within
units (multilevel models) by modeling both fixed and
random effects.

Results
To determine whether using HLM was empirically
justified, we calculated the intraclass correlation coef-
ficients ICC(1), which is a measure of the variance
that is attributable to the three levels, project, per-
son, and day, for our dependent variable. We found
that although there was significant variance in recruit
by hours that is explained at both the project (95%,
p < 00001) and the person (5%, p < 0005) levels, we found no significant variance in our dependent vari- able that was explained at the day level (0%, p > 0010).
These findings indicate that using HLM is an appro-
priate analytical technique and that two-level models
(project nested within person) are suitable for these
data (Kreft and De Leeuw 2002).

Means, standard deviations, and intercorrelations
of study variables are provided in Table 1. Before test-
ing our interaction hypothesis, we first examined the
main effects of posting and groupwork. The results
of the regression analyses showed that neither post-
ing (b = 0002, p = 0063) nor groupwork (b = −0002,
p = 0062) significantly predicted task performance.
As anticipated, however, the interaction term signif-
icantly predicted individual task performance (b =

0042, t = 4020, p < 0001) (see Table 2, Model 4). Explor- ing this interaction, we find that when posting was present, individuals working in groups performed better than when working alone (simple slope = 0019, t = 2018, p = 0003). However, the opposite pattern

Table 1 Means, Standard Deviations, and Intercorrelations Among
Study Variables

Variable Mean SD 1 2 3

1. Recruits per hour 0059 0061
2. Posting (1= posting) 0042 0049 0001
3. Groupwork (1= group) 0026 0044 −0003 0013∗∗

4. Days on project 1036 0072 −0004 0012∗∗ 0001

Notes. Within-person correlations between variables were obtained using
HLM analyses to account for nonindependence. N = 737 (pairwise, within-
person correlations).

∗p < 0005; ∗∗p < 0001.

Lount and Wilk: Working Harder or Hardly Working?
Management Science 60(5), pp. 1098–1106, © 2014 INFORMS 1103

Table 2 HLM Analyses of Recruits per Hour

Measure Model 1 Model 2 Model 3 Model 4

Intercept 0064∗∗∗ 0063∗∗∗ 0064∗∗∗ 0068∗∗∗

Days on project −0004 −0004 −0004 −0004
Groupwork (1= group) −0002 −0003 −0023∗

Posting (1= posting) 0002 0003 −0009
Groupwork×Posting 0042∗∗

�2 22033∗∗∗ 22039∗∗∗ 22064∗∗∗ 27043∗∗∗

Sample size (project per /person) 737 737 737 737

∗p < 0005; ∗∗p < 0001; ∗∗∗p < 00001.

occurred when posting was not present; individu-
als working in groups performed worse than when
working alone (simple slope = −0023, t = −4033, p < 0001).5 Taken together, these results supported our pri- mary hypothesis (see Figure 1).

Supplemental Analyses
We conducted additional analyses to help rule out
potential alternative explanations for our findings.
One might argue that the evidence of social loafing
while working in groups when there was no posting
was an artifact of the ordering of our data collection.
That is, the social loafing finding may be a reaction to
the removal of posting; thus, there is a concern that this
finding may not occur prior to the posting period. To
test whether social loafing was occurring prior to the
posting period, we ran HLM analyses on the entire
year of data (including all employees) prior to posting
and tested whether working in a group had a negative
effect on individual task performance. This allowed
us to maximize the use of our data and increase the
power of our analyses. Suggestive of social loafing,
working in a group was negatively associated with
individual task performance (b = −0010, t = −6004, p < 00001; person: n = 123, event: n = 51152). As an addi- tional check, we also ran the same analyses with a reduced sample of only those who were employed sometime during the period prior to posting as well as in the posting period. We find a similar pattern of results. Working in a group had a negative effect on individual task performance (b = −0004, t = −1077, p = 0008; person: n= 15, event: n= 11559).

Next, we sought to examine whether seasonal dif-
ferences may have accounted for the motivation gains
documented in our posting period. To test this we

5 The statistical interaction between groupwork × posting was also
significant when groupwork was entered as a continuous predic-
tor: b = 0042, t = 3068, p < 00001. Simple slope analyses showed that when posting was present, individuals working with more group members tended to perform better than when working with fewer group members (simple slope = 0015, t = 2075, p < 0001). When post- ing was not present, individuals working with more people tended to perform worse than when working with fewer people (simple slope = −0018, t = −1049, p = 0014).

Figure 1 Plot of Posting ×Groupwork for Recruits per Hour

0.25

0.35

0.45

0.55

0.65

0.75

0.85

Alone In group

R
ec

ru
its

p
er

h
ou

No posting

Posting

examined the same six-week period corresponding
to the posting period but in the year before, a time
when no posting was present. We ran HLM analy-
ses on these data, including all employees, and tested
whether working in a group had a negative effect on
task performance. Social loafing effects on individ-
ual task performance were observed as working in
a group was negatively related to performance (b =

−0013, t = −2025, p = 0002; person: n = 33, event: n =

640). Additionally, we ran the same analyses using the
full 12 weeks of data corresponding to our posting
and nonposting period but in the year prior. Similar
results were observed; working in a group was neg-
atively related to performance (b = −0010, t = −3034,
p < 00001; person: n = 49, event: n = 11458). As a final check, we also ran the same analyses with a reduced sample of only those who were employed in the 12 weeks in the corresponding year prior and also during the posting period. We again find a similar pattern of results: working in a group had a negative effect on task performance (b = −0008, t = −1064, p =

0010; person: n = 8, event: n = 346). Taken together,
these additional analyses help rule out the possibility
that our effects were likely solely attributable to sea-
sonal effects or that our loafing results were triggered
by the removal of posting performance.

We also wanted to examine whether individuals’
performance in groups during the nonposting period
was affected by the reputation of their teammates.
Whereas prior work has found that motivation is sen-
sitive to real-time differences in teammates’ perfor-
mance (e.g., Messé et al. 2002, Schultz et al. 2010),
expectations about differences in relative abilities may
also affect motivation in groups. By the end of the
six weeks of posting performance, employees may
have made a general observation of their coworkers’
performance, which may have influenced subsequent
levels of motivation while working with others. As
such, we computed an average performance value
for each employee during the posting period and

Lount and Wilk: Working Harder or Hardly Working?
1104 Management Science 60(5), pp. 1098–1106, © 2014 INFORMS

examined whether the average performance of one’s
group members affected individual performance in
the time period following posting. Analyses showed
that mean coworkers’ prior performance did not
influence the performance of individuals working in
groups (b = −0005, t = 0038, p = 0070). We also tested
both the interaction between an individual’s mean
performance during the posting period with their
average coworkers’ performance during posting and
for a possible curvilinear relationship. Neither the
interaction analysis (b = −0003, t = −0005, p = 0096)
nor the curvilinear test (b = 0052, t = 1019, p = 0024)
was significant. Taken together, these analyses sug-
gest that individual performance was not affected by
differences in performance reputation between group
members.

Discussion
Whereas the literature on motivation in groups has
regularly speculated that loafing may occur in orga-
nizational workgroups, the findings of this study
highlight that the relationship between working in
a group and individual motivation depends on the
broader work environment. That is, whether or not
the organization posted employee performance—an
act that triggers increased social comparisons between
workers—was found to moderate the relationship
between groupwork and employee motivation. Specif-
ically, whereas the absence of posting performance
in an office was associated with a decrease in task
performance for employees working in groups com-
pared with when they work alone (i.e., social loafing),
the presence of posting performance was associated
with an increase in task performance for employ-
ees working in groups compared with when they
work alone (i.e., social laboring). These findings high-
light the important role that social comparison pro-
cesses can play in influencing individual motivation,
and they provide support for the expectation that
group settings can either positively or negatively affect
employee motivation (Hackman 2002).

In addition to documenting how heightening social
comparisons processes can aid motivation in groups,
through examining differences in motivation as a
function of whether an employee worked alone or
in a group, our results demonstrate that employee
effort can be sensitive to groupwork. When perfor-
mance was not posted in the office, groupwork was
found to promote loafing. This finding is consistent
with prior work showing students (Erev et al. 1993)
and trainees (Early 1989) loafing at simulated work
tasks. However, whereas these prior studies showed
evidence of loafing when individual performance was
anonymous, in the current work setting, individual
contributions to the group task were not anonymous

because employees could track and compare their
performance with their fellow group members. With
conditions of anonymity frequently shown to elicit
loafing, one may anticipate that even higher levels of
loafing may have occurred if the work setting was
one where individual performance was completely
anonymous.

Despite showing that groupwork can elicit social
loafing among employees, it is important to highlight
that the results also show the potential of groupwork
to positively influence employee motivation. Namely,
posting performance in the office not only helped to
eliminate loafing but also resulted in motivation gains
in workgroups. This finding supports recent specu-
lation that managers and practitioners may actively
manage the broader work context to help elicit social
laboring in groups (van Dick et al. 2009).

The current study also helps further our under-
standing into potential boundary conditions about
when posting performance in the workplace may
impact individual performance. Specifically, there was
not an overall change in individual performance for
employees who worked alone during posting and
after posting was removed. Although this may appear
to be inconsistent with prior work linking posting
performance with increased task performance (e.g.,
Azmat and Iriberri 2010, Blanes i Vidal and Nos-
sol 2011), our findings suggest that the benefits of
performance comparisons in some organizations may
depend, in part, on being compared with others per-
forming the exact same task. Although individuals may
be compared on tasks that may appear similar on
the surface (e.g., two employees installing parts into
a car), if the tasks are not identical (e.g., one per-
son is installing seats and the other is installing steer-
ing wheels), publicly posting how long it took each
person to perform his or her task may be perceived
as irrelevant information, and therefore not aid in
improving employee motivation. Thus, merely post-
ing performance data in the office may be insufficient
to augment effort if employees do not see the perfor-
mance comparisons as personally relevant.

Finally, our results also contribute to the grow-
ing research on within-person performance, which
suggests that the same individuals will exert differ-
ent levels of effort depending on the context. Whereas
characteristics of the task (Fisher and Noble 2004)
and the behavior of others (Stewart and Nandkeolyar
2007) have been found to relate to within-person per-
formance variation, we find that working with others
on a shared task and posting performance matters as
well.

Limitations and Future Directions
It is important to note that there are likely bound-
ary conditions that influence motivation in work-
groups. Given that employees working in groups in

Lount and Wilk: Working Harder or Hardly Working?
Management Science 60(5), pp. 1098–1106, © 2014 INFORMS 1105

our study experienced minimal task interdependence
and worked together for short periods of time, the
groups we studied may differ from workgroups com-
monly found in other organizations (Kozlowski and
Bell 2003). Accordingly, group-level features that can
shape individual behavior (see Cronin et al. 2011),
such as cohesion, should be less influential in the
types of temporary workgroups examined in the cur-
rent study. As such, one should be cautious about
generalizing the motivational effects of groupwork
seen in the current study to all workgroups. For
instance, although we found evidence of social loafing
when the office did not post performance, there are
likely instances where employees would not loaf—
and may even display motivation gains—while work-
ing with others in a setting where performance is not
posted. Namely, employees working alongside rivals
(Kilduff et al. 2010) or those facing intergroup compe-
tition (Erev et al. 1993, Pettit and Lount 2010, Wittchen
et al. 2011) may be especially motivated, regardless of
whether the office posts employee performance.

Although we have argued that heightening social
comparison processes in workgroups promotes a
variety of psychological states argued to facilitate
increased performance (i.e., increased evaluation con-
cerns, self-evaluation, competition, and the desire to
be seen as a valued group member), the degree to
which each of these psychological states was acti-
vated cannot be determined in the current study.
Future research in settings involving daily changes
in one’s work environment (i.e., working alone ver-
sus working in a group) could capitalize on daily
surveys or surveys administered following the com-
pletion of each project. Such data may provide valu-
able insight into the psychological states responsible
for performance changes when individuals worked
alone versus in a group. Insight into psychologi-
cal mechanisms may also be garnered in the lab-
oratory. For instance, experimentally manipulating
posting performance (present versus not present),
groupwork (alone versus group), and task similarity
(identical versus different) may help to better under-
stand why posting performance is particularly moti-
vating in groups. Self-report data could be collected
in an experiment to help examine the degree to which
an increased desire to be seen in a positive light
by other group members underlies changes in moti-
vation while posting is present. Thus, although the
current study showed that performance posting was
associated with improved motivation for employees
working in groups, future work is needed to more
closely examine the specific psychological processes
that underlie these effects.

Conclusion
Consistent with a contingency-based approach to
understanding behavior in organizations, we have

argued in the current paper that employee motivation
can be both positively and negatively affected by work-
ing in a group. These findings highlight that factors
present in the broader organizational context, such as
whether or not performance is posted, can in part
help to explain when working in a group will help or
hurt employee motivation.

Acknowledgments
The authors thank Hillary Anger Elfenbein, Norbert Kerr,
Nathan Pettit, and three anonymous reviewers for their
helpful feedback on earlier versions of this paper.

References
Aiello JR, Douthitt EA (2001) Social facilitation from Triplett to elec-

tronic performance monitoring. Group Dynam. 5:163–180.
Azmat GN, Iriberri N (2010) The importance of relative perfor-

mance feedback information: Evidence from a natural experi-
ment using high school students. J. Public Econom. 94:435–452.

Blanes i Vidal J, Nossol M (2011) Tournaments without prizes: Evi-
dence from personnel records. Management Sci. 57:1721–1736.

Buunk AP, Gibbons FX (2007) Social comparison: The end of a the-
ory and the emergence of a field. Organ. Behav. Human Decision
Processes 102:3–21.

Cottrell NB, Wack DL, Sekerak GL, Rittle RH (1968) Social facilita-
tion of dominant responses by presence of others. J. Personality
Soc. Psych. 9:245–250.

Cronin MA, Weingart LR, Todorova G (2011) Dynamics in groups:
Are we there yet? Acad. Management Ann. 5:571–612.

Early PC (1989) Social loafing and collectivism: A comparison of
the United States and the People’s Republic of China. Admin.
Sci. Quart. 34:565–581.

Erev I, Bornstein G, Galili R (1993) Constructive intergroup com-
petition as a solution to the free rider problem: A field experi-
ment. J. Experiment. Soc. Psych. 29:463–478.

Erez M, Somech A (1996) Is group productivity loss the rule or
the exception? Effects of culture and group-based motivation.
Acad. Management J. 39:1513–1537.

Festinger L (1954) A theory of social comparison processes. Human
Relations 7:117–140.

Fisher CD, Noble CS (2004) A within-person examination of cor-
relates of performance and emotions while working. Human
Performance 17:145–168.

George JM (1992) Extrinsic and intrinsic origins of perceived social
loafing in organizations. Acad. Management J. 35:191–202.

Grant AM (2008) Does intrinsic motivation fuel the prosocial fire?
Motivational synergy in predicting persistence, performance,
and productivity. J. Appl. Psych. 93:48–58.

Hackman JR (2002) Leading Teams: Setting the Stage for Great Perfor-
mances (Harvard Business School Press, Boston).

Harkins SG (1987) Social loafing and social facilitation. J. Experi-
ment. Soc. Psych. 23:1–18.

Harkins SG, Szymanski K (1989) Social loafing and group evalua-
tion. J. Personality Soc. Psych. 56:934–941.

Hertel G, Kerr NL, Messé LA (2000) Motivation gains in perfor-
mance groups: Paradigmatic and theoretical developments on
the Köhler effect. J. Personality Soc. Psych. 79:580–601.

Hertel G, Niemeyer G, Clauss A (2008) Social indispensability or
social comparison: The why and when of motivation gains of
inferior group members. J. Appl. Soc. Psych. 38:1329–1363.

Hill GW (1982) Group vs. individual performance: Are N +1 heads
better than one? Psych. Bull. 91:517–539.

Lount and Wilk: Working Harder or Hardly Working?
1106 Management Science 60(5), pp. 1098–1106, © 2014 INFORMS

Hogg MA (1996) Social identity, self-categorization, and the small
group. Witte E, Davis J, eds. Understanding Group Behavior,
Vol. 2 (Lawrence Erlbaum Associates, Hillsdale, NJ), 227–253.

Hüffmeier J, Hertel G (2012) When the whole is more than the sum
of its parts: Motivation gains in the wild. J. Experiment. Soc.
Psych. 47:455–459.

Ilies R, Judge TA (2002) Understanding the dynamic relationships
among personality, mood, and job satisfaction: A field expe-
rience sampling study. Organ. Behav. Human Decision Processes
89:1119–1139.

Karau SJ, Williams KD (1993) Social loafing: A meta-analytic review
and theoretical integration. J. Personality Soc. Psych. 65:681–706.

Kerr NL (1983) Motivation losses in small groups: A social dilemma
analysis. J. Personality Soc. Psych. 45:819–828.

Kerr NL, Hertel G (2011) The Köhler group motivation gain: How
to motivate the “weak links” in a group. Soc. Personality Com-
pass 5:43–55.

Kerr NL, Tindale RS (2004) Group performance and decision mak-
ing. Annual Rev. Psych. 55:623–655.

Kerr NL, Messé LA, Park ES, Sambolec EJ (2005) Identifiability,
performance feedback and the Köhler effect. Group Processes
Internat. Relations 8:375–390.

Kerr NL, Messé LA, Seok DH, Sambolec EJ, Lount RB Jr, Park ES
(2007) Psychological mechanisms underlying the Köhler moti-
vation gain effect. Personality Soc. Psych. Bull. 33:828–841.

Kilduff GJ, Elfenbein HA, Staw BM (2010) The psychology of
rivalry: A relationally dependent analysis of competition. Acad.
Management J. 53 (5):943–969.

Köhler O (1926) Kraftleistungen bei Einzel- und Gruppenabeit
[Physical performance in individual and group situations].
Industrielle Psychotechnik 3:274–282.

Kozlowski SWJ, Bell BS (2003) Work groups and teams in organiza-
tions. Borman WC, Illgen DR, Klimoski RJ, eds. Comprehensive
Handbook of Psychology: Industrial and Organizational Psychology,
Vol. 12 (John Wiley & Sons, New York), 333–375.

Kreft I, De Leeuw J (2002) Introducing Multilevel Modeling (Sage,
London).

Larson JR Jr (2010) In Search of Synergy in Small Group Performance
(Psychology Press, New York).

Larson JR Jr, Schaumann L (1993) Group goals, group coordination,
and group member motivation. Human Performance 6:49–69.

Latané B, Williams KD, Harkins SG (1979) Many hands make light
the work: The causes and consequences of social loafing. J. Per-
sonality Soc. Psych. 37:822–832.

Liden RC, Wayne SJ, Jaworski RA, Bennett N (2004) Social loafing:
A field investigation. J. Management 30:285–304.

Lount RB Jr, Phillips KW (2007) Working harder with the out-group:
The impact of social category diversity on motivation gains.
Organ. Behav. Human Decision Processes 103:214–224.

Lount RB Jr, Park ES, Kerr NL, Messé LA, Seok D (2008) Evaluation
concerns and the Köhler effect: The impact of physical presence
on motivation gains. Small Group Res. 39:795–812.

Messé LA, Hertel G, Kerr NL, Lount RB Jr, Park ES (2002) Knowl-
edge of partner’s ability as a moderator of group motivation
gains: Exploration of the Köhler discrepancy effect. J. Personal-
ity Soc. Psych. 82:935–946.

Nordstrom R, Lorenzi P, Hall RV (1991) A review of public post-
ing of performance feedback in work settings. J. Organ. Behav.
Management 11:101–123.

Pettit NC, Lount RB Jr (2010) Looking down and ramping up: The
impact of status differences on effort in intergroup contexts.
J. Experiment. Soc. Psych. 46:9–20.

Quinones MA, Ford JK, Teachout MS (1995) The relationship
between work experience and job performance: A conceptual
and meta-analytic review. Personality Psych. 48(4):887–910.

Raudenbush SW, Bryk AS (2002) Hierarchical Linear Models: Applica-
tions and Data Analysis Methods (Sage, Thousand Oaks, CA).

Ringelmann M (1913) Recherches sur les moteurs animés: Travail
de l’homme. [Research on animate sources of power: The work
of man]. Ann. l’Instiuit National Agronomique 12:1–40.

Rutte CG (2003) Social loafing in teams. West MA, Tjosvold D,
Smith KG, eds. International Handbook of Organizational Team-
work and Cooperative Working (John Wiley & Sons, Chichester,
UK), 361–378.

Sanders GS, Baron RS, Moore DL (1978) Distraction and social com-
parison as mediators of social facilitation effects. J. Experiment.
Soc. Psych. 14:291–303.

Schultz KL, Schoenherr T, Nembhard D (2010) An example and
proposal concerning the correlation of working processing
times in parallel tasks. Management Sci. 56:176–191.

Steiner ID (1972) Group Processes and Productivity (Academic Press,
New York).

Stewart GL, Nandkeolyar AK (2007) Exploring how constraints
created by other people influence intraindividual variation in
objective performance measures. J. Appl. Psych. 92:1149–1158.

Suls J, Wheeler L (2000) Handbook of Social Comparison Processes:
Theory and Research (Kluwer Academic Publishers, New York).

Suls J, Martin R, Wheeler L (2002) Social comparison: Why, with
whom, and with what effect? Current Directions Psych. Sci.
11:159–163.

Tindale RS, Larson JR Jr (1992) Assembly bonus effect or typical
group performance? A comment on Michaelsen, Watson, and
Black (1989). J. Appl. Psych. 77:102–105.

Totterdell P, Holman D (2003) Emotion regulation in customer ser-
vice roles: Testing a model of emotional labor. J. Occupational
Health Psych. 8:55–73.

van Dick R, Tissington PA, Hertel G (2009) Do many hands make
light the work? How to overcome social loafing and gain moti-
vation in work teams. Eur. Bus. Rev. 21:233–245.

Weber B, Hertel G (2007) Motivation gains of inferior group
members: A meta-analytical review. J. Personality Soc. Psych.
93:973–993.

Williams KD (2010) Dyads can be groups (and often are). Small
Group Res. 41:268–274.

Williams KD, Harkins SG, Latané B (1981) Identifiability as a deter-
rent to social loafing: Two cheering experiments. J. Personality
Soc. Psych. 40:303–311.

Wittchen M, van Dick R, Hertel G (2011) Motivated information
processing during intergroup competition: A model of inter-
group competition effects on individual effort. Organ. Psych.
Rev. 1:257–272.

Taking a Free Ride: How Team Learning Affects Social Loafing

Catherine Gabelica1, Sven De Maeyer2, and Michaéla C. Schippers3
1 Department of People, Organizations and Negotiation, IESEG School of Management

2 Department of Training and Education Sciences, University of Antwerp
3 Department of Technology and Operations Management, Rotterdam School of Management (RSM), Erasmus University Rotterdam

Although collaboration is increasingly required in today’s academic and work contexts, there are many
ways in which teamwork can be impaired by dysfunctional inefficiencies and process loss. An important
form of process loss is the tendency for individual members of a team to exert less effort than their fel-
low team members (i.e., social loafing). Since teams need to sustain the effort of team members as a col-
laborative resource, it is imperative to understand factors that shape social loafing in team tasks. This
study examines simultaneously the degree to which goal orientation and changes in team learning (i.e.,
shifts in collective knowledge) affect social loafing. The authors use a multiwave design to explain
changes in social loafing tendencies of 675 students working in teams. They conduct linear mixed
effects modeling to show that individual team members who belong to teams that score higher than
other teams on team learning throughout 9 weeks of teamwork experience a decrease in social loafing.
Although learning and performance orientations are significantly related to initial self- or peer-rated
social loafing, they cannot explain ensuing changes in social loafing. Results highlight the importance of
considering team-level dynamic properties when explaining fluctuations of motivation in teams.

Educational Impact and Implications Statement
Even though small group work has gradually progressed to being one of the dominant approaches
in the domain of learning and instruction and professional development, research shows that large
numbers of team members exhibit unco-operative behaviors such as social loafing (i.e., individuals’
tendency to expend less effort than their fellow team members). The results of a nine-week longitu-
dinal study with 675 students working in teams reveal that teams experiencing a steeper shift in
team’s collective knowledge (i.e., team learning) than other teams show a decrease in social loafing
tendencies over time. Additionally, they show that the learning and performance orientations of
individual members predict social loafing at the start of the collaboration. These findings help us
better understand how dynamic team-level properties can prevent individual members from engag-
ing in dysfunctional behaviors.

Keywords: teams, co-operative learning, collaboration, social loafing, team learning

In the past few decades, classroom instructors and professional
practitioners increasingly have used teams to improve learning and
achievement (Johnson & Johnson, 2015; Salas et al., 2007). Both
team and collaborative learning research are rooted in the principle
that to be effective, teams must collaborate to overcome barriers to
their interpersonal processes (Mathieu et al., 2019). That is, team
success depends on team members’ contributions to team out-
comes, such that low contributions to teamwork and motivational
losses are associated with low achievement (Kirschner, 2009).

Although many studies have investigated the factors that explain
how and why some teams outperform other teams (e.g., Kozlowski
& Ilgen, 2006), only a relatively smaller body of literature consid-
ers and explains social motivation losses, such as “social loafing”
(Kozlowski & Bell, 2013). Social loafing, which occurs when peo-
ple expend less effort than their fellow team members in team con-
texts (Karau & Williams, 1993), is common in classroom settings.
Most college graduates likely can recall instances in which they
worked collectively on projects that were graded on a team basis,
yet some team members “slacked off” and failed to put an equal
share of effort into achieving the team outcomes.

Social loafing theory (also known as collective effort theory)
(Karau & Williams, 1993) proposes explanations for why loafing
occurs, most of which cite structural reasons for withheld inputs or
team set-up factors, such as group size. While situational and dis-
positional variables can both drive social motivation (Toma &
Butera, 2015), relatively few social loafing models incorporate
team members’ individual differences, which may account for the
fact that the research evidence to date is limited and mixed (Karau

This article was published Online First October 25, 2021.
Catherine Gabelica https://orcid.org/0000-0003-0096-6940
Sven De Maeyer https://orcid.org/0000-0003-2888-1631
Michaéla C. Schippers https://orcid.org/0000-0002-0795-5454
Correspondence concerning this article should be addressed to Catherine

Gabelica, Department of People, Organizations and Negotiation, IESEG
School of Management, Rue de la Digue 3, 59000 Lille, France. Email:
c.gabelica@ieseg.fr

716

Journal of Educational Psychology

© 2021 American Psychological Association 2022, Vol. 114, No. 4, 716–733
ISSN: 0022-0663 https://doi.org/10.1037/edu0000713

T
hi
s
do
cu
m
en
ti
s
co
py
ri
gh
te
d
by

th
e
A
m
er
ic
an

Ps
yc
ho
lo
gi
ca
lA

ss
oc
ia
tio

n
or

on
e
of

its
al
lie
d
pu
bl
is
he
rs
.

T
hi
s
ar
tic
le
is
in
te
nd
ed

so
le
ly

fo
r
th
e
pe
rs
on
al
us
e
of

th
e
in
di
vi
du
al
us
er

an
d
is
no
tt
o
be

di
ss
em

in
at
ed

br
oa
dl
y.

https://orcid.org/0000-0003-0096-6940

https://orcid.org/0000-0003-2888-1631

https://orcid.org/0000-0002-0795-5454

mailto:c.gabelica@ieseg.fr

https://doi.org/10.1037/edu0000713

& Wilhau, 2020). Differences in goal orientations (learning vs.
performance) are expected to drive social motivation as they can
influence the extent to which individual members generally value
certain tasks (Karau & Wilhau, 2020). When team members hold
certain goal orientations (i.e., situated orientations for action in an
achievement task, Dweck, 1986), they are expected to display and
sustain low social loafing when they collaborate, specifically when
they attach value to task mastery, understanding, and growth (i.e.,
learning orientation). Individual members who focus on demon-
strating ability (i.e., performance orientation) might start their col-
laborative task with low social loafing because they seek to gain
favorable judgments from others. However, performance orienta-
tion might relate to increased social loafing over time, due to the
reception of team feedback and therefore, lower individual identi-
fiability (Karau & Wilhau, 2020).
Research in this area is even scarcer at the team level of analy-

sis. In a team, communication is directed toward a twofold pur-
pose: (a) to develop the interpersonal relations within the team,
and (b) to build a collective knowledge pool. However, most stud-
ies focus on the socioemotional side of teamwork (e.g., creation
and maintenance of cohesiveness and a sense of community;
Kreijns et al., 2003), while there is a larger gap in our understand-
ing of the influence of important sociocognitive mechanisms, such
as team learning, on social loafing. As teamwork enables individu-
als to merge their individual knowledge and skills to reach a com-
mon goal, it is characterized by the phenomenon of team learning.
Through team learning, defined as “a change in the team’s collec-
tive level of knowledge and skill produced by the shared experi-
ence of the team members” (Ellis et al., 2003, p. 822), individual
members’ knowledge is transformed and integrated into a collec-
tive knowledge pool (Van den Bossche et al., 2011). Thereby, by
progressively acquiring more complex knowledge and skills,
teams can overcome motivational barriers such as social loafing
(Raes et al., 2015; van Dick et al., 2009). In this sense, team learn-
ing and team motivation are closely related (Bell et al., 2012).
Importantly, social loafing develops over time during collabora-

tion. As such, time is a key factor. As team members socially
interact and initiate momentum on team tasks, they increase their
collective knowledge pool, which is expected to decrease social
loafing over time because of the whole team being involved in
maintaining a shared conception of problems they encounter.
However, the time factor is underresearched (Fransen et al., 2013;
Hofmann & Jones, 2005). Although many researchers have stud-
ied how groups develop into functional teams in organizational
settings (Kozlowski & Bell, 2013), data about why teams develop
differently and how different aspects of interaction are related are
limited (Fransen et al., 2013). Research studying teams in educa-
tional settings proposes that high-learning teams likely follow a
linear progressive development (Fransen et al., 2013; Johnson et
al., 2002) because of their specific features (e.g., restricted dura-
tion of teamwork, valence of deadlines and grades, low expertise
at the start of a collaboration). Accordingly, we expect student
teams to follow a linear progression, on average. However, build-
ing upon group socialization theory supporting that the relation-
ship between a team and its members also changes over time, we
propose that time spent in teams is not sufficient to explain
increases or decreases in social loafing. Teams also need to learn

(Bell et al., 2012). Consequently, we expect high-learning teams
to experience downward shifts in individual social loafing.

We first extend social loafing research by testing the impact of
the emergence of, and change in, team learning on social loafing
trajectories. We then connect these variables to person-related fac-
tors (i.e., goal orientations), moving back to the more proximal in-
dependent variables of our model. That is, we propose it is change
in learning during the collaborative process, rather than team
learning measured at a static point in time, and initial levels of
individual differences, that decrease social loafing over time. This
study makes several contributions to team motivation and team
learning literature by (1) investigating interdependent contexts of
naturally occurring teams; (2) using a multilevel, interactive
framework to analyze social loafing tendencies in teams that incor-
porates important but under-researched individual and team-level
factors; and (3) adopting a multiwave, multisource design to check
for patterns in how social loafing evolves over time and account
for differing perspectives on individual behavior in teams.

Literature Review and Hypotheses

Concept of Social Loafing

A team is a collection of individuals who work interdependently
to achieve a common goal and share responsibility for team out-
comes (Cohen & Bailey, 1997; Michaelsen et al., 2004). Individu-
als, in co-operative as opposed to competitive and individualistic
situations, tend to engage in more on-task behaviors and less off-
task, disruptive behaviors (Johnson & Johnson, 2015). However,
placing individuals in teams and having them work together does
not necessarily lead to co-operative efforts. Teamwork can also
generate dysfunctional inefficiencies such as “social loafing.”
According to the collective effort model (CEM), social loafing
refers to individuals’ behavioral tendencies to put forth less effort
than their teammates (Karau & Williams, 1993). It is believed to
occur in teams as a result of the presence of others as coactors who
combine their efforts on a collective task (Karau & Wilhau, 2020).

Social psychologists and organizational behavior researchers
conceptualize social loafing as an individual motivational con-
struct that operates in team contexts (Karau & Wilhau, 2020).
They categorize team motivation losses due to social loafing into
“interpersonal processes” in most team interaction classification
systems (Kozlowski & Bell, 2013; Mathieu et al., 2008). Interest-
ingly, in the literature on student engagement in educational psy-
chology, the notion of effort is included in definitions of both
cognitive and behavioral engagement (Fredricks et al., 2004). In
the definition of social loafing mentioned above, the notion of
effort is primarily behavioral, a matter of doing the work (or a fair
share of the work), and less of learning and mastering the task. We
could hence stipulate that social loafing is closer to the concept of
behavioral (dis)engagement (i.e., individuals’ active participation,
involvement and persistence in a learning activity) but applied to
team settings and with a strong notion of relative efforts (relative
to fellow team members) that is not specifically mentioned in the
engagement literature (Fredricks et al., 2004; Skinner et al., 2009).

Compared with the volume of research on individual motivation,
relatively little work has directly addressed social motivation and
social loafing in teams (Kozlowski & Bell, 2013). Prior research

TAKING A FREE RIDE 717

T
hi
s
do
cu
m
en
ti
s
co
py
ri
gh
te
d
by

th
e
A
m
er
ic
an

Ps
yc
ho
lo
gi
ca
lA

ss
oc
ia
tio

n
or

on
e
of

its
al
lie
d
pu
bl
is
he
rs
.

T
hi
s
ar
tic
le
is
in
te
nd
ed

so
le
ly

fo
r
th
e
pe
rs
on
al
us
e
of

th
e
in
di
vi
du
al
us
er

an
d
is
no
tt
o
be

di
ss
em

in
at
ed

br
oa
dl
y.

showed that social loafing leads to several negative team processes
and outcomes. It evokes distrust, lowered morale, and low team
cohesion and performance (Duffy & Shaw, 2000; Jassawalla et al.,
2008). Of moderate magnitude, it appears to be generalizable across
tasks and subject populations (Karau & Williams, 1997).
Because teams that display detrimental processes are likely to

sustain such negative interaction patterns over time (Webb & Cull-
ian, 1983), literature on teams has implicitly regarded social loafing
as a static rather than temporal variable (Aggarwal & O’Brien,
2008; Hofmann & Jones, 2005). However, we propose that social
loafing may be more dynamic than previously conceptualized. In
this article, we posit that social loafing is not a single, discrete act;
rather, individual team members may be inclined to contribute their
fair shares at different times or according to different tasks. Hence,
we view social loafing as a time-varying phenomenon that follows
different trajectories over time. Whereas the focus of prior work has
been on identifying the causes of social loafing at one point in time,
we oppose the idea of social loafing as a static phenomenon and
examine whether and how social loafing changes over time.

Operationalization of Social Loafing

To date, researchers have tended to capture the social loafing
tendencies of individual team members from a single-source per-
spective. Most previous studies on social loafing use self-ratings
of loafing; only a few studies have used peer ratings (e.g., Price et
al., 2006), and only one study, to our knowledge, has used both
peer and self-ratings (Stark et al., 2007).
Karau and Williams (1993) and Jassawalla et al. (2008) suggest

social loafing occurs without self-awareness and that loafers gen-
erally find it socially undesirable to admit they loafed on complet-
ing collective tasks; the authors’ argument draws on sources other
than team members themselves, that is, their teammates. Arguably,
according to human behavior concepts and theories (e.g., attribu-
tion theory, decision making, performance appraisal; Ilgen et al.,
1994), attitudes and behaviors depend largely on perceptions. We
can argue that social loafing starts to exert influence in a team
when other members perceive that some member who relies too
much on his or her teammates to accomplish his or her portion of
the work takes advantage of them while “unfairly” enjoying and/
or sharing the team outcome equally well with less work (Jassa-
walla et al., 2008; Schippers, 2014). This proposal is often used as
a main argument for measuring “perceived social loafing of
others” (i.e., an individual’s assessment of the others’ relative con-
tribution to the team; Piezon & Ferree, 2008; Zhu et al., 2019).
At the same time, some researchers (e.g., Cheng & Warren,

1999) question the reliability of peer evaluations, suggesting peer
ratings may suffer from a halo effect (Loughry et al., 2007), leni-
ency effect, or lack of skill in differentiating teammates. For exam-
ple, Davison et al. (2014) find that only high performers are able
to deliver evaluations of teammates that differentiate between
those who perform well and those who perform poorly. Peer rat-
ings also may be biased by friendships or personal dislikes (Bar-
clay & Harland, 1995). These limitations could lead to the use of
self-ratings of social loafing. For example, Price and colleagues
(2006) found in their study using both peer and self-ratings that
individuals were more inclined to highlight their own loafing than
the loafing of others. Another argument in favor of self-assessment
purports that questioning one’s own relative contribution to the

team can lead to disclosure of one’s beliefs about him or herself as
a team member (McCardle & Hadwin, 2015) and self-awareness
of one’s antisocial behavior (Simms & Nichols, 2014). Finally,
Conway and Lance (2010) claim that there are two major miscon-
ceptions about self versus other-ratings. The first misconception is
that other-report is superior to self-report measures. The second is
that relationships between self-reported constructs are always
upwardly biased. They contend that “rather than providing a more
accurate estimate of true relationships among constructs, relation-
ships estimated using different methods tend to be more attenuated
and less accurate as compared to same-method correlations” (Con-
way & Lance, 2010, p. 327). In sum, thus far, prior outcomes are
mixed with regard to which source best assesses social loafing.

Social Loafing and Contextual Factors

Researchers offer multiple explanations for why social loafing
takes place, with early work indicating that characteristics of the sit-
uation and individual members’ situational interpretations often
drive social loafing (Williams et al., 1981). Specifically, the social
loafing literature proposes that people engage in social loafing
mostly because of a decreased perceived accountability and
increased dispensability of effort experienced by team members
(Harkins, 1987; Price et al., 2006). Similarly, co-operative learning
research also demonstrates that positive goal interdependence and
individual responsibility and accountability are likely to reduce
social loafing (Buchs et al., 2015; Johnson & Johnson, 2009).

The robust presence of social loafing in teams has led research-
ers to identify not only its antecedents but also variables that might
moderate the tendency to engage in social loafing (Kozlowski &
Bell, 2013). Most authors note the influence of set-ups or work
designs to minimize social loafing (Erez & Somech, 1996; Koz-
lowski & Bell, 2013; Stark et al., 2007). For example, social loaf-
ing can be reduced by improving task management and reward
structures (George, 1992; Pearsall et al., 2010). Other strategies
that reduce individual tendencies to loaf include increasing team
familiarity and identifiability of individual members and decreas-
ing ‘team size’ (Erez & Somech, 1996; Lam, 2015). However, we
propose that work-design factors are not sufficient to explain
social loafing tendencies, because they also reside in individual
team members. Accordingly, individual-level factors may explain
individual differences in social loafing.

Social Loafing and Individual Differences

Individual differences have received less attention in social loaf-
ing research (Stark et al., 2007). As early as 1995; Comer began to
integrate team members’ attitudes and individual differences into
social loafing frameworks (Comer, 1995), but empirical evidence
and understanding of these factors remain relatively limited and
are mostly derived from laboratory settings (Karau & Wilhau,
2020). There is increasing evidence that individual differences can
explain the extent to which team members loaf (Bolin & Neuman,
2006; Morgeson et al., 2005); for example, those who believe they
are better than others (Huguet et al., 1999) are more likely to loaf,
whereas those with high levels of winning orientations and prefer-
ences for group work (Stark et al., 2007) and conscientious, agree-
able team members (Schippers, 2014; Tan & Tan, 2008) are less
likely to loaf.

718 GABELICA, DE MAEYER, AND SCHIPPERS

T
hi
s
do
cu
m
en
ti
s
co
py
ri
gh
te
d
by

th
e
A
m
er
ic
an

Ps
yc
ho
lo
gi
ca
lA

ss
oc
ia
tio

n
or

on
e
of

its
al
lie
d
pu
bl
is
he
rs
.

T
hi
s
ar
tic
le
is
in
te
nd
ed

so
le
ly

fo
r
th
e
pe
rs
on
al
us
e
of

th
e
in
di
vi
du
al
us
er

an
d
is
no
tt
o
be

di
ss
em

in
at
ed

br
oa
dl
y.

This angle of individual differences points to a need for addi-
tional hypotheses that include person-based factors that can pre-
vent or lower the occurrence and magnitude of social loafing
throughout team collaborations.
A person-related motivational factor that appears to have

received little research attention in the social loafing literature is
goal orientations, including learning orientation and performance
orientation (cf. Gagné & Zuckerman, 1999).

Learning Orientation and Performance Orientation

Work on goal orientations in team contexts is rooted in research
arguing that how people change a given situation into an effective
situation depends on their social motivation (Forgas et al., 2005;
Schippers, & Scheepers, 2020). Social motivation theories are
concerned with goal-directed behaviors that are aimed at, or cen-
tral to, social interaction (Carver & Scheier, 1998; De Dreu et al.,
2008). An assumption of social motivation is that one’s tendency
to collaborate and interact with others is largely driven by individ-
ual differences, in particular achievement goals (De Dreu et al.,
2008). In accordance with this premise, we can hypothesize that
goal orientations have important consequences for interpersonal
interactions and for behavior change, more specifically change in
social loafing. Since the purpose of the present article is to investi-
gate antecedents of social loafing viewed as a dynamic behavior
that emerges in social contexts, we expect members to bring their
behavior in line with their initial goals.
Much research on motivation in individual settings has examined

the basic concept of “goal” that accounts for how people intend to
behave (Locke et al., 1981). Goal-related motivation theories and
research have given rise to Achievement Goal Theory (AGT) that
focuses on the psychological features of goals and individuals’
intention beyond a goal (i.e., goal orientation, Pintrich, 2000). Sev-
eral goal structure models have emerged to explain the reasons for
achievement behaviors (Kaplan & Maehr, 2007). In early work,
goal structure is conceptualized as two-dimensional (Elliot, 2005).
Specifically, these models stipulate that people’s goals focus on
increasing competencies via learning (i.e., learning or mastery goals)
versus obtaining affirmative judgments about their competencies
(i.e., performance goals; Dweck, 1986, 1999). Despite the varying
terminologies, mastery versus performance goal orientations are closely
related to learning versus performance orientations.
Later research on achievement goal orientations proposes to con-

sider whether achievement goal orientations lead individuals to
approach or avoid a task (e.g., Elliot & Church, 1997). In the trichoto-
mous achievement goal framework, the performance goal orientation
construct is divided into a performance-approach goal orientation and
a performance-avoidance goal orientation. Individuals who are per-
formance-avoidance oriented are concerned with avoiding demon-
strating low ability, mostly in comparative terms (Urdan & Kaplan,
2020). Following this logic, Elliot and McGregor (2001) later pro-
pose a 2 3 2 model that adds a fourth goal orientation, a mastery-
avoidance orientation, whereby a learner’s goal is to avoid misun-
derstandings and mistakes. It implies a fear of failure that is rooted
in an intrapersonal rather than an interpersonal perspective.
Mastery or learning orientations generally relate to interest, per-

sistence, positive emotions, use of deep learning approaches, and,
under certain conditions, to achievement. In contrast, perform-
ance-avoidance goals relate to negative emotions, disengagement

in the face of obstacles, and low achievement. Performance-
approach goals are associated with higher achievement, and under
different circumstances, with more and less adaptive and maladap-
tive emotions and learning strategies (Payne et al., 2007; Rolland,
2012; Ramos et al., 2021; Urdan & Kaplan, 2020). Mastery-avoid-
ance goals have received less scrutiny than the other goals.
Although patterns of relations between mastery-avoidance goals
and outcomes are inconsistent, they are generally associated with
maladaptive outcomes (Madjar et al., 2011).

There is a growing number of studies incorporating AGT in
team and collaborative learning research (Poortvliet et al., 2009).
However, to understand how those operate in the context of team-
work, further empirical studies are needed (Lim & Lim, 2020). In
collaborative learning research, studies consistently show that
mastery orientation has positive effects on individual-level cogni-
tive and affective outcomes such as cognitive processing (e.g., Pat-
rick et al., 2008) and a handful of studies similarly demonstrate
positive effects on team behaviors such as other-regulation (Grei-
sel et al., 2018; Lee et al., 2010; Lim & Lim, 2020; Volet & Mans-
field, 2006) or feedback-seeking (Payne et al., 2007). By contrast,
inconsistent relationships have been found between performance
orientation and other-regulation. For example, some studies show
that performance orientation has negative (Lee et al., 2010), posi-
tive (Greisel et al., 2018), and no significant relationships (Lim &
Lim, 2020) with other-regulation, and feedback-seeking (Cellar et
al., 2010; Payne et al., 2007). Further, in situations of team prob-
lem solving, Poortvliet and colleagues (Poortvliet et al., 2007;
Poortvliet et al., 2012) show that performance orientation is related
to information retention and even thwarting behavior. Most studies
find no significant effects of the performance-avoidance goal ori-
entation on team constructs. Payne et al. (2007) find a negative
correlation with feedback-seeking in nonteam settings, whereas
Cellar et al. (2010) conclude that there is no significant relation
between the two constructs.

In the present study, we decided to focus exclusively on the
approach variants of the achievement goals because these are pre-
dictive of process variables in the collaborative learning literature,
while the avoidance goals have been less studied and seem to nei-
ther hinder nor promote collaboration (Lim & Lim, 2020). For the
sake of parsimony, we include learning and performance orienta-
tions in our multivariate approach, as the goal of our study is to
investigate whether the significant relationships found in this liter-
ature reproduce at the team level.

As stated, studies to date suggest that team members scoring
high on learning orientation tend to engage more in adaptive col-
laborative learning than members scoring low on this orientation.
However, the results on the effects of performance orientations in
collaborative contexts are mixed. Further, what is not yet clear in
this strand of research is how different goal orientations induce
differences in social loafing trajectories (Skinner et al., 2009).

Because they attach great value to hard work for its own sake,
achievement or personal growth, team members who are learning
oriented are also more likely to place value in specific collabora-
tive tasks, and hence, are less likely to loaf. This task value propo-
sition is consistent with the Collective Effort model that suggests
that individuals who view tasks as meaningful, important, or
intrinsically interesting are less likely to engage in social loafing
(Karau & Wilhau, 2020). Furthermore, individuals scoring high on
learning orientation seek more help from, and exchange more

TAKING A FREE RIDE 719

T
hi
s
do
cu
m
en
ti
s
co
py
ri
gh
te
d
by

th
e
A
m
er
ic
an

Ps
yc
ho
lo
gi
ca
lA

ss
oc
ia
tio

n
or

on
e
of

its
al
lie
d
pu
bl
is
he
rs
.

T
hi
s
ar
tic
le
is
in
te
nd
ed

so
le
ly

fo
r
th
e
pe
rs
on
al
us
e
of

th
e
in
di
vi
du
al
us
er

an
d
is
no
tt
o
be

di
ss
em

in
at
ed

br
oa
dl
y.

information with, their peers (Newman & Schwager, 1995).
Engaging in such help-seeking and information-sharing behaviors
implies that this team member lacks a particular skill that others
might have (Veenman et al., 2005). Thus, a learning orientation
likely encourages collaboration and discourages social loafing
(Poortvliet et al., 2009), such that it should associate positively
with a willingness to participate in a team activity, regardless of
effort identifiability. We propose that those with a high learning
orientation are less likely to loaf at the start and over the course of
collaborations.

H1: Team members with a higher learning orientation are less suscep-
tible to display social loafing throughout the collaboration.

Similarly, when the pursuit of performance goals is driven by
need for achievement, these goals might stimulate high relative
contribution in a team (Lim & Lim, 2020). Specifically, since
team members who endorse performance goals tend to strive to
demonstrate their competence to others, performance orientation
could be an effective motive in the short term, and hence, at the
start of a team project. However, this effect might change in the
long term (Brophy, 2005). In teams that have co-operative reward
structures (e.g., team scores), members with high levels of per-
formance orientation may not be able to use interpersonal stand-
ards, such as performance relative to their peers, to assess competence
in achievement situations (Elliot & McGregor, 2001; Pintrich,
2000). Also, in teams, their individual efforts may not be identifia-
ble, and feedback is generally provided at the team level. Since
reward and recognition are important for such people (Reeve,
2015), they might consequently develop a lowered sense of
accountability and thus greater tendencies to loaf over time. Addi-
tionally, if individuals compete with their teammates to establish
their abilities, they are less likely to collaborate, which may gener-
ate less harmonious social relations or augment disruptive behav-
ior (Butler, 1995; Midgley et al., 2001). Accordingly, it is likely
that a performance orientation does not encourage teamwork in
the long term but does elicit the growth of antisocial tendencies
such as social loafing (Poortvliet et al., 2009).

H2: Team members with a higher performance orientation are (a) less
susceptible to display social loafing at the start of a team collaboration,
(b) more susceptible to display social loafing over time.

Social Loafing and Team-Level Factors

Traditionally, psychological theories have mostly focused on indi-
vidual variables (e.g., personality traits, attitudes, values) in their
attempts to explain individual behavior, the underlying assumption
being that the causes of an individual’s behavior are inside the indi-
vidual. Social interdependence theory, on the other hand, postulates
that individual behavior can be explained by the interactions among
individuals that are inherently dynamic (Johnson & Johnson, 2015).
As such, this theory recognizes the critical role played by team fac-
tors in the completion of a team task for individual members. There
is a growing body of literature that recognizes the importance of
team-level factors during collaboration (Johnson & Johnson, 2009).
Despite this growing interest, in contrast to research on individual-
level antecedents of social loafing, there is much less information

about team-level factors that enable team members to resist social
loafing or decrease its intensity over time.

The collaborative learning literature supports that team commu-
nication can serve two complementary purposes,(a) building a pos-
itive and cohesive socioemotional climate (Bakhtiar et al., 2017;
Isohätälä et al., 2020) and (b) facilitating team cognitive processes
(Järvelä et al., 2016; Rogat & Linnenbrink García, 2011).

A few studies on social loafing focus on the socioemotional
aspects of teams, and they typically rely on laboratory work to
reveal, for example, that group cohesiveness reduces or eliminates
social loafing (e.g., Duffy & Shaw, 2000; Lam, 2015). This result
was replicated in field studies that affirm that social loafing in
teams relates to low team cohesiveness (Høigaard et al., 2006;
Liden et al., 2004). This finding usually is explained by high levels
of member identification with teams and concerns about team
welfare.

However, much less is known about the sociocognitive factors
that could substantially lower or even eliminate social loafing
(Erez & Somech, 1996; Lam, 2015). Whereas empirical work on
social loafing implies that team members simply add their individ-
ual inputs to produce team outcomes, teams are social systems that
evolve and create multiple solutions that stem from ongoing
knowledge sharing (Jassawalla et al., 2008). Despite this observa-
tion, there is a paucity of evidence on the extent to which team-
level differences in team learning during collaborative learning,
can explain differences in individual loafing behavior. The present
study aims to address this gap.

Social Loafing and

Team Learning

In response to the lack of research on team sociocognitive fac-
tors, we propose that individual team members reduce their loafing
tendencies when their teams increase their collective learning.
According to Wilson et al. (2007), team-level learning represents a
change in a team’s collective level of knowledge and skills. We
conceptualize team learning as an output of shared experience of
the team members, and more specifically, as a newly shared under-
standing of how the team should function and develop new knowl-
edge and skills about the team tasks (Ellis et al., 2003; Van den
Bossche et al., 2011).

We hence view team learning from a social constructivist per-
spective, according to which people create knowledge during
social interactions (Boud et al., 2001; Oliveira & Sadler, 2008).
Team learning is frequently compared with collaborative and
co-operative learning, though the concepts are not mutually exclu-
sive. In this article, team learning is not conceived as a structured
peer learning method but shares some conceptual similarities with
the two other constructs. As variations of “peer learning”, they all
incorporate features such as shared experiences and responsibil-
ities, positive interdependence, individual accountability, and pro-
motive interaction (Johnson & Johnson, 1999; Slavin, 2011).
However, team learning, typically studied in work settings, also
encompasses (a) the production of team-level outcomes, such as
collective knowledge (i.e., knowledge held by the team as its own
united entity) and team performance, (b) the main goal of success-
fully completing a given task, and (c) mutual accountability for
these outcomes (Dochy et al., 2014). While research on co-operative
and collaborative learning has recently shifted its attention to the
group as the unit of analysis, it has traditionally focused on outputs at

720 GABELICA, DE MAEYER, AND SCHIPPERS

T
hi
s
do
cu
m
en
ti
s
co
py
ri
gh
te
d
by

th
e
A
m
er
ic
an

Ps
yc
ho
lo
gi
ca
lA

ss
oc
ia
tio

n
or

on
e
of

its
al
lie
d
pu
bl
is
he
rs
.

T
hi
s
ar
tic
le
is
in
te
nd
ed

so
le
ly

fo
r
th
e
pe
rs
on
al
us
e
of

th
e
in
di
vi
du
al
us
er

an
d
is
no
tt
o
be

di
ss
em

in
at
ed

br
oa
dl
y.

the individual level (e.g., what do students learn?) (Fransen et al.,
2013; Vangrieken et al., 2016; Weinberger et al., 2007). As such,
both research lines complement each other when building an
understanding of the extent to which team members converge
toward increased collective knowledge.

Dynamics of Social Loafing and Team Learning

Teams are not static entities, but instead change in dynamic ways
over time. To clarify the determinants of social loafing, it is there-
fore necessary to consider temporal aspects of teams, which include
team development (i.e., changes in the team as a whole) and team
socialization (i.e., changes in the relationship between the team and
its members; Arrow et al., 2000; Levine & Moreland, 1994).
Group socialization theory stipulates that both the team and its

members are “potential influence agents” (Levine & Moreland,
1994, p. 306). This perspective purports that people change as a
function of the team that they join. Traditionally, small group
research focuses on the team perspective and overlooks how rela-
tions between a team and its members develop over time (Mathieu
et al., 2019). This theory recognizes that individual members’ con-
tribution levels change over time and that it can, in turn, change
the relationship between the team and its members. As such, the
effects of the team on an individual’s behavior can depend on
team socialization, reflecting changes over time. If changes in con-
tribution occur, this can result in divergence and the potential
exclusion of the individual from the team. However, the team can
also resocialize the individual (Levine et al., 2001). In line with
this theory, we posit that when contribution levels become increas-
ingly unequal, it creates a tension that can be repaired through
knowledge creation. The team can hence change the individual so
he or she can exert more effort toward the team goals. We hence
propose that the development of new knowledge and skills has the
potential to raise the satisfaction of the loafers’ needs.
Furthermore, there is a consensus across disciplines that teams as

a whole develop or change over time (Fransen et al., 2013;
Hommes et al., 2014; Kozlowski & Bell, 2013). Since team learn-
ing requires interactions between individuals, inherently, it is emer-
gent and dynamic and involves developmental progression
(Kozlowski & Bell, 2013). It supposes a shift in knowledge state—
a knowledge trajectory over time. As teams develop and evolve
from groups of individual members to become collectivities with
well-mapped repertoires of adaptive skills, the learning that
emerges is not only inextricably connected to the fundamentals of
social motivation but also changes over time (Goodman & Dabbish,
2011; Wiese & Burke, 2019).
Recently, more promising research efforts adopt a regulatory

approach to team learning. In this view, team learning takes a reg-
ulatory role. Team members respond to goal progress, adjust their
efforts and strategies and create newly shared understandings. In
turn, this role should benefit motivational processes (Bell et al.,
2012; Chen et al., 2009). However, the regulatory perspective on
team learning requires further consideration, especially with
regard to its relationship to motivation in team contexts. Using this
theoretical model, we posit that dynamics inherent to team learn-
ing shape motivational states that emerge over time. By increasing
team learning, teams can increase their effort and attention to team
goal accomplishment and strategies and thereby reduce process
losses in the form of social loafing. A steeper change in collective

knowledge is expected to lower social loafing because it would ne-
cessitate that the whole team devotes attention to integrating indi-
vidually held information into the team’s collective knowledge
state and maintaining a shared conception of a problem.

To join emerging efforts to explore the dynamic relationships
between team learning and social loafing, both conceptually and
empirically, we formulate and test the following hypothesis:

H3: An increase in team learning leads to a decrease in social loafing,
even when controlling for individual goal orientations.

In summary, though prior work on social loafing offers important
theoretical foundations pertaining to the reasons for social loafing
and the limiting conditions of its effects, several significant theoreti-
cal and practical gaps remain. First, it has traditionally conceptualized
social loafing as a stable rather than a dynamic construct. Second, it
has mostly focused on structural reasons and set-up factors to explain
social loafing. Relatively fewer studies have investigated other rea-
sons related to individual differences and team-level factors. Third,
even though goal orientation theory and social motivation theory pos-
tulate interrelations between goal orientations and motivation, the
effects of goals orientations on social loafing development have not
been closely examined. Fourth, research on team-level factors, and
more specifically on team sociocognitive factors, is even scarcer in
the social loafing literature. Furthermore, building upon social inter-
dependence theory and a regulatory approach of team learning (for
theoretical considerations) as well as on group socialization theory
and team development models (for temporal considerations), team
learning appears as a promising yet underexplored emergent socio-
cognitive mechanism that can initiate a downward shift in individual
social loafing. So far, however, there has been little discussion about
the power of team learning growth on change in social loafing. Fifth,
studies have tended to collect data from single sources, leaving room
for same-source biases. To address these research gaps on social loaf-
ing, our goal is to identify individual and team factors, namely goal
orientations and team learning, that together make up for this process
loss; to do so, we use a multilevel framework and research design
(Kozlowski & Klein, 2000), a repeated-measure design, and multiple
assessors of social loafing tendencies.

Method

Data and Sample

Participants in our study (n = 675) were first-year business stu-
dents attending a Research Methods course in their first trimester
at a Dutch university. They were required to form three- or four-
person teams (n = 195 teams, 105 three-person teams, 90 four-per-
son teams) to complete tasks. The course used a self-selection
approach in which students selected their own teams for the entire
trimester. At the start of the course, students completed an online
survey measuring the independent variables, that is, learning ori-
entation and performance orientation (T0). Throughout the trimes-
ter, they were required to complete three team assignments, which
counted toward their final grade. Just before they turned in each
assignment, students were contacted by e-mail and were asked to
fill out the online surveys individually to measure team learning
(T1, T2, T3) and social loafing (T1, T2, T3). They were briefed

TAKING A FREE RIDE 721

T
hi
s
do
cu
m
en
ti
s
co
py
ri
gh
te
d
by

th
e
A
m
er
ic
an

Ps
yc
ho
lo
gi
ca
lA

ss
oc
ia
tio

n
or

on
e
of

its
al
lie
d
pu
bl
is
he
rs
.

T
hi
s
ar
tic
le
is
in
te
nd
ed

so
le
ly

fo
r
th
e
pe
rs
on
al
us
e
of

th
e
in
di
vi
du
al
us
er

an
d
is
no
tt
o
be

di
ss
em

in
at
ed

br
oa
dl
y.

that the questionnaire was referring to the team assignments they
had just completed collaboratively. The assignments varied in dif-
ficulty. The first task consisted of choosing a research topic from a
list, reading the accompanying case, conducting a literature search
using different databases (e.g., Google Scholar, JSTOR), making
an inventory of relevant articles, and comparing their results. Most
students already were acquainted with literature search in data-
bases, so this task was not difficult. The second task, of greater dif-
ficulty, involved reading and analyzing a scientific article, building
a complex conceptual model of the variables measured in the arti-
cle, and formulating research hypotheses. The task was additive in
nature: it lacked structure, there were no clear strategies, and more
than one correct solution was possible. Finally, the third task, of
moderately high difficulty, required teams to read a case, compose
a research question, and answer scientific reasoning questions.
According to their research question, students had to select and
justify the most appropriate research method (e.g., experiment,
case study, survey study); define whether the aim of the study
would be to explore, explain, or describe (e.g., theory building vs.
theory testing); and justify which research strategy would be least
suitable for answering the research question. Teams also had to
formulate recommendations according to the case. In total, they
worked together for about nine weeks to complete these three
team assignments. All members received the same grade on their
assignments irrespective of individual effort, and performance
standards were clearly communicated.
The response rate for the first survey was 94.43% (729 stu-

dents); for the second survey, it was 91.58% (707 students); and
for the third survey, it was 88.60% (684 students). We omitted
from the analysis teams for which the data of two or three mem-
bers were missing. The final sample consisted of 675 students dis-
tributed in 195 teams. Of these respondents, 70.80% were men,
28.90% were women, and for .30%, information about gender was
missing. The mean age of the participants was 18.76 years (stand-
ard deviation [SD] = 1.48); 68.80% were Dutch, 24.60% indicated
non-Dutch nationality, and 6.60% did not indicate any nationality.

Procedure

Data were collected with an online survey, sent by two research
assistants. None of the authors nor the assistants were involved in
teaching the Research Methods class. Moreover, the teachers were
not aware of the purposes of the research. Because students filled out
the questionnaires before they received their grades for their tasks,
feedback on how well they did on the task did not affect their percep-
tions of the measured variables. Participants were briefed about the
purpose of the research and given the opportunity to opt out, but none
of the students did so, and the final sample remained unchanged.

Measures

Team Learning

To assess team learning, we used a 5-item scale from the input-
mediator-output-input (IMOI) model to grasp team dynamics, as
described by Ilgen et al. (2005) and adapted by Schippers et al.
(2013). Items included, for instance, “We learned from our mistakes
in our tasks,” “We learned how to improve at our tasks,” and “We
developed new knowledge or skills about our tasks” (1 = “strongly

disagree;” 5 = “strongly agree”). Team members rated these items
individually. Their responses were aggregated to the team level to
obtain team learning scores for each team at the three time points
when team learning was measured. The Cronbach’s alpha coeffi-
cients were .79 for time 1, .78 for time 2, and .80 for time 3.

Social Loafing Tendencies

We assessed social loafing tendencies with a 4-item measure
derived from a questionnaire developed by George (1992) and
adapted by Schippers (2014). We operationalized social loafing in
two ways: self-reported and peer-reported. Because both sources of
assessment have advantages and disadvantages, combining them
offers a valid alternative to using one source over the other. To our
knowledge, only Stark et al. (2007) use both self-ratings and peer
ratings to study social loafing, concluding that participants are more
willing to admit their own loafing behaviors than recognize the loaf-
ing of their teammates. However, they emphasize it is legitimate to
expect that social loafing appraisals from different perspectives
(e.g., self vs. teammates) will differ. Therefore, to account for dif-
fering perspectives on individual behavior in teams, we use the two
separate source measures of social loafing behavior.

We summed self-reported responses across items that asked team
members about the extent to which they “defer responsibilities they
should assume to other team members,” “put forth less effort than
other members of their team,” “prefer to let the other team members
do the work if possible,” and “put forth less effort on the assign-
ment when other team members are around to do the work” (1 =
“totally disagree;” 5 = “totally agree”). For this measure, the Cron-
bach’s alphas were of .85 for time 1, .88 for time 2, and .88 for time
3. With regard to peer-rated social loafing, team members wrote
down the names of their teammates and rated them on each of the
four items on a 5-point Likert scale using the same labels as the
self-report questionnaire. To justify aggregating the peer ratings, we
assessed interrater agreement within teams according to rwg values
(level of within-group agreement of the peer evaluation score for
each referent). Because these estimates produced very good indica-
tors of peer evaluation reliability (average rwg = .88), we averaged
the peer ratings and used these scores for all analyses in the study.
The Cronbach’s alphas were .87 for time 1, .87 for time 2, and .86
for time 3. In the coding, items were reversed, such that higher
scores indicated higher levels of social loafing tendencies.

Learning Orientation and Performance Orientation

To assess learning and performance orientations, we used the 8-
item scales developed by Button et al. (1996). Sample items for
learning orientation (a = .84) included “The opportunity to learn
new things is important to me,” and “I prefer to work on tasks that
force me to learn new things.” Sample items for performance ori-
entation (a = .74) included “I prefer to do things that I can do well
rather than things that I do poorly,” and “The opinions others have
about how well I can do certain things are important to me.”

Data Aggregation

We evaluated individual-level scores on the team learning scale
to justify aggregation to the team level. To assess within-group
heterogeneity, we calculated rWG(j) indices (James et al., 1984) for
each measurement time of team learning with a cutoff criterion of

722 GABELICA, DE MAEYER, AND SCHIPPERS

T
hi
s
do
cu
m
en
ti
s
co
py
ri
gh
te
d
by

th
e
A
m
er
ic
an

Ps
yc
ho
lo
gi
ca
lA

ss
oc
ia
tio

n
or

on
e
of

its
al
lie
d
pu
bl
is
he
rs
.

T
hi
s
ar
tic
le
is
in
te
nd
ed

so
le
ly

fo
r
th
e
pe
rs
on
al
us
e
of

th
e
in
di
vi
du
al
us
er

an
d
is
no
tt
o
be

di
ss
em

in
at
ed

br
oa
dl
y.

.70 (George, 1990). Using the uniform null and normal distribu-
tions (George & James, 1993), the average rWG(j) scores were
appropriate for T1 (rWG[j] = .99, SD = .52), T2 (rWG[j] = .99, SD = .52),
and T3 (rWG[j] = 98, SD = .55). We also calculated the intraclass cor-
relation coefficient, ICC(1), to identify the proportion of the var-
iance in the measures that could be explained by team
membership, and the ICC(2) to assess the reliability of the team
means for team learning (Bliese, 2000). All ICC(1) scores were
greater than 0, and their corresponding one-way analyses of var-
iance (ANOVAs) were significant at p , .05. Specifically, the
ICC(1) coefficients were .33 (T1), .41 (T2), .and 40 (T3). The ICC
(2) coefficients were .60 (T1), .68 (T2), and .66 (T3). The cutoff
level of .60 thus was attained for ICC(2) too (Glick, 1985). These
analyses provided sufficient support for aggregating our individ-
ual-level scores to the team level.

Hypotheses Testing

We conducted linear mixed effects modeling to examine the
degrees to which goal orientations affected initial levels and
growth of social loafing and the initial levels and growth of team
learning affected initial levels and growth of social loafing (Dun-
can et al., 2006). With this technique, we can examine average tra-
jectories, the pattern of change in individual and team constructs,
and variations across individuals and teams, as well as analyzing
the instigators of such variations (e.g., intercept or change in team
learning; Mathieu & Rapp, 2009). This method models the
repeated measures of an observed variable, reflecting the initial
status of individuals and the rate of change in the dependent varia-
bles across time periods. Moreover, it allows us to account for the
complex multilevel structure of the data. Repeated measures
(Level 1) were nested within individuals (Level 2) who were
nested within teams (Level 3). For these analyses, we used the
computing environment R Core Team (R) and the linear mixed-
effects models using “Eigen” and S4 package (LME4; Bates et al.,
2016).
In a first step, we modeled three unconditional-growth models

in which no predictors were included except the effects of time.
For both dependent variables (peer-rated and self-rated social loaf-
ing), we first estimated a model in which we assumed a linear
effect of time. In the second model, we allowed the intercepts and
the slope of time to vary from individual to individual. In the third
model, we allowed both the intercept and the slope of time to vary
from individual to individual and from team to team. We expected
between-team differences in both the initial scores and how social
loafing tendencies evolved over the three measurement occasions.
The Step 2 analyses tested the effects of goal orientations and

team learning (H1, H2, H3) on both dependent variables. We first
modeled the effects of learning and performance orientation on the
social loafing intercept and change. We compared the fit of this
model to the fit of the best unconditional model using a �2 log
likelihood test and the Akaike information criterion (AIC; lower
AIC values indicate better model fit). Then, we compared the fit of
the model with only individual-level factors against a model in
which we added team learning as a team-level explanatory factor,
to decide which fit the data best. Finally, to test H3, we con-
structed two measures of team learning: team learning initial states
and team learning growth throughout the trimester.

Results

Self-Rated Social Loafing

Level 1 Analyses: How Does Self-Rated Social Loafing
Change Over Time?

In the first step, we modeled an unconditional growth model in
which no predictors of social loafing were included, except the
effects of time (with the time variable coded such that the initial time
point = 0). We contrasted a model in which the slope of time could
vary from individual to individual (model 2) with a model in which
the effect of time was included only in the fixed part (model 1; see
Table 1). Model 2 achieved better fit. Some individuals loafed more
over time, some loafed less, and others stagnated. Moreover, the
model that added the team-level perspective of social loafing (model
3) attained an even better fit; the slope of time varied from individual
to individual and from team to team. Accordingly, this model pre-
dicts that social loafing evolves differently in different teams, such
that some teams show increased social loafing and other teams show
either no evolution or a decrease in social loafing.

Level 2 Analyses: How Do Learning Orientation, Performance
Orientation, and Team Learning Affect Self-Rated Social
Loafing?

In the second step, we investigated factors that may explain the
change trajectories of social loafing. This stage was fundamental
to understanding why some individuals loafed more or reduced
their loafing behaviors over time. In model 4, we tested only goal
orientation effects, whereas in model 5, we added the main effects
of team learning initial states at time 0 and team learning growth,
as well as the interaction effects between these variables. Finally,
in model 6, we added the control variable ‘team size’.

From the comparison of the various models tested, we conclude
that the multilevel model combining the three explanatory factors—

Table 1
Model Fit Statistics for the Five Models Fitted on Self-Rated Social Loafing

Model �2LL AIC v2 df p

Model 1 (growth only fixed effect) 1,635.4 1,645.4
Model 2 (M1 þ individual differences in growth) 1,492.7 1,506.7 142.67 2 ,.001
Model 3 (M2 þ team differences in growth) 1,485.9 1,503.9 6.78 2 .033
Model 4 (M3 þ goal orientation effects) 1,405.9 1,431.9 80.04 4 ,.001
Model 5 (M4 þ team learning effects) 1,394.8 1,424.8 11.07 2 .004
Model 6 (M5 þ team size) 1,389.5 1,421.5 5.04 1 .021

Note. �2LL = �2 log-likelihood, AIC = Akaike information criterion, df = degrees of freedom.

TAKING A FREE RIDE 723

T
hi
s
do
cu
m
en
ti
s
co
py
ri
gh
te
d
by

th
e
A
m
er
ic
an

Ps
yc
ho
lo
gi
ca
lA

ss
oc
ia
tio

n
or

on
e
of

its
al
lie
d
pu
bl
is
he
rs
.

T
hi
s
ar
tic
le
is
in
te
nd
ed

so
le
ly

fo
r
th
e
pe
rs
on
al
us
e
of

th
e
in
di
vi
du
al
us
er

an
d
is
no
tt
o
be

di
ss
em

in
at
ed

br
oa
dl
y.

learning orientation and performance orientations of individual
members and team learning (model 5)—showed better fit than
the model that accounted for individual-level factors only
(model 4), which was better than the unconditional model
(model 3). Finally, model 6 controlling for team size showed a
better fit than model 5. Table 2 displays the model 6 parameter
estimates.
Individual-Level Factors. Our results show that only learn-

ing orientation had stable effects over time. There was no signifi-
cant interaction with time. That is, though neither learning nor
performance orientation explained why some individuals differed
in their social loafing tendencies over time, learning orientation
did influence their initial states of social loafing. Partially consist-
ent with H1, learning orientation relates negatively to self-rated
social loafing but there are no time effects. We did not, however,
find support for H2.
Team-Level Factor. At the team level, the change in team

learning showed a negative effect on the change of social loafing.
Individual members who were part of teams that scored higher on
team learning throughout the nine weeks of teamwork scored
lower on social loafing. Thus, only change in team learning
explains variations of social loafing over time, thereby confirming
our H3 with regard to self-reported social loafing. Finally, there

was a significant effect of the control variable ‘team size’, showing
a higher degree of self-rated social loafing for members in teams
of 3 than for members in teams of 4.

Peer-Rated Social Loafing

Level 1 Analyses: How Does Self-Rated Social Loafing
Change Over Time?

Following the same procedure for self-rated social loafing,
we modeled unconditional growth without any predictors of
peer-rated social loafing except the effects of time. On average,
we found the same pattern of results. In model 3, in which we
allowed the slope of time to vary from individual member to
individual member, and from team to team, we found better fit
than model 2 (in which we allowed the slope of time to vary
from individual member to individual member), which was
better than model 1, in which we added only the effect of time
to the fixed part (see Table 3). Model 3 predicts that growth
trajectories in peer-rated social loafing differ from team to
team, such that some indicate increases in peer-rated social
loafing, but others show no change or decreases in peer-rated
social loafing.

Table 2
Parameter Estimates (Est.), Standard Errors (SE), and p-Values From Model 6 Fitted on Self-Rated Social Loafing

Parameter Est. SE p

Fixed part
Intercept * 3.171 0.235 ,.001
Time �0.018 0.014 .182
Team size (= 3) 0.543 0.234 .021
Performance orientation �0.015 0.045 .744
Learning orientation �0.387 0.045 ,.001
Team learning (initial score) �0.459 0.353 .194
Team learning (growth) 0.294 0.703 .676
Team Learning (initial score) 3 Time 0.189 0.187 .315
Team Learning (growth) 3 Time �1.181 0.378 .002

Random part
Individual level
Variance in intercepts 0.243
Variance in slopes 0.037
Correlation intercept slope �0.16

Team level
Variance in intercepts 0.002
Variance in slopes 0.006
Correlation intercept slope �1
Residual variance 0.048

* Reference category: team of size = 4.

Table 3
Model Fit Statistics for the Five Models Fitted on Peer-Rated Social Loafing

Model �2LL AIC v2 df p

Model 1 (growth only fixed effect) 2,632.6 2,642.6
Model 2 (M1 þ individual differences in growth) 2,512.2 2,526.2 120.403 2 ,.001
Model 3 (M2 þ team differences in growth) 2,484.6 2,502.6 27.555 2 ,.001
Model 4 (M3 þ goal orientation effects) 2,477.0 2,503.3 7.621 4 .107
Model 5 (M4 þ team learning effects) 2,452.8 2,482.8 24.216 2 ,.001
Model 6 (M5 þ team size) 2,445.7 2,477.7 7.122 1 ,.008

Note. �2LL = �2 log-likelihood, AIC = Akaike information criterion, df = degrees of freedom.

724 GABELICA, DE MAEYER, AND SCHIPPERS

T
hi
s
do
cu
m
en
ti
s
co
py
ri
gh
te
d
by

th
e
A
m
er
ic
an

Ps
yc
ho
lo
gi
ca
lA

ss
oc
ia
tio

n
or

on
e
of

its
al
lie
d
pu
bl
is
he
rs
.

T
hi
s
ar
tic
le
is
in
te
nd
ed

so
le
ly

fo
r
th
e
pe
rs
on
al
us
e
of

th
e
in
di
vi
du
al
us
er

an
d
is
no
tt
o
be

di
ss
em

in
at
ed

br
oa
dl
y.

Level 2 Analyses: HowDo Learning Orientation, Performance
Orientation, and Team Learning Affect Peer-Rated Social
Loafing?

In the second step, we tested whether variations of the direction
of change in peer-rated social loafing also can be explained by the
explanatory factors of our study. Model 4, in which we added the
effects of performance and learning orientations on social loafing
and their interaction effects with the time variable, did not have a
significantly better fit than the unconditional growth model (model
3); we concluded that both performance and learning orientations
have no significant effects on peer-rated social loafing. Accord-
ingly, we estimated model 5 in a more parsimonious way, keeping
the main effects of goal orientations in the model as control varia-
bles but removing the interaction effects with time. Thus, model 5
models the effects of team learning on peer-rated social loafing, af-
ter controlling for the main effects of the individual-level factors,
learning and performance orientations. It achieves a significantly
better fit than model 4. Finally, in model 6, in which we added
team size, we found better fit than model 5. Table 4 displays the
parameter estimates of this model.
Individual-Level Factors. Although we controlled for the

effects of goal orientations, the parameter estimates for the effects of
learning orientation were not significantly different from zero. By
contrast, performance orientation was found to be negatively related
to peer-rated social loafing (H2a) but there was no significant interac-
tion with time (H2b). This result differs from the self-rated data.
Thus, H1 and H2b are not confirmed for peer-rated social loafing.
Team-Level Factor. The initial level of team learning had a

significant negative effect on peer-rated social loafing at the start.
Therefore, in teams in which initial learning scores were higher,
lower social loafing was reported by peers. Over time, the change
of team learning (growth) had a negative interaction effect on
social loafing as rated by peers. That is, teams that increased their
team learning over time were able to counteract the negative
effects of social loafing tendencies perceived by the teammates;

these teams showed a decrease in peer-rated social loafing (H3).
There was also a significant effect of the control variable ‘team
size’, showing a higher degree of peer-rated social loafing for
members in teams of 3 than for members in teams of 4.

Discussion

Research in work and educational settings shows that simply ask-
ing individuals to collaborate does not necessarily lead to optimal
collaboration (Johnson & Johnson, 2014; Kozlowski & Bell, 2013).
Teamwork creates social motivational challenges that teams need to
overcome throughout their experiences (Järvelä & Järvenoja,
2011). Typically, motivational challenges in teams tend to lie in
individual members’ tendency to exert less effort than their team-
mates (i.e., social loafing), leading to process loss. This is highly
concerning as social loafing may intensify over time and lead to a
downward spiral of motivation and process losses. This article
aimed to examine how working on a team task shapes individual
members’ tendency to exert their fair share of effort. Our study
showed that teams that score high on team learning throughout nine
weeks of teamwork experience decreased social loafing.

The primary contribution of this article has been to account for
the temporal dynamics of social loafing and identify important
individual- and team-level factors that affect its development. In
doing so, our study produces three important sets of findings.

First, building on the collective effort model (CEM) and social
interdependence theory, we find that loafing tendencies are more
dynamic than previously thought. In a sample of temporary teams,
social loafing trajectories appear to fluctuate across individuals
and teams and even over a three-month period. Literature on teams
has implicitly considered social loafing as a static rather than tem-
poral variable (Aggarwal & O’Brien, 2008; Hofmann & Jones,
2005). Hence, this finding extends current knowledge about the
dynamic nature of social motivation losses in teams (Kozlowski &
Bell, 2013). Our finding is also consistent with the conceptualiza-
tion that social loafing behaves like effort exertion (as part of

Table 4
Parameter Estimates (Est.), Standard Errors (SE), and P-Values From Model 6 Fitted on Peer-Rated Social Loafing

Parameter Est. SE p

Fixed part
Intercept* 2.105 0.283 ,.001
Time 0.016 0.021 .449
Team size (= 3) 0.565 0.210 .007
Performance orientation �0.111 0.055 .045
Learning orientation 0.016 0.054 .770
Team learning (initial score) �1.292 0.505 .012
Team learning (growth) 0.912 1.008 .367
Team Learning (initial score) 3 Time 0.251 0.295 .455
Team Learning (growth) 3 Time �2.406 0.597 ,.001

Random part
Individual level
Variance in intercepts 0.255
Variance in slopes 0.048
Correlation intercept_slope 0.230

Team level
Variance in intercepts 0.061
Variance in slopes 0.025
Correlation intercept_slope �0.670
Residual variance 0.135

* Reference category: team size = 4.

TAKING A FREE RIDE 725

T
hi
s
do
cu
m
en
ti
s
co
py
ri
gh
te
d
by

th
e
A
m
er
ic
an

Ps
yc
ho
lo
gi
ca
lA

ss
oc
ia
tio

n
or

on
e
of

its
al
lie
d
pu
bl
is
he
rs
.

T
hi
s
ar
tic
le
is
in
te
nd
ed

so
le
ly

fo
r
th
e
pe
rs
on
al
us
e
of

th
e
in
di
vi
du
al
us
er

an
d
is
no
tt
o
be

di
ss
em

in
at
ed

br
oa
dl
y.

behavioral engagement) in individual learning situations, which
has been shown to be altered by situational constraints (Malmberg
& Martin, 2019). Researchers who investigated participation in
social settings more generally have successfully demonstrated that
participation can fluctuate over time (Cheung et al., 2008; Hewitt,
2005). Complementary research focused on SSRL in collaborative
learning has recently provided evidence that engagement in cogni-
tive interactions can vary from moment to moment (e.g., Isohätälä
et al., 2020). However, factors triggering fluctuations in participa-
tion in student-led team tasks are less well understood (Isohätälä
et al., 2020). Extending these lines of research on the temporal
aspects of participation into social loafing models allowed us to
verify that social loafing was also a fluctuating phenomenon across
individuals and teams and to identify factors contributing to those
fluctuations.
Second, building on previous research on the individual characteris-

tics that determine people’s tendencies to loaf (e.g., Charbonnier et
al., 1998; Schippers, 2014), our findings show that the learning orien-
tation of individual team members appears to have constant effects
for any member across time (H1). However, if we had measured
learning orientation repeatedly as well, we might have found some
time effects of other observations of learning orientation on social
loafing trajectories, in line with the strand of research that supports
goal orientation variability (Bernacki et al., 2014). Nevertheless, these
results corroborate the findings of recent work applying Achievement
Goal theory (AGT) to collaborative settings. In this work, cross-sec-
tional data reveal that learning orientation is positively related to col-
laborative (as opposed to antisocial) behaviors such as coregulating
the team processes and elaborating peers’ content (Greisel et al.,
2018; Lee et al., 2010). Note that an unanticipated finding of our
study is that self-reported learning orientation does not predict peer-
rated social loafing. This inconsistency may be due to differing per-
ceptions of attitudes and behaviors by different members of the team.
Finally, although the results of this study do not show any significant
effects of performance orientation on self-rated social loafing emer-
gence or development (H2), performance orientation is found to be
negatively related to initial peer-rated social loafing (H2a). This means
that individuals scoring high on performance orientation are rated by
their peers as low loafers at the first team assignment. This result may
be explained by the fact that, because they seek to obtain affirmative
judgments about their competencies, members scoring high on per-
formance orientation are perceived as behaving collaboratively. Since
the effect is not present for self-rated social loafing, these relationships
may partly be explained by differing perceptions of own versus other
behaviors, an interesting avenue for future research. These conflicting
results corroborate previous studies in the collaborative learning litera-
ture. In fact, contrary to learning orientation’s main motivative role in
collaborative learning, mixed results have been described so far
regarding performance orientation (e.g., Lim & Lim, 2020). Such
results raise the possibility that holding a performance orientation
might have different consequences in team contexts where only team
performance is measured, depending on the timing of the collabora-
tion (Muis & Edwards, 2009). Additionally, it might be that social
loafing is related to the avoidance variant of the achievement goals.
Performance-avoidance goals—engaging in a task with the goal of
avoiding revealing inabilities—have been shown to be related to dis-
engagement in individual learning situations (Urdan & Kaplan, 2020).
It can thus be suggested that the relationship between goal orien-

tation and social loafing is mediated by social goals, such as

building caring and committed relationships and belonging to a
team, and team orientation (Johnson & Johnson, 2009). Moreover,
social goals could increase or decrease the level of endorsement of
members’ goals throughout the process of teamwork (Bernacki et
al., 2014). For example, a high team orientation might explain how
self-interest is expanded to joint interest and how new goals are
crafted in collaborative situations, reducing the emergence of social
loafing. Reaching a shared clarity and consensus about the team’s
purpose and an alignment between individual and team goals could
hence help teams prevent dysfunctional inefficiencies such as social
loafing and optimize the use of the team capabilities (Johnson &
Johnson, 2015; Kayes et al., 2005). If this hypothesis holds true,
this will also suggest that social loafing can be changed and com-
pensated for by strengthening team members’ identification.

Third, the development of social loafing depends not only on
the passage of time but also on the increase of team learning that
arises and grows among team members. Importantly, our results
show that only team learning —a team-level concept—appears to
explain changes in the trajectories of social loafing, over and
above individual goal orientations. Consistent with our hypothesis
3, over time, an increase in team learning leads to a decrease in
social loafing. This finding is particularly significant in the context
of the complex nature of motivation loss and the dearth of research
that demonstrates a relationship between the emergence and
changes in team learning and social loafing (Bell et al., 2012). It
highlights the need to consider temporal aspects of teams, which
include not only team development (i.e., changes in the team as a
whole) but also team socialization (i.e., changes in the relationship
between the team and its members; Levine & Moreland, 1994).
Consequently, these results corroborate group socialization theory
introduced by Levine and Moreland (1994) who suggested that
individuals change as a function of the team that they join. This
theory provides a valuable temporal explanation of how individu-
als can become team members although, as noted by Kozlowski
and Bell (2013), there is a paucity of research focusing on team
socialization over time. Surprisingly, it is still widely believed that
over time, individuals striving for their own goals naturally develop
into team members of an autonomous team capable of adapting
itself to meet environmental contingencies (Kayes et al., 2005).
Furthermore, the present study extends our understanding of the
regulatory approach to team learning (Bell et al., 2012; Chen
et al., 2009) by linking the upgrade of shared knowledge to moti-
vational processes.

However, in the current study we could only infer that sociocog-
nitive interactions had occurred that led to a shift in team’s collec-
tive knowledge (Fransen et al., 2013). Prior research has identified
several factors that may influence why and how an increase in
team knowledge predicts ensuing changes in social loafing,
namely: (1) positive interdependence, (2) group processing behav-
iors, (3) perception of a team reward, and (4) socioemotional inter-
actions. Below, we elaborate on these four factors.

First, it is possible to hypothesize that positive interdependence
(i.e., team members’ perception that they can attain their goals
only if all other teammates promote each other’s efforts to achieve
the goals) is necessary for team learning to have positive effects
on social loafing. When individual members perceive positive
interdependence, they might realize that their efforts are required
for the team to create team knowledge and that they make a unique
contribution to their team. Positive interdependence is also posited

726 GABELICA, DE MAEYER, AND SCHIPPERS

T
hi
s
do
cu
m
en
ti
s
co
py
ri
gh
te
d
by

th
e
A
m
er
ic
an

Ps
yc
ho
lo
gi
ca
lA

ss
oc
ia
tio

n
or

on
e
of

its
al
lie
d
pu
bl
is
he
rs
.

T
hi
s
ar
tic
le
is
in
te
nd
ed

so
le
ly

fo
r
th
e
pe
rs
on
al
us
e
of

th
e
in
di
vi
du
al
us
er

an
d
is
no
tt
o
be

di
ss
em

in
at
ed

br
oa
dl
y.

to create a sense of responsibility and accountability for complet-
ing their share of work (Johnson & Johnson, 2015).
Second, we can argue that group processing enables team learn-

ing development. Several fields of research provide insights into
the nature of group processing. Social interdependence theory
states that group processing encompasses analyzing and imple-
menting actions to achieve the team’s goals (Johnson & Johnson,
2009). In social psychology, group-level information processing
(Hinsz et al., 1997) involves information sharing and use. Simi-
larly, in the research on socially shared regulation of learning
(SSRL), Volet and colleagues (2009) use the term ‘high-level cog-
nitive processing’ depicting behaviors such as elaborating, drawing
inferences, asking thought-provoking questions, and negotiating.
They are all presumed to contribute to the coconstruction of
knowledge, a core behavior that can augment team knowledge
(Van den Bossche et al., 2011). Hence, based on the premise that
shared regulation leads to increased shared knowledge (Lajoie &
Lu, 2011; Saab et al., 2012), and that shared regulation is scarce
when at least one member is disengaged (Isohätälä et al., 2017),
we could suggest that teams that experienced the steeper team
learning shifts in our study self-regulated their motivation and
cognition. Finally, these social regulation processes are similar to
team learning behaviors described in small group research. They
include reflecting on team processes and outcomes, asking ques-
tions, sharing and discussing ideas and divergences, and solving
them constructively to coconstruct new understandings and reach
mutual agreement (see Decuyper et al., 2010; for review).
Third, based on behavioral learning theories (Bandura, 1977)

that posit that individuals will work hard on tasks for which they
obtain a reward and exert less effort in tasks that yield no reward,
we could propose that an increase in team knowledge can be per-
ceived as a reward that make loafers work harder toward their
team goals.
Finally, team learning may affect social loafing through enhanced

concern with the team and its outcomes, higher sense of community
and/or higher cohesiveness (Lam, 2015). Both research on collabo-
rative learning and work in social psychology and organizational
behavior have raised the importance of socioemotional interactions
that complement sociocognitive interactions for successful team-
work (Isohätälä et al., 2017).
To summarize, our study complements past research by demon-

strating the salience of studying the temporal dynamics of group
motivational constructs and identifying team factors that eliminate
motivation losses in group endeavors (Aggarwal & O’Brien, 2008;
Bell et al., 2012). It therefore contributes to address the essential
issues of why teams develop differently and how different aspects
of interaction are connected at the individual and team levels
(Fransen et al., 2013). Examining these relationships over a pro-
longed period of time, and over many performance episodes, may
be a viable route for further research, which also should seek to
specify any boundary conditions for the present effects. Research
on other individual differences or contextual variables that might
explain different social loafing trajectories also is necessary. For
example, positive norms for co-operative work and constructive
behaviors (Buchs et al., 2015) could prevent social loafing. Specif-
ically, social norms that promote team goals, open lines of com-
munication, early resolution, and that expect everyone to work
hard will likely increase members’ motivation to contribute to the
team efforts. It is expected that the more those norms are shared,

the stronger would be the involvement of members in the team ac-
tivity (Levine & Moreland, 2004). Further, research on other
team-emergent mechanisms (e.g., trust, psychological safety, team
cohesion) that might minimize social loafing also is necessary.
Complementary research on regulated learning in social settings
has provided insightful evidence that team members need to
engage in regulated learning to develop joint knowledge construc-
tion (Järvelä et al., 2016; Malmberg et al., 2017). Growth in this
research field provides an exciting opportunity for researchers to
investigate teamwork by shedding light on metacognitive proc-
esses that are essential for overcoming motivational problems in
collaborative learning. By examining these phenomena empiri-
cally, we could gain a better grasp on the complexities of motiva-
tion in team settings. Such insights could assist the design and
application of interventions that stimulate behaviors and processes
that have been shown to be helpful in reducing the tendency to
engage in social loafing. If these results replicate across settings
(e.g., in workplaces) and tasks, the use of team exercises, feed-
back, incentives, and debriefing interventions arguably could
increase the use of effective behaviors and even reduce motivation
loss (Gabelica et al., 2014; Pritchard et al., 2008).

Limitations and Future Directions

Although obvious strengths of the current study are that we
tested the hypotheses with a large number of teams, over time and
in a context where social loafing often occurs, our study is not
without limitations. First, it is conceivable that there was a per-
cept–percept bias in the first model, that predicted changes in self-
rated loafing for testing relationships between variables from the
same questionnaire. However, we minimized the impact of this
bias by using temporal measurements (Podsakoff et al., 2003).
Although the instruments and constructs we use have been shown
to be both reliable and valid, self-reported team learning cannot
fully cover learning behaviors and strategies in which teams
engage. Because we did not systematically observe team learning
processes, the challenges for continuing research are to document
the processes that occur when individuals collaborate to solve
team tasks (Fransen et al., 2013), validate interventions to make
teams function as effectively as possible, and investigate the
impact of team learning and motivation processes on performance.
Closer examination of communication processes may help deter-
mine whether and how learning behaviors vary in quality and
affect social loafing. To address this issue, researchers could over-
lay qualitative analyses to clarify how the quality of specific learn-
ing processes (e.g., sharing information and knowledge; mutually
refining, building on, or modifying each original offer; reflecting
on team processes) increases or decreases over time in dynamic
episodes with social loafing tendencies (Goodman & Dabbish,
2011). The focus of these analyses should be on the sociocognitive
and socioemotional interactions that occur during teamwork, the
conditions under which they occur, what the effects of these inter-
actions are, and how they are interrelated (i.e., the interactions par-
adigm; Dillenbourg et al., 1996).

Second, our validated model differs slightly across the two sour-
ces of ratings of social loafing. We chose to investigate peer ratings
and self ratings independently, because prior outcomes are mixed
with regard to which source best assesses social loafing (Karau &
Williams, 1993; Stark et al., 2007). We find a different pattern

TAKING A FREE RIDE 727

T
hi
s
do
cu
m
en
ti
s
co
py
ri
gh
te
d
by

th
e
A
m
er
ic
an

Ps
yc
ho
lo
gi
ca
lA

ss
oc
ia
tio

n
or

on
e
of

its
al
lie
d
pu
bl
is
he
rs
.

T
hi
s
ar
tic
le
is
in
te
nd
ed

so
le
ly

fo
r
th
e
pe
rs
on
al
us
e
of

th
e
in
di
vi
du
al
us
er

an
d
is
no
tt
o
be

di
ss
em

in
at
ed

br
oa
dl
y.

(higher peer-rating means) than Stark et al. (2007; higher self-rating
means); their study participants were more willing to report their
own versus their teammates’ social loafing. However, the question
of the “true” score of social loafing remains unanswered. To mea-
sure actual social loafing, researchers would need to observe, re-
cord, and interpret accurately team members’ efforts (Lord, 1985;
Mulvey & Klein, 1998). Although perceptions of social loafing and
actual reduced effort may be associated, reduced effort also may
occur without the awareness of team members (Mulvey & Klein,
1998). If reduced efforts are not perceived by the team, they may
not affect team functioning and motivation. Therefore, perceptions
of social loafing require further research. Along these lines, it also
is important to note that prior work has provided empirical evidence
that peer appraisals are associated with reduced social loafing (e.g.,
Druskat & Wolff, 1999). In our study, because students’ evalua-
tions were completed early in the academic year and at multiple
points, social loafing may have been lower than expected in situa-
tions of no peer appraisal. As a result, the magnitude of the underly-
ing effects may be underestimated.
Third, we conducted our study with undergraduate student pro-

ject teams. Although past research on social loafing also has used
student samples (Alnuaimi et al., 2010; Gagné & Zuckerman,
1999; Schippers, 2014), we are cautious about the external validity
of our findings. Student groups sometimes work less as a team and
more as individual participants who complete separate portions of
their assigned task independently (Skilton et al., 2008). Moreover,
expertise distribution within teams in educational settings may be
limited, which may limit the inputs team members have available
to complete tasks and increase their dispensability. Researchers
should determine if our results generalize to employees who con-
stitute project teams outside formal educational settings (Price et
al., 2006). Although loafing tendencies usually are demonstrated
in laboratory settings (Huguet et al., 1999), team members in our
study were not role playing; rather, they were performing mean-
ingful tasks designed to be complex enough to demand team
efforts, have a team goal and reward (i.e., have positive interde-
pendence), and require that a few months be spent together. Our
student teams had assignments that required the cooperation and
coordination of team efforts across multiple meetings, but unlike
teams in a work context, they lacked the same history of common
experiences and identity (Karau & Hart, 1998).
Finally, the current study focused on just two goals assessed

once at the start of the collaboration. While focusing on learning
and performance goals is parsimonious, it fails to account for other
goals that are potentially important in achievement situations in
teams. Research within the achievement goal framework has pro-
liferated over the past years and more complex models have been
studied (i.e., trichotomous achievement goal framework and 2 3 2
achievement goal framework; Urdan & Kaplan, 2020). Addition-
ally, there has been growing evidence that achievement goals can
change across tasks (Bernacki et al., 2014; Fryer & Elliot, 2007).
Future research could capture variations in team members’
endorsement of achievement goals over time and relate these fluc-
tuations to social loafing trajectories. Researchers could verify if
throughout the process of team goal pursuit and regulation, indi-
vidual goal switches or intensification are related to increases or
drops of social loafing.
Despite these limitations, our research contributes to emerging

literature on the development of social loafing. By demonstrating

that the increase of team learning can lower the emergence of
social loafing, it provides further empirical support for the power
of team learning on individual behaviors (Gabelica et al., 2014;
Bell et al., 2012; Decuyper et al., 2010). It also provides an inte-
grative theoretical model that combines individual- and team-level
predictors of social loafing. It highlights the importance of other
team members and their interactive behaviors in determining indi-
vidual behavior. We hope this study stimulates further empirical
and theoretical research on the temporal dynamics of social
loafing.

Practical Implications

Any setting in which people’s efforts are merged into a single
output might be conducive to the demotivating effects of working
in teams. Teachers and trainers may experience withheld effort
that negatively affects not only teams’ but also classes’ perform-
ance and dynamics. In school settings, dealing with social loafing
and its consequences has become a time-consuming concern for
teachers who use team-based learning. An important challenge for
research and practice is to implement strategies for maximizing
team functioning and team learning, such that the potential of each
team’s resources can be fulfilled (Webb et al., 1998).

The outcomes of our study provide substantial insights for
designing and supporting teams in ways that reduce opportunistic
behavior such as social loafing (Tan & Tan, 2008). Our findings
underscore the positive effects of learning orientation on the level
of social loafing at the start of team activities. During team forma-
tion phases (Tuckman & Jenson, 1977), devoting specific attention
to favorable beliefs and appraisals of tasks and teams (high value
to the task and team) may reduce tension arising from the uneven
motivations that often occur in newly formed teams. Assessing
members’ goal orientations may help team managers and teachers
anticipate antisocial behaviors and take early action to build the
learning tones of their teams (Bunderson & Sutcliffe, 2003; Gagné
& Zuckerman, 1999).

When working in increasingly learning-oriented teams, individ-
ual members also may move away from individualistic concerns
and work harder when everyone’s ideas and contributions are val-
ued. This result is encouraging, because it suggests social loafing
is a changeable behavior that fluctuates over time. Stimulating
knowledge sharing and building, learning from prior mistakes, and
constructive team discussions may reduce social loafing tenden-
cies. By asking critical questions and introducing competing per-
spectives and interpretations, teachers and team facilitators can
broaden discussions and promote deeper team concern, commit-
ment, and engagement. This approach calls for the implementation
and evaluation of the motivational benefits of interventions that
facilitate team learning and maintain high learning opportunities
and challenges throughout team tasks (Gabelica et al., 2014; Hack-
man & Wageman, 2005). For example, emerging research indi-
cates that providing teams with feedback on how they have
performed, and inducing team reflection on what teams do and
how they do it, helps them become more effective, especially if
their initial team performance is low (Gurtner et al., 2007). The
co-operative learning literature also provides insight in this regard.
Buchs et al. (2015), for example, highlight the needs to better pre-
pare students for collaboration and use structured methods to en-
courage constructive interactions. Social interdependence theory

728 GABELICA, DE MAEYER, AND SCHIPPERS

T
hi
s
do
cu
m
en
ti
s
co
py
ri
gh
te
d
by

th
e
A
m
er
ic
an

Ps
yc
ho
lo
gi
ca
lA

ss
oc
ia
tio

n
or

on
e
of

its
al
lie
d
pu
bl
is
he
rs
.

T
hi
s
ar
tic
le
is
in
te
nd
ed

so
le
ly

fo
r
th
e
pe
rs
on
al
us
e
of

th
e
in
di
vi
du
al
us
er

an
d
is
no
tt
o
be

di
ss
em

in
at
ed

br
oa
dl
y.

traditionally presumed that team members had the necessary skills
to collaborate successfully (Johnson & Johnson, 2015). To achieve
team learning and effectiveness, it therefore appears necessary to
help teams construct shared understandings of task characteristics
and the team’s knowledge in early stages of teamwork (Fransen et
al., 2013). From a cognitive perspective, team members with poor
communication skills are less likely to benefit from team-based
learning, because they may not be able to share their ideas and
proposals with others; ask critical questions; reflect on their own
and team functioning; provide constructive criticism; or disagree
with elaborated argumentation (Kramarski, & Mevarech, 2003;
Webb & Farivar, 1994). Therefore, preparing newly formed teams
for collaboration by training them in team learning processes (e.g.,
shared reflection, coconstruction, high-level elaboration, construc-
tive disagreements, reaching agreement) that produce high team
performance (Webb et al., 1998) is a promising avenue for team
development.

References

Aggarwal, P., & O’Brien, C. L. (2008). Social loafing on group projects:
Structural antecedents and effect on student satisfaction. Journal of Market-
ing Education, 30(3), 255–264. https://doi.org/10.1177/0273475308322283

Alnuaimi, O. A., Robert, L. P., & Maruping, L. M. (2010). Team size, disper-
sion, and social loafing in technology-supported teams: A perspective on
the theory of moral disengagement. Journal of Management Information
Systems, 27(1), 203–230. https://doi.org/10.2753/MIS0742-1222270109

Arrow, H., McGrath, J. E., & Berdahl, J. L. (2000). Small groups as com-
plex systems: Formation, coordination, development, and adaptation.
Sage.

Bakhtiar, A., Webster, E. A., & Hadwin, A. F. (2017). Regulation and
socio-emotional interactions in a positive and a negative group climate.
Metacognition and Learning, 13(1), 57–90. https://doi.org/10.1007/
s11409-017-9178-x

Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral
change. Psychological Review, 84(2), 191–215. https://doi.org/10.1037/
0033-295X.84.2.191

Barclay, J. H., & Harland, L. K. (1995). Peer performance appraisals: The
impact of rater competence, rater location, and rating correctability on
fairness perceptions. Group & Organization Management, 20(1), 39–60.
https://doi.org/10.1177/1059601195201004

Bates, D. M., Maechler, M., Bolker, B., Walker, S., Christensen, R. H. B.,
Singmann, H., Dai, B., Grothendieck, G., & Green, P. (2016). lme4:
Linear mixed-effects models using S4 classes. R package version
1.1–12.

Bell, B. S., Kozlowski, S. W. J., & Blawath, S. (2012). Team learning: A
theoretical integration and review. In S. W. J. Kozlowski (Ed.), The
Oxford handbook of organizational psychology (pp. 859–909). Oxford
University Press.

Bernacki, M. L., Aleven, V., & Nokes-Malach, T. J. (2014). Stability and
change in adolescents’ task-specific achievement goals and implications
for learning mathematics with intelligent tutors. Computers in Human
Behavior, 37, 73–80. https://doi.org/10.1016/j.chb.2014.04.009

Bliese, P. D. (2000). Within-group agreement, non-independence, and reli-
ability: Implications for data aggregation and analysis. In K. J. Klein &
S. W. J. Kozlowski (Eds.), Multilevel theory, research, and methods in
organizations: Foundations, extensions, and new directions (pp.
349–381). Jossey-Bass.

Bolin, A. U., & Neuman, G. A. (2006). Personality, process, and perform-
ance in interactive brainstorming groups. Journal of Business and Psy-
chology, 20(4), 565–584. https://doi.org/10.1007/s10869-005-9000-7

Boud, D., Cohen, R., & Sampson, J. (2001). Peer Learning in Higher Edu-
cation: Learning from and with each other. Kogan.

Brophy, J. (2005). Goal theorists should move on from performance goals.
Educational Psychologist, 40(3), 167–176. https://doi.org/10.1207/
s15326985ep4003_3

Buchs, C., Gilles, I., Antonietti, J.-P., & Butera, F. (2015). Why students
need to be prepared to cooperate: A co-operative nudge in statistics
learning at university. Educational Psychology, 36(5), 956–974. https://
doi.org/10.1080/01443410.2015.1075963

Bunderson, J. S., & Sutcliffe, K. M. (2003). Management team learning
orientation and business unit performance. Journal of Applied Psychol-
ogy, 88(3), 552–560. https://doi.org/10.1037/0021-9010.88.3.552

Butler, R. (1995). Motivational and informational functions and consequen-
ces of children’s attention to peers’ work. Journal of Educational Psy-
chology, 87(3), 347–360. https://doi.org/10.1037/0022-0663.87.3.347

Button, S. B., Mathieu, J. E., & Zajac, D. M. (1996). Goal orientation in
organizational research: A conceptual and empirical foundation. Organi-
zational Behavior and Human Decision Processes, 67(1), 26–48. https://
doi.org/10.1006/obhd.1996.0063

Carver, C. S., & Scheier, M. F. (1998). On the self-regulation of behavior.
Cambridge University Press. https://doi.org/10.1017/CBO9781139174794

Cellar, D. F., Stuhlmacher, A. F., Young, S. K., Fisher, D. M., Adair,
C. K., Haynes, S., & Riester, D. (2010). Trait goal orientation, self-regu-
lation, and performance: A meta-analysis. Journal of Business and Psy-
chology, 26, 467–483. https://doi.org/10.1007/s10869-010-9201-6

Charbonnier, E., Huguet, P., Brauer, M., & Monteil, J. M. (1998). Social
loafing and self-beliefs: People’s collective effort depends on the extent
to which they distinguish themselves as better than others. Social Behav-
ior and Personality, 26(4), 329–340. https://doi.org/10.2224/sbp.1998
.26.4.329

Chen, G., Kanfer, R., DeShon, R. P., Mathieu, J. E., & Kozlowski, S. W. J.
(2009). The motivating potential of teams: Test and extension of Chen
and Kanfer’s (2006) cross-level model of motivation in teams. Organi-
zational Behavior and Human Decision Processes, 110(1), 45–55.
https://doi.org/10.1016/j.obhdp.2009.06.006

Cheng, W., & Warren, M. (1999). Peer teacher assessment of the oral and
written tasks of a group project. Assessment & Evaluation in Higher
Education, 24(3), 301–314. https://doi.org/10.1080/0260293990240304

Cheung, W. S., Hew, K. F., & Ng, S. L. C. (2008). Toward an understand-
ing of why students contribute in asynchronous online discussions. Jour-
nal of Educational Computing Research, 38(1), 29–50. https://doi.org/
10.2190/EC.38.1.b

Cohen, S. G., & Bailey, D. E. (1997). What makes teams work: Group effec-
tiveness research from the shop floor to the executive suite. Journal of Man-
agement, 23(3), 239–290. https://doi.org/10.1177/014920639702300303

Comer, D. (1995). A model of social loafing in real work groups? Human
Relations, 48(6), 647–667. https://doi.org/10.1177/001872679504800603

Conway, J. M., & Lance, C. E. (2010). What reviewers should expect from
authors regarding common method bias in organizational research. Jour-
nal of Business and Psychology, 25(3), 325–334. https://doi.org/10
.1007/s10869-010-9181-6

Davison, H. K., Mishra, V., Bing, M. N., & Frink, D. D. (2014). How indi-
vidual performance affects the variability of peer evaluations in class-
room teams: A distributive justice perspective. Journal of Management
Education, 38(1), 43–85. https://doi.org/10.1177/1052562912475286

De Dreu, C. K. W., Nijstad, B. A., & van Knippenberg, D. (2008). Moti-
vated information processing in group judgment and decision making.
Personality and Social Psychology Review, 12(1), 22–49. https://doi
.org/10.1177/1088868307304092

Decuyper, S., Dochy, F., & Van den Bossche, P. (2010). Grasping the
dynamic complexity of team learning: An integrative model for effective
team learning in organizations. Educational Research Review, 5(2),
111–133. https://doi.org/10.1016/j.edurev.2010.02.002

TAKING A FREE RIDE 729

T
hi
s
do
cu
m
en
ti
s
co
py
ri
gh
te
d
by

th
e
A
m
er
ic
an

Ps
yc
ho
lo
gi
ca
lA

ss
oc
ia
tio

n
or

on
e
of

its
al
lie
d
pu
bl
is
he
rs
.

T
hi
s
ar
tic
le
is
in
te
nd
ed

so
le
ly

fo
r
th
e
pe
rs
on
al
us
e
of

th
e
in
di
vi
du
al
us
er

an
d
is
no
tt
o
be

di
ss
em

in
at
ed

br
oa
dl
y.

https://doi.org/10.1177/0273475308322283

https://doi.org/10.2753/MIS0742-1222270109

https://doi.org/10.1007/s11409-017-9178-x

https://doi.org/10.1037/0033-295X.84.2.191

https://doi.org/10.1177/1059601195201004

https://doi.org/10.1016/j.chb.2014.04.009

https://doi.org/10.1007/s10869-005-9000-7

https://doi.org/10.1207/s15326985ep4003_3

https://doi.org/10.1080/01443410.2015.1075963

https://doi.org/10.1037/0021-9010.88.3.552

https://doi.org/10.1037/0022-0663.87.3.347

https://doi.org/10.1006/obhd.1996.0063

https://doi.org/10.1017/CBO9781139174794

https://doi.org/10.1007/s10869-010-9201-6

https://doi.org/10.2224/sbp.1998.26.4.329

https://doi.org/10.1016/j.obhdp.2009.06.006

https://doi.org/10.1080/0260293990240304

https://doi.org/10.2190/EC.38.1.b

https://doi.org/10.1177/014920639702300303

https://doi.org/10.1177/001872679504800603

https://doi.org/10.1007/s10869-010-9181-6

https://doi.org/10.1177/1052562912475286

https://doi.org/10.1177/1088868307304092

https://doi.org/10.1016/j.edurev.2010.02.002

Dillenbourg, P., Baker, M., Blaye, A., & O’Malley, C. (1996). The evolu-
tion of research on collaborative learning. In E. Spada & P. Reiman
(Eds.), Learning in Humans and Machine: Towards an interdisciplinary
learning science (pp. 189–211). Elsevier.

Dochy, F., Gijbels, D., Raes, E., & Kyndt, E. (2014). Team learning in
education and professional organisations. In S. Billett, C. Harteis, & H.
Gruber (Eds.), International handbook of research in professional and
practice-based learning (pp. 987–1020). Springer. https://doi.org/10
.1007/978-94-017-8902-8_36

Druskat, V. U., & Wolff, S. B. (1999). Effects and timing of developmen-
tal peer appraisals in self-managing work groups. Journal of Applied
Psychology, 84(1), 58–74. https://doi.org/10.1037/0021-9010.84.1.58

Duffy, M. K., & Shaw, J. D. (2000). The Salieri syndrome: Consequences
of envy in groups. Small Group Research, 31(1), 3–23. https://doi.org/
10.1177/104649640003100101

Duncan, T. E., Duncan, S. C., & Strycker, L. A. (2006). An introduction to
latent variable growth curve modeling. LEA.

Dweck, C. S. (1986). Motivational processes affecting learning. American
Psychologist, 41(10), 1040–1048. https://doi.org/10.1037/0003-066X.41
.10.1040

Dweck, C. S. (1999). Self-theories: Their role in motivation, personality,
and development. Psychology Press.

Elliot, A. J. (2005). A conceptual history of the achievement goal con-
struct. In A. J. Elliot & C. Dweck (Eds.), Handbook of competence and
motivation (pp. 52–72). Guilford Press.

Elliot, A. J., & McGregor, H. A. (2001). A 2 X 2 achievement goal frame-
work. Journal of Personality and Social Psychology, 80(3), 501–519.
https://doi.org/10.1037/0022-3514.80.3.501

Elliot, A. J., & Church, M. A. (1997). A hierarchical model of approach
and avoidance achievement motivation. Journal of Personality and
Social Psychology, 72(1), 218–232. https://doi.org/10.1037/0022-3514
.72.1.218

Ellis, A. P., Hollenbeck, J. R., Ilgen, D. R., Porter, C. O., West, B. J., &
Moon, H. (2003). Team learning: Collectively connecting the dots. Jour-
nal of Applied Psychology, 88(5), 821–835. https://doi.org/10.1037/
0021-9010.88.5.821

Erez, M., & Somech, A. (1996). Is group productivity loss the rule or the
exception? Effects of culture and group-based motivation. Academy of
Management Journal, 39(6), 1513–1537. https://doi.org/10.2307/257067

Forgas, J., Williams, K., & Laham, S. (2005). Social motivation: introduc-
tion and overview. In K. D. Williams & S. M. Laham (Eds.), Social
motivation: Conscious and unconscious processes (pp. 1–15). Cam-
bridge University Press.

Fransen, J., Weinberger, A., & Kirschner, P. (2013). Team effectiveness
and team development in CSCL. Educational Psychologist, 48(1), 9–24.
https://doi.org/10.1080/00461520.2012.747947

Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engage-
ment: Potential of the concept, state of the evidence. Review of Educational
Research, 74(1), 59–109. https://doi.org/10.3102/00346543074001059

Fryer, J. W., & Elliot, A. J. (2007). Stability and change in achievement
goals. Journal of Educational Psychology, 99(4), 700–714. https://doi
.org/10.1037/0022-0663.99.4.700

Gabelica, C., Van den Bossche, P., De Maeyer, S., Segers, M., &
Gijselaers, W. (2014). The effect of team feedback and guided reflexiv-
ity on team performance change. Learning and Instruction, 34, 86–96.
https://doi.org/10.1016/j.learninstruc.2014.09.001

Gagné, M., & Zuckerman, M. (1999). Performance and learning goal orien-
tations as moderators of social loafing and social facilitation. Small Group
Research, 30(5), 524–541. https://doi.org/10.1177/104649649903000502

George, J. M. (1990). Personality, affect, and behavior in groups. Journal
of Applied Psychology, 75(2), 107–116. https://doi.org/10.1037/0021
-9010.75.2.107

George, J. M. (1992). Extrinsic and intrinsic origins of perceived social
loafing in organizations. Academy of Management Journal, 35(1),
191–202. https://doi.org/10.2307/256478

George, J. M., & James, L. R. (1993). Personality, affect, and behavior in
groups revisited: Comment on aggregation, levels of analysis, and a
recent application of within and between analysis. Journal of Applied
Psychology, 78(5), 798–804. https://doi.org/10.1037/0021-9010.78.5.798

Glick, W. H. (1985). Conceptualizing and Measuring Organizational and
Psychological Climate: Pitfalls in Multilevel Research. Academy of
Management Review, 10(3), 601–616. https://doi.org/10.5465/amr.1985
.4279045

Goodman, P., & Dabbish, L. (2011). Methodological issues in measuring
group learning. Small Group Research, 42(4), 379–404. https://doi.org/
10.1177/1046496410385471

Greisel, M., Melzner, N., Kollar, I., & Dresel, M. (2018). How groups reg-
ulate their learning: The influence of achievement goals on self-, co- and
shared regulation strategies. Proceedings of the 13th International Con-
ference of the Learning Sciences: Rethinking Learning in the Digital
Age. Making the Learning Sciences Count.

Gurtner, A., Tschan, F., Semmer, N. K., & Nagele, C. (2007). Getting
groups to develop good strategies: Effects of reflexivity interventions on
team process, team performance, and shared mental models. Organiza-
tional Behavior and Human Decision Processes, 102(2), 127–142.
https://doi.org/10.1016/j.obhdp.2006.05.002

Hackman, J. R., & Wageman, R. (2005). A theory of team coaching. Acad-
emy of Management Review, 30, 269–287. https://doi.org/10.5465/amr
.2005.16387885

Harkins, S. (1987). Social loafing and social facilitation. Journal of Experi-
mental Social Psychology, 23(1), 1–18. https://doi.org/10.1016/0022
-1031(87)90022-9

Hewitt, J. (2005). Toward an understanding of how threads die in asyn-
chronous compute conferences. Journal of the Learning Sciences, 14(4),
567–589. https://doi.org/10.1207/s15327809jls1404_4

Hinsz, V. B., Tindale, R. S., & Vollrath, D. A. (1997). The emerging con-
ceptualization of groups as information processors. Psychological Bulle-
tin, 121(1), 43–64. https://doi.org/10.1037/0033-2909.121.1.43

Hofmann, D. A., & Jones, L. M. (2005). Leadership, collective personality,
and performance. Journal of Applied Psychology, 90, 509–522. https://
doi.org/10.1037/0021-9010.90.3.509

Høigaard, R., Safvenbom, R., & Tonnessen, F. E. (2006). The relationship
between group cohesion, group norms, and perceived social loafing in
soccer teams. Small Group Research, 37(3), 217–232. https://doi.org/10
.1177/1046496406287311

Hommes, J., Van den Bossche, P., de Grave, W., Bos, G., Schuwirth, L., &
Scherpbier, A. (2014). Understanding the effects of time on collabora-
tive learning processes in problem based learning: A mixed methods
study. Advances in Health Sciences Education: Theory and Practice,
19(4), 541–563. https://doi.org/10.1007/s10459-013-9487-z

Huguet, P., Charbonnier, E., & Monteil, J. (1999). Productivity loss in per-
formance groups: People who see themselves as average do not engage
in social loafing. Group Dynamics, 3(2), 118–131. https://doi.org/10
.1037/1089-2699.3.2.118

Ilgen, D. R., Hollenbeck, J. R., Johnson, M., & Jundt, D. (2005). Teams in
organizations: From input-process-output models to IMOI models. An-
nual Review of Psychology, 56, 517–543. https://doi.org/10.1146/
annurev.psych.56.091103.070250

Ilgen, D. R., Major, D. A., & Spencer, L. T. (1994). The cognitive revolu-
tion in organizational behavior. In J. Greenberg (Ed.), Organizational
Behavior: The State of the Science (pp. 1–22). Erlbaum.

Isohätälä, J., Näykki, P., & Järvelä, S. (2020). Cognitive and socio-emo-
tional interaction in collaborative learning: Exploring fluctuations in stu-
dents’ participation. Scandinavian Journal of Educational Research,
64(6), 831–851. https://doi.org/10.1080/00313831.2019.1623310

730 GABELICA, DE MAEYER, AND SCHIPPERS

T
hi
s
do
cu
m
en
ti
s
co
py
ri
gh
te
d
by

th
e
A
m
er
ic
an

Ps
yc
ho
lo
gi
ca
lA

ss
oc
ia
tio

n
or

on
e
of

its
al
lie
d
pu
bl
is
he
rs
.

T
hi
s
ar
tic
le
is
in
te
nd
ed

so
le
ly

fo
r
th
e
pe
rs
on
al
us
e
of

th
e
in
di
vi
du
al
us
er

an
d
is
no
tt
o
be

di
ss
em

in
at
ed

br
oa
dl
y.

https://doi.org/10.1007/978-94-017-8902-8_36

https://doi.org/10.1037/0021-9010.84.1.58

https://doi.org/10.1177/104649640003100101

https://doi.org/10.1037/0003-066X.41.10.1040

https://doi.org/10.1037/0022-3514.80.3.501

https://doi.org/10.1037/0022-3514.72.1.218

https://doi.org/10.1037/0021-9010.88.5.821

https://doi.org/10.2307/257067

https://doi.org/10.1080/00461520.2012.747947

https://doi.org/10.3102/00346543074001059

https://doi.org/10.1037/0022-0663.99.4.700

https://doi.org/10.1016/j.learninstruc.2014.09.001

https://doi.org/10.1177/104649649903000502

https://doi.org/10.1037/0021-9010.75.2.107

https://doi.org/10.2307/256478

https://doi.org/10.1037/0021-9010.78.5.798

https://doi.org/10.5465/amr.1985.4279045

https://doi.org/10.1177/1046496410385471

https://doi.org/10.1016/j.obhdp.2006.05.002

https://doi.org/10.5465/amr.2005.16387885

https://doi.org/10.1016/0022-1031(87)90022-9

https://doi.org/10.1207/s15327809jls1404_4

https://doi.org/10.1037/0033-2909.121.1.43

https://doi.org/10.1037/0021-9010.90.3.509

https://doi.org/10.1177/1046496406287311

https://doi.org/10.1007/s10459-013-9487-z

https://doi.org/10.1037/1089-2699.3.2.118

https://doi.org/10.1146/annurev.psych.56.091103.070250

https://doi.org/10.1080/00313831.2019.1623310

Isohätälä, J., Näykki, P., Järvelä, S., & Baker, M. J. (2017). Striking a bal-
ance: Socio-emotional processes during argumentation in collaborative
learning interaction. Learning, Culture and Social Interaction, 16, 1–19.
https://doi.org/10.1016/j.lcsi.2017.09.003

James, L. R., Demaree, R. J., & Wolf, G. (1984). Estimating withingroup
interrater reliability with and without response bias. Journal of Applied
Psychology, 69(1), 85–98. https://doi.org/10.1037/0021-9010.69.1.85

Järvelä, S., & Järvenoja, H. (2011). Socially constructed self-regulated
learning and motivation regulation in collaborative learning groups.
Teachers College Record, 113(2), 350–374.

Järvelä, S., Järvenoja, H., Malmberg, J., Isohätälä, J., & Sobocinski, M.
(2016). How do types of interaction and phases of self-regulated learn-
ing set a stage for collaborative engagement? Learning and Instruction,
43, 39–51. https://doi.org/10.1016/j.learninstruc.2016.01.005

Jassawalla, A. R., Malshe, A., & Sashittal, H. (2008). Student perceptions
of social loafing in undergraduate business classroom teams. Decision
Sciences Journal of Innovative Education, 6(2), 403–406. https://doi
.org/10.1111/j.1540-4609.2008.00183.x

Johnson, D. W., & Johnson, R. T. (1999). Making co-operative learning
work. Theory into Practice, 38(2), 67–74. https://doi.org/10.1080/
00405849909543834

Johnson, D. W., & Johnson, R. T. (2009). An educational psychology success
story: Social interdependence theory and co-operative learning. Educa-
tional Researcher, 38(5), 365–379. https://doi.org/10.3102/0013189X09
339057

Johnson, D. W., & Johnson, R. T. (2014). co-operative Learning in 21st
Century. Anales de Psicología, 30(3), 841–851. https://doi.org/10.6018/
analesps.30.3.201241

Johnson, D. W., & Johnson, R. T. (2015). Theoretical approaches to co-op-
erative learning. In R. Gillies (Ed.), Collaborative learning: Develop-
ments in research and practice (pp. 17–46). Nova.

Johnson, S. D., Suriya, C., Won Yoon, S., Berrett, J. V., & La Fleur, J.
(2002). Team development and group processes of virtual learning
teams. Computers & Education, 39(4), 379–393. https://doi.org/10
.1016/S0360-1315(02)00074-X

Kaplan, A., & Maehr, M. L. (2007). The contributions and prospects of
goal orientation theory. Educational Psychology Review, 19(2),
141–184. https://doi.org/10.1007/s10648-006-9012-5

Karau, S. J., & Wilhau, A. J. (2020). Social loafing and motivation gains
in groups: An integrative review. In S. J. Karau (Ed.), Individual motiva-
tion within groups: Social loafing and motivation gains in work, aca-
demic, and sports teams (pp. 3–51). Academic Press. https://doi.org/10
.1016/B978-0-12-849867-5.00001-X

Karau, S. J., & Hart, J. R. (1998). Group cohesiveness and social loafing:
Effects of a social interaction manipulation on individual motivation
within groups. Group Dynamics Theory Research and Practice, 2(3),
185–191. https://doi.org/10.1037/1089-2699.2.3.185

Karau, S. J., & Williams, K. D. (1993). Social loafing: A meta-analytic
review and theoretical integration. Journal of Personality and Social Psy-
chology, 65(4), 681–706. https://doi.org/10.1037/0022-3514.65.4.681

Karau, S. J., & Williams, K. D. (1997). The effects of group cohesiveness
on social loafing and social compensation. Group Dynamics, 1(2),
156–168. https://doi.org/10.1037/1089-2699.1.2.156

Kayes, A. B., Kayes, C., & Kolb, D. A. (2005). Experiential learning in
teams. Simulation & Gaming, 36(3), 330–354. https://doi.org/10.1177/
1046878105279012

Kirschner, P. A. (2009). Epistemology or pedagogy, that is the question. In
S. Tobias & T. M. Duffy (Eds.), Constructivist theory applied to instruc-
tion: Success or failure? (pp. 144–157). Routledge.

Kozlowski, S. W. J., & Bell, B. S. (2008). Team learning, development,
and adaptation. In V. I. Sessa & M. London (Eds.),Work group learning
(pp. 15–44). LEA.

Kozlowski, S. W. J., & Bell, B. S. (2013). Work groups and teams in
organizations: Review update. In N. Schmitt & S. Highhouse (Eds.),

Handbook of psychology, vol. 12: Industrial and organizational psy-
chology (2nd ed., pp. 412–469). Wiley.

Kozlowski, S. W. J., & Ilgen, D. R. (2006). Enhancing the effectiveness of
work groups and teams. Psychological Science in the Public Interest,
7(3), 77–124. https://doi.org/10.1111/j.1529-1006.2006.00030.x

Kozlowski, S. W. J., & Klein, K. J. (2000). A multilevel approach to
theory and research in organizations: Contextual, temporal, and emer-
gent processes. In K. J. Klein & S. W. J. Kozlowski (Eds.), Multilevel
theory, research, and methods in organizations: Foundations, exten-
sions, and new directions (pp. 3–90). Jossey-Bass.

Kramarski, B., & Mevarech, Z. R. (2003). Enhancing mathematical rea-
soning in the classroom: The effects of co-operative learning and meta-
cognitive training. American Educational Research Journal, 40(1),
281–310. https://doi.org/10.3102/00028312040001281

Kreijns, K., Kirschner, P. A., & Jochems, W. (2003). Identifying the pit-
falls for social interaction in computer-supported collaborative learning
environments: A review of the research. Computers in Human Behavior,
19(3), 335–353. https://doi.org/10.1016/S0747-5632(02)00057-2

Lajoie, S. P., & Lu, J. (2011). Supporting collaboration with technology:
Does shared cognition lead to coregulation in medicine? Metacognition
and Learning, 7(1), 45–62. https://doi.org/10.1007/s11409-011-9077-5

Lam, C. (2015). The role of communication and cohesion in reducing social
loafing in group projects. Business and Professional Communication
Quarterly, 78(4), 454–475. https://doi.org/10.1177/2329490615596417

Lee, E., Yoon, J., & Kim, M. (2010). Analysing participation types and
developing instructional strategies of wiki-based collaborative learning
by considering learners’ goal orientation and self-esteem. The Korean
Journal of Educational Methodology Studies, 22(4), 43–66.

Levine, J. M., & Moreland, R. L. (1994). Group socialization: Theory and
research. European Review of Social Psychology, 5(1), 305–336. https://
doi.org/10.1080/14792779543000093

Levine, J. M., & Moreland, R. L. (2004). Collaboration: The social context
of theory development. Personality and Social Psychology Review, 8(2),
164–172. https://doi.org/10.1207/s15327957pspr0802_10

Levine, J. M., Moreland, R. L., & Choi, H.-S. (2001). Group socialization
and newcomer innovation. In M. Hogg & R. S. Tindale (Eds.), Black-
well handbook of social psychology: Group processes (pp. 86–106).
Blackwell.

Liden, R. C., Wayne, S. J., Jaworski, R. A., & Bennett, N. (2004). Social
loafing: A field investigation. Journal of Management, 30(2), 285–304.
https://doi.org/10.1016/j.jm.2003.02.002

Lim, J. Y., & Lim, K. Y. (2020). Co-regulation in collaborative learning:
Grounded in achievement goal theory. International Journal of Educa-
tional Research, 103(3), 101621. https://doi.org/10.1016/j.ijer.2020.101621

Locke, E. A., Shaw, K. N., Saari, L. M., & Latham, G. P. (1981). Goal set-
ting and task performance: 1969–1980. Psychological Bulletin, 90(1),
125–152. https://doi.org/10.1037/0033-2909.90.1.125

Lord, R. G. (1985). An information processing approach to social percep-
tions, leadership, and behavioral measurement in organizations.
Research in Organizational Behavior, 7, 87–128.

Loughry, M. L., Ohland, M. W., & Moore, D. D. (2007). Development of
a theory-based assessment of team member effectiveness. Educational
and Psychological Measurement, 67(3), 505–524. https://doi.org/10
.1177/0013164406292085

Madjar, N., Kaplan, A., & Weinstock, M. (2011). Clarifying mastery-avoid-
ance goals in high school: Distinguishing between intrapersonal and task-
based standards of competence. Contemporary Educational Psychology,
36(4), 268–279. https://doi.org/10.1016/j.cedpsych.2011.03.003

Malmberg, J., Järvelä, S., & Järvenoja, H. (2017). Capturing temporal and
sequential patterns of self, co- and socially shared regulation in the con-
text of collaborative learning. Contemporary Educational Psychology,
49(1), 160–174. https://doi.org/10.1016/j.cedpsych.2017.01.009

Malmberg, L. E., & Martin, A. J. (2019). Processes of students’ effort
exertion, competence beliefs and motivation: Cyclic and dynamic effects

TAKING A FREE RIDE 731

T
hi
s
do
cu
m
en
ti
s
co
py
ri
gh
te
d
by

th
e
A
m
er
ic
an

Ps
yc
ho
lo
gi
ca
lA

ss
oc
ia
tio

n
or

on
e
of

its
al
lie
d
pu
bl
is
he
rs
.

T
hi
s
ar
tic
le
is
in
te
nd
ed

so
le
ly

fo
r
th
e
pe
rs
on
al
us
e
of

th
e
in
di
vi
du
al
us
er

an
d
is
no
tt
o
be

di
ss
em

in
at
ed

br
oa
dl
y.

https://doi.org/10.1016/j.lcsi.2017.09.003

https://doi.org/10.1037/0021-9010.69.1.85

https://doi.org/10.1016/j.learninstruc.2016.01.005

https://doi.org/10.1111/j.1540-4609.2008.00183.x

https://doi.org/10.1080/00405849909543834

https://doi.org/10.3102/0013189X09339057

https://doi.org/10.6018/analesps.30.3.201241

https://doi.org/10.1016/S0360-1315(02)00074-X

https://doi.org/10.1007/s10648-006-9012-5

https://doi.org/10.1016/B978-0-12-849867-5.00001-X

https://doi.org/10.1037/1089-2699.2.3.185

https://doi.org/10.1037/0022-3514.65.4.681

https://doi.org/10.1037/1089-2699.1.2.156

https://doi.org/10.1177/1046878105279012

https://doi.org/10.1111/j.1529-1006.2006.00030.x

https://doi.org/10.3102/00028312040001281

https://doi.org/10.1016/S0747-5632(02)00057-2

https://doi.org/10.1007/s11409-011-9077-5

https://doi.org/10.1177/2329490615596417

https://doi.org/10.1080/14792779543000093

https://doi.org/10.1207/s15327957pspr0802_10

https://doi.org/10.1016/j.jm.2003.02.002

https://doi.org/10.1016/j.ijer.2020.101621

https://doi.org/10.1037/0033-2909.90.1.125

https://doi.org/10.1177/0013164406292085

https://doi.org/10.1016/j.cedpsych.2011.03.003

https://doi.org/10.1016/j.cedpsych.2017.01.009

of learning experiences within school days and school subjects. Contem-
porary Educational Psychology, 58, 299–309. https://doi.org/10.1016/j
.cedpsych.2019.03.013

Mathieu, J. E., & Rapp, T. L. (2009). Laying the foundation for successful
team performance trajectories: The roles of team charters and perform-
ance strategies. Journal of Applied Psychology, 94(1), 90–103. https://
doi.org/10.1037/a0013257

Mathieu, J. E., Gallagher, P. T., Domingo, M. A., & Klock, E. A. (2019).
Embracing complexity: Reviewing the past decade of team effectiveness
research. Annual Review of Organizational Psychology and Organiza-
tional Behavior, 6(1), 17–46. https://doi.org/10.1146/annurev-orgpsych
-012218-015106

Mathieu, J. E., Maynard, M. T., Rapp, T. L., & Gilson, L. L. (2008). Team
effectiveness 1997-2007: A review of recent advancements and a
glimpse into the future. Journal of Management, 34(3), 410–476.
https://doi.org/10.1177/0149206308316061

McCardle, L., & Hadwin, A. F. (2015). Using multiple, contextualized
data sources to measure learners’ perceptions of their self-regulated
learning. Metacognition and Learning, 10(1), 43–75. https://doi.org/10
.1007/s11409-014-9132-0

Michaelsen, L., Bauman Knight, A., & Fink, L. D. (Eds.). (2004). Team-
based learning: A transformative use of small groups in college teach-
ing. Stylus.

Midgley, C., Kaplan, A., & Middleton, M. (2001). Performance-approach
goals: Good for what, for whom, under what circumstances, and at what
cost? Journal of Educational Psychology, 93(1), 77–86. https://doi.org/
10.1037/0022-0663.93.1.77

Morgeson, F. P., Reider, M. H., & Campion, M. A. (2005). Selecting indi-
viduals in team settings: The importance of social skills, personality
characteristics, and teamwork knowledge. Personnel Psychology, 58(3),
583–611. https://doi.org/10.1111/j.1744-6570.2005.655.x

Muis, K. R., & Edwards, O. (2009). Examining the stability of achieve-
ment goal orientation. Contemporary Educational Psychology, 34(4),
265–277. https://doi.org/10.1016/j.cedpsych.2009.06.003

Mulvey, P. W., & Klein, H. J. (1998). The impact of perceived loafing and
collective efficacy on group goal processes and group performance.
Organizational Behavior and Human Decision Processes, 74(1), 62–87.
https://doi.org/10.1006/obhd.1998.2753

Newman, R. S., & Schwager, M. T. (1995). Students’ help seeking during
problem solving: Effects of grade, goal, and prior achievement. Ameri-
can Educational Research Journal, 32(2), 352–376. https://doi.org/10
.3102/00028312032002352

Oliveira, A. W., & Sadler, T. D. (2008). Interactive patterns and conver-
gence of meaning during student collaborations in science. Journal of
Research in Science Teaching, 45(5), 634–658. https://doi.org/10.1002/
tea.20211

Patrick, H. S., Van Joolingen, W. R., Savelsbergh, E. R., & van Hout-
Wolters, B. (2008). Motivation and performance within a collaborative
computer-based modelling task: Relations between students’ achieve-
ment goal orientation, self-efficacy, cognitive processing, and achieve-
ment. Contemporary Educational Psychology, 33(1), 58–77. https://doi
.org/10.1016/j.cedpsych.2006.12.004

Payne, S. C., Youngcourt, S. S., & Beaubien, J. M. (2007). A meta-analytic
examination of the goal orientation nomological net. Journal of Applied
Psychology, 92(1), 128–150. https://doi.org/10.1037/0021-9010.92.1.128

Pearsall, M. J., Ellis, A. P. J., & Bell, B. S. (2010). Building the infrastruc-
ture: The effects of role identification behaviors on team cognition de-
velopment and performance. Journal of Applied Psychology, 95(1),
192–200. https://doi.org/10.1037/a0017781

Piezon, S., & Ferree, W. (2008). Perceptions of social loafing in online
learning groups: A study of public university and U.S. Naval War Col-
lege students. International Review of Research in Open and Distance
Learning. Advance online publication. https://doi.org/10.19173/irrodl
.v9i2.484

Pintrich, R. R. (2000). Multiple goals, multiple pathways: The role of goal
orientation in learning and achievement. Journal of Educational Psy-
chology, 92(3), 544–555. https://doi.org/10.1037//0022-O663.92.3.544

Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003).
Common method biases in behavioral research: A critical review of the
literature and recommended remedies. Journal of Applied Psychology,
88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879

Poortvliet, P. M., Janssen, O., Van Yperen, N. W., & Van de Vliert, E.
(2009). The joint impact of achievement goals and performance feed-
back on information giving. Basic and Applied Social Psychology, 31,
197–209. https://doi.org/10.1080/01973530903058276

Poortvliet, P. M., Anseel, F., Janssen, O., Van Yperen, N. W., & Van de
Vliert, E. (2012). Perverse effects of other-referenced performance goals
in an information exchange context. Journal of Business Ethics, 106(4),
401–414. https://doi.org/10.1007/s10551-011-1005-8

Poortvliet, P. M., Janssen, O., Van Yperen, N. W., & Van de Vliert, E.
(2009). Low ranks make the difference: How achievement goals and
ranking information affect cooperation intentions. Journal of Experi-
mental Social Psychology, 45(5), 1144–1147. https://doi.org/10.1016/j
.jesp.2009.06.013

Poortvliet, P. M., Janssen, O., Van Yperen, N. W., & Van de Vliert, E.
(2007). Achievement goals and interpersonal behavior: How mastery
and performance goals shape information exchange. Personality and
Social Psychology Bulletin, 33(10), 1435–1447. https://doi.org/10.1177/
0146167207305536

Price, K. H., Harrison, D. A., & Gavin, J. H. (2006). Withholding inputs in
team contexts: Member composition, interaction processes, evaluation
structure, and social loafing. Journal of Applied Psychology, 91(6),
1375–1384. https://doi.org/10.1037/0021-9010.91.6.1375

Pritchard, R. D., Harrell, M. M., DiazGranados, D., & Guzman, M. J.
(2008). The productivity measurement and enhancement system: A
meta-analysis. Journal of Applied Psychology, 93(3), 540–567. https://
doi.org/10.1037/0021-9010.93.3.540

Raes, E., Kyndt, E., Decuyper, S., Van den Bossche, P., & Dochy, F.
(2015). An exploratory study of group development and team learning.
Human Resource Development Quarterly, 26(1), 5–30. https://doi.org/
10.1002/hrdq.21201

Ramos, A., De Fraine, B., & Verschueren, K. (2021). Learning goal orien-
tation in high-ability and average-ability students: Developmental trajec-
tories, contextual predictors, and long-term educational outcomes.
Journal of Educational Psychology, 113(2), 370–389. https://doi.org/10
.1037/edu0000476

Reeve, J. (2015). Understanding motivation and emotion (6th ed.). Wiley.
Rogat, T., & Linnenbrink-García, L. (2011). Socially shared regulation in

collaborative groups: An analysis of the interplay between quality of
social regulation and group processes. Cognition and Instruction, 29(4),
375–415. https://doi.org/10.1080/07370008.2011.607930

Rolland, R. G. (2012). Synthesizing the evidence on classroom goal struc-
tures in middle and secondary schools: A meta-analysis and narrative
review. Review of Educational Research, 82(4), 396–435. https://doi
.org/10.3102/0034654312464909

Saab, N., Van Joolingen, W. R., & Van Hout-Wolters, B. (2012). Support
of the collaborative inquiry learning process: influence of support on
task and team regulation. Metacognition and Learning, 7(1), 7–23.
https://doi.org/10.1007/s11409-011-9068

Salas, E., Stagl, K. C., Burke, C. S., & Goodwin, G. F. (2007). Fostering
team effectiveness in organizations: Toward an integrative theoretical
framework. In B. Shuart, W. Spaulding, & J. Poland (Eds.), Modeling
complex systems (pp. 185–243). University of Nebraska Press.

Schippers, M. C. (2014). Social loafing tendencies and team performance:
The compensating effect of agreeableness and conscientiousness. Acad-
emy of Management Learning & Education, 13(1), 62–81. https://doi
.org/10.5465/amle.2012.0191

732 GABELICA, DE MAEYER, AND SCHIPPERS

T
hi
s
do
cu
m
en
ti
s
co
py
ri
gh
te
d
by

th
e
A
m
er
ic
an

Ps
yc
ho
lo
gi
ca
lA

ss
oc
ia
tio

n
or

on
e
of

its
al
lie
d
pu
bl
is
he
rs
.

T
hi
s
ar
tic
le
is
in
te
nd
ed

so
le
ly

fo
r
th
e
pe
rs
on
al
us
e
of

th
e
in
di
vi
du
al
us
er

an
d
is
no
tt
o
be

di
ss
em

in
at
ed

br
oa
dl
y.

https://doi.org/10.1016/j.cedpsych.2019.03.013

https://doi.org/10.1037/a0013257

https://doi.org/10.1146/annurev-orgpsych-012218-015106

https://doi.org/10.1177/0149206308316061

https://doi.org/10.1007/s11409-014-9132-0

https://doi.org/10.1037/0022-0663.93.1.77

https://doi.org/10.1111/j.1744-6570.2005.655.x

https://doi.org/10.1016/j.cedpsych.2009.06.003

https://doi.org/10.1006/obhd.1998.2753

https://doi.org/10.3102/00028312032002352

https://doi.org/10.1002/tea.20211

https://doi.org/10.1016/j.cedpsych.2006.12.004

https://doi.org/10.1037/0021-9010.92.1.128

https://doi.org/10.1037/a0017781

https://doi.org/10.19173/irrodl.v9i2.484

https://doi.org/10.1037//0022-O663.92.3.544

https://doi.org/10.1037/0021-9010.88.5.879

https://doi.org/10.1080/01973530903058276

https://doi.org/10.1007/s10551-011-1005-8

https://doi.org/10.1016/j.jesp.2009.06.013

https://doi.org/10.1177/0146167207305536

https://doi.org/10.1037/0021-9010.91.6.1375

https://doi.org/10.1037/0021-9010.93.3.540

https://doi.org/10.1002/hrdq.21201

https://doi.org/10.1037/edu0000476

https://doi.org/10.1080/07370008.2011.607930

https://doi.org/10.3102/0034654312464909

https://doi.org/10.1007/s11409-011-9068

https://doi.org/10.5465/amle.2012.0191

Schippers, M. C., Homan, A. C., & van Knippenberg, D. L. (2013). To
reflect or not to reflect: Prior team performance as a boundary condition
of the effects of reflexivity on learning and final team performance.
Journal of Organizational Behavior, 34(1), 6–23. https://doi.org/10
.1002/job.1784

Schippers, M. C., & Scheepers, A. W. A. (2020). Individual motivation,
team learning and performance in collaborative academic contexts. In
S. J. Karau (Ed.), Individual motivation within groups: Social loafing
and motivation gains in work, academic, and sports teams (pp. 81–108).
Academic Press. https://doi.org/10.1016/B978-0-12-849867-5.00003-3

Simms, A., & Nichols, T. (2014). Social loafing: A review of the literature.
Journal of Management Policy and Practice, 15(1), 58.

Skilton, P. F., Forsyth, D., & White, O. J. (2008). Interdependence and
integration learning in student project teams: Do team project assign-
ments achieve what we want them to? Journal of Marketing Education,
30(1), 57–65. https://doi.org/10.1177/0273475307312198

Skinner, E. A., Kindermann, T. A., Connell, J. P., Wellborn, J. G. (2009).
Engagement and disaffection as organizational constructs in the dynam-
ics of motivational development. In K. R. Wenzel & A. Wigfield (Eds.),
Educational psychology handbook series. Handbook of motivation at
school (p. 223–245). Routledge/Taylor & Francis Group.

Slavin, R. E. (2011). Instruction based on co-operative learning. In R.
Mayer (Ed.), Handbook of research on learning and instruction (pp.
344–360). Taylor and Francis.

Stark, E. M., Shaw, J. D., & Duffy, M. K. (2007). Preference for group
work, winning orientation, and social loafing behavior in groups. Group
& Organization Management, 32(6), 699–723. https://doi.org/10.1177/
1059601106291130

Tan, H. H., & Tan, M. L. (2008). Organizational citizenship behavior and
social loafing: The role of personality, motives, and contextual factors.
The Journal of Psychology, 142(1), 89–108. https://doi.org/10.3200/
JRLP.142.1.89-112

Tan, H. H., & Tan, M. L. (2008). Cooperation versus competition effects
on information sharing and use in group decision-making. Social and
Personality Psychology Compass, 142(1), 89–467.

Toma, C., & Butera, F. (2015). Cooperation versus competition effects on
information sharing and use in group decision making. Social and Per-
sonality Psychology Compass, 9(9), 455–467. https://doi.org/10.1111/
spc3.12191

Tuckman, B. W., & Jensen, M. A. C. (1977). Stages of small-group devel-
opment revisited. Group & Organization Studies, 2(4), 419–427. https://
doi.org/10.1177/105960117700200404

Urdan, T., & Kaplan, A. (2020). The origins, evolution and future direc-
tions of achievement goal theory. Contemporary Educational Psychol-
ogy, 61, 101862https://doi.org/10.1016/j.cedpsych.2020.101862

Van den Bossche, P., Gijselaers, W., Segers, M., Woltjer, G., & Kirschner,
P. A. (2011). Team Learning: Building Shared Mental Models. Instruc-
tional Science, 39(3), 283–301. https://doi.org/10.1007/s11251-010-9128-3

van Dick, R., Tissington, P. A., & Hertel, G. (2009). Do many hands make
light work? How to overcome social loafing and gain motivation in

work teams. European Business Review, 21(3), 233–245. https://doi.org/
10.1108/09555340910956621

Vangrieken, K., Dochy, F., & Raes, E. (2016). Team learning in teacher
teams: Team entitativity as a bridge between teams-in-theory and teams-
in-practice. European Journal of Psychology of Education, 31(3),
275–298. https://doi.org/10.1007/s10212-015-0279-0

Veenman, S., Denessen, E., van den Akker, A., & van der Rijt, J. (2005).
Effects of co-operative learning program on the elaborations of students
during help seeking and help-giving. American Educational Research
Journal, 42(1), 115–115. https://doi.org/10.3102/00028312042001115

Volet, S., & Mansfield, C. (2006). Group work at university: Significance
of personal goals in the regulation strategies of students with positive
and negative appraisals. Higher Education Research & Development,
25(4), 341–356. https://doi.org/10.1080/07294360600947301

Volet, S. E., Summers, M., & Thurman, J. (2009). High-level co-regulation
in collaborative learning: How does it emerge and how is it sustained?
Learning and Instruction, 19(2), 128–143. https://doi.org/10.1016/j
.learninstruc.2008.03.001

Webb, N., & Cullian, L. (1983). Group interaction and achievement in
small groups: Stability over time. American Educational Research Jour-
nal, 20(3), 411–423. https://doi.org/10.3102/00028312020003411

Webb, N. M., Nemer, K. M., Chizhik, A. W., & Sugrue, B. (1998). Equity
issues in collaborative group assessment: Group composition and per-
formance. American Educational Research Journal, 35(4), 607–651.
https://doi.org/10.3102/00028312035004607

Webb, N., & Farivar, S. (1994). Promoting helping behavior in co-opera-
tive small groups in middle school mathematics. American Educa-
tional Research Journal, 31(2), 369–396. https://doi.org/10.3102/
00028312031002369

Weinberger, A., Stegmann, K., & Fischer, F. (2007). Knowledge conver-
gence in collaborative learning: Concepts and assessment. Learning and
Instruction, 17(4), 416–426. https://doi.org/10.1016/j.learninstruc.2007
.03.007

Wiese, C. W., & Burke, C. S. (2019). Understanding Team Learning Dy-
namics Over Time. Frontiers in Psychology, 10, 1417. https://doi.org/10
.3389/fpsyg.2019.01417

Williams, K., Harkins, S., & Latane, B. (1981). Identifiability as a deter-
rent to social loafing: Two cheering experiments. Journal of Personality
and Social Psychology, 40(2), 303–311. 0022-3514/814002-0303100.

Wilson, J. M., Goodman, P. S., & Cronin, M. (2007). Group learning.
Academy of Management Review, 32(4), 1041–1059. https://doi.org/10
.5465/amr.2007.26585724

Zhu, M., Singh, S., & Wang, H. (2019). Perceptions of social loafing dur-
ing the process of group development. International Journal of Organi-
zation Theory and Behavior, 22(4), 350–368. https://doi.org/10.1108/
IJOTB-04-2018-0049

Received August 19, 2020
Revision received July 10, 2021

Accepted August 17, 2021 n

TAKING A FREE RIDE 733

T
hi
s
do
cu
m
en
ti
s
co
py
ri
gh
te
d
by

th
e
A
m
er
ic
an

Ps
yc
ho
lo
gi
ca
lA

ss
oc
ia
tio

n
or

on
e
of

its
al
lie
d
pu
bl
is
he
rs
.

T
hi
s
ar
tic
le
is
in
te
nd
ed

so
le
ly

fo
r
th
e
pe
rs
on
al
us
e
of

th
e
in
di
vi
du
al
us
er

an
d
is
no
tt
o
be

di
ss
em

in
at
ed

br
oa
dl
y.

https://doi.org/10.1002/job.1784

https://doi.org/10.1016/B978-0-12-849867-5.00003-3

https://doi.org/10.1177/0273475307312198

https://doi.org/10.1177/1059601106291130

https://doi.org/10.3200/JRLP.142.1.89-112

https://doi.org/10.1111/spc3.12191

https://doi.org/10.1177/105960117700200404

https://doi.org/10.1016/j.cedpsych.2020.101862

https://doi.org/10.1007/s11251-010-9128-3

https://doi.org/10.1108/09555340910956621

https://doi.org/10.1007/s10212-015-0279-0

https://doi.org/10.3102/00028312042001115

https://doi.org/10.1080/07294360600947301

https://doi.org/10.1016/j.learninstruc.2008.03.001

https://doi.org/10.3102/00028312020003411

https://doi.org/10.3102/00028312035004607

https://doi.org/10.3102/00028312031002369

https://doi.org/10.1016/j.learninstruc.2007.03.007

https://doi.org/10.3389/fpsyg.2019.01417

https://doi.org/10.5465/amr.2007.26585724

https://doi.org/10.1108/IJOTB-04-2018-0049

Literature Review and Hypotheses

Concept of Social Loafing

Operationalization of Social Loafing

Social Loafing and Contextual Factors

Social Loafing and Individual Differences

Learning Orientation and Performance Orientation

Social Loafing and Team-Level Factors

Social Loafing and Team Learning

Dynamics of Social Loafing and Team Learning

Method

Data and Sample

Procedure

Measures

Team Learning

Social Loafing Tendencies

Learning Orientation and Performance Orientation

Data Aggregation

Hypotheses Testing

Results

Self-Rated Social Loafing

Level 1 Analyses: How Does Self-Rated Social Loafing Change Over Time?

Level 2 Analyses: How Do Learning Orientation, Performance Orientation, and Team Learning Affect Self-Rated Social Loafing?

Peer-Rated Social Loafing

Level 1 Analyses: How Does Self-Rated Social Loafing Change Over Time?

Level 2 Analyses: How Do Learning Orientation, Performance Orientation, and Team Learning Affect Peer-Rated Social Loafing?

Discussion

Limitations and Future Directions

Practical Implications

References

SOCIAL PSYCHOLOGY | SHORT COMMUNICATION

The impact of motive disposition on group
performance
Frederic Hilkenmeier1*

Abstract: People exert less effort when performing in groups than when working
alone. Based on the collective effort model’s core principle that individuals are only
willing to work hard if they expect their individual contribution to be instrumental in
obtaining personally satisfying outcomes, this study demonstrates the strong
influence of individual motive dispositions on group performance. Motive disposi-
tions vary from person to person and, when triggered by appropriate cues in the
environment, form the current motivation and determine behavior. In experimental
ad-hoc groups designed to provoke social loafing for individuals with a high need for
achievement, i.e. with few opportunities for self-evaluation, team-members with a
high need for achievement (N = 28) substantially reduced their effort to participate
in the task at hand. Contrary, in the same situation, team-members with a high
need for affiliation (N = 55) showed no social loafing at all, but social laboring
instead, resulting in nearly 50% better performance in the group task compared to
their team members with a high need for achievement.

Subjects: Social Psychology; Personality; Group Processes

Keywords: social loafing; social laboring; need for achievement; need for affiliation; motive
disposition

ABOUT THE AUTHOR
Frederic Hilkenmeier studied psychology at the
University of Hamburg and obtained his Ph.D.
from the University of Paderborn in 2012. He is
currently working as a lecturer and researcher in
the psychology department at Fresenius
University of Applied Sciences on projects deal-
ing with the impact of organizational context
factors as well as individual motivational factors
on learning and performance.

PUBLIC INTEREST STATEMENT
Most teams fall short of their individual potential,
they perform worse on a group-task than one
would expect based on the team-members’ indi-
vidual performances. This is mainly due to moti-
vational losses, meaning many team-members
are less motivated and therefore exert less effort
when they work in a group compared to when
they work alone. However, people are motivated
by different things: two of the main drivers of
human behavior are need for achievement and
need for affiliation. People with a high need for
achievement seek opportunities for self-evalua-
tion, whereas individuals with a high need for
affiliation are incentivized by being with other
people. The same group-task thus offers different
incentives for individuals with different needs,
leading to performance differences in the same
group-task by nearly 50%. Incorporating these
motivational needs into both team-member
selection and design of the group-task at hand
can have substantial implications for a work-
team’s performance and productivity.

Hilkenmeier, Cogent Psychology (2018), 5: 1507123
https://doi.org/10.1080/23311908.2018.1507123

Received: 07 May 201

Accepted: 27 July 2018
First Published: 01 August 2018

*Corresponding author: Frederic
Hilkenmeier, Psychology School,
Fresenius University of Applied
Sciences, Germany
E-mail: frederic.hilkenmeier@hs-fre-
senius.de

Reviewing editor:
Juliet Wakefield, Nottingham Trent
University, United Kingdom

Additional information is available at
the end of the article

Page 1 of 9

http://crossmark.crossref.org/dialog/?doi=10.1080/23311908.2018.1507123&domain=pdf&date_stamp=2018-08-01

http://creativecommons.org/licenses/by/4.0/

1. Introduction
Groups and teams have become basic building blocks of modern organizations, performing all
different types of tasks ranging from physical ones like manufacturing or maintenance to cognitive
ones like decision making or problem solving. However, a host of previous research shows that
most teams fall short of their individual potential, that is, they perform worse than one would
expect based on the team members’ individual performances when working coactively (for a
meta-analysis, see Karau & Williams, 1993). Considerable evidence indicates that a substantial
portion of the team’s decreased performance is due to motivational losses, namely due to social
loafing (for a recent review, see Simms & Nichols, 2014). This means, team members exert less
effort when they work in a group compared to when they work alone. This reduction in effort is not
necessarily a conscious decision, but seems to be the result of a number of social and situational
factors (Williams, Karau, & Bourgeois, 1993). However, the same meta-analysis by Karau and
Williams (1993) shows that more than one fifth of all reported effect sizes point in the opposite
direction. Meaning that in these studies, teams actually increased effort and performance on a
collective task compared to an individual condition (social laboring, Haslam, 2004).

These apparently contradicting findings of motivational losses and motivational gains have been
subsumed in the collective effort model (CEM; Karau & Williams, 1993, 1997, 2001). As summarized
by Karau and Williams (1997, p. 156), the CEM states that individuals are only willing to work hard
on a collective task to the degree that they expect their individual efforts to be instrumental in
obtaining outcomes that are personally satisfying. When the outcomes tied to the group’s perfor-
mance are not perceived as important or relevant, individuals are unlikely to work hard. The CEM
further suggests that outcomes that have intrinsic importance (i.e. are personally involving, or
have personal meaning; see Brickner, Harkins, & Ostrom, 1986) may be particularly important for
individual motivation on collective tasks. The CEM thus opens a promising line of research exam-
ining the role of individual differences in motivational losses and gains (see Hart, Karau, Stasson, &
Kerr, 2004; Stark, Shaw, & Duffy, 2007; Tan & Tan, 2008): Since it is the perceived intrinsic
importance of the group outcome, individuals with different importance-standards should perceive
the identical group situation differently and thus behave differently, resulting in different levels of
performance. As Smith, Kerr, Markus, and Stasson (2001, p. 157) put it: “Future research would do
well to identify other individual-differences variables as moderators of social loafing effects. By
examining these phenomena empirically, we would better understand motivation in group and
team performance [. . .].” Individual-difference constructs of special relevance should be the ones
postulated by the motive disposition approach as represented in McClelland and colleague’s
research tradition (McClelland, 1987; also see Hart et al., 2004; Sorrentino & Sheppard, 1978).
Within McClelland’s research tradition, human needs, particularly need for achievement (nAch) and
need for affiliation (nAffil) are conceptualized as stable motive dispositions that vary from person
to person and, when triggered by appropriate cues in the environment, form the current situational
motivation and determine behavior (e.g. Chun & Choi, 2014; McClelland, 1985, 1987; Schüler,
Sheldon, & Fröhlich, 2010; Sheldon, Prentice, Halusic, & Schüler, 2015).

Individuals with a high nAch seek opportunities for self-evaluation, that is, situations in which
they can get realistic feedback about their own level of (superior) performance, be it by comparing
oneself to others or to a (normative or individual) standard (Atkinson, 1957; Brunstein &
Heckhausen, 2008; McClelland, 1987). For instance, Hart et al. (2004) could show that participants
with a high nAch did not engage in social loafing compared to participants with a low nAch when
the collaborative task was directly related to both individual achievement and intelligence, pre-
sumably because participants with a high nAch perceived this task as a meaningful opportunity for
self-evaluation and instrumental in obtaining personally satisfying outcomes, whereas participants
with a low nAch did not. However, if the collaborative task would not offer such opportunities for
self-evaluation, for instance by featuring low task difficulty (Huguet, Charbonnier, & Monteil, 1999),
or low task meaningfulness (Williams & Karau, 1991), group members with a high nAch should
perceive the task as not important and are therefore unlikely to work hard.

Hilkenmeier, Cogent Psychology (2018), 5: 1507123
https://doi.org/10.1080/23311908.2018.1507123

Page 2 of 9

In contrast, individuals with a high nAffil are concerned “with establishing, maintaining, or restoring
positive interactions with another person or group” (van Cappellen, Frederickson, Saroglou, &
Corneille, 2017, p. 24). They seek social contact and are incentivized by being with other people,
even strangers (McClelland, 1987). As Wiesenfeld, Raghuram, and Garud (2001) could demonstrate,
members of virtual working groups with a high nAffil showed higher identification (i.e. a stronger
sense of belonging) towards their group. These individuals are therefore more likely to work for the
group’s interest, irrespective of the effort and performance they expect from their fellow group
members and of the identifiability of their own contribution (Barreto & Ellemers, 2000; Fielding &
Hogg, 2000; van Knippenberg, 2000; Worchel, Rothgerber, Day, Hart, & Butemeyer, 1998). Group
members with a high nAffil, “need andwant to belong” (Wiesenfeld et al., 2001, p. 217), thus for these
individuals, a group situation per se, even a virtual one or one of low cohesiveness, elicits a feeling of
“groupiness” and should trigger affiliate cues that promise to be rewarding (e.g. Hill, 1987; Høigaard,
Boen, De Cuyper, & Peters, 2013; McAdams & Constantian, 1983).

The focus of the present short communication is therefore to test the influence of motive
disposition – a factor that is “likely to be centrally linked to one’s motivation across a range of
settings” (Hart et al., 2004, p. 987)—on group performance. Understanding individual motive
disposition as a moderator that should interact with the situational incentives offered by the
group situation to shape behavior “might help in the development and implementation of inter-
ventions designed to eliminate motivation losses in group endeavors” (Smith et al., 2001, p. 157).
To test this moderator-effect, the present experiment is provoking social loafing for individuals
with a high nAch. As detailed in the Method Section later, the group situation is therefore designed
in a way that it should not offer appropriate incentives for individuals with a high nAch, by (a)
minimizing saliency and cohesiveness of the ad-hoc-groups (Karau & Hart, 1998), (b) using a task
that is relatively easy and depends on participants’ efforts rather than abilities (van Knippenberg,
2000), and (c) not allowing opportunities for self-evaluation (Karau & Williams, 1997; Lount & Wilk,
2014; Williams et al., 1993). In contrast, group members with a high n Affil should be more
incentivized by the group situation itself and thus show social laboring compared to an individual
coactive situation (van Knippenberg, 2000; Wiesenfeld et al., 2001). However, the design of the
present group condition does not offer additional incentives for individuals with a high nAffil other
than being a group-situation per se, suggesting a rather small social-laboring effect. More for-
malized, the hypothesis of the present study are as follows:

H1: In a given group-situation that does not offer cues relevant to individual achievement,
individuals with a high nAch should reduce performance compared to a situation that offers
such opportunities.

H2: In the same group situation, individuals with a high n Affil should increase performance
compared to the individual achievement-cues situation.

2. Method

2.1. Pretest
A convenience sample of 246 students from the economics department of a medium-sized
University in Germany, all native in the German language, was recruited for course-credit and
pretested on implicit achievement and affiliation motives using the short form of the Multi-
Motive-Grid (Schmalt, Sokolowski, & Langens, 2000; Sokolowski, Schmalt, Langens, & Puca,
2000). The MMG-S is a semiprojective measure, which presents 14 ambiguous line drawings of
everyday situations followed by statements describing feelings, thoughts and action tendencies.
For instance, one line drawing shows two couples, each dancing with one another. This line
drawing is followed by 10 statements, for example, “Feeling good about meeting other people”
(representing nAffil), or “Feeling confident to succeed at this task” (representing nAch).
Participants have to indicate with a simple binary choice whether each statement fits with
the situation or not. Agreements are then aggregated to form sum scores for nAch and nAffil,

Hilkenmeier, Cogent Psychology (2018), 5: 1507123
https://doi.org/10.1080/23311908.2018.1507123

Page 3 of 9

respectively, which are then transformed into T-scores (Schmalt et al., 2000). Reliability and
validity of the MMG and MMG-S has been shown previously. For instance, the retest correlations
for the motive scores range from .77 to .92 (Sokolowski et al., 2000), whereas Puca and Schmalt
(1999) could find support for criterial validity of the nAch score by predicting performance in a
simple reaction task.

2.2. Main experiment
The main experiment involved two within-subject conditions: individual and group. In the indivi-
dual condition, participants were told that their personal performance on a task would be com-
pared with the performance of other individuals in the group, thereby creating an interpersonal
context. In the group condition, participants were told that the unidentifiable individual perfor-
mance of all group members would be combined to form the group score which would be
compared with the scores of other groups, thereby creating an intergroup context (see Smith
et al., 2001 for a similar [but between-subjects-] design).

Performance in both the individual as well as in the group condition was measured using an
anagram word-puzzle. From a nine-letter grid, participants had to find as many words of four
letters or more within three minutes (see Bargh, Gollwitzer, Lee-Chai, Barndollar, &Trötschel, 2001
for a similar performance task). The letters of the grid changed between conditions, while keeping
difficulty the same: Each 9-letter grid contained 18 words in total.

2.3. Participants
In the pretest, 186 students showed T-scores of ≥ 56 on either nAch or nAffil and were thus
contacted via e-mail and asked to return to the lab for another study. Students who preliminary
agreed to participate in the main experiment were invited to the lab in random groups of four,
approximately one to two weeks after the pretest. When at least three students showed up at the
appointed time, the research assistant proceeded with the experiment. Of the 83 final participants,
55 were classified as high nAffil and 28 as high nAch (correlation between nAch and nAffil T-scores:
r [81] = -.09, p = .44; mean difference between the nAch and nAffil T-scores: M = 8.76, SD = 6.61).1

2.4. Design and procedure
Upon arrival, the three or four participants of a given session were seated at separate desks and were
told by the research assistant that they were part of a larger study about a newly designed
performance task (i.e. the anagram-task) to be potentially used in an upcoming assessment center
of a large firm to select apprentices. However, before this task could be integrated into the assess-
ment center, the research assistant’s job was to determine the strength of the training effect of this
new performance task: If performance would strongly increase with repeated training of the task, the
task would be inapplicable for the assessment center. However, if repeating the task would not
increase performance, the task would be implemented into the assessment center. To determine the
strength of the training effect, participants therefore had to perform the task twice in succession.

As an incentive to do their best, participants could earn raffle tickets for a 100€ shopping
voucher in addition to their guaranteed course credit. Participants were told in advance that on
the first run (the individual condition), the individual scores of all members of their group would
immediately be analyzed, compared to each other and announced; and the individual with the
highest score in the anagram-task within the group would get an extra raffle ticket. Therefore,
participants had to sign their task-sheet with their name.

After completing the individual condition and individual scores were announced, participants
came together at a larger table and the research assistant informed them that they now, as
instructed, had to perform the task a second time. However, that after this second run (the group
condition) the research assistant would just gather the individual results, and analyze and combine
them later on. Then, after the whole study was completed, the research assistant would compare
the group’s collective performance to the performance of all other groups taking part in the

Hilkenmeier, Cogent Psychology (2018), 5: 1507123
https://doi.org/10.1080/23311908.2018.1507123

Page 4 of 9

experiment and inform the members of the group with the highest combined group-score via email
that they would each get an extra raffle-ticket. After each member of this newly formed group
again received a task sheet and signed it with the group name instead of its individual name, the
second run started. After they performed the individual as well as the group condition, participants
were thanked for their participation and fully debriefed.

As previously discussed, this relatively simple performance task as well as the general design
was chosen to facilitate possible social loafing effects. As for instance stated by van Knippenberg
(2000), motivational influences on performance are enhanced when the task in question is
relatively easy and mostly depends on participants’ efforts rather than abilities. To further facilitate
social loafing for individuals with high nAch, the group condition lacked opportunities for self-
evaluation: not analyzing individual scores on the second run (the group condition) undermines
social comparison, whereas telling subjects that a practice-effect might be expected undermines
realistic feedback about their own level of performance improvement (Karau & Williams, 1997;
Lount & Wilk, 2014; Williams et al., 1993). Independent of individual motive disposition, the
competitive environment in which only one group could gain the extra raffle-tickets might trigger
social identity and thus facilitate social laboring (i.e. motivational gains, see Kerr & Hertel, 2011;
Worchel et al., 1998). However, this potential effect should be diminished by minimizing saliency
and cohesiveness of the ad-hoc-groups (Karau & Hart, 1998): Even in the group condition, parti-
cipants each worked on their own anagram-task. Moreover, the other groups were not physically
present (i.e. reducing the likelihood to categorize oneself as a group member). Lastly, the delayed
announcement of the winner only to the group that actually won, without any information to all
other groups, should make it hard for individuals to see their coparticipants as members of a
relevant ingroup, especially since they competed against these coparticipants moments ago (for a
review, see Haslam & Ellemers, 2005).

3. Results
Motivational losses (i.e. social loafing) and motivational gains (i.e. social laboring) were assessed by
a two-way ANOVA on number of words produced in the word puzzle with the within-subjects factor
condition (individual vs. group) and the between-subjects factor motive disposition (nAch vs.
nAffil).

As shown in Figure 1, overall performance of the anagram word puzzle did not change sig-
nificantly between the individual and the group condition (M = 6.83, SD = 2.88, range 1–14, max
number of words = 18 vs. M = 6.67, SD = 3.32, range 1–16, max number of words = 18; F[1,
81] = 2.81, p = .10). However, the interaction between the two factors was significant (F[1,
81] = 15.77, p < .01). This interaction reflects the fact that participants with a high nAch indeed showed social loafing (M = 7.11, SD = 2.23 in the individual task vs. M = 5.11, SD = 2.82 in the group task; Holm–Bonferroni corrected one-sided paired t-test t[27] = 4.46, p < .01). Moreover, partici- pants with a high nAffil showed no loafing at all, but social laboring instead (M = 6.69, SD = 2.88 vs. M = 7.47, SD = 3.30; t[54] = 1.76, p < .05), i.e. participants with a high nAffil performed better in the group condition compared to the individual condition. In the group condition, individuals with a high n Affil performed nearly 50% higher than group members with high n Ach (M = 5.11, SD = 2.82 vs. M = 7.47, SD = 3.30; t[81] = 3.10, p < 0.01).

To further corroborate the relationship between underlying motivational needs and (group)
performance, the relative strength of the motivational need was correlated with performance
both in the individual and in the group condition. A stronger nAch relates to higher performance
in the individual condition (r[81] = .32, p < .01); the correlation between the strength of the nAch and the performance in the group condition is negative but nonsignificant (r[81] = -.16, p = .15).

The opposite pattern is shown for nAffil: the strength of nAffil is not related to performance in
the individual task (r[81] = .11, p = .34); however, it correlates with performance in the group task
at least by trend (r[81] = .18, p = .10). Moreover, the more pronounced the achievement motive is

Hilkenmeier, Cogent Psychology (2018), 5: 1507123
https://doi.org/10.1080/23311908.2018.1507123

Page 5 of 9

compared to the affiliation motive within an individual (nAch T-score minus nAffil T-score), the
stronger the social loafing effect (r[81] = .36, p < .01).

4. Discussion
Taken together, the present short communication suggest that different motive dispositions lead to
different perceptions of a given (group) situation, thus have a strong impact on exerted effort and
therewith performance. As predicted, if a group situation offers few opportunities for self-evalua-
tion, group members with high nAch perform less. Group members with a high nAffil on the other
hand show no performance reduction in the same group situation. On the contrary, the group
situation per se seems sufficient to induce a small social laboring effect.

As stated by the CEM (Karau & Williams, 2001) as well as McClelland (1987), the present results
reiterate that individuals are only willing to work hard if the situational cues fit the dispositional
need and thus individual efforts are expected to be instrumental in obtaining outcomes that are
personally satisfying. This line of argumentation can also account for the apparently opposing
results of Hart et al. (2004). As discussed in the introduction, in Hart et al., participants with a high
nAch did not engage in social loafing compared to participants with a low nAch. However, unlike in
the present experiment, Hart et al. told participants that performance in the coactive as well as in
the collaborative task was directly related to both achievement and intelligence. Thus, for Hart
et al.’s participants with a high nAch, the group-task represented a meaningful opportunity for self-
evaluation as well, and thus did not lead to any performance reduction (also see Smith et al., 2001
for similar findings regarding need for cognition).

However, while interpreting the present results, one should keep a number of study-limitations
in mind. The most obvious ones being the low number of participants, the use of university
students in ad-hoc groups, the fixed order of presentation of conditions, and the use of a rather
arbitrary maximizing task that might become dull after participants had proven to themselves they
could do the task sufficiently (Simms & Nichols, 2014). Using established work-groups might have
addressed many of these limitations, but might also have shifted the results by a) attenuating the
strong social-loafing effect shown by individuals with a high nAch, and b) enhancing the social-
laboring effect for individuals with a high nAffil. Established work-groups should show increased
cohesiveness (Lount & Wilk, 2014): members spend more time on the group task, have positive
interactions within the group, as well as opportunities to increase one’s status within the group. All
factors that can reduce social loafing or facilitate social laboring (Høigaard et al., 2013; Karau &
Williams, 1993; Sorrentino & Sheppard, 1978, respectively).

To further support the moderating effect of individual differences in motive disposition on perfor-
mance, future experimental research should overcome the limitations of the present study andaim for
a more comprehensive design, integrating between-subjects conditions that should result in either

individual task group task

Need for Affiliation

Need for Achievement
nu

m
be

r
of

w
or

ds
p

ro
du

ce
d

Figure 1. Average number of
words produced by group
members with high need for
achievement (solid line) and
high need for affiliation (dotted
line). Error bars represent stan-
dard error of the mean.

Hilkenmeier, Cogent Psychology (2018), 5: 1507123
https://doi.org/10.1080/23311908.2018.1507123

Page 6 of 9

motivational gains or motivational losses (Karau & Williams, 1993), for both individuals with high or
low nAch and individuals with high or low nAffil (Hart et al., 2004; Stark et al., 2007; Wiesenfeld, et al.,
2001), in collocated workgroups as well as in virtual ones (Blaskovich, 2008).

Since more and more organizations allocate tasks to distributed temporary project-teams, the
latter differentiation might prove especially promising (Gilson, Maynard, Young, Vartiainen, &
Hakonen, 2015): As previously shown, social loafing poses a particular critical problem for virtual
teams. Thus, understanding how to select and incentivize individuals in virtual group settings is
critical to future organizational success (Blaskovich, 2008). However, virtual-work-group environ-
ments in principle also allow for an individualized configuration of a shared group situation, that is,
offer an individualized vantage point on the identical group situation or task. Using the CEM’s credo
that effort motivation depends on individual’s perceived meaningfulness as a guiding principle, the
well understood motive dispositions nAch and nAffil tested here should enable researchers and
practitioners to design virtual-work-group environments (i.e. groupware) in a way that appropriate
cues for any given motive disposition become more salient. For instance by showing group
member with a high nAch different information than group members with a high nAffil, for
example, different (individual- or group-) statistics on task progress, or highlighting different
goals and outcomes. Such a customized vantage point on the shared group-situation and -task,
based on individual differences in motive disposition, should increase individual motivation while
simultaneously increasing group productivity.

Funding
The author received no direct funding for this research.

Competing interests
The author declares no competing interests.

Author details
Frederic Hilkenmeier1

E-mail: frederic.hilkenmeier@hs-fresenius.de
ORCID ID: http://orcid.org/0000-0002-5068-3108
1 Fresenius University of Applied Sciences Alte Rabenstr,
120148 Hamburg, Germany.

Citation information
Cite this article as: The impact of motive disposition on
group performance, Frederic Hilkenmeier, Cogent
Psychology (2018), 5: 1507123.

Note
1. To contrast the effects of motive disposition on perfor-

mance, it was planned to only invite students with
T-scores of ≥ 60 in one motive disposition to the main
experiment. However, due to the distribution of nAch
and nAffil T-scores in the pretested sample, the more
lenient selection criterion stated above was used to
reach a sufficient sample at all. This more lenient
selection criterion leads to a bias against our hypoth-
eses: Since the respective individual motives are not as
pronounced, the hypothesized effects will most likely
be reduced, that is, the resulting effects sizes should
be interpreted with this caveat in mind.

References
Atkinson, J. W. (1957). Motivational determinants of risk-

taking behaviour. Psychological Review, 64, 359–372.
doi:10.1037/h0043445

Bargh, J. A., Gollwitzer, P. M., Lee-Chai, A., Barndollar, K., &
Trötschel, R. (2001). The automated will:
Nonconscious activation and pursuit of behavioral
goals. Journal of Personality and Social Psychology,
81, 1014–1027. doi:10.1037/0022-3514.81.6.1014

Barreto, M., & Ellemers, N. (2000). You can’t always do
what you want: Social identity and self-presenta-
tional determinants of the choice to work for a low

status group. Personality and Social Psychology
Bulletin, 26, 891–906. doi:10.1177/
01461672002610001

Blaskovich, J. L. (2008). Exploring the effect of distance:
An experimental investigation of virtual collabora-
tion, social loafing, and group decisions. Journal of
Information Systems, 22, 27–46. doi:10.2308/
jis.2008.22.1.27

Brickner, M. A., Harkins, S. G., & Ostrom, T. M. (1986).
Effects of personal involvement: Thoughtprovoking
implications for social loafing. Journal of Personality
and Social Psychology, 51, 763–770. doi:10.1037/
0022-3514.51.4.763

Brunstein, J. C., & Heckhausen, H. (2008). Achievement
motivation. In H. Heckhausen & J. Heckhausen (Eds.),
Motivation and action (pp. 137–183). Cambridge, UK:
Cambridge University Press.

Chun, J. S., & Choi, J. N. (2014). Members’ needs, intragroup
conflict, and group performance. Journal of Applied
Psychology, 99, 437–450. doi:10.1037/a0035640

Fielding, K. S., & Hogg, M. A. (2000). Working hard to
achieve self-defining group goals: A social identity
analysis. Social Psychology, 31, 191–203.

Gilson, L. L., Maynard, M. T., Young, N. C. J., Vartiainen, M.,
& Hakonen, M. (2015). Virtual teams research: 10
years, 10 themes, and 10 opportunities. Journal of
Management, 41, 1313–1337. doi:10.1177/
0149206314559946

Hart, J. W., Karau, S. J., Stasson, M. F., & Kerr, N. A. (2004).
Achievement motivation, expected coworker perfor-
mance, and collective task motivation: Working hard
or hardly working? Journal of Applied Social
Psychology, 34, 984–1000. doi:10.1111/jasp.2004.34.
issue-5

Haslam, S. A. (2004). Psychology in organizations: The
social identity approach. London: Sage.

Haslam, S. A., & Ellemers, N. (2005). Social identity in
industrial and organizational psychology: Concepts,
controversies and contributions. International Review
of Industrial and Organizational Psychology, 20, 39–
118.

Hill, C. A. (1987). Affiliation motivation: People who need
people. . .but in different ways. Journal of Personality
and Social Psychology, 52, 1008–1018.

Hilkenmeier, Cogent Psychology (2018), 5: 1507123
https://doi.org/10.1080/23311908.2018.1507123

Page 7 of 9

https://doi.org/10.1037/h0043445

https://doi.org/10.1037/0022-3514.81.6.1014

https://doi.org/10.1177/01461672002610001

https://doi.org/10.2308/jis.2008.22.1.27

https://doi.org/10.1037/0022-3514.51.4.763

https://doi.org/10.1037/a0035640

https://doi.org/10.1177/0149206314559946

https://doi.org/10.1111/jasp.2004.34.issue-5

Høigaard, R., Boen, F., De Cuyper, B., & Peters, D. M.
(2013). Team identification reduces social loafing
and promotes social laboring in cycling. International
Journal of Applied Sports Science, 25, 33–40.

Huguet, P., Charbonnier, E., & Monteil, J.-M. (1999).
Productivity loss in performance groups: People who
see themselves as average do not engage in social
loafing. Group Dynamics: Theory, Research, and
Practice, 3, 18–131. doi:10.1037/1089-2699.3.2.118

Karau, S. J., & Williams, K. D. (2001). Understanding indi-
vidual motivation in groups: The collective effort
model. In M. E. Turner (Ed.), Groups at work: Theory
and research (2012 ed., pp. 113–141). New York, NY:
Routledge Psychology Press.

Karau, S. J., & Hart, J. W. (1998). Group cohesiveness
and social loafing: Effects on a social interaction
manipulation on individual motivation within
groups. Group Dynamics: Theory, Research, and
Practice, 2, 185–191. doi:10.1037/1089-
2699.2.3.185

Karau, S. J., & Williams, K. (1993). Social loafing: A meta-
analytic review and theoretical integration. Journal of
Personality and Social Psychology, 65, 681–706.
doi:10.1037/0022-3514.65.4.681

Karau, S. J., & Williams, K. (1997). The effects of group
cohesiveness on social loafing and social compen-
sation. Group Dynamics: Theory, Research, and
Practice, 1, 156. doi:10.1037/1089-2699.1.2.156

Kerr, N. L., & Hertel, G. (2011). The Köhler group motiva-
tion gain: How to motivate the ‘weak links’ in a
group. Social and Personality Psychology Compass, 5,
43–55. doi:10.1111/spco.2010.5.issue-1

Lount, R. B., & Wilk, S. L. (2014). Working harder or hardly
working? Posting performance eliminates social
loafing and promotes social laboring in workgroups.
Management Science, 60, 1098–1106. doi:10.1287/
mnsc.2013.1820

McAdams, D. P., & Constantian, C. A. (1983). Intimacy and
affiliation motives in daily living: An experience
sampling analysis. Journal of Personality and Social
Psychology, 45, 851–861. doi:10.1037/0022-
3514.45.4.851

McClelland, D. C. (1985). How motives, skills, and values
determine what people do. American Psychologist,
40, 812–825. doi:10.1037/0003-066X.40.7.812

McClelland, D. C. (1987). Human motivation. New York, NY:
Cambridge University Press.

Puca, R. M., & Schmalt, H.-D. (1999). Task enjoyment: A
mediator between achievement motives and perfor-
mance. Motivation and Emotion, 23, 15–29.
doi:10.1023/A:1021327300925

Schmalt, H.-D., Sokolowski, K., & Langens, T. A. (2000). Das
Multi-Motiv-Gitter für Anschluss, Leistung und Macht
[The multi-motive grid for achievement, affiliation,
and power; measurement instrument]. Frankfurt am
Main, Germany, Pearson.

Schüler, J., Sheldon, K. M., & Fröhlich, S. M. (2010). Implicit
need for achievement moderates the relationship
between competence need satisfaction and subse-
quent motivation. Journal of Research in Personality,
44, 1–12. doi:10.1016/j.jrp.2009.09.002

Sheldon, K. M., Prentice, M., Halusic, M., & Schüler, J.
(2015). Matches between assigned goal-types and
both implicit and explicit motive dispositions predict
goal self-concordance. Motivation and Emotion, 39,
335–343. doi:10.1007/s11031-014-9468-4

Simms, A., & Nichols, T. (2014). Social loafing: A review of
the literature. Journal of Management Policy and
Practice, 15, 58–67.

Smith, B. N., Kerr, N. A., Markus, M. J., & Stasson, M. F.
(2001). Individual differences in social loafing: Need
for cognition as a motivator in collective perfor-
mance. Group Dynamics: Theory, Research, and
Practice, 5, 150–158. doi:10.1037/1089-2699.5.2.150

Sokolowski, K., Schmalt, H.-D., Langens, T. A., & Puca, R. M.
(2000). Assessing achievement, affiliation, and power
motives all at once – The multi-motive grid (MMG).
Journal of Personality Assessment, 74, 126–145.
doi:10.1207/S15327752JPA740109

Sorrentino, R. M., & Sheppard, B. H. (1978). Effects of
affiliation-related motives on swimmers in individual
versus group competition: A field experiment. Journal
of Personality and Social Psychology, 36, 704–714.
doi:10.1037/0022-3514.36.7.704

Stark, E. M., Shaw, J. D., & Duffy, M. K. (2007). Preference
for group work, winning orientation, and social loaf-
ing behavior in groups. Group & Organization
Management, 32, 699–723. doi:10.1177/
1059601106291130

Tan, H. H., & Tan, M. L. (2008). Organizational citizenship
behavior and social loafing: The role of personality,
motives, and contextual factors. The Journal of
Psychology, 142, 89–108. doi:10.3200/JRLP.142.1.89-
112

van Cappellen, P, Fredrickson, B. L, Saroglou, V, &
Corneille, O. (2017). Religiosity and the motivation for
social affiliation. Personality and Individual
Differences, 113, 24–31. doi: 10.1016/j.
paid.2017.02.065

van Knippenberg, D. (2000). Work motivation and perfor-
mance: A social identity perspective. Applied
Psychology: An International Review, 49, 357–372.
doi:10.1111/1464-0597.00020

Wiesenfeld, B. M, Raghuram, S, & Garud, R. (2001).
Organizational identification among virtual workers:
the role of need for affiliation and perceived work-
based social support. Journal Of Management, 27,
213-229. doi: 10.1177/014920630102700205

Williams, K., Karau, S. J., & Bourgeois, M. (1993). Working
on collective tasks: Social loafing and social com-
pensation. In M. A. Hogg & D. Abrams (Eds.), Group
motivation. Social psychological perspectives (pp.
130–148). New York: Harvester Wheatsheaf.

Williams, K., & Karau, S. J. (1991). Social loafing and social
compensation: The effects of expectations of co-
worker performance. Journal of Personality and Social
Psychology, 61, 570–580.

Worchel, S., Rothgerber, H., Day, E. A., Hart, D., &
Butemeyer, J. (1998). Social identity and individual
productivity within groups. British Journal of Social
Psychology, 37, 389–413. doi:10.1111/bjso.1998.37.
issue-4

Hilkenmeier, Cogent Psychology (2018), 5: 1507123
https://doi.org/10.1080/23311908.2018.1507123

Page 8 of 9

https://doi.org/10.1037/1089-2699.3.2.118

https://doi.org/10.1037/1089-2699.2.3.185

https://doi.org/10.1037/0022-3514.65.4.681

https://doi.org/10.1037/1089-2699.1.2.156

https://doi.org/10.1111/spco.2010.5.issue-1

https://doi.org/10.1287/mnsc.2013.1820

https://doi.org/10.1037/0022-3514.45.4.851

https://doi.org/10.1037/0003-066X.40.7.812

https://doi.org/10.1023/A:1021327300925

https://doi.org/10.1016/j.jrp.2009.09.002

https://doi.org/10.1007/s11031-014-9468-4

https://doi.org/10.1037/1089-2699.5.2.150

https://doi.org/10.1207/S15327752JPA740109

https://doi.org/10.1037/0022-3514.36.7.704

https://doi.org/10.1177/1059601106291130

https://doi.org/10.3200/JRLP.142.1.89-112

https://doi.org/10.1016/j.paid.2017.02.065

https://doi.org/10.1111/1464-0597.00020

https://doi.org/10.1177/014920630102700205

https://doi.org/10.1111/bjso.1998.37.issue-4

You are free to:
Share — copy and redistribute the material in any medium or format.
Adapt — remix, transform, and build upon the material for any purpose, even commercially.
The licensor cannot revoke these freedoms as long as you follow the license terms.

Under the following terms:
Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made.
You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
No additional restrictions

Youmay not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Cogent Psychology (ISSN: 2331-1908) is published by Cogent OA, part of Taylor & Francis Group.

Publishing with Cogent OA ensures:

• Immediate, universal access to your article on publication

• High visibility and discoverability via the Cogent OA website as well as Taylor & Francis Online

• Download and citation statistics for your article

• Rapid online publication

• Input from, and dialog with, expert editors and editorial boards

• Retention of full copyright of your article

• Guaranteed legacy preservation of your article

• Discounts and waivers for authors in developing regions

Submit your manuscript to a Cogent OA journal at www.CogentOA.com

Hilkenmeier, Cogent Psychology (2018), 5: 1507123
https://doi.org/10.1080/23311908.2018.1507123

Page 9 of 9

© 2018 The Author(s). This open access article is distributed under a Creative
Commons Attribution (CC-BY) 4.0 license. This work is licensed under the

Creative Commons Attribution License creativecommons.org/licenses/by/4.0/
(the “License”). Notwithstanding the ProQuest Terms and Conditions, you may

use this content in accordance with the terms of the License.

https://doi.org/10.1177/0273475317708588

Journal of Marketing Education
2018, Vol. 40(2) 117 –127
© The Author(s) 2017
Reprints and permissions:
sagepub.com/journalsPermissions.nav
DOI: 10.1177/0273475317708588
journals.sagepub.com/home/jmed

Article

Group-based teaching and learning is ubiquitous across
undergraduate and graduate business curricula (Chapman &
Van Auken, 2001; see also, Batra, Walvoord, & Krishnan,
1997; Huff, Cooper, & Jones, 2002), and with any type of
group work, free-riding—a form of social loafing in which
free-riding group members reap the rewards of nonloafing
members without exerting comparable effort (Comer,
1995)—is a concern (McCorkle et al., 1999; Strong &
Anderson, 1990). Several methods for reducing free-riding
in student groups have been explored (see, Karau & Williams,
1993 for a review). Particular emphasis has been placed on
the use of periodic peer evaluations for curbing and sanction-
ing free-riders (e.g., Aggarwal & O’Brien, 2008; Brooks &
Ammons, 2003; Druskat & Wolff, 1999); however, less
attention has been given to how group assignment may con-
tribute to free-riding.

The present research examines an instructor-driven
method of group assignment, herein called the flocking
method, designed to improve both students’ motivation and
ability to contribute to the group. In particular, students are
flocked, or matched, by the instructor according to their
schedule availability and willingness to devote time to the

course, such that motivated students (i.e., those who plan to
devote more time to the course) are grouped with other
motivated students with similar schedules, whereas unmo-
tivated students (i.e., those who plan to devote less time to
the course) are grouped with other unmotivated students
with similar schedules. Based on a review of the determi-
nants of free-riding, it is proposed that assigning students
with similar motivation levels and schedules to the same
group will reduce many of the temptations and obstacles
commonly associated with free-riding (Hall & Buzwell,
2012), resulting in more equitable contributions across
group members. It is also proposed that this reduction in
free-riding will, in turn, lead to better student learning out-
comes—not only on the group project, but also with regard
to students’ individual understanding of the course content

708588 JMDXXX10.1177/0273475317708588Journal of Marketing EducationHarding
research-article2017

1Belmont University, Nashville, TN, USA

Corresponding Author:
Lora Mitchell Harding, Jack C. Massey College of Business, Belmont
University, 1900 Belmont Boulevard, Nashville, TN 37212-3757, USA.
Email: lora.harding@belmont.edu

Students of a Feather “Flocked”
Together: A Group Assignment Method
for Reducing Free-Riding and Improving
Group and

Individual Learning Outcomes

Lora Mitchell Harding1

Abstract
Group-based teaching and learning is ubiquitous across undergraduate and graduate business curricula, and with any type of
group work, free-riding—a form of social loafing in which free-riding group members reap the rewards of nonloafing members
without exerting comparable effort—is a concern. This research examines a group assignment method, herein called the
flocking method, designed to reduce free-riding by improving students’ motivation and availability to contribute to the group.
A quasi-experiment is described in which students were flocked, or matched, according to their schedule availability and
willingness to devote time to the course, such that motivated students (i.e., those who planned to devote more time) were
grouped with other motivated students with similar schedules, whereas unmotivated students were grouped with other
unmotivated students with similar schedules. Compared with self-selected groups, students in flocked groups not only
reported less free-riding, they also performed better on group and individual assignments, indicating an actual reduction in
free-riding. Additionally, compared with the most prominent methods for reducing free-riding examined in literature, the
flocking method of group assignment reduces resource demands on the instructor and students, making it as efficient to
implement as it is effective. Limitations and directions for future research are discussed.

Keywords
free-riding, social loafing, group project, teamwork, student motivation, learning approaches and issues, marketing education
issues

https://us.sagepub.com/en-us/journals-permissions

https://journals.sagepub.com/home/jmed

mailto:lora.harding@belmont.edu

http://crossmark.crossref.org/dialog/?doi=10.1177%2F0273475317708588&domain=pdf&date_stamp=2017-05-16

118 Journal of Marketing Education 40(2)

on which the group project is based (Slavin, 1990; see also,
Kimber, 1996; Webb, 1997).

In the next sections, the literatures on free-riding and
social loafing are reviewed, with emphasis placed on the
causes of free-riding and corresponding methods of reducing
it. Next, the rationale behind the flocking method of group
assignment is described, drawing from research on the con-
sequences of free-riding and social loafing for other group
members to formulate hypotheses. The results of a quasi-
experiment in which flocked groups are compared with self-
selected groups in an undergraduate marketing research
course are then presented, providing support for the proposi-
tion that students in flocked groups perceive less free-riding
and enjoy better group and individual learning outcomes.
Finally, the contributions and limitations of the research are
discussed, including the benefits and drawbacks of the flock-
ing method of group assignment.

Methods for Reducing Free-Riding in
Groups

The phenomenon of social loafing, defined as “a decrease in
individual effort due to the social presence of other[s]”
(Latané, Williams, & Harkins, 1979, p. 823), was first recog-
nized over a century ago when Ringelmann (see, Latané
et al., 1979, for a discussion) reported that the collective
effort that groups exerted during a rope-pulling exercise was
less than the sum of the group members’ individual efforts
when pulling the rope alone. Social loafing is particularly
problematic when a loafing group member profits from, or
free-rides on, the efforts of nonloafing members, thereby
“deriving benefits . . . that are disproportionately larger than
his or her contributions to the group” (Comer, 1995, p. 649;
see also, Albanese & Van Fleet, 1985). Although several
causes of free-riding have been identified (see, Comer, 1995;
Hall & Buzwell, 2012; Karau & Williams, 1993; Strong &
Anderson, 1990, for reviews), most are predictive of a
decrease in the free-rider’s motivation to contribute to the
group (as opposed to, for example, a decline in intragroup
coordination; Ingham, Levinger, Graves, & Peckham, 1974).
For instance, people are more likely to free-ride when they
believe it will be difficult to identify their individual contri-
butions (George, 1992; Harkins & Jackson, 1985; Jones,
1984; Karau & Williams, 1993; Liden, Wayne, Jaworski, &
Bennett, 2004; Price, Harrison, & Gavin, 2006; K. D.
Williams, Harkins, & Latané, 1981), when they expect other
group members to perform well (Karau & Williams, 1993;
K. D. Williams & Karau, 1991), when the group task is of
low personal meaningfulness (e.g., not intrinsically interest-
ing or consequential to their personal outcomes; Karau &
Williams, 1993; K. D. Williams & Karau, 1991), or when
they feel they are dispensable with little to uniquely contrib-
ute (Harkins & Petty, 1982; Kerr & Bruun, 1983; Price et al.,
2006; Weldon & Mustari, 1988).

Although motivational drivers have received the most
attention, free-riding may also be a product of factors that
constrain one’s ability to contribute to the group, such as lim-
ited scholarly aptitude (real or perceived; Börjesson et al.,
2006; Freeman & Greenacre, 2011; Kerr, 1983; March, 1954;
see also, Karau & Williams, 1997), differing work styles or
time constraints (i.e., availability; Hall & Buzwell, 2012).
For instance, Freeman and Greenacre (2011) find that when
students with limited scholarly aptitude are perceived to be
unwilling to exert comparable effort, they are often ostra-
cized by other group members and effectively blocked from
contributing to the group. Likewise, students with schedules
that routinely prohibit them from meeting with the group
may be willing but, unfortunately, unable to contribute fully
(Hall & Buzwell, 2012). Thus, free-riding is not always a
consequence of one’s willingness to contribute—it may also
be a consequence of one’s ability to contribute.

Several methods for reducing free-riding in groups have
been explored, with particular emphasis on the use of peri-
odic peer evaluations for curbing and sanctioning free-riders
(Mello, 1993; Strong & Anderson, 1990; D. L. Williams,
Beard, & Rymer, 1991). In particular, research shows that
multiple peer evaluations (Aggarwal & O’Brien, 2008;
Brooks & Ammons, 2003), implemented early and with spe-
cific evaluative criteria (Brooks & Ammons, 2003), can
reduce free-riding and improve perceived group outcomes
(Druskat & Wolff, 1999). Peer evaluations are especially
effective at reducing free-riding when used to reward and
sanction individual group members through individualized
group project grades (Cook, 1981; Kench, Field, Agudera, &
Gill, 2009; Jalajas & Sutton, 1984; Maranto & Gresham,
1998; Mello, 1993; D. L. Williams et al., 1991), firing free-
riding members (Abernethy & Lett, 2005), and so on. Other
methods for reducing free-riding have been identified,
including the use of self-evaluations (Harkins & Szymanski,
1988; Szymanski & Harkins, 1987), and the formation of
smaller groups (Aggarwal & O’Brien, 2008; Alnuaimi,
Robert, & Maruping, 2010; Ingham et al., 1974; Karau &
Williams, 1993; Kerr & Bruun, 1981, 1983; Latané et al.,
1979; Liden et al., 2004). However, little attention has been
given to how group assignment may contribute to free-riding
(cf. Bacon, Stewart, & Anderson, 2001; Karau & Hart, 1998;
Karau & Williams, 1993, 1997; Liden et al., 2004; Muller,
1989).

The limited research that has considered the role of group
assignment generally recommends that students form their
own groups. Indeed, self-selection is associated with higher
initial cohesion, motivation to resolve interpersonal conflicts
and established group norms—factors which are predictive
of reduced free-riding (Bacon, Stewart, & Silver, 1999; see
also, Mello, 1993; Strong & Anderson, 1990). Furthermore,
empirical work has shown that self-selection is predictive of
superior group dynamics (Chapman, Meuter, Toy, & Wright,
2006), positive group experiences (Bacon et al., 1999;

Harding 119

Chapman et al., 2006; Mahenthiran & Rouse, 2000), and
higher grades (Mahenthiran & Rouse, 2000).

However, it is important to note that these advantages are
in comparison with randomly-assigned groups; only one
article, to the author’s knowledge, has compared self-selected
with instructor-assigned groups, and no difference in per-
ceived social loafing was found (Aggarwal & O’Brien,
2008). One reason for this null effect may be that the
researchers did not empirically distinguish between groups
assigned randomly and those formed on more strategic bases
(e.g., skill sets, personality types); thus, the effect of each
instructor-assignment method may have nullified the other.
Alternately, Aggarwal and O’Brien note that some instruc-
tors may have used instructor-assignment and self-selection
simultaneously. Regardless, it is unclear why students in
self-selected (vs. instructor-assigned) groups did not report a
lower incidence of social loafing, as predicted. Furthermore,
self-selected groups may suffer from a lack of diversity
(Jalajas & Sutton, 1984), critical task-related skills (Blowers,
2003), cohesion due to tight-knit subgroups (Michaelsen &
Black, 1994), and task focus during meetings (Chapman
et al., 2006), which may impede performance. Thus, the
question remains as to whether self-selection is indeed the
preferred group assignment method for reducing free-riding
or, alternately, if and when instructor-assignment to groups is
preferable.

The Flocking Method of Group
Assignment

The present research examines the flocking method, an
instructor-driven method of group assignment designed to
reduce free-riding by improving students’ motivation and
ability to contribute to the group. As previously discussed,
although there is a robust literature on the motivational ante-
cedents of free-riding and social loafing (Comer, 1995;
Karau & Williams, 1993; Strong & Anderson, 1990), free-
riding is not always a result of apathy or a deliberate lack of
effort—that is, one’s willingness to contribute to the group.
Numerous other factors may instead diminish one’s ability to
contribute, such as time constraints (see, Hall & Buzwell
2012, for a review). Thus, a group assignment method
designed to reduce free-riding would ideally address both
variables.

It is postulated that flocking, or matching, students with
similar motivation levels (i.e., willingness to contribute) and
schedules (i.e., ability to contribute) will reduce many of the
temptations and obstacles commonly associated with free-
riding (Hall & Buzwell, 2012; Mello, 1993). For instance, it
becomes more difficult for a student to willfully free-ride
when other group members are similarly unmotivated; like-
wise, it is easier to avoid unintentionally free-riding when
other group members have similar availability to meet. Thus,
it is proposed that the flocking method of group assignment

will maximize students’ motivation and ability to contribute,
resulting in more equitable contributions (i.e., less free-rid-
ing) in flocked (vs. self-selected) groups. Specifically, it is
hypothesized that

Hypothesis 1: Students in flocked (vs. self-selected)
groups will perceive less free-riding.

Furthermore, it is proposed that a reduction in free-riding
will lead to better group and individual learning outcomes
for all students. It is fairly apparent why this may be the case
for “low motivation” free-riding students: Those who other-
wise would have ridden on the coattails of more motivated
group members are not given the chance to do so; thus, they
are forced to exert more effort themselves (Karau & Williams,
1993; K. D. Williams & Karau, 1991). It may also be that
“low motivation” and “low ability” students (i.e., those who
are more likely to free-ride) are better able to contribute to
the group because their contributions are no longer blocked
by more motivated and/or able group members (Freeman &
Greenacre, 2011; see also, Börjesson et al., 2006; Kerr, 1983;
March, 1954). This enhanced ability to contribute may, in
turn, lead them to become more engaged. In either case,
increased effort on the group project is anticipated to trans-
late not only to better group learning outcomes, but also to a
better individual understanding of the course content on
which the group project is based (Slavin, 1990; see also,
Kimber, 1996; Webb, 1997; cf. Bacon, 2005).

It is also anticipated that a reduction in free-riding will
improve the learning outcomes of non-free-riding students.
This conjecture is based on research on the consequences of
free-riding and social loafing for other group members (see,
Comer, 1995 for a review). As implied by the definition of
free-riding, other group members often pick up free-riders’
slack by increasing their own efforts (Huff et al., 2002; Liden
et al., 2004; K. D. Williams & Karau, 1991). This is most
likely to occur when free-riding is attributed to a lack of abil-
ity on the part of the free-rider (e.g., free-riding members are
trying to pull their weight but are unable to because of their
limited scholarly aptitude, schedule availability, etc.; Karau
& Williams, 1997). However, when free-riding is perceived
to stem from an unwillingness to contribute, as is often the
case (Hall & Buzwell, 2012), the consequences are often less
favorable. In particular, non-free-riders may fall victim to
“disheartened” loafing (Comer, 1995)—that is, reducing
their own efforts with the belief that, no matter the caliber of
their own contributions, they will not be able to pick up the
slack of free-riding members. Alternately, they may succumb
to “retributive” loafing (aka the sucker effect; Kerr, 1983;
see also, Comer, 1995; Jackson & Harkins, 1985)—that is,
choosing to reduce their efforts rather than be a “sucker” who
picks up the slack of others. In either case, perceptions of
free-riding often diminish the motivation of otherwise moti-
vated group members; thus, if perceptions of free-riding

120 Journal of Marketing Education 40(2)

were reduced by creating groups in a manner that minimizes
the willingness and ability to free-ride, the motivation and
efforts of non-free-riding students should remain high.
Again, this heightened effort should lead to better perfor-
mance on the group project and, thus, a better individual
understanding of the course content on which the group proj-
ect is based. Therefore, it is hypothesized that

Hypothesis 2: Students in flocked (vs. self-selected)
groups will have better group and individual learning
outcomes.
Hypothesis 3: The effect of group assignment method on
group and individual learning outcomes will be mediated
by perceived free-riding.

Method

To test these hypotheses, two group assignment methods
(flocking vs. self-selection) are compared using a between-
participants, quasi-experimental design. Data were collected
over a two-year period in an undergraduate marketing research
course with a substantial group work component. In particular,
whereas 50% of the total course grade is based on a variety of
individual assessments (i.e., four multiple-choice exams, α =
.80; 16 true/false quizzes, count top 10, α = .74; two home-
work assignments with correct/incorrect answers, α = .60), the
remaining 50% of the total course grade is based on a semes-
ter-long, multideliverable, client-based group research project.
The group project consists of five major deliverables: (1) a
research request agreement, (2) a research proposal, (3) a
research presentation to the class, (4) a research presentation
to the client, and (5) a final research report. The research pre-
sentation to the client is not graded, per se; rather, students
receive full credit once the instructor receives client confirma-
tion that the presentation took place (all groups reported in this
research received full credit for the client presentation). In
contrast, all other group project deliverables are graded using
detailed rubrics (α = .61; see, Web Appendix for rubrics, avail-
able online at http://journals.sagepub.com/home/jmd). The
purpose of the group project is to enable students to apply the
concepts discussed in class in a real-world setting, thereby
deepening their understanding of those concepts.

In the first academic year (fall and spring semesters;
2014-2015), students were instructed to form their own
groups, which ranged in size from four to six students.
Because research shows that the benefits of self-selection for
subjective group experiences and other outcomes are stron-
gest when students know each other prior to selecting their
own groups (Bacon, Stewart, & Stewart-Belle, 1998), some
insight into how well-acquainted students were prior to
forming groups is warranted. This research was conducted at
a smaller private teaching university with a mostly tradi-
tional, full-time undergraduate population. This course is
typically taken in one’s senior year, which increases the

likelihood that students have already taken one or more
upper-level marketing courses together—courses which
range in size from 20 to 30 students. Anecdotally, most stu-
dents appear to know each other on the first day of class and,
in the self-selection condition, appear to choose group mem-
bers with whom they are reasonably familiar. In the subse-
quent academic year (fall and spring semesters; 2015-2016),
students were instead assigned to groups using the flocking
method of matching students based on motivation and avail-
ability; again, groups ranged in size from four to six students.
All other elements of the course—organization, content,
assignments, and grading—were identical.

The flocking method was implemented using CATME
(www.catme.org), a web-based team management system
that facilitates group formation using responses to an online
survey (Hrivnak, 2013; see also, Bacon, 2014; Loughry,
Ohland, & Woehr, 2014). Survey questions can be custom-
ized and their impact on group formation weighted using an
11-point scale (1 = group dissimilar; 6 = ignore; 11 = group
similar). Although additional questions were included in the
survey, only CATME’s preset questions regarding schedule
availability and the number of hours one plans to devote to
the course were weighted in the formation of groups.
Specifically, students were asked (a) “Please check the times
that you are busy and unavailable for group work” (98 one-
hour blocks between 8:00 am and 10:00 pm each day,
Monday through Sunday; i.e., CATME question titled,
“Schedule”) and (b) “In this course, you intend to work how
many hours per week outside of class (not counting lectures
or labs)?” (1 = 1 hour per week; 2 = 2-4 hours; 3 = 5-7 hours;
4 = 8-10 hours; 5 = whatever it takes; i.e., CATME question
titled, “Commitment Lvl”). Weights of 11 and 9 were desig-
nated for the availability and motivation questions, respec-
tively, such that students assigned to any given group were
similar on these variables. Whereas students were told that
the CATME survey would be used to place them into groups
with others who shared similar schedules, the motivational
component of group assignment was not disclosed.

Perceived free-riding was assessed at the end of each
semester using a confidential peer-evaluation form in which
students individually reported the relative contributions of
each of their group members, including themselves, using a
constant-sum scale (100 points). Little variation in the num-
ber of points allocated to each member represents a low inci-
dence of perceived free-riding, whereas high variation
represents the opposite. Because the number of points repre-
senting equitable contribution varies according to the size of
the group, a coefficient of variation (σ/µ) was computed by
dividing the standard deviation of the set of points allocated
by a given student to his or her group members by the mean
of that set (Muller, 1989). Thus, the smaller (larger) the coef-
ficient of variation, the more (less) equally students were
perceived to contribute to the group, indicating a lower
(higher) incidence of free-riding.

http://journals.sagepub.com/home/jmd

www.catme.org

Harding 121

Finally, student learning outcomes were assessed by
examining group and individual grades, which were col-
lapsed across the various group and individual assignments
in the course. Although grades are an imperfect indicator of
student learning, the number and variety of assessments used
in this course serves to minimize the failure of any particular
assessment to satisfactorily reflect student learning.
Furthermore, grades are widely regarded in the literature as a
valid proxy for actual (vs. perceived) student learning
(Sitzmann, Ely, Brown, & Bauer, 2010; see also, Bacon,
2016; Clayson, 2009).

Results

Prior to testing the conjecture that flocking (vs. self-selec-
tion) reduces free-riding and, thus, improves student learning
outcomes, the two group assignment conditions were com-
pared on four demographic variables: gender, grade point
average (GPA), class standing, and number of absences. A
series of analyses of variance (ANOVAs) and Pearson chi-
square analyses indicated that the conditions are equivalent
on all four variables (see, Table 1); nevertheless, all subse-
quent analyses were conducted using these variables as
covariates.

Perceived Free-Riding

To determine whether flocking (vs. self-selection) reduces
free-riding (Hypothesis 1), individual students’ perceptions
of free-riding (i.e., the coefficient of variation) were

submitted to a one-way between-participants ANOVA. This
analysis yielded a main effect of group assignment, such that
free-riding was reduced (i.e., contribution variance was
lower) when student groups were flocked (vs. self-selected):
M = 0.07 versus 0.15; F(1, 79) = 8.01, p = .01, ηp2 = .09; see,
Table 2. This effect remained significant in a subsequent
analysis of covariance (ANCOVA) with gender, GPA, class
standing, and number of absences included as covariates:
F(1, 75) = 6.78, p = .01, ηp2 = .08. Because individual stu-
dents are nested within groups, supplemental hierarchical
linear modeling (HLM) analyses were conducted to control
for any possible confounding effects of group-level factors
(see, Table 3 for HLM results; students were modeled at
Level 1 and groups at Level 2; Raudenbush & Bryk, 2002).
Three models were estimated: (1) an empty model with no
predictors (M1), which provides a baseline estimate of the
impact of group-level factors on the dependent variable; (2)
a treatment model (M2), which examines the main effect of
group assignment on the dependent variable after controlling
for other group-level factors; (3) a treatment + covariates
model (M3), which examines the robustness of the main
effect of group assignment on the dependent variable after
controlling for gender, GPA, class standing, number of
absences, and other group-level factors (see, Table 3).

First, as shown in M1, group-level factors had a signifi-
cant impact on perceived free-riding ( γ00 = 0.11, p < .001), accounting for one fifth of the variance in the dependent variable (intraclass correlation coefficient = .20). However, as seen in M2, even after controlling for group-level factors ( γ00 = 0.07, p = .02), the main effect of group assignment

Table 1. Group Characteristics.

Group assignment condition Semester Group Group size Gender (female) GPA Class (senior) Absences

Self-selection Fall 1 5 80% (0.45) 3.31 (0.36) 100% (0.00) 3.20 (1.64)
2 6 33% (0.52) 3.42 (0.31) 83% (0.41) 2.00 (1.26)
3 5 80% (0.45) 3.46 (0.38) 100% (0.00) 2.60 (2.30)
4 4 50% (0.58) 3.50 (0.27) 50% (0.58) 2.25 (1.50)
Spring 5 5 60% (0.55) 3.27 (0.49) 80% (0.45) 6.60 (1.14)
6 6 50% (0.55) 3.24 (0.36) 67% (0.52) 2.67 (1.75)
7 6 67% (0.52) 3.22 (0.28) 83% (0.41) 3.83 (2.23)
8 6 33% (0.52) 3.26 (0.38) 100% (0.00) 4.17 (1.17)
Collapsed within condition 5.38 (0.74) 56% (0.50) 3.33 (0.34) 84% (0.37) 3.42 (2.06)

Instructor-assignment
(flocking method)

Fall 9 6 83% (0.41) 3.55 (0.44) 100% (0.00) 4.00 (2.10)
10 6 33% (0.52) 2.96 (0.21) 100% (0.00) 6.50 (2.81)

11 6 83% (0.41) 3.35 (0.24) 100% (0.00) 3.17 (2.32)
12 4 50% (0.58) 3.23 (0.49) 50% (0.58) 4.25 (2.22)
Spring 13 5 40% (0.55) 3.47 (0.39) 80% (0.45) 3.20 (2.77)
14 6 83% (0.41) 3.51 (0.36) 50% (0.55) 2.83 (2.04)
15 6 17% (0.41) 3.03 (0.55) 100% (0.00) 3.67 (3.20)
16 5 60% (0.55) 3.45 (0.28) 60% (0.55) 4.40 (2.51)
Collapsed within condition 5.50 (0.76) 57% (0.50) 3.31 (0.41) 82% (0.39) 4.00 (2.58)
Significance test for difference between conditions (p

value, two-tailed)
F(1, 14) = 0.11,

p = .74
χ2 (1, N = 87) = 0.01,

p = .93
F(1, 85) = 0.02,

p = .89
χ2 (1, N = 87) = 0.06,

p = .81
F(1, 85) = 1.35,

p = .25

Note. Standard deviations indicated in parentheses; n = 87 students and 16 groups.

122 Journal of Marketing Education 40(2)

on free-riding was significant ( γ01 = 0.08, p = .04); in fact,
more than one third (39%) of between-group variance in
perceived free-riding was accounted for by group assign-
ment. Finally, as seen in M3, the main effect of group
assignment on free-riding remained marginally significant
( γ01 = 0.08, p = .06) when group averages for gender, GPA,

Table 2. Descriptive Statistics for Dependent Variables.

Group assignment
condition Semester Group

Perceived variability of
contributions (free-riding) Group grade Average individual grade

Self-selection Fall 1 0.10 (0.22) 88% 79% (0.10)
2 0.14 (0.10) 87% 84% (0.04)
3 0.08 (0.12) 87% 82% (0.08)
4 0.30 (0.19) 90% 85% (0.10)
Spring 5 0.12 (0.11) 83% 78% (0.09)
6 0.06 (0.14) 88% 75% (0.06)
7 0.21 (0.24) 87% 78% (0.07)
8 0.24 (0.08) 76% 74% (0.07)
Collapsed within

condition
0.15 (0.16) 86% (0.04) 79% (0.08)

Instructor-assignment
(flocking method)

Fall 9 0.00 (0.00) 95% 87% (0.07)
10 0.16 (0.12) 83% 79% (0.04)

11 0.12 (0.07) 90% 80% (0.04)
12 0.05 (0.08) 81% 78% (0.08)
Spring 13 0.11 (0.11) 95% 87% (0.08)
14 0.01 (0.02) 93% 92% (0.01)
15 0.10 (0.09) 83% 80% (0.10)
16 0.02 (0.04) 90% 85% (0.05)
Collapsed within

condition
0.07 (0.09) 89% (0.05) 84% (0.07)

Note. Standard deviations indicated in parentheses; n = 87 students and 16 groups.

Table 3. Hierarchical Linear Modeling Results.

Predictors

Dependent variables

Perceived variability of contributions (free-riding) Individual grade

M1 (empty
model) M2 (treatment)

M3 (treatment
+ covariates)

M1 (empty
model) M2 (treatment)

M3 (treatment +
covariates)

Intercept γ00 0.111** (0.020) 0.070* (0.025) 0.070* (0.026) 0.814** (0.012) 0.835** (0.016) 0.839** (0.011)
Treatment
Group assignment γ01 0.082* (0.036) 0.082† (0.038) −0.043† (0.022) −0.048** (0.015)
Covariates
Gender γ02 −0.140 (0.109) −0.029 (0.044)
GPA γ03 −0.022 (0.170) 0.207** (0.069)
Class standing γ04 0.027 (0.104) −0.027 (0.043)
Number of absences γ05 0.001 (0.018) −0.002 (0.007)
Group-level variance (between-group) τ00 0.004 (0.002) 0.002 (0.002) 0.003 (0.003) 0.001 (0.001) 0.001 (0.001) 0.000 (0.000)
Individual-level variance (within-group) σ2 0.014** (0.003) 0.014** (0.003) 0.014** (0.003) 0.005** (0.001) 0.005** (0.001) 0.005** (0.001)
Deviance −96.119 −96.119 −85.218** −195.138 −192.786** −187.263**

Note. Standard errors indicated in parentheses; n = 87 students and 16 groups.
†p < .10. *p < .05. **p < .01.

class standing, and number of absences were added to the
model (covariates, ps >.20; other group-level factors, γ00 =
0.07, p = .03). Collectively, these results provide support
for Hypothesis 1 by showing that students in flocked (vs.
self-selected) groups perceive less free-riding, even after
holding other group-level factors constant.

Harding 123

Group Learning Outcomes
To determine whether flocking (vs. self-selection) leads to
better student learning outcomes (Hypothesis 2), group
grades and individual grades were examined in turn. First, a
one-way ANOVA assessing the impact of group assignment
on group grades revealed that, although the difference was
not significant due to the relatively small number of groups
(n = 16), students in flocked (vs. self-selected) groups per-
formed directionally better on the group project: M = 88.57

versus 85.72; F(1, 14) = 1.22, p = .29, ηp2 = .08; see, Table
2. This main effect became marginally significant in a sub-
sequent ANCOVA when group averages for gender, GPA,
class standing, and number of absences were included as
covariates: F(1, 10) = 3.82, p = .08, ηp2 = .28. To guard
against the possibility of overfitting given the number of
parameters relative to the sample size, covariates were
removed from the model sequentially. First, the main effect
of group assignment remained marginally significant when
class standing, which has the smallest effect size of the
four covariates ( ηp2 = .01), was removed from the model:
F(1, 11) = 4.09, p = .07, ηp2 = .27. Furthermore, this mar-
ginal main effect remained robust when gender (second
smallest effect size; ηp2 = .08) was also removed from the
model: F(1, 12) = 3.91, p = .07, ηp2 = .25). Finally, the
main effect of group assignment remained marginally sig-
nificant when number of absences ( ηp2 = .11) was removed
from the model, leaving only GPA (ηp2 = .22) as a covari-
ate: F(1, 13) = 3.25, p = .10, ηp2 = .20. Thus, overfitting
does not appear to be an issue. Collectively, these results
provide preliminary support for Hypothesis 2 by showing
that students in flocked (vs. self-selected) groups have
directionally better group learning outcomes.

Individual Learning Outcomes

Next, to determine whether flocking (vs. self-selection) leads
to better individual learning outcomes (Hypothesis 2), indi-
vidual grades were examined using a one-way ANOVA. As
predicted, students in flocked (vs. self-selected) groups per-
formed better on the individual component of their grades:
M = 83.59 versus 79.12; F(1, 85) = 7.39, p = .01, ηp2 = .08;
see, Table 2. Furthermore, when all covariates were included
in a subsequent ANCOVA, this effect remained significant:
F(1, 81) = 19.81, p < .001, ηp2 = .20. Again, to control for any possible confounding effects of group-level factors, supple- mental HLM analyses were conducted (see, Table 3). First, as with perceived free-riding, group-level factors had a signifi- cant impact on individual grades ( γ00 = 0.81, p < .001), accounting for nearly one fourth of the variance in the depen- dent variable (intraclass correlation coefficient = .24; see, M1). However, as seen in M2, even after controlling for group-level factors ( γ00 = 0.84, p < .001), the main effect of group assignment on individual grades was marginally signifi- cant ( γ01 = −0.04, p = .08); in fact, one fourth (25%) of

between-group variance in individual grades was accounted
for by group assignment. Finally, as seen in M3, the main
effect of group assignment on individual grades was signifi-
cant ( γ01 = −0.05, p = .003) when group averages for gender,
GPA, class standing, and number of absences were added to
the model (GPA γ03 = 0.21, p = .004; all other covariates, ps
>.50; other group-level factors, γ00 = 0.84, p < .001). Collectively, these results provide additional support for Hypothesis 2 by showing that students in flocked (vs. self- selected) groups have better individual learning outcomes, even after holding other group-level factors constant.

Mediation Analyses

To determine whether perceptions of free-riding mediate the
relationship between group assignment and group and indi-
vidual learning outcomes (Hypothesis 3), mediation models
for group grades and individual grades were examined in
turn (see, Table 4 for complete path analyses; abbreviated
results reported here). A mediation analysis for group grades
was conducted first (Hayes, 2013, PROCESS Model 4), with
group assignment (1 = flocking; −1 = self-selection) entered
into the model as the independent variable, free-riding (i.e.,
the coefficient of variation; centered) entered as the proposed
mediator, and group grade entered as the dependent variable
(see, Figure 1; top panel). As predicted, flocking was associ-
ated with reduced free-riding (i.e., lower contribution vari-
ance) and reduced free-riding was associated with higher
group grades. Most important, a bias-corrected, 95% confi-
dence interval (CI) based on 5,000 bootstrap samples
revealed that group assignment had an indirect effect on
group grade through the proposed mediator, free-riding
(indirect effect [ab] = 0.003, standard error [SE] = 0.002, CI
[0.001, 0.008]), which indicates that free-riding mediated the
effect of group assignment on group grades.

A parallel analysis was conducted for individual grades,
which revealed that, although flocking was associated
with reduced free-riding and higher individual grades,
perceived free-riding alone did not mediate the relation-
ship between group assignment and individual learning
outcomes (indirect effect [ab] = −0.001, SE = 0.003, CI
[−0.009, 0.004]). However, it was postulated that the
effect of free-riding on individual learning may be indi-
rect, such that it is only when students contribute more
equally (and, thus, perform better) on the group project
that they learn more as individuals. Indeed, a multiple
mediator path analysis (Hayes, 2013, PROCESS Model 6)
with group assignment entered as the independent vari-
able, free-riding and group grade (centered) entered as
serial mediators, and individual grade entered as the
dependent variable (see, Figure 1; bottom panel) showed
that the benefits of reduced free-riding for group learning
extended to individual learning outcomes, such that when
students contributed more equally to the group, the

124 Journal of Marketing Education 40(2)

increased learning that took place through the applied
group project translated to a better individual understand-
ing of the course material on which the project was based
(indirect effect [a

1
d

21
b

2
] = 0.002, SE = 0.001, CI [.0003,

.006]). Thus, Hypothesis 3 is generally supported.

Discussion

Free-riding is a pervasive issue in courses that include a sig-
nificant group work component, and although several meth-
ods for reducing free-riding have been examined, little
empirical insight has been provided as to how group assign-
ment may contribute. The present research examines an
instructor-driven method of group assignment, the flocking
method, designed to improve students’ motivation and abil-
ity to contribute to the group. In particular, students are
flocked, or matched, according to their self-reported willing-
ness and availability to contribute, such that unmotivated
(motivated) students are grouped with other unmotivated
(motivated) students with similar schedules. As predicted,
the results reveal that students in flocked (vs. self-selected)
groups not only report less free-riding, they also perform bet-
ter on both group and individual assignments, indicating an
actual reduction in free-riding. This latter finding is notable
as the preponderance of past metrics for gauging the impact
of free-riding in groups have been perceptual (Aggarwal &
O’Brien, 2008; Brooks & Ammons, 2003; Liden et al., 2004;
Muller, 1989; Price et al., 2006; cf. Asmus & James, 2005;
Dommeyer, 2012), which is problematic as meta-analyses
have found little to no correlation between actual and per-
ceived learning measures (Sitzmann et al., 2010; see also,
Bacon, 2011; Clayson, 2009). Thus, in addition to identify-
ing an effective method for reducing free-riding in groups,
this research also addresses the recent call for pedagogical
researchers to attend more closely to actual outcomes (Bacon,
2016).

Additionally, compared with the most commonly exam-
ined methods for reducing free-riding in groups—periodic
peer evaluations and corresponding individualized group
project grades (Strong & Anderson, 1990; D. L. Williams
et al., 1991)—the flocking method of group assignment
reduces resource demands on the instructor and students,
making it as efficient to implement as it is effective. In par-
ticular, once flocked groups are formed using CATME’s
web-based team management system, no further oversight
by the instructor or periodic evaluations by students are
required. One potential drawback of the flocking method
compared with periodic peer evaluations is that it may not
serve as an early warning system for free-riding students.
However, by grouping students with similar motivation lev-
els and schedules together, the flocking method is designed
to reduce many of the temptations and obstacles commonly
associated with free-riding (Hall & Buzwell, 2012), thereby
better equipping students to avoid free-riding altogether.
Nonetheless, it would be interesting to explore whether peri-
odic peer evaluations, which are also facilitated by CATME,
might further reduce free-riding when used in combination
with the flocking method.

Periodic peer evaluations may also provide more nuanced
insight into how the flocking method works, allowing future

Table 4. Mediation Model Coefficients.

Variable Path Β SE p

Single mediator model
Mediator variable model (perceived free-riding)
Group assignment a −0.04 0.01 .006
Dependent variable model (group grade)
Perceived free-riding b −0.08 0.04 .067
Group assignment c′ 0.01 0.01 .012
Dependent variable model (individual grade)
Perceived free-riding b 0.03 0.07 .606
Group assignment c′ 0.02 0.01 .011

Serial mediator model
Mediator variable model (perceived free-riding)
Group assignment a

1
−0.04 0.01 .006

Mediator variable model (group grade)
Perceived free-riding d

21
−0.08 0.04 .067

Group assignment a
2

0.01 0.01 .012
Dependent variable model (individual grade)
Perceived free-riding b

1
0.08 0.06 .201

Group grade b
2

0.61 0.17 .001
Group assignment c′ 0.01 0.01 .095

Note. SE = Standard error.

Figure 1. Mediation models for group and individual learning
outcomes. IE = indirect effect; TE = total effect; DE = direct effect.
mp < .10. *p < .05. **p < .01. ***p < .001.

Harding 125

research to examine, for instance, whether free-riding is
reduced in the early stages of a group project or, rather,
diminishes over time. Along these lines, it would have been
useful to reassess students’ motivation near the end of the
group project to ascertain whether motivation levels
increased for all students throughout the course of the proj-
ect, as anticipated. Because controlling for group-level fac-
tors did not eliminate the main effect of group assignment on
free-riding, it indeed appears that “low motivation” groups
experienced the same motivational (and learning outcome)
benefits as “high motivation” groups. Nonetheless, a post-
measure of motivation would have strengthened the empiri-
cal support for the flocking method.

Although the quasi-experimental methodology used in
this research bolsters confidence in the causal claim that the
flocking method reduces free-riding, which in turn improves
group and individual learning outcomes, the method of group
assignment used each semester (i.e., flocking vs. self-selec-
tion) was not randomly determined. Thus, although efforts
were made to ensure and verify that the treatment and control
conditions were comparable (e.g., both conditions included
fall and spring semesters; other elements of the course were
held constant; no differences in gender, GPA, class standing,
or number of absences were found), it is possible that the
group assignment conditions differed in ways that were nei-
ther anticipated nor detected. An additional limitation of this
research is that the bases by which students were flocked, or
matched (i.e., their stated motivation and availability to con-
tribute to the group), were not manipulated independently.
As a result, the relative impacts of these criteria on perceived
free-riding and student learning cannot be distinguished.
Because it is possible that one criterion may have been more
consequential than the other (or, alternately, that the criteria
only work in tandem to reduce free-riding), future research
might study these criteria independently using a 2 (motiva-
tion: flocked vs. not flocked) × 2 (availability: flocked vs.
not flocked) between-participants design.

The flocking method of group assignment advanced in
this research raises questions about diversity (Milliken &
Martins, 1996), and creativity (Hülsheger, Anderson, &
Salgado, 2009) in groups. These constructs are closely linked
as creativity and other positive group outcomes are more
prevalent in groups that are diversified on task-related vari-
ables such as skill sets (Blowers, 2003; Cummings, 2004;
Katzenbach & Smith, 1993; Metheny & Metheny, 1997;
Michaelsen & Black, 1994; Milliken & Martins, 1996; Price
et al., 2006), and educational backgrounds (Beheshtian-
Ardekani & Mahmood, 1986; Muller, 1989)—likely because
diversity on these variables increases the cognitive diversity
of the group (Hoever, Van Knippenberg, Van Ginkel, &
Barkema, 2012; Kurtzberg, 2005; Wang, Kim, & Lee, 2016).
Therefore, some attention to diversity should be paid in
group assignment. One might argue that the flocking method
runs counter to this premise; however, this need not be the

case. A sophisticated approach to the flocking method might
ensure that group members are (a) similar in terms of their
motivation and ability to contribute to the group, which
serves to safeguard against free-riding, but also (b) diverse in
terms of their task-related skills and backgrounds, which
serves to foster creativity.

Nevertheless, it would be useful to identify criteria by
which flocking (i.e., matching) might have the opposite effect
on free-riding. For instance, there is evidence which suggests
that assigning groups to include students from a mix of educa-
tional backgrounds (Beheshtian-Ardekani & Mahmood, 1986;
Muller, 1989), or with a diversity of skill sets (Blowers, 2003;
Katzenbach & Smith, 1993; Metheny & Metheny, 1997;
Michaelsen & Black, 1994; Price et al., 2006) may reduce
feelings of dispensability (Price et al., 2006), which is a moti-
vational antecedent of free-riding (Harkins & Petty, 1982;
Karau & Williams, 1993; Kerr & Bruun, 1983; Price et al.,
2006; Weldon & Mustari, 1988). Thus, although flocking stu-
dents with similar others may not be universally effective at
reducing free-riding, doing so strategically on variables related
to students’ motivation and ability to contribute to the group
can have a positive effect on student participation and learn-
ing—desirable outcomes that are likely to be augmented on
group projects that are heavily weighted in students’ grades
(Aggarwal & O’Brien, 2008; Bacon et al., 1999).

Acknowledgments

The author wishes to thank the reviewing team, D. Lee Warren and
Joe F. Alexander for their valuable comments.

Declaration of Conflicting Interests

The author declared no potential conflicts of interest with respect to
the research, authorship, and/or publication of this article.

Funding

The author received no financial support for the research, author-
ship, and/or publication of this article.

References

Abernethy, A. M., & Lett, W. L., III. (2005). You are fired! A
method to control and sanction free riding in group assign-
ments. Marketing Education Review, 15, 47-54.

Aggarwal, P., & O’Brien, C. L. (2008). Social loafing on group
projects: Structural antecedents and effect on student satisfac-
tion. Journal of Marketing Education, 30, 255-264.

Albanese, R., & Van Fleet, D. D. (1985). Rational behavior in
groups: The free-riding tendency. Academy of Management
Review, 10, 244-255.

Alnuaimi, O. A., Robert, L. P., & Maruping, L. M. (2010). Team
size, dispersion, and social loafing in technology-supported
teams: A perspective on the theory of moral disengagement.
Journal of Management Information Systems, 27, 203-230.

Asmus, C. L., & James, K. (2005). Nominal group technique, social
loafing, and group creative project quality. Creativity Research
Journal, 17, 349-354.

126 Journal of Marketing Education 40(2)

Bacon, D. R. (2005). The effect of group projects on content-related
learning. Journal of Management Education, 29, 248-267.

Bacon, D. R. (2011). Comparing direct versus indirect measures
of the pedagogical effectiveness of team testing. Journal of
Marketing Education, 33, 348-358.

Bacon, D. R. (2014). The editor’s corner. Journal of Marketing
Education, 36, 3-4.

Bacon, D. R. (2016). Reporting actual and perceived student learn-
ing in education research. Journal of Marketing Education, 38,
3-6.

Bacon, D. R., Stewart, K. A., & Anderson, E. S. (2001). Methods
of assigning players to teams: A review and novel approach.
Simulation & Gaming, 32, 6-17.

Bacon, D. R., Stewart, K. A., & Silver, W. S. (1999). Lessons from
the best and worst student team experiences: How a teacher
can make the difference. Journal of Management Education,
23, 467-488.

Bacon, D. R., Stewart, K. A., & Stewart-Belle, S. (1998). Exploring
predictors of student team project performance. Journal of
Marketing Education, 20, 63-71.

Batra, M. M., Walvoord, B. E., & Krishnan, K. S. (1997). Effective
pedagogy for student-team projects. Journal of Marketing
Education, 19, 26-42.

Beheshtian-Ardekani, M., & Mahmood, M. A. (1986). Development
and validation of a tool for assigning students to groups for
class projects. Decision Sciences, 17, 92-113.

Blowers, P. (2003). Using student skill self-assessments to get
balanced groups for group projects. College Teaching, 51,
106-110.

Börjesson, P. O., Hamidian, A., Kubilinskas, E., Richter, U., Weyns,
K., & Ödling, P. (2006). Free-riding in group work—mecha-
nisms and countermeasures. Seventh Educational Inspiration
Conference. Retrieved from https://www.lth.se/fileadmin/lth/
genombrottet/konferens2006/p_o_b_rjesson_mfl

Brooks, C. M., & Ammons, J. L. (2003). Free riding in group proj-
ects and the effects of timing, frequency, and specificity of cri-
teria in peer assessments. Journal of Education for Business,
78, 268-272.

Chapman, K. J., Meuter, M., Toy, D., & Wright, L. (2006). Can’t we
pick our own groups? The influence of group selection method
on group dynamics and outcomes. Journal of Management
Education, 30, 557-569.

Chapman, K. J., & Van Auken, S. (2001). Creating positive group
project experiences: An examination of the role of the instruc-
tor on students’ perceptions of group projects. Journal of
Marketing Education, 23, 117-127.

Clayson, D. E. (2009). Student evaluations of teaching: Are they
related to what students learn? A meta-analysis and review of
the literature. Journal of Marketing Education, 31, 16-30.

Comer, D. R. (1995). A model of social loafing in real work groups.
Human Relations, 48, 647-667.

Cook, R. W. (1981). An investigation of student peer evaluation on
group project performance. Journal of Marketing Education,
3(1), 50-52.

Cummings, J. N. (2004). Work groups, structural diversity, and
knowledge sharing in a global organization. Management
Science, 50, 352-364.

Dommeyer, C. J. (2012). A new strategy for dealing with social
loafers on the group project: The segment manager method.
Journal of Marketing Education, 34, 113-127.

Druskat, V. U., & Wolff, S. B. (1999). Effects and timing of
developmental peer appraisals in self-managing work groups.
Journal of Applied Psychology, 84, 58.

Freeman, L., & Greenacre, L. (2011). An examination of socially
destructive behaviors in group work. Journal of Marketing
Education, 33, 5-17.

George, J. M. (1992). Extrinsic and intrinsic origins of perceived
social loafing in organizations. Academy of Management
Journal, 35, 191-202.

Hall, D., & Buzwell, S. (2012). The problem of free-riding in group
projects: Looking beyond social loafing as reason for non-
contribution. Active Learning in Higher Education, 14, 37-49.

Harkins, S. G., & Jackson, J. M. (1985). The role of evaluation in
eliminating social loafing. Personality and Social Psychology
Bulletin, 11, 457-465.

Harkins, S. G., & Petty, R. E. (1982). Effects of task difficulty and
task uniqueness on social loafing. Journal of Personality and
Social Psychology, 43, 1214.

Harkins, S. G., & Szymanski, K. (1988). Social loafing and self-
evaluation with an objective standard. Journal of Experimental
Social Psychology, 24, 354-365.

Hayes, A. F. (2013). Introduction to mediation, moderation, and
conditional process analysis: A regression-based approach.
New York, NY: Guilford Press.

Hrivnak, G. A. (2013). CATME smarter teamwork. Academy of
Management Learning & Education, 12, 679-681.

Hoever, I. J., Van Knippenberg, D., Van Ginkel, W. P., & Barkema,
H. G. (2012). Fostering team creativity: Perspective taking
as key to unlocking diversity’s potential. Journal of Applied
Psychology, 97, 982.

Huff, L. C., Cooper, J., & Jones, W. (2002). The development and
consequences of trust in student project groups. Journal of
Marketing Education, 24, 24-34.

Hülsheger, U. R., Anderson, N., & Salgado, J. F. (2009). Team-
level predictors of innovation at work: A comprehensive meta-
analysis spanning three decades of research. Journal of Applied
Psychology, 94, 1128.

Ingham, A. G., Levinger, G., Graves, J., & Peckham, V. (1974).
The Ringelmann effect: Studies of group size and group per-
formance. Journal of Experimental Social Psychology, 10,
371-384.

Jackson, J. M., & Harkins, S. G. (1985). Equity in effort: An expla-
nation of the social loafing effect. Journal of Personality and
Social Psychology, 49, 1199.

Jalajas, D. S., & Sutton, R. I. (1984). Feuds in student groups:
Coping with whiners, martyrs, saboteurs, bullies, and dead-
beats. Journal of Management Education, 9(4), 94-102.

Jones, G. R. (1984). Task visibility, free riding, and shirking:
Explaining the effect of structure and technology on employee
behavior. Academy of Management Review, 9, 684-695.

Karau, S. J., & Hart, J. W. (1998). Group cohesiveness and social
loafing: Effects of a social interaction manipulation on indi-
vidual motivation within groups. Group Dynamics: Theory,
Research, and Practice, 2, 185.

Karau, S. J., & Williams, K. D. (1993). Social loafing: A meta-ana-
lytic review and theoretical integration. Journal of Personality
and Social Psychology, 65, 681-706.

Karau, S. J., & Williams, K. D. (1997). The effects of group cohe-
siveness on social loafing and social compensation. Group
Dynamics: Theory, Research, and Practice, 1, 156-168.

https://www.lth.se/fileadmin/lth/genombrottet/konferens2006/p_o_b_rjesson_mfl

Harding 127

Katzenbach, J. R., & Smith, D. K. (1993). The discipline of teams.
Boston, MA: Harvard Business School Press.

Kench, P. L., Field, N., Agudera, M., & Gill, M. (2009). Peer
assessment of individual contributions to a group project:
Student perceptions. Radiography, 15, 158-165.

Kerr, N. L. (1983). Motivation losses in small groups: A social
dilemma analysis. Journal of Personality and Social
Psychology, 45, 819-828.

Kerr, N. L., & Bruun, S. E. (1981). Ringelmann revisited: Alternative
explanations for the social loafing effect. Personality and
Social Psychology Bulletin, 7, 224-231.

Kerr, N. L., & Bruun, S. E. (1983). Dispensability of member effort
and group motivation losses: Free-rider effects. Journal of
Personality and Social Psychology, 44, 78-94.

Kimber, D. (1996). Collaborative learning in management edu-
cation: Issues, benefits, problems and solutions: A literature
review. Melbourne, Victoria, Australia: Royal Melbourne
Institute of Technology University.

Kurtzberg, T. R. (2005). Feeling creative, being creative: An
empirical study of diversity and creativity in teams. Creativity
Research Journal, 17, 51-65.

Latané, B., Williams, K., & Harkins, S. (1979). Many hands make
light the work: The causes and consequences of social loafing.
Journal of Personality and Social Psychology, 37, 822-832.

Liden, R. C., Wayne, S. J., Jaworski, R. A., & Bennett, N. (2004).
Social loafing: A field investigation. Journal of Management,
30, 285-304.

Loughry, M. L., Ohland, M. W., & Woehr, D. J. (2014). Assessing
teamwork skills for assurance of learning using CATME team
tools. Journal of Marketing Education, 36, 5-19.

Mahenthiran, S., & Rouse, P. J. (2000). The impact of group selec-
tion on student performance and satisfaction. International
Journal of Educational Management, 14(6), 255-265.

Maranto, R., & Gresham, A. (1998). Using “world series shares”
to fight free riding in group projects. PS: Political Science &
Politics, 31, 789-791.

March, J. G. (1954). Group norms and the active minority. American
Sociological Review, 19, 733-741.

McCorkle, D. E., Reardon, J., Alexander, J. F., Kling, N. D., Harris,
R. C., & Iyer, R. V. (1999). Undergraduate marketing students,
group projects, and teamwork: The good, the bad, and the
ugly? Journal of Marketing Education, 21, 106-117.

Mello, J. A. (1993). Improving individual member accountability in
small work group settings. Journal of Management Education,
17, 253-259.

Metheny, D., & Metheny, W. (1997). Enriching technical courses
with learning teams. College Teaching, 45, 32-35.

Michaelsen, L. K., & Black, R. H. (1994). Building learning teams:
The key to harnessing the power of small groups in higher

education. Collaborative Learning: A Sourcebook for Higher
Education, 2, 65-81.

Milliken, F. J., & Martins, L. L. (1996). Searching for common
threads: Understanding the multiple effects of diversity in
organizational groups. Academy of Management Review, 21,
402-433.

Muller, T. E. (1989). Assigning students to groups for class proj-
ects: An exploratory test of two methods. Decision Sciences,
20, 623-634.

Price, K. H., Harrison, D. A., & Gavin, J. H. (2006). Withholding
inputs in team contexts: Member composition, interaction
processes, evaluation structure, and social loafing. Journal of
Applied Psychology, 91, 1375-1384.

Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear
models: Applications and data analysis methods (2nd ed.).
Thousand Oaks, CA: Sage.

Sitzmann, T., Ely, K., Brown, K. G., & Bauer, K. N. (2010). Self-
assessment of knowledge: A cognitive learning or affective
measure? Academy of Management Learning & Education, 9,
169-191.

Slavin, R. E. (1990). Research on cooperative learning: Consensus
and controversy. Educational Leadership, 47(4), 52-54.

Strong, J. T., & Anderson, R. E. (1990). Free-riding in group proj-
ects: Control mechanisms and preliminary data. Journal of
Marketing Education, 12(2), 61-67.

Szymanski, K., & Harkins, S. G. (1987). Social loafing and self-
evaluation with a social standard. Journal of Personality and
Social Psychology, 53, 891-897.

Wang, X. F., Kim, T., & Lee, D. (2016). Cognitive diversity and
team creativity: Effects of team intrinsic motivation and trans-
formational leadership. Journal of Business Research, 69,
3231-3239.

Webb, N. M. (1997). Assessing students in small collaborative
groups. Theory into Practice, 36, 205-213.

Weldon, E., & Mustari, E. L. (1988). Felt dispensability in groups
of coactors: The effects of shared responsibility and explicit
anonymity on cognitive effort. Organizational Behavior and
Human Decision Processes, 41, 330-351.

Williams, D. L., Beard, J. D., & Rymer, J. (1991). Team projects:
Achieving their full potential. Journal of Marketing Education,
13(2), 45-53.

Williams, K. D., Harkins, S. G., & Latané, B. (1981).
Identifiability as a deterrent to social loafing: Two cheering
experiments. Journal of Personality and Social Psychology,
40, 303-311.

Williams, K. D., & Karau, S. J. (1991). Social loafing and social
compensation: The effects of expectations of co-worker per-
formance. Journal of Personality and Social Psychology, 61,
570-581.

Group Dynamics: Theory, Research, and Practice
1998, Vol. 2, No. 3,

185

-191

Group Cohesiveness and Social Loafing: Effects of a Social
Interaction Manipulation on Individual Motivation Within Groups

Steven J. Karau
Southern Illinois University

Jason W. Hart
Virginia Commonwealth University

Previous research has shown that individuals often engage in social loafing, exerting
less effort on collective rather than individual tasks. However, nearly all of the prior
research has examined noncohesive groups. An experiment was designed to test the
hypothesis that social loafing can be reduced or eliminated among cohesive groups.
Fifty-nine dyads discussed a controversial issue on which they agreed strongly (high
cohesiveness), disagreed strongly (low cohesiveness), or disagreed mildly (control),
then worked either coactively or collectively on an idea-generation task. Members of
low-cohesiveness and control groups engaged in social loafing, whereas members of
high-cohesiveness groups worked just as hard collectively as coactively. These findings
are discussed in relation to S. J. Karau and K. D. Williams’s (1993) Collective Effort
Model of individual motivation in groups.

One of the major promises of groups is the
potential to energize and motivate individual
members; however, this potential is not always
realized. In fact, a large and growing body of
research has demonstrated that individuals often
work less hard on collective tasks than they do
on individual tasks, a phenomenon known as
social loafing.

Formally, social loafing refers to the tendency
for individuals to exert less effort when working
collectively (such that individual inputs are
combined into a single group product) than
when working individually or coactively (such
that individuals work in the actual or implied
presence of others, but inputs are not combined).
Social loafing has been established as a robust
effect that generalizes across tasks, as well as
most populations (for a review, see Karau &
Williams, 1993). In addition, a number of
factors have been found to moderate the effect.
For example, social loafing can be reduced or

Steven J. Karau, Department of Management, Southern
Illinois University; Jason W. Hart, Department of Psychol-
ogy, Virginia Commonwealth University.

We thank Mike Markus, Mark Stasson, and Kip Williams
for providing comments on drafts of this article. Portions of
this article were presented at the 1997 convention of the
American Psychological Society in Washington, DC. We
also thank Dave Blaiklock, Craig Hardy, and Julia Woidyla
for their assistance in data collection.

Correspondence concerning this article should be ad-
dressed to Steven J. Karau, Department of Management,
Southern Illinois University, Carbondale, Illinois 62901-
4627. Electronic mail may be sent to skarau@siu.edu.

eliminated by making individual inputs identifi-
able (Williams, Harkins, & Latane, 1981),
enhancing personal involvement with the task
(Brickner, Harkins, & Ostrom, 1986), providing
individual or group comparison standards (Har-
kins & Szymanski, 1988, 1989), or increasing
the uniqueness of individual contributions (Har-
kins & Petty, 1982).

However, almost all of the prior research on
social loafing has examined unacquainted aggre-
gates of strangers, limiting the potential general-
izability of the research. The present research
was designed to fill this gap by manipulating
group cohesiveness and examining its effects on
individuals’ efforts in both coactive and collec-
tive settings. Although cohesiveness is a com-
plex and possibly multidimensional construct
(e.g., Zaccaro & McCoy, 1988) that has been
defined and operationalized in a variety of ways
(Evans & Jarvis, 1980), most treatments have
emphasized members’ attraction to the group or
to its members (Hogg, 1992). Thus, we defined
cohesiveness as the degree to which group
membership was desired and valued by individu-
als and manipulated cohesiveness by having
pairs of previously unacquainted participants
engage in interactions that were designed to
have a significant influence on their attraction to
their coworker.

We framed our hypotheses in terms of the
Collective Effort Model (CEM; Karau &
Williams, 1993). The CEM represents an
expansion of individual-level expectancy-value

185

186 KARAU AND HART

theories of work motivation (e.g., Vroom, 1964)
to the more complex realm of collective tasks,
and an integration of an expectancy-value
framework with key elements of social identity
and self-evaluation theories. The CEM suggests
that individuals will only be willing to work
hard on a collective task to the degree that they
expect their efforts to be useful in leading to
outcomes that they personally value. Thus,
individuals are not likely to work hard when
they view the outcomes of the collective
situation or the group’s performance as unimpor-
tant or meaningless. In addition, even when the
relevant outcomes are highly valued, individuals
are not likely to work hard unless they expect
their efforts to lead to performance that will be
useful in obtaining those outcomes.

Collective

tasks also introduce a number of unique barriers
to individual motivation, because individual
outcomes are affected by factors beyond indi-
vidual performance—such as the performance
of other group members and the possible
diffusion of group outcomes across members.

The CEM also suggests that individuals are
likely to be motivated by collective settings that
provide the potential for self-evaluation (cf.
Breckler & Greenwald, 1986; Goethals &
Darley, 1987; Harkins & Szymanski, 1989).
Cohesive groups or groups with which individu-
als strongly identify are likely to enhance
concern with self-evaluation, especially as
related to group activities and outcomes. Indeed,
theory and research on social identity and on
social comparison processes in groups has
shown that individuals often seek to maintain
and enhance their self-evaluation by identifying
with the successes and positive attributes of
groups and social categories to which they
belong (Abrams & Hogg, 1990; Goethals &
Darley, 1987). Thus, the CEM suggests that
group cohesiveness should reduce or eliminate
social loafing when individual inputs contribute
to favorable group outcomes and when compari-
son with other groups is available.

Almost no research has examined group
cohesiveness and social loafing. In the handful
of studies that are available, cohesiveness has
been examined only indirectly, by comparing
groups that differed in their level of prior
acquaintance. These studies have also produced
mixed results. First, Shirakashi (1985) had
Japanese students shout and clap in groups
comprising either strangers or members of one’s

own sports club. Participants in both the high-
and low-cohesiveness conditions worked equally
hard collectively and coactively (consistent,
perhaps, with a cultural emphasis on collectiv-
ism), thereby leaving the cohesiveness question
unanswered. Second, Hardy and Latane (1988)
had high school cheerleaders perform a shouting
task with another cheerleader from the same or
from a different squad. Although all participants
tended to reduce their collective efforts and
there was no significant interaction between
group cohesiveness and individual versus group
work condition, the social loafing effect only
reached significance in the low-cohesiveness
condition—providing initial, tentative support
for the notion that group cohesiveness might at
least reduce the absolute magnitude of social
loafing. Third, a study of social ostracism by
Williams and Sommer (1997) found that indi-
viduals did not engage in social loafing when
they were included, rather than excluded, from
participation in a group activity before working
on the task. However, participants also did not
engage in social loafing in a control condition
that did not involve the group activity, once
again leaving the question of whether cohesive-
ness can eliminate social loafing unanswered. It
is interesting that when individuals were ostra-
cized by the group, women actually worked
harder collectively than coactively (presumably
to regain their sense of belonging), whereas men
worked equally hard in both conditions—
providing indirect support for the general notion
that one’s relationship with the group has
motivational implications.

Finally, the most direct evidence on group
cohesiveness and social loafing comes from two
studies by Karau and Williams (1997), who
examined groups that differed in friendship
status. In Experiment 1, secretarial students
typed both individually and collectively in
groups comprising either friends or strangers. A
significant interaction emerged such that partici-
pants tended to type faster collectively than
individually when working with friends, but
slower when working with strangers, although
neither simple effect was significant. In Experi-
ment 2, group cohesiveness moderated social
loafing on a brainstorming task such that
individuals loafed when working with strangers
but worked just as hard collectively as coac-
tively when working with close friends.

Taken as a whole, the results of prior research

GROUP COHESIVENESS AND SOCIAL LOAFING 187

provide initial, tentative support for the hypoth-
esis that social loafing can be reduced or
eliminated in cohesive groups. However, these
results are certainly not definitive. All of the
prior research (with the exception of Williams
and Sommer, 1997, which addressed ostracism
rather than cohesiveness) has operationalized
cohesiveness in terms of the degree of prior
acquaintance among group members. Although
friends and strangers (or, similarly, teammates
and competitors) likely differ in their levels of
cohesiveness, the precise nature of those differ-
ences is unclear, and such groups also differ in a
wide variety of attributes other than cohesive-
ness (Duck, 1994; Hogg, 1992). Moreover, most
of these prior studies did not manipulate
cohesion, but instead studied groups that dif-
fered in their existing levels of familiarity,
leaving open the possibility that preexisting
individual or group differences in factors other
than cohesiveness produced the observed ef-
fects. In the present research, we took the vital
step of manipulating group cohesiveness in a
manner that was not confounded with the
diversity of constructs that may accompany
friendship status and degree of prior acquain-
tance. Specifically, we manipulated group cohe-
siveness directly by asking unacquainted dyads
to discuss an issue on which they either strongly
agreed (high cohesiveness), strongly disagreed
(low cohesiveness), or mildly disagreed (con-
trol). After the discussion task, participants
worked either coactively or collectively with
their partner on an idea-generation task. We
predicted that group cohesiveness would reduce
or eliminate social loafing.

Method

Participants and Design

Participants were 118 undergraduate psychol-
ogy students at Virginia Commonwealth Univer-
sity (94 women and 24 men). Dyads were
randomly assigned to one cell of a 3 (cohesive-
ness: high, low, or control) X 2 (work condition:
coactive or collective) between-groups factorial
design. Group composition (mixed-sex groups
or groups of women) was counterbalanced
across cells (men were not assigned to same-sex
groups due to insufficient sample size).

Procedure

On arrival, participants were told that they
would be participating in two separate experi-
ments examining different performance tasks: a
group discussion task and an idea-generation
task. First, participants were asked to complete a
social issues questionnaire that used Likert-type
scales to assess (a) agreement or disagreement
with each of 30 controversial issues ranging
from abortion to gun control, and (b) the
personal importance ascribed to each issue.
When completed, the experimenter took the
questionnaires into another room, presumably to
score them, and selected an issue for discussion.
An issue was selected on which participants
either (a) agreed strongly and felt was very
important (high cohesiveness), (b) disagreed
strongly and felt was very important (low
cohesiveness), or (c) disagreed mildly and felt
was moderate to low in importance (control).1

Pretesting revealed that mere discussion of
issues was not enough to create strong differ-
ences in group cohesiveness, so a manipulation
with multiple operations was developed. Thus,
the experimenter also provided false similarity
feedback and framed the discussion as either
cooperative or competitive. Participants were
told that they had agreed on either 7 issues (low
cohesiveness), 15 issues (control), or 23 issues
(high cohesiveness). The experimenter then

1 For each of the 30 issues on the social issues
questionnaire, the agreement scale ranged from 1 (strongly
disagree) to 7 (strongly agree), and the importance scale
ranged from 1 (very unimportant) to 7 (very important). The
experimenter selected for discussion the single issue
showing the highest possible match, given the group
members’ responses, with me optimal levels of agreement
and importance desired for the appropriate cohesiveness
condition. Thus, die selected item was always rated greater
than 4 on importance by both group members in the high-
and low-cohesiveness conditions, whereas it was always
rated less than 5 on importance by both group members in
the control condition. In the high-cohesiveness condition,
group members’ agreement ratings were always at the same
end of the scale, were always within two points (i.e., the
issue was rated either between 1 and 3 by each group
member, or between 5 and 7 by each group member), and
were within one point for 17 of 20 groups. In the
low-cohesiveness condition, group members’ agreement
ratings were always rated at least 4 points apart (e.g., if one
participant’s rating was 2, the other participant’s rating had
to be either 6 or 7), and were rated at least 5 points apart for
16 of 19 groups. In the control condition, agreement ratings
always ranged between 1 and 6 for each participant, and
were always rated either 2 or 3 points apart.

188 KARAU AND HART

provided discussion instructions, asked partici-
pants to begin, and left the room. The discussion
instructions stressed either (a) trying to work
with one’s “partner” to devise strategies for
convincing outsiders that their shared view was
correct (high cohesiveness), (b) trying to con-
vert one’s opponent to the correct view (low
cohesiveness), or (c) discussing some of the pros
and cons of each side of the issue (control).
After the discussion, participants filled out a
brief questionnaire including manipulation
checks for cohesiveness.

Participants were then thanked for their help
with the first study and the idea-generation task
was described. A divider was placed between
participants that prevented them from seeing
each other. Participants were asked to generate
as many uses as possible for an object (a knife)
in 12 min. They were told that a recent theory
suggested that rapid thinking was highly corre-
lated with intelligence, and that it was therefore
important that they generate as many uses as
possible. They were also told that their scores
would be compared with those of either
individuals (coactive condition) or groups (col-
lective condition) that had participated in similar
studies at other universities. Each use was
written on a separate slip of paper and inserted
into a box between the participants that was
either separated by a divider (coactive) or was
not (collective). During the task, participants
listened to music on headphones to prevent
monitoring of work rates. After the idea-
generation task, participants were asked to fill
out a brief questionnaire, then were debriefed
and dismissed.

Results

We used the group as the unit of analysis for
all analyses. Where appropriate, we used a priori
orthogonal contrasts to make planned compari-
sons (Kirk, 1982). Neither gender nor group
composition had any significant effects, and
both factors were excluded from final analyses.

Manipulation Checks

After the discussion, participants were asked
how much they liked their partner, how willing
they would be to work with their partner again in
the future, and how similar they thought they
were to their partner. These three items were

averaged to produce a cohesiveness index
(a = .85). A main effect of cohesiveness was
found, F(2, 53) = 11.73, p < .001, such that members of high-cohesiveness groups scored higher on the index (M = 5.39 on a 7-point scale) than did members of control groups (M = 4.83), F(l, 53) = 7.41, p < .01, who in turn scored higher than did members of low-cohesiveness groups (A/= 4.09), F(l, 53) = 4.36, p < . 0 5 .

After the idea-generation task, participants
were asked to what extent they thought the
experimenter would be able to tell how well
they had performed individually. Participants in
the coactive condition rated the likelihood that
the experimenter would be able to monitor their
individual scores as higher (M = 80.67) than
did participants in the collective condition
(M = 45.92), F(l, 53) = 40.33,p < .0001.

Performance Data

A 3 X 2 between-groups analysis of variance
was conducted on the performance data. A main
effect of work condition indicated that there was
a significant social loafing effect, F(l , 53) =
8.88, p < .01. Participants worked harder coactively (M = 31.05) than collectively (M = 24.15).

More important, the predicted two-way inter-
action was significant, F{2, 53) = 3.78, p < .03 (cell means and standard deviations are pro- vided in Table 1). Significant social loafing effects were found in both the low-cohesiveness

Table 1
Uses Generated for a Knife as a Function of Group
Cohesiveness and Work Condition

Group cohesiveness

Low
M
SD
n

Control
M
SD
n

High
M
SD
n

Work condition

Coactive

32.

7.33

34.15
15.14
10

26.44
8.49
9

Collective

20.72
6.37
9

22.40
6.83

28.55
8.49

Note, n is based on the number of dyads in each condition.

GROUP COHESIVENESS AND SOCIAL LOAFING 189

condition, F(l , 53) = 7.56, p < .01, and the control condition, F(l , 53) = 8.50, p < .01, such that participants worked harder coactively than collectively. In contrast, members of high-cohesiveness groups worked equally hard collectively and coactively (F< 1).

Discussion

This experiment provides strong support for
the hypothesis that group cohesiveness can
reduce or eliminate social loafing when individu-
als have the opportunity to make useful
contributions that can lead to favorable and
valued group outcomes. Given that the vast
majority of prior studies on social loafing have
examined noncohesive groups, these results
raise important questions as to the generality of
social loafing. Specifically, the present research
raises the intriguing possibility that factors that
serve to increase intragroup attraction, or that
otherwise serve to activate individuals’ concern
for collective outcomes and the reflection those
outcomes have on the self, may be helpful in
reducing or overcoming social loafing.

However, cohesiveness alone may not be
sufficient for maintaining high levels of motiva-
tion. As the CEM suggests, cohesiveness is most
likely to have motivational implications for
individual group members when their efforts are
likely to be useful in leading to group outcomes
that have implications for their own self-
evaluation, or for other consequences that they
personally value. Even though these individual
outcomes are indirect, as they are associated
with collective rather than individual perfor-
mance, they still appear to have significant
effects on motivation. Yet on tasks that are not
valued or have little implication for self-
evaluation—as well as in situations in which
individual inputs have little or no impact on
group outcomes or in which concern for
comparison with other groups is not present—
motivation losses might still occur even in
cohesive groups.

Prior research on group cohesiveness and
social loafing has either measured existing
cohesiveness levels among intact groups, in-
ferred cohesiveness solely from participants’
friendship or teammate status, or used manipula-
tions based solely on the existing relationship
between group members. Because the current
study actually manipulated cohesiveness, ran-

domly assigned participants to conditions, and
held prior acquaintance levels constant across
conditions, it is also the first to demonstrate that
social loafing can be moderated by group
cohesiveness, distinct from any of a number of
other attributes that may covary with friendship
or teammate status. However, it should be
recognized that our cohesiveness manipulation
invoked multiple operations, thereby preventing
us from determining which specific operation
was most crucial to our results. Because
cohesiveness is a complex construct, the next
step may be to determine which specific
elements of cohesiveness have motivating prop-
erties for individuals within groups and when
each element is operative. The manipulation
used in the present study implicates interper-
sonal comfort with other group members and
perceived similarity most directly. Given that
similarity is a potent determinant of attraction
(e.g., Byrne, 1997), our manipulation taps
directly into the attraction-to-group component
of cohesion, but may affect other components
less directly.

The present study is also somewhat unique in
its examination of low-cohesiveness conditions.
Prior research has documented a variety of ways
to reduce or eliminate social loafing, but has not
studied ways to increase it, even though factors
that exacerbate loafing may have equally
important practical consequences (Karau &
Williams, 1995). Our results showed that
members of low-cohesiveness groups engaged
in social loafing, producing a pattern of results
nearly identical to that found for members of
control groups. Thus, the relative decrease in
cohesiveness produced by engaging in a competi-
tively framed interaction with a dissimilar
individual was not enough to significantly
enhance the magnitude of social loafing. Yet if
the manipulation was strengthened or rede-
signed to produce very high levels of dislike and
discomfort among coworkers, we might expect
social loafing to actually increase in magnitude.
Moreover, each factor that reduces cohesiveness
may have its own unique motivational proper-
ties for group members. In this regard, it is
interesting that Williams and Sommer (1997)
found that women who had been ostracized by a
group actually worked harder collectively than
coactively, whereas ostracized men showed a
nonsignificant tendency to engage in social
loafing. Being actively excluded from a group

190 KARAU AND HART

may produce different motivations—such as a
desire to reassert feelings of belonging or, con-
versely, to demonstrate one’s reciprocal rejection of
the group through further disengagement—than
viewing other group members as dissimilar or
engaging in unfavorable interactions.

Our results also suggest that group cohesive-
ness may influence the degree to which
members focus their attention on strategic,
individualistic concerns. The pattern of means
producing the predicted, significant interaction
shows that members of high-cohesiveness groups
worked relatively hard regardless of whether
they were working coactively or collectively,
whereas members of low-cohesiveness and
control groups appear to have worked very hard
coactively and significantly less hard collec-
tively (see Table 1). The CEM suggests that
individuals are unlikely to systematically pro-
cess all information relevant to the situation and
task and are likely to focus on salient features.
Therefore, “some situations may lead individu-
als to respond automatically to a preexisting
effort script, whereas other situations may lead
individuals to strategically increase or decrease
their collective effort” (Karau & Williams,
1993, p. 685). Members of noncohesive groups
may have been more attentive to the strategic
implications of their efforts than were members
of cohesive groups, and may have behaved in a
manner that maximized their individual out-
comes relative to costs. The cooperative versus
competitive aspect of the cohesion manipulation
likely strengthened these tendencies. Specifi-
cally, when working coactively, members of
low-cohesiveness and control groups may have
enhanced their efforts because of the risk of a
potentially negative comparison with their
coworker. However, when working collectively,
they may have reduced their efforts because this
allowed them to devote less effort to the task
without being identified, and the group outcome
had low relevance to their own self-evaluation.
In contrast, members of highly cohesive groups
behaved in a much less individualistic and
strategic fashion, and worked fairly hard both
coactively and collectively.

With regard to self-evaluation processes, it is
intriguing to compare our results with those of
Harkins and Szymanski (1989), who found that
providing a tangible, objective, group-level
performance standard eliminated social loafing

within noncohesive groups. In contrast, we
found that social loafing was eliminated in
cohesive groups merely by telling participants
that group-level comparisons would be made,
without actually providing a comparison stan-
dard. Both their findings and ours suggest that
enhancing individuals’ attention to how a
collective performance may have implications
for their own self-evaluation can eliminate
social loafing. However, this concern for group
and collective outcomes may be harder to
activate in members of noncohesive groups,
who will likely view such outcomes solely in
terms of individual consequences. Therefore,
consistent with the CEM, group-level outcomes
may have special relevance to members of
cohesive groups.

In conclusion, our research demonstrates that
group cohesiveness can eliminate social loafing
when individuals’ efforts are seen as useful and
important to a valued group performance. By
actually manipulating group cohesiveness, we
have taken the vital first step of separating
cohesiveness from mere friendship or teammate
status. Our results, as well as the logic of the
CEM, also provide several tantalizing clues as to
why and when cohesiveness might enhance
individual members’ motivation. Future re-
search could seek to identify the conditions
under which specific aspects of cohesiveness,
such as task commitment (e.g., Zaccaro &
McCoy, 1988) and identification with the group
(e.g., Hogg, 1992), enhance motivation, exam-
ine the effects of discrete aspects of attraction to
the group, or clarify further the motivational
implications of low cohesiveness levels. Such
research could be very useful in developing
cohesiveness interventions that could reduce or
eliminate the potential for motivation losses in
groups.

References

Abrams, D., & Hogg, M. A. (1990). Social identity
theory; Constructive and critical advances. New
York: Springer-Verlag.

Breckler, S. JM & Greenwald, A. G. (1986).
Motivational facets of the self. In R. M. Sorrentino
& E. T. Higgins (Eds.), Handbook of motivation
and cognition (Vol. 1, pp. 145-164). New York:
Guilford Press.

GROUP COHESIVENESS AND SOCIAL LOAFING 191

Brickner, M. A., Harkins, S. G., & Ostrom, T. M.
(1986). Effects of personal involvement: Thought
provoking implications for social loafing. Journal
of Personality and Social Psychology, 51, 763-
769.

Byrne, D. (1997). An overview (and underview) of
research and theory within the attraction paradigm.
Journal of Social and Personal Relationships, 14,
417-431.

Duck, S. (Ed.). (1994). Dynamics of relationships.
Thousand Oaks, CA: Sage.

Evans, N. J., & Jarvis, P. A. (1980). Group cohesion:
A review and re-evaluation. Small Group Behavior,
11, 359-370.

Goethals, G. R., & Darley, J. M. (1987). Social
comparison theory: Self-evaluation and group life.
In B. Mullen & G. R. Goethals (Eds.), Theories of
group behavior (pp. 21-47). New York: Springer-
Verlag.

Hardy, C. J., & Latane”, B. (1988). Social loafing in
cheerleaders: Effects of team membership and
competition. Journal of Sport and Exercise Psychol-
ogy, 10, 109-114.

Harkins, S. G., & Petty, R. E. (1982). Effects of task
difficulty and task uniqueness on social loafing.
Journal of Personality and Social Psychology, 43,
1214-1230.

Harkins, S. G., & Szymanski, K. (1988). Social
loafing and self-evaluation with an objective
standard. Journal of Experimental Social Psychol-
ogy, 24, 354-365.

Harkins, S. G., & Szymanski, K. (1989). Social
loafing and group evaluation. Journal of Personal-
ity and Social Psychology, 56, 934-941.

Hogg, M. A. (1992). The social psychology of group
cohesiveness: From attraction to social identity.
New York: New York University Press.

Karau, S. J., & Williams, K. D. (1993). Social loafing:
Ameta-analytic review and theoretical integration.
Journal of Personality and Social Psychology, 65,
681-706.

Karau, S. J., & Williams, K. D. (1995). Social loafing:
Research findings, implications, and future direc-
tions. Current Directions in Psychological Science,
4, 134-140.

Karau, S. J., & Williams, K. D. (1997). The effects of
group cohesiveness on social loafing and social
compensation. Group Dynamics: Theory, Re –
search, and Practice, 1, 156-168.

Kirk, R. E. (1982). Experimental design (2nd ed.).
Belmont, CA: Wadsworth.

Shirakashi, S. (1985). Social loafing of Japanese
students. Hiroshima Forum for Psychology, 10,
35-40.

Vroom, V. H. (1964). Work and motivation. New
York: Wiley.

Williams, K. D., Harkins, S. G., & Latane, B. (1981).
Identifiability as a deterrent to social loafing: Two
cheering experiments. Journal of Personality and
Social Psychology, 40, 303-311.

Williams, K. D., & Sommer, K. L. (1997). Social
ostracism by coworkers: Does rejection lead to
loafing or compensation? Personality and Social
Psychology Bulletin, 23, 693-706.

Zaccaro, S. J., & McCoy, M. C. (1988). The effects of
task and interpersonal cohesiveness on perfor-
mance of a disjunctive task. Journal of Applied
Social Psychology, 18, 837-851.

Vol.:(0123456789)

1 3

Journal of Business Ethics (2019) 160:713–727
https://doi.org/10.1007/s10551-018-3933-z

ORIGINAL PAPER

Reaping the Fruits of Another’s Labor: The Role of Moral
Meaningfulness, Mindfulness, and Motivation in Social Loafing

Katarina Katja Mihelič1 · Barbara Culiberg1

Received: 30 August 2017 / Accepted: 28 May 2018 / Published online: 5 June 2018
© Springer Science+Business Media B.V., part of Springer Nature 2018

Abstract
Despite the popularity of teams in universities and modern organizations, they are often held back by dishonest actions, social
loafing being one of them. Social loafers hide in the crowd and contribute less to the pooled effort of a team, which leads to
an unfair division of work. While previous studies have mostly delved into the factors related to the task or the group in an
attempt to explain social loafing, this study will instead focus on individual factors. Accordingly, the aim is to investigate the
determinants of social loafing attitudes, namely moral meaningfulness and mindfulness in a university setting. We further
examine the relationship between attitudes and intentions and introduce the moderating role of motivation in the attitude–
intention link. The findings from a sample of 319 business students reveal that both mindfulness and moral meaningfulness
are negatively related to loafing attitudes, while attitudes positively predict social loafing intentions. In addition, we find that
extrinsic motivation strengthens the relationship between social loafing attitudes and intentions.

Keywords Academic misconduct · Moral meaningfulness · Mindfulness · Motivation · Social loafing · University

Introduction

Working in teams has become a common feature of contem‑
porary working lives (Kozlowski and Bell 2013; Schlossberg
2016). It is therefore not surprising that in higher educa‑
tion institutions team/group projects have gained traction
in “preparing students for the real world” (Forehand et al.
2016, p. 62) as they mirror the experiences of the modern
workplace. However, while teamwork is popular in univer‑
sities and businesses alike, it is not immune to individual
dishonest behavior such as social loafing which occurs when
individuals expend less work effort when they form part of
a group than they do when working individually (George
1992; Kidwell and Bennett 1993; Latané et al. 1979). Draw‑
ing on assertions by Bennett and Naumann (2005), social
loafing is problematic for two main reasons: (1) an indi‑
vidual is not delivering what is expected of him/her; and (2)
when observed by others, incidences of slacking off may

decrease motivation and trigger a negative performance
spiral among peers. The negative effects of social loafing
manifest in teams and organizations as diminished cohe‑
siveness, hindered work processes, greater dissatisfaction
with results (Monzani et al. 2014), lower potency (Duffy and
Shaw 2000) and reduced motivation of other members (Price
et al. 2006). This all diminishes a team’s productivity and
efficiency (Comer 1995; Karau and Williams 1995; Bennett
and Naumann 2005). Because it results in adverse conse‑
quences for individuals and societies, it has been dubbed a
“social disease” (Latané et al. 1979, p. 831). In line with this
reasoning, social loafing is a moral issue since it is a choice
that “involves modifying the life plan of another individual
or group of individuals” (Morris 2004, p. 353).

Understanding what drives social loafing is relevant
nowadays for educators teaching ethics in business schools
and managers who encourage and advocate teamwork.
Social loafing can be addressed through ethics educa‑
tion and development at university, in order to potentially
repress this questionable practice early on and discourage
its occurrence in future employment. It has been suggested
that the relationship between ethics instruction and ethi‑
cal perception and behavior is affected by an individual’s
personal characteristics (Wang and Calvano 2015). As is
evident from recent research (May and Luth 2013; Floyd

* Barbara Culiberg
Barbara.culiberg@ef.uni‑lj.si

Katarina Katja Mihelič
Katja.mihelic@ef.uni‑lj.si

1 Faculty of Economics, University of Ljubljana, Kardeljeva
pl. 17, Ljubljana, Slovenia

http://crossmark.crossref.org/dialog/?doi=10.1007/s10551-018-3933-z&domain=pdf

714 K. K. Mihelič, B. Culiberg

1 3

et al. 2013; Wang and Calvano 2015), the diverse effects of
business ethics education have the makings of a viable set
of predictors for explaining ethically questionable situations,
including social loafing. For example, moral meaningfulness
was initially approached as an outcome of business ethics
education (May and Luth 2013), but has the potential to
serve as an antecedent in social loafing decision‑making
since it describes the relative importance of ethics in an
individual’s life. Lampe and Engleman‑Lampe (2012, p. 99)
also emphasized the role of mindfulness, conceptualized as
present‑centered attention and awareness (Brown and Ryan
2003), by stressing “a growing need to educate students
about how the mind works in ways that can help or hinder
making ethical decisions.” Moreover, when Ballantine et al.
(2016) recently demonstrated that students’ ethical decisions
are a result of their learning approaches (which incorporate
their motivation), business ethics educators were alerted to
the complex role of student motivation in academic miscon‑
duct. Motivation, referring to a set of energetic forces that
initiate, direct, and sustain action (Pinder 2008), may not
only serve as a predictor, as studies of academic misconduct
(Davy et al. 2007) suggest, but also as a moderator, as shown
in studies of job‑related intentions and performance (Dysvik
and Kuvaas 2010, 2011). Following these recent research
developments, the objective of this study is to examine (a)
moral meaningfulness and mindfulness as novel antecedents
of social loafing attitudes; and (b) motivation as a modera‑
tor in the social loafing attitudes–intentions relationship. By
introducing these constructs to the domain of social loafing,
this paper strives to link the literature on business ethics
education with ethically questionable behaviors.

Because social loafing takes place in various settings,
such as at work and at university, separate research streams
have developed to examine this issue. Accordingly, organi‑
zational scholars have studied employees’ social loafing in
an effort to better understand what causes a team’s subop‑
timal performance (e.g., Meyer et al. 2016; Kidwell and
Valentine 2009). In addition, considerable attention has
also been devoted to this topic in the higher education
setting (e.g., Jassawalla et al. 2009; Schippers 2014) by
treating it as a form of academic misconduct. Throughout
the years, the efforts of both research streams have sought
to understand the conditions that give rise to social loafing
tendencies. To this end, studies have largely focused on
factors that describe either the task or the team charac‑
teristics and its relationships, i.e., among team members
or with team leaders (e.g., Meyer et al. 2016; Murphy
et al. 2003; Kidwell and Valentine 2009). Considerably
less attention has been devoted to understanding how the
characteristics of an individual team member impact their
decision to withhold effort. Conversely, a recent meta‑
review of ethical decision‑making studies in business
pointed out that individual factors have been extensively

studied in business ethics literature and there is a trend
towards identifying new individual factors which could
work as antecedents or moderators in the decision‑making
process (Lehnert et al. 2015). In this regard, it is important
to consider the findings of Hoon and Tan (2008) where
one individual factor, i.e., conscientiousness, significantly
predicted the occurrence of social loafing, while group
and task characteristics did not. Social loafing research in
higher education has lately further attested to the relevance
of other individual factors (e.g., Schippers 2014), thus
sowing the seeds for further scholarly investigations. In
light of the apparent relevance and potential of novel indi‑
vidual factors and their underrepresentation in previous
social loafing studies, this study will focus on social loaf‑
ing as a type of academic misconduct and complement this
thinking with research from the business ethics research
stream, its rich background and the more recent develop‑
ments therein. Hence, this study adopts an intra‑individual
lens while examining this phenomenon by focusing on the
“bad apples” (Kish‑Gephart et al. 2010), i.e., the individu‑
als, their characteristics, and their decision‑making.

The study aims to make the following unique contribu‑
tions to the literature. First, considering social loafing is a
moral issue, we contribute to the literature on academic mis‑
conduct by proposing two promising constructs with ethical
ties as antecedents to social loafing attitudes. In this way,
we answer a recent call (Cronan et al. 2015) to identify the
determinants of attitudes in studies of academic integrity
violations. We thus introduce mindfulness, which has been
advocated as an important decision‑making determinant in
ethical situations (Ruedy and Schweitzer 2010; Schuh et al.
2017) and also holds the potential to predict social loafing
attitudes. In addition, recent recommendations highlighting
the need to explore how mindfulness influences ethical con‑
duct in concert with other individual‑level characteristics
(Schuh et al. 2017) are followed. Hence, moral meaning‑
fulness is introduced in order to explain social loafing by
looking into the way ethics is considered in students’ daily
lives at university.

Second, considering the important role of motivation
found in previous studies of academic misconduct (e.g.,
Davy et al. 2007; Jordan et al. 2013; Rettinger et al. 2004),
it seems likely that the effects of attitudes on the intentions
of social loafing may differ depending on the level of student
motivation. Therefore, this study contributes to this line of
research and provides a more nuanced understanding of the
attitude–intention link by introducing extrinsic motivation
as a moderator, which takes account of the fact that the fun‑
damental underpinnings of social loafing are motivational
(George 1992; Shepperd 1993). The inclusion of extrinsic
motivation also responds to the appeal by Smith et al. (2001)
to identify other individual variables as moderators of social
loafing effects.

715Reaping the Fruits of Another’s Labor: The Role of Moral Meaningfulness, Mindfulness, and…

1 3

Third, an incremental contribution refers to the position‑
ing of social loafing in academic misconduct research, which
has mostly focused on cheating and plagiarism (Bing et al.
2012; McCabe et al. 2006; Cronan et al. 2015; Lawson 2004;
Ballantine et al. 2016; Fida et al. 2016), while giving consid‑
erably less attention to other practices. Therefore, this study
contributes to a more comprehensive understanding of social
loafing as a dishonest student act. According to research‑
ers, this phenomenon has surprisingly been neglected (Jas‑
sawalla et al. 2009) even though students express concerns
about social loafing and its consequences such as the quality
of the work that is submitted and lower grades (Clark and
Baker 2011).

The remainder of the paper offers an overview of the
social loafing phenomenon and its characteristics, followed
by a review of the empirical studies that investigated loafing
determinants in the educational and organizational settings.
Thereafter, a conceptual model of social loafing intentions
among business students is proposed and argumentation for
the proposed hypotheses is developed. The empirical study’s
research design is then described and the results of hypoth‑
eses testing are provided. The “Discussion” section offers an
interpretation of the findings through the lens of academic
misconduct and business ethics education and outlines prac‑
tical suggestions for reducing the incidence of loafing at uni‑
versity. The paper concludes with limitations and suggests
opportunities for future scholarly exploration of the social
loafing phenomenon.

Theoretical Background

Origins of the Term and Conceptualization

In the early 1880s, a professor of agricultural engineering
Max Ringelmann designed a rope‑pulling task for his stu‑
dents and measured their performance. What he observed
was a worse performance when the number of students pull‑
ing the rope increased. In other terms, when working with
their peers students were more likely to slack off, which dec‑
ades later came to be known as the Ringelmann effect (Krav‑
itz and Martin 1986). It was not until the late 1970s that this
pioneering study was replicated in a series of experiments
demonstrating that students who performed alone clapped
their hands and shouted more intensely than those who did
the same thing as part of a group. The presence of other
people led them to reduce their effort in clapping and cheer‑
ing (Latané et al. 1979; Williams et al. 1981). It was then
that Latané and colleagues coined the term social loafing.1

When social loafing occurs at university, it is a form of
academic misconduct because it creates an unfair academic
advantage for an individual or an unfair academic disadvan‑
tage for other members of the academic community (Uni‑
versity of California). The problem of social loafing is that
students hide in the crowd and contribute less to the pooled
effort of a team, particularly in situations where the potential
for evaluation is low (Hoon and Tan 2008). As a result, pro‑
fessors obtain a false representation of an individual student’s
(i.e., loafer’s) efforts, while other members of the team need
to compensate for the resulting slack so they obtain better
results. After having experienced loafing by team members,
students may form a negative attitude towards teamwork
which may manifest itself in the form of a reluctance to work
in teams even later on in future employment.

Teamwork at university enables interpersonal interactions
while simultaneously fostering adaptability and tolerance.
However, those students who have had negative experiences
with teamwork mostly associate it with “frustration” (Hall
and Buzwell 2012, p. 7). The main source of this frustration
is often the problem of social loafing, and as a result students
complain about the team members’ unequal contributions.
Jassawalla and colleagues found that students perceive loaf‑
ers as those that (a) do less and slack off, (b) do poor quality
work for the team, and (c) engage in distractive and disrup‑
tive behaviors (Jassawalla et al. 2009). Students therefore
turn to lecturers to report how certain team members spend
minimal amounts of time and effort while at the same time
expecting to be rewarded equally, which seems unfair to
those who do their fair share of the work (Hall and Buzwell
2012; Jassawalla et al. 2009; Clark and Baker 2011). Indeed,
a loafer profits from being a member of groups where the
successful completion of a project leads to equal rewards for
all members (Comer 1995). In situations where the individ‑
ual contributions are difficult to evaluate, it is relatively easy
for a loafer to evade his/her job or task (Karau and Williams
1993; Price et al. 2006; Williams et al. 1981).

Determinants of Social Loafing

Social loafing is widespread and can be found in both the
organizational as well as educational setting, across gender
and age and in various occupations and different cultures

1 In day‑to‑day discussions we often hear the term “free riding” when
describing someone slacking off on team assignments. Social loafing
and free riding are similar in that they both entail effort being withheld,
i.e., investing less than full effort when performing a task (Bennett and

Naumann 2005; Kidwell and Bennett 1993). Loafers put in less effort
when working in a group compared to the effort they devote when work‑
ing individually due to reduced identifiability or evaluation (Latané
et al. 1979; Kidwell and Bennett 1993). Free riders enjoy the benefits
of belonging to a group while they are simultaneously unburdened by
the equivalent costs of providing those benefits. The decision to free ride
resides in comparing the benefits of contributing to a group’s goals and
the benefits obtained by free riding (Albanese and Van Fleet 1985).

Footnote 1 (continued)

716 K. K. Mihelič, B. Culiberg

1 3

(Karau and Williams 1993). This makes it of interest to
researchers studying academic and workplace misconduct.
Therefore, this section offers an overview of the main deter‑
minants that have previously been investigated in relation to
social loafing.

In terms of the team and task characteristics associated
with loafing, field studies among employees have established
that group size and a lack of cohesiveness (Liden et al. 2004)
exacerbate loafing, whereas team identification and a posi‑
tive group context (Kidwell and Valentine 2009; Høigaard
et al. 2013) reduce it. A study conducted among lower‑level
employees from an electronics firm and a machinery pro‑
ducing firm demonstrated that higher task interdependence,
lower task visibility and lower distributive justice predicted
social loafing (Liden et al. 2004). In the educational setting,
social loafing was more prevalent in larger groups and was
present in situations where the task/project was greater in
scope and more comprehensive, thus carrying a considerable
weight in the overall grade (Aggarwal and O’Brien 2008).

As far as interpersonal exchanges are concerned, exist‑
ing evidence reveals that a higher quality of leader‑member
exchange decreased social loafing among manufacturing
employees (Murphy et al. 2003). Further, analyzing teams
of blue‑collar workers in German companies, Meyer and col‑
leagues (2016) found that social loafing was most prevalent in
teams with strong homogeneous subgroups within the team
(i.e., strong faultlines). A study involving students working
on an idea‑generation task demonstrated that students with
high and average levels of interpersonal trust engaged in
social loafing (Williams and Karau 1991). Scholars have also
explored one’s perceptions and attributions of peers’ loafing.
Australian students, for example, attributed loafing to peers’
apathy and laziness (Hall and Buzwell 2012). Similarly, Jasa‑
walla et al. (2009) inquired about students’ perceptions of
their peers’ loafing and found that students attributed loaf‑
ers’ slacking off to apathy and their disruptive behavior to
social disconnectedness. The way individuals perceive the
loafing of others also affects their own behavior. In particu‑
lar, empirical studies demonstrate that perceiving that other
members loaf, or even anticipating that other members will
loaf, increases the incidence of loafing (Karau and Williams
1993; Jackson and Harkins 1985). Contrary to these find‑
ings from the workplace, a study involving students found
that perceptions of peers’ loafing reduced one’s own loafing
(Jassawalla et al. 2009), i.e., social compensation.

Next, we turn to the individual variables that drive social
loafing. Existing organizational studies have found that indi‑
vidual job satisfaction has a negative effect on social loafing
among military reserve personnel (Kidwell and Valentine
2009). Similarly, satisfaction with the management of a
company negatively predicted loafing among hotel employ‑
ees in China, turnover intentions contributed to more social
loafing, while affective organizational commitment was not

significantly associated with loafing (Luo et al. 2013). In
an academic setting, students with a low need for cognition
loafed more on a vigilance task (i.e., paying attention to
dots appearing on a computer screen), confirming the need
for cognition as a moderator (Smith et al. 2001). Authors of
two studies involving undergraduate students incorporated
personality characteristics in their research and found that
conscientiousness had a significant negative effect on loaf‑
ing (Hoon and Tan 2008; Ferrari and Pychyl 2012). More
recently, Schippers (2014) revealed that conscientiousness
as well as agreeableness do indeed compensate for loafing
tendencies among Dutch undergraduate students and thereby
affect a team’s overall performance less. Further, Duffy and
Shaw (2000) report that the presence of envy enhances loaf‑
ing, while a student’s felt responsibility contributes to less
slacking (Hoon and Tan 2008). Negative affectivity does
not have a significant influence on social loafing (Murphy
et al. 2003). The range of factors explored in social loafing
studies is wide, but there is a deficit of individual factors
with stronger ethical ties. In the following section, we fill
this void by developing a conceptual model that explains an
individual student’s loafing intention.

Conceptual Model and Hypotheses

This study draws on insights from early theoretical frame‑
works of social loafing (Comer 1995; Kidwell and Bennett
1993) and recent additions to social loafing theory, which
pointed to the explanatory power of individual factors
(Schippers 2014; Jassawalla et al. 2009) by focusing on the
drivers of social loafing through an intra‑individual view.
In the model, the proposed constructs are linked to the atti‑
tude–intention relationship of social loafing which stems
from the basic proposition that attitudes shape intentions,
which in turn lead to behavior (Bentler and Speckart 1979;
Ajzen 1991). Attitudes are conceptualized as one’s disposi‑
tion to respond favorably or unfavorably to social loafing,
while intentions indicate how much of an effort people plan
to exert in order to loaf (Ajzen 2002).

To explain how students form their attitudes towards
social loafing, we propose a pair of constructs that describe
how students approach tasks (i.e., mindfulness) and ethics
(i.e., moral meaningfulness) in their daily lives. While their
handling of tasks helps determine the role of their state of
mind in this situation, the role ethics plays in students’ lives
is important because they are dealing with a moral issue. By
including mindfulness, the psychological state of conscious‑
ness that reflects how present and engrossed students are
when they perform required tasks, student involvement in
team tasks is taken into account. Mindfulness may help indi‑
viduals withdraw from automatic thoughts and unhealthy
behavior (Brown and Ryan 2003). More specifically, being

717Reaping the Fruits of Another’s Labor: The Role of Moral Meaningfulness, Mindfulness, and…

1 3

aware of what is going on during teamwork leads students to
refrain from automatically performing their tasks and to also
pay attention to their peers’ engagement in tasks. We further
focus on the role ethics plays in student life to account for the
fact that social loafing may be viewed as a moral issue (Mor‑
ris 2004) since students may benefit at the expense of others.
Given that social loafing holds negative consequences for
other team members, we include moral meaningfulness to
complement mindfulness as an antecedent of social loafing
attitudes and account for its moral aspects.

Based on existing theorizing on the role of motivation
in teams (Shepperd 1993) and following Comer’s propo‑
sitions (1995), we introduce motivation as a moderator in
the attitude–intention relationship. In this way, we strive to
capture student engagement in their studies as this repre‑
sents the context in which social loafing occurs. Integrating
these three different aspects of social loafing from an indi‑
vidual’s perspective allows for a more comprehensive and
balanced understanding of the social loafing phenomenon.
In what follows, argumentation for each of the hypotheses
is provided.

The first hypothesis relies on previous studies on aca‑
demic misconduct that highlight various moral anteced‑
ents of attitudes such as moral obligation (Beck and Ajzen
1991), idealism (Etter et al. 2006), and moral perspective
(Eisenberg 2004). Considering these findings and the recent
developments in literature on business ethics education (May
et al. 2014), we first introduce an antecedent of social loaf‑
ing attitudes that captures how much meaning an individual
gains from behaving ethically, namely moral meaningfulness
(May et al. 2014). In an educational context, moral meaning‑
fulness reflects the value of ethics in students’ lives and the
extent to which ethical actions are integrated into their iden‑
tities (May and Luth 2013). Hanson et al. (2017) denoted
how relevant the students’ sense of moral right, practical
consequence and moral worth are in their ethical decisions,
particularly in the way students determine moral meaning.
Following May et al.’s (2014) reasoning, high levels of
moral meaningfulness should motivate students to recognize
ethical dilemmas, such as social loafing, and resolve them.
When students encounter and form their attitudes towards
social loafing, they may be influenced by the meaning they
have obtained from behaving ethically at university. By hav‑
ing gained meaning from ethical behavior, students may be
averse to ethically questionable practices like social loafing
since morally oriented students have been shown to hold less
favorable attitudes regarding academic misconduct (Eisen‑
berg 2004). In line with this proposition, we believe that a
higher level of moral meaningfulness leads to more negative
attitudes to social loafing.

Hypothesis 1 Moral meaningfulness is negatively related to
social loafing attitudes.

The second hypothesis concerns the relationship between
mindfulness and attitudes to social loafing. When an individ‑
ual is in a mindful state, they are alert, aware of the present
moment and focus their attention on what is currently going
on. In other words, mindful people have greater external
awareness and are attentive to daily occurrences (Dane and
Brummel 2014). They are also more selfless than mindless
individuals (Hunter and McCormick 2008), exhibit a strong
orientation to caring for others (Good et al. 2016) and dis‑
play fewer Machiavellian tendencies (Krishnakumar and
Robinson 2015). This suggests they are unlikely to delib‑
erately engage in selfish acts such as investing less effort
than peers in a team. Because mindfulness increases other‑
oriented and prosocial behaviors (Good et al. 2016), it can
be speculated that it leads to the formation of more negative
attitudes about withholding effort. In this sense, mindful‑
ness should protect individuals from developing favorable
attitudes towards acts that put others at a disadvantage. For
the reasons outlined above, we hypothesize:

Hypothesis 2 Mindfulness is negatively related to social
loafing attitudes.

A highly recognized relationship in academic miscon‑
duct studies is the link between attitudes and intentions (e.g.,
Beck and Ajzen 1991; Stone et al. 2009; Harding et al. 2007;
Mayhew et al. 2009). It has been suggested that the more
favorable an individual’s attitudes to dishonest behavior
are, the stronger their intention to perform such behavior
(Ajzen 1991). Researchers have well documented that when
students have more positive attitudes towards academic mis‑
conduct, their intentions will be more positive (Stone et al.
2009; Lim and See 2001). Although this relationship has
not been tested for social loafing, it may also apply here.
Students who regard social loafing as something positive
are more likely to engage in social loafing. Therefore, we
propose that:

Hypothesis 3 Social loafing attitudes are positively related
to social loafing intentions.

In addition to the above foci, we sought to further under‑
stand the link between attitudes and intentions. To do so,
we turned to Comer’s theorizing since his model of social
loafing (Comer 1995) speculated that task motivation may
moderate the links between social loafing and the predictive
factors. When someone works on a task and is extrinsically
motivated, they are focused on attaining an outcome that
is separate from performing the task. They chiefly perform
the task because it has an instrumental value for them (Ryan
and Deci 2000). Several studies lend support for the theo‑
rized role of motivation in intentions. For example, research
on ethically questionable consumer behavior has endorsed

718 K. K. Mihelič, B. Culiberg

1 3

a concept similar to motivation, i.e. involvement, which
describes the relevance of an object, situation or action for
an individual (Celsi and Olson 1988) as a moderator in the
link between attitudes and intention (Kos Koklic et al. 2014).
Further, George (1992) previously showed that salespeople’s
intrinsic task involvement was predictive of less social loaf‑
ing. It seems plausible then that when a student needs to
complete a group assignment and is doing so for extrinsic
reasons (e.g., obtaining a grade exclusively in order to pass
a course), their attitudes towards social loafing will translate
into intentions more strongly than for those students with
lower extrinsic motivation levels. We assume that extrinsic
motivation would strengthen the relationship between atti‑
tudes and intentions to engage in loafing.

Hypothesis 4 The relationship between social loafing
attitudes and intentions is moderated by extrinsic motiva‑
tion: The higher the extrinsic motivation, the stronger the
relationship.

Methods

Sample and Procedure

Data were collected from business students in a European
business school holding accreditations from three institu‑
tions: the Association to Advance Collegiate Schools of
Business (AACSB), EFMD Quality Improvement System
(EQUIS) and the Association for MBAs (AMBA). As part
of their courses there, undergraduate students are regularly
required to develop group projects during the semester in
which they may themselves loaf or encounter their peers’
social loafing. In addition, they often participate in ad hoc
team assignments during lectures.

Students were invited to take part in this study at the
beginning of seminar sessions of a core undergraduate
course. They were informed of the study’s purpose by teach‑
ing assistants, who also instructed them about the research
protocol. Then, teaching assistants distributed the paper‑
and‑pencil surveys. Participation in the study was voluntary
and students could withdraw at any point during the data
collection. Anonymity was guaranteed as no identification
information was required.

After initially inspecting the data, 12 questionnaires were
removed from the analysis due to substantial missing values
and/or a central tendency error. Therefore, the final sample is
comprised of 319 usable responses. Altogether, 57% of the
study participants were female and 43% were male, with an
average age of 19.73 years (SD = 1.13).

Measures

Unless otherwise indicated, the survey items used a five‑
point Likert scale with the anchors: 1‑strongly disagree and
5‑strongly agree. Established and previously validated scales
(listed in Table 4 in Appendix) were used to measure the
constructs.

Moral Meaningfulness

Four items were used to assess this construct (May et al.
2014) after being adapted to fit a university context (i.e., the
item “work” was replaced by the term “school”). A sample
item is: “Maintaining high morals/ethics brings me meaning
at school.”

Mindfulness

Trait mindfulness was measured with five items from the
Mindful Attention Awareness Scale (MAAS) (Brown and
Ryan 2003). They form the validated short version scale
used in previous studies (Osman et al. 2016; Smith et al.
2017). All items were reverse‑coded in order to evaluate how
often an individual experiences mindless states. Response
anchors ranged from: 1‑almost never to 5‑almost always.
After recoding, higher values indicate an elevated level of
trait mindfulness. A sample item is: “I do jobs or tasks auto‑
matically without being aware of what I’m doing.”

Attitudes

This construct was measured using a semantic differential
scale (Beck and Ajzen 1991) based on five pairs of adjec‑
tives (e.g., good/bad).

Intentions

Three items were used to measure social loafing inten‑
tions (Chen and Tung 2009). Items were adapted to fit the
social loafing context. A sample item is: “In future group
projects, I may let my peers carry out some of my tasks/
responsibilities.”

Motivation

The Academic Motivation Scale (Vallerand et al. 1989)
was used to measure extrinsic motivation (i.e., four items
for extrinsic motivation—external regulation). Participants
were asked why they study and then offered statements to
respond to. A sample item is: “Because with only a high
school degree I would not find a high‑paying job later on.”

719Reaping the Fruits of Another’s Labor: The Role of Moral Meaningfulness, Mindfulness, and…

1 3

Analytical Procedure

This study used a structural equation modeling procedure to
test the hypotheses proposed in the conceptual model. This
procedure differs from other multivariate procedures in that
it assumes a confirmatory approach to the data analysis and
takes account of the measurement error present in social
science research because the manifest indicators do not per‑
fectly represent their underlying, latent factor. Aside from
this, it considers the strength of the individual relationships
with respect to other paths between factors and evaluates a
model of relationships as a whole (Byrne 2012).

The effects were estimated using the latent moderated
structural equation method, a more recent approach in
structural equation modeling that enables the modeling of
interactions of latent variables that are measured with con‑
tinuous indicators. The analyses were performed with the
M‑Plus program, version 7.4 (Muthén and Muthén 2012).
The structural equation modeling proceeded in the following
steps. We began the analysis by estimating the measurement
model and inspecting the goodness‑of fit indices in order to
evaluate to what extent the model fits the data. Then com‑
posite reliabilities and average variance extracted (AVE) of
the respective scales were calculated, followed by tests to
evaluate the convergent and discriminant validity. Next, we
proceeded by estimating the structural model, which allowed
us to examine the magnitude of the relationships between the
factors as demonstrated by the regression coefficients. As
regards the interaction effect, the chosen approach uses raw
data of the indicators of the moderating factor to estimate
the effect. It does not require a product term to be formed
between the antecedent and moderator in order to create
the latent interaction factor (Klein and Moosbrugger 2000).
Finally, to evaluate the model fit we compared two nested
models, whereby one included the moderating effect while
the other one did not.

Results

This section begins with a presentation of the descriptive
statistics. It then continues by testing the measurement and
structural models and concludes by examining the statistical
significance of the proposed relationships.

Descriptive Statistics

Table 1 provides an overview of descriptive statistics, Cron‑
bach’s alpha, and untabulated correlations between the vari‑
ables. Among the study variables, extrinsic motivation had
the highest mean value (4.20), suggesting that business stu‑
dents find outcomes outside of studies (e.g., a high‑paying
and prestigious job) to be important motivating factors. The
mean values for moral meaningfulness and mindfulness are
3.80 and 3.27, respectively, while the lowest mean values
pertain to social loafing intentions (2.12) and attitudes (1.60),
on average indicating that business students hold relatively
negative views of social loafing.

Measurement Model

To establish the validity and reliability of the scales, we
first performed a series of confirmatory factor analyses,
which are reported in Table 2. We inspected the factor load‑
ings and their significance levels for each underlying factor
independently and dropped one indicator of the mindful‑
ness construct that exhibited a low loading (i.e., 0.293).
The proposed five‑factor solution demonstrated an excel‑
lent fit with the data (χ2 = 239.833 (df = 160; p = 0.000);
CFI = 0.962; TLI = 0.955; RMSEA = 0.040; SRMR = 0.042).
The RMSEA and SRMR were well below the 0.8 threshold,
while CFI and TLI were well above the required 0.9 values
(Kline 2016; Hu and Bentler 1998). The standardized factor
loadings were all significant and ranged between 0.629 and
0.882 for extrinsic motivation, 0.480 and 0.780 for moral
meaningfulness, 0.510 and 0.792 for loafing intention, 0.578
and 0.756 for attitudes, and from 0.533 to 0.681 for mind‑
fulness. This attests to the convergent validity of the indi‑
cators. The proposed measurement model was superior to

Table 1 Descriptive statistics,
Cronbach’s alpha, and
correlations among the study
variables

n = 319; Scales adopted a 5‑point response format with 1 indicating the minimum value and 5 the maxi‑
mum value. Reliabilities are displayed in the third column
**p < 0.01. *p < 0.05

Variable M SD α 1 2 3 4 5

1. Social loafing intention 2.12 0.86 0.66 1
2. Social loafing attitude 1.60 0.69 0.80 0.50** 1
3. Mindfulness 3.27 0.73 0.72 − 0.21** − 0.20** 1
4. Moral meaningfulness 3.80 0.74 0.79 − 0.34** − 0.32** 0.14* 1
5. Extrinsic motivation 4.20 0.79 0.88 − 0.04 − 0.04 − 0.09 0.04 1

720 K. K. Mihelič, B. Culiberg

1 3

the one‑factor model (χ2 = 1590.879 (df = 170; p = 0.000);
CFI = 0.327; TLI = 0.924; RMSEA = 0.165; SRMR = 0.191).
To further examine the reliability of the constructs, we com‑
puted the composite reliability which exceeded the required
value of 0.7 for all constructs (Nunnally and Bernstein
2007; Hair et al. 2010). In addition, the values of AVE for
the constructs were around 0.45 and above (see Table 3),
which is reasonable (Netemeyer et al. 2003). In order to
determine discriminant validity, we followed Fornell and
Larcker’s (1981) approach where we compared the AVE of
each construct with the shared variance (i.e., the squared

correlation) between the constructs (Farrell 2010). Because
the values of AVE were higher than the squared correla‑
tions between the constructs, discriminant validity was
confirmed (see Table 3). We ran an additional confirma‑
tory factor analysis whereby social loafing attitudes and
intentions were collapsed into one factor and the resulting
model fit was poorer than the proposed 5‑factor model at
p = 0.001 (χ2 = 313.727 (df = 164; p = 0.000); CFI = 0.929;
TLI = 0.918; RMSEA = 0.055; SRMR = 0.049; Δ = 73.894),
providing further evidence of discriminant validity.

Table 2 Results of confirmatory
factor analyses

n = 319
CFI comparative fit index, TLI Tucker‑Lewis index, RMSEA root‑mean‑square error of approximation,
SRMR standardized root mean square residual
***p < 0.001 a Harman’s single factor model: all variables combined into a single factor b Social loafing attitudes and social loafing intentions collapsed into a single factor

Model Chi square (χ2) (df, p) Δχ2 CFI TLI RMSEA SRMR

Full measurement
model, five factors

239.833
(df = 160; p = 0.000)

– 0.962 0.955 0.040 0.042

Model A, one factora 1590.879
(df = 170; p = 0.000)

1351.046*** 0.327 0.924 0.165 0.191

Model B, four factorsb 313.727
(df = 164; p = 0.000)

73.894*** 0.929 0.918 0.055 0.049

Table 3 Discriminant validity
matrix

The values of AVE appear diagonally and below the diagonal are the squared correlations between the
constructs

Social loafing
intention

Social loafing
attitude

Mindfulness Moral mean‑
ingfulness

Extrinsic
motiva‑
tion

Social loafing intention 0.45
Social loafing attitude 0.25 0.46
Mindfulness 0.04 0.04 0.42
Moral meaningfulness 0.12 0.10 0.02 0.50
Extrinsic motivation 0.00 0.00 0.01 0.00 0.62

Fig. 1 Results of the hypotheses testing. Note Unstandardized regression coefficients are reported. *Significant at p ≤ 0.05. Arrow indicates sup‑
ported hypothesis

721Reaping the Fruits of Another’s Labor: The Role of Moral Meaningfulness, Mindfulness, and…

1 3

Structural Model and Hypotheses Testing

Next, the relationships proposed in the conceptual model
were tested and the results are summarized in Fig. 1. As
standard model fit indicators are not available for latent inter‑
action models, the model is evaluated based on the follow‑
ing information criteria: Loglikelihood Value = − 7384.381,
free parameters = 68; Akaike Information Criterion
(AIC) = 14904.762. Hypothesis 1 assumed a negative rela‑
tionship between moral meaningfulness and social loafing
attitudes and was supported (γ = − 0.26, p < 0.01). Further, Hypothesis 2 proposed that mindfulness is negatively related to social loafing attitudes. A significant regression coefficient provides support for this hypothesis (γ = − 0.17, p < 0.05). Hypothesis 3 contends that more favorable attitudes to social loafing are associated with greater social loafing intentions (γ = 0.76, p < 0.01), which is supported. Finally, the find‑ ings provide support for the moderating effect of extrinsic motivation, which was proposed in Hypothesis 4 (γ = 0.26, p < 0.01). Extrinsic motivation strengthens the relationship between attitudes and intentions. To evaluate the model fit and further establish the significance of the moderating effect, we compared nested models with and without inter‑ action. The fit indices for the model without the interaction yielded a poorer fit (Loglikelihood Value = − 7386.366, free parameters = 67; Akaike (AIC) = 14906.732). The loglikeli‑ hood difference between the two nested models was signifi‑ cant (3.974) at the 5‑percent level for one degree of freedom. Based on this, we can conclude that the model with interac‑ tion is superior and more parsimonious and can be accepted.

Discussion

Business ethics educators argue that the key to reducing aca‑
demic misconduct is through business ethics instruction (Wang
and Calvano 2015). However, in order to facilitate change, edu‑
cators need to be familiar with the individual characteristics
that influence such behavior. By considering the outcomes of
business ethics education as predictors of academic miscon‑
duct, i.e., social loafing, this study attempts to add to earlier
work by authors who emphasized the role of moral meaning‑
fulness (May and Luth 2013) and mindfulness (Pandey et al.
2018) in pedagogical interventions that shape moral reasoning.
Unlike demographic factors, these factors are potentially open
to manipulation either through a specific business ethics course
or university ethical guidelines and codes of conduct (Jordan
2001). A better understanding of the drivers of social loafing
intentions through an intra‑individual lens may offer the tools
to address individual students’ academic misconduct. More
specifically, while prior research on academic misconduct
concentrated on cheating and plagiarism, this study instead
looked at the dishonest act of social loafing which has become

a significant concern not only for universities and professors
who encourage teamwork and students who are required to
participate in teams as part of their studies, but also for manag‑
ers as the future employers of graduates. Because social loaf‑
ing is a complex phenomenon, this study drew on knowledge
from different research fields and referred to three distinct
factors that shape an individual’s decision to loaf, namely
how involved students are in tasks (i.e., mindfulness), ethics
(i.e., moral meaningfulness) and their studies in general (i.e.,
motivation). The study contributed to the literature on aca‑
demic misconduct and business ethics education by present‑
ing mindfulness and moral meaningfulness as novel predictors
and introducing an alternative role for extrinsic motivation to
explain social loafing.

The current study established the importance of moral
meaningfulness in social loafing (Hypothesis 1) as it found
that students who draw meaning from ethics in their stud‑
ies will hold more negative attitudes towards social loafing.
If students find doing the right thing important, they will
find withholding effort more unacceptable because it brings
unfair advantages to loafers. Existing research on academic
misconduct considers various ethical factors, such as ethi‑
cal orientation (Allmon et al. 2000) and moral philosophies
(Sierra and Hyman 2008). Accordingly, this study extends
their findings with an alternative concept that considers the
meaning of ethics in a particular, i.e., educational, setting.
May et al. (2013) reported that moral meaningfulness is
influenced by business ethics education, and more attention
should thus be devoted to ethical issues in class by encourag‑
ing discussions on ethics and providing ethical guidelines.
In addition, Lau (2010) demonstrated the significant value
of ethics education in improving students’ overall ethical
orientation. Our results suggest that providing students with
opportunities to increase the value of ethics in their lives, to
see it as meaningful and, ultimately, to make ethics a part of
their identities could lead students to constructively resolve
moral issues (May and Luth 2013), i.e., social loafing.

Moreover, the relationship between mindfulness and
social loafing attitudes was negative (Hypothesis 2), con‑
firming that students who are more observant, selfless,
and guided by other‑oriented motives perceive social loaf‑
ing more negatively. This finding extends the reasoning of
Valentine et al. (2010) who approached mindfulness as an
outcome of ethical guidelines in a health care institution,
whereas in this study mindfulness was treated as an anteced‑
ent, thereby establishing its position in business ethics edu‑
cation literature, where the interest in mindfulness is grow‑
ing (Good et al. 2016; Schuh et al. 2017). Extant research
namely indicates that mindfulness not only makes people
more aware of their own behavior, but also of occurrences in
their environment (Brown and Ryan 2003; Dane and Brum‑
mel 2014). In turn, the realization of how hard their peers
intend to work makes students more attentive to the amount

722 K. K. Mihelič, B. Culiberg

1 3

of effort they themselves invest (Williams and Karau 1991).
Therefore, the act of benefiting from other students’ work is
less acceptable in the eyes of a mindful student. In line with
scholars’ suggestions that mindfulness is “a stance of greater
objectivity” (Adair and Fredrickson 2015, p. 198), mindful
students would consider the issues of fairness, equality and
justice when distributing the set tasks among peers. This
corresponds with research indicating that mindfulness leads
to more ethical decision‑making and less cheating (Ruedy
and Schweitzer 2010). While previous empirical work has
established mindfulness as a relevant determinant of proso‑
cial behaviors, showing how it facilitates more positive rela‑
tionships at work (Good et al. 2016; Hunter and McCor‑
mick 2008), our findings indicate that mindfulness can also
contribute to reducing undesirable behaviors which greatly
hinder a team’s effectiveness. By exploring the ‘dark side’
of teamwork, we expand the current understanding of the
beneficial role of mindfulness in shaping more negative atti‑
tudes to social loafing.

Regarding the attitude–intention link (Hypothesis 3), atti‑
tudes to social loafing had a significant positive influence
on loafing intentions. While this result is not surprising, it
provides additional support for this relationship in the grow‑
ing academic misconduct literature (e.g., Stone et al. 2009;
Mayhew et al. 2009; Harding et al. 2007), where the studies
demonstrated the positive influence of attitudes on intentions
to engage in various types of academic misconduct (Stone
et al. 2009) or cheating in particular (Mayhew et al. 2009).
By transferring this link to the social loafing context and
confirming its significance, we demonstrate the relevance of
attitudes in the formation of intentions to loaf, and the need
to consider this relationship by researchers as well as busi‑
ness ethics educators, who are trying to limit and prevent it.

Finally, we found that extrinsic motivation is a significant
moderator between attitudes and intentions (Hypothesis 4).
By corroborating the moderating role of motivation, this
study complements the findings of previous studies where
motivation was positioned as an antecedent of academic mis‑
conduct (Davy et al. 2007) and critical thinking (Howard
et al. 2015). Building on this knowledge, this study advances
the understanding of the role of motivation in academic
misconduct, i.e., social loafing. Jordan (2001) found both
motivation and attitudes were related to cheating behavior.
Furthering this insight, our findings indicate that for students
with a more pronounced extrinsic motivation to study, the
positive link between attitudes and intentions is stronger. In
other terms, students whose main inclination to study stems
from extrinsic factors (e.g., a desire to obtain a high salary
or a better job later on) will be more likely to loaf if they
evaluate it positively. These results suggest that extrinsic
motivation drives students with positive attitudes to be will‑
ing to put even more effort into social loafing.

Implications

It is important to gauge business students’ attitudes not only
to understand their behavior in student teams, but because
students are the employees and managers of tomorrow, who
are likely to transfer their work ethic and habits as well as
experiences they acquire at university, including their way
of working in teams, to the work environment. In times
when higher education institutions and organizations are
increasingly attempting to prevent harmful misconduct and
facilitate the ethical development of their students, our study
offers the following implications for universities and teach‑
ing practices.

First, we concur with researchers who have emphasized
the importance of teaching about ethical challenges at uni‑
versity (Lau 2010; de los Reyes et al. 2017), as we found
support for the role of moral meaningfulness in social loaf‑
ing attitudes, thereby providing pertinent implications for
business ethics education. Students could be educated about
academic misconduct as well as misconduct in business in
order to facilitate their ethical development (Hanson et al.
2017). Universities could integrate ethics into courses across
disciplines and stress the importance of ethical behavior by
presenting real‑life cases of ethical lapses and discussing
with students the ethical implications of different courses of
action. Students could also study novels and—through story‑
telling—grow both professionally and personally (Michael‑
son 2016). Universities could organize keynote speeches on
ethical issues by people who are recognized as role models
in the business community. In this way, students would be
equipped to solve the problems that arise during their studies
and become better prepared to tackle challenges pertaining
to misbehavior at work.

Second, our results indicate that mindfulness facilitates
the formation of more critical attitudes to social loafing.
Therefore, students could be guided towards a more mind‑
ful state in their team tasks, which would make them more
observant of their own and others’ loafing incidences. One
way to encourage students to be more present and pay atten‑
tion to the occurrences in their immediate environment is
to make them acquainted with mindfulness training that,
aside from benefiting teamwork, improves working memory
capacity and reading comprehension (Mrazek et al. 2013).
Acquainting students with the mindfulness concept and inte‑
grating mindfulness exercises into the curriculum could lead
to more transformational learning, as recently demonstrated
in a pedagogical innovation in an MBA leadership course
(Kuechler and Stedham 2017). With regard to teamwork,
students could be encouraged to consciously observe them‑
selves while performing their role and to reflect on a particu‑
lar team task. This could be achieved by using diaries (e.g.,
weekly logs) in which students reflect on their experiences
both in and outside of class (e.g., during meetings with team

723Reaping the Fruits of Another’s Labor: The Role of Moral Meaningfulness, Mindfulness, and…

1 3

members). These short reflective exercises could draw atten‑
tion to the ethical aspects of students’ own behavior as well
as that of their peers. As mindfulness is also related to com‑
mitment (Zivnuska et al. 2016), such practices could have
broader beneficial effects reflected in increased engagement
in class.

Third, the present study found that students who find
social loafing beneficial (i.e., have positive attitudes to
social loafing) are more likely to shirk responsibility (i.e.,
have positive loafing intentions); therefore, educators should
make it clear that social loafing is unacceptable. One way
of doing this is to instruct students both on their duty to
achieve objectives in a team project as well as on the equal
distribution of tasks. The code of ethics and active discus‑
sions in class could point out the negative consequences of
social loafing such as procrastination (Ferrari and Pychyl
2012), lower grades or even the failure to submit projects.
The negative consequences a loafer causes for fellow team
members should also be outlined. Universities could also
rely on the following quote by Confucius (Jia and Jia 2017):
“don’t do unto others what you don’t want others to do unto
you” in presenting this issue to students.

Fourth, as the link between social loafing attitudes and
intentions is stronger for extrinsically motivated students,
educators could pay attention to students’ motivation when
attempting to identify potential loafers. While extrinsic
motivation per se does not have a negative connotation, it is
problematic if, in conjunction with other factors, it results
in individual actions that bring negative consequences for
other people (e.g., peers, co‑workers). In teaching business
ethics, it would be worthwhile to foster discussions about
student motivation and the potential academic misconduct
resulting from it because that would help increase students’
self‑awareness about their own motivation in a particular
course, thereby enabling them to make more informed deci‑
sions regarding course selection (Cole et al. 2004). On a
more general note, given the presence of team projects dur‑
ing studies, students could be frequently reminded of the dos
and don’ts in teamwork and the characteristics of effective
team members as well as those members who take advantage
of others’ efforts while withholding their own. This should
be followed by an outline of possible courses of action to
ensure an equal division of tasks and the successful comple‑
tion of a project.

Limitations and Future Research

While the present study provides a meaningful contribution
to the existing literature on social loafing, it is not without
limitations. The first concerns the cross‑sectional design
which limits the ability to firmly establish causality. Second,
the sample was relatively homogenous (i.e., undergraduate
students from a single business school in one geographic

location). In future research scholars could cross‑validate
the proposed conceptual model on samples of students from
other disciplines and countries. Related to this, it was not our
intention to examine the influence of various demographic
characteristics on social loafing, hence future studies could
focus on other characteristics such as full‑ and part‑time
studies and the duration and type of work experience to
account for the possible differences. Level of study, namely
the differences between undergraduate, graduate and PhD
students could also be examined. This would allow research‑
ers to make more general conclusions about the nature of the
phenomenon in question. Moreover, more attention could
also be devoted to analyzing relationships through a cross‑
cultural lens by evaluating how prone social loafing is to the
influence of individualist versus collectivist values.

In the current study, social loafing intentions were
measured in team projects whereby the act of withholding
effort mainly occurs outside of class. Yet, aside from group
projects, social loafing can also occur during lectures, as
exemplified by students not preparing for class, not reading
the assigned materials, and relying on peers to participate
in class discussions and share knowledge. Future research
could thus also concentrate on understanding what causes
social loafing in class.

This study was conducted in a higher education institu‑
tion and therefore certain constructs, i.e., moral meaningful‑
ness, attitudes, and intentions, were adapted to this setting.
The values of the reliability coefficients for the social loafing
intention scale were very close to the cut‑off values, imply‑
ing that its use in future studies should be reconsidered.
Moreover, the values of AVE suggest that the transfer of
measurement scales from other settings to examine social
loafing may be problematic. This could be solved in future
studies by using alternative scales for the chosen constructs.
Alternatively, future research could replicate the research
design in the workplace setting in order to test whether the
model and its relationships hold there as well. In addition,
because of the deficiencies in social loafing literature, the
study’s approach was focused as it only introduced a narrow
set of individual factors. The interaction between individual
and group‑related factors could also provide a promising
area for investigation.

Conclusion

Engaging in social loafing, a form of academic miscon‑
duct, not only impairs the learning process of the loafer, but
decreases the motivations of his/her peers to participate in
team tasks. If students experience frustration in team assign‑
ments during their studies and end up doing extra work to
compensate for loafers, they might develop unfavorable atti‑
tudes towards collaborating with other people. Once in the

724 K. K. Mihelič, B. Culiberg

1 3

workplace, these previous negative experiences can lead to
an overall reluctance to become involved in teams and to
then favor individual assignments. With ever more work in
companies being performed in teams, knowing more about
what drives social loafing at university is both timely and
important for business ethics educators. The present study
provides a fresh insight into the individual factors triggering
social loafing intentions.

Acknowledgements The authors would like to thank the students who
participated in the study.

Compliance with Ethical Standards

Conflict of interest The authors declare that they have no conflict of
interest.

Appendix

See Table 4.

Table 4 Measurement scales

Variable Composite reli‑
ability

Item

Social loafing intention 0.70 In future group projects, I may let my peers carry out some of my tasks/responsibilities
If I had the opportunity, I would let my peers carry out some of my study assignments for me
I would never let my peers do some of my study assignments for me

Social loafing attitude 0.81 I find social loafing…
Good–bad
Pleasant–unpleasant
Foolish–wise
Useful–useless
Unattractive–attractive

Mindfulness 0.73 It seems I am “running on automatic” without much awareness
I run through activities without being really attentive to them
I get so focused on the goal I want to achieve that I lose touch with what I am doing right

now to get there—(dropped item)
I do jobs or tasks automatically, without being aware of what I’m doing
I find myself doing things without paying attention

Moral meaningfulness 0.80 Maintaining high morals/ethics brings me meaning at school
I find that doing the “right thing” at school is personally meaningful for me
Doing the ethical thing gives me purpose at school
Behaving consistently with my morals is quite important to me

Extrinsic motivation 0.89 Why do you study?
Because with only a high‑school degree I would not find a high‑paying job later on
In order to obtain a more prestigious job later on
Because I want to have “the good life” later on
In order to have a better salary later on

725Reaping the Fruits of Another’s Labor: The Role of Moral Meaningfulness, Mindfulness, and…

1 3

References

Adair, K. C., & Fredrickson, B. L. (2015). Be open: Mindfulness pre‑
dicts reduced motivated perception. Personality and Individual
Differences, 83(1), 198–201.

Aggarwal, P., & O’Brien, C. L. (2008). Social loafing on group pro‑
jects: Structural antecedents and effect on student satisfaction.
Journal of Marketing Education, 30(3), 255–264.

Ajzen, I. (1991). The theory of planned behavior. Organizational
behavior and human decision processes, 50(2), 179–211.

Ajzen, I. (2002). Perceived behavioral control, self‑efficacy, locus of
control, and the theory of planned behavior. Journal of Applied
Social Psychology, 32(4), 665–683.

Albanese, R., & Van Fleet, D. D. (1985). Rational behavior in
groups: The free‑riding tendency. Academy of Management
Review, 10(2), 244–255.

Allmon, D. E., Page, D., & Roberts, R. (2000). Determinants of
perceptions of cheating: Ethical orientation, personality and
demographics. Journal of Business Ethics, 23(4), 411–422.

Ballantine, J. A., Guo, X., & Larres, P. (2016). Can future managers
and business executives be influenced to behave more ethi‑
cally in the workplace? The impact of approaches to learning
on business students’ cheating behavior. Journal of Business
Ethics, 1–14.

Beck, L., & Ajzen, I. (1991). Predicting dishonest actions using the
theory of planned behavior. Journal of Research in Personal-
ity, 25(3), 285–301.

Bennett, N., & Naumann, S. E. (2005). Understanding and prevent‑
ing shirking, job neglect, social loafing, and free riding. In R.
E. Kidwell Jr. & C. L. Martin (Eds.), Managing organizational
deviance (pp. 113–130). Thousand Oaks, CA: Sage Publications.

Bentler, P. M., & Speckart, G. (1979). Models of attitude–behavior
relations. Psychological Review, 86(5), 452–464.

Bing, M. N., Davison, H. K., Vitell, S. J., Ammeter, A. P., Garner, B.
L., & Novicevic, M. M. (2012). An experimental investigation
of an interactive model of academic cheating among business
school students. Academy of Management Learning & Educa-
tion, 11(1), 28–48.

Brown, K. W., & Ryan, R. M. (2003). The benefits of being present:
Mindfulness and its role in psychological well‑being. Journal
of Personality and Social Psychology, 84(4), 822–848.

Byrne, B. M. (2012). Structural equation modeling with Mplus:
Basic concepts, applications, and programming. Abingdon:
Routledge.

Celsi, R. L., & Olson, J. C. (1988). The role of involvement in attention
and comprehension processes. Journal of Consumer Research,
15(2), 210–224.

Chen, M.‑F., & Tung, P.‑J. (2009). The moderating effect of perceived
lack of facilities on consumers’ recycling intentions. Environ-
ment and Behavior, 42(6), 824–844.

Clark, J., & Baker, T. (2011). It‘s not fair: Cultural attitudes to social
loafing in ethnically diverse groups. Intercultural Communica-
tion Studies, XX(1), 124–140.

Cole, M. S., Feild, H. S., & Harris, S. G. (2004). Student learning
motivation and psychological hardiness: Interactive effects on
students’ reactions to a management class. Academy of Manage-
ment Learning & Education, 3(1), 64–85.

Comer, D. R. (1995). A model of social loafing in real work groups.
Human Relations, 48(6), 647–667.

Cronan, T. P., Mullins, J. K., & Douglas, D. E. (2015). Further under‑
standing factors that explain freshman business students’ aca‑
demic integrity intention and behavior: Plagiarism and sharing
homework. Journal of Business Ethics, 1–24.

Dane, E., & Brummel, B. J. (2014). Examining workplace mindful‑
ness and its relations to job performance and turnover intention.
Human Relations, 67(1), 105–128.

Davy, J. A., Kincaid, J. F., Smith, K. J., & Trawick, M. A. (2007). An
examination of the role of attitudinal characteristics and moti‑
vation on the cheating behavior of business students. Ethics &
Behavior, 17(3), 281–302.

de los Reyes, G., Kim, T. W., & Weaver, G. R. (2017). Teaching eth‑
ics in business schools: A conversation on disciplinary differ‑
ences, academic provincialism, and the case for integrated peda‑
gogy. Academy of Management Learning & Education, 16(2),
314–336.

Duffy, M. K., & Shaw, J. D. (2000). The Salieri syndrome conse‑
quences of envy in groups. Small Group Research, 31(1), 3–23.

Dysvik, A., & Kuvaas, B. (2010). Exploring the relative and combined
influence of mastery‑approach goals and work intrinsic motiva‑
tion on employee turnover intention. Personnel Review, 39(5),
622–638.

Dysvik, A., & Kuvaas, B. (2011). Intrinsic motivation as a moderator
on the relationship between perceived job autonomy and work
performance. European Journal of Work and Organizational
Psychology, 20(3), 367–387.

Eisenberg, J. (2004). To cheat or not to cheat: Effects of moral perspec‑
tive and situational variables on students’ attitudes. Journal of
Moral Education, 33(2), 163–178.

Etter, S., Cramer, J. J., & Finn, S. (2006). Origins of academic dishon‑
esty: Ethical orientations and personality factors associated with
attitudes about cheating with information technology. Journal of
Research on Technology in Education, 39(2), 133–155.

Farrell, A. M. (2010). Insufficient discriminant validity: A comment
on Bove, Pervan, Beatty. and Shiu (2009). Journal of Business
Research, 63(3), 324–327.

Ferrari, J. R., & Pychyl, T. A. (2012). “If I wait, my partner will do
it”: The role of conscientiousness as a mediator in the relation
of academic procrastination and perceived social loafing. North
American Journal of Psychology, 14(1), 13–24.

Fida, R., Tramontano, C., Paciello, M., Ghezzi, V., & Barbaranelli,
C. (2016). Understanding the interplay among regulatory self‑
efficacy, moral disengagement, and academic cheating behav‑
iour during vocational education: A three‑wave study. Journal
of Business Ethics 1–16.

Floyd, L. A., Xu, F., Atkins, R., & Caldwell, C. (2013). Ethical out‑
comes and business ethics: Toward improving business ethics
education. Journal of Business Ethics, 117(4), 753–776.

Forehand, J. W., Leigh, K. H., Farrell, R. G., & Spurlock, A. Y.
(2016). Social dynamics in group work. Teaching and Learning
in Nursing, 11(2), 62–66.

Fornell, C., & Larcker, D. F. (1981). Structural equation models with
unobservable variables and measurement error: Algebra and
statistics. Journal of Marketing Research, 382–388.

George, J. M. (1992). Extrinsic and intrinsic origins of perceived
social loafing in organizations. Academy of Management Jour-
nal, 35(1), 191–202.

Good, D. J., Lyddy, C. J., Glomb, T. M., Bono, J. E., Brown, K.
W., Duffy, M. K., et al. (2016). Contemplating mindfulness at
work: An integrative review. Journal of Management, 42(4),
114–142.

Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R.
L. (2010). Multivariate data analysis (Vol. 7). Upper Saddle
River, NJ: Prentice Hall.

Hall, D., & Buzwell, S. (2012). The problem of free‑riding in group
projects: Looking beyond social loafing as reason for non‑con‑
tribution. Active Learning in Higher Education, 14(1), 37–49.

Hanson, W. R., Moore, J. R., Bachleda, C., Canterbury, A., Franco,
C., Marion, A., et al. (2017). Theory of moral development of
business students: Case studies in Brazil, North America, and

726 K. K. Mihelič, B. Culiberg

1 3

Morocco. Academy of Management Learning & Education,
16(3), 393–414.

Harding, T. S., Mayhew, M. J., Finelli, C. J., & Carpenter, D. D.
(2007). The theory of planned behavior as a model of academic
dishonesty in engineering and humanities undergraduates. Eth-
ics & Behavior, 17(3), 255–279.

Høigaard, R., Boen, F., De Cuyper, B., & Peters, D. M. (2013).
Team identification reduces social loafing and promotes social
laboring in cycling. International Journal of Applied Sports
Science, 25(1), 30–40.

Hoon, H., & Tan, T. M. L. (2008). Organizational citizenship behav‑
ior and social loafing: The role of personality, motives, and
contextual factors. The Journal of Psychology, 142(1), 89–108.

Howard, L. W., Tang, T. L.‑P., & Austin, M. J. (2015). Teaching criti‑
cal thinking skills: Ability, motivation, intervention, and the
Pygmalion effect. Journal of Business Ethics, 128(1), 133–147.

Hu, L., & Bentler, P. M. (1998). Fit indices in covariance structure
modeling: Sensitivity to underparameterized model misspeci‑
fication. Psychological Methods, 3(4), 424–453.

Hunter, J., & McCormick, D. W. (2008). Mindfulness in the work‑
place: An exploratory study. In SE Newell (Facilitator), Weick-
ian Ideas. Symposium conducted at the annual meeting of the
Academy of Management, Anaheim, CA.

Jackson, J. M., & Harkins, S. G. (1985). Equity in effort: An expla‑
nation of the social loafing effect. Journal of Personality and
Social Psychology, 49(5), 1199–1206.

Jassawalla, A., Sashittal, H., & Sashittal, A. (2009). Students’ per‑
ceptions of social loafing: Its antecedents and consequences in
undergraduate business classroom teams. Academy of Manage-
ment Learning & Education, 8(1), 42–54.

Jia, Y., & Jia, X. L. (2017). A dialogic approach to intercultural
conflict management and harmonious relationships. In X. Dai
& G. M. Chen (Eds.), Conflict management and intercultural
communication. The art of intercultural harmony. Oxon:
Routledge.

Jordan, A. E. (2001). College student cheating: The role of motivation,
perceived norms, attitudes, and knowledge of institutional policy.
Ethics & Behavior, 11(3), 233–247.

Jordan, J., Brown, M. E., Treviño, L. K., & Finkelstein, S. (2013).
Someone to look up to executive–follower ethical reasoning and
perceptions of ethical leadership. Journal of Management, 39(3),
660–683.

Karau, S. J., & Williams, K. D. (1993). Social loafing: A meta‑analytic
review and theoretical integration. Journal of personality and
social psychology, 65(4), 681–706.

Karau, S. J., & Williams, K. D. (1995). Social loafing: Research find‑
ings, implications, and future directions. Current Directions in
Psychological Science, 4(5), 134–140.

Kidwell, R. E., & Bennett, N. (1993). Employee propensity to withhold
effort: A conceptual model to intersect three avenues of research.
Academy of Management Review, 18(3), 429–456.

Kidwell, R. E., & Valentine, S. R. (2009). Positive group context, work
attitudes, and organizational misbehavior: The case of withhold‑
ing job effort. Journal of Business Ethics, 86(1), 15–28.

Kish‑Gephart, J. J., Harrison, D. A., & Treviño, L. K. (2010). Bad
apples, bad cases, and bad barrels: Meta‑analytic evidence about
sources of unethical decisions at work. Journal of Applied Psy-
chology, 95(1), 1–31.

Klein, A., & Moosbrugger, H. (2000). Maximum likelihood estima‑
tion of latent interaction effects with the LMS method. Psycho-
metrika, 65(4), 457–474.

Kline, R. B. (2016). Principles and practice of structural equation
modeling (4th edn.). New York: The Guilford Press.

Kos Koklic, M., Vida, I., Bajde, D., & Culiberg, B. (2014). The study
of perceived adverse effects of digital piracy and involvement:

Insights from adult computer users. Behaviour & Information
Technology, 33(3), 225–236.

Kozlowski, S. W. J., & Bell, B. S. (2013). Work groups and teams in
organizations: Review update. In N. Schmitt & S. Highhouse
(Eds.), Handbook of psychology. Industrial and organizational
psychologoy (Vol. 12, pp. 412–469). Hoboken: Wiley.

Kravitz, D. A., & Martin, B. (1986). Ringelmann rediscovered: The
original article. Journal of Personality and Social Psychology,
50(5), 936–941.

Krishnakumar, S., & Robinson, M. D. (2015). Maintaining an even
keel: An affect‑mediated model of mindfulness and hostile work
behavior. Emotion, 15(5), 579–589.

Kuechler, W., & Stedham, Y. (2017). Management Education and
Transformational Learning: The Integration of Mindfulness in
an MBA Course. Journal of Management Education, 1–26.

Lampe, M., & Engleman‑Lampe, C. (2012). Mindfulness‑based busi‑
ness ethics education. Academy of Educational Leadership Jour-
nal, 16(3), 99–130.

Latané, B., Williams, K., & Harkins, S. (1979). Many hands make light
the work: The causes and consequences of social loafing. Journal
of Personality and Social Psychology, 37(6), 822–832.

Lau, C. L. (2010). A step forward: Ethics education matters! Journal
of Business Ethics, 92(4), 565–584.

Lawson, R. A. (2004). Is classroom cheating related to business stu‑
dents’ propensity to cheat in the” real world”? Journal of Busi-
ness Ethics, 49(2), 189–199.

Lehnert, K., Park, Y., & Singh, N. (2015). Research note and review
of the empirical ethical decision‑making literature: Boundary
conditions and extensions. Journal of Business Ethics, 129(1),
195–219.

Liden, R. C., Wayne, S. J., Jaworski, R. A., & Bennett, N. (2004).
Social loafing: A field investigation. Journal of Management,
30(2), 285–304.

Lim, V. K., & See, S. K. (2001). Attitudes toward, and intentions to
report, academic cheating among students in Singapore. Ethics
& Behavior, 11(3), 261–274.

Luo, Z., Qu, H., & Marnburg, E. (2013). Justice perceptions and drives
of hotel employee social loafing behavior. International Journal
of Hospitality Management, 33, 456–464.

May, D. R., & Luth, M. T. (2013). The effectiveness of ethics educa‑
tion: A quasi‑experimental field study. Science and Engineering
Ethics, 19(2), 545–568.

May, D. R., Luth, M. T., & Schwoerer, C. E. (2014). The influence of
business ethics education on moral efficacy, moral meaningful‑
ness, and moral courage: A quasi‑experimental study. Journal of
Business Ethics, 124(1), 67–80.

Mayhew, M. J., Hubbard, S. M., Finelli, C. J., Harding, T. S., & Car‑
penter, D. D. (2009). Using structural equation modeling to vali‑
date the theory of planned behavior as a model for predicting stu‑
dent cheating. The Review of Higher Education, 32(4), 441–468.

McCabe, D. L., Butterfield, K. D., & Treviño, L. K. (2006). Academic
dishonesty in graduate business programs: Prevalence, causes,
and proposed action. Academy of Management Learning & Edu-
cation, 5(3), 294–305.

Meyer, B., Schermuly, C. C., & Kauffeld, S. (2016). That’s not my
place: The interacting effects of faultlines, subgroup size, and
social competence on social loafing behaviour in work groups.
European Journal of Work and Organizational Psychology,
25(1), 31–49.

Michaelson, C. (2016). A novel approach to business ethics education:
Exploring how to live and work in the 21st century. Academy of
Management Learning & Education, 15(3), 588–606.

Monzani, L., Ripoll, P., Peiró, J. M., & Van Dick, R. (2014). Loafing
in the digital age: The role of computer mediated communica‑
tion in the relation between perceived loafing and group affective
outcomes. Computers in Human Behavior, 33, 279–285.

727Reaping the Fruits of Another’s Labor: The Role of Moral Meaningfulness, Mindfulness, and…

1 3

Morris, D. (2004). Defining a moral problem in business ethics. Jour-
nal of Business Ethics, 49(4), 347–357.

Mrazek, M. D., Franklin, M. S., Phillips, D. T., Baird, B., & Schooler,
J. W. (2013). Mindfulness training improves working memory
capacity and GRE performance while reducing mind wandering.
Psychological Science, 24(5), 776–781.

Murphy, S. M., Wayne, S. J., Liden, R. C., & Erdogan, B. (2003).
Understanding social loafing: The role of justice perceptions and
exchange relationships. Human Relations, 56(1), 61–84.

Muthén, L. K., & Muthén, B. O. (2012). Mplus User’s Guide (7th edn.).
Los Angeles, CA: Muthén & Muthén.

Netemeyer, R. G., Bearden, W. O., & Sharma, S. (2003). Scaling pro-
cedures: Issues and applications. Thousand Oaks, CA: Sage
Publications.

Nunnally, J. C., & Bernstein, I. H. (2007). Psychometric theory
(3rd edn.). New York: McGraw Hill.

Osman, A., Lamis, D. A., Bagge, C. L., Freedenthal, S., & Barnes,
S. M. (2016). The mindful attention awareness scale: Further
examination of dimensionality, reliability, and concurrent valid‑
ity estimates. Journal of Personality Assessment, 98(2), 189–199.

Pandey, A., Chandwani, R., & Navare, A. (2018). How can mindfulness
enhance moral reasoning? An examination using business school
students. Business Ethics: A European Review, 27(1), 56–71.

Pinder, C. C. (2008). Work motivation in organizational behavior (2nd
edn.). New York: PsychologyPress.

Price, K. H., Harrison, D. A., & Gavin, J. H. (2006). Withholding
inputs in team contexts: Member composition, interaction
processes, evaluation structure, and social loafing. Journal of
Applied Psychology, 91(6), 1375–1384.

Rettinger, D. A., Jordan, A. E., & Peschiera, F. (2004). Evaluating the
motivation of other students to cheat: A vignette experiment.
Research in Higher Education, 45(8), 873–890.

Ruedy, N. E., & Schweitzer, M. E. (2010). In the moment: The effect
of mindfulness on ethical decision making. Journal of Business
Ethics, 95, 73–87.

Ryan, R. M., & Deci, E. L. (2000). Self‑determination theory and the
facilitation of intrinsic motivation, social development, and well‑
being. American Psychologist, 55(1), 68–78.

Schippers, M. C. (2014). Social loafing tendencies and team perfor‑
mance: The compensating effect of agreeableness and consci‑
entiousness. Academy of Management Learning & Education,
13(1), 62–81.

Schlossberg, M. (2016). Google experiment reveals the single most
important quality for teamwork. Business insider. Retrieved from
http://www.busin essin sider .com/googl e‑revea ls‑how‑to‑have‑
the‑perfe ct‑team‑2016‑2.

Schuh, S. C., Zheng, M. X., Xin, K. R., & Fernandez, J. A. (2017). The
interpersonal benefits of leader mindfulness: A serial mediation

model linking leader mindfulness, leader procedural justice
enactment, and employee exhaustion and performance. Journal
of Business Ethics, 1–19.

Shepperd, J. A. (1993). Productivity loss in performance groups: A
motivation analysis. Psychological Bulletin, 113(1), 67–81.

Sierra, J. J., & Hyman, M. R. (2008). Ethical antecedents of cheating
intentions: Evidence of mediation. Journal of Academic Ethics,
6(1), 51–66.

Smith, B. N., Kerr, N. A., Markus, M. J., & Stasson, M. F. (2001).
Individual differences in social loafing: Need for cognition as a
motivator in collective performance. Group Dynamics: Theory,
Research, and Practice, 5(2), 150–158.

Smith, O. R. F., Melkevik, O., Samdal, O., Larsen, T. M., & Haug,
E. (2017). Psychometric properties of the five‑item version of
the Mindful Awareness Attention Scale (MAAS) in Norwegian
adolescents. Scandinavian Journal of Public Health, 45(4),
373–380.

Stone, T. H., Jawahar, I., & Kisamore, J. L. (2009). Using the theory of
planned behavior and cheating justifications to predict academic
misconduct. Career Development International, 14(3), 221–241.

University of California, B. Definitions & Examples of Academic Mis‑
conduct. Retrieved May 2017, from http://sa.berke ley.edu/condu
ct/integ rity/defin ition .

Valentine, S., Godkin, L., & Varca, P. E. (2010). Role conflict, mindful‑
ness, and organizational ethics in an education‑based healthcare
institution. Journal of Business Ethics, 94(3), 455–469.

Vallerand, R. J., Blais, M. R., Brière, N. M., & Pelletier, L. G. (1989).
Construction et validation de l’Échelle de Motivation en Édu‑
cation (EME)/Construction and validation of the Motivation
toward Education Scale. Canadian Journal of Behavioural Sci-
ence/Revue canadienne des sciences du comportement, 21(3),
323–349.

Wang, L. C., & Calvano, L. (2015). Is business ethics education effec‑
tive? An analysis of gender, personal ethical perspectives, and
moral judgment. Journal of Business Ethics, 126(4), 591–602.

Williams, K. D., Harkins, S. G., & Latané, B. (1981). Identifiability as
a deterrant to social loafing: Two cheering experiments. Journal
of Personality and Social Psychology, 40(2), 303–311.

Williams, K. D., & Karau, S. J. (1991). Social loafing and social com‑
pensation: The effects of expectations of co‑worker performance.
Journal of Personality and Social Psychology, 61(4), 570–581.

Zivnuska, S., Kacmar, K. M., Ferguson, M., & Carlson, D. S. (2016).
Mindfulness at work: Resource accumulation, well‑being, and
attitudes. Career Development International, 21(2), 106–124.

http://www.businessinsider.com/google-reveals-how-to-have-the-perfect-team-2016-2

http://sa.berkeley.edu/conduct/integrity/definition

Reproduced with permission of copyright owner. Further reproduction
prohibited without permission.

Reaping the Fruits of Another’s Labor: The Role of Moral Meaningfulness, Mindfulness, and Motivation in Social Loafing

Abstract

Introduction

Theoretical Background

Origins of the Term and Conceptualization

Determinants of Social Loafing

Conceptual Model and Hypotheses

Methods

Sample and Procedure

Measures

Moral Meaningfulness

Mindfulness

Attitudes

Intentions

Motivation

Analytical Procedure

Results

Descriptive Statistics

Measurement Model

Structural Model and Hypotheses Testing

Discussion

Implications

Limitations and Future Research

Conclusion

Acknowledgements

References

Articles to Use for Paper I: For your first paper, you MUST cite to three of the following articles. You can cite four of them if you like, but you must find a fifth article to cite using PsycInfo. These are listed in no particular order, but make sure to read the abstracts to see how well they will fit in with your own paper. Some might be more relevant to your study than others.

Collective Effort Model and Group Cohesion (Karau)



Morality of Social Loafing (Mihelic)



Free Ride Flocking (Harding)



Group Size and Reward (Mefoh)

 

Motive Disposition (Hilkenmeier)

 

Partner Productivity and Social Loafing (Hamamoto)



Performance Knowledge (Lount)

 

Social Loafing in the Classroom (North)



Team Learning and Social Loafing (Gabelica)

Read Aloud Assignment #3

For this “Read Aloud Assignment”, I want you to complete four steps.

Question 1: Submit your one-page document by uploading the paper file to Canvas.

Questions For Your Listener										Rating (1 to 7)
1. The introductory paragraph provides a clear description of the purpose and topic of the paper
1. The paper has a nice flow, with smooth transitions between sentences as well as between the introductory paragraph and the second paragraph
1. The second paragraph (which most likely focuses on describing a prior study or studies on the same topic) seems to lack the detail that I need to fully understand that prior study
1. Although I am only listening to the student author as they read me their paper, I feel like the paper needs additional proofreading
1. The student author does a good job supporting factual claims by citing other authors/studies
1. I feel like I have a good understanding of the topic the author discussed in this paper

Rating (1 to 7)

Questions For You (The Author)

1. My listener accurately described my study hypotheses

1. My listener seems confused about my study design

Questions For You (The Author)

Rating (1 to 7)

1. I feel my introductory paragraph adequately describes what my paper is about.

1. I think I can do a better job making sure that my paper flows well, with smoother transitions between sentences and between paragraphs

1. I think I need more detail when describing prior research so that I can better discuss what the prior research did and what they found.

1. Reading my paper aloud helped me figure out which sentences / passages need additional proofreading attention

1. Reading my paper aloud helped me figure out where I need to better cite resources to support my factual claims.

1. I feel like I have a good idea about how to improve my writing before I turn in the final draft of Paper I.

Continue to order Get a quote

Calculate the price of your order

Type of paper needed:

Pages:

550 words

Academic level:

We'll send you the first draft for approval by September 11, 2018 at 10:52 AM

Total price:

$26

The price is based on these factors:

Academic level

Number of pages

Urgency

Basic features

Free title page and bibliography
Unlimited revisions
Plagiarism-free guarantee
Money-back guarantee
24/7 support

On-demand options

Writer’s samples
Part-by-part delivery
Overnight delivery
Copies of used sources
Expert Proofreading

Paper format

275 words per page
12 pt Arial/Times New Roman
Double line spacing
Any citation style (APA, MLA, Chicago/Turabian, Harvard)

Our guarantees

Delivering a high-quality product at a reasonable price is not enough anymore.
That’s why we have developed 5 beneficial guarantees that will make your experience with our service enjoyable, easy, and safe.

Money-back guarantee

You have to be 100% sure of the quality of your product to give a money-back guarantee. This describes us perfectly. Make sure that this guarantee is totally transparent.

Zero-plagiarism guarantee

Each paper is composed from scratch, according to your instructions. It is then checked by our plagiarism-detection software. There is no gap where plagiarism could squeeze in.

Free-revision policy

Thanks to our free revisions, there is no way for you to be unsatisfied. We will work on your paper until you are completely happy with the result.

Confidentiality Guarantee

Your email is safe, as we store it according to international data protection rules. Your bank details are secure, as we use only reliable payment systems.

Fair-cooperation guarantee

By sending us your money, you buy the service we provide. Check out our terms and conditions if you prefer business talks to be laid out in official language.

24/7 Support

Our specialists are always online to help you! We are available 24/7 via live chat, WhatsApp, and phone to answer questions, correct mistakes, or just address your academic fears.

See our T&Cs

Live Chat +1(978) 822-0999 Email WhatsApp

assig 3

image1

Read Aloud Assignment #3

Read Aloud Assignment #3

Recent Posts

Recent Comments

Calculate the price of your order

Our guarantees

Money-back guarantee

Zero-plagiarism guarantee

Free-revision policy

Confidentiality Guarantee

Fair-cooperation guarantee

24/7 Support