A good article review will include the following:
Your complete assignment will be 1 page per article, 2 pages total. Each article is worth 1.5 points.
J Bus Ethics (2011) 99:39–48
DOI 10.1007/s10551-011-1165-6
Substantive Ethics: Integrating Law and Ethics in Corporate
Ethics Programs
Mark S. Blodget
t
Published online: 24 January 2012
� Springer Science+Business Media B.V. 2012
Abstract Continual corporate malfeasance signals the
need for obeying the law and for enhancing business ethics
perspectives. Yet, the relationship between law and ethics
and its integrative role in defining values are often unclear.
While integrity-based ethics programs emphasize ethics
values more than law or compliance, viewing ethics as
being integrated with law may enhance understanding of a
n
organization’s core values. The author refers to this inte-
gration of law and ethics as ‘‘substantive ethics,’’ analo-
gous to the substantive law that evolves over time, which is
applied to ethical breaches and carries sanctions for non-
compliance. This article describes the integration of law
and ethics as a mid-point between two polar views that
define law and ethics either as having no relation or as
being one and the same. Since corporations expressly state
which laws they follow, a sample of corporate compliance
statements is used to demonstrate this integrative mid-
point. The sample also reveals that corporate ethics codes
rarely express ethics and law as being integrated per se.
Therefore, the author creates an example of a securities law
compliance statement that is introduced with an integrative
perspective of law and ethics. Perhaps such revised cor-
porate codes will encourage corporate respect for both law
and ethics and enhance ethical sustainability.
Keywords Business ethics and law � Core values �
Corporate ethics codes � Ethical sustainability �
Integrity-based corporate ethics programs �
Substantive ethics
M. S. Blodgett (&)
Business Law & Ethics, Sawyer Business School,
Suffolk University, Boston, MA 02108-2770, USA
e-mail: mblodget@suffolk.edu
‘‘Obeying the law, both in letter and in spirit, is the
foundation on which this Company’s ethical stan-
dards are built’’ (Avery 2009).
Introduction
Business ethics controversies continue to arise in an era of
global economic crisis, egregious corporate malfeasance,
exorbitant CEO compensation, fraudulent investment
schemes, proliferation of tort suits, and global human rights
abuses. While protection of the economy, investors, and
other stakeholders is of major concern, calls for tort caps
may reduce the parameters of responsibility. Despite the
need for greater understanding of these matters, the role of
law as it relates to these business ethics issues is not well
understood. The law is often discounted as ‘‘mere rules’’
without acknowledgment of its ethical content. Yet,
responses to crises in business ethics often include new
regulation in addition to pleas for more ethical business
behavior. The connection between law and business ethics
compels us to more fully explore its role in the current
global business environment that increasingly demands
ethical sustainability. ‘‘For globalization to succeed, it must
be ethical’’ (Hoffman and Driscoll 2000, p. 222) and
generate new business ethics perspectives.
Perhaps this role and challenge are the most prominent
within the context of corporate behavior. Thus, this article
explores the inter-relationship of law and ethics as applied
to managerial decision-making and corporate governance
by (1) explaining a current, applied approach to the inter-
relationship between law and ethics; (2) proposing that a
new way of thinking about this inter-relationship is by
‘‘re-imaging’’ the ethics content of the law as ‘‘substantive
123
mailto:mblodget@suffolk.edu
40 M. S. Blodgett
ethics,’’ analogous to the substantive law; and by (3) pro-
posing that corporate codes of ethics be revised to
expressly encompass this inter-relationship as consistent
with values or integrity-based corporate ethics programs.
An Applied Approach to Law and Ethics
Over the centuries, numerous philosophers and legal
scholars have debated the relationship between law and
ethics. However, it is not the intent of this author to review
either ancient philosophy or the more recent exchanges of
Hart (1958) and Fuller’s (1958) debate on their relation-
ship, or to revive the past philosophical discourse of
luminaries as enumerated without elaboration in Dunfee
and Paine’s similar approaches to this topic (1996; 1994a,
b). Each accepts such a connection and applies it to busi-
ness ethics issues. Nor does the author address unethical or
ethically neutral law. As Herrera tells us, an exhaustive
answer to the relationship between law and ethics is
complicated and leads only to further inquiry. He points
out that ‘‘entire books will continue to be written on the
philosophical linkage between law and ethics from the
utilitarian perspective, the Kantian perspective, or the
Natural-law perspective’’ (Herrera 2000, p. 2).
Rather, this article draws upon the scholarly tradition
that recognizes a connection between law and ethics, an
enduring philosophical interest (Dunfee 1996) that is
foundational to contemporary business and legal issues.
Law and ethics do not conflict, nor are they mutually
exclusive (Schwartz et al. 2005). As Rawls tells us, the law
has exerted considerable influence upon philosophical
thought through its evolution, principles, and precedent
(Dunfee 1996). Therefore, the author addresses this inte-
grated or ‘‘coinciding’’ view of law and ethics (Paine
1994a, b, p. 165) in the section below to further enhance
understanding of the role of law within the application of
business ethics today.
Coinciding View
Where there is integration of law and ethics, the ethical
purpose of the law should be evident; for example, laws
prohibiting fraud enhance the ethics of disclosure and
fairness and in this example, law and ethics can be said to
coincide. Yet, perhaps it is more helpful elaborating on this
coinciding view of law and ethics by thinking of it as a
middle ground existing between two polar extremes: (1)
where law and ethics are considered to be totally separate,
and (2) where law and ethics are considered to be identical.
Although at times law and ethics are inter-related, many
continue to differentiate sharply between law and ethics,
and statements relegating law to a threshold status are
common. This ‘‘clear-line’’ approach appears in statements
that distinguish ethics from law as not only different but
also superior, such as ‘‘ethics consists of standards and
norms for behavior that are beyond laws and legal rights’’
and ‘‘ethical standards are not the standards of the law. In
fact, they are a higher standard’’ (Jennings 2006, p. 3).
While these statements contribute significantly to our
understanding of ethics and law, they may appear to
embrace the ‘‘separate realms view’’ (Paine 1994a, b,
p. 154), where law constitutes a normative minimum to
which neither ethical values attach nor from which do they
derive or evolve. Such a sharp distinction between law and
business ethics may lead to the conclusion that there is little
if any relationship between them. This supposition may
obfuscate their ‘‘coinciding’’ relationship, what Nesteruk
describes as a conduit for the law’s ‘‘morally creative role’’
that ‘‘rich interplay between law and ethics in the contem-
porary business environment’’ (Nesteruk 1999a, b, p. 604).
It is this rich inter-relationship that the American Law
Institute emphasizes as the ethical viewpoint or purpose of
the law that must be complied with rather than a narrow,
literal interpretation (Di Lorenzo 2007). As Hartman
reminds us, these rules or laws of compliance also provide
clarity to the new culture of integrity-based corporate ethics
programs (Hartman 2000). However, such lofty perceptions
do not often prevail when laws are looked upon as man-
datory compliance or as ‘‘mere rules to be followed.’’
To further enhance our perspective on this inter-rela-
tionship between law and ethics, it is necessary to identify
another viewpoint, namely, that law and ethics are in
complete harmony (the ‘‘correspondence view’’) (Paine
1994a, b, p. 156). However, this view precludes much
ethical responsibility and discretion. Each viewpoint of
separate realms and correspondence has its adherents;
however, there is a middle ground as Dunfee tells us, ‘‘the
two domains [law and ethics] are synergistically and inti-
mately related’’ and ‘‘neither can be fully meaningful or
realized without the other’’ (1996, p. 319). Hosmer and
Ehrlich deduce that, although not complete, there is con-
siderable overlap between law and ethics (2008; 2005).
This deduction leads Shaw (1996) to conclude that,
although insufficient to establish an organization’s values,
law evolves with society’s view of morals which it codifies
along with ideals. Perhaps a closer examination of these
codified morals and ideals will reveal some values suitable
for a corporation’s core values.
This considerable overlap forms an intersecting point
between the ‘‘separate realms view’’ and the ‘‘correspon-
dence view.’’ Identifying and exploring this coinciding or
integrative aspect of law and business ethics is important to
understanding a business environment that is often guided
by corporate compliance-based programs, but frequently
123
41
Substantive Ethics
engulfed in egregious breaches of both law and business
ethics. Let not the ‘‘incompleteness’’ distract us from the
mutuality of law and ethics. Separating law from business
ethics does not enhance our understanding of ethical
behavior or corporate malfeasance. Corporate compliance
statements of law carry tangible civil and/or criminal
sanctions for violations, and when sanctions are imposed,
there occurs enforcement of any coinciding business ethics
values. An emphasis on aspiration ethics may assume,
imply, and even demand another layer of responsible and
ethical business behavior, and when this occurs, it is
laudable; however, experience tells us more, and perhaps
this is the compelling reason for re-aligning and enhancing
perspectives on the coinciding view where law and ethics
are at times ‘‘synergistically and intimately related.’’
It is clear that corporations have a duty to obey the law,
yet unfortunately there are business executives who may
ignore this duty, be unaware of it, not understand it, or be
apprehensive of it. Hence, the need for compliance state-
ments, training, and broad-based communication and edu-
cation regarding the law. Ethically integrated compliance
statements imbued with express ethical perspectives may
more effectively guide behavior than narrow statements of
rules and obligations that are juxtaposed with corporate
values. For example, compliance statements prohibiting
fraud reveal the ethical perspective that intentional mis-
representation obviates good faith and honesty. This results
in a lack of trust, which should be avoided when doing
business, whether regulated or not. Integrating such ethics
values into compliance statements will unambiguously
allow the law’s ‘‘morally creative role’’ to more fully
participate in fashioning corporate ethics codes.
Corporate Ethics Codes
Analyzing corporate ethics codes is worthwhile in a global
business environment where ethical issues demand inves-
tigation (Donaldson and Werhane 1993) and where orga-
nizational culture is reflected in these formal statements
(Trevino et al. 1999). As part of corporate culture, ethics
codes contain statements of law and ethics that are self-
selected expressions or values of the corporation that are
also an identified source of
business ethics (Schwartz 2005).
Ethics codes are common among large firms (Donaldson
and Werhane 1993), and more than 90% currently use them
(Murphy 2005). They aid in identifying expectations
(Davies, ed. 1977) and provide guidance to managerial
decision-making by establishing ethical standards (Peppas
2002). According to Webley (Davies, ed. 1977), Cavanaugh
(1998) and Boatright (2003) they often include the business
ethics values of integrity, honesty, fairness, trust, and
responsibility. The last three of these values are also iden-
tified as among ‘‘six universal values’’ (Schwartz 2005).
One portion of today’s business ethics environment
centers upon corporate behavior and two approaches to
influencing this behavior through corporate ethics codes are
commonly identified as compliance-based and values or
integrity-based ethics programs. Compliance programs
focus on law and emphasize prevention and punishment. In
contrast, integrity-based programs acknowledge the law,
but are dominated by commitment to organizational values
(Trevino et al. 1999; Paine 1994a, b). Despite their differing
emphases, these two approaches are not mutually exclusive.
Approaches to corporate ethics programs have various
names and content (Weaver and Trevino 1999) spanning the
two poles of the ethics codes continuum from compliance to
integrity. Regardless of the corporate codes nomenclature,
‘‘an integrity-based program recognizes the complex rela-
tionship between law and ethics and is far more likely to
achieve the objective of responsible and effective organi-
zational conduct’’ (Paine 1994a, b, p. 169). Thus, the
identifiable and evolving inter-relationship of law and eth-
ics may reveal a new understanding and application of
business ethics that re-enforces the values or integrity-based
approach where the maximum emphasis is placed not upon
legal compliance but upon ethical decision-making.
In a 2005 comprehensive review, Schwartz compiled
and analyzed past studies of corporate ethics codes as part
of an extensive search for ‘‘universal values.’’ He also
included global codes and the writings of business ethicists,
all identified by him as sources of business ethics (Sch-
wartz 2005). His thorough review and analysis confirmed
the Aspen Declaration’s identification of six universal
values as follows: ‘‘(1) trustworthiness, (2) respect, (3)
responsibility, (4) fairness, (5) caring and (6) citizenship’’
(Schwartz 2005, p. 36). It is therefore reasonable to con-
clude that corporate ethics codes generally share in a rich
deposit of universal ethics values.
Just as corporate codes contain expressions of universal
values, they also contain legal compliance statements that
address many areas of current business concern. Many
codes blend law and ethics by varying degrees; they do not
merely juxtapose them. These ethics codes often include
expansive and global expressions of law. Because of this
expansive blend, the composition of corporate ethics codes
is worth investigating.
Methodology
Although the major or dominant types of legal compliance
statements are generally well known, commonly refer-
enced, (Post et al. 2002; Pagnatarro and Peirce 2007), and
static, the author studied a sample of 2008 Fortune 50
0
corporate ethics codes to further identify and substantiate
them and to glean additional data relevant to this study.
123
42 M. S. Blodgett
It should be, however, noted that the primary purpose of
studying this sample was not to establish the most fre-
quently occurring compliance statements per se but rather
to identify coinciding ethics values in some commonly
occurring corporate statements of legal compliance.
The sample was selected through an on-line random
number generator, and then the frequency of compliance
statements by topic was recorded, for example, ‘‘securities
laws’’ (See Exhibits 1A, 1B, 1C, 2A, and 2B). Also, state-
ments indicating the three different views—separate, cor-
responding, and coinciding, were gleaned (See Exhibit 3).
Some of the possible business ethics values coinciding with
the legal compliance areas were then identified as examples
of ‘‘substantive ethics,’’ a concept to be explained later in the
article. These examples of ‘‘substantive ethics’’ were then
corroborated with the ‘‘six universal values’’ (See Exhibit 4).
Results
The sample yielded 21 areas of corporate compliance rang-
ing in frequency from 19.35% to .81% as displayed in
Exhibit 1A 2008 Fortune 500 companies compliance data (30-
company sample)
Compliance area Term Term
frequency frequency
percentage
1 Securities 24 19.3
5
2 ‘‘All laws’’ 16 12.90
3 Anti-trust/competition 13 10.48
4 FCPA 9 7.26
5 Environment 9 7.26
6 Health and safety 9 7.26
7 Information/data 7 5.65
8 Anti-boycott 6 4.84
9 Corporate opportunity 5 4.03
10 Employment/EO/non- 5 4.03
discrimination
11 Fraud 4 3.23
12 Export law 4 3.23
13 Intellectual property 3 2.42
14 Money laundering 2 1.61
15 Bribes/Anti-Kickback Act of 1986 2 1.61
16 Immigration 1 0.81
17 Terrorism 1 0.81
18 Unfair dealing 1 0.81
19 Fair dealing 1 0.81
20 Child & forced labor 1 0.81
21 U.S. Embargo 1 0.81
Total compliance terms 1
24
Exhibits 1A, 1B 1C. Among the most prevalent areas of law
expressed in these compliance statements are as follows:
securities (30%), anti-trust (16.25%), Foreign Corrupt
Practices Act or FCPA (11.25%), environment (11.25%),
and health and safety (11.25%) (See 2A, 2B with percentages
based on a sample of 6). Four of these areas, securities
including securities fraud, FCPA, and anti-trust, track the
Federal Organizational Sentencing Guidelines for compli-
ance programs (Pagnatarro and Peirce 2007). Also prevalent
within the top 6 was ‘‘compliance with all laws’’ (20%). This
compliance statement has significance since it conceivably
includes all laws, not merely the ones specifically stated,
including U.S. law, ‘‘host countries’ laws’’ and in some
cases, ‘‘all other countries’ laws.’’ International law, a body
or system of law that exists beyond the legal system of any
particular country (Schaffer et al. 2009) may reasonably be
included in this expansive language. International law is rich
in ethics content such as the peremptory norm of jus cogens
that embodies high ideals of civilization ‘‘from which no
derogation is permitted’’ (August et al. 2009, pp. 8–9). It may
be interesting to note that no company’s ‘‘Integrity Policy’’
goes so far as to generally embrace ‘‘due care’’ (duty of care),
a legal element, and ethical value. This is consistent with past
studies of corporate ethics codes (Blodgett and Carlson
1997) unless relegated to the Board of Directors or to a
specific ‘‘professional area’’ within or tangential to the code
for accountants, lawyers, or brokers, for example.
In addition, statements among the different views—
separate, corresponding, and coinciding—yielded a variety
of ethics and law expressions along this total spectrum. The
following are representative of these expressions: ‘‘3M is
recognized worldwide as an ethical and law-abiding
company’’ and Altria’s ‘‘Our Compliance and Integrity
program is focused on doing the right thing, and reflects
our family of companies’ culture and values,’’ and Pacific
Life’s ‘‘Ethics and compliance are two closely related and
intertwining concepts that work together to help us do the
right thing’’ (2009). In general, such statements reveal
aspects of the three views—separate, corresponding, and
coinciding, but may often appear mixed and possibly
ambiguous when interpreted alone or together as in the
ethics code of one company presented below.
Since law and ethics at times coincide, it is helpful
assigning ethics values to the areas of law found in the
sample. The chart given here shows common examples of
legal compliance areas and possible coinciding ethics val-
ues that are corroborated with the ‘‘six universal values.’’
While not intended as exhaustive or complete, Exhibit 4
shows examples of numerous ethical values encompassed
by legal compliance. Many of these values are often found
in the ethics sections of corporate ethics codes—a potential
reciprocity of express ethical values with compliance
statements that may lend even more meaning to the
123
43
Sec
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FCPA
Substantive Ethics
24
16
13
9
9 9
7 6 5 5 4 4 3 2 2 1 1 1 1 1 1
0
5
10
15
20
25
30
T
er
m
F
re
q
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en
cy
Compliance Term
Exhibit 1B 2008 Fortune 500 companies’ compliance areas (30-company sample)
2
5.00%
19.35%
12.90%
10.48%
7.26% 7.26% 7.26%
5.65%
4.84%
4.03% 4.03%
3.23% 3.23%
2.42%
1.61% 1.61%
0.81% 0.81% 0.81% 0.81% 0.81% 0.81%
P
er
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Compliance Term
Exhibit 1C 2008 Fortune 500 companies’ compliance areas percentages (30-company sample)
24
16
13
9
T
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m
F
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cy 30
25
20
15
10
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9 9
Compliance Term
Exhibit 2A 2008 Fortune 500 companies’ most frequent compliance areas
statement that ‘‘obeying the law, both in letter and in spirit, representative of many corporations’ stated core values, the
is the foundation on which this Company’s ethical stan- identification of which Hartman recognizes as an important
dards are built’’ (Avery 2009). Surely, these values are part of the ‘‘process of ethics integration’’ (2000, p. 157)
123
44 M. S. Blodgett
Health and Safety,
11.25%
Environment, Securities, 30.00%
11.25%
FCPA, 11.25%
Anti- All Laws , 20.00%
trust/Competition,
16.25%
Exhibit 2B 2008 Fortune 500 companies’ most frequent compliance
areas percentages
adding even more impetus to the inter-relationship of law
and ethics as an emerging perspective in ethical decision-
making and corporate governance.
Analysis: Emerging Perspectives
Many compliance areas identified in the sample are also
commonly identified in the literature (Post et al. 2002;
Pagnatarro and Peirce 2007). They refer to substantive law
Exhibit 3 Excerpts from Pacific Life, Inc. code of business conduct
that defines rights and duties (Reed et al. 2009) and they
tell much about what should be among the current ethical
concerns of business. After all, the statements were self-
selected; albeit, selected with the encouragement of the
Federal Organizational Sentencing Guidelines. Perhaps
ironically, many of the dominant legal compliance areas
are also identified as the most frequently violated laws
within firms (Post et al. 2002) and as such, their coinciding
ethics values are also violated. According to Tucker, the
federal guidelines expressly communicate that ‘‘bad ethics
is bad business’’ (Cohen 1993, p. 355). Perhaps this ethical
perspective is even more acute when viewed within a
global context since the statement ‘‘we obey all laws’’
conceivably encompasses universal ethical content and
purpose, and some areas of compliance such as ‘‘corrup-
tion’’ exist as presumed ‘‘hyper-norms’’ or fundamental
universal principles that embrace deeply held values of
humanity (Donaldson and Dunfee 1999).
Clearly, business needs a fresh outlook in managing law
and ethics. From the discussion and data presented above,
it is evident that both legal compliance and ethics are key
components of corporate governance and that reliance
Separate Coinciding Corresponding
‘‘While [ethics and compliance] serve similar ‘‘Ethics and compliance are two closely ‘‘We are committed to following laws and
functions, they are distinct enough to justify related and intertwining concepts that regulations, just as we are committed to
separate principles in our Code of Business work together to help us do the right providing excellent products and services’’
Conduct’’ thing’’
‘‘Just as there are many laws and regulations that
guide us in our compliance efforts, there are
many ethical standards that guide us in doing the
right thing’’
Exhibit 4 Compliance areas
and coinciding ethics values
Compliance area Law governing Substantive ethics values Universal values
Securities Fraud Fairness Fairness
Disclosure
Responsibility Responsibility
Insider trading
Trustworthiness Trustworthiness
Fiduciary duty
FCPA Bribes Fairness Fairness
Accounting
Anti-trust Competition Fairness Fairness
Employment Equal opportunity Caring Caring
Discrimination Fairness Fairness
Responsibility Responsibility
Trustworthiness Trustworthiness
Environment Environmental protection Caring Caring
Responsibility Responsibility
Trustworthiness Trustworthiness
123
45 Substantive Ethics
upon one may detract from the other. The currently all too
common juxtaposition of law and ethics does not serve the
best interests of ethical sustainability. Perhaps what is
necessary is a more unified view of the substantive law and
ethics.
Substantive Ethics
The argument for ethics without regard for law to guide
business behavior may be analogous to arguing for the
abolition of law and for religious teachings, philosophy,
etiquette and civility to guide our citizenry in correct
societal behavior. While this non-legal background is
necessary, highly desirable, and profound, it is also of great
importance to have laws that prohibit deceit, fraud, theft,
murder, and discrimination and that dole out substantial
penalties for violations. It is also important that society and
business respect these laws, recognizing that they embrace
fundamental ethics values.
After all, if one were to decide between laws that
‘‘coincide’’ or aspiration ethics, which would be then the
better choice: laws that embrace business ethics that are
enforced with tangible penalties, or discretionary ethical
practice that may not be intrinsically valued or acted upon
and that carries no formal incentive for doing so? If laws
carrying sanctions did not exist, how much influence would
their coinciding ethics values have in guiding managerial
decision-making?
Fortunately, there is no need to decide between law and
ethics. But this duality has been the challenge at hand
because law and ethics are more appropriately viewed as
integrative, and if not so viewed contributes to dysfunction
in corporate governance. By the late nineteenth century,
our nation’s history showed us that ‘‘[i]n a lawless world,
the exigencies of competition tended to drive commercial
practices toward the level of the most unscrupulous’’ (Hilts
2003, pp. 45–46). Hence, followed the decades of evolving
regulatory response amidst concerns for the fundamental
undermining of ‘‘faith in commercial integrity and the very
foundation of trade’’ (Hilts 2003, pp. 45–46). Conse-
quently, in our current era, substantive law makes a major
impact on ethical behavior. For example, the design,
manufacture, and distribution of products and services is a
function of the law’s standards of ‘‘duty of care.’’
Not to recognize ethics in the substantive law is to miss a
significant coinciding perspective, for our products and
services are governed as much by the ethics and law of
the ‘‘duty of care’’ as are decisions of corporate boards.
Hoffman and Driscoll (2000) and Schwartz et al. (2005)
recognize that corporate board decision-making is central to
ethics integration within corporations and decisions of
corporate boards carry expectations of trust, a reciprocal
value to responsibility (Fritzsche 1997). As Ehrlich reminds
us, even many routine questions posed to corporate ethics
officers deal with conflicts of interest that encompass both
the legal and ethical concept of ‘‘duty of loyalty’’ (2005,
p. 4). Thus, values are less ambiguous when perceived as
part of the rules themselves (Hartman 2000) that also reveal
currently perceived ethical demands in today’s business and
regulatory environment (Nesteruk 1999a, b).
Codes that take a coinciding view of legal compliance
and ethics have much more to offer our understanding of
the role of law than those taking a separated view. The
ethical content of law is of such great magnitude that
Nesteruk calls for a new way to view the images of law
(1999a, b). It is so inter-twined with ethics that Salbu
concludes that ethics permeates the law through its
emphasis on equity or fairness, constitutional concepts
such as ‘‘due process’’ and modern statutory law (2001).
His specific examples include the Civil Rights Act of 1964,
cyber law and environmental law (Salbu 2001), each
exemplifying an ‘‘applied ethics’’ (Dunfee 1996, p. 318)
within the substantive law or perhaps a ‘‘substantive eth-
ics.’’ This author therefore suggests that the concept of
‘‘substantive ethics’’ aptly and accurately conveys the
coinciding view of law and business ethics as (1) ethics that
is part of the rights and duties of the substantive law, and
(2) ethics that therefore evolves as the substantive law
evolves. The following employment law example, one area
of ‘‘ethics-permeated’’ laws shown above in Exhibit 4,
illustrates these two aspects of ‘‘substantive ethics.’’
It has been said that education is the answer to guar-
anteeing equal opportunity to all and that the Civil Rights
Acts, and other similar laws are unnecessary. In such a
society, equal employment opportunity would be bestowed
upon the deserving by noble minded, ethical, and moral
people. Unfortunately, much of this ‘‘equal opportunity’’
would be dependent upon the ethical and moral largesse of
many who are the least likely to possess it. Here, as in other
business ethics challenges, substantive law imbued with
ethics values has been the necessary response. It also
reveals the concurrent unfolding of coinciding ethics val-
ues that is analogous to the evolution of the substantive
law. Following is an example as seen in the history of the
common law doctrine of ‘‘employment-at-will.’’
Common law doctrines trace their origin to medieval
England, the source of our legal system that is based upon
stari decisis or the reliance upon case precedent as a guide
to deciding current controversies. The common law system
spans the globe and many of its doctrines are imbued with
ethics, in particular, the ethic of ‘‘individual responsibil-
ity;’’ however, our society has gradually eroded this stark
aspect of the common law by favoring a more societal
viewpoint or sharing of responsibility. According to the
common law doctrine of ‘‘employment at will,’’ either
party can terminate employment at whim without liability
123
46 M. S. Blodgett
(Ballam 2000). This doctrine has been fundamentally
altered over time to produce a more just and responsible
employment environment given the changes that have
evolved with the industrial revolution and our nation’s
commitment to equal opportunity. Among the current
restrictions on this doctrine are ‘‘wrongful discharge’’ and
the protections against some forms of discrimination
offered by the Civil Rights Acts. Evolving societal ethics
have thus transformed this common law doctrine and oth-
ers such as caveat emptor or ‘‘buyer beware.’’
As ethics evolves, so does the legislative response or what
some have called ‘‘legislating ethics’’ (Jennings 2006). This
dynamic of regulatory response to ethical breach is highly
predictable as the demand for business ethics increases.
Hosmer also recognizes this ‘‘complex response’’ where
changing moral standards become institutionalized by social
and political processes (2008, p. 71). Thus, law and ethics
evolve over time as legislation responds to ethical demands.
Perhaps another way of expressing the complexities of
‘‘legislating ethics’’ is through the role of social responsi-
bility, or duty. Just as Ostas recognizes that legal duty is
encompassed by a more expansive social duty, one that
‘‘could be entrusted to the goodwill and ethics of the
business community’’ (2004, p. 563), as a Kantian ‘‘self-
regulator’’ (Herrera 2000, p. 2), he also concludes that if
this duty were not met then regulation would follow. The
Sarbannes-Oxley Act is one of our most recent and dra-
matic examples of this inter-relation of law and ethics—a
breach of business ethics and a legislative response that
demands more ethical behavior.
Other business ethics issues continue to arise, and in
reciprocal fashion, regulations and corporate ethics codes
respond. This should not be surprising because the under-
pinnings of many legal compliance statements such as anti-
trust, securities, employment and intellectual property are
based upon tort law. The business ethics of tort law is
profound. It defines the contours of responsibility, or duty,
and greatly impacts our society’s essential value system
and culture (France 2005). Unfortunately, the ethical and
legal underpinnings and relationships of these compliance
areas are generally not well communicated nor well
understood although ‘‘exemplary conduct usually reflects
an organizational culture and philosophy that is infused
with a sense of responsibility’’ (Paine 1994a, b, p. 109).
Ethical and legal inter-relationships are pervasive, pre-
dictable and continuously evolving. They have an ethical
impact on business and society as people learn about the
law, apply it, and eventually embrace it. Our jurispruden-
tial and legislative processes institutionalize this evolving
ethical impact. As coinciding business ethics evolves, so
does substantive, coinciding law to such an extent that
Hoffman recommends that ethics codes stay abreast of the
latest legal developments (Boatright 2003). The law is not
always a threshold. It is at times an evolving and vast array
of business ethics.
Hence, we arrive at an emerging perspective of law and
business ethics as part of values- or integrity-based ethics
programs—a ‘‘substantive ethics’’ that more descriptively
reflects the evolving and coinciding, inter-relationship of
law and ethics. But how can the image of law be transformed
from the often pervasively narrow view of ‘‘rules to be fol-
lowed’’ to an image that encourages the best applications in
ethical decision-making and corporate governance?
Re-Imaged Corporate Compliance
Emerging perspectives on the relationship between law and
ethics are prompted by Nesteruk’s call for ‘‘re-imagining’’
law (1999a, b) and Paine’s and Trevino’s passionate views
on integrity-based ethics programs where both legal com-
pliance and ethics are recognized as vital, integrative parts
of the whole (1994a, b; Trevino et al. 1999). The inter-
relationship of law and ethics also conforms to Hartman’s
‘‘process of ethics integration’’ (2000, p. 157) where law
and ethics coincide in corporate codes beyond narrow
notions of ‘‘rules to be obeyed’’ and where ethical values
are clarified by law (Hartman 2000). This clarity of values
is consistent with an expanded view of ‘‘shared values,’’
the norms that create organizational expectations (Weaver
and Trevino 1999), as they imbue legal compliance and the
corporation’s total ethical culture. As the values or integ-
rity approach advances, corporate ethics programs may
more distinctively transform beyond a juxtaposition of the
polar realms of compliance and ethical values.
There is now an opportunity for re-imaging the law by
enhancing the compliance parts of corporate codes with
ethics. By re-writing codes to explain and elaborate on the
business ethics context of the law, business can demon-
strate the reasons why laws should be followed and clarify
that although law is not an ethical totality—neither is it
devoid of ethics. Such revised expressions should explain
unambiguously that ethics and law at times coincide, and
they should also make use of identified global values.
For example, the legal compliance statement ‘‘we abide
by securities regulation’’ can be prefaced with the historical
objective of the Securities Acts which is to protect inves-
tors by upholding business ethics through fair dealing (Cox
et al. 2004) or as our courts have stated, by substituting ‘‘a
philosophy of full disclosure for the philosophy of caveat
emptor and thus to achieve a high standard of business
ethics in the securities industry’’ (Di Lorenzo 2007, p. 280).
The author developed an example of such a values or
integrity-based statement set forth in Exhibit 5.
Enhancing compliance statements with their ethical
dimensions will not only communicate that there is ethics
in compliance but enhance the ethical context of business
123
47 Substantive Ethics
Exhibit 5 Integrity-based statement
‘‘Securities regulation’’
Introduction
Our company’s commitment to comply with the securities laws is
consistent with the business ethics objectives of the Securities
Acts. Much of securities law today is concerned with ensuring
‘‘fairness’’ for both consumers and business by balancing the
interests of these two parties. Among the ways it is achieved is
through appropriate transparency and disclosure of material
information. Investors must be adequately informed before they
purchase equities and we must ensure that employees are not
trading on inside-information nor engaging in fraudulent
activities
We believe in treating all of our stakeholders, both internal and
external, in a fair manner. Fairness is highly valued by our
company in any context across all of our business practices,
relationships and commitments
As such, fairness is one of our core and inter-related ethics and
legal compliance values that we use to guide our decision-
making on a daily basis. This integration of ethics and law is part
of our company’s commitment to our shared core values—a
vibrant part of our organizational culture and strength
generally—a perceived ‘‘coming together’’ of ethics and
law that confronts current and anticipated business issues.
The extended context of the value of fairness as indicated
above, is an example of this ethical enhancement and a way
to deepen ethical culture, (Trevino et al. 1998; Paine
1994a, b) invigorate managerial decision-making and cor-
porate governance, and reach for the ‘‘goal to achieving
global and universal standards of fundamental ethical val-
ues’’ (Hoffman and Driscoll 2000, p. 230). Presently, what
may appear as a faint glimmer in corporate ethics codes
that may mention ‘‘integrity’’ and refer to the law and
ethics as ‘‘intertwining concepts,’’ may in reality be a
beacon of change. This enhanced ethics content is consis-
tent with the preferred values or integrity-based ethics
program and as this article asserts, an emerging perspective
on the substantive law and ethics, a ‘‘substantive ethics.’’
Conclusion
This article analyzes coinciding aspects of law and busi-
ness ethics as an emerging perspective in managerial
decision-making and corporate governance. It does so with
the hope of enhancing understanding of the significance of
the law so that it is perceived not as mere rules to be
obeyed, but rather as integral to ethical decision-making.
After all, corporate ethics codes that contain statements of
legal compliance have been identified as a source of
business ethics (Schwartz 2005).
The author reviewed legal compliance statements in
corporate codes of ethics, measured their frequency of
occurrence and explored their ethical content. This article
makes recommendations to revise statements of corporate
compliance to more fully express their ethical content. This
enhanced process of ethics integration is consistent with
the call to transition from legal-compliance-based ethics
programs to values or integrity-based programs rooted in
the idea that the individual internalizes the shared core
values of the firm as a personal commitment to self-gov-
ernance (Trevino et al. 1999; Paine 1994a, b) where law is
well acknowledged and ethics is emphasized.
This recommended approach will help business not only
to reach beyond the legal compliance-based notion that
whatever is legal is the ethical extent of corporate respon-
sibility, yet also help business to see the ethical value in
obeying laws. With this knowledge, business is better able to
apply ethical reasoning to even non-regulated areas as part of
its ethical identity of shared core values and its commitment
to ethical sustainability. Greater compliance as a function of
ethics is an appropriate approach and goal for corporate
governance today where the substantive law is re-imaged as
a vital part of business ethics, a ‘‘substantive ethics.’’
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Journal of Applied Psychology
2001, Vol. 86, No. 3, 425-445
Copyright 2001 by the American Psychological Association, Inc.
0021-9010/01/$5.00 DOI: 10.1037//0021-9010.86.3.425
Justice at the Millennium: A Meta-Analytic Review of 25 Years of
Organizational Justice Research
Jason A. Colquitt
University of Florida
Michael J. Wesson and Christopher O. L. H. Porter
Texas A&M University
Donald E. Conlon
Michigan State University
K. Yee Ng
Michigan State University
The field of organizational justice continues to be marked by several important research questions,
including the size of relationships among justice dimensions, the relative importance of different justice
criteria, and the unique effects of justice dimensions on key outcomes. To address such questions, the
authors conducted a meta-analytic review of 183 justice studies. The results suggest that although
different justice dimensions are moderately to highly related, they contribute incremental variance
explained in fairness perceptions. The results also illustrate the overall and unique relationships among
distributive, procedural, interpersonal, and informational justice and several organizational outcomes
(e.g., job satisfaction, organizational commitment, evaluation of authority, organizational citizenship
behavior, withdrawal, performance). These findings are reviewed in terms of their implications for future
research on organizational justice.
The study of justice or fairness has been a topic of philosophical
interest that extends back at least as far as Plato and Socrates
(Ryan, 1993). Colloquially, the term justice is used to connote
“oughtness” or “righteousness.” Under the purview of ethics, an
act can be defined as just through comparison with a prevailing
philosophical system. Unfortunately, often there is no agreement
on what that philosophical system should be. For example, Aris
totle (reprinted in Frost, 1972) noted that people in different roles
will advocate different justice rules, arguing that “the democrats
are for freedom, oligarchs for wealth, others for nobleness of birth”
(p. 136; see also Pillutla & Mumighan, 1999).
In research in the organizational sciences, justice is considered
to be socially constructed. That is, an act is defined as just if most
individuals perceive it to be so on the basis of empirical research
(Cropanzano & Greenberg, 1997). Thus, “what is fair” is derived
from past research linking objective facets of decision making to
subjective perceptions of fairness. In particular, justice in organi
zational settings can be described as focusing on the antecedents
and consequences of two types of subjective perceptions: (a) the
fairness of outcome distributions or allocations and (b) the fairness
of the procedures used to determine outcome distributions or
allocations. These forms of justice are typically referred to as
Jason A. Colquitt, Department of Management, University of Florida;
Donald E. Conlon and K. Yee Ng, Department of Management, Michigan
State University; Michael J. Wesson and Christopher O. L. H. Porter,
Department of Management, Texas A&M University.
We thank George Barnekov and Yumi Eto for their assistance in
gathering the articles covered in this review.
Correspondence concerning this article should be addressed to Jason A.
Colquitt, Warrington College of Business Administration, Department of
Management, University of Florida, P.O. Box 117165, Gainesville, Florida
32611-7165. Electronic mail may be sent to colquitt@ufl.edu.
distributive justice (Adams, 1965; Deutsch, 1975; Homans, 1961;
Leventhal, 1976) and procedural justice (Leventhal, 1980; Lev
enthal, Karuža, & Fry, 1980; Thibaut & Walker, 1975).
Efforts to explain the impact of justice on effective organiza
tional functioning have come under the rubric of organizational
justice research (Greenberg, 1987b, 1990b). Greenberg (1990b)
described organizational justice as a literature “grown around
attempts to describe and explain the role of fairness as a consid
eration in the workplace” (p. 400). This literature includes both
field and laboratory research, and organizational justice has been
among the most frequently researched topics in industrial-
organizational psychology, human resource management, and or
ganizational behavior over the last decade (Cropanzano & Green
berg, 1997).
As interest in organizational justice has proliferated, so too have
the theoretical approaches used to study it, particularly in relation
to procedural justice. These approaches each propose a different
way of conceptualizing justice, from the provision of process
control (Thibaut & Walker, 1975) to a focus on consistency
(Leventhal, 1980; Leventhal et al., 1980) and an examination of
interpersonal treatment (Bies & Moag, 1986). In addition, a large
number of studies have sought to link justice perceptions to a
variety of organizational outcomes, including job satisfaction, or
ganizational commitment, withdrawal, and organizational citizen
ship behavior.
Because of this diversity in theoretical approach and construct
focus, organizational justice is a field in need of integration. There
have been a number of narrative reviews that have sought to
achieve such integration (e.g., Cropanzano & Greenberg, 1997;
Folger & Cropanzano, 1998; Lind & Tyler, 1988; Greenberg,
1987b, 1990b). However, important questions remain, including
the following: How highly related are the different dimensions of
organizational justice, and can they be empirically distinguished
425
mailto:colquitt@ufl.edu
COLQUITT, CONLON, WESSON, PORTER, AND NG426
from one another? Have the different ways of conceptualizing
justice improved our ability to create perceptions of fairness? and
What are the relationships between different organizational justice
dimensions and important outcomes relevant to organizations? The
first question deals with issues of construct discrimination (i.e., to
what extent are constructs distinct from one another?). The second
question deals with what Greenberg (1987b) called proactive re
search (i.e., research devoted to creating perceptions of fairness).
The last question deals with what Greenberg (1987b) called reac
tive research (i.e., research devoted to understanding how individ
uals react to fair or unfair treatment).
The purpose of this study was to conduct a comprehensive,
meta-analytic review of the existing literature on organizational
justice. To our knowledge, a meta-analysis has never been con
ducted in the organizational justice literature, even though meta
analysis has several important strengths relative to traditional
narrative reviews (Hunter & Schmidt, 1990). First, meta-analysis
is a more powerful summarizing tool because it yields a quantita
tive population value for a relationship of interest. Second, meta
analysis typically includes more studies than narrative reviews and
is therefore less susceptible to biases based on study inclusion.
Third, meta-analysis allows the reviewer to understand why rela
tionships in the literature vary as a function of sampling error,
measurement error, and moderator variables. These strengths make
meta-analysis an effective way of examining the three types of
questions just listed.
We conducted meta-analyses on all articles in the organizational
justice literature published since 1975. We chose 1975 as our
starting date because this is when Thibaut and Walker introduced
the procedural justice construct, which allowed for the compara
tive study of the influence of multiple dimensions of justice. That
year also marks, approximately, the time when justice researchers
began integrating fairness concerns with outcomes relevant to
organizations (e.g., job satisfaction and organizational commit
ment). Thus, as we reach the millennium, this review covers a
quarter century of academic research. Our analyses dealt with all
three types of questions raised earlier: construct discrimination
issues, proactive research issues, and reactive research issues. In
total, we relied on 120 separate meta-analyses, along with the
emerging technique of meta-analytic regression analysis (Viswes-
varan & Ones, 1995), to explore the three types of questions. We
provide a brief review of the organizational justice literature before
reviewing the specific research questions explored in this article.
A Brief Review of the Organizational Justice Literature
Introduction of Distributive Justice
Before 1975, the study of justice was primarily concerned with
distributive justice. Much of this research was derived from initial
work conducted by Adams (1965), who used a social exchange
theory framework to evaluate fairness. According to Adams, what
people were concerned about was not the absolute level of out
comes per se but whether those outcomes were fair. Adams sug
gested that one way to determine whether an outcome was fair was
to calculate the ratio of one’s contributions or “inputs” (e.g.,
education, intelligence, and experience) to one’s outcome and then
compare that ratio with that of a comparison other. Although the
comparison of the two input-outcome ratios gives Adams’s equity
theory an “objective” component, he was clear that this process
was completely subjective.
Whereas Adams’s theory advocated the use of an equity rule to
determine fairness, several other allocation rules have also been
identified, such as equality and need (e.g., Leventhal, 1976).
Studies have shown that different contexts (e.g., work vs. family),
different organizational goals (e.g., group harmony vs. productiv
ity), and different personal motives (e.g., self-interest motives vs.
altruistic motives) can activate the use or primacy of certain
allocation rules (Deutsch, 1975). Nevertheless, all of the allocation
standards have as their goal the achievement of distributive justice;
they merely attempt to create it through the use of different rules.
Introduction of Procedural Justice
With the publication of their book summarizing disputant reac
tions to legal procedures, Thibaut and Walker (1975) introduced
the study of process to the literature on justice. Thibaut and Walker
(1975) viewed third-party dispute resolution procedures such as
mediation and arbitration as having both a process stage and a
decision stage. They referred to the amount of influence disputants
had in each stage as evidence of process control and decision
control, respectively. Their research suggested that disputants were
willing to give up control in the decision stage as long as they
retained control in the process stage. Stated differently, disputants
viewed the procedure as fair if they perceived that they had process
control (i.e., control over the presentation of their arguments and
sufficient time to present their case). This process control effect is
often referred to as the “fair process effect” or “voice” effect (e.g.,
Folger, 1977; Lind & Tyler, 1988), and it is one of the most
replicated findings in the justice literature. Indeed, Thibaut and
Walker (1975) virtually equated process control with procedural
justice (Folger & Cropanzano, 1998).
Although Thibaut and Walker (1975) introduced the concept of
procedural justice, their work focused primarily on disputant re
actions to legal procedures. Although a focus on justice and law
continues to be of interest to scholars (e.g., Tyler, 1990), Leventhal
and colleagues can be credited for extending the notion of proce
dural justice into nonlegal contexts such as organizational settings
(Leventhal, 1980; Leventhal et al., 1980). In doing so, Leventhal
and colleagues also broadened the list of determinants of proce
dural justice far beyond the concept of process control. Leventhal’s
theory of procedural justice judgments focused on six criteria that
a procedure should meet if it is to be perceived as fair. Procedures
should (a) be applied consistently across people and across time,
(b) be free from bias (e.g., ensuring that a third party has no vested
interest in a particular settlement), (c) ensure that accurate infor
mation is collected and used in making decisions, (d) have some
mechanism to correct flawed or inaccurate decisions, (e) conform
to personal or prevailing standards of ethics or morality, and (f)
ensure that the opinions of various groups affected by the decision
have been taken into account.
Introduction of Interactional Justice
Bies and Moag (1986) introduced the most recent advance in the
justice literature by focusing attention on the importance of the
quality of the interpersonal treatment people receive when proce
dures are implemented. Bies and Moag (1986) referred to these
META-ANALYTIC REVIEW OF ORGANIZATIONAL JUSTICE 427
aspects of justice as “interactional justice.” More recently, inter
actional justice has come to be seen as consisting of two specific
types of interpersonal treatment (e.g., Greenberg, 1990a, 1993b).
The first, labeled interpersonal justice, reflects the degree to which
people are treated with politeness, dignity, and respect by author
ities or third parties involved in executing procedures or determin
ing outcomes. The second, labeled informational justice, focuses
on the explanations provided to people that convey information
about why procedures were used in a certain way or why outcomes
were distributed in a certain fashion.
Questions Permeating the Organizational
Justice Literature
The proliferation of studies on organizational justice has cer
tainly enhanced the visibility of fairness concerns, but the large
number of studies and the differing theoretical perspectives raise
the concern that justice scholars may be “losing the forest for the
trees.” In other words, despite the large accumulation of findings,
many central questions remain either unaddressed or unclear. Until
such questions are addressed, theory development in the organi
zational justice literature will continue to be hindered. Our meta-
analytic review examines some of these central questions, with
specific areas of focus discussed in the sections to follow.
Construct Discrimination Questions
Perhaps the oldest debate in the justice literature concerns the
independence of procedural and distributive justice. Some studies
have revealed extremely high correlations between the two justice
dimensions, suggesting that they may not be distinct in the minds
of many people (Folger, 1987). For example, Sweeney and Mc
Farlin (1997) found an uncorrected correlation of .72 between
procedural and distributive justice in a study of attitudes among
federal employees. Welbourne, Balkin, and Gomez-Mejia (1995)
found an uncorrected correlation of .74 in a study of employees in
two different companies, one a high-technology firm and the other
a consumer products firm. Possibly as a result of such findings,
Martocchio and Judge (1995) conducted a study of disciplinary
decisions in which no effort was made to separate procedural and
distributive justice. Rather, the authors examined the effects of
“organizational justice.”
Such high correlations are congruent with theoretical arguments
made by Cropanzano and Ambrose (2001). These authors have
argued that the procedural justice-distributive justice distinction,
although necessary and valuable, may sometimes be overempha
sized. Their “monistic perspective” notes that procedural evalua
tions are based in large part on outcomes attained (Thibaut &
Walker, 1975) and that the same event can be seen as a process in
one context and an outcome in another. For example, reorganizing
a performance evaluation system so that it provides employees
more process control can be termed a fair outcome, even though
process control is a procedural construct.
The construct discrimination concern applies to an even greater
degree to procedural and interactional justice. Bies and Moag
(1986) originally declared interactional justice to be a third type of
justice. They argued that people draw on interactional justice
perceptions when deciding how to react to authority figures (i.e.,
bosses and supervisors), whereas procedural justice perceptions
are used to decide how to react to the overall organization. How
ever, Bies retracted the position that interactional justice was a
third type of justice in a subsequent review (Tyler & Bies, 1990).
The author’s retraction of his earlier stance has become widely
held, as one recent narrative review treated interactional justice as
a social form of procedural justice (Cropanzano & Greenberg,
1997). In keeping with this view, many researchers have opera
tionalized procedural justice by measuring process control or Lev
enthal criteria, along with interactional justice, in one combined
scale (e.g., Brockner, Siegel, Daly, & Martin, 1997; Brockner,
Wiesenfeld, & Martin, 1995; Folger & Konovsky, 1989;
Konovsky & Folger, 1991; Mansour-Cole & Scott, 1998; Skarlicki
& Latham, 1997). This practice seems to suggest that the inter
personal implementation of procedures need not (or cannot) be
separated from their structural aspects.
However, other research has renewed the debate surrounding the
distinctiveness of procedural and interactional justice. Studies that
have examined the two constructs separately have shown that they
have different correlates or independent effects, or both (e.g.,
Barling & Phillips, 1993; Blader & Tyler, 2000; Cropanzano &
Prehar, 1999; Masterson, Lewis, Goldman, & Taylor, 2000; Moye,
Masterson, & Bartol, 1997; Skarlicki & Folger, 1997). Blader and
Tyler (2000), in a survey of 404 U.S. workers, found that system
originating procedural factors and leader-originating procedural
factors remained distinct in a confirmatory factor analysis. Master
son, Lewis, et al. (2000) drew on social exchange theory to show
that procedural and interactional justice affected other variables
through different intervening mechanisms. Specifically, proce
dural justice affected other variables by altering perceived organi
zational support perceptions; interactional justice affected other
variables by altering leader-member exchange perceptions (Graen
& Scandura, 1987).
Even assuming that interactional justice can and should be
distinguished from procedural justice, another question is whether
the interpersonal and informational facets of the construct merit
conceptual separation. Greenberg (1993b) suggested that interper
sonal and informational justice should be separated because they
are logically distinct and have been shown to have independent
effects (e.g., Greenberg, 1993c, 1994). Interpersonal justice acts
primarily to alter reactions to decision outcomes, because sensi
tivity can make people feel better about an unfavorable outcome.
Informational justice acts primarily to alter reactions to proce
dures, in that explanations provide the information needed to
evaluate structural aspects of the process.
Some recent work has attempted to address the construct dis
crimination questions raised earlier. Colquitt (2001) developed
measures of distributive, procedural, informational, and interper
sonal justice based on the seminal introductions of each construct
(Bies & Moag, 1986; Leventhal, 1976, 1980; Leventhal et al.,
1980; Thibaut & Walker, 1975) and validated them in both a
university and a field setting. Colquitt found that a four-factor
confirmatory model provided the best fit to the data and further
showed that the four justice dimensions predicted different out
comes. Thus, although some progress is being made, the literature
on organizational justice is still marked by a debate over whether
the domain includes one, two, three, or four dimensions of justice.
This is the subject of the first research question addressed in our
meta-analytic review.
428 COLQUITT, CONLON, WESSON, PORTER, AND NG
Research Question 1: How highly related are the different dimensions
of organizational justice, and can they be empirically distinguished
from one another?
Proactive Research Questions
The history of research devoted to understanding what promotes
perceptions of fairness has been marked by increasing complexity
in operationalization as new and different conceptualizations have
been introduced over the years. Thibaut and Walker (1975) ini
tially assumed that perceptions of procedural fairness were driven
by process control. Leventhal and colleagues (Leventhal, 1980;
Leventhal et al., 1980), on the other hand, eschewed the parsimo
nious approach offered by Thibaut and Walker and instead argued
that fairness perceptions were created by adherence to six different
criteria. Bies and Moag (1986) further suggested that fairness
perceptions were created by the proper enactment of procedures in
terms of interpersonal and informational justice.
Such additional complexity is warranted if new approaches
contribute incrementally to our understanding of how to foster
perceptions of procedural fairness. Unfortunately, at present we do
not actually know whether such incremental contributions exist.
This is because so many studies of procedural justice collapse
process control, Leventhal criteria, and interpersonal and informa
tional justice into a single variable (e.g., Brockner et al., 1995,
1997; Folger & Konovsky, 1989; Konovsky & Folger, 1991;
Mansour-Cole & Scott, 1998; Skarlicki & Latham, 1997). This
makes it impossible to gauge the relative influence of each element
on procedural fairness perceptions. Still other studies assess only
one conceptualization of procedural justice, again making it im
possible to assess the merits of different approaches.
Moreover, it is well accepted that people judge procedures as
more fair when they result in fair or favorable outcomes (Lind &
Tyler, 1988; Thibaut & Walker, 1975). Despite this, many studies
of procedural justice do not also examine distributive justice. Other
studies do examine distributive justice but use it only in analyses
separate from procedural justice. As a result, we cannot even be
sure that process control, Leventhal criteria, and so forth explain
variance in procedural fairness perceptions beyond distributive
justice. If the operationalizations of procedural justice contribute
little to procedural fairness perceptions beyond simple outcome
fairness, then the focus on additional conceptualizations has been
unwarranted.
Thus, in terms of creating procedural fairness perceptions, it is
unclear to what extent new conceptualizations of procedural jus
tice (including the relatively recent introductions of interpersonal
and informational justice) have contributed to our understanding.
Nor is it clear how important they are beyond the fairness of
outcome distributions. This is the subject of our next two research
questions.
Research Question 2: Have the additional conceptualizations of pro
cedural justice developed over time (including interpersonal and in
formational justice) contributed incremental variance explained in
procedural fairness perceptions?
Research Question 3: Do those conceptualizations contribute incre
mental variance explained in procedural fairness perceptions beyond
the effects of distributive justice?
Reactive Research Questions
Of course, one of the reasons scholars study justice is the belief
that enhanced fairness perceptions can improve outcomes relevant
to organizations (e.g., organizational commitment, job satisfaction,
and performance). One goal of our meta-analytic review is to help
develop some consensus regarding the relationships between di
mensions of justice and key outcomes. In particular, we evaluate
the predictive ability of three different models that attempt to
explain relationships between justice dimensions and important
outcomes. These three models are the distributive dominance
model suggested by Leventhal (1980), the two-factor model sug
gested by Sweeney and McFarlin (1993), and the agent-system
model suggested by Bies and Moag (1986).
The relative predictive power of procedural and distributive
justice has been of long-standing concern in the justice literature.
An interesting aspect of Leventhal’s (1980) work is that he ex
plicitly considered the impact of both procedural and distributive
justice and argued that distributive justice is generally more salient
than procedural justice. He further argued that distributive justice
judgments are likely to be more influential than procedural justice
judgments in determining “overall fairness judgments” (Leventhal,
1980, p. 133; Lind & Tyler, 1988). Consistent with this argument,
Conlon (1993) found that distributive justice explained more vari
ance in grievant evaluations of authorities (an appeal board) than
did procedural justice. These works support a strong, parsimonious
prediction that distributive justice will dominate (i.e., explain more
variance than) other forms of justice.
However, some prior research and theory have questioned this
thesis. In perhaps the first empirical study to explicitly link mul
tiple dimensions of justice to organizational outcomes, Alexander
and Ruderman (1987) surveyed more than 2,000 federal employ
ees, measuring procedural and distributive justice along with six
outcomes. Their regression analyses showed that justice measures
affected five of six organizational outcomes and that, for four of
these five outcomes, procedural justice had stronger relationships
than distributive justice.
More recently, scholars have argued that distributive justice is
likely to exert greater influence on more specific, person-
referenced outcomes such as satisfaction with a pay raise or
performance evaluation. In contrast, procedural justice is likely to
exert greater influence on more general evaluations of systems and
authorities (Greenberg, 1990b; Lind & Tyler, 1988). Consistent
with this prediction, McFarlin and Sweeney (1992) found that
distributive justice was a more important predictor of what they
termed two “personal outcomes” (pay satisfaction and job satis
faction) and that procedural justice was a more important predictor
of two “organizational outcomes” (organizational commitment and
subordinate’s evaluation of supervisor).
Sweeney and McFarlin (1993) conducted perhaps the most
comprehensive test of this notion. They contrasted four models
expressing the relationship between procedural and distributive
justice and two outcomes (pay satisfaction and organizational
commitment). The idea that procedural justice predicts more
system-referenced outcomes and distributive justice predicts more
person-referenced outcomes was termed in their article the “two-
factor model.” They found that the two-factor model fit their data
better than three competing models. Thus, drawing on the results
META-ANALYTIC REVIEW OF ORGANIZATIONAL JUSTICE 429
of these studies, we examine the two-factor model’s prediction of
differing effects for procedural and distributive justice.
Finally, Bies and Moag’s (1986) focus on interpersonal treat
ment suggests a third approach to explaining organizational out
comes, one that explicitly examines the role of interpersonal and
informational justice in addition to procedural justice. Recall that
Bies and Moag (1986) originally argued that individuals draw on
interpersonal and informational justice perceptions when deciding
how to react to authority figures (i.e., bosses and supervisors) and
draw on procedural justice perceptions when deciding how to react
to the overall organization. Building on this work, Masterson,
Lewis, et al. (2000) drew on social exchange theory (Blau, 1964)
and reasoned that individuals in organizations were involved in
two types of exchange relationships: exchanges with their imme
diate supervisor and exchanges with the larger organization. In a
field study, the authors showed that interactional justice predicted
supervisor-referenced outcomes (e.g., citizenship behaviors di
rected at supervisor and supervisor rating of performance),
whereas procedural justice predicted organization-referenced out
comes (e.g., citizenship behaviors directed at the organization and
organizational commitment). Thus, our third reactive model, the
agent-system model, reflects the assertion that interpersonal and
informational justice will be more powerful predictors of agent-
referenced outcomes than system-referenced outcomes.
The distributive dominance model, the two-factor model, and
the agent-system model are explored in the following set of
research questions.
Research Question 4: What are the relationships between distributive
justice and important organizational outcomes?
Research Question 5: What are the relationships between procedural
justice and important organizational outcomes?
Research Question 6: What are the relationships between interper
sonal and informational justice and important organizational
outcomes?
Research Question 7: If considered simultaneously, what are the
unique effects of these justice dimensions on key outcomes, and
which of the three reactive models receives the most support?
Our review focuses on several different outcomes representing
those most commonly examined in the organizational justice lit
erature. In the following sections, we briefly review each type of
outcome.
Outcome satisfaction. Many justice studies have measured
satisfaction with the outcomes of a decision-making process, such
as pay, promotions, and performance evaluations. Given the logic
presented earlier, we expect that distributive justice judgments will
be a better predictor of outcome satisfaction than will procedural
justice or interpersonal and informational justice. This pattern has
been empirically supported through the use of pay satisfaction and
satisfaction with job restructuring (e.g., Folger & Konovsky, 1989;
Lowe & Vodanovich, 1995; Sweeney & McFarlin, 1993), and it is
consistent with both the distributive dominance and two-factor
models.
Job satisfaction. Many studies also ask about employees’ sat
isfaction with their jobs in general. McFarlin and Sweeney (1992)
showed that distributive justice was a more powerful predictor of
job satisfaction than was procedural justice. However, this does
not seem to fit the two-factor theory argument that procedural
justice predicts system-referenced outcomes, whereas distributive
justice predicts person-referenced outcomes. Job satisfaction is a
more general, multifaceted, and global response than is outcome
satisfaction. Consistent with this reasoning, other studies have
shown high correlations between procedural justice and job satis
faction (e.g., Mossholder, Bennett, & Martin, 1998; Wesolowski &
Mossholder, 1997). In addition, Masterson, Lewis, et al. (2000)
showed procedural justice to be a stronger predictor of job satis
faction than interactional justice, although both had significant
independent effects. These results are consistent with the two-
factor model and the agent-system model.
Organizational commitment. Organizational commitment rep
resents a global, systemic reaction that people have to the company
for which they work. Most measures of organizational commit
ment assess affective commitment, the degree to which employees
identify with the company and make the company’s goals their
own (Allen & Meyer, 1990). Prior work by Tyler (e.g., Tyler,
1990) argues that procedural justice has stronger relationships with
support for institutions than does distributive justice. This is also
consistent with the two-factor model and has been supported in
several studies (e.g., Folger & Konovsky, 1989; McFarlin &
Sweeney, 1992; Sweeney & McFarlin, 1993). However, we should
note that several studies have instead supported the distributive
dominance model. For example, Lowe and Vodanovich (1995)
found a stronger relationship for distributive justice and organiza
tional commitment than for procedural justice, as did Greenberg
(1994). Other results support the agent-system model, in which
procedural justice is a stronger predictor of organizational com
mitment than interactional justice (Masterson, Lewis, et al., 2000).
Trust. Trust has recently emerged as a popular topic in orga
nizational research (as evidenced by the 1998 Academy of Man
agement Review special issue devoted to the topic). Tyler (1989)
argued that trust in decision makers or authorities is important
because these people typically have considerable discretion in
terms of allocating rewards and resources. Whereas Tyler (1989)
initially conceptualized trust in relation to a third party or an
authority, Folger and Cropanzano (1998) made the point that trust
reactions are relevant to any person with whom one is interdepen
dent. Given the centrality of trust in theorizing on procedural
justice, we would expect to find stronger relationships between
trust and procedural justice than between trust and distributive
justice, consistent with past research (e.g., Alexander & Ruder
man, 1987; Konovsky & Pugh, 1994). However, given that trust is
usually referenced to a particular person, the agent-system model
would predict that interpersonal and informational justice are even
better predictors of this outcome than procedural justice.
Evaluation of authority. A number of studies of third-party
dispute resolution procedures have asked disputants to make eval
uations of the third party (Lind & Tyler, 1988). Still other work in
organizations asks respondents to rate the acceptability of their
supervisors or management in more general terms. Much of the
research on evaluation of authorities comes from work merging
psychology and political science (e.g., Tyler, 1990). Tyler’s (1990)
work, along with the two-factor model, would suggest that we
should find stronger relationships between procedural justice and
evaluation of authorities than between distributive justice and
evaluation of authorities. However, as with organizational com
mitment, this prediction has been supported in multiple studies
(e.g., Ball, Trevino, & Sims, 1993; McFarlin & Sweeney, 1992)
430 COLQUITT. CONLON, WESSON, PORTER, AND NG
and refuted in multiple studies (e.g., Conlon, 1993; Taylor, Tracy,
Renard, Harrison, & Carroll, 1995). In addition, the agent-system
model would predict that interpersonal and informational justice
are better predictors of evaluation of authority in cases in which
the authority in question is one’s leader as opposed to management
in general. For this reason, our examination of the reactive models
distinguishes between agent-referenced evaluations of authority
(e.g., focusing on one’s supervisor) and system-referenced evalu
ations of authority (e.g., focusing on management in general).
Organizational citizenship behaviors (OCBs). Organ (1990)
defined OCBs as behaviors that are discretionary and not explicitly
rewarded but that can help improve organizational functioning.
Organ (1990) posited that OCBs are driven largely by fairness
perceptions. He suggested that people in organizations assume, at
the outset, a social exchange relationship. This expectation con
tinues until unfairness is evidenced, at which time the relationship
is reinterpreted as economic rather than social. Research on OCBs
has repeatedly demonstrated stronger linkages between procedural
justice and OCBs than between distributive justice and OCBs
(Ball, Trevino, & Sims, 1994; Moorman, 1991). For example,
Moorman (1991) reported that procedural justice influenced four
of five OCB dimensions, whereas distributive justice failed to
influence any dimensions. Skarlicki and Latham (1996) even
showed that training supervisors on procedural justice principles
was capable of improving OCB levels. To the extent that OCBs
were measured in relation to supervisors rather than the organiza
tion as a whole, we would expect interpersonal and informational
justice to be stronger predictors, consistent with the agent-system
model and the results of Masterson, Lewis, et al. (2000). Thus, our
examination of the reactive models distinguishes between agent-
referenced OCBs and system-referenced OCBs. Following Wil
liams and Anderson (1991), we refer to the former as individual
OCBs (OCBIs) and the latter as organization OCBs (OCBOs).
Withdrawal. Behaviors and behavioral intentions such as ab
senteeism, turnover, and neglect are often subsumed under the
heading of job withdrawal. Although withdrawal is a relatively
common outcome in the justice literature, it has not been examined
in the context of the two-factor model. Withdrawal can occur as a
result of a thorough, reasoned evaluation of the organization as a
system or on a more “spur of the moment” basis in reaction to an
unsatisfactory outcome or poor interpersonal treatment by an au
thority. However, because employees who withdraw are typically
leaving the overall organization, we would argue that withdrawal
is system referenced in nature, similar to organizational commit
ment. Unfortunately, the literature linking different justice dimen
sions to withdrawal is somewhat muddied, with some studies
showing that distributive justice influences job withdrawal (e.g.,
Hom, Griffeth, & Sellare, 1984) and other studies revealing effects
for procedural justice (e.g., Dailey & Kirk, 1992). Moreover,
Masterson, Lewis, et al. (2000) showed that procedural justice had
more of an impact on withdrawal than interactional justice. Thus,
past research has, at various times, supported the distributive
dominance model, the two-factor model, and the agent-system
model.
Negative reactions. Some recent justice research has looked at
the relationship between perceived unfairness and a variety of
negative reactions, such as employee theft (e.g., Greenberg, 1990a,
1993c) and organizational retaliatory behaviors (ORBs; Skarlicki
& Folger, 1997; Skarlicki, Folger, & Tesluk, 1999). As with
withdrawal, negative reactions have not been examined from the
standpoint of the two-factor model. Whereas negative reactions
can occur because of purely cognitive evaluations of the merits of
the organization as a whole or as strong emotional reactions to
one’s own treatment, reactions such as theft and ORBs clearly
damage the larger organizational system. However, Skarlicki and
Folger (1997) found that ORBs had approximately equal correla
tions with distributive, procedural, and interactional justice, with
interactional justice having the strongest unique effect. To the
extent that ORBs are system-referenced outcomes, this provides
little support for any of the three reactive models.
Performance. Perhaps the most unclear of all relationships in
the justice literature is the relationship between procedural justice
and performance. For example, Earley and Lind (1987) found a
relationship between procedural fairness judgments and perfor
mance in a laboratory study but not in a field study. Kanfer,
Sawyer, Earley, and Lind (1987) found a negative correlation
between procedural justice and performance. Keller and Dansereau
(1995) found a moderately strong relationship between procedural
justice and performance as measured by performance appraisal
records. Other studies have linked distributive justice to perfor
mance, consistent with equity theory’s predictions (e.g., Ball et al.,
1994; Griffeth, Vecchio, & Logan, 1989). It is difficult to apply the
logic of the agent-system and two-factor models to the prediction
of performance. On the one hand, performance supports, and is
often measured by, agents such as one’s supervisor. For this
reason, Masterson, Lewis, et al. (2000) predicted, and found,
stronger interactional justice effects on performance, consistent
with the agent-system model. On the other hand, performance
reflects members’ contributions to organizational goals (Borman,
1991), giving it a system-referenced character and suggesting that
procedural justice should be its primary predictor.
Different Operationalizations of Procedural Justice
Of course, the relative strength of the correlations between the
justice dimensions and the outcomes just described may depend on
how procedural justice is operationalized. For example, some
studies assess only process control but label it procedural justice
(e.g., Joy & Witt, 1992). Others use a variable that is composed
only of Leventhal criteria, labeling that procedural justice (e.g.,
Konovsky & Folger, 1991). Still others measure informational or
interpersonal justice as the process variable (e.g., Greenberg,
1990a). Another common operationalization is measuring proce
dural fairness perceptions (e.g., Bies, Martin, & Brockner, 1993;
Colquitt & Chertkoff, 1996; Gilliland, 1994), which is what Lind
and Tyler (1988) labeled a direct measure (i.e., a measure that
directly asks respondents “how fair” a procedure is). Finally,
another common operationalization is an indirect combination
measure (Lind & Tyler, 1988). Such a measure asks respondents
about some combination of process control, Leventhal criteria, and
interpersonal or informational justice, labeling that procedural
justice (e.g., Brockner et al., 1995, 1997; Folger & Konovsky,
1989; Konovsky & Folger, 1991; Mansour-Cole & Scott, 1998;
Skarlicki & Latham, 1997). Presumably, those who use such
measures subscribe to the view that interpersonal and informa
tional justice are facets of procedural justice, as with process
control or Leventhal criteria.
META-ANALYTIC REVIEW OF ORGANIZATIONAL JUSTICE 431
Our examination of the relative strength of the correlations
between the different dimensions of justice and the outcomes
described uses the broadest conceptualization of procedural justice
by combining all of its potential operationalizations. However, our
review also presents analyses broken down by operationalization.
One strength of meta-analysis is that it allows a researcher to
examine the degree to which a relationship varies across a partic
ular moderator variable. Our review examines operationalization
as a moderator variable, allowing us to see to what extent rela
tionships vary by how procedural justice is conceptualized. For
instance, one might expect that procedural fairness perceptions
will yield the highest relationships with organizational outcomes,
in that fairness perceptions could be construed as the intervening
mechanism linking process control, Leventhal criteria, and so forth
to outcomes. Conversely, one might expect indirect combination
measures to yield the highest relationships, because they capture
more of the conceptual domain of organizational justice.
Method
We conducted a meta-analytic review of the literature on organizational
justice to examine the questions discussed earlier. In the following sec
tions, we review the methods for this review.
Literature Search
We first performed a literature search of the PsycINFO database for the
years 1975 to 1999. Our starting date coincided with the year in which
Thibaut and Walker (1975) introduced the procedural justice construct.
Given that a major goal of this review was to examine the relative impact
of multiple dimensions of justice, articles published before 1975 would be
less useful. Such articles were typically proactive distributive justice arti
cles that examined how individuals allocate rewards across different situ
ations and did not normally assess any of the outcomes examined in this
review. Moreover, from a practical perspective, articles published before
1975 rarely reported the types of statistics included in a meta-analysis. We
conducted our literature search using the following keywords: procedural
fairness, procedural justice, distributive fairness, distributive justice, inter
actional justice, interpersonal treatment, and equity. In addition to the
PsycINFO search, we conducted an author search of 10 of the most
published authors in the organizational justice literature. Any article that
included a relationship in the meta-analysis, whether it was a single
justice-outcome relationship or a relationship between two dimensions of
justice, was relevant.
The search yielded 300 articles. Of these 300 articles, 76 did not include
a relationship in the meta-analysis and were deemed not relevant. For
example, Tyler, Lind, Ohbuchi, Sugawara, and Huo (1998) examined the
effects of ‘‘relational judgments” (an aggregate measure of procedural,
interpersonal, and informational justice judgments) on the willingness of
disputants to accept a third-party solution in a conflict resolution setting.
Bazerman, Schroth, Shah, Diekmann, and Tenbrunsel (1994) examined the
effects of justice on job search decisions. Such studies did not focus on one
of the nine outcome variables included in our review or did not include a
relationship between different dimensions of justice.
Another 41 studies included a relationship in the meta-analysis but could
not be coded because of the way in which the results were presented.
Meta-analysis requires zero-order effect size information, whether in the
form of correlations, F statistics, t statistics, or even means and standard
deviations of a dependent variable across multiple experimental conditions.
Articles that present only partial or semipartial unique, independent effects
cannot be coded unless the independent variables are uncorrelated, as in
most experiments in which conditions are manipulated orthogonal to one
another. Several articles uncovered in our literature review could not be
coded because they presented only multiple regression or structural equa
tion modeling results. Examples included several of Tyler’s investigations
of the “relational” or “group-value” model of justice (e.g., Tyler, 1989,
1994; Tyler, Degoey, & Smith, 1996). Other articles could not be coded
because they presented incomplete results (e.g., only labeling F statistics in
an analysis of variance as significant or not significant) or combined
procedural and distributive justice into a larger justice variable (e.g.,
Martocchio & Judge, 1995).
The final number of studies included in the review was 183. These
studies are marked with an asterisk in the References section. We should
note that this number included both laboratory studies and field studies; the
term organizational justice in no way implies that the research must occur
in a field setting but indicates only that the research must be relevant to the
role of fairness in the workplace (Greenberg, 1990b).
Meta-Analysis Strategy
Meta-analysis is a technique that allows individual study results to be
aggregated while correcting for various artifacts that can bias relationship
estimates. Our meta-analyses were conducted with Hunter and Schmidt’s
(1990) procedures. Inputs into the meta-analyses included zero-order effect
sizes in the form of correlations, along with sample sizes and reliability
information. In instances in which articles reported statistics other than
correlations (e.g., F statistics, t statistics, or means and standard devia
tions), results were transformed into correlations through the formulas
provided by Hunter and Schmidt (1990). Because of the subjectivity and
judgment calls inherent in meta-analytic efforts, all coding of meta-analytic
data was performed by author dyads formed from the study’s five authors.
In cases in which a variable was assessed with multiple measures, we
acted in accordance with Hunter and Schmidt’s (1990) recommendations
for conceptual replication (see pp. 451-463). Specifically, when multiple
measures were highly correlated and seemed to each be construct valid, the
correlations were averaged together (see Hunter & Schmidt, 1990, p. 457).
Thus, one composite correlation was formed in lieu of multiple correla
tions, preventing a study that involved multiple measures from being
“double counted.” This technique improves both reliability and construct
validity. We should also note that, when an article reported results from
multiple independent samples, each correlation was included in the meta
analysis (see Hunter & Schmidt, 1990, pp. 463-466, for a discussion of
these issues).
Meta-analysis requires that each observed correlation from a given study
be weighted by that study’s sample size to provide a weighted mean
estimate of the population correlation. The standard deviation of this
estimate across the multiple studies is also computed. This variation is
composed of true variation in the population value as well as variation due
to artifacts such as sampling error and measurement error. To provide a
more accurate estimate of each population correlation and its variability,
our analyses corrected for both sampling error and unreliability. However,
because reliability information was not always available, the method of
artifact-distribution meta-analysis was used (Hunter & Schmidt, 1990). For
those studies that did not report reliability information for any given
variable, that variable’s weighted mean reliability based on all other studies
was used to correct for measurement error.
Meta-analysis results typically include both uncorrected (r) and cor
rected (rc) estimates of the population correlation. The latter are corrected
for unreliability in both variables. Also reported are the 95% confidence
intervals for each population correlation. Confidence intervals are gener
ated with the standard error of the weighted mean correlation. They reflect
the “extent to which sampling error remains in the estimate of a mean
effect size” and are applied to estimates that have not been corrected for
artifacts (Whitener, 1990, p. 316). If a confidence interval does not include
the value of zero, that population correlation is judged to be “statistically
significant.”
Also presented is the standard deviation of the population correlation
(SDrc). This provides an index of the variation in the corrected population
432 COLQUITT, CONLON, WESSON, PORTER, AND NG
values across the studies in our sample. One indication that moderators
may be present in a given relationship is the case in which artifacts such as
unreliability fail to account for a substantial portion of the variance in
correlations. Thus, the percentage of variance explained by artifacts (VOT)
is also presented. Hunter and Schmidt (1990) have suggested that, if
artifacts fail to account for 75% of the variance in the correlations,
moderators probably exist. Mathieu and Zajac (1990) and Hom, Caranikas
Walker, Prussia, and Griffeth (1992) amended the 75% criterion to 60% in
cases in which range restriction is not one of the artifacts that is corrected
for. We should note that the 60% rule only implies the existence of a
moderator; it does not indicate what variable is acting as the moderator.
Identifying the actual moderator variable requires coding potential mod
erators and then performing subgroup analyses to determine whether the
population correlations vary across the subgroup boundaries. In our review,
this entailed determining whether the population correlations varied across
different operationalizations of procedural justice.
Meta-Analytic Regression Strategy
Many questions cannot be answered by a matrix of meta-analyzed
correlations. For example, do Leventhal’s (1980) justice criteria explain
variance in procedural fairness perceptions beyond the effects of Thibaut
and Walker’s (1975) process control construct? Do procedural, distribu
tive, interpersonal, and informational justice each have independent effects
on organizational commitment? Such questions require multiple regression
to assess independent, semipartial effects. Fortunately, recent advances in
meta-analytic regression have allowed researchers to combine the benefits
of meta-analysis with the strengths of regression procedures (see Viswes
varan & Ones, 1995). Meta-analytic regression has been used in contexts
such as training motivation (Colquitt, LePine, & Noe, 2000), leadership
(Podsakoff, MacKenzie, & Bommer, 1996), turnover (Hom et al., 1992),
and job performance (Schmidt, Hunter, & Outerbridge, 1986).
In practice, there are some decision points that researchers using meta-
analytic regression will encounter (Viswesvaran & Ones, 1995). First,
many researchers will conduct regressions on correlation matrices that vary
in sample size. This raises the question of what sample size to use when
computing the standard errors associated with the regression weights.
Potential solutions include using the smallest cell sample size or using the
mean sample size. We chose to use the harmonic mean of the correlation
matrix sample sizes, as opposed to the arithmetic mean (consistent with
Viswesvaran & Ones, 1995). The formula for the harmonic mean is
[k/(lW1 + 1W2 + ■·· + 1/AJ], where к refers to the number of study
correlations and N refers to the sample sizes of the studies. An inspection
of the formula shows that the harmonic mean gives much less weight to
substantially large individual study sample sizes, so it is always more
conservative than the arithmetic mean (Viswesvaran & Ones, 1995). Note,
however, that the sample size issue is not very critical to the current
meta-analytic review. This is because the sample sizes for almost all of the
cells of the correlation matrices are in the thousands, making even small
effect sizes statistically significant, no matter what sample size option is
used.
Second, researchers must choose whether to use maximum-likelihood
estimation (the choice of Hom et al., 1992), ordinary least squares (the
choice of Colquitt et al., 2000, Podsakoff et al., 1996, and Schmidt et al.,
1986), or some other method. We elected to use ordinary least squares
estimation, consistent with Colquitt et al. (2000), Podsakoff et al. (1996),
and Schmidt et al. (1986). Ordinary least squares assumptions are less
restrictive than maximum likelihood, which assumes multivariate normal
ity. Maximum-likelihood estimation is also less optimal in instances in
which the data are in the form of correlations rather than covariances
(Cudeck, 1989). Given that meta-analysis results in correlational data, we
believed that ordinary least squares would be more appropriate.
Results
Construct Discrimination Questions
Research Question I concerned the magnitude of the relation
ships among the various organizational justice conceptualizations.
Table 1 shows the correlations among process control, Leventhal
criteria, interpersonal justice, informational justice, distributive
justice, and procedural fairness perceptions. Cohen and Cohen
(1983) classified correlations as high, moderate, or weak according
to uncorrected r values of .50, .30, and .10, respectively. Thus,
Table 1 shows high correlations among the justice conceptualiza
tions, but not so high that they seem to be multiple indicators of
one underlying construct. Process control and Leventhal criteria,
the two original operationalizations of procedural justice, were
highly correlated with each other (r = .50, rc = .67) and with
procedural fairness perceptions (r = .41, rc = .51 and r = .53, rc =
.68, respectively). However, the relationship between Leventhal
criteria and procedural fairness perceptions was significantly
stronger than the relationship between process control and proce
dural fairness perceptions, as evidenced by the fact that the two
correlations’ confidence intervals did not overlap.
Table 1 also shows the correlations among the interactional
justice dimensions. Interpersonal justice was highly related to
informational justice (r = .57, rc = .66), although again not so
highly that the two necessarily seem to be indicators of the same
underlying construct. Interpersonal justice and informational jus
tice were also highly correlated with procedural fairness percep
tions (r = .56, rc = .63 and r = .51, rc = .58, respectively). These
relationships were similar in magnitude to the process control and
Leventhal relationships, although the interpersonal justice
procedural fairness relationship was significantly stronger than the
process control-procedural fairness relationship.
Interestingly, the relationships between interpersonal and infor
mational justice and procedural fairness perceptions were not
significantly stronger than the relationship between distributive
justice and procedural fairness perceptions (r = .48, rc = .57).
This suggests that interpersonal and informational justice should
be considered to be distinct from procedural justice, just as the case
with distributive justice. The uncorrected correlation of .48 for
distributive justice and procedural fairness perceptions may seem
surprisingly low, given the many empirical articles that have
reported uncorrected relationships in the .60s and .70s. To take a
closer look at this relationship. Table 2 shows relationships be
tween distributive justice and every possible conceptualization of
procedural justice, including interpersonal and informational jus
tice, to explore whether operationalization moderates the proce
dural justice-distributive justice relationship. The top row of Ta
ble 2, labeled “Broadly defined procedural justice,” shows the
procedural justice-distributive relationship in which all potential
operationalizations, shown in the remaining rows, are considered
together. The final row contains the “indirect combination mea
sure” operationalization discussed previously. Recall that indirect
combination measures are those that assess some combination of
process control, interpersonal or informational justice, and Lev
enthal variables. They are labeled indirect because they do not
directly ask “how fair” something is (see Lind & Tyler, 1988).
Combining all operationalizations, broadly defined procedural
justice was strongly related to distributive justice (r = .56, rc =
.67). The high standard deviation of the population correlation
META-ANALYTIC REVIEW OF ORGANIZATIONAL JUSTICE 433
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(SDrc = .23) and the low variance explained from artifacts
(Vatt = 2.74%) show that moderators exist in the broadly defined
procedural justice-distributive justice relationship. Operational
ization explains some of that variation, in that the highest relation
ship was evident when an indirect combination measure was used
0 = .63, r. = .77). Moreover, because their confidence intervals
do not overlap, Table 2 shows that the indirect combination mea
sure relationship is significantly stronger than the more unidimen
sional justice measures: procedural fairness perceptions (r = .48,
rc = .57), process control (r = .27, rc = .34), Leventhal criteria
(r = .46, r, = .55), interpersonal justice (r = .38, rc = .42), and
informational justice (r = .39, rc = .46).
Proactive Research Questions
Research Question 2 explored whether the additional conceptu
alizations of justice over the course of its history have contributed
incremental variance explained in regard to promoting procedural
fairness perceptions. This was tested by regressing procedural
fairness perceptions onto the various justice operationalizations
using hierarchical regression. Order of entry was based on histor
ical introduction, so the following steps were used: (a) Thibaut and
Walker’s (1975) process control operationalization, (b) Lev
enthal’s (1980) justice criteria operationalization, and (c) Bies and
Moag’s (1986) interactional justice construct, broken down into
interpersonal and informational justice (as in Greenberg, 1993b).
The meta-analytic regression results are shown in Table 3. The
original operationalization of procedural justice, process control,
explained 26% of the variance in procedural fairness perceptions,
with higher levels of process control producing more favorable
fairness perceptions (ß = .51). Leventhal criteria explained an
additional 21% of the variance, with higher levels of his criteria
also producing more favorable perceptions (ß = .61). Interper
sonal and informational justice explained an additional 6% of the
variance in fairness perceptions. That effect was due primarily to
interpersonal justice (ß = .29), although informational justice also
had a significant effect (ß = .11).
Research Question 3 asked how much variance the justice
operationalizations explained in procedural fairness perceptions
beyond the effects of distributive justice. This was tested by
regressing procedural fairness perceptions onto the various justice
operationalizations after controlling for distributive justice. These
regression results are shown in Table 4. Distributive justice ex
plained 33% of the variance in procedural fairness perceptions,
with higher levels of distributive justice being associated with
more favorable fairness perceptions (ß = .57). The remaining
justice operationalizations explained an incremental 24% of the
variance. However, only two operationalizations had strong unique
effects: Leventhal criteria (ß = .30) and interpersonal justice (ß =
.26). Although statistically significant, the unique effects of pro
cess control (ß = .03) and informational justice (ß = .07) were not
practically significant.
Reactive Research Questions
Research Questions 4-6 explored the relationships between the
organizational justice dimensions and several key outcome vari
ables. Table 5 presents the results for these research questions.
Research Question 4 explored the relationships between distribu-
434 COLQUITT, CONLON, WESSON, PORTER, AND NG
Table 2
Relationship Between Distributive and Procedural Justice Conceptualizations
(Including Interpersonal and Informational Justice)
Conceptualization
Distributive justice
r (95% CI) N (SDrO k (N) Vm (%)
Broadly defined procedural justice .56 (.52, .60) .67 (.23) 92 (42,576) 2.74
Procedural fairness perceptions .48 (.41, .55) .57 (.28) 45(13,418) 3.41
Process control .27 (.22, .33) .34 (.13) 23(5,137) 24.15
Leventhal criteria .46 (.38, .54) .55 (.17) 15 (4,743) 8.27
Interpersonal justice .38 (.26, .50) .42 (.20) 9 (3,496) 5.62
informational justice .39 (.32, .47) .46 (.15) 14 (3,807) 13.19
Indirect combination measure .63 (.59, .66) .77 (.14) 54 (51,446) 2.32
Note, r = uncorrected population correlation; Cl = confidence interval around uncorrected population
correlation; rc = corrected population correlation; SDrc = standard deviation of corrected population correlation;
к = number of studies; Vart = percentage of variance in rc explained by study artifacts.
tive justice and the outcomes. Distributive justice had high corre
lations with outcome satisfaction (r = .52, rc — .61), job satisfac
tion (r = .46, rc = .56), organizational commitment (r = .42, r,. =
.51), trust (r = .48, rc = .57), agent-referenced evaluation of
authority (r = .53, = .59), and withdrawal (r = —.41, rc =
—.50). Distributive justice had moderate correlations with system-
referenced evaluation of authority (r = .30, rc = .37), OCBOs (r =
.20, rc = .25), and negative reactions (r = —.26, ra = —.30) and
was weakly related to OCBIs (r = .13, rc = .15) and performance
(r = .13, rc = .15).
Research Question 5 explored relationships between procedural
justice and the same set of outcomes. Combining all conceivable
procedural justice conceptualizations, again labeled broadly de
fined procedural justice, we see that procedural justice had high
correlations with outcome satisfaction (r = .40, rc = .48), job
satisfaction (r = .51, rc = .62), organizational commitment (r =
.48, rc = .57), trust (r = .52, rc = .61), and agent-referenced
evaluation of authority (r = .56, rc = .64). Procedural justice had
moderate correlations with system-referenced evaluation of au
thority (r = .35, rc = .42), OCBOs (r = .23, rc = .27), withdrawal
(r = —.36, re = —.46), negative reactions (r = —.Ti, rc = —.31),
and performance (r = .30, = .36). Finally, procedural justice
had weak correlations with OCBIs (r = .19, rc = .22). Table 5 also
shows that moderators were present in the procedural justice
outcome relationships, with the exception of the relationships with
the OCB variables. Operationalization could be one potential mod
erator for several of the outcome variables, because the indirect
Table 3
Incremental Effects of Justice Operationalizations on
Procedural Fairness Perceptions
Regression step Total R2 Δ/?2 В
1. Process control .26* .26* .51*
2. Leventhal criteria .47* .21* .61*
3. Interpersonal justice .53* .06* .28*
Informational justice .11*
Note. N – 4,165 (based on the harmonic mean sample size of the Table 1
cells used in this regression).
*p< .05.
combination measure was significantly more related to job satis
faction, organizational commitment, and withdrawal than was any
other operationalization.
Research Question 6 explored relationships between interper
sonal and informational justice and the outcome variables. Inter
personal justice was strongly related to agent-referenced evalua
tion of authority (r = .57, rc = .62) and moderately related to job
satisfaction (r = .31, rc = .35), system-referenced evaluation of
authority (r = .20, rc = .23), OCBIs (r = .23, rc = .29), and
negative reactions (r = —.30, rc = —.35). It was weakly related to
outcome satisfaction (r = .19), organizational commitment (r =
. 16, rc = .19), withdrawal (r = —.02, rc = —.02), and performance
(r = .03, r^ = .03). Informational justice was strongly related to
trust (r = .43, rc = .51), agent-referenced evaluation of authority
(r = .58, rc = .65), and system-referenced evaluation of authority
(r = .42, r = .47) and was moderately related to outcome
satisfaction (r = .27, rc = .30), job satisfaction (r = .38, rc = .43),
organizational commitment (r = .26, r^ = .29), OCBIs (r = .21,
rc = .26), withdrawal (r = —.21, re = —.24), and negative
reactions (r = — .29, rc = — .33). It was weakly related to OCBOs
(r = .18) and performance (r = .11, rc = .13).
Research Question 7 examined the unique effects of the justice
dimensions on the outcome variables considered simultaneously.
Table 6 presents beta weights derived from regressing each of the
outcomes on all four justice dimensions simultaneously. The table
also presents unique R2 values derived from a “usefulness analy
sis” in which the effects of one justice dimension were examined
after controlling for the others. The table also presents the total
variance explained in each outcome by the justice dimensions.
Note that, in some cases, the interpersonal justice beta weights
were reversed in sign from that dimension’s correlations. This was
due to the multicollinearity in some of the regressions. If hierar
chical regression had been used and interpersonal justice had been
entered in a step before procedural and informational justice were
entered, the signs of the beta weights would not have been
reversed.
The regression results in Table 6 allowed us to examine the
adequacy of the distributive dominance, two-factor, and agent
system reactive models. Leventhal’s (1980) distributive domi
nance model would predict higher unique effects for distribu-
META-ANALYTIC REVIEW OF ORGANIZATIONAL JUSTICE 435
Table 4
Incremental Effects of Justice Operationalizations on Procedural
Fairness Perceptions Beyond Distributive Justice Effects
Regression step Total R2 Δ«2 В
1. Distributive justice .33* .33* .57*
2. Process control .57* .24* .03*
Leventhal criteria .30*
Interpersonal justice .26*
Informational justice .07*
Note. N = 4,165 (based on the harmonic mean sample size of the Table 1
cells used in this regression).
* p < .05.
tive justice than for the other three justice forms. This
prediction was supported for two outcomes (outcome satisfac
tion and withdrawal) and was refuted for the remaining nine
outcomes.
Sweeney and McFarlin’s (1993) two-factor model would predict
higher unique effects of distributive justice for person-referenced
outcomes and higher unique effects of procedural justice for
system-referenced outcomes. This prediction was supported for
five outcomes (outcome satisfaction, job satisfaction, organiza
tional commitment, system-referenced evaluation of authority, and
performance) and was refuted for three outcomes (OCBOs, with
drawal, and negative reactions). The two-factor model was not
relevant to the three agent-referenced outcomes (agent-referenced
evaluation of authority, trust, and OCBIs).
Bies and Moag’s (1986) agent-system model would predict
higher unique effects of interpersonal or informational justice for
agent-referenced outcomes and higher unique effects of procedural
justice for system-referenced outcomes. This prediction was sup
ported for five outcomes (job satisfaction, organizational commit
ment, agent-referenced evaluation of authority, OCBIs, and per
formance) and refuted for five outcomes (system-referenced
evaluation of authority, trust, OCBOs, withdrawal, and negative
reactions). The agent-system model was not relevant to person-
referenced outcomes such as outcome satisfaction.
Discussion
This meta-analytic review, consisting of 120 separate meta
analyses of 183 empirical studies, explored three types of research
questions to aid further theory development in the organizational
justice literature. The first type of question was related to construct
discrimination (i.e., how highly related are the various facets of
organizational justice?). Process control and Leventhal criteria, the
two original procedural justice operationalizations, were highly
correlated, although perhaps not as highly as one would think
given that they are used interchangeably to express the same
construct. Similarly, interpersonal and informational justice were
highly correlated, but again not so highly that it seems prudent to
lump them together under the “interactional justice” label. Indeed,
their correlation was not significantly higher than the correlation
between procedural justice and distributive justice, two constructs
whose separation has become canon. Further analyses showed that
the procedural justice-distributive justice relationship varies to
some degree by how the researcher operationalizes the former. The
relationship is strongest when an indirect combination measure is
used and weaker when procedural fairness perceptions, Leventhal
criteria, and especially process control are used.
The second type of research question dealt with proactive re
search, which is concerned with creating procedural fairness per
ceptions by adhering to certain rules, such as providing process
control, being consistent, treating people with sensitivity, or ex
plaining things adequately. Our results showed that the historical
progression of proactive research on procedural justice has in fact
contributed to our ability to promote procedural fairness percep
tions. The original conceptualization, Thibaut and Walker’s (1975)
process control, predicted procedural fairness perceptions, but
Leventhal’s (1980) criteria contributed significant incremental
variance. Indeed, it is worth noting that the Leventhal criteria had
a significantly stronger relationship to procedural fairness percep
tions than did process control. In fact, the Leventhal criteria are
even more impressive when we consider that they predicted almost
as much variance in procedural fairness perceptions as process
control, even when entered in a later step in the regression
analysis.
The concepts of interpersonal and informational justice, drawn
from the field’s recent interest in interactional justice, show a more
mixed pattern of results. Their correlations with procedural fair
ness perceptions were just as strong as the correlations for Lev
enthal criteria. However, although they explained significant in
cremental variance in fairness perceptions, their contribution was
small in comparison with the contributions of the other justice
facets. Thus, interpersonal and informational justice, when con
sidered alone, were powerful predictors of procedural fairness
perceptions. When considered in conjunction with structural facets
of procedural justice, their contribution was less important, partic
ularly in the case of informational justice. Perhaps this is not
surprising considering that informational justice often provides the
opportunity to judge structural qualities of procedural justice
(Greenberg, 1993b).
Because it is well known that the fairness of decision-making
procedures is often judged according to the kinds of outcomes one
receives (Lind & Tyler, 1988), it is also important to show that the
various conceptualizations of procedural justice are important even
after control for distributive justice. If this had not been the case,
then the procedural justice literature would have contributed little
over earlier work by Homans (1961), Adams (1965), Leventhal
(1976), and Deutsch (1975). Our results showed that, when dis
tributive justice was controlled, only Leventhal criteria and inter
personal justice retained their explanatory power. Because process
control added little, it is tempting to conclude that measuring it is
unnecessary if distributive justice and Leventhal criteria are also
being considered. Perhaps this is not surprising given Lind and
Tyler’s (1988) assertion that Leventhal’s “representativeness” cri
terion includes the process control concept.
Turning to our third type of research question, reactive research,
we tested three separate reactive models: Leventhal’s (1980) dis
tributive dominance model, Sweeney and McFarlin’s (1993) two-
factor model, and Bies and Moag’s (1986) agent-system model.
Support for these models can be evaluated by examining the
relative effects of distributive, procedural, interpersonal, and in
formational justice on the basis of the size of their meta-analytic
correlations, as well as their unique effects in the meta-analytic
regressions. We find little support for the distributive dominance
436 COLQUITT, CONLON, WESSON, PORTER, AND NG
Table 5
Relationships Between Organizational Justice Dimensions and Outcome Variables
Dimension r (95% CI) % «DrJ k (N)
van(%) r (95% CI) % W к IN)
vart (%)
Outcome satisfaction Job satisfaction
Broadly defined procedural justice .40 (.35, .46) .48 (.18) 30 (8,073) 10.02 .51 (.46, .56) .62 (.18) 40 (31,774) 2.88
Procedural fairness perceptions .45 (.36, .54) .53 (.17) 11 (4,420) 6.59 .33 (.28, .38) .40 (.09) 11 (4,958) 24.00
Process control .38 (.27, .48) .45 (.16) 8(1,774) 14.74 .30 (.25, .35) .37 (.05) 5 (2,577) 50.39
Leventhal criteria .25 (.13, .37) .32 (.17) 6(1,796) 13.03 .36 (.33, .40) .42 (.00) 4(2,315) 100.00
Interpersonal justice .19 1 (301) .31 (.26,.36) .35 (.02) 2(1,795) 65.96
Informational justice .27 (.21, .33) .30 (.04) 4(1,404) 65.02 .38 (.34, .42) .43 (.00) 2(1,872) 100.00
Indirect combination measure .47 (.39, .54) .54 (.15) 14 (2,242) 18.87 .55 (.49, .61) .68 (.17) 22(25,221) 2.07
Distributive justice .52 (.46, .59) .61 (.20) 28 (9,321) 5.07 .46 (.42, .49) .56 (.09) 24 (57,515) 8.31
Organizational commitment Trust
Broadly defined procedural justice .48 (.44, .52) .57 (.18) 53 (33,455) 3.84 .52 (.44, .59) .61 (.20) 24 (4,522) 8.42
Procedural fairness perceptions .32 (.25, .39) .37 (.16) 18 (6,767) 9.58 .56 (.49, .64) .62 (.08) 7 (802) 39.78
Process control .22 (.18, .27) .27 (.05) 7 (2,898) 53.50 .40 (.30, .50) .47 (.13) 7(1,031) 26.54
Leventhal criteria .26 (.22, .29) .30 (.00) 5 (3,162) 100.00 .58 (.09, .99) .65 (.38) 2 (628) 1.23
Interpersonal justice .16 (.11, .20) .19 (.00) 2(1,824) 100.00
Informational justice .26 (.18, .34) .29 (.14) 10 (3,968) 12.01 .43 (.30, .57) .51 (.11) 3 (487) 30.21
Indirect combination measure .55 (.51, .58) .65 (.10) 26 (24,606) 6.10 .55 (.45, .66) .64 (.18) 10(2,169) 8.02
Distributive justice .42 (.38, .47) .51 (.13) 24 (27,805) 4.11 .48 (.40, .57) .57 (.13) 8 (1,735) 17.24
Evaluation of authority: Agent referenced Evaluation of authority: System referenced
Broadly defined procedural justice .56 (.52, .59) .64 (.11) 33 (20,034) 7.17 .35 (-31,-40) .42 (.13) 25 (9,708) 13.09
Procedural fairness perceptions .53 (.46, .60) .60 (.13) 13 (4,753) 8.76 .45 (.42, .48) .51 (.12) 14 (5,637) 11.63
Process control .42 (.35, .50) .50 (.14) 10 (3,436) 12.56 .12 (.05, .20) .16 (.00) 3(663) 100.00
Leventhal criteria .53 (.41, .64) .63 (.17) 7 (3,104) 4.86 .19 (.02, .36) .22 (.15) 3 (427) 29.27
Interpersonal justice .57 (.43, .71) .62 (.17) 5 (2,534) 3.44 .20 (.01, .38) .23 (.16) 3 (469) 22.95
Informational justice .58 (.46, .71) .65 (.21) 9 (3,210) 3.21 .42 (.29, .55) .47 (.15) 5(1,035) 14.94
Indirect combination measure .58 (.54, .62) .67 (.05) 9 (13,850) 6.65 .31 (.24, .38) .37 (.12) 11 (3,790) 17.96
Distributive justice .53 (.46, .61) .59 (.15) 13 (16,963) 1.96 .30 (.24, .36) .37 (.12) 13 (4,103) 20.64
OCBs: Individual referenced OCBs: Organization referenced
Broadly defined procedural justice .19 (.16, .22) .22 (.00) 15 (4,414) 100.00 .23 (.19, .26) .27 (.04) 15(3,176) 78.62
Procedural fairness perceptions .21 (.17, .25) .25 (.00) 2(1,872) 100.00 .21 1 (140)
Process control .16 (.12, .20) .21 (.00) 3 (2,000) 100.00 .14 1 (206)
Leventhal criteria .18 (.14, .23) .22 (.01) 3 (2,108) 85.39 .15 (.06, .24) .18 (.00) 2(431) 100.00
Interpersonal justice .23 (.18, .27) .29 (.00) 2(1,794) 100.00
Informational justice .21 (.17, .26) .26 (.00) 2(1,883) 100.00 .18 1 (206)
Indirect combination measure .19 (.14, .23) .22 (.02) 10(1,994) 90.18 .25 (.20, .30) .30 (.06) 9(1,961) 63.06
Distributive justice .13 (.09, .17) .15 (.02) 6 (2,633) 86.57 .20 (.14, .26) .25 (.00) 5 (903) 100.00
Withdrawal Negative reactions
Broadly defined procedural justice -.36 (-.42, -.31) -.46 (.20) 39 (24,273) 4.12 -.27 (-.33, -.21) -.31 (.18) 27 (6,275) 13.37
Procedural fairness perceptions -.27 (-.32, -.21) -.34 (.14) 21 (7,344) 14.46 -.33 (-.39, -.26) -.38 (.12) 13 (3,563) 22.15
Process control -.19 (-.27, -.10) -.24 (.14) 10(1,190) 39.94 -.23 (-.27, -.19) -.30 (.00) 3 (2,094) 100.00
Leventhal criteria -.23 (-.30, -.16) -.29 (.07) 6(1,431) 50.87 -.28 (-.35, -.22) -.35 (.06) 5 (2,308) 34.76
Interpersonal justice -.02 (-.13, .09) -.02 (.00) 2(316) 100.00 -.30 (-.35, -.26) -.35 (.04) 7 (2,707) 58.78
Informational justice -.21 (-.34, -.07) -.24 (.21) 8(1,692) 11.42 -.29 (-.34, -.24) -.33 (.06) 8(2,731) 45.25
Indirect combination measure -.44 (-.56, -.32) -.55 (.19) 6 (14,392) 1.11 -.20 (-.35, -.05) -.22 (.21) 7(1,807) 9.28
Distributive justice -.41 (-.46, -.37) -.50 (.12) 18(15,888) 7.45 -.26 (-.35, -.17) -.30 (.17) 13 (3,782) 12.27
Performance
Broadly defined procedural justice .30 (.21,-39) .36 (.29) 30 (8,317) 4.83
Procedural fairness perceptions .30 (.17, .43) .36 (.33) 18 (6,925) 2.71
Process control .14 (-.01,-29) .17 (.25) 8(1,002) 16.17
Leventhal criteria .08 (-.05, .21) ■ 10(.ll) 3 (501) 44.34
Interpersonal justice .03 (-.14, .20) .03 (.11) 2 (389) 34.78
Informational justice .11 (.00, .22) .13 (.11) 4(1,036) 29.79
Indirect combination measure .23 (.12, .35) .27 (.00) 7 (1,084) 23.83
Distributive justice .13 (.03, .22) .15 (.18) 13(2,294) . 18.43
Note. r = uncorrected population correlation; CI = confidence interval around uncorrected population correlation; r. = corrected population correlation;
SDr = standard deviation of corrected population correlation; к = number of studies; Vart = percentage of variance in rc explained by study artifacts;
OCBs = organizational citizenship behaviors.
META-ANALYTIC REVIEW OF ORGANIZATIONAL JUSTICE 437
Table 6
Unique Effects of Procedural, Interpersonal, Informational, and Distributive Justice on Outcome Variables
Outcome variable
Justice dimension
Total
R2Procedural Interpersonal Informational Distributive
Outcome satisfaction (N = 1,792)
ß .17* -.08* .02 .54*
Unique R2 .02* .00* .00 .18* .39*
Job satisfaction (N = 4,039)
ß .48* -.09* .13* .26*
Unique R2 .11* .01* .01* .04* .45*
Organizational commitment (N = 4,582)
ß .42* -.18* .07* .31*
Unique R2 .09* .02* .00* .06* .35*
Evaluation of authority: Agent-referenced (N = 4,517)
ß . .01 .27* .32* .32*
Unique R2 .00 .04* .05* .06* .57*
Evaluation of authority: System-referenced (N = 2,114)
ß .30* -.19* .44* .11*
Unique R2 .04* .02* .10* .01* .31*
Trust (N = 1,711)
ß
Unique R2
.31*
.05*
.21*
.03*
.30*
.05* .45*
OCBs: Individual referenced (N = 3,192)
ß .06* .19* .11* -.01*
Unique R2 .00* .02* .01* .00 .09*
OCBs: Organization referenced (N = 782)
ß
Unique R2
.12*
.01*
.11*
.01*
.12*
.01* .08*
Performance (N = 1,855)
ß .56* -.20* .07* -.07
Unique R2 .15* .02* .00* .00* .19*
Withdrawal (N = 1,919)
ß -.10* .23* -.21* -.51*
Unique R2 .01* .02* .02* .16* .33*
Negative reactions (N = 4,039)
ß -.06* -.18* -.12* -.14*
Unique R2 .00* .02* .01* .01* .16*
Note. Sample sizes are based on the harmonic mean of the sample sizes for the correlations among the justice and outcome variables. The procedural
justice variable includes process control, Leventhal criteria, and procedural fairness perceptions. OCBs = organizational citizenship behaviors.
* p < .05.
model, which predicts that distributive justice will have stronger
effects than the other justice dimensions. This model was sup
ported for outcome satisfaction and withdrawal but not for any of
the other nine outcomes.
The two-factor model predicts that procedural justice will have
stronger effects than distributive justice on system-referenced vari
ables but weaker effects than distributive justice on person-
referenced variables. This model seemed to receive support only
for person-referenced and system-referenced attitudes such as out
come satisfaction, job satisfaction, organizational commitment,
and system-referenced evaluation of authority. The two-factor
model’s predictions were not supported for more behavioral vari
ables such as OCBs, withdrawal, and negative reactions. The only
exception to this observation involved performance. Procedural
justice was more capable of predicting performance than distrib
utive justice, which supports the two-factor model if performance
is assumed to be a system-referenced outcome.
The agent-system model predicts that interpersonal or informa
tional justice will have stronger effects than procedural justice on
agent-referenced variables but weaker effects than procedural jus
tice on system-referenced variables. This model was supported for
agent-referenced outcomes, including agent-referenced evaluation
of authority and OCBIs, but not for trust, which was more related
to procedural and distributive justice. The agent-system model
was also supported for job satisfaction, organizational commit
ment, and performance. The model actually seems to underesti
mate the importance of interpersonal or informational justice for
behavioral variables. Interpersonal or informational justice was a
strong predictor of OCBOs, withdrawal, and negative reactions,
which would not have been predicted on the basis of the agent
system model.
Implications for the Organizational Justice Literature
The conceptualization, measurement, and analysis of organiza
tional justice depend in large part on a given study’s research
question, as well as the sample or setting used to examine it.
Nonetheless, the results of our review have some broad, general
implications for the justice literature as a whole.
Distinctiveness of justice dimensions. The construct discrimi
nation results suggest that procedural, interpersonal, and informa
tional justice are distinct constructs that can be empirically distin-
438 COLQUITT, CONLON, WESSON, PORTER, AND NG
guished from one another. We would therefore call for a
moratorium on indirect combination measures that combine the
three justice dimensions into a single variable. Thirty-five of the
studies included in our review used such measures (e.g., Brockner
et al., 1995, 1997; Folger & Konovsky, 1989; Konovsky & Folger,
1991; Mansour-Cole & Scott, 1998; Skarlicki & Latham, 1997).
Our review showed that procedural, interpersonal, and informa
tional justice have different correlates, and measuring the three
separately allows for further differences among the dimensions to
be examined.
Measurement of justice dimensions. It is also critical that
researchers devote more care and effort to the measurement of
justice dimensions. Some of the articles we reviewed used mea
sures that assessed, among supervisors, granting subordinates
voice, treating subordinates consistently, suppressing biases, being
respectful, and providing explanations. Such measures were la
beled “interactional justice” (e.g., Moorman, 1991; Skarlicki &
Latham, 1997), even though only the latter two are included in
Bies and Moag’s (1986) construct. Authors may have included
such items on the basis of Folger and Bies’s (1989) article on
“managerial responsibilities” for procedural justice, which listed
seven principles (process control, bias suppression, consistency,
feedback, justification, truthfulness, and courtesy) managers
should use to promote procedural justice. Not surprisingly, re
searchers using such measures have been forced to collapse the
interactional justice measure with their procedural justice measure
as a result of high intercorrelations (Mansour-Cole & Scott, 1998;
Skarlicki & Latham, 1997). Thus, more attention should be paid to
content validity, as in a recent study by Colquitt (2001), who
developed scales for the justice dimensions based on the seminal
works introducing them and validated the scales in two indepen
dent studies. ■
Distinguishing justice content from justice source. Relatedly,
future research should seek to separate the effects of justice con
tent from the effects of justice source. Procedural justice can be a
function of an organization, as when a formalized decision-making
system provides process control or consistency as a result of the
way in which it is structured (e.g., Adams-Roy & Barling, 1998;
Ehlen, Magner, & Welker, 1999; Skarlicki et al., 1999). Procedural
justice can also be a function of a decision-making agent, as when
a manager takes steps to involve subordinates in decisions or treat
subordinates consistently (e.g., Folger & Konovsky, 1989;
Konovsky, Folger, & Cropanzano, 1987; Korsgaard, Schweiger, &
Sapienza, 1995). Likewise, informational and interpersonal justice
can be fostered through organizational policies and initiatives (e.g.,
Konovsky & Folger, 1991; Mansour-Cole & Scott, 1998; Tansky,
1993) or through the actions of a decision-making agent (e.g.,
Bies, Shapiro, & Cummings, 1988; Greenberg, 1994; Moorman,
1991). It is difficult to draw conclusions from studies comparing
the effects of organization-originating procedural justice with
agent-originating interpersonal or informational justice because
source and content are confounded. Fortunately, recent research is
beginning to examine this important issue by crossing justice
source with justice content to assess their joint effects (Blader &
Tyler, 2000; Byrne & Cropanzano, 2000; Masterson, Bartol, &
Moye, 2000).
Including multiple justice dimensions in single studies. Our
results also clearly show that researchers can explain more out
come variance by including multiple justice dimensions within
single studies, although there are some diminishing returns asso
ciated with this strategy. Our proactive research results showed
that distributive justice, procedural justice (in terms of Leventhal
criteria), interpersonal justice, and, to a lesser extent, informational
justice each contribute uniquely to the creation of fairness percep
tions. Our reactive research results showed that procedural and
distributive justice are sufficient to adequately predict several
outcomes, and procedural and distributive justice were either the
strongest or second strongest predictors of 15 outcomes. However,
interpersonal and informational justice clearly contributed to the
prediction of other outcomes. For example, one or both of these
variables were strong independent predictors of behavioral out
comes such as OCBIs, OCBOs, withdrawal, and negative reac
tions. Informational justice was the strongest predictor of both
agent-referenced and system-referenced evaluation of authority.
These results suggest that researchers interested in most evaluation
or behavioral outcomes should assess both structural and interac
tional facets of justice.
Examining interactions among justice dimensions. In addition
to explaining more outcome variance, including multiple dimen
sions will also allow for the testing of interaction effects. The
interaction between procedural and distributive justice has been
perhaps the most robust finding in the justice literature (Brockner
& Wiesenfeld, 1996). Skarlicki and Folger (1997) further showed
that procedural and interactional justice interact in predicting
ORBs. These authors also found support for three-way interactions
among procedural, interactional, and distributive justice. Such
complex relationships do not map neatly onto reactive models such
as the two-factor or agent-system model. However, the fact that
moderators were present in almost all of the justice-outcome
relationships suggests that more complex relationships may be the
key to improving outcome prediction.
Gaps in the existing literature. A final implication of our
results resides in the gaps revealed by this review. A scan of
Table 5 highlights areas where more research ought to be done. In
terms of sheer number of studies, we note that procedural justice
is much better represented in studies of satisfaction, commitment,
evaluation of authorities, withdrawal, and negative reactions and
relatively underrepresented in studies of performance, OCBs, and
trust. We also note that interpersonal and informational justice
have received less attention than distributive and procedural jus
tice, probably as a result of their more recent appearance in the
justice literature. This is particularly evident for interpersonal
justice, which has been assessed in 16 studies, as opposed to 31
studies for informational justice. As more researchers consider
multiple justice dimensions in their work, these gaps should begin
to be filled.
Limitations
This review has some limitations that should be noted. First, as
in the primary studies on which our review is based, many of the
variables were assessed with self-report measures. Thus, many of
the relationships may be inflated because of same source bias.
Second, any meta-analysis is subject to a variety of judgment calls
META-ANALYTIC REVIEW OF ORGANIZATIONAL JUSTICE 439
(Wanous, Sullivan, & Malinak, 1989). Although we performed all
coding in author dyads, it is possible that some of these judgment
calls affected our results. Finally, the fact that meta-analysis re
quires the reporting of zero-order results meant that several im
portant justice articles could not be included in our review. In
particular, many of Tyler’s examinations of the relational model of
justice had to be omitted (e.g., Tyler, 1989, 1994; Tyler et al.,
1996).
Conclusion
In a review of the organizational justice literature, Greenberg
(1993a) suggested that the field was in a state of “intellectual
adolescence.” This adolescence, though marked by many advance
ments, is also characterized by “stumbling awkwardness” due to
underdeveloped research agendas and the absence of underlying
theory (Greenberg, 1993a, p. 139). In an earlier review, Greenberg
(1990b) echoed these sentiments, noting that the field was years
away from the final stage of Reichers and Schneider’s (1990)
construct life cycle. That final stage, termed “consolidation and
accommodation,” is characterized by a reduction in controversies
and an increase in agreement about definitions, antecedents, and
consequences. Meta-analytic reviews, according to Greenberg
(1990b), can help create such consolidation. Thus, we hope that the
review presented in this article can help the field enter a more
mature stage, as research on justice enters the new millennium.
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META-ANALYTIC REVIEW OF ORGANIZATIONAL JUSTICE 445
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Received August 23, 1999
Revision received May 12, 2000
Accepted May 15, 2000 ■
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Vol. 86, No. 3, 425-445
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0021-9010/01/$5.00 DOI: 10.1037//0021-9010.86.3.425
0021-9010/01/$5.00 DOI: 10.1037//0021-9010.86.3.425
Justice at the Millennium: A Meta-Analytic Review of 25 Years of Organizational Justice Research
Justice at the Millennium: A Meta-Analytic Review of 25 Years of Organizational Justice Research
Jason A. Colquitt
Jason A. Colquitt
University of Florida
University of Florida
Michael J. Wesson and Christopher O. L. H. Porter
Michael J. Wesson and Christopher O. L. H. Porter
Texas A&M University
Texas A&M University
Donald E. Conlon
Donald E. Conlon
Michigan State University
Michigan State University
K. Yee Ng
K. Yee Ng
Michigan State University
Michigan State University
The field of organizational justice continues to be marked by several important research questions, including the size of relationships among justice dimensions, the relative importance of different justice criteria, and the unique effects of justice dimensions on key outcomes. To address such questions, the authors conducted a meta-analytic review of 183 justice studies. The results suggest that although different justice dimensions are moderately to highly related, they contribute incremental variance exp
The field of organizational justice continues to be marked by several important research questions, including the size of relationships among justice dimensions, the relative importance of different justice criteria, and the unique effects of justice dimensions on key outcomes. To address such questions, the authors conducted a meta-analytic review of 183 justice studies. The results suggest that although different justice dimensions are moderately to highly related, they contribute incremental variance exp
The study of justice or fairness has been a topic of philosophical interest that extends back at least as far as Plato and Socrates (Ryan, 1993). Colloquially, the term justice is used to connote “oughtness” or “righteousness.” Under the purview of ethics, an act can be defined as just through comparison with a prevailing philosophical system. Unfortunately, often there is no agreement on what that philosophical system should be. For example, Aristotle (reprinted in Frost, 1972) noted that people in differ
The study of justice or fairness has been a topic of philosophical interest that extends back at least as far as Plato and Socrates (Ryan, 1993). Colloquially, the term justice is used to connote “oughtness” or “righteousness.” Under the purview of ethics, an act can be defined as just through comparison with a prevailing philosophical system. Unfortunately, often there is no agreement on what that philosophical system should be. For example, Aristotle (reprinted in Frost, 1972) noted that people in differ
In research in the organizational sciences, justice is considered to be socially constructed. That is, an act is defined as just if most individuals perceive it to be so on the basis of empirical research (Cropanzano & Greenberg, 1997). Thus, “what is fair” is derived from past research linking objective facets of decision making to subjective perceptions of fairness. In particular, justice in organizational settings can be described as focusing on the antecedents and consequences of two types of subjectiv
In research in the organizational sciences, justice is considered to be socially constructed. That is, an act is defined as just if most individuals perceive it to be so on the basis of empirical research (Cropanzano & Greenberg, 1997). Thus, “what is fair” is derived from past research linking objective facets of decision making to subjective perceptions of fairness. In particular, justice in organizational settings can be described as focusing on the antecedents and consequences of two types of subjectiv
Jason A. Colquitt, Department of Management, University of Florida; Donald E. Conlon and K. Yee Ng, Department of Management, Michigan State University; Michael J. Wesson and Christopher
Jason A. Colquitt, Department of Management, University of Florida; Donald E. Conlon and K. Yee Ng, Department of Management, Michigan State University; Michael J. Wesson and Christopher
O.
L. H. Porter, Department of Management, Texas A&M University.
We thank George Barnekov and Yumi Eto for their assistance in gathering the articles covered in this review.
We thank George Barnekov and Yumi Eto for their assistance in gathering the articles covered in this review.
Correspondence concerning this article should be addressed to Jason A. Colquitt, Warrington College of Business Administration, Department of Management, University of Florida, P.O. Box 117165, Gainesville, Florida 32611-7165. Electronic mail may be sent to
Correspondence concerning this article should be addressed to Jason A. Colquitt, Warrington College of Business Administration, Department of Management, University of Florida, P.O. Box 117165, Gainesville, Florida 32611-7165. Electronic mail may be sent to
colquitt@ufl.edu
colquitt@ufl.edu
.
distributive justice (Adams, 1965; Deutsch, 1975; Homans, 1961; Leventhal, 1976) and procedural justice (Leventhal, 1980; Leventhal,
distributive justice (Adams, 1965; Deutsch, 1975; Homans, 1961; Leventhal, 1976) and procedural justice (Leventhal, 1980; Leventhal,
Karuža,
& Fry, 1980; Thibaut & Walker, 1975).
Efforts to explain the impact of justice on effective organizational functioning have come under the rubric of organizational justice research (Greenberg, 1987b, 1990b). Greenberg (1990b) described organizational justice as a literature “grown around attempts to describe and explain the role of fairness as a consideration in the workplace” (p. 400). This literature includes both field and laboratory research, and organizational justice has been among the most frequently researched topics in industrial- or
Efforts to explain the impact of justice on effective organizational functioning have come under the rubric of organizational justice research (Greenberg, 1987b, 1990b). Greenberg (1990b) described organizational justice as a literature “grown around attempts to describe and explain the role of fairness as a consideration in the workplace” (p. 400). This literature includes both field and laboratory research, and organizational justice has been among the most frequently researched topics in industrial- or
As interest in organizational justice has proliferated, so too have the theoretical approaches used to study it, particularly in relation to procedural justice. These approaches each propose a different way of conceptualizing justice, from the provision of process control (Thibaut & Walker, 1975) to a focus on consistency (Leventhal, 1980; Leventhal
As interest in organizational justice has proliferated, so too have the theoretical approaches used to study it, particularly in relation to procedural justice. These approaches each propose a different way of conceptualizing justice, from the provision of process control (Thibaut & Walker, 1975) to a focus on consistency (Leventhal, 1980; Leventhal
et
al., 1980) and an examination of interpersonal treatment
(Bies
& Moag, 1986). In addition, a large number of studies have sought to link justice perceptions to a variety of organizational outcomes, including job satisfaction, organizational commitment, withdrawal, and organizational citizenship behavior.
Because of this diversity in theoretical approach and construct focus, organizational justice is a field in need of integration. There have been a number of narrative reviews that have sought to achieve such integration (e.g., Cropanzano & Greenberg, 1997; Folger & Cropanzano, 1998; Lind & Tyler, 1988; Greenberg, 1987b, 1990b). However, important questions remain, including the following: How highly related are the different dimensions of organizational justice, and can they be empirically distinguished
Because of this diversity in theoretical approach and construct focus, organizational justice is a field in need of integration. There have been a number of narrative reviews that have sought to achieve such integration (e.g., Cropanzano & Greenberg, 1997; Folger & Cropanzano, 1998; Lind & Tyler, 1988; Greenberg, 1987b, 1990b). However, important questions remain, including the following: How highly related are the different dimensions of organizational justice, and can they be empirically distinguished
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COLQUITT, CONLON, WESSON, PORTER, AND NG
COLQUITT, CONLON, WESSON, PORTER, AND NG
COLQUITT, CONLON, WESSON, PORTER, AND NG
COLQUITT, CONLON, WESSON, PORTER, AND NG
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from one another? Have the different ways of conceptualizing justice improved our ability to create perceptions of fairness? and What are the relationships between different organizational justice dimensions and important outcomes relevant to organizations? The first question deals with issues of construct discrimination (i.e., to what extent are constructs distinct from one another?). The second question deals with what Greenberg (1987b) called proactive research (i.e., research devoted to creating percep
from one another? Have the different ways of conceptualizing justice improved our ability to create perceptions of fairness? and What are the relationships between different organizational justice dimensions and important outcomes relevant to organizations? The first question deals with issues of construct discrimination (i.e., to what extent are constructs distinct from one another?). The second question deals with what Greenberg (1987b) called proactive research (i.e., research devoted to creating percep
The purpose of this study was to conduct a comprehensive, meta-analytic review of the existing literature on organizational justice. To our knowledge, a meta-analysis has never been conducted in the organizational justice literature, even though metaanalysis has several important strengths relative to traditional narrative reviews (Hunter & Schmidt, 1990). First, meta-analysis is a more powerful summarizing tool because it yields a quantitative population value for a relationship of interest. Second, met
The purpose of this study was to conduct a comprehensive, meta-analytic review of the existing literature on organizational justice. To our knowledge, a meta-analysis has never been conducted in the organizational justice literature, even though metaanalysis has several important strengths relative to traditional narrative reviews (Hunter & Schmidt, 1990). First, meta-analysis is a more powerful summarizing tool because it yields a quantitative population value for a relationship of interest. Second, met
We conducted meta-analyses on all articles in the organizational justice literature published since 1975. We chose 1975 as our starting date because this is when Thibaut and Walker introduced the procedural justice construct, which allowed for the comparative study of the influence of multiple dimensions of justice. That year also marks, approximately, the time when justice researchers began integrating fairness concerns with outcomes relevant to organizations (e.g., job satisfaction and organizational com
We conducted meta-analyses on all articles in the organizational justice literature published since 1975. We chose 1975 as our starting date because this is when Thibaut and Walker introduced the procedural justice construct, which allowed for the comparative study of the influence of multiple dimensions of justice. That year also marks, approximately, the time when justice researchers began integrating fairness concerns with outcomes relevant to organizations (e.g., job satisfaction and organizational com
A Brief Review of the Organizational Justice Literature
A Brief Review of the Organizational Justice Literature
Introduction of Distributive Justice
Introduction of Distributive Justice
Before 1975, the study of justice was primarily concerned with distributive justice. Much of this research was derived from initial work conducted by Adams (1965), who used a social exchange theory framework to evaluate fairness. According to Adams, what people were concerned about was not the absolute level of outcomes per se but whether those outcomes were fair. Adams suggested that one way to determine whether an outcome was fair was to calculate the ratio of one’s contributions or “inputs” (e.g., educ
Before 1975, the study of justice was primarily concerned with distributive justice. Much of this research was derived from initial work conducted by Adams (1965), who used a social exchange theory framework to evaluate fairness. According to Adams, what people were concerned about was not the absolute level of outcomes per se but whether those outcomes were fair. Adams suggested that one way to determine whether an outcome was fair was to calculate the ratio of one’s contributions or “inputs” (e.g., educ
theory an “objective” component, he was clear that this process was completely subjective.
theory an “objective” component, he was clear that this process was completely subjective.
Whereas Adams’s theory advocated the use of an equity rule to determine fairness, several other allocation rules have also been identified, such as equality and need (e.g., Leventhal, 1976). Studies have shown that different contexts (e.g., work vs. family), different organizational goals (e.g., group harmony vs. productivity), and different personal motives (e.g., self-interest motives vs. altruistic motives) can activate the use or primacy of certain allocation rules (Deutsch, 1975). Nevertheless, all of
Whereas Adams’s theory advocated the use of an equity rule to determine fairness, several other allocation rules have also been identified, such as equality and need (e.g., Leventhal, 1976). Studies have shown that different contexts (e.g., work vs. family), different organizational goals (e.g., group harmony vs. productivity), and different personal motives (e.g., self-interest motives vs. altruistic motives) can activate the use or primacy of certain allocation rules (Deutsch, 1975). Nevertheless, all of
Introduction of Procedural Justice
Introduction of Procedural Justice
With the publication of their book summarizing disputant reactions to legal procedures, Thibaut and Walker (1975) introduced the study of process to the literature on justice. Thibaut and Walker (1975) viewed third-party dispute resolution procedures such as mediation and arbitration as having both a process stage and a decision stage. They referred to the amount of influence disputants had in each stage as evidence of process control and decision control, respectively. Their research suggested that disput
With the publication of their book summarizing disputant reactions to legal procedures, Thibaut and Walker (1975) introduced the study of process to the literature on justice. Thibaut and Walker (1975) viewed third-party dispute resolution procedures such as mediation and arbitration as having both a process stage and a decision stage. They referred to the amount of influence disputants had in each stage as evidence of process control and decision control, respectively. Their research suggested that disput
Although Thibaut and Walker (1975) introduced the concept of procedural justice, their work focused primarily on disputant reactions to legal procedures. Although a focus on justice and law continues to be of interest to scholars (e.g., Tyler, 1990), Leventhal and colleagues can be credited for extending the notion of procedural justice into nonlegal contexts such as organizational settings (Leventhal, 1980; Leventhal
Although Thibaut and Walker (1975) introduced the concept of procedural justice, their work focused primarily on disputant reactions to legal procedures. Although a focus on justice and law continues to be of interest to scholars (e.g., Tyler, 1990), Leventhal and colleagues can be credited for extending the notion of procedural justice into nonlegal contexts such as organizational settings (Leventhal, 1980; Leventhal
et
al., 1980). In doing so, Leventhal and colleagues also broadened the list of determinants of procedural justice far beyond the concept of process control. Leventhal’s theory of procedural justice judgments focused on six criteria that a procedure should meet if it is to be perceived as fair. Procedures should (a) be applied consistently across people and across time, (b) be free from bias (e.g., ensuring that a third party has no vested interest in a particular settlement), (c) ensure that accurate inform
Introduction of Interactional Justice
Introduction of Interactional Justice
Bies
Bies
and Moag (1986) introduced the most recent advance in the justice literature by focusing attention on the importance of the quality of the interpersonal treatment people receive when procedures are implemented.
Bies
and Moag (1986) referred to these
META-ANALYTIC REVIEW OF ORGANIZATIONAL JUSTICE
META-ANALYTIC REVIEW OF ORGANIZATIONAL JUSTICE
META-ANALYTIC REVIEW OF ORGANIZATIONAL JUSTICE
META-ANALYTIC REVIEW OF ORGANIZATIONAL JUSTICE
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aspects of justice as “interactional justice.” More recently, interactional justice has come to be seen as consisting of two specific types of interpersonal treatment (e.g., Greenberg, 1990a, 1993b). The first, labeled interpersonal justice, reflects the degree to which people are treated with politeness, dignity, and respect by authorities or third parties involved in executing procedures or determining outcomes. The second, labeled informational justice, focuses on the explanations provided to people t
aspects of justice as “interactional justice.” More recently, interactional justice has come to be seen as consisting of two specific types of interpersonal treatment (e.g., Greenberg, 1990a, 1993b). The first, labeled interpersonal justice, reflects the degree to which people are treated with politeness, dignity, and respect by authorities or third parties involved in executing procedures or determining outcomes. The second, labeled informational justice, focuses on the explanations provided to people t
Questions Permeating the Organizational Justice Literature
Questions Permeating the Organizational Justice Literature
The proliferation of studies on organizational justice has certainly enhanced the visibility of fairness concerns, but the large number of studies and the differing theoretical perspectives raise the concern that justice scholars may be “losing the forest for the trees.” In other words, despite the large accumulation of findings, many central questions remain either unaddressed or unclear. Until such questions are addressed, theory development in the organizational justice literature will continue to be h
The proliferation of studies on organizational justice has certainly enhanced the visibility of fairness concerns, but the large number of studies and the differing theoretical perspectives raise the concern that justice scholars may be “losing the forest for the trees.” In other words, despite the large accumulation of findings, many central questions remain either unaddressed or unclear. Until such questions are addressed, theory development in the organizational justice literature will continue to be h
Construct Discrimination Questions
Construct Discrimination Questions
Perhaps the oldest debate in the justice literature concerns the independence of procedural and distributive justice. Some studies have revealed extremely high correlations between the two justice dimensions, suggesting that they may not be distinct in the minds of many people (Folger, 1987). For example, Sweeney and McFarlin (1997) found an uncorrected correlation of .72 between procedural and distributive justice in a study of attitudes among federal employees. Welbourne,
Perhaps the oldest debate in the justice literature concerns the independence of procedural and distributive justice. Some studies have revealed extremely high correlations between the two justice dimensions, suggesting that they may not be distinct in the minds of many people (Folger, 1987). For example, Sweeney and McFarlin (1997) found an uncorrected correlation of .72 between procedural and distributive justice in a study of attitudes among federal employees. Welbourne,
Balkin,
and Gomez-Mejia (1995) found an uncorrected correlation of .74 in a study of employees in two different companies, one a high-technology firm and the other a consumer products firm. Possibly as a result of such findings, Martocchio and Judge (1995) conducted a study of disciplinary decisions in which no effort was made to separate procedural and distributive justice. Rather, the authors examined the effects of “organizational justice.”
Such high correlations are congruent with theoretical arguments made by Cropanzano and Ambrose (2001). These authors have argued that the procedural justice-distributive justice distinction, although necessary and valuable, may sometimes be overemphasized. Their “monistic perspective” notes that procedural evaluations are based in large part on outcomes attained (Thibaut & Walker, 1975) and that the same event can be seen as a process in one context and an outcome in another. For example, reorganizing a p
Such high correlations are congruent with theoretical arguments made by Cropanzano and Ambrose (2001). These authors have argued that the procedural justice-distributive justice distinction, although necessary and valuable, may sometimes be overemphasized. Their “monistic perspective” notes that procedural evaluations are based in large part on outcomes attained (Thibaut & Walker, 1975) and that the same event can be seen as a process in one context and an outcome in another. For example, reorganizing a p
The construct discrimination concern applies to an even greater degree to procedural and interactional justice.
The construct discrimination concern applies to an even greater degree to procedural and interactional justice.
Bies
and Moag (1986) originally declared interactional justice to be a third type of justice. They argued that people draw on interactional justice perceptions when deciding how to react to authority figures (i.e., bosses and supervisors), whereas procedural justice perceptions
are used to decide how to react to the overall organization. However,
are used to decide how to react to the overall organization. However,
Bies
retracted the position that interactional justice was a third type of justice in a subsequent review (Tyler &
Bies,
1990). The author’s retraction of his earlier stance has become widely held, as one recent narrative review treated interactional justice as a social form of procedural justice (Cropanzano & Greenberg, 1997). In keeping with this view, many researchers have operationalized procedural justice by measuring process control or Leventhal criteria, along with interactional justice, in one combined scale (e.g., Brockner, Siegel, Daly, & Martin, 1997; Brockner,
Wiesenfeld,
& Martin, 1995; Folger & Konovsky, 1989; Konovsky & Folger, 1991; Mansour-Cole & Scott, 1998; Skarlicki & Latham, 1997). This practice seems to suggest that the interpersonal implementation of procedures need not (or cannot) be separated from their structural aspects.
However, other research has renewed the debate surrounding the distinctiveness of procedural and interactional justice. Studies that have examined the two constructs separately have shown that they have different correlates or independent effects, or both (e.g., Barling & Phillips, 1993;
However, other research has renewed the debate surrounding the distinctiveness of procedural and interactional justice. Studies that have examined the two constructs separately have shown that they have different correlates or independent effects, or both (e.g., Barling & Phillips, 1993;
Blader
& Tyler, 2000; Cropanzano & Prehar, 1999; Masterson, Lewis, Goldman, & Taylor, 2000; Moye, Masterson, &
Bartol,
1997; Skarlicki & Folger, 1997).
Blader
and Tyler (2000), in a survey of 404 U.S. workers, found that systemoriginating procedural factors and leader-originating procedural factors remained distinct in a confirmatory factor analysis.
Master
son,
Lewis,
et al.
(2000) drew on social exchange theory to show that procedural and interactional justice affected other variables through different intervening mechanisms. Specifically, procedural justice affected other variables by altering perceived organizational support perceptions; interactional justice affected other variables by altering leader-member exchange perceptions (Graen & Scandura, 1987).
Even assuming that interactional justice can and should be distinguished from procedural justice, another question is whether the interpersonal and informational facets of the construct merit conceptual separation. Greenberg (1993b) suggested that interpersonal and informational justice should be separated because they are logically distinct and have been shown to have independent effects (e.g., Greenberg, 1993c, 1994). Interpersonal justice acts primarily to alter reactions to decision outcomes, because s
Even assuming that interactional justice can and should be distinguished from procedural justice, another question is whether the interpersonal and informational facets of the construct merit conceptual separation. Greenberg (1993b) suggested that interpersonal and informational justice should be separated because they are logically distinct and have been shown to have independent effects (e.g., Greenberg, 1993c, 1994). Interpersonal justice acts primarily to alter reactions to decision outcomes, because s
Some recent work has attempted to address the construct discrimination questions raised earlier. Colquitt (2001) developed measures of distributive, procedural, informational, and interpersonal justice based on the seminal introductions of each construct
Some recent work has attempted to address the construct discrimination questions raised earlier. Colquitt (2001) developed measures of distributive, procedural, informational, and interpersonal justice based on the seminal introductions of each construct
(Bies
& Moag, 1986; Leventhal, 1976, 1980; Leventhal
et
al., 1980; Thibaut & Walker, 1975) and validated them in both a university and a field setting. Colquitt found that a four-factor confirmatory model provided the best fit to the data and further showed that the four justice dimensions predicted different outcomes. Thus, although some progress is being made, the literature on organizational justice is still marked by a debate over whether the domain includes one, two, three, or four dimensions of justice. This is the subject of the first research question a
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COLQUITT, CONLON, WESSON, PORTER, AND NG
COLQUITT, CONLON, WESSON, PORTER, AND NG
Research Question 1: How highly related are the different dimensions of organizational justice, and can they be empirically distinguished from one another?
Research Question 1: How highly related are the different dimensions of organizational justice, and can they be empirically distinguished from one another?
Proactive Research Questions
Proactive Research Questions
The history of research devoted to understanding what promotes perceptions of fairness has been marked by increasing complexity in operationalization as new and different conceptualizations have been introduced over the years. Thibaut and Walker (1975) initially assumed that perceptions of procedural fairness were driven by process control. Leventhal and colleagues (Leventhal, 1980; Leventhal
The history of research devoted to understanding what promotes perceptions of fairness has been marked by increasing complexity in operationalization as new and different conceptualizations have been introduced over the years. Thibaut and Walker (1975) initially assumed that perceptions of procedural fairness were driven by process control. Leventhal and colleagues (Leventhal, 1980; Leventhal
et
al., 1980), on the other hand, eschewed the parsimonious approach offered by Thibaut and Walker and instead argued that fairness perceptions were created by adherence to six different criteria.
Bies
and Moag (1986) further suggested that fairness perceptions were created by the proper enactment of procedures in terms of interpersonal and informational justice.
Such additional complexity is warranted if new approaches contribute incrementally to our understanding of how to foster perceptions of procedural fairness. Unfortunately, at present we do not actually know whether such incremental contributions exist. This is because so many studies of procedural justice collapse process control, Leventhal criteria, and interpersonal and informational justice into a single variable (e.g., Brockner
Such additional complexity is warranted if new approaches contribute incrementally to our understanding of how to foster perceptions of procedural fairness. Unfortunately, at present we do not actually know whether such incremental contributions exist. This is because so many studies of procedural justice collapse process control, Leventhal criteria, and interpersonal and informational justice into a single variable (e.g., Brockner
et al.,
1995, 1997; Folger & Konovsky, 1989; Konovsky & Folger, 1991; Mansour-Cole & Scott, 1998; Skarlicki & Latham, 1997). This makes it impossible to gauge the relative influence of each element on procedural fairness perceptions. Still other studies assess only one conceptualization of procedural justice, again making it impossible to assess the merits of different approaches.
Moreover, it is well accepted that people judge procedures as more fair when they result in fair or favorable outcomes (Lind & Tyler, 1988; Thibaut & Walker, 1975). Despite this, many studies of procedural justice do not also examine distributive justice. Other studies do examine distributive justice but use it only in analyses separate from procedural justice. As a result, we cannot even be sure that process control, Leventhal criteria, and so forth explain variance in procedural fairness perceptions beyon
Moreover, it is well accepted that people judge procedures as more fair when they result in fair or favorable outcomes (Lind & Tyler, 1988; Thibaut & Walker, 1975). Despite this, many studies of procedural justice do not also examine distributive justice. Other studies do examine distributive justice but use it only in analyses separate from procedural justice. As a result, we cannot even be sure that process control, Leventhal criteria, and so forth explain variance in procedural fairness perceptions beyon
Thus, in terms of creating procedural fairness perceptions, it is unclear to what extent new conceptualizations of procedural justice (including the relatively recent introductions of interpersonal and informational justice) have contributed to our understanding. Nor is it clear how important they are beyond the fairness of outcome distributions. This is the subject of our next two research questions.
Thus, in terms of creating procedural fairness perceptions, it is unclear to what extent new conceptualizations of procedural justice (including the relatively recent introductions of interpersonal and informational justice) have contributed to our understanding. Nor is it clear how important they are beyond the fairness of outcome distributions. This is the subject of our next two research questions.
Research Question 2: Have the additional conceptualizations of procedural justice developed over time (including interpersonal and informational justice) contributed incremental variance explained in procedural fairness perceptions?
Research Question 2: Have the additional conceptualizations of procedural justice developed over time (including interpersonal and informational justice) contributed incremental variance explained in procedural fairness perceptions?
Research Question 3: Do those conceptualizations contribute incremental variance explained in procedural fairness perceptions beyond the effects of distributive justice?
Research Question 3: Do those conceptualizations contribute incremental variance explained in procedural fairness perceptions beyond the effects of distributive justice?
Reactive Research Questions
Reactive Research Questions
Of course, one of the reasons scholars study justice is the belief that enhanced fairness perceptions can improve outcomes relevant to organizations (e.g., organizational commitment, job satisfaction, and performance). One goal of our meta-analytic review is to help develop some consensus regarding the relationships between dimensions of justice and key outcomes. In particular, we evaluate the predictive ability of three different models that attempt to explain relationships between justice dimensions and
Of course, one of the reasons scholars study justice is the belief that enhanced fairness perceptions can improve outcomes relevant to organizations (e.g., organizational commitment, job satisfaction, and performance). One goal of our meta-analytic review is to help develop some consensus regarding the relationships between dimensions of justice and key outcomes. In particular, we evaluate the predictive ability of three different models that attempt to explain relationships between justice dimensions and
Bies
and Moag (1986).
The relative predictive power of procedural and distributive justice has been of long-standing concern in the justice literature. An interesting aspect of Leventhal’s (1980) work is that he explicitly considered the impact of both procedural and distributive justice and argued that distributive justice is generally more salient than procedural justice. He further argued that distributive justice judgments are likely to be more influential than procedural justice judgments in determining “overall fairness j
The relative predictive power of procedural and distributive justice has been of long-standing concern in the justice literature. An interesting aspect of Leventhal’s (1980) work is that he explicitly considered the impact of both procedural and distributive justice and argued that distributive justice is generally more salient than procedural justice. He further argued that distributive justice judgments are likely to be more influential than procedural justice judgments in determining “overall fairness j
However, some prior research and theory have questioned this thesis. In perhaps the first empirical study to explicitly link multiple dimensions of justice to organizational outcomes, Alexander and
However, some prior research and theory have questioned this thesis. In perhaps the first empirical study to explicitly link multiple dimensions of justice to organizational outcomes, Alexander and
Ruderman
(1987) surveyed more than 2,000 federal employees, measuring procedural and distributive justice along with six outcomes. Their regression analyses showed that justice measures affected five of six organizational outcomes and that, for four of these five outcomes, procedural justice had stronger relationships than distributive justice.
More recently, scholars have argued that distributive justice is likely to exert greater influence on more specific, person- referenced outcomes such as satisfaction with a pay raise or performance evaluation. In contrast, procedural justice is likely to exert greater influence on more general evaluations of systems and authorities (Greenberg, 1990b; Lind & Tyler, 1988). Consistent with this prediction, McFarlin and Sweeney (1992) found that distributive justice was a more important predictor of what they t
More recently, scholars have argued that distributive justice is likely to exert greater influence on more specific, person- referenced outcomes such as satisfaction with a pay raise or performance evaluation. In contrast, procedural justice is likely to exert greater influence on more general evaluations of systems and authorities (Greenberg, 1990b; Lind & Tyler, 1988). Consistent with this prediction, McFarlin and Sweeney (1992) found that distributive justice was a more important predictor of what they t
Sweeney and McFarlin (1993) conducted perhaps the most comprehensive test of this notion. They contrasted four models expressing the relationship between procedural and distributive justice and two outcomes (pay satisfaction and organizational commitment). The idea that procedural justice predicts more system-referenced outcomes and distributive justice predicts more person-referenced outcomes was termed in their article the “two- factor model.” They found that the two-factor model fit their data better tha
Sweeney and McFarlin (1993) conducted perhaps the most comprehensive test of this notion. They contrasted four models expressing the relationship between procedural and distributive justice and two outcomes (pay satisfaction and organizational commitment). The idea that procedural justice predicts more system-referenced outcomes and distributive justice predicts more person-referenced outcomes was termed in their article the “two- factor model.” They found that the two-factor model fit their data better tha
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of these studies, we examine the two-factor model’s prediction of differing effects for procedural and distributive justice.
of these studies, we examine the two-factor model’s prediction of differing effects for procedural and distributive justice.
Finally,
Finally,
Bies
and Moag’s (1986) focus on interpersonal treatment suggests a third approach to explaining organizational outcomes, one that explicitly examines the role of interpersonal and informational justice in addition to procedural justice. Recall that
Bies
and Moag (1986) originally argued that individuals draw on interpersonal and informational justice perceptions when deciding how to react to authority figures (i.e., bosses and supervisors) and draw on procedural justice perceptions when deciding how to react to the overall organization. Building on this work, Masterson, Lewis,
et al.
(2000) drew on social exchange theory (Blau, 1964) and reasoned that individuals in organizations were involved in two types of exchange relationships: exchanges with their immediate supervisor and exchanges with the larger organization. In a field study, the authors showed that interactional justice predicted supervisor-referenced outcomes (e.g., citizenship behaviors directed at supervisor and supervisor rating of performance), whereas procedural justice predicted organization-referenced outcomes (e.g.
The distributive dominance model, the two-factor model, and the agent-system model are explored in the following set of research questions.
The distributive dominance model, the two-factor model, and the agent-system model are explored in the following set of research questions.
Research Question 4: What are the relationships between distributive justice and important organizational outcomes?
Research Question 4: What are the relationships between distributive justice and important organizational outcomes?
Research Question 5: What are the relationships between procedural justice and important organizational outcomes?
Research Question 5: What are the relationships between procedural justice and important organizational outcomes?
Research Question 6: What are the relationships between interpersonal and informational justice and important organizational outcomes?
Research Question 6: What are the relationships between interpersonal and informational justice and important organizational outcomes?
Research Question 7: If considered simultaneously, what are the unique effects of these justice dimensions on key outcomes, and which of the three reactive models receives the most support?
Research Question 7: If considered simultaneously, what are the unique effects of these justice dimensions on key outcomes, and which of the three reactive models receives the most support?
Our review focuses on several different outcomes representing those most commonly examined in the organizational justice literature. In the following sections, we briefly review each type of outcome.
Our review focuses on several different outcomes representing those most commonly examined in the organizational justice literature. In the following sections, we briefly review each type of outcome.
Outcome satisfaction. Many justice studies have measured satisfaction with the outcomes of a decision-making process, such as pay, promotions, and performance evaluations. Given the logic presented earlier, we expect that distributive justice judgments will be a better predictor of outcome satisfaction than will procedural justice or interpersonal and informational justice. This pattern has been empirically supported through the use of pay satisfaction and satisfaction with job restructuring (e.g., Folger &
Outcome satisfaction. Many justice studies have measured satisfaction with the outcomes of a decision-making process, such as pay, promotions, and performance evaluations. Given the logic presented earlier, we expect that distributive justice judgments will be a better predictor of outcome satisfaction than will procedural justice or interpersonal and informational justice. This pattern has been empirically supported through the use of pay satisfaction and satisfaction with job restructuring (e.g., Folger &
Job satisfaction. Many studies also ask about employees’ satisfaction with their jobs in general. McFarlin and Sweeney (1992) showed that distributive justice was a more powerful predictor of job satisfaction than was procedural justice. However, this does not seem to fit the two-factor theory argument that procedural
Job satisfaction. Many studies also ask about employees’ satisfaction with their jobs in general. McFarlin and Sweeney (1992) showed that distributive justice was a more powerful predictor of job satisfaction than was procedural justice. However, this does not seem to fit the two-factor theory argument that procedural
justice predicts system-referenced outcomes, whereas distributive justice predicts person-referenced outcomes. Job satisfaction is a more general, multifaceted, and global response than is outcome satisfaction. Consistent with this reasoning, other studies have shown high correlations between procedural justice and job satisfaction (e.g., Mossholder, Bennett, & Martin, 1998; Wesolowski & Mossholder, 1997). In addition, Masterson, Lewis,
justice predicts system-referenced outcomes, whereas distributive justice predicts person-referenced outcomes. Job satisfaction is a more general, multifaceted, and global response than is outcome satisfaction. Consistent with this reasoning, other studies have shown high correlations between procedural justice and job satisfaction (e.g., Mossholder, Bennett, & Martin, 1998; Wesolowski & Mossholder, 1997). In addition, Masterson, Lewis,
et al.
(2000) showed procedural justice to be a stronger predictor of job satisfaction than interactional justice, although both had significant independent effects. These results are consistent with the two- factor model and the agent-system model.
Organizational commitment. Organizational commitment represents a global, systemic reaction that people have to the company for which they work. Most measures of organizational commitment assess affective commitment, the degree to which employees identify with the company and make the company’s goals their own (Allen & Meyer, 1990). Prior work by Tyler (e.g., Tyler, 1990) argues that procedural justice has stronger relationships with support for institutions than does distributive justice. This is also co
Organizational commitment. Organizational commitment represents a global, systemic reaction that people have to the company for which they work. Most measures of organizational commitment assess affective commitment, the degree to which employees identify with the company and make the company’s goals their own (Allen & Meyer, 1990). Prior work by Tyler (e.g., Tyler, 1990) argues that procedural justice has stronger relationships with support for institutions than does distributive justice. This is also co
et
al., 2000).
Trust. Trust has recently emerged as a popular topic in organizational research (as evidenced by the 1998 Academy of Management Review special issue devoted to the topic). Tyler (1989) argued that trust in decision makers or authorities is important because these people typically have considerable discretion in terms of allocating rewards and resources. Whereas Tyler (1989) initially conceptualized trust in relation to a third party or an authority, Folger and Cropanzano (1998) made the point that trust r
Trust. Trust has recently emerged as a popular topic in organizational research (as evidenced by the 1998 Academy of Management Review special issue devoted to the topic). Tyler (1989) argued that trust in decision makers or authorities is important because these people typically have considerable discretion in terms of allocating rewards and resources. Whereas Tyler (1989) initially conceptualized trust in relation to a third party or an authority, Folger and Cropanzano (1998) made the point that trust r
Ruder
man,
1987; Konovsky & Pugh, 1994). However, given that trust is usually referenced to a particular person, the agent-system model would predict that interpersonal and informational justice are even better predictors of this outcome than procedural justice.
Evaluation of authority. A number of studies of third-party dispute resolution procedures have asked disputants to make evaluations of the third party (Lind & Tyler, 1988). Still other work in organizations asks respondents to rate the acceptability of their supervisors or management in more general terms. Much of the research on evaluation of authorities comes from work merging psychology and political science (e.g., Tyler, 1990). Tyler’s (1990) work, along with the two-factor model, would suggest that we
Evaluation of authority. A number of studies of third-party dispute resolution procedures have asked disputants to make evaluations of the third party (Lind & Tyler, 1988). Still other work in organizations asks respondents to rate the acceptability of their supervisors or management in more general terms. Much of the research on evaluation of authorities comes from work merging psychology and political science (e.g., Tyler, 1990). Tyler’s (1990) work, along with the two-factor model, would suggest that we
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and refuted in multiple studies (e.g., Conlon, 1993; Taylor, Tracy, Renard, Harrison, & Carroll, 1995). In addition, the agent-system model would predict that interpersonal and informational justice are better predictors of evaluation of authority in cases in which the authority in question is one’s leader as opposed to management in general. For this reason, our examination of the reactive models distinguishes between agent-referenced evaluations of authority (e.g., focusing on one’s supervisor) and system
and refuted in multiple studies (e.g., Conlon, 1993; Taylor, Tracy, Renard, Harrison, & Carroll, 1995). In addition, the agent-system model would predict that interpersonal and informational justice are better predictors of evaluation of authority in cases in which the authority in question is one’s leader as opposed to management in general. For this reason, our examination of the reactive models distinguishes between agent-referenced evaluations of authority (e.g., focusing on one’s supervisor) and system
Organizational citizenship behaviors (OCBs). Organ (1990) defined OCBs as behaviors that are discretionary and not explicitly rewarded but that can help improve organizational functioning. Organ (1990) posited that OCBs are driven largely by fairness perceptions. He suggested that people in organizations assume, at the outset, a social exchange relationship. This expectation continues until unfairness is evidenced, at which time the relationship is reinterpreted as economic rather than social. Research on
Organizational citizenship behaviors (OCBs). Organ (1990) defined OCBs as behaviors that are discretionary and not explicitly rewarded but that can help improve organizational functioning. Organ (1990) posited that OCBs are driven largely by fairness perceptions. He suggested that people in organizations assume, at the outset, a social exchange relationship. This expectation continues until unfairness is evidenced, at which time the relationship is reinterpreted as economic rather than social. Research on
et al.
(2000). Thus, our examination of the reactive models distinguishes between agent- referenced OCBs and system-referenced OCBs. Following Williams and Anderson (1991), we refer to the former as individual OCBs (OCBIs) and the latter as organization OCBs (OCBOs).
Withdrawal. Behaviors and behavioral intentions such as absenteeism, turnover, and neglect are often subsumed under the heading of job withdrawal. Although withdrawal is a relatively common outcome in the justice literature, it has not been examined in the context of the two-factor model. Withdrawal can occur as a result of a thorough, reasoned evaluation of the organization as a system or on a more “spur of the moment” basis in reaction to an unsatisfactory outcome or poor interpersonal treatment by an au
Withdrawal. Behaviors and behavioral intentions such as absenteeism, turnover, and neglect are often subsumed under the heading of job withdrawal. Although withdrawal is a relatively common outcome in the justice literature, it has not been examined in the context of the two-factor model. Withdrawal can occur as a result of a thorough, reasoned evaluation of the organization as a system or on a more “spur of the moment” basis in reaction to an unsatisfactory outcome or poor interpersonal treatment by an au
Sellare,
1984) and other studies revealing effects for procedural justice (e.g., Dailey & Kirk, 1992). Moreover, Masterson, Lewis,
et al.
(2000) showed that procedural justice had more of an impact on withdrawal than interactional justice. Thus, past research has, at various times, supported the distributive dominance model, the two-factor model, and the agent-system model.
Negative reactions. Some recent justice research has looked at the relationship between perceived unfairness and a variety of negative reactions, such as employee theft (e.g., Greenberg, 1990a, 1993c) and organizational retaliatory behaviors (ORBs; Skarlicki & Folger, 1997; Skarlicki, Folger, & Tesluk, 1999). As with
Negative reactions. Some recent justice research has looked at the relationship between perceived unfairness and a variety of negative reactions, such as employee theft (e.g., Greenberg, 1990a, 1993c) and organizational retaliatory behaviors (ORBs; Skarlicki & Folger, 1997; Skarlicki, Folger, & Tesluk, 1999). As with
withdrawal, negative reactions have not been examined from the standpoint of the two-factor model. Whereas negative reactions can occur because of purely cognitive evaluations of the merits of the organization as a whole or as strong emotional reactions to one’s own treatment, reactions such as theft and ORBs clearly damage the larger organizational system. However, Skarlicki and Folger (1997) found that ORBs had approximately equal correlations with distributive, procedural, and interactional justice, wit
withdrawal, negative reactions have not been examined from the standpoint of the two-factor model. Whereas negative reactions can occur because of purely cognitive evaluations of the merits of the organization as a whole or as strong emotional reactions to one’s own treatment, reactions such as theft and ORBs clearly damage the larger organizational system. However, Skarlicki and Folger (1997) found that ORBs had approximately equal correlations with distributive, procedural, and interactional justice, wit
Performance. Perhaps the most unclear of all relationships in the justice literature is the relationship between procedural justice and performance. For example, Earley and Lind (1987) found a relationship between procedural fairness judgments and performance in a laboratory study but not in a field study. Kanfer, Sawyer, Earley, and Lind (1987) found a negative correlation between procedural justice and performance. Keller and Dansereau (1995) found a moderately strong relationship between procedural just
Performance. Perhaps the most unclear of all relationships in the justice literature is the relationship between procedural justice and performance. For example, Earley and Lind (1987) found a relationship between procedural fairness judgments and performance in a laboratory study but not in a field study. Kanfer, Sawyer, Earley, and Lind (1987) found a negative correlation between procedural justice and performance. Keller and Dansereau (1995) found a moderately strong relationship between procedural just
et
al., 1994; Griffeth, Vecchio, & Logan, 1989). It is difficult to apply the logic of the agent-system and two-factor models to the prediction of performance. On the one hand, performance supports, and is often measured by, agents such as one’s supervisor. For this reason, Masterson, Lewis,
et al.
(2000) predicted, and found, stronger interactional justice effects on performance, consistent with the agent-system model. On the other hand, performance reflects members’ contributions to organizational goals (Borman, 1991), giving it a system-referenced character and suggesting that procedural justice should be its primary predictor.
Different Operationalizations of Procedural Justice
Different Operationalizations of Procedural Justice
Of course, the relative strength of the correlations between the justice dimensions and the outcomes just described may depend on how procedural justice is operationalized. For example, some studies assess only process control but label it procedural justice (e.g., Joy & Witt, 1992). Others use a variable that is composed only of Leventhal criteria, labeling that procedural justice (e.g., Konovsky & Folger, 1991). Still others measure informational or interpersonal justice as the process variable (e.g., Gre
Of course, the relative strength of the correlations between the justice dimensions and the outcomes just described may depend on how procedural justice is operationalized. For example, some studies assess only process control but label it procedural justice (e.g., Joy & Witt, 1992). Others use a variable that is composed only of Leventhal criteria, labeling that procedural justice (e.g., Konovsky & Folger, 1991). Still others measure informational or interpersonal justice as the process variable (e.g., Gre
Bies,
Martin, & Brockner, 1993; Colquitt & Chertkoff, 1996; Gilliland, 1994), which is what Lind and Tyler (1988) labeled a direct measure (i.e., a measure that directly asks respondents “how fair” a procedure is). Finally, another common operationalization is an indirect combination measure (Lind & Tyler, 1988). Such a measure asks respondents about some combination of process control, Leventhal criteria, and interpersonal or informational justice, labeling that procedural justice (e.g., Brockner
et al.,
1995, 1997; Folger & Konovsky, 1989; Konovsky & Folger, 1991; Mansour-Cole & Scott, 1998; Skarlicki & Latham, 1997). Presumably, those who use such measures subscribe to the view that interpersonal and informational justice are facets of procedural justice, as with process control or Leventhal criteria.
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Our examination of the relative strength of the correlations between the different dimensions of justice and the outcomes described uses the broadest conceptualization of procedural justice by combining all of its potential operationalizations. However, our review also presents analyses broken down by operationalization. One strength of meta-analysis is that it allows a researcher to examine the degree to which a relationship varies across a particular moderator variable. Our review examines operationaliza
Our examination of the relative strength of the correlations between the different dimensions of justice and the outcomes described uses the broadest conceptualization of procedural justice by combining all of its potential operationalizations. However, our review also presents analyses broken down by operationalization. One strength of meta-analysis is that it allows a researcher to examine the degree to which a relationship varies across a particular moderator variable. Our review examines operationaliza
Method
Method
We conducted a meta-analytic review of the literature on organizational justice to examine the questions discussed earlier. In the following sections, we review the methods for this review.
We conducted a meta-analytic review of the literature on organizational justice to examine the questions discussed earlier. In the following sections, we review the methods for this review.
Literature Search
Literature Search
We first performed a literature search of the PsycINFO database for the years 1975 to 1999. Our starting date coincided with the year in which Thibaut and Walker (1975) introduced the procedural justice construct. Given that a major goal of this review was to examine the relative impact of multiple dimensions of justice, articles published before 1975 would be less useful. Such articles were typically proactive distributive justice articles that examined how individuals allocate rewards across different si
We first performed a literature search of the PsycINFO database for the years 1975 to 1999. Our starting date coincided with the year in which Thibaut and Walker (1975) introduced the procedural justice construct. Given that a major goal of this review was to examine the relative impact of multiple dimensions of justice, articles published before 1975 would be less useful. Such articles were typically proactive distributive justice articles that examined how individuals allocate rewards across different si
The search yielded 300 articles. Of these 300 articles, 76 did not include a relationship in the meta-analysis and were deemed not relevant. For example, Tyler, Lind, Ohbuchi, Sugawara, and Huo (1998) examined the effects of ‘‘relational judgments” (an aggregate measure of procedural, interpersonal, and informational justice judgments) on the willingness of disputants to accept a third-party solution in a conflict resolution setting. Bazerman,
The search yielded 300 articles. Of these 300 articles, 76 did not include a relationship in the meta-analysis and were deemed not relevant. For example, Tyler, Lind, Ohbuchi, Sugawara, and Huo (1998) examined the effects of ‘‘relational judgments” (an aggregate measure of procedural, interpersonal, and informational justice judgments) on the willingness of disputants to accept a third-party solution in a conflict resolution setting. Bazerman,
Schroth,
Shah,
Diekmann,
and Tenbrunsel (1994) examined the effects of justice on job search decisions. Such studies did not focus on one of the nine outcome variables included in our review or did not include a relationship between different dimensions of justice.
Another 41 studies included a relationship in the meta-analysis but could not be coded because of the way in which the results were presented. Meta-analysis requires zero-order effect size information, whether in the form of correlations,
Another 41 studies included a relationship in the meta-analysis but could not be coded because of the way in which the results were presented. Meta-analysis requires zero-order effect size information, whether in the form of correlations,
F
statistics, t statistics, or even means and standard deviations of a dependent variable across multiple experimental conditions. Articles that present only partial or semipartial unique, independent effects cannot be coded unless the independent variables are uncorrelated, as in most experiments in which conditions are manipulated orthogonal to one another. Several articles uncovered in our literature review could not be
coded because they presented only multiple regression or structural equation modeling results. Examples included several of Tyler’s investigations of the “relational” or "group-value" model of justice (e.g., Tyler, 1989, 1994; Tyler, Degoey, & Smith, 1996). Other articles could not be coded because they presented incomplete results (e.g., only labeling
coded because they presented only multiple regression or structural equation modeling results. Examples included several of Tyler’s investigations of the “relational” or "group-value" model of justice (e.g., Tyler, 1989, 1994; Tyler, Degoey, & Smith, 1996). Other articles could not be coded because they presented incomplete results (e.g., only labeling
F
statistics in an analysis of variance as significant or not significant) or combined procedural and distributive justice into a larger justice variable (e.g., Martocchio & Judge, 1995).
The final number of studies included in the review was 183. These studies are marked with an asterisk in the References section. We should note that this number included both laboratory studies and field studies; the term organizational justice in no way implies that the research must occur in a field setting but indicates only that the research must be relevant to the role of fairness in the workplace (Greenberg, 1990b).
The final number of studies included in the review was 183. These studies are marked with an asterisk in the References section. We should note that this number included both laboratory studies and field studies; the term organizational justice in no way implies that the research must occur in a field setting but indicates only that the research must be relevant to the role of fairness in the workplace (Greenberg, 1990b).
Meta-Analysis Strategy
Meta-Analysis Strategy
Meta-analysis is a technique that allows individual study results to be aggregated while correcting for various artifacts that can bias relationship estimates. Our meta-analyses were conducted with Hunter and Schmidt’s (1990) procedures. Inputs into the meta-analyses included zero-order effect sizes in the form of correlations, along with sample sizes and reliability information. In instances in which articles reported statistics other than correlations (e.g.,
Meta-analysis is a technique that allows individual study results to be aggregated while correcting for various artifacts that can bias relationship estimates. Our meta-analyses were conducted with Hunter and Schmidt’s (1990) procedures. Inputs into the meta-analyses included zero-order effect sizes in the form of correlations, along with sample sizes and reliability information. In instances in which articles reported statistics other than correlations (e.g.,
F
statistics, t statistics, or means and standard deviations), results were transformed into correlations through the formulas provided by Hunter and Schmidt (1990). Because of the subjectivity and judgment calls inherent in meta-analytic efforts, all coding of meta-analytic data was performed by author dyads formed from the study’s five authors.
In cases in which a variable was assessed with multiple measures, we acted in accordance with Hunter and Schmidt’s (1990) recommendations for conceptual replication (see pp. 451-463). Specifically, when multiple measures were highly correlated and seemed to each be construct valid, the correlations were averaged together (see Hunter & Schmidt, 1990, p. 457). Thus, one composite correlation was formed in lieu of multiple correlations, preventing a study that involved multiple measures from being “double cou
In cases in which a variable was assessed with multiple measures, we acted in accordance with Hunter and Schmidt’s (1990) recommendations for conceptual replication (see pp. 451-463). Specifically, when multiple measures were highly correlated and seemed to each be construct valid, the correlations were averaged together (see Hunter & Schmidt, 1990, p. 457). Thus, one composite correlation was formed in lieu of multiple correlations, preventing a study that involved multiple measures from being “double cou
Meta-analysis requires that each observed correlation from a given study be weighted by that study’s sample size to provide a weighted mean estimate of the population correlation. The standard deviation of this estimate across the multiple studies is also computed. This variation is composed of true variation in the population value as well as variation due to artifacts such as sampling error and measurement error. To provide a more accurate estimate of each population correlation and its variability, our a
Meta-analysis requires that each observed correlation from a given study be weighted by that study’s sample size to provide a weighted mean estimate of the population correlation. The standard deviation of this estimate across the multiple studies is also computed. This variation is composed of true variation in the population value as well as variation due to artifacts such as sampling error and measurement error. To provide a more accurate estimate of each population correlation and its variability, our a
Meta-analysis results typically include both uncorrected (r) and corrected (rc) estimates of the population correlation. The latter are corrected for unreliability in both variables. Also reported are the 95% confidence intervals for each population correlation. Confidence intervals are generated with the standard error of the weighted mean correlation. They reflect the “extent to which sampling error remains in the estimate of a mean effect size” and are applied to estimates that have not been corrected
Meta-analysis results typically include both uncorrected (r) and corrected (rc) estimates of the population correlation. The latter are corrected for unreliability in both variables. Also reported are the 95% confidence intervals for each population correlation. Confidence intervals are generated with the standard error of the weighted mean correlation. They reflect the “extent to which sampling error remains in the estimate of a mean effect size” and are applied to estimates that have not been corrected
Also presented is the standard deviation of the population correlation (SDrc). This provides an index of the variation in the corrected population
Also presented is the standard deviation of the population correlation (SDrc). This provides an index of the variation in the corrected population
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values across the studies in our sample. One indication that moderators may be present in a given relationship is the case in which artifacts such as unreliability fail to account for a substantial portion of the variance in correlations. Thus, the percentage of variance explained by artifacts (VOT) is also presented. Hunter and Schmidt (1990) have suggested that, if artifacts fail to account for 75% of the variance in the correlations, moderators probably exist. Mathieu and Zajac (1990) and Hom,
values across the studies in our sample. One indication that moderators may be present in a given relationship is the case in which artifacts such as unreliability fail to account for a substantial portion of the variance in correlations. Thus, the percentage of variance explained by artifacts (VOT) is also presented. Hunter and Schmidt (1990) have suggested that, if artifacts fail to account for 75% of the variance in the correlations, moderators probably exist. Mathieu and Zajac (1990) and Hom,
Caranikas
Walker,
Prussia, and Griffeth (1992) amended the 75% criterion to 60% in cases in which range restriction is not one of the artifacts that is corrected for. We should note that the 60% rule only implies the existence of a moderator; it does not indicate what variable is acting as the moderator. Identifying the actual moderator variable requires coding potential moderators and then performing subgroup analyses to determine whether the population correlations vary across the subgroup boundaries. In our review, this
Meta-Analytic Regression Strategy
Meta-Analytic Regression Strategy
Many questions cannot be answered by a matrix of meta-analyzed correlations. For example, do Leventhal’s (1980) justice criteria explain variance in procedural fairness perceptions beyond the effects of Thibaut and Walker’s (1975) process control construct? Do procedural, distributive, interpersonal, and informational justice each have independent effects on organizational commitment? Such questions require multiple regression to assess independent, semipartial effects. Fortunately, recent advances in meta
Many questions cannot be answered by a matrix of meta-analyzed correlations. For example, do Leventhal’s (1980) justice criteria explain variance in procedural fairness perceptions beyond the effects of Thibaut and Walker’s (1975) process control construct? Do procedural, distributive, interpersonal, and informational justice each have independent effects on organizational commitment? Such questions require multiple regression to assess independent, semipartial effects. Fortunately, recent advances in meta
et al.,
1992), and job performance (Schmidt, Hunter, & Outerbridge, 1986).
In practice, there are some decision points that researchers using meta- analytic regression will encounter (Viswesvaran & Ones, 1995). First, many researchers will conduct regressions on correlation matrices that vary in sample size. This raises the question of what sample size to use when computing the standard errors associated with the regression weights. Potential solutions include using the smallest cell sample size or using the mean sample size. We chose to use the harmonic mean of the correlation ma
In practice, there are some decision points that researchers using meta- analytic regression will encounter (Viswesvaran & Ones, 1995). First, many researchers will conduct regressions on correlation matrices that vary in sample size. This raises the question of what sample size to use when computing the standard errors associated with the regression weights. Potential solutions include using the smallest cell sample size or using the mean sample size. We chose to use the harmonic mean of the correlation ma
к
refers to the number of study correlations and N refers to the sample sizes of the studies. An inspection of the formula shows that the harmonic mean gives much less weight to substantially large individual study sample sizes, so it is always more conservative than the arithmetic mean (Viswesvaran & Ones, 1995). Note, however, that the sample size issue is not very critical to the current meta-analytic review. This is because the sample sizes for almost all of the cells of the correlation matrices are in th
Second, researchers must choose whether to use maximum-likelihood estimation (the choice of Hom
Second, researchers must choose whether to use maximum-likelihood estimation (the choice of Hom
et
al., 1992), ordinary least squares (the choice of Colquitt
et al.,
2000, Podsakoff
et al.,
1996, and Schmidt
et al.,
1986), or some other method. We elected to use ordinary least squares estimation, consistent with Colquitt
et al.
(2000), Podsakoff
et al.
(1996), and Schmidt
et al.
(1986). Ordinary least squares assumptions are less restrictive than maximum likelihood, which assumes multivariate normality. Maximum-likelihood estimation is also less optimal in instances in which the data are in the form of correlations rather than covariances (Cudeck, 1989). Given that meta-analysis results in correlational data, we believed that ordinary least squares would be more appropriate.
Results
Results
Construct Discrimination Questions
Construct Discrimination Questions
Research Question I concerned the magnitude of the relationships among the various organizational justice conceptualizations. Table 1 shows the correlations among process control, Leventhal criteria, interpersonal justice, informational justice, distributive justice, and procedural fairness perceptions. Cohen and Cohen (1983) classified correlations as high, moderate, or weak according to uncorrected r values of .50, .30, and .10, respectively. Thus, Table 1 shows high correlations among the justice concep
Research Question I concerned the magnitude of the relationships among the various organizational justice conceptualizations. Table 1 shows the correlations among process control, Leventhal criteria, interpersonal justice, informational justice, distributive justice, and procedural fairness perceptions. Cohen and Cohen (1983) classified correlations as high, moderate, or weak according to uncorrected r values of .50, .30, and .10, respectively. Thus, Table 1 shows high correlations among the justice concep
Table 1 also shows the correlations among the interactional justice dimensions. Interpersonal justice was highly related to informational justice (r = .57, rc = .66), although again not so highly that the two necessarily seem to be indicators of the same underlying construct. Interpersonal justice and informational justice were also highly correlated with procedural fairness perceptions (r = .56, rc = .63 and r = .51, rc = .58, respectively). These relationships were similar in magnitude to the process co
Table 1 also shows the correlations among the interactional justice dimensions. Interpersonal justice was highly related to informational justice (r = .57, rc = .66), although again not so highly that the two necessarily seem to be indicators of the same underlying construct. Interpersonal justice and informational justice were also highly correlated with procedural fairness perceptions (r = .56, rc = .63 and r = .51, rc = .58, respectively). These relationships were similar in magnitude to the process co
Interestingly, the relationships between interpersonal and informational justice and procedural fairness perceptions were not significantly stronger than the relationship between distributive justice and procedural fairness perceptions (r = .48, rc = .57). This suggests that interpersonal and informational justice should be considered to be distinct from procedural justice, just as the case with distributive justice. The uncorrected correlation of .48 for distributive justice and procedural fairness percep
Interestingly, the relationships between interpersonal and informational justice and procedural fairness perceptions were not significantly stronger than the relationship between distributive justice and procedural fairness perceptions (r = .48, rc = .57). This suggests that interpersonal and informational justice should be considered to be distinct from procedural justice, just as the case with distributive justice. The uncorrected correlation of .48 for distributive justice and procedural fairness percep
Combining all operationalizations, broadly defined procedural justice was strongly related to distributive justice (r = .56, rc = .67). The high standard deviation of the population correlation
Combining all operationalizations, broadly defined procedural justice was strongly related to distributive justice (r = .56, rc = .67). The high standard deviation of the population correlation
META-ANALYTIC REVIEW OF ORGANIZATIONAL JUSTICE
META-ANALYTIC REVIEW OF ORGANIZATIONAL JUSTICE
META-ANALYTIC REVIEW OF ORGANIZATIONAL JUSTICE
META-ANALYTIC REVIEW OF ORGANIZATIONAL JUSTICE
433
433
Figure
Table 1
Table 1
Table 1
Relationships Among Different Conceptualizations of Organizational Justice
Relationships Among Different Conceptualizations of Organizational Justice
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and the low variance explained from artifacts (Vatt = 2.74%) show that moderators exist in the broadly defined procedural justice-distributive justice relationship. Operationalization explains some of that variation, in that the highest relationship was evident when an indirect combination measure was used 0 = .63, r. = .77). Moreover, because their confidence intervals do not overlap, Table 2 shows that the indirect combination measure relationship is significantly stronger than the more
unidimensional
justice measures: procedural fairness perceptions (r = .48, rc = .57), process control (r = .27, rc = .34), Leventhal criteria (r = .46, r, = .55), interpersonal justice (r = .38, rc = .42), and informational justice (r = .39, rc = .46).
Proactive Research Questions
Proactive Research Questions
Research Question 2 explored whether the additional conceptualizations of justice over the course of its history have contributed incremental variance explained in regard to promoting procedural fairness perceptions. This was tested by regressing procedural fairness perceptions onto the various justice operationalizations using hierarchical regression. Order of entry was based on historical introduction, so the following steps were used: (a) Thibaut and Walker’s (1975) process control operationalization,
Research Question 2 explored whether the additional conceptualizations of justice over the course of its history have contributed incremental variance explained in regard to promoting procedural fairness perceptions. This was tested by regressing procedural fairness perceptions onto the various justice operationalizations using hierarchical regression. Order of entry was based on historical introduction, so the following steps were used: (a) Thibaut and Walker’s (1975) process control operationalization,
Bies
and Moag’s (1986) interactional justice construct, broken down into interpersonal and informational justice (as in Greenberg, 1993b).
The meta-analytic regression results are shown in Table 3. The original operationalization of procedural justice, process control, explained 26% of the variance in procedural fairness perceptions, with higher levels of process control producing more favorable fairness perceptions
The meta-analytic regression results are shown in Table 3. The original operationalization of procedural justice, process control, explained 26% of the variance in procedural fairness perceptions, with higher levels of process control producing more favorable fairness perceptions
(ß
= .51). Leventhal criteria explained an additional 21% of the variance, with higher levels of his criteria also producing more favorable perceptions
(ß
= .61). Interpersonal and informational justice explained an additional 6% of the variance in fairness perceptions. That effect was due primarily to interpersonal justice
(ß
= .29), although informational justice also had a significant effect
(ß
= .11).
Research Question 3 asked how much variance the justice operationalizations explained in procedural fairness perceptions beyond the effects of distributive justice. This was tested by regressing procedural fairness perceptions onto the various justice operationalizations after controlling for distributive justice. These regression results are shown in Table 4. Distributive justice explained 33% of the variance in procedural fairness perceptions, with higher levels of distributive justice being associated w
Research Question 3 asked how much variance the justice operationalizations explained in procedural fairness perceptions beyond the effects of distributive justice. This was tested by regressing procedural fairness perceptions onto the various justice operationalizations after controlling for distributive justice. These regression results are shown in Table 4. Distributive justice explained 33% of the variance in procedural fairness perceptions, with higher levels of distributive justice being associated w
(ß
= .57). The remaining justice operationalizations explained an incremental 24% of the variance. However, only two operationalizations had strong unique effects: Leventhal criteria
(ß
= .30) and interpersonal justice
(ß
= .26). Although statistically significant, the unique effects of process control
(ß
= .03) and informational justice
(ß
= .07) were not practically significant.
Reactive Research Questions
Reactive Research Questions
Research Questions 4-6 explored the relationships between the organizational justice dimensions and several key outcome variables. Table 5 presents the results for these research questions. Research Question 4 explored the relationships between
Research Questions 4-6 explored the relationships between the organizational justice dimensions and several key outcome variables. Table 5 presents the results for these research questions. Research Question 4 explored the relationships between
distribu-
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434
434
434
COLQUITT, CONLON, WESSON, PORTER, AND NG
COLQUITT, CONLON, WESSON, PORTER, AND NG
Table 2
Table 2
Table 2
Table 2
Relationship Between Distributive and Procedural Justice Conceptualizations (Including Interpersonal and Informational Justice)
Relationship Between Distributive and Procedural Justice Conceptualizations (Including Interpersonal and Informational Justice)
Conceptualization
Conceptualization
Conceptualization
Conceptualization
Distributive justice
Distributive justice
Distributive justice
TR
r (95% CI)
r (95% CI)
r (95% CI)
N (SDrO
N (SDrO
N (SDrO
k
k
k
(N)
Vm (%)
Vm (%)
Vm (%)
Broadly defined procedural justice
Broadly defined procedural justice
Broadly defined procedural justice
Broadly defined procedural justice
.56 (.52, .60)
.56 (.52, .60)
.56 (.52, .60)
.67 (.23)
.67 (.23)
.67 (.23)
92 (42,576)
92 (42,576)
92 (42,576)
2.74
2.74
2.74
Procedural fairness perceptions
Procedural fairness perceptions
Procedural fairness perceptions
Procedural fairness perceptions
.48 (.41, .55)
.48 (.41, .55)
.48 (.41, .55)
.57 (.28)
.57 (.28)
.57 (.28)
45(13,418)
45(13,418)
45(13,418)
3.41
3.41
3.41
Process control
Process control
Process control
Process control
.27 (.22, .33)
.27 (.22, .33)
.27 (.22, .33)
.34 (.13)
.34 (.13)
.34 (.13)
23(5,137)
23(5,137)
23(5,137)
24.15
24.15
24.15
Leventhal criteria
Leventhal criteria
Leventhal criteria
Leventhal criteria
.46 (.38, .54)
.46 (.38, .54)
.46 (.38, .54)
.55 (.17)
.55 (.17)
.55 (.17)
15 (4,743)
15 (4,743)
15 (4,743)
8.27
8.27
8.27
Interpersonal justice
Interpersonal justice
Interpersonal justice
Interpersonal justice
.38 (.26, .50)
.38 (.26, .50)
.38 (.26, .50)
.42 (.20)
.42 (.20)
.42 (.20)
9 (3,496)
9 (3,496)
9 (3,496)
5.62
5.62
5.62
informational justice
informational justice
informational justice
informational justice
.39 (.32, .47)
.39 (.32, .47)
.39 (.32, .47)
.46 (.15)
.46 (.15)
.46 (.15)
14 (3,807)
14 (3,807)
14 (3,807)
13.19
13.19
13.19
Indirect combination measure
Indirect combination measure
Indirect combination measure
Indirect combination measure
.63 (.59, .66)
.63 (.59, .66)
.63 (.59, .66)
.77 (.14)
.77 (.14)
.77 (.14)
54 (51,446)
54 (51,446)
54 (51,446)
2.32
2.32
2.32
Note, r = uncorrected population correlation; Cl = confidence interval around uncorrected population correlation; rc = corrected population correlation; SDrc = standard deviation of corrected population correlation;
Note, r = uncorrected population correlation; Cl = confidence interval around uncorrected population correlation; rc = corrected population correlation; SDrc = standard deviation of corrected population correlation;
к
= number of studies; Vart = percentage of variance in rc explained by study artifacts.
tive justice and the outcomes. Distributive justice had high correlations with outcome satisfaction (r = .52, rc — .61), job satisfaction (r = .46, rc = .56), organizational commitment (r = .42, r,. = .51), trust (r = .48, rc = .57), agent-referenced evaluation of authority (r = .53, = .59), and withdrawal (r = —.41, rc =
tive justice and the outcomes. Distributive justice had high correlations with outcome satisfaction (r = .52, rc — .61), job satisfaction (r = .46, rc = .56), organizational commitment (r = .42, r,. = .51), trust (r = .48, rc = .57), agent-referenced evaluation of authority (r = .53, = .59), and withdrawal (r = —.41, rc =
—.50). Distributive justice had moderate correlations with system- referenced evaluation of authority (r = .30, rc = .37), OCBOs (r = .20, rc = .25), and negative reactions (r = —.26, ra = —.30) and was weakly related to OCBIs (r = .13, rc = .15) and performance (r = .13, rc = .15).
—.50). Distributive justice had moderate correlations with system- referenced evaluation of authority (r = .30, rc = .37), OCBOs (r = .20, rc = .25), and negative reactions (r = —.26, ra = —.30) and was weakly related to OCBIs (r = .13, rc = .15) and performance (r = .13, rc = .15).
Research Question 5 explored relationships between procedural justice and the same set of outcomes. Combining all conceivable procedural justice conceptualizations, again labeled broadly defined procedural justice, we see that procedural justice had high correlations with outcome satisfaction (r = .40, rc = .48), job satisfaction (r = .51, rc = .62), organizational commitment (r = .48, rc = .57), trust (r = .52, rc = .61), and agent-referenced evaluation of authority (r = .56, rc = .64). Procedural justice
Research Question 5 explored relationships between procedural justice and the same set of outcomes. Combining all conceivable procedural justice conceptualizations, again labeled broadly defined procedural justice, we see that procedural justice had high correlations with outcome satisfaction (r = .40, rc = .48), job satisfaction (r = .51, rc = .62), organizational commitment (r = .48, rc = .57), trust (r = .52, rc = .61), and agent-referenced evaluation of authority (r = .56, rc = .64). Procedural justice
had weak correlations with OCBIs (r = .19, rc = .22). Table 5 also shows that moderators were present in the procedural justiceoutcome relationships, with the exception of the relationships with the OCB variables. Operationalization could be one potential moderator for several of the outcome variables, because the indirect
had weak correlations with OCBIs (r = .19, rc = .22). Table 5 also shows that moderators were present in the procedural justiceoutcome relationships, with the exception of the relationships with the OCB variables. Operationalization could be one potential moderator for several of the outcome variables, because the indirect
Table 3
Table 3
Table 3
Table 3
Incremental Effects of Justice Operationalizations on
Incremental Effects of Justice Operationalizations on
Procedural Fairness Perceptions
Procedural Fairness Perceptions
Regression step
Regression step
Regression step
Regression step
Total R2
Total R2
Total R2
Δ/?2
Δ/?2
Δ/?2
В
В
В
1. Process control
1. Process control
1. Process control
1. Process control
.26*
.26*
.26*
.26*
.26*
.26*
.51*
.51*
.51*
2. Leventhal criteria
2. Leventhal criteria
2. Leventhal criteria
2. Leventhal criteria
.47*
.47*
.47*
.21*
.21*
.21*
.61*
.61*
.61*
3. Interpersonal justice
3. Interpersonal justice
3. Interpersonal justice
3. Interpersonal justice
.53*
.53*
.53*
.06*
.06*
.06*
.28*
.28*
.28*
Informational justice
Informational justice
Informational justice
Informational justice
.11*
.11*
.11*
Note. N - 4,165 (based on the harmonic mean sample size of the Table 1 cells used in this regression).
Note. N - 4,165 (based on the harmonic mean sample size of the Table 1 cells used in this regression).
*p< .05.
*p< .05.
combination measure was significantly more related to job satisfaction, organizational commitment, and withdrawal than was any other operationalization.
combination measure was significantly more related to job satisfaction, organizational commitment, and withdrawal than was any other operationalization.
Research Question 6 explored relationships between interpersonal and informational justice and the outcome variables. Interpersonal justice was strongly related to agent-referenced evaluation of authority (r = .57, rc = .62) and moderately related to job satisfaction (r = .31, rc = .35), system-referenced evaluation of authority (r = .20, rc = .23), OCBIs (r = .23, rc = .29), and negative reactions (r = —.30, rc = —.35). It was weakly related to outcome satisfaction (r = .19), organizational commitment (
Research Question 6 explored relationships between interpersonal and informational justice and the outcome variables. Interpersonal justice was strongly related to agent-referenced evaluation of authority (r = .57, rc = .62) and moderately related to job satisfaction (r = .31, rc = .35), system-referenced evaluation of authority (r = .20, rc = .23), OCBIs (r = .23, rc = .29), and negative reactions (r = —.30, rc = —.35). It was weakly related to outcome satisfaction (r = .19), organizational commitment (
Research Question 7 examined the unique effects of the justice dimensions on the outcome variables considered simultaneously. Table 6 presents beta weights derived from regressing each of the outcomes on all four justice dimensions simultaneously. The table also presents unique R2 values derived from a “usefulness analysis” in which the effects of one justice dimension were examined after controlling for the others. The table also presents the total variance explained in each outcome by the justice dimensi
Research Question 7 examined the unique effects of the justice dimensions on the outcome variables considered simultaneously. Table 6 presents beta weights derived from regressing each of the outcomes on all four justice dimensions simultaneously. The table also presents unique R2 values derived from a “usefulness analysis” in which the effects of one justice dimension were examined after controlling for the others. The table also presents the total variance explained in each outcome by the justice dimensi
The regression results in Table 6 allowed us to examine the adequacy of the distributive dominance, two-factor, and agentsystem reactive models. Leventhal’s (1980) distributive dominance model would predict higher unique effects for
The regression results in Table 6 allowed us to examine the adequacy of the distributive dominance, two-factor, and agentsystem reactive models. Leventhal’s (1980) distributive dominance model would predict higher unique effects for
distribu-
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435
Table 4
Table 4
Table 4
Table 4
Incremental Effects of Justice Operationalizations on Procedural
Incremental Effects of Justice Operationalizations on Procedural
Fairness Perceptions Beyond Distributive Justice Effects
Fairness Perceptions Beyond Distributive Justice Effects
Regression step
Regression step
Regression step
Regression step
Total R2
Total R2
Total R2
Δ«2
Δ«2
Δ«2
В
В
В
1. Distributive justice
1. Distributive justice
1. Distributive justice
1. Distributive justice
.33*
.33*
.33*
.33*
.33*
.33*
.57*
.57*
.57*
2. Process control
2. Process control
2. Process control
2. Process control
.57*
.57*
.57*
.24*
.24*
.24*
.03*
.03*
.03*
Leventhal criteria
Leventhal criteria
Leventhal criteria
Leventhal criteria
.30*
.30*
.30*
Interpersonal justice
Interpersonal justice
Interpersonal justice
Interpersonal justice
.26*
.26*
.26*
Informational justice
Informational justice
Informational justice
Informational justice
.07*
.07*
.07*
Note. N = 4,165 (based on the harmonic mean sample size of the Table 1 cells used in this regression).
Note. N = 4,165 (based on the harmonic mean sample size of the Table 1 cells used in this regression).
* p < .05.
* p < .05.
tive justice than for the other three justice forms. This prediction was supported for two outcomes (outcome satisfaction and withdrawal) and was refuted for the remaining nine outcomes.
tive justice than for the other three justice forms. This prediction was supported for two outcomes (outcome satisfaction and withdrawal) and was refuted for the remaining nine outcomes.
Sweeney and McFarlin’s (1993) two-factor model would predict higher unique effects of distributive justice for person-referenced outcomes and higher unique effects of procedural justice for system-referenced outcomes. This prediction was supported for five outcomes (outcome satisfaction, job satisfaction, organizational commitment, system-referenced evaluation of authority, and performance) and was refuted for three outcomes (OCBOs, withdrawal, and negative reactions). The two-factor model was not relevan
Sweeney and McFarlin’s (1993) two-factor model would predict higher unique effects of distributive justice for person-referenced outcomes and higher unique effects of procedural justice for system-referenced outcomes. This prediction was supported for five outcomes (outcome satisfaction, job satisfaction, organizational commitment, system-referenced evaluation of authority, and performance) and was refuted for three outcomes (OCBOs, withdrawal, and negative reactions). The two-factor model was not relevan
Bies
Bies
and Moag’s (1986) agent-system model would predict higher unique effects of interpersonal or informational justice for agent-referenced outcomes and higher unique effects of procedural justice for system-referenced outcomes. This prediction was supported for five outcomes (job satisfaction, organizational commitment, agent-referenced evaluation of authority, OCBIs, and performance) and refuted for five outcomes (system-referenced evaluation of authority, trust, OCBOs, withdrawal, and negative reactions).
Discussion
Discussion
This meta-analytic review, consisting of 120 separate metaanalyses of 183 empirical studies, explored three types of research questions to aid further theory development in the organizational justice literature. The first type of question was related to construct discrimination (i.e., how highly related are the various facets of organizational justice?). Process control and Leventhal criteria, the two original procedural justice operationalizations, were highly correlated, although perhaps not as highly as
This meta-analytic review, consisting of 120 separate metaanalyses of 183 empirical studies, explored three types of research questions to aid further theory development in the organizational justice literature. The first type of question was related to construct discrimination (i.e., how highly related are the various facets of organizational justice?). Process control and Leventhal criteria, the two original procedural justice operationalizations, were highly correlated, although perhaps not as highly as
relationship is strongest when an indirect combination measure is used and weaker when procedural fairness perceptions, Leventhal criteria, and especially process control are used.
relationship is strongest when an indirect combination measure is used and weaker when procedural fairness perceptions, Leventhal criteria, and especially process control are used.
The second type of research question dealt with proactive research, which is concerned with creating procedural fairness perceptions by adhering to certain rules, such as providing process control, being consistent, treating people with sensitivity, or explaining things adequately. Our results showed that the historical progression of proactive research on procedural justice has in fact contributed to our ability to promote procedural fairness perceptions. The original conceptualization, Thibaut and Wal
The second type of research question dealt with proactive research, which is concerned with creating procedural fairness perceptions by adhering to certain rules, such as providing process control, being consistent, treating people with sensitivity, or explaining things adequately. Our results showed that the historical progression of proactive research on procedural justice has in fact contributed to our ability to promote procedural fairness perceptions. The original conceptualization, Thibaut and Wal
The concepts of interpersonal and informational justice, drawn from the field’s recent interest in interactional justice, show a more mixed pattern of results. Their correlations with procedural fairness perceptions were just as strong as the correlations for Leventhal criteria. However, although they explained significant incremental variance in fairness perceptions, their contribution was small in comparison with the contributions of the other justice facets. Thus, interpersonal and informational justi
The concepts of interpersonal and informational justice, drawn from the field’s recent interest in interactional justice, show a more mixed pattern of results. Their correlations with procedural fairness perceptions were just as strong as the correlations for Leventhal criteria. However, although they explained significant incremental variance in fairness perceptions, their contribution was small in comparison with the contributions of the other justice facets. Thus, interpersonal and informational justi
Because it is well known that the fairness of decision-making procedures is often judged according to the kinds of outcomes one receives (Lind & Tyler, 1988), it is also important to show that the various conceptualizations of procedural justice are important even after control for distributive justice. If this had not been the case, then the procedural justice literature would have contributed little over earlier work by Homans (1961), Adams (1965), Leventhal (1976), and Deutsch (1975). Our results showed
Because it is well known that the fairness of decision-making procedures is often judged according to the kinds of outcomes one receives (Lind & Tyler, 1988), it is also important to show that the various conceptualizations of procedural justice are important even after control for distributive justice. If this had not been the case, then the procedural justice literature would have contributed little over earlier work by Homans (1961), Adams (1965), Leventhal (1976), and Deutsch (1975). Our results showed
Turning to our third type of research question, reactive research, we tested three separate reactive models: Leventhal’s (1980) distributive dominance model, Sweeney and McFarlin’s (1993) two- factor model, and
Turning to our third type of research question, reactive research, we tested three separate reactive models: Leventhal’s (1980) distributive dominance model, Sweeney and McFarlin’s (1993) two- factor model, and
Bies
and Moag’s (1986) agent-system model. Support for these models can be evaluated by examining the relative effects of distributive, procedural, interpersonal, and informational justice on the basis of the size of their meta-analytic correlations, as well as their unique effects in the meta-analytic regressions. We find little support for the distributive dominance
436
436
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COLQUITT, CONLON, WESSON, PORTER, AND NG
COLQUITT, CONLON, WESSON, PORTER, AND NG
Table 5
Table 5
Table 5
Table 5
Relationships Between Organizational Justice Dimensions and Outcome Variables
Relationships Between Organizational Justice Dimensions and Outcome Variables
Dimension
Dimension
Dimension
Dimension
r (95% CI)
r (95% CI)
r (95% CI)
% «DrJ
% «DrJ
% «DrJ
k
k
k
(N)
van
van
van
(%)
(%)
r (95% CI)
r (95% CI)
r (95% CI)
%
%
%
W
к
к
к
IN)
vart (%)
vart (%)
vart (%)
TR
Outcome satisfaction
Outcome satisfaction
Outcome satisfaction
Job satisfaction
Job satisfaction
Job satisfaction
Broadly defined procedural justice
Broadly defined procedural justice
Broadly defined procedural justice
Broadly defined procedural justice
.40 (.35, .46)
.40 (.35, .46)
.40 (.35, .46)
.48 (.18)
.48 (.18)
.48 (.18)
30 (8,073)
30 (8,073)
30 (8,073)
10.02
10.02
10.02
.51 (.46, .56)
.51 (.46, .56)
.51 (.46, .56)
.62 (.18)
.62 (.18)
.62 (.18)
40 (31,774)
40 (31,774)
40 (31,774)
2.88
2.88
2.88
Procedural fairness perceptions
Procedural fairness perceptions
Procedural fairness perceptions
Procedural fairness perceptions
.45 (.36, .54)
.45 (.36, .54)
.45 (.36, .54)
.53 (.17)
.53 (.17)
.53 (.17)
11 (4,420)
11 (4,420)
11 (4,420)
6.59
6.59
6.59
.33 (.28, .38)
.33 (.28, .38)
.33 (.28, .38)
.40 (.09)
.40 (.09)
.40 (.09)
11 (4,958)
11 (4,958)
11 (4,958)
24.00
24.00
24.00
Process control
Process control
Process control
Process control
.38 (.27, .48)
.38 (.27, .48)
.38 (.27, .48)
.45 (.16)
.45 (.16)
.45 (.16)
8(1,774)
8(1,774)
8(1,774)
14.74
14.74
14.74
.30 (.25, .35)
.30 (.25, .35)
.30 (.25, .35)
.37 (.05)
.37 (.05)
.37 (.05)
5 (2,577)
5 (2,577)
5 (2,577)
50.39
50.39
50.39
Leventhal criteria
Leventhal criteria
Leventhal criteria
Leventhal criteria
.25 (.13, .37)
.25 (.13, .37)
.25 (.13, .37)
.32 (.17)
.32 (.17)
.32 (.17)
6(1,796)
6(1,796)
6(1,796)
13.03
13.03
13.03
.36 (.33, .40)
.36 (.33, .40)
.36 (.33, .40)
.42 (.00)
.42 (.00)
.42 (.00)
4(2,315)
4(2,315)
4(2,315)
100.00
100.00
100.00
Interpersonal justice
Interpersonal justice
Interpersonal justice
Interpersonal justice
.19
.19
.19
1 (301)
1 (301)
1 (301)
.31 (.26,.36)
.31 (.26,.36)
.31 (.26,.36)
.35 (.02)
.35 (.02)
.35 (.02)
2(1,795)
2(1,795)
2(1,795)
65.96
65.96
65.96
Informational justice
Informational justice
Informational justice
Informational justice
.27 (.21, .33)
.27 (.21, .33)
.27 (.21, .33)
.30 (.04)
.30 (.04)
.30 (.04)
4(1,404)
4(1,404)
4(1,404)
65.02
65.02
65.02
.38 (.34, .42)
.38 (.34, .42)
.38 (.34, .42)
.43 (.00)
.43 (.00)
.43 (.00)
2(1,872)
2(1,872)
2(1,872)
100.00
100.00
100.00
Indirect combination measure
Indirect combination measure
Indirect combination measure
Indirect combination measure
.47 (.39, .54)
.47 (.39, .54)
.47 (.39, .54)
.54 (.15)
.54 (.15)
.54 (.15)
14 (2,242)
14 (2,242)
14 (2,242)
18.87
18.87
18.87
.55 (.49, .61)
.55 (.49, .61)
.55 (.49, .61)
.68 (.17)
.68 (.17)
.68 (.17)
22(25,221)
22(25,221)
22(25,221)
2.07
2.07
2.07
Distributive justice
Distributive justice
Distributive justice
Distributive justice
.52 (.46, .59)
.52 (.46, .59)
.52 (.46, .59)
.61 (.20)
.61 (.20)
.61 (.20)
28 (9,321)
28 (9,321)
28 (9,321)
5.07
5.07
5.07
.46 (.42, .49)
.46 (.42, .49)
.46 (.42, .49)
.56 (.09)
.56 (.09)
.56 (.09)
24 (57,515)
24 (57,515)
24 (57,515)
8.31
8.31
8.31
TR
Organizational commitment
Organizational commitment
Organizational commitment
Trust
Trust
Trust
Broadly defined procedural justice
Broadly defined procedural justice
Broadly defined procedural justice
Broadly defined procedural justice
.48 (.44, .52)
.48 (.44, .52)
.48 (.44, .52)
.57 (.18)
.57 (.18)
.57 (.18)
53 (33,455)
53 (33,455)
53 (33,455)
3.84
3.84
3.84
.52 (.44, .59)
.52 (.44, .59)
.52 (.44, .59)
.61 (.20)
.61 (.20)
.61 (.20)
24 (4,522)
24 (4,522)
24 (4,522)
8.42
8.42
8.42
Procedural fairness perceptions
Procedural fairness perceptions
Procedural fairness perceptions
Procedural fairness perceptions
.32 (.25, .39)
.32 (.25, .39)
.32 (.25, .39)
.37 (.16)
.37 (.16)
.37 (.16)
18 (6,767)
18 (6,767)
18 (6,767)
9.58
9.58
9.58
.56 (.49, .64)
.56 (.49, .64)
.56 (.49, .64)
.62 (.08)
.62 (.08)
.62 (.08)
7 (802)
7 (802)
7 (802)
39.78
39.78
39.78
Process control
Process control
Process control
Process control
.22 (.18, .27)
.22 (.18, .27)
.22 (.18, .27)
.27 (.05)
.27 (.05)
.27 (.05)
7 (2,898)
7 (2,898)
7 (2,898)
53.50
53.50
53.50
.40 (.30, .50)
.40 (.30, .50)
.40 (.30, .50)
.47 (.13)
.47 (.13)
.47 (.13)
7(1,031)
7(1,031)
7(1,031)
26.54
26.54
26.54
Leventhal criteria
Leventhal criteria
Leventhal criteria
Leventhal criteria
.26 (.22, .29)
.26 (.22, .29)
.26 (.22, .29)
.30 (.00)
.30 (.00)
.30 (.00)
5 (3,162)
5 (3,162)
5 (3,162)
100.00
100.00
100.00
.58 (.09, .99)
.58 (.09, .99)
.58 (.09, .99)
.65 (.38)
.65 (.38)
.65 (.38)
2 (628)
2 (628)
2 (628)
1.23
1.23
1.23
Interpersonal justice
Interpersonal justice
Interpersonal justice
Interpersonal justice
.16 (.11, .20)
.16 (.11, .20)
.16 (.11, .20)
.19 (.00)
.19 (.00)
.19 (.00)
2(1,824)
2(1,824)
2(1,824)
100.00
100.00
100.00
Informational justice
Informational justice
Informational justice
Informational justice
.26 (.18, .34)
.26 (.18, .34)
.26 (.18, .34)
.29 (.14)
.29 (.14)
.29 (.14)
10 (3,968)
10 (3,968)
10 (3,968)
12.01
12.01
12.01
.43 (.30, .57)
.43 (.30, .57)
.43 (.30, .57)
.51 (.11)
.51 (.11)
.51 (.11)
3 (487)
3 (487)
3 (487)
30.21
30.21
30.21
Indirect combination measure
Indirect combination measure
Indirect combination measure
Indirect combination measure
.55 (.51, .58)
.55 (.51, .58)
.55 (.51, .58)
.65 (.10)
.65 (.10)
.65 (.10)
26 (24,606)
26 (24,606)
26 (24,606)
6.10
6.10
6.10
.55 (.45, .66)
.55 (.45, .66)
.55 (.45, .66)
.64 (.18)
.64 (.18)
.64 (.18)
10(2,169)
10(2,169)
10(2,169)
8.02
8.02
8.02
Distributive justice
Distributive justice
Distributive justice
Distributive justice
.42 (.38, .47)
.42 (.38, .47)
.42 (.38, .47)
.51 (.13)
.51 (.13)
.51 (.13)
24 (27,805)
24 (27,805)
24 (27,805)
4.11
4.11
4.11
.48 (.40, .57)
.48 (.40, .57)
.48 (.40, .57)
.57 (.13)
.57 (.13)
.57 (.13)
8 (1,735)
8 (1,735)
8 (1,735)
17.24
17.24
17.24
TR
Evaluation of authority: Agent referenced
Evaluation of authority: Agent referenced
Evaluation of authority: Agent referenced
Evaluation of authority: System referenced
Evaluation of authority: System referenced
Evaluation of authority: System referenced
Broadly defined procedural justice
Broadly defined procedural justice
Broadly defined procedural justice
Broadly defined procedural justice
.56 (.52, .59)
.56 (.52, .59)
.56 (.52, .59)
.64 (.11)
.64 (.11)
.64 (.11)
33 (20,034)
33 (20,034)
33 (20,034)
7.17
7.17
7.17
.35 (-31,-40)
.35 (-31,-40)
.35 (-31,-40)
.42 (.13)
.42 (.13)
.42 (.13)
25 (9,708)
25 (9,708)
25 (9,708)
13.09
13.09
13.09
Procedural fairness perceptions
Procedural fairness perceptions
Procedural fairness perceptions
Procedural fairness perceptions
.53 (.46, .60)
.53 (.46, .60)
.53 (.46, .60)
.60 (.13)
.60 (.13)
.60 (.13)
13 (4,753)
13 (4,753)
13 (4,753)
8.76
8.76
8.76
.45 (.42, .48)
.45 (.42, .48)
.45 (.42, .48)
.51 (.12)
.51 (.12)
.51 (.12)
14 (5,637)
14 (5,637)
14 (5,637)
11.63
11.63
11.63
Process control
Process control
Process control
Process control
.42 (.35, .50)
.42 (.35, .50)
.42 (.35, .50)
.50 (.14)
.50 (.14)
.50 (.14)
10 (3,436)
10 (3,436)
10 (3,436)
12.56
12.56
12.56
.12 (.05, .20)
.12 (.05, .20)
.12 (.05, .20)
.16 (.00)
.16 (.00)
.16 (.00)
3(663)
3(663)
3(663)
100.00
100.00
100.00
Leventhal criteria
Leventhal criteria
Leventhal criteria
Leventhal criteria
.53 (.41, .64)
.53 (.41, .64)
.53 (.41, .64)
.63 (.17)
.63 (.17)
.63 (.17)
7 (3,104)
7 (3,104)
7 (3,104)
4.86
4.86
4.86
.19 (.02, .36)
.19 (.02, .36)
.19 (.02, .36)
.22 (.15)
.22 (.15)
.22 (.15)
3 (427)
3 (427)
3 (427)
29.27
29.27
29.27
Interpersonal justice
Interpersonal justice
Interpersonal justice
Interpersonal justice
.57 (.43, .71)
.57 (.43, .71)
.57 (.43, .71)
.62 (.17)
.62 (.17)
.62 (.17)
5 (2,534)
5 (2,534)
5 (2,534)
3.44
3.44
3.44
.20 (.01, .38)
.20 (.01, .38)
.20 (.01, .38)
.23 (.16)
.23 (.16)
.23 (.16)
3 (469)
3 (469)
3 (469)
22.95
22.95
22.95
Informational justice
Informational justice
Informational justice
Informational justice
.58 (.46, .71)
.58 (.46, .71)
.58 (.46, .71)
.65 (.21)
.65 (.21)
.65 (.21)
9 (3,210)
9 (3,210)
9 (3,210)
3.21
3.21
3.21
.42 (.29, .55)
.42 (.29, .55)
.42 (.29, .55)
.47 (.15)
.47 (.15)
.47 (.15)
5(1,035)
5(1,035)
5(1,035)
14.94
14.94
14.94
Indirect combination measure
Indirect combination measure
Indirect combination measure
Indirect combination measure
.58 (.54, .62)
.58 (.54, .62)
.58 (.54, .62)
.67 (.05)
.67 (.05)
.67 (.05)
9 (13,850)
9 (13,850)
9 (13,850)
6.65
6.65
6.65
.31 (.24, .38)
.31 (.24, .38)
.31 (.24, .38)
.37 (.12)
.37 (.12)
.37 (.12)
11 (3,790)
11 (3,790)
11 (3,790)
17.96
17.96
17.96
Distributive justice
Distributive justice
Distributive justice
Distributive justice
.53 (.46, .61)
.53 (.46, .61)
.53 (.46, .61)
.59 (.15)
.59 (.15)
.59 (.15)
13 (16,963)
13 (16,963)
13 (16,963)
1.96
1.96
1.96
.30 (.24, .36)
.30 (.24, .36)
.30 (.24, .36)
.37 (.12)
.37 (.12)
.37 (.12)
13 (4,103)
13 (4,103)
13 (4,103)
20.64
20.64
20.64
TR
OCBs: Individual referenced
OCBs: Individual referenced
OCBs: Individual referenced
OCBs: Organization referenced
OCBs: Organization referenced
OCBs: Organization referenced
Broadly defined procedural justice
Broadly defined procedural justice
Broadly defined procedural justice
Broadly defined procedural justice
.19 (.16, .22)
.19 (.16, .22)
.19 (.16, .22)
.22 (.00)
.22 (.00)
.22 (.00)
15 (4,414)
15 (4,414)
15 (4,414)
100.00
100.00
100.00
.23 (.19, .26)
.23 (.19, .26)
.23 (.19, .26)
.27 (.04)
.27 (.04)
.27 (.04)
15(3,176)
15(3,176)
15(3,176)
78.62
78.62
78.62
Procedural fairness perceptions
Procedural fairness perceptions
Procedural fairness perceptions
Procedural fairness perceptions
.21 (.17, .25)
.21 (.17, .25)
.21 (.17, .25)
.25 (.00)
.25 (.00)
.25 (.00)
2(1,872)
2(1,872)
2(1,872)
100.00
100.00
100.00
.21
.21
.21
1 (140)
1 (140)
1 (140)
Process control
Process control
Process control
Process control
.16 (.12, .20)
.16 (.12, .20)
.16 (.12, .20)
.21 (.00)
.21 (.00)
.21 (.00)
3 (2,000)
3 (2,000)
3 (2,000)
100.00
100.00
100.00
.14
.14
.14
1 (206)
1 (206)
1 (206)
Leventhal criteria
Leventhal criteria
Leventhal criteria
Leventhal criteria
.18 (.14, .23)
.18 (.14, .23)
.18 (.14, .23)
.22 (.01)
.22 (.01)
.22 (.01)
3 (2,108)
3 (2,108)
3 (2,108)
85.39
85.39
85.39
.15 (.06, .24)
.15 (.06, .24)
.15 (.06, .24)
.18 (.00)
.18 (.00)
.18 (.00)
2(431)
2(431)
2(431)
100.00
100.00
100.00
Interpersonal justice
Interpersonal justice
Interpersonal justice
Interpersonal justice
.23 (.18, .27)
.23 (.18, .27)
.23 (.18, .27)
.29 (.00)
.29 (.00)
.29 (.00)
2(1,794)
2(1,794)
2(1,794)
100.00
100.00
100.00
Informational justice
Informational justice
Informational justice
Informational justice
.21 (.17, .26)
.21 (.17, .26)
.21 (.17, .26)
.26 (.00)
.26 (.00)
.26 (.00)
2(1,883)
2(1,883)
2(1,883)
100.00
100.00
100.00
.18
.18
.18
1 (206)
1 (206)
1 (206)
Indirect combination measure
Indirect combination measure
Indirect combination measure
Indirect combination measure
.19 (.14, .23)
.19 (.14, .23)
.19 (.14, .23)
.22 (.02)
.22 (.02)
.22 (.02)
10(1,994)
10(1,994)
10(1,994)
90.18
90.18
90.18
.25 (.20, .30)
.25 (.20, .30)
.25 (.20, .30)
.30 (.06)
.30 (.06)
.30 (.06)
9(1,961)
9(1,961)
9(1,961)
63.06
63.06
63.06
Distributive justice
Distributive justice
Distributive justice
Distributive justice
.13 (.09, .17)
.13 (.09, .17)
.13 (.09, .17)
.15 (.02)
.15 (.02)
.15 (.02)
6 (2,633)
6 (2,633)
6 (2,633)
86.57
86.57
86.57
.20 (.14, .26)
.20 (.14, .26)
.20 (.14, .26)
.25 (.00)
.25 (.00)
.25 (.00)
5 (903)
5 (903)
5 (903)
100.00
100.00
100.00
TR
Withdrawal
Withdrawal
Withdrawal
Negative reactions
Negative reactions
Negative reactions
Broadly defined procedural justice
Broadly defined procedural justice
Broadly defined procedural justice
Broadly defined procedural justice
-.36 (-.42, -.31)
-.36 (-.42, -.31)
-.36 (-.42, -.31)
-.46 (.20)
-.46 (.20)
-.46 (.20)
39 (24,273)
39 (24,273)
39 (24,273)
4.12
4.12
4.12
-.27 (-.33, -.21)
-.27 (-.33, -.21)
-.27 (-.33, -.21)
-.31 (.18)
-.31 (.18)
-.31 (.18)
27 (6,275)
27 (6,275)
27 (6,275)
13.37
13.37
13.37
Procedural fairness perceptions
Procedural fairness perceptions
Procedural fairness perceptions
Procedural fairness perceptions
-.27 (-.32, -.21)
-.27 (-.32, -.21)
-.27 (-.32, -.21)
-.34 (.14)
-.34 (.14)
-.34 (.14)
21 (7,344)
21 (7,344)
21 (7,344)
14.46
14.46
14.46
-.33 (-.39, -.26)
-.33 (-.39, -.26)
-.33 (-.39, -.26)
-.38 (.12)
-.38 (.12)
-.38 (.12)
13 (3,563)
13 (3,563)
13 (3,563)
22.15
22.15
22.15
Process control
Process control
Process control
Process control
-.19 (-.27, -.10)
-.19 (-.27, -.10)
-.19 (-.27, -.10)
-.24 (.14)
-.24 (.14)
-.24 (.14)
10(1,190)
10(1,190)
10(1,190)
39.94
39.94
39.94
-.23 (-.27, -.19)
-.23 (-.27, -.19)
-.23 (-.27, -.19)
-.30 (.00)
-.30 (.00)
-.30 (.00)
3 (2,094)
3 (2,094)
3 (2,094)
100.00
100.00
100.00
Leventhal criteria
Leventhal criteria
Leventhal criteria
Leventhal criteria
-.23 (-.30, -.16)
-.23 (-.30, -.16)
-.23 (-.30, -.16)
-.29 (.07)
-.29 (.07)
-.29 (.07)
6(1,431)
6(1,431)
6(1,431)
50.87
50.87
50.87
-.28 (-.35, -.22)
-.28 (-.35, -.22)
-.28 (-.35, -.22)
-.35 (.06)
-.35 (.06)
-.35 (.06)
5 (2,308)
5 (2,308)
5 (2,308)
34.76
34.76
34.76
Interpersonal justice
Interpersonal justice
Interpersonal justice
Interpersonal justice
-.02 (-.13, .09)
-.02 (-.13, .09)
-.02 (-.13, .09)
-.02 (.00)
-.02 (.00)
-.02 (.00)
2(316)
2(316)
2(316)
100.00
100.00
100.00
-.30 (-.35, -.26)
-.30 (-.35, -.26)
-.30 (-.35, -.26)
-.35 (.04)
-.35 (.04)
-.35 (.04)
7 (2,707)
7 (2,707)
7 (2,707)
58.78
58.78
58.78
Informational justice
Informational justice
Informational justice
Informational justice
-.21 (-.34, -.07)
-.21 (-.34, -.07)
-.21 (-.34, -.07)
-.24 (.21)
-.24 (.21)
-.24 (.21)
8(1,692)
8(1,692)
8(1,692)
11.42
11.42
11.42
-.29 (-.34, -.24)
-.29 (-.34, -.24)
-.29 (-.34, -.24)
-.33 (.06)
-.33 (.06)
-.33 (.06)
8(2,731)
8(2,731)
8(2,731)
45.25
45.25
45.25
Indirect combination measure
Indirect combination measure
Indirect combination measure
Indirect combination measure
-.44 (-.56, -.32)
-.44 (-.56, -.32)
-.44 (-.56, -.32)
-.55 (.19)
-.55 (.19)
-.55 (.19)
6 (14,392)
6 (14,392)
6 (14,392)
1.11
1.11
1.11
-.20 (-.35, -.05)
-.20 (-.35, -.05)
-.20 (-.35, -.05)
-.22 (.21)
-.22 (.21)
-.22 (.21)
7(1,807)
7(1,807)
7(1,807)
9.28
9.28
9.28
Distributive justice
Distributive justice
Distributive justice
Distributive justice
-.41 (-.46, -.37)
-.41 (-.46, -.37)
-.41 (-.46, -.37)
-.50 (.12)
-.50 (.12)
-.50 (.12)
18(15,888)
18(15,888)
18(15,888)
7.45
7.45
7.45
-.26 (-.35, -.17)
-.26 (-.35, -.17)
-.26 (-.35, -.17)
-.30 (.17)
-.30 (.17)
-.30 (.17)
13 (3,782)
13 (3,782)
13 (3,782)
12.27
12.27
12.27
TR
Performance
Performance
Performance
Broadly defined procedural justice
Broadly defined procedural justice
Broadly defined procedural justice
Broadly defined procedural justice
.30 (.21,-39)
.30 (.21,-39)
.30 (.21,-39)
.36 (.29)
.36 (.29)
.36 (.29)
30 (8,317)
30 (8,317)
30 (8,317)
4.83
4.83
4.83
Procedural fairness perceptions
Procedural fairness perceptions
Procedural fairness perceptions
Procedural fairness perceptions
.30 (.17, .43)
.30 (.17, .43)
.30 (.17, .43)
.36 (.33)
.36 (.33)
.36 (.33)
18 (6,925)
18 (6,925)
18 (6,925)
2.71
2.71
2.71
Process control
Process control
Process control
Process control
.14 (-.01,-29)
.14 (-.01,-29)
.14 (-.01,-29)
.17 (.25)
.17 (.25)
.17 (.25)
8(1,002)
8(1,002)
8(1,002)
16.17
16.17
16.17
Leventhal criteria
Leventhal criteria
Leventhal criteria
Leventhal criteria
.08 (-.05, .21)
.08 (-.05, .21)
.08 (-.05, .21)
■ 10(.ll)
■ 10(.ll)
■ 10(.ll)
3 (501)
3 (501)
3 (501)
44.34
44.34
44.34
Interpersonal justice
Interpersonal justice
Interpersonal justice
Interpersonal justice
.03 (-.14, .20)
.03 (-.14, .20)
.03 (-.14, .20)
.03 (.11)
.03 (.11)
.03 (.11)
2 (389)
2 (389)
2 (389)
34.78
34.78
34.78
Informational justice
Informational justice
Informational justice
Informational justice
.11 (.00, .22)
.11 (.00, .22)
.11 (.00, .22)
.13 (.11)
.13 (.11)
.13 (.11)
4(1,036)
4(1,036)
4(1,036)
29.79
29.79
29.79
Indirect combination measure
Indirect combination measure
Indirect combination measure
Indirect combination measure
.23 (.12, .35)
.23 (.12, .35)
.23 (.12, .35)
.27 (.00)
.27 (.00)
.27 (.00)
7 (1,084)
7 (1,084)
7 (1,084)
23.83
23.83
23.83
Distributive justice
Distributive justice
Distributive justice
Distributive justice
.13 (.03, .22)
.13 (.03, .22)
.13 (.03, .22)
.15 (.18)
.15 (.18)
.15 (.18)
13(2,294) .
13(2,294) .
13(2,294) .
18.43
18.43
18.43
Note. r = uncorrected population correlation; CI = confidence interval around uncorrected population correlation; r. = corrected population correlation; SDr = standard deviation of corrected population correlation;
Note. r = uncorrected population correlation; CI = confidence interval around uncorrected population correlation; r. = corrected population correlation; SDr = standard deviation of corrected population correlation;
к
= number of studies; Vart = percentage of variance in rc explained by study artifacts; OCBs = organizational citizenship behaviors.
META-ANALYTIC REVIEW OF ORGANIZATIONAL JUSTICE
META-ANALYTIC REVIEW OF ORGANIZATIONAL JUSTICE
META-ANALYTIC REVIEW OF ORGANIZATIONAL JUSTICE
META-ANALYTIC REVIEW OF ORGANIZATIONAL JUSTICE
437
437
Table 6
Table 6
Table 6
Table 6
Unique Effects of Procedural, Interpersonal, Informational, and Distributive Justice on Outcome Variables
Unique Effects of Procedural, Interpersonal, Informational, and Distributive Justice on Outcome Variables
Outcome variable
Outcome variable
Outcome variable
Outcome variable
Justice dimension
Justice dimension
Justice dimension
Total R2
Total R2
Total R2
TR
Procedural
Procedural
Procedural
Interpersonal
Interpersonal
Interpersonal
Informational
Informational
Informational
Distributive
Distributive
Distributive
Outcome satisfaction (N = 1,792)
Outcome satisfaction (N = 1,792)
Outcome satisfaction (N = 1,792)
Outcome satisfaction (N = 1,792)
ß
ß
ß
ß
.17*
.17*
.17*
-.08*
-.08*
-.08*
.02
.02
.02
.54*
.54*
.54*
Unique R2
Unique R2
Unique R2
Unique R2
.02*
.02*
.02*
.00*
.00*
.00*
.00
.00
.00
.18*
.18*
.18*
.39*
.39*
.39*
Job satisfaction (N = 4,039)
Job satisfaction (N = 4,039)
Job satisfaction (N = 4,039)
Job satisfaction (N = 4,039)
ß
ß
ß
ß
.48*
.48*
.48*
-.09*
-.09*
-.09*
.13*
.13*
.13*
.26*
.26*
.26*
Unique R2
Unique R2
Unique R2
Unique R2
.11*
.11*
.11*
.01*
.01*
.01*
.01*
.01*
.01*
.04*
.04*
.04*
.45*
.45*
.45*
Organizational commitment (N = 4,582)
Organizational commitment (N = 4,582)
Organizational commitment (N = 4,582)
Organizational commitment (N = 4,582)
ß
ß
ß
ß
.42*
.42*
.42*
-.18*
-.18*
-.18*
.07*
.07*
.07*
.31*
.31*
.31*
Unique R2
Unique R2
Unique R2
Unique R2
.09*
.09*
.09*
.02*
.02*
.02*
.00*
.00*
.00*
.06*
.06*
.06*
.35*
.35*
.35*
Evaluation of authority: Agent-referenced (N = 4,517)
Evaluation of authority: Agent-referenced (N = 4,517)
Evaluation of authority: Agent-referenced (N = 4,517)
Evaluation of authority: Agent-referenced (N = 4,517)
ß
ß
ß
ß
.
.01
.01
.01
.27*
.27*
.27*
.32*
.32*
.32*
.32*
.32*
.32*
Unique R2
Unique R2
Unique R2
Unique R2
.00
.00
.00
.04*
.04*
.04*
.05*
.05*
.05*
.06*
.06*
.06*
.57*
.57*
.57*
Evaluation of authority: System-referenced (N = 2,114)
Evaluation of authority: System-referenced (N = 2,114)
Evaluation of authority: System-referenced (N = 2,114)
Evaluation of authority: System-referenced (N = 2,114)
ß
ß
ß
ß
.30*
.30*
.30*
-.19*
-.19*
-.19*
.44*
.44*
.44*
.11*
.11*
.11*
Unique R2
Unique R2
Unique R2
Unique R2
.04*
.04*
.04*
.02*
.02*
.02*
.10*
.10*
.10*
.01*
.01*
.01*
.31*
.31*
.31*
Trust (N = 1,711)
Trust (N = 1,711)
Trust (N = 1,711)
Trust (N = 1,711)
ß
ß
ß
ß
Unique R2
Unique R2
.31*
.31*
.31*
.05*
.05*
.21*
.21*
.21*
.03*
.03*
.30*
.30*
.30*
.05*
.05*
.45*
.45*
.45*
OCBs: Individual referenced (N = 3,192)
OCBs: Individual referenced (N = 3,192)
OCBs: Individual referenced (N = 3,192)
OCBs: Individual referenced (N = 3,192)
ß
ß
ß
ß
.06*
.06*
.06*
.19*
.19*
.19*
.11*
.11*
.11*
-.01*
-.01*
-.01*
Unique R2
Unique R2
Unique R2
Unique R2
.00*
.00*
.00*
.02*
.02*
.02*
.01*
.01*
.01*
.00
.00
.00
.09*
.09*
.09*
OCBs: Organization referenced (N = 782)
OCBs: Organization referenced (N = 782)
OCBs: Organization referenced (N = 782)
OCBs: Organization referenced (N = 782)
ß
ß
ß
ß
Unique R2
Unique R2
.12*
.12*
.12*
.01*
.01*
.11*
.11*
.11*
.01*
.01*
.12*
.12*
.12*
.01*
.01*
.08*
.08*
.08*
Performance (N = 1,855)
Performance (N = 1,855)
Performance (N = 1,855)
Performance (N = 1,855)
ß
ß
ß
ß
.56*
.56*
.56*
-.20*
-.20*
-.20*
.07*
.07*
.07*
-.07
-.07
-.07
Unique R2
Unique R2
Unique R2
Unique R2
.15*
.15*
.15*
.02*
.02*
.02*
.00*
.00*
.00*
.00*
.00*
.00*
.19*
.19*
.19*
Withdrawal (N = 1,919)
Withdrawal (N = 1,919)
Withdrawal (N = 1,919)
Withdrawal (N = 1,919)
ß
ß
ß
ß
-.10*
-.10*
-.10*
.23*
.23*
.23*
-.21*
-.21*
-.21*
-.51*
-.51*
-.51*
Unique R2
Unique R2
Unique R2
Unique R2
.01*
.01*
.01*
.02*
.02*
.02*
.02*
.02*
.02*
.16*
.16*
.16*
.33*
.33*
.33*
Negative reactions (N = 4,039)
Negative reactions (N = 4,039)
Negative reactions (N = 4,039)
Negative reactions (N = 4,039)
ß
ß
ß
ß
-.06*
-.06*
-.06*
-.18*
-.18*
-.18*
-.12*
-.12*
-.12*
-.14*
-.14*
-.14*
Unique R2
Unique R2
Unique R2
Unique R2
.00*
.00*
.00*
.02*
.02*
.02*
.01*
.01*
.01*
.01*
.01*
.01*
.16*
.16*
.16*
Note. Sample sizes are based on the harmonic mean of the sample sizes for the correlations among the justice and outcome variables. The procedural justice variable includes process control, Leventhal criteria, and procedural fairness perceptions. OCBs = organizational citizenship behaviors.
Note. Sample sizes are based on the harmonic mean of the sample sizes for the correlations among the justice and outcome variables. The procedural justice variable includes process control, Leventhal criteria, and procedural fairness perceptions. OCBs = organizational citizenship behaviors.
* p < .05.
* p < .05.
model, which predicts that distributive justice will have stronger effects than the other justice dimensions. This model was supported for outcome satisfaction and withdrawal but not for any of the other nine outcomes.
model, which predicts that distributive justice will have stronger effects than the other justice dimensions. This model was supported for outcome satisfaction and withdrawal but not for any of the other nine outcomes.
The two-factor model predicts that procedural justice will have stronger effects than distributive justice on system-referenced variables but weaker effects than distributive justice on person- referenced variables. This model seemed to receive support only for person-referenced and system-referenced attitudes such as outcome satisfaction, job satisfaction, organizational commitment, and system-referenced evaluation of authority. The two-factor model’s predictions were not supported for more behavioral va
The two-factor model predicts that procedural justice will have stronger effects than distributive justice on system-referenced variables but weaker effects than distributive justice on person- referenced variables. This model seemed to receive support only for person-referenced and system-referenced attitudes such as outcome satisfaction, job satisfaction, organizational commitment, and system-referenced evaluation of authority. The two-factor model’s predictions were not supported for more behavioral va
The agent-system model predicts that interpersonal or informational justice will have stronger effects than procedural justice on agent-referenced variables but weaker effects than procedural justice on system-referenced variables. This model was supported for
The agent-system model predicts that interpersonal or informational justice will have stronger effects than procedural justice on agent-referenced variables but weaker effects than procedural justice on system-referenced variables. This model was supported for
agent-referenced outcomes, including agent-referenced evaluation of authority and OCBIs, but not for trust, which was more related to procedural and distributive justice. The agent-system model was also supported for job satisfaction, organizational commitment, and performance. The model actually seems to underestimate the importance of interpersonal or informational justice for behavioral variables. Interpersonal or informational justice was a strong predictor of OCBOs, withdrawal, and negative reactions
agent-referenced outcomes, including agent-referenced evaluation of authority and OCBIs, but not for trust, which was more related to procedural and distributive justice. The agent-system model was also supported for job satisfaction, organizational commitment, and performance. The model actually seems to underestimate the importance of interpersonal or informational justice for behavioral variables. Interpersonal or informational justice was a strong predictor of OCBOs, withdrawal, and negative reactions
Implications for the Organizational Justice Literature
Implications for the Organizational Justice Literature
The conceptualization, measurement, and analysis of organizational justice depend in large part on a given study’s research question, as well as the sample or setting used to examine it. Nonetheless, the results of our review have some broad, general implications for the justice literature as a whole.
The conceptualization, measurement, and analysis of organizational justice depend in large part on a given study’s research question, as well as the sample or setting used to examine it. Nonetheless, the results of our review have some broad, general implications for the justice literature as a whole.
Distinctiveness of justice dimensions. The construct discrimination results suggest that procedural, interpersonal, and informational justice are distinct constructs that can be empirically
Distinctiveness of justice dimensions. The construct discrimination results suggest that procedural, interpersonal, and informational justice are distinct constructs that can be empirically
distin-
438
438
438
438
COLQUITT, CONLON, WESSON, PORTER, AND NG
COLQUITT, CONLON, WESSON, PORTER, AND NG
guished from one another. We would therefore call for a moratorium on indirect combination measures that combine the three justice dimensions into a single variable. Thirty-five of the studies included in our review used such measures (e.g., Brockner
guished from one another. We would therefore call for a moratorium on indirect combination measures that combine the three justice dimensions into a single variable. Thirty-five of the studies included in our review used such measures (e.g., Brockner
et
al., 1995, 1997; Folger & Konovsky, 1989; Konovsky & Folger, 1991; Mansour-Cole & Scott, 1998; Skarlicki & Latham, 1997). Our review showed that procedural, interpersonal, and informational justice have different correlates, and measuring the three separately allows for further differences among the dimensions to be examined.
Measurement of justice dimensions. It is also critical that researchers devote more care and effort to the measurement of justice dimensions. Some of the articles we reviewed used measures that assessed, among supervisors, granting subordinates voice, treating subordinates consistently, suppressing biases, being respectful, and providing explanations. Such measures were labeled “interactional justice” (e.g., Moorman, 1991; Skarlicki & Latham, 1997), even though only the latter two are included in
Measurement of justice dimensions. It is also critical that researchers devote more care and effort to the measurement of justice dimensions. Some of the articles we reviewed used measures that assessed, among supervisors, granting subordinates voice, treating subordinates consistently, suppressing biases, being respectful, and providing explanations. Such measures were labeled “interactional justice” (e.g., Moorman, 1991; Skarlicki & Latham, 1997), even though only the latter two are included in
Bies
and Moag’s (1986) construct. Authors may have included such items on the basis of Folger and Bies’s (1989) article on “managerial responsibilities” for procedural justice, which listed seven principles (process control, bias suppression, consistency, feedback, justification, truthfulness, and courtesy) managers should use to promote procedural justice. Not surprisingly, researchers using such measures have been forced to collapse the interactional justice measure with their procedural justice measure as a
Distinguishing justice content from justice source. Relatedly, future research should seek to separate the effects of justice content from the effects of justice source. Procedural justice can be a function of an organization, as when a formalized decision-making system provides process control or consistency as a result of the way in which it is structured (e.g., Adams-Roy & Barling, 1998;
Distinguishing justice content from justice source. Relatedly, future research should seek to separate the effects of justice content from the effects of justice source. Procedural justice can be a function of an organization, as when a formalized decision-making system provides process control or consistency as a result of the way in which it is structured (e.g., Adams-Roy & Barling, 1998;
Ehlen,
Magner, & Welker, 1999; Skarlicki
et
al., 1999). Procedural justice can also be a function of a decision-making agent, as when a manager takes steps to involve subordinates in decisions or treat subordinates consistently (e.g., Folger & Konovsky, 1989; Konovsky, Folger, & Cropanzano, 1987; Korsgaard, Schweiger, &
Sapienza,
1995). Likewise, informational and interpersonal justice can be fostered through organizational policies and initiatives (e.g., Konovsky & Folger, 1991; Mansour-Cole & Scott, 1998; Tansky, 1993) or through the actions of a decision-making agent (e.g.,
Bies,
Shapiro, & Cummings, 1988; Greenberg, 1994; Moorman, 1991). It is difficult to draw conclusions from studies comparing the effects of organization-originating procedural justice with agent-originating interpersonal or informational justice because source and content are confounded. Fortunately, recent research is beginning to examine this important issue by crossing justice source with justice content to assess their joint effects
(Blader
& Tyler, 2000; Byrne & Cropanzano, 2000; Masterson,
Bartol,
& Moye, 2000).
Including multiple justice dimensions in single studies. Our results also clearly show that researchers can explain more outcome variance by including multiple justice dimensions within single studies, although there are some diminishing returns associated with this strategy. Our proactive research results showed that distributive justice, procedural justice (in terms of Leventhal criteria), interpersonal justice, and, to a lesser extent, informational justice each contribute uniquely to the creation of f
Including multiple justice dimensions in single studies. Our results also clearly show that researchers can explain more outcome variance by including multiple justice dimensions within single studies, although there are some diminishing returns associated with this strategy. Our proactive research results showed that distributive justice, procedural justice (in terms of Leventhal criteria), interpersonal justice, and, to a lesser extent, informational justice each contribute uniquely to the creation of f
Examining interactions among justice dimensions. In addition to explaining more outcome variance, including multiple dimensions will also allow for the testing of interaction effects. The interaction between procedural and distributive justice has been perhaps the most robust finding in the justice literature (Brockner &
Examining interactions among justice dimensions. In addition to explaining more outcome variance, including multiple dimensions will also allow for the testing of interaction effects. The interaction between procedural and distributive justice has been perhaps the most robust finding in the justice literature (Brockner &
Wiesenfeld,
1996). Skarlicki and Folger (1997) further showed that procedural and interactional justice interact in predicting ORBs. These authors also found support for three-way interactions among procedural, interactional, and distributive justice. Such complex relationships do not map neatly onto reactive models such as the two-factor or agent-system model. However, the fact that moderators were present in almost all of the justice-outcome relationships suggests that more complex relationships may be the key to imp
Gaps in the existing literature. A final implication of our results resides in the gaps revealed by this review. A scan of Table 5 highlights areas where more research ought to be done. In terms of sheer number of studies, we note that procedural justice is much better represented in studies of satisfaction, commitment, evaluation of authorities, withdrawal, and negative reactions and relatively underrepresented in studies of performance, OCBs, and trust. We also note that interpersonal and informational ju
Gaps in the existing literature. A final implication of our results resides in the gaps revealed by this review. A scan of Table 5 highlights areas where more research ought to be done. In terms of sheer number of studies, we note that procedural justice is much better represented in studies of satisfaction, commitment, evaluation of authorities, withdrawal, and negative reactions and relatively underrepresented in studies of performance, OCBs, and trust. We also note that interpersonal and informational ju
Limitations
Limitations
This review has some limitations that should be noted. First, as in the primary studies on which our review is based, many of the variables were assessed with self-report measures. Thus, many of the relationships may be inflated because of same source bias. Second, any meta-analysis is subject to a variety of judgment calls
This review has some limitations that should be noted. First, as in the primary studies on which our review is based, many of the variables were assessed with self-report measures. Thus, many of the relationships may be inflated because of same source bias. Second, any meta-analysis is subject to a variety of judgment calls
META-ANALYTIC REVIEW OF ORGANIZATIONAL JUSTICE
META-ANALYTIC REVIEW OF ORGANIZATIONAL JUSTICE
META-ANALYTIC REVIEW OF ORGANIZATIONAL JUSTICE
META-ANALYTIC REVIEW OF ORGANIZATIONAL JUSTICE
439
439
(Wanous, Sullivan, &
(Wanous, Sullivan, &
Malinak,
1989). Although we performed all coding in author dyads, it is possible that some of these judgment calls affected our results. Finally, the fact that meta-analysis requires the reporting of zero-order results meant that several important justice articles could not be included in our review. In particular, many of Tyler’s examinations of the relational model of justice had to be omitted (e.g., Tyler, 1989, 1994; Tyler
et
al., 1996).
Conclusion
Conclusion
In a review of the organizational justice literature, Greenberg (1993a) suggested that the field was in a state of “intellectual adolescence.” This adolescence, though marked by many advancements, is also characterized by “stumbling awkwardness” due to underdeveloped research agendas and the absence of underlying theory (Greenberg, 1993a, p. 139). In an earlier review, Greenberg (1990b) echoed these sentiments, noting that the field was years away from the final stage of Reichers and Schneider’s (1990) con
In a review of the organizational justice literature, Greenberg (1993a) suggested that the field was in a state of “intellectual adolescence.” This adolescence, though marked by many advancements, is also characterized by “stumbling awkwardness” due to underdeveloped research agendas and the absence of underlying theory (Greenberg, 1993a, p. 139). In an earlier review, Greenberg (1990b) echoed these sentiments, noting that the field was years away from the final stage of Reichers and Schneider’s (1990) con
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COLQUITT, CONLON, WESSON, PORTER, AND NG
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META-ANALYTIC REVIEW OF ORGANIZATIONAL JUSTICE
META-ANALYTIC REVIEW OF ORGANIZATIONAL JUSTICE
META-ANALYTIC REVIEW OF ORGANIZATIONAL JUSTICE
META-ANALYTIC REVIEW OF ORGANIZATIONAL JUSTICE
445
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Received August 23, 1999
Received August 23, 1999
Revision received May 12, 2000
Revision received May 12, 2000
Accepted May 15, 2000 ■
Accepted May 15, 2000 ■
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