Available online at www.sciencedirect.com
Journal of Vocational Behavior 73 (2008) 63–77
www.elsevier.com/locate/jvb
A meta-analytic examination of the construct validity
of the Michigan Organizational Assessment Questionnaire
Job Satisfaction Subscale
Nathan A. Bowling *, Gregory D. Hammond
Wright State University, Department of Psychology, 3640 Colonel Glenn Highway, Dayton, OH 45435-0001, USA
Received 21 December 2007
Available online 1 February 2008
Abstract
Although several different measures have been developed to assess job satisfaction, large-scale examinations of the psychometric properties of most satisfaction scales are generally lacking. In the current study we used meta-analysis to examine the construct validity of the Michigan Organizational Assessment Questionnaire Job Satisfaction Subscale (MOAQJSS; [Cammann, C., Fichman, M., Jenkins, D., & Klesh, J. (1979). The Michigan Organizational Assessment Questionnaire.
Unpublished manuscript, University of Michigan, Ann Arbor; Cammann, C., Fichman, M., Jenkins, G. D., & Klesh, J.
(1983). Michigan Organizational Assessment Questionnaire. In S. E. Seashore, E. E. Lawler, P. H. Mirvis, & C. Cammann
(Eds.), Assessing organizational change: A guide to methods, measures, and practices (pp. 71–138). New York: Wiley-Interscience]), which is a brief, face-valid measure of global job satisfaction. Our analyses indicate that the MOAQ-JSS is a reliable and construct-valid measure of job satisfaction. We also report normative data for the MOAQ-JSS.
Ó 2008 Elsevier Inc. All rights reserved.
Keywords: Job satisfaction; Construct validity; Meta-analysis
1. Introduction
The study of job satisfaction has a long history in industrial and organizational psychology (Wright, 2006),
where it is examined as a potential cause, correlate, and consequence of both work-related and non-work variables. A number of studies, for example, have examined the potential situational (Fisher & Gitelson, 1983;
Fried & Ferris, 1987; Jackson & Schuler, 1985; Loher, Noe, Moeller, & Fitzgerald, 1985) and dispositional
(Connolly & Viswesvaran, 2000; Judge & Bono, 2001) causes of job satisfaction and job satisfaction has been
examined as a potential cause of important work-related behaviors, such as job performance (Iaffaldano &
Muchinsky, 1985; Judge, Thoresen, Bono, & Patton, 2001; Petty, McGee, & Cavender, 1984), absenteeism
*
Corresponding author.
E-mail address: nathan.bowling@wright.edu (N.A. Bowling).
0001-8791/$ - see front matter Ó 2008 Elsevier Inc. All rights reserved.
doi:10.1016/j.jvb.2008.01.004
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(Farrell & Stamm, 1988), and turnover (Tett & Meyer, 1993). Indeed, Spector (1997) observed that job satisfaction is the most widely-studied topic in industrial and organizational psychology.
Given its popularity as a research topic, it should be no surprise that several different measures have been
developed to assess job satisfaction. Unfortunately, there are few large-scale studies that examine the psychometric properties of these measures. One notable exception, however, is a meta-analysis by Kinicki, McKeeRyan, Schriesheim, and Carson (2002), which examined the construct validity of the Job Descriptive Index
(JDI; Smith, Kendall, & Hulin, 1969). Although Kinicki et al. found evidence that the JDI is a construct-valid
measure of facet satisfaction, we believe that efforts should be made to examine the validity of other job satisfaction measures. As we detail below, such research is especially needed in light of potentially serious limitations of the JDI. Thus, in the current study we provide a quantitative review of a job satisfaction measure
that avoids many of the JDI’s limitations. Specifically, we used meta-analysis to examine the reliability and
construct validity of the Michigan Organizational Assessment Questionnaire Job Satisfaction Subscale
(MOAQ-JSS; Cammann, Fichman, Jenkins, & Klesh, 1979, 1983). We also compiled normative data for
the MOAQ-JSS. First, however, we briefly describe the nature of the MOAQ-JSS and discuss its history.
1.1. Michigan Organizational Assessment Questionnaire
The MOAQ was developed as an alternative to the Job Diagnostic Survey (JDS; Hackman & Oldham,
1980) and thus includes subscale that assess the variables identified by Hackman and Oldham’s (1976) Job
Characteristics Model (for reviews of the development and early history of the MOAQ see Cammann
et al., 1979, 1983). These variables include descriptions of the work environment (e.g., job characteristics), psychological states (e.g., experienced meaningfulness, feelings of responsibility), and employee responses (e.g.,
job satisfaction, motivation). In the current study, however, we focus exclusively on the Job Satisfaction Subscale of the MOAQ.
Scores on the MOAQ-JSS are computed using the average of the following three items (note that the second
item is reversed-scored):
‘‘All in all I am satisfied with my job.”
‘‘In general, I don’t like my job.”
‘‘In general, I like working here.”
Although the original version of the MOAQ-JSS used a 7-point agree–disagree scale (Cammann et al.,
1979, Cammann, Fichman, Jenkins, & Klesh, 1983), some researchers have used 5-point (e.g., Allen, 2001;
Grandey, 2003) and 6-point (e.g., Brasher & Chen, 1999; Fox & Spector, 1999) versions of the measure.
1.2. Advantages of the MOAQ-JSS over other job satisfaction measures
One obvious advantage of the MOAQ-JSS is its length. While the MOAQ-JSS consists of only three items,
other popular job satisfaction scales are generally much longer. The JDI (Smith et al., 1969), for example,
includes 72 items, while the long-form and short-form of the Minnesota Satisfaction Questionnaire (MSQ;
Weiss, Dawis, England, & Lofquist, 1967) include 100 items and 20 items, respectively. Thus, the MOAQJSS can be especially useful when concerns about questionnaire length make longer job satisfaction measures
impractical.
The MOAQ-JSS also offers an advantage over other job satisfaction measures in that it is a face-valid measure of the affective component of job satisfaction. This is important because definitions of job satisfaction
have generally described it as including an affective or emotional component (Brief, 1998; Brief & Roberson,
1989; Organ & Near, 1985). Job satisfaction, in other words, involves not only one’s thoughts but also one’s
feelings about his or her job. Each of the three MOAQ-JSS items, for example, includes either the word ‘‘satisfied” or ‘‘like,” which can be described as being affective or emotion-oriented words. This is in contrast to
other measures, such as the JDI, which have been criticized for not adequately assessing employee affect (Brief,
1998; Brief & Roberson, 1989; Organ & Near, 1985).
Finally, we should also note that the MOAQ-JSS assesses a different construct than those assessed by the
JDI subscales. While the JDI assesses specific facets of job satisfaction (i.e., satisfaction with work itself,
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65
supervision, co-workers, pay, and promotional opportunities), the MOAQ-JSS assesses global job satisfaction.
Although the JDI research group developed a measure of global job satisfaction (the Job In General Scale or
JIG; Ironson, Smith, Brannick, Gibson, & Paul, 1989) many years after the introduction of the original JDI,
this general measure was not examined in the Kinicki et al. (2002) meta-analysis. Thus, although research by
Kinicki et al. on the validity of the JDI provides a useful contribution to the literature, it is important to examine the construct validity of other job satisfaction measures, such as the MOAQ-JSS.
In the next section we develop a nomological network (Cronbach & Meehl, 1955) for the global job satisfaction construct. Using this network as a guide, we conducted a meta-analysis that examined the construct
validity of the MOAQ-JSS.
2. A nomological network for job satisfaction
In order to examine the construct validity of a measure, it is important to first specify a nomological network for the construct of interest (Cronbach & Meehl, 1955). That is, one should identify a pattern of relationships that theoretically exist between the given construct and several external variables. One can conclude
that a specific measure is construct-valid if it yields a pattern of relationships with external variables that is
similar to the pattern specified by the nomological network.
In the current section we present a nomological network that identifies the hypothesized causes, correlates,
and consequences of job satisfaction (see Fig. 1). This network is based on decades of theoretical and empirical
work that examines the job satisfaction construct (for reviews of the job satisfaction literature see Brief, 1998;
Spector, 1997) and is not intended to represent a comprehensive theory of job satisfaction.
Our subsequent meta-analysis examined whether the MOAQ-JSS yields a pattern of relationships similar to that
predicted in the nomological network. We should note that Kinicki et al. (2002) used a similar strategy in examining
the construct validity of the JDI. Their work largely forms the basis for the approach used in the current study.
2.1. Hypothesized antecedents of job satisfaction
2.1.1. Job characteristics
Job characteristics, which are a reflection of the complexity of one’s work tasks, have long been established both theoretically and empirically as a potentially important cause of job satisfaction. More specifHypothesized Correlates
Hypothesized Antecedents
Job Complexity (+)
Skill Variety
Task Identity
Task Significance
Autonomy
Feedback
Stressors (-)
Role Conflict
Role Ambiguity
Role Overload
Organizational Constraints
Interpersonal Conflict
Work-Family Conflict
Social and Organizational Support (+)
Person-Environment Fit (+)
Job Attitudes (+)
Facet Satisfaction
Organizational Commitment
Job Involvement
Career Satisfaction
Organizational Justice
Strains (-)
Job Tension
Anxiety
Depression
Emotional Exhaustion
Frustration
Physical Strains
Life Satisfaction (+)
Hypothesized Consequences
JOB
SATISFACTION
Job Performance (+)
Organizational Citizenship Behavior (+)
Counterproductive Work Behavior (-)
Employee Withdrawal (-)
Turnover Intentions
Turnover
Absenteeism
Fig. 1. Nomological network of hypothesized antecedents, correlates, and consequences of job satisfaction.
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ically, the Job Characteristics Model (JCM; Hackman & Oldham, 1976, 1980) suggests that job complexity, which includes skill variety, task identify, task significance, autonomy, and feedback, is positively associated with job satisfaction. Consistent with the JCM, research has found considerable support for the
relationships between job characteristics and satisfaction (Fried & Ferris, 1987; Loher et al., 1985).
2.1.2. Work stressors
Work stressors, which are any aspects of one’s work environment that have the potential to cause mental or
physical illness (Jex, Beehr, & Roberts, 1992), are theoretically and empirically related to job satisfaction.
Research and theory suggest, for example, that stressors such as role ambiguity and role conflict (Fisher &
Gitelson, 1983; Jackson & Schuler, 1985), role overload (Spector & Jex, 1998), organizational constraints
(Spector & Jex, 1998), work–family conflict (Kossek & Ozeki, 1998), and interpersonal conflict (Bowling &
Beehr, 2006; Lapierre, Spector, & Leck, 2005) are all negatively associated with job satisfaction.
2.1.3. Social and organizational support
The receipt of support from one’s supervisors, co-workers, or organization has been widely examined as a
potential cause of job satisfaction. Research has consistently found positive relationships between both social
support and perceived organizational support and satisfaction (Rhoades & Eisenberger, 2002; Viswesvaran,
Sanchez, & Fisher, 1999).
2.1.4. Person–environment fit
Person–environment fit is the degree of compatibility between an employee and his or her work environment (Kristof, 1996). Theoretically, a good fit between what an employee wants or needs and what the
organization or job actually supplies is expected to contribute to one’s level of satisfaction. Consistent
with this hypothesis, previous research has established a strong positive relationship between person–environment fit and job satisfaction (Kristof-Brown, Zimmerman, & Johnson, 2005; Verquer, Beehr, & Wagner, 2003).
2.2. Hypothesized correlates of job satisfaction
2.2.1. Job attitudes
Previous research suggests that job satisfaction yields positive relationships with other job attitudes, such as
organizational commitment (Mathieu & Zajac, 1990; Meyer, Stanley, Herscovitch, & Topolnytsky, 2002), job
involvement (Brown, 1996), and career satisfaction (Bowling, Beehr, & Lepisto, 2006). Confirmatory factor
analyses (CFA) further suggest that these attitudes are distinct from each other (Brooke, Russell, & Price,
1988; Mathieu & Farr, 1991). Thus, job satisfaction is related to but not redundant with other job attitudes.
Given the results of prior meta-analyses that have examined job satisfaction (Brown, 1996; Mathieu & Zajac,
1990; Meyer et al., 2002), we expected that the MOAQ-JSS will yield especially strong relationships with all
job attitudes except continuance commitment.
2.2.2. Organizational justice
Organizational justice includes several sub-dimensions, including distributive, procedural, and interactional justice (Colquitt, 2001). Research and theory suggest that each of these sub-dimensions is positively
related to job satisfaction (Cohen-Charash & Spector, 2001; Colquitt, Conlon, Wesson, Porter, & Ng,
2001).
2.2.3. Psychological and physical strains
Strains represent the psychological (e.g., anxiety, burnout, etc.) or physical (e.g., headaches, upset stomach,
etc.) illness that results from being exposed to stressors (Jex et al., 1992) and are typically found to yield negative relationships with job satisfaction (e.g., Sanchez & Viswesvaran, 2002; Spector & Jex, 1991; Tepper,
2000). Because job satisfaction is generally defined as including an affective component (Brief, 1998), emotion-oriented strains, such as anxiety, depression, emotional exhaustion, and frustration, should yield
especially strong relationships with satisfaction.
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2.2.4. Life satisfaction
Research and theory suggest that job satisfaction is positively related to non-work attitudes, such as life
satisfaction (Tait, Padgett, & Baldwin, 1989). This is likely to occur because emotions experienced in one life
domain (e.g., work) ‘‘spill over” into other life domains (e.g., life in general; Judge & Watanabe, 1994).
2.3. Hypothesized consequences of job satisfaction
2.3.1. In-role performance
Much theoretical and empirical attention has been given to the consequences of job satisfaction. Several
studies, for instance, have examined in-role job performance as a potential consequence of satisfaction
(Iaffaldano & Muchinsky, 1985; Judge et al., 2001; Petty et al., 1984). Satisfaction, for instance, has been
hypothesized to influence in-role performance via effects on employee motivation (Strauss, 1968). Consistent
with this, research has consistently found a positive relationship between satisfaction and in-role performance
(Iaffaldano & Muchinsky, 1985; Judge et al., 2001; Petty et al., 1984).
2.3.2. Extra-role performance
In response to the modest findings yielded by research on the satisfaction–performance relationship, some
researchers have advocated the broadening of the performance domain to include extra-role behaviors
(Borman & Motowidlo, 1993; Brief, 1998). These researchers reason that because in-role performance is often
closely managed by organizations, then satisfaction should not be strongly related to in-role performance.
That is, given the situational constraints created by organizations to encourage effective in-role performance,
dissatisfied employees will often avoid withholding performance even if they desire to. On the other hand,
extra-role behaviors, such as organizational citizenship behavior (OCBs; Smith, Organ, & Near, 1983) and
counterproductive work behavior (CWBs; Chen & Spector, 1992) are voluntary in nature. Thus, the decision
to engage or not engage in OCBs and CWBs is largely based on the discretion of the individual employee. For
this reason, satisfaction is expected to yield positive relationships with OCBs and negative relationships with
CWBs and these relationships are expected to be stronger than those found between satisfaction and in-role
performance. Consistent with this reasoning, meta-analyses have found that satisfaction yields significant relationships with both OCBs and CWBs (Dalal, 2005; LePine, Erez, & Johnson, 2002; Organ & Ryan, 1995).
2.3.3. Withdrawal behavior
In addition to being a potential predictor of in-role and extra-role performance, job satisfaction is theoretically
and empirically linked to several forms of withdrawal behavior. These behaviors include absenteeism (Farrell &
Stamm, 1988) as well as turnover intention and actual turnover (Tett & Meyer, 1993). Given the findings of prior
job satisfaction research (Tett & Meyer, 1993), the relationship between the MOAQ-JSS and turnover intention is
expected to be especially strong. In explaining these relationships, researchers have theorized that withdrawal
behaviors are a strategy used by workers to avoid unpleasant or dissatisfying work (Hanisch & Hulin, 1991).
In sum, we used meta-analysis to examine the reliability and construct validity of the MOAQ-JSS. Specifically,
we examined whether the MOAQ-JSS yields a pattern of relationships consistent with that described above in the
nomological network and presented in Fig. 1. We also compiled normative data for the MOAQ-JSS.
3. Method
We used meta-analysis to examine the psychometric properties of the Michigan Organizational Assessment
Questionnaire Job Satisfaction Subscale (MOAQ-JSS; Cammann et al., 1979, 1983). Below, we discuss our
literature search strategy and the methods used to examine the reliability and construct validity of the
MOAQ-JSS. We also describe the methods used to compile the normative data.
3.1. Literature search
We first searched the PsycINFO database using the keywords ‘‘job satisfaction.” Given the size of the job
satisfaction literature, it was impractical to examine every article that was identified using ‘‘job satisfaction” as
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the search term (a December 20, 2007 search of the PsycINFO database using the key words ‘‘job satisfaction”
yielded a total of 21,968 sources published between 1979 and 2007). Thus, we limited our initial literature
search to articles published between 1979 (i.e., the year Cammann et al. first introduced the MOAQ) and
2007 in the following journals: Academy of Management Journal, Administrative Science Quarterly, Journal
of Applied Psychology, Organizational Behavior and Human Decision Processes, and Personnel Psychology.
We chose these particular journals because Kinicki et al. (2002) limited their search to the same sources.
Although we concede that several studies using the MOAQ-JSS are likely to appear in other journals, it
was necessary to limit this initial search due to the size of the job satisfaction literature. We conducted additional PsycINFO searches using the key words ‘‘Michigan Organizational Assessment Questionnaire” and we
also searched for articles that mentioned the name ‘‘Cammann” in their reference section. These later searches
were not limited to any particular journals, and thus we identified articles to add to our database that were
published in several additional journals (e.g., Journal of Management, Journal of Occupational Health Psychology, Journal of Occupational and Organizational Psychology, Journal of Organizational Behavior, and Journal
of Vocational Behavior).
In an effort to identify additional MOAQ-JSS samples, we reviewed each article found via the above PsycINFO searches. This yielded additional samples, because articles found in the PsycINFO searches often cited
additional MOAQ-JSS studies that we had not previously identified.
3.2. Inclusion criteria
After identifying potentially relevant studies, we closely reviewed each to ensure that they used the original
MOAQ-JSS. We excluded some studies from our database because they either adapted the MOAQ-JSS to laboratory tasks (e.g., Douthitt & Aiello, 2001), modified one or more MOAQ-JSS items (e.g., Duffy & Shaw,
2000), did not use all three MOAQ-JSS items (e.g., Vandenberg, Richardson, & Eastman, 1999), or because
they combined the MOAQ-JSS with other measures of job satisfaction (e.g., Barsky, Thoresen, Warren, &
Kaplan, 2004). We also excluded studies that translated the MOAQ-JSS into languages other than English,
since there were too few studies using any single non-English language to make meta-analysis feasible. We also
excluded studies that adapted the MOAQ-JSS for use in non-employee samples. These criteria yielded a final
total of 80 samples (overall N = 30,703) that used the MOAQ-JSS.
3.3. Analyses examining the reliability of the MOAQ-JSS
To examine the reliability of the MOAQ-JSS, we used methods similar to those of Kinicki et al. (2002).
First, we computed the mean internal consistency reliabilities (coefficient alpha) for the MOAQ-JSS. We also
computed the range of internal consistency reliabilities across samples. Similar analyses were conducted for
the test–retest reliability of the MOAQ-JSS. In examining the reliability of the MOAQ-JSS, we computed both
sample-weighted and un-weighted statistics.
3.4. Analyses examining the construct validity of the MOAQ-JSS
We used Hunter and Schmidt’s (2004) method to conduct meta-analyses examining the construct validity of
the MOAQ-JSS. We computed sample-weighted mean correlations corrected for unreliability in both the
MOAQ-JSS and its hypothesized antecedents/correlates/consequences. We corrected the correlations individually when all reliability data were available. Artifact distributions were used to estimate missing reliabilities.
We used Wanous, Reichers, and Hudy’s (1997) meta-analytic reliability estimate to correct for unreliability in
single-item turnover intention measures and Viswesvaran, Ones, and Schmidt’s (1996) meta-analytic reliability
estimate to correct for inter-rater reliability in job performance ratings.
3.5. Normative data for the MOAQ-JSS
Finally, we computed normative means and standard deviations for the MOAQ-JSS. We calculated both
un-weighted and sample-weighted normative data.
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69
4. Results
4.1. Reliability of the MOAQ-JSS
Table 1 reports analyses examining the internal consistency and test–retest reliabilities of the Michigan
Organizational Assessment Questionnaire Job Satisfaction Subscale (MOAQ-JSS). As displayed in the table,
we found that the MOAQ-JSS yielded acceptable levels of reliability. Specifically, the mean sample-weighted
internal consistency reliability was.84 (k = 79, N = 30,623) and the mean sample-weighted test–retest reliability was .50 (k = 4, N = 746).
4.2. Construct validity of the MOAQ-JSS
4.2.1. Hypothesized antecedents of job satisfaction
Table 2 presents meta-analyses examining the relationships between the hypothesized antecedents of job
satisfaction and the MOAQ-JSS.
These analyses found that job complexity (q = .46, k = 5, N = 877), skill variety (q = .28, k = 3, N = 725),
task identity (q = .28, k = 3, N = 725), task significance (q = .17, k = 3, N = 725) autonomy (q = .35, k = 13,
N = 2984), and feedback (q = .46, k = 3, N = 725) were each positively related to the MOAQ-JSS. Work
stressors, on the other hand, were negatively associated with the MOAQ-JSS. Specifically, role ambiguity
(q = .42, k = 14, N = 3060), role conflict (q = .32, k = 12, N = 3164), organizational constraints
(q = .39, k = 8, N = 1690), interpersonal conflict (q = .29, k = 18, N = 7634), work–family conflict
(q = .41, k = 3, N = 1204), work to family conflict (q = .21, k = 6, N = 1787) and family to work conflict
(q = .13, k = 5, N = 1493) each yielded negative relationships.
Finally, the table shows that supervisor social support (q = .47, k = 6, N = 1616), co-worker social support
(q = .33, k = 4, N = 703), perceived organizational support (q = .46, k = 4, N = 1084), and person–environment fit (q = .49, k = 3, N = 524) were all positively related to the MOAQ-JSS. Of the 18 hypothesized antecedents, the only one that did not yielded the expected relationship with the MOAQ-JSS was role overload
(q = .03, k = 12, N = 3259). As a whole, therefore, these results regarding the hypothesized causes of job
satisfaction are consistent with the nomological network.
4.2.2. Hypothesized correlates of job satisfaction
In Table 3 we report the results of meta-analyses examining the relationship between the MOAQ-JSS and
the hypothesized correlates of job satisfaction. As shown in the table, the MOAQ-JSS yielded positive relationships with other job attitudes. Specifically, satisfaction with work itself (q = .74, k = 2, N = 316), supervision (q = .57, k = 2, N = 316), co-workers (q = .40, k = 2, N = 316), pay (q = .43, k = 5, N = 1322),
promotional opportunities (q = .54, k = 3, N = 730), organizational commitment (q = .69, k = 9,
N = 3161), affective commitment (q = .77, k = 16, N = 8061), normative commitment (q = .52, k = 6,
N = 1626) continuance commitment (q = .05, k = 8, N = 2446), job involvement (q = .53, k = 5, N = 1627),
career satisfaction (q = .55, k = 2, N = 463), distributive justice (q = .44, k = 4, N = 896), procedural justice
(q = .54, k = 6, N = 3480), and interactional justice (q = .42, k = 3, N = 2946) each yielded positive relationships with the MOAQ-JSS.
We also found that the MOAQ-JSS was negatively associated with several strains, including job tension
(q = .42, k = 3, N = 654), anxiety (q = .15, k = 11, N = 4255), depression (q = .41, k = 6, N = 3693),
Table 1
Internal consistency and test–retest reliability for the Michigan Organizational Assessment Questionnaire Job Satisfaction Scale
Internal-consistency reliability
Test–retest reliability
k
N
Un-weighted M
Sample-weighted M
Range
k
N
Un-weighted M
Sample-weighted M
Range
79
30,623
.85
.84
.67, .94
4
746
.49
.50
.40, .64
Note. k, number of samples; N, total sample size.
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Table 2
Relationships between Michigan Organizational Assessment Questionnaire Satisfaction Scale and the hypothesized causes of job
satisfaction
Variable
k
N
Job complexity
Skill variety
Task identify
Task significance
Autonomy
Feedback
Role ambiguity
Role conflict
Role overload
Organizational constraints
Interpersonal conflict
Work–family conflict
Work–family conflict
Family–work conflict
Supervisor support
Co-worker support
Perceived organizational support
Person–environment fit
5
3
3
3
13
3
14
12
12
8
18
3
6
5
6
4
4
3
877
725
725
725
2984
725
3060
3164
3259
1690
7634
1204
1787
1493
1616
703
1084
524
Mean r
Mean q
SDq
.40
.23
.21
.10
.29
.35
.34
.26
.02
.33
.23
.36
.18
.11
.37
.27
.41
.44
.46
.28
.28
.17
.35
.46
.42
.32
.03
.39
.29
.41
.21
.13
.47
.33
.46
.49
.09
.05
.01
.08
.19
.05
.10
.22
.23
.08
.09
.00
.06
.06
.15
.28
.18
.13
Note. k, number of samples; N, total sample size; mean r, average weighted correlation coefficient; mean q, average weighted correlation.
Coefficient corrected for unreliability in both the predictor and criterion.
Table 3
Relationships between Michigan Organizational Assessment Questionnaire Satisfaction Scale and the hypothesized correlates of job
satisfaction
Variable
k
N
Satisfaction with work itself
Satisfaction with supervision
Satisfaction with co-workers
Satisfaction with pay
Satisfaction with promotional opportunities
Organizational commitment
Affective commitment
Normative commitment
Continuance commitment
Job involvement
Career satisfaction
Distributive justice
Procedural justice
Interactional justice
Job tension
Anxiety
Depression
Emotional exhaustion
Frustration
Generic psychological strains
Physical symptoms
Life satisfaction
2
2
2
5
3
9
16
6
8
5
2
4
6
3
3
11
6
5
12
5
13
3
316
316
316
1322
730
3161
8061
1626
2446
1627
463
896
3480
2946
654
4255
3693
898
2624
2566
4180
941
Mean r
Mean q
SDq
.62
.50
.36
.37
.47
.59
.64
.43
.04
.39
.45
.40
.45
.32
.33
.13
.32
.54
.36
.39
.18
.35
.74
.57
.40
.43
.54
.69
.77
.52
.05
.53
.55
.44
.54
.42
.42
.15
.41
.62
.45
.46
.22
.41
.07
.00
.22
.06
.05
.09
.03
.14
.11
.17
.00
.00
.08
.08
.00
.19
.01
.07
.04
.06
.08
.05
Note. k, number of samples; N, total sample size; mean r, average weighted correlation coefficient; mean q, average weighted correlation.
Coefficient corrected for unreliability in both the predictor and criterion.
emotional exhaustion (q = .62, k = 5, N = 898), frustration (q = .45, k = 12, N = 2624), general psychology strains (q = .46, k = 5, N = 2566), and physical symptoms (q = .22, k = 13, N = 4180). Finally, the
N.A. Bowling, G.D. Hammond / Journal of Vocational Behavior 73 (2008) 63–77
71
Table 4
Relationships between Michigan Organizational Assessment Questionnaire Satisfaction Scale and the hypothesized consequences of job
satisfaction
Variable
k
N
Job performance
Organizational citizenship behavior
Counterproductive work behavior
Turnover intension
Turnover
Absenteeism
12
8
3
31
7
5
2401
1555
874
12,618
3818
1180
Mean r
Mean q
SDq
.15
.17
.29
.52
.14
.12
.19
.21
.33
.65
.15
.13
.13
.07
.01
.16
.08
.00
Note. k, number of samples; N, total sample size; mean r, average weighted correlation coefficient; mean q, average weighted correlation.
Coefficient corrected for unreliability in both the predictor and criterion.
Table 5
Normative data for the Michigan Organizational Assessment Questionnaire Job Satisfaction Measure
MOAQ-JSS
k
N
Un-Weighted M
Un-weighted SD
Sample-weighted M
Sample-weighted SD
5-point
6-point
7-point
18
8
36
7135
1865
15,234
3.93
4.70
5.48
0.83
1.20
1.31
3.87
4.70
5.40
0.82
1.19
1.37
Note. MOAQ-JSS, Michigan Organizational Assessment Questionnaire Job Satisfaction Subscale; k, number of samples; N, total sample
size.
MOAQ-JSS was positively related to life satisfaction (q = .41, k = 3, N = 941). In sum, these findings regarding the relationships between the MOAQ-JSS and each of the 22 hypothesized correlates of job satisfaction are
consistent with the pattern depicted in Fig. 1.
4.2.3. Hypothesized consequences of job satisfaction
We conducted meta-analyses examining the relationships between the MOAQ-JSS and the hypothesized
consequences of job satisfaction (see Table 4). As hypothesized in Fig. 1, the MOAQ-JSS yielded positive relationships with in-role job performance (q = .19, k = 12, N = 2401) and organizational citizenship behaviors
(q = .21, k = 8, N = 1555), and negative relationships with counterproductive work behaviors (q = .33,
k = 3, N = 874), turnover intentions (q = .65, k = 31, N = 12,618), turnover (q = .15, k = 7, N = 3818),
and absenteeism (q = .13, k = 5, N = 1180).
4.3. MOAQ-JSS norms
Finally, we compiled norms for the MOAQ-JSS. Because some authors reported the sum of the 3 MOAQJSS items and others reported the average of the items, it was necessary for us to place all the descriptive statistics (i.e., means and standard deviations) form the primary studies on a common metric. Thus, we transformed the MOAQ-JSS descriptive statistics from studies that used the sum of the MOAQ-JSS items into
scores that represented the average of the MOAQ-JSS items. This was achieved by dividing the descriptive
statistics by 3 (i.e., the number of MOAQ-JSS items). As shown in Table 5, separate norms are reported
for the 5-, 6-, and 7-point versions of the MOAQ-JSS. Seventeen samples were excluded from these analyses
because the authors did not report the number of scale points they used for the MOAQ-JSS.
5. Discussion
The current study used meta-analysis to provide the largest and most comprehensive examination ever conducted of the psychometric properties of a global job satisfaction measure. Our analyses revealed important
findings concerning the reliability of the MOAQ-JSS. First, we found that the MOAQ-JSS yielded acceptable
levels of reliability (see Nunnally, 1978). We also found extensive evidence of the construct validity of the
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N.A. Bowling, G.D. Hammond / Journal of Vocational Behavior 73 (2008) 63–77
MOAQ-JSS. Specifically, the MOAQ-JSS generally yielded a pattern of relationships with external variables
that is consistent with that identified in the nomological network (see Fig. 1). Job characteristics, social and
organizational support, and person–environment fit were positively related to and stressors were negatively
related to the MOAQ-JSS. Furthermore, the MOAQ-JSS was positively associated with other job attitudes
and with life satisfaction and negatively associated with strains. Finally, the MOAQ-JSS was positively related
to in-role performance and organizational citizenship behaviors (OCBs), but was negatively associated with
counterproductive work behaviors (CWBs) and employee withdrawal.
In addition to noting that the direction of the correlations that we found for the MOAQ-JSS generally
matched those hypothesized in Fig. 1, it is also important to consider that the magnitude of the relationships
generally supported our predictions. The relationships for job attitudes and turnover intention, for instance,
were among the strongest relationships that we found. Continuance commitment was the only job attitude
found to be weakly related to the MOAQ-JSS. This overall pattern of results is consistent with past job satisfaction research (Brown, 1996; Mathieu & Zajac, 1990; Meyer et al., 2002; Tett & Meyer, 1993). Likewise, we
found some evidence that the MOAQ-JSS was more strongly related to extra-role performance (particularly
CWBs) than to in-role performance. This pattern is also consistent with past research (Brief, 1998).
Given such evidence that the MOAQ-JSS is a reliable and valid measure of global job satisfaction, it may in
many situations offer advantages over other popular measures of job satisfaction. First, the MOAQ-JSS consists of only three items. It might thus be preferred over longer satisfaction measures in instances where questionnaire length is a concern. Second, the MOAQ-JSS appears to better assess the affective component of job
satisfaction than does many other popular measures. This is important because scholars have generally
described job satisfaction as including an emotional response to one’s job (Brief, 1998; Brief & Roberson,
1989; Organ & Near, 1985). As discussed above in the introduction, some satisfaction measures, such as
the Job Descriptive Index (JDI; Smith et al., 1969) have been criticized for not effectively assessing the affective
component of job satisfaction (Brief, 1998; Brief & Roberson, 1989; Organ & Near, 1985). Because it contains
words such as ‘‘satisfaction” and ‘‘like,” the MOAQ-JSS is a face-valid measure of affective job satisfaction.
Furthermore, the current findings regarding the relatively strong relationships between the MOAQ-JSS and
emotion-related variables (i.e., affective commitment, job tension, depression, emotional exhaustion, and frustration) provide support for the affective nature of the MOAQ-JSS.
Finally, we reported normative data for the MOAQ-JSS. The mean MOAQ-JSS scores that we obtained
are consistent with the common research finding that most employees are satisfied with their jobs (Spector,
1997). Because they can help managers and researchers interpret MOAQ-JSS scores, these normative data
have important practical applications.
5.1. Limitations
Because nearly all of the primary studies used cross-section designs, the current study was unable to test
causal relationships. Furthermore, common-method variance may have influenced the correlations that we
found, since most of the primary studies exclusively used self-report data. Finally, it is likely that our literature
search may not have found all studies that have used the MOAQ-JSS. This may be particularly true because
our search focused exclusively on published research. We should note, however, that our literature search did
yield a large number of studies (k = 80) and a large overall sample size (N = 30,703).
6. Summary
In sum, we found evidence that the MOAQ-JSS is a reliable and construct-valid measure of job satisfaction.
We strongly encourage both researchers and practitioners to use the MOAQ-JSS to assess global job
satisfaction.
Acknowledgement
The authors which to thank Marsha Moss for assisting us with the literature search.
N.A. Bowling, G.D. Hammond / Journal of Vocational Behavior 73 (2008) 63–77
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