Journal of Management
199.5,Vol. 21, No. 2,279-303
The Critical PsychologicalStates:
An Underrepresented Component in
Job Characteristics bode/ Research
Robert W. Rem
2% Universityof Memphis
Robert J. Vandenberg
university of Georgia
The mediating role of the critical psychological states (CPS) in
the job characteristics model was examined in two studies. Using
Baron and Kenny’s (1986) approach for examining mediation
hypotheses, results from Study 1: (1) supported the hypothesized
linkages between the core job dimensions and the CPS, and between
the CPS and attitudinal outcomes; (2) provided no support for the
hypothesis that all three CPS must be experienced to m~Kirniz~
internal work motivation; (3) supported the present authors’
hypothesis that the CPS would explain signt&mt amounts of
outcome variance beyond the core job dimensions; and (4) supported
the present authors *hypothesis that the CPS are partial rather than
complete mediator var~~b~es~Using causal modeling analyst and
another sample, results from Study 2 provided the strongest support
for a job characteristics modeI that allowed the core job dimensions
to have direct and indirect effects on personal and work outcomes,
further supporting the Study 1 finding that the CPS were partial
mediator variables. The general discussion centered on the
implications the present findings have for future job characteristics
model research.
Hackman and Oldham’s (1976) job characteristics model has stimulated over
200 published empirical studies and at least three comprehensive reviews (e.g.,
Fried & Ferris, 1987; Loher, Noe, Moeller & Fitzgerald, 1985; Roberts & Glick,
1981). In their review, Fried and Ferris (1987) found that only eight studies
included the critical psychologic~ states (CPS), and only three of those eight
studies examined the CPS mediation hypothesis (Arnold & House, 1980;
Hackman & Oldham, 1976; Wall, Clegg & Jackson, 1978).
That the CPS mediation hypothesis rarely has been examined is not a trivial
issue. First, Hackman and Lawler (1971), and Hackman and Oldham (1975;
Direct all correspondent
to: Robert W. Renn, The University of Memphis,
and Economics, Department of Maaa~ment,
Memphis, TN 38152.
Copyright
@ 1995 by JAI Press Inc. 031494063
Fogelman
College of Business
280
RENN AND VANDENBERG
1976) presented the CPS as the primary motivational component of the job
characteristics model. Since few studies have included the CPS, one could
question whether the motivational underpinnings of this theory have been
adequately examined or represented in job characteristics model evaluations
(Gardner & Cummings, 1988; Kanfer, 1991). Second, excluding the mediating
role of the CPS could be overlooked if there was enough evidence supporting
their exclusion. Excluding the CPS from tests of the theory, thus, would have
represented the normal practice of modifying a theory as warranted by the
accumulated evidence (Bacharach, 1989). For instance, sufficient empirical
evidence has accumulated to support evaluating the relations among the job
characte~stics model’s components without the growth need strength moderator
(Graen, Scandura & Graen, 1986; Johns, Xie & Fang, 1992; Tiegs, Tetrick &
Fried, 1992). By contrast, virtually no empirical evidence has accumulated
supporting the practice of excluding the CPS from tests of the theory. In fact,
Hogan and Mat-tell suggested that the CPS have been excluded from past studies
not because the empirical evidence supported this trend but because of the
analytical difficulties associated with testing the mediation hypothesis (1987, p.
244). Thus, the practice of excluding the mediating role of the CPS appears to
have occurred without theoretical or empirical justification.
The purpose of the present research was to examine the soundness of
excluding the mediating role of the CPS from the job characteristics model.
This was accomplished through two studies, both of which addressed the
following underlying question: Do the CPS make a contribution to our
understanding of indi~duals’ reactions to their jobs, or are the CPS an
unnecessary component of the job characteristics model whose exclusion would
make the theory more parsimonious? In addressing the latter question, the
present research was critical in nature. Specifically, in both studies the
hypothesis that the CPS are important components of the job characteristics
model was tested against the alternative hypothesis that they may not be
necessary, and that their removal may result in a more parsimonious
explanation of job design processes (Harris & Schaubroeck, 1990; James,
Mulaik & Brett, 1982). The present research was also critical in that, assuming
the CPS possess a mediating role, the nature of that role (i.e., whether the CPS
are complete or partial mediators) was examined in a series of hypotheses that
contrasted the theoretical statements of that role with the accumulated empirical
evidence. It is important to note that the purpose of the present research was
not to examine every nuance of the job characteristics model, but rather, only
the role the CPS have in the model. In the following sections, we provide a
basis for the present research question by briefly reviewing the role of the CPS
in the job characteristics model and the findings from studies that included the
CPS.
The Role of the CPS in the Job Characteristics Model
Hackman and colleagues (Hackman & Lawier; 1971; Hackman & Oldham,
1976; 1980) used the CPS to provide a theoretical link between perceived job
characteristics and internal work motivation. As can be seen in Figure 1, internal
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VOL. 21. NO. 2. 1995
ldentl
Feedback
IAutonomy
Task Slgnlf
l&k
lcance
ty
Sk111Variety
Core Job
Dimensions
F
Figure 1.
I
J
The Job Characteristics
Know I CYly]c of the
Flc tual
Resul ts of
Work Flc tlvl ties
Exper 1enc ed
Responslblll
ty
for Outcomes
of the Work
Exper i one ed
Meaninyfulness
of
the Work
Crltlcal
Psychologlcal
States
Model
Internal
and Turnover
1.0~ Ilbsentceism
HI gh Sat I sfac t 1on
WI th the Work
Quai 1 ty
Work Performance
tllgh
1JorkMotlvatlon
llicjh
Personal and
Work Outcomes
F
r
iA
2
;;1
WY
6
0
g
2
2
g
$
7
E
282
RENN AND VANDENBERG
work motivation is hypothesized to result from work that prompts three CPS,
experienced
meaningfulness,
experienced
responsibility,
and knowledge of
results. Experienced meaningfulness refers to the extent to which an individual
believes his or her job is important vis a vis the individual’s own value system.
Experienced responsibility represents the degree of personal accountability
an
individual has for his or her work outcomes. And knowledge of results refers
to the extent to which an individual knows how well he or she is performing
on the job.
Hackman and colleagues hypothesize that the three CPS are prompted
by work consisting of five core job dimensions. Skill variety (the breadth of
skills used while performing work), task identity (the opportunity to complete
an entire piece of work), and task significance (the impact the work has on
others) are hypothesized
to prompt experienced meaningfulness.
Autonomy
(the depth of discretion allowed while performing work) is hypothesized
to
prompt experienced responsibility. And feedback (the amount of information
provided about work performance)
is hypothesized
to cause knowledge of
results. In brief, greater amounts of these five core job dimensions are postulated
to lead to stronger experiences of the three CPS which, in turn, lead to more
positive responses to work as evidenced by changes in both attitudinal (e.g.,
increased internal work motivation,
increased job satisfaction,
decreased
turnover intentions, etc.) and behavioral (increased performance,
decreased
turnover, etc.) outcomes.
Although never explicitly stated by Hackman and colleagues, Figure 1
indicates that the CPS are complete mediators of the core job dimensions-outcomes
relations. That is, the effects of the core job dimensions on personal and work
outcomes are shown to be fully transmitted by the CPS (Baron & Kenny, 1986;
James, 1980; James & Brett, 1984). Also, as mentioned, Hackman and Oldham
state that “the five core job dimensions are seen as prompting three psychological
states, which, in turn, lead [italics added] to a number of beneficial personal and
work outcomes” (1976, p. 255). Hackman and Oldham emphasize the impact the
CPS have on personal and work outcomes by labeling them the job characteristics
model’s “causal core” (1976, p. 255). Finally, Hackman et al. hypothesize that ail
three CPS must be experienced to maximize internal work motivation.
Examinations of the Mediation Hypothesis
Few studies have examined the hypothesized mediating role of the CPS
in the model (cf. Arnold & House, 1980; Champoux,
1991; Fox & Feldman,
1988; Fried & Ferris, 1987; Hackman & Oldham, 1976; Hogan & Martell, 1987;
Johns et al., 1992; Tiegs et al., 1992; Wall et al., 1978). Instead, studies that
included the CPS typically examined the linkages between the core job
dimensions and the CPS (e.g., Does skill variety correlate with experienced
meaningfulness?),
and between the CPS and attitudinal
and behavioral
outcomes
(e.g., Do the CPS correlate
with internal work motivation,
performance,
and turnover?). Although correlation studies cannot be viewed
as tests of the mediation hypothesis (Fried & Ferris, 1987), they do provide
some insight into the hypothesized linkages among the model’s components.
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283
Regarding the core job dimensions-CPS linkages, task identity has not
always related well to experienced meaningfulne-ss. Instead, task identity has:
(1) operated just the opposite of what was originally hypothesized (Miner, 1980);
(2) not related to any CPS (Fox & Feldman, 1988; Hackman & Oldham, 1976);
or (3) related better to experienced responsibility or knowledge of results than
to experienced meaningfulness (Arnold & House, 1980; Fried & Ferris, 1987;
Johns et al., 1992). Autonomy has been shown to relate equally well to all three
CPS (Arnold & House, 1980; Fried & Ferris, 1987). Feedback, in general, has
related well to knowledge of results, although Fried and Ferris’ (1987) meta
analysis showed feedback related equally well to all three CPS. Skill variety
and task significance have related well to experienced meaningfulness.
Regarding the CPS-outcomes linkages, the CPS have related well to
internal work motivation, growth satisfaction, and general satisfaction (Fried
& Ferris, 1987; Hackman & Oldham, 1976; Johns et al., 1992). They have not,
however, consistently related well to performance or absenteeism (cf. Berlinger,
Glick & Rodgers, 1988; Fried & Ferris, 1987; Griffin, Welsh & Moorhead, 1981:
Griffin, 1991; Hackman & Oldham, 1976). The Fried and Ferris (1987) metaanalysis found that experienced meaningfulness had stronger associations with
attitudinal outcomes than did responsibility or knowledge of results, but a more
recent study by Johns et al. (1992) showed that the three CPS related equally
well to attitudinal outcomes.
A few studies have examined whether the CPS mediated the relations
between the core job dimensions and outcomes and/or the requirement that
all three CPS must be experienced. With regard to their role as mediators,
Hackman and Oldham (1976) demonstrated that the CPS completely mediated
the effects of fewer than half of the hypothesized linkages between the core job
dimensions and personal and work outcomes. That is, after controlling for the
CPS, many of the core job dimensions had significant associations with the
outcome variables. Hackman and Oldham’s findings, thus, suggested that the
CPS were partial mediators of most of the core job dimensions-outcomes
relations. Johns et al., (1992) showed that meaningfulness and responsibility
did not completely mediate the relations between skill variety, autonomy, and
a set of personal and work outcomes. With regard to the requirement of
experiencing all three CPS, reviews and studies have not supported the
hypothesis that all three CPS must be experienced to maximize improvements
in personal and work outcomes (Arnold & House, 1980; Fried & Ferris, 1987;
Hackman & Oldham, 1976; Johns et al., 1992).
To summarize, these findings appear to suggest that: (1) some of the core
job dimensions may not relate as expected to their theoretically specified CPS;
(2) the CPS may relate more strongly to attitudinal outcomes than to behavioral
outcomes; (c) the CPS may be partial mediator variables; and (d) all three CPS
may not be necessary to optimize improvements in personal and work outcomes.
Recall, however, that the majority of the above studies did not examine the
mediation hypothesis. Consequently, the collective findings derived from these
studies must be viewed as only suggestive of a lack of support and not conclusive
evidence against the hypothesized mediating role of the CPS. It seems
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important, therefore, for additional research to focus on answering the question
of whether the CPS should be included in the job characteristics model and,
if so, in what form their role should be modeled.
The Present Research
Two studies were conducted to address the latter issue. Study 1 was
primarily a test of the original mediation hypothesis using Baron and Kenny’s
(1986) mediation testing approach. The first question addressed in Study 1 was
the main one underlying the stated purpose of the present research: Do the CPS
mediate the relationship between the core job dimensions and personal and
work outcomes, or are they an unnecessary component of the job characteristics
model per the impression given by the bulk of studies excluding them from
their tests? As noted earlier, we found no evidence to suggest that they should
be excluded. Thus, we predicted that:
Hypothesis I: The CPS will mediate the relations between the core
job dimensions and outcomes.
Although never explicitly stated by Hackman and colleagues (Hackman
& Lawler, 1971; Hackman & Oldham, 1976; 1980), an examination of both
past and contemporary portrayals of the job characteristics model (i.e., Figure
1; Hogan & Martell, $987) gives the impression that the CPS are complete
mediators of the core job dimens~ons~ut~omes relations. That is, the job
characteristics model suggests that the core job dimensions’ total effects on
outcomes are transmitted through the CPS (James & Brett, 1984). As noted,
however, there is empirical evidence indicating that the core job dimensions’
total effects may not be fully transmitted through the CPS (e.g., Hackman &
Oldham, 1976; Johns et al., 1992). First, one cannot ignore that fact that two
meta-analyses show that core job dimensions have significant direct effects on
outcomes (Fried & Ferris, 1987; Loher et al., 1985). Second, in tests including
the CPS, there exists support for the core job dimensions’ direct effects and
indirect effects through the CPS on outcomes. This empirical evidence,
therefore, suggests that the CPS may be partial rather than complete mediators.
Study I was designed to test this aspect of the CPS’ mediating role more
explicitly than has previous research. Based on the evidence bearing on the
question of complete or partial mediation, we predicted that:
Hypothesis 2: The CPS will be partial mediators in that the core
job dimensions will have direct effects on outcomes, and indirect
effects through the CPS.
Unlike the above, Hackman and Oldham do state explicitly that all three
CPS must be experienced to maximize the explanation of internal work
motivation (1976, p. 256). However, like the above, there is empirical evidence
suggesting that this aspect of the mediation hypothesis may not hold.
Specifically, the Hackman and UIdham (1976) and Arnold and House (1980)
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PSYCHOLOGICAL
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STATES
studies show that all three CPS are not necessary to maximize the explanation
of outcome variance. Thus, we predicted that:
Hypothesis 3: All three CFS will not be necessary to maximize the
explanation of outcome variance; however, the CPS will account for
significant amounts of outcome variance beyond the core job
dimensions.
Study 2 represented a validation of the Study 1 findings. It was based on
a different sample and different methodology. In this vein, Study 2 permitted
the determination of whether conclusions regarding the CPS’ mediating role
converged when examined with different samples and methods. To the degree
that convergence occurs, confidence is gained in the validity of the conceptual
premises underlying the theory in question (Brewer & Hunter, 1989). Using
structural equation methodology, Study 2 examined the fit of three different
job characteristics models, each of which included a different role for the CPS
in the model: (1) the job characteristics model shown in Figure 1, which modeled
the CPS a complete mediators; (2) a job characteristics model that included
the CPS’ direct effects and indirect effects through the CPS on outcome
variables, thus testing the partial mediating role of the CPS; and (3) a job
characteristics model that excluded the mediating role of the CPS altogether,
thus modeling the majority of job characteristics model research. These three
models were compared to themselves and “best” and “worst” fitting reference
points (discussed below). For the reasons explained under the description of
Study I above, it was postulated that the model most representative of the data
would be the one in which the CPS possess a mediating role, and a role of
partial rather than complete mediation.
Hypothesis 4: The job characteristics model that includes the CPS
as partial mediators
will provide
the best explanation
of the
motivational processes underlying the job characteristics model.
STUDY I
Method
Sample
Data for Study 1 were collected from 188 geographically dispersed subjects
working for different offices of one organization located in the Southeast.
Subjects performed a variety of jobs, including management (15% of the
sample), professional counseling (72% of the sample), and secretarial and
administrative support (13% of the sample). The average age of the subjects
was 44 years, 55% of whom were males. Fifty-five percent of the subjects had
at least eleven years of experience with the organization. All subjects held high
school diplomas, and among them 85(ro had bachelors degrees and 66% had
master’s degrees.
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RENN AND VANDENBERG
Measures
The data were collected through surveys, distributed to and completed by
the subjects at their work sites. The surveys were given to the subjects in a packet,
which also contained a letter of endorsement
from the organization’s
chief
executive
officer and a return envelope
addressed
to the researchers.
Participation
was voluntary, and the subjects were guaranteed their responses
would remain confidential. Of the surveys distributed (N-230) and returned,
188 were fully completed and usable, yielding a response rate of 82%.
Core job dimensions. The revised Job Diagnostic Survey (JDS) was used
to measure live core job dimensions (Idaszak & Drasgow, 1987). The scales
and their internal consistency coefficients were: skill variety ((Y = .76), task
identity (a = .76), task significance (CX= .77), autonomy (CX= .79), and feedback
from the job (a = .74).
Critical psychological states. Scales from the original JDS were used to
measure the CPS (Hackman & Oldham, 1980). The scales and their alpha
coefficients were: meaningfulness
(a = .81), responsibility
((Y = .83), and
knowledge of results ((Y= .80).
Outcomes. Scales from the original JDS were used to measure general
satisfaction, internal work motivation, and growth satisfaction. The scales and
their alpha coefficients were: general satisfaction (CV= .85), internal work
motivation (a! = .90), and growth satisfaction (a! = .81).
Analysis
Baron and Kenny’s (1986) approach for testing mediation hypotheses was
used to test Hypotheses
1 and 2. Their approach required estimating three
regression equations,
which we have labeled Steps 1, 2 and 3, for each
hypothesized mediated relationship. Step 1 required regressing the mediator on
the independent variable. Step 2 required regressing the dependent variable of
the independent variable. And Step 3 required regressing the dependent variable
on the independent variable and the mediator.
According to Baron and Kenny, support for mediation is provided if the
following conditions hold: (1) the first regression shows that the independent
variable affects the mediator;
(2) the second regression shows that the
independent variable affects the dependent variable; and (3) the third regression
shows that the mediator affects the dependent variable and the effect of the
independent variable on the dependent variable is lower in magnitude in the
third equation than in the second equation (1986, p. 1177). To provide support
for complete mediation, the independent variable must not affect the dependent
variable when the mediator is controlled.
Hypothesis 1 states that the CPS will possess a mediating role in the job
characteristics
model. Thus, support for Hypothesis 1 would be provided if:
(1) each core job dimension affects its hypothesized
CPS (e.g., skill variety
affects experienced meaningfulness) (Step 1); (2) each core job dimension affects
each outcome variable (e.g., skill variety affects internal work motivation) (Step
2); and (3) each CPS affects each outcome variable (e.g., experienced
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CRITICAL
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STATES
281
meaningfulness affects internal work motivation) (Step 3). Further, the effect
of each core job dimension on each outcome variable must be lower in
magnitude when each theory-specified CPS is controlled (e.g., the effect of skill
variety on internal work motivation must be lower in magnitude when
experienced meaningfulness is controlled) (Step 2 vs. Step 3).
Hypothesis 2 states that the CPS will be partial rather than complete
mediators. To provide support for this hypothesis, the results of Step 3 must
show that each core job dimension affects each outcome variable when each
theory-specified CPS is controlled (e.g., skill variety must affect internal work
motivation when experienced meaningfulness is controlled).
Hypothesis 3 states that all three CPS will not be necessary to maximize
the explanation of outcome variance; however, the CPS will account for
significant amounts of outcome variance beyond the core job dimensions.
Arnold and House’s (1980) regression technique was used to test this hypothesis.
They tested the requirement that all three CPS are necessary by comparing the
amount of outcome variance explained by a regression equation including the
main effects of the CPS and the CPS’ three two-way interaction terms to the
amount of variance explained by a regression equation including the latter terms
plus the CPS’ three-way interaction term. To support this requirement, they
suggested that the regression equation that included the main effects of the CPS,
the CPS’ three two-way interactions, and the CPS’ three-way interaction term:
(1) should explain the greatest amount of variance in an outcome variable; and
(2) should have a significant partial regression coefficient representing the CPS’
three-way product term.
The second part of Hypothesis 3 states that the CPS will explain significant
amounts of outcome variance beyond the core job dimensions. To test this part
of Hypothesis 3, we compared the amount of outcome variance explained by
a regression equation that included the main effects of the core job dimensions
to the amount of outcome variance explained by a regression equation that
included the main effects of the core job dimensions and the CPS, the CPS’
three two-way interactions, and the CPS’ three-way interaction. If the CPS
contribute to the job characteristics model’s explanatory power beyond the core
job dimensions, the second regression equation that includes the CPS would
be expected to explain significantly greater proportions of outcome variance
than the regression equation that included only the main effects of the core
job dimensions.
Results and Discussion
The means, standard deviations, and correlations among all Study 1
variables are presented in Table 1. Hypothesis 1 states that the CPS will possess
a mediating role between the core job dimensions and outcome variables. The
test for Hypothesis 1 required the estimation of three regression equations. In
the first regression equation, each CPS was regressed on its hypothesized core
job dimension. To satisfy this part of the test (Step I), each core job dimension
must affect its hypothesized CPS in the first regression equation. The regression
results for Step 1 are shown in Table 2. As seen in Table 2, all the regression
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1.17
1.22
5.22
4.77
Autonomy
1.30
1.18
5.38
5.59
Note:
47
34
30
36
40
53
26
41
28
&j
1
Deviations,
:‘:
46
32
51
47
57
35
57
..-
2
::
28
23
57
61
18
40
3
22
32
18
49
39
47
26
4
and Inte~~orrelations
15
11
13
34
-10
19
5
6
::
58
29
24
Among
26
35
14
49
-
7
31
37
29
8
Study I Variables
N = 188. Decimals omitted from correlation matrix. Correlations equal to r = ,151
are significant at p < .OS.
1.25
Task Identity
Task Significance
11. Job Feedback
10.
9.
7.
8.
.79
1.32
1.06
1.29
5.83
5.49
6.10
5.19
5.40
3.
4.
5.
6.
“5
h,
5
v1
SD
1.35
1.24
internal
Motivation
Meanin~ulness
Knowledge of Results
Responsibility
Skill Variety
1. General Satisfaction
2. Growth Satisfaction
M
4.89
4.17
Table 1. Means, Standard
p
E
*!
2
2
=;
s
:
;
8
25
45
-
9
42
IO
--
II
g
!z
?z
5
z!
d
$
ifi
z
289
CRITICAL PSYCHOLOGICAL STATES
Table 2.
Regression Results for Core Job Dimensions’Effects on Psychological States
Critical Psychological States
Core Job Dimension
Now
-
.53**
.62**
.E*
-
N = 188. Standardized
* p < ‘05; ** p < .Ol.
Table 3.
-
.40**
.17*
Skill variety
Task identity
Task significance
Autonomy
Job feedback
Knowledge
Responsibility
Meaningfulness
regression
coefficients
reported.
Dashes indicate
coeffkient
not estimated.
Regression Results for Core Job Dimensions’ Effects on Outcomes
Regression and Partial Regression Coefficients
for Core Job Dimensions’
Outcomes
Skill
Variety
Task
Identity
Task
Significance
Autonomy
Feedback
.31**
.50**
.27**
.27**
.28**
.14**
*44**
.55**
57**
.69**
.36**
.47**
.34**
.20**
.19**
General satisfaction
Growth satisfaction
Internal motivation
Note:
N= 188.
a Standardized
regression
* p < .05; ** p < .Ol.
coefficients
reported.
coefficients representing the core job dimensions’ main effects on their
hypothesized CPS were statistically significant. These results, therefore, satisfied
Step 1 of the test for mediation.
In the second regression equation, each outcome variable was regressed
on each core job dimension (Step 2). The Step 2 test required that each core
job dimension affect each outcome variable in the second regression equation.
The results for the Step 2 test are shown in Table 3. Findings showed that the
regression coefficients representing the five core job dimensions’ main effects
on general satisfaction, growth satisfaction, and internal work motivation were
all significant. These findings, thus, satisfied the Step 2 test for mediation.
In the third regression equation, each outcome variable was regressed on
each core job dimension and hypothesized mediating CPS (Step 3). The Step
3 test required that the CPS affect each outcome variable in the third regression
equation, and that the effects of each core job dimension be lower in magnitude
in the third versus the second regression equation. Table 4 depicts the results
for the Step 3 test. As seen in Table 4, all but one of the regression coefficients
representing the CPS’ main effects on general satisfaction, growth satisfaction,
and internal work motivation were significant. The one exception was the
nonsign~icant regression coefficient representing the effects of knowledge of
results effect on internal work motivation.
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RENN AND VANDENBERG
Table 4.
Regression Results for Core Job Dimensions’ and CPS’ Effects on Outcomes
Outcomes
General
Satisfaction
Predictor
Growth
Satisfaction
Internal
Motivation
Skill variety
Meaningfulness
.08
.51**
.31**
.41**
.14**
.30**
Task identity
Meaningfulness
.20**
.51**
.20**
.50**
.09*
.34**
Task significance
Meanin~u~ness
.15**
.47*x
.31**
.39**
.19**
.26**
Autonomy
Responsibility
.53**
.29**
*64**
.33+*
.14**
.44**
Feedback
Knowledge of results
.I1
.39**
.18**
.45**
.17**
.Ol
Note:
N= 188.
*p
< .os;** p < .Ol.
The second part of the Step 3 test required that the partial regression
coefficients representing the core job dimensions’ main effects on the outcome
variables be lower in magnitude in the regression equations that controlled the
hypothesized CPS (shown in Tabie 4) than the regression coefficients obtained
from the regression equations that excluded the CPS (Step 2 regression results
shown in Table 3). A comparison of the partial regression and regression
coefficients (Table 4 vs. Table 3) revealed that the effects of the core job
dimensions on general satisfaction, growth satisfaction, and internal work
motivation were all lower in magnitude when the hypothesized CPS were
controlled. These findings satisfied the second part of the Step 3 test for
mediation. Combined, the results of the three regression equations satisfied all
three steps in the test for mediation. Except in the case of knowledge of results,
these findings provided support for Hypothesis 1.
Hypothesis 2 states that the CPS will be partial rather than complete
mediators of the core job dimensions-outcomes relations. The test for this
hypothesis related to the partia1 regression coefficients representing the core job
dimensions’ effects on the outcome variables when the theory specified CPS
were controlled (Table 4 regression results). Specifically, if the partial regression
coefficients representing the core job dimensions’ effects on the outcomes are
significant when the CPS are controlled, support for partial mediation is
provided. By contrast, if the partial regression coefficients are not significant
when the CPS are controlled, support for complete mediators is provided. As
shown in Table 4, thirteen of the fifteen partial regression coefficients were
significant after the theory-specified CPS were controlled. Two exceptions were
the partial regression coefficients representing the direct effects of skill variety
and feedback on general job satisfaction. Aside from these two exceptions, the
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Table 5.
291
Outcome Variance Explained by Job Dimensions
and Critical ~sychologic~ States
&for Outcome Variables
General
Satisfaction
Growth
Satisfaction
Internal
Motivation
Five core job dimensions
.31
.56
.29
M, R, K, M X R, M X K, R X IL”
.43
.63
.51
M, R, K, M X R, M X K, R X K,
MXRXK”
.43
.63
.5f
Predictor
Note:
N = 188. All R2’s 0, < .Ol). M = experienced meaningfulness; R = experienced responsibility;
K = knowledge of results.
a Variables entered into regression equation after the five core job dimensions.
findings supported the hypothesis that the CPS are partial rather than complete
mediator variables.
Hypothesis 4 states that all three CPS will not be necessary to maximize
the explanation of outcome variance, and that the CPS will account for significant amounts of outcome variance beyond the core job dimensions. If the three
CPS are necessary to maximize the explanation of outcome variance, there
should be a significant R2 increment when the CPS’ three-way product term
is included in the regression equation containing the main effects of the core
job dimensions and the three CPS, and the CPS’ three two-way product terms.
Table 5 summa~zes the regression results for this test. As seen in Table 5, the
findings showed that the three-way product term did not increase the amount
of variance explained in general satisfaction, growth satisfaction, or internal
work motivation beyond the amount of variance explained by the regression
equation that included the main effects of the core job dimensions, the CPS,
and the CPS’ two-way interaction terms. Further, the partial regression
coefficients representing the CPS’ three-way interaction te2ms in these
regressions were all nonsigni~cant (results available from the authors).
The regression results shown in Table 5 also indicated that the CPS
explained significant amounts of variance in general satisfaction, growth
satisfaction, and internal work motivation beyond the core job dimensions. As
expected, the five core job dimensions alone accounted for significant amounts
of variance in these outcome variables. However, the propo~ion of variance
accounted for in all three outcome variables increased sign~cantly when the
three CPS were added to the regression equations. Specifically, adding the three
CPS to the regression equations increased the proportion of explained outcome
variance in general job satisfaction by 13% (Fj,179=: 14.4, p < .Ol), growth
satisfaction by 12% (F 3,t79= 22.5, p < .Ol), and internal work motivation by
22% (F3,179= 22.5, p < .Ol). These findings, thus, provided support for
Hypothesis 3.
To summarize, the findings from the Baron and Kenny (1986) approach
provided support for Hypotheses 1 and 2. In accordance with the job
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characteristics model, the findings indicated that the core job dimensions related
well to their specified CPS and that the CPS related well to general job
satisfaction, growth satisfaction, and internal work motivation. Further,
experienced meaningfulness completely mediated the skill variety-general job
satisfaction relationship, and knowledge of results completely mediated the
feedback-general satisfaction linkage. By constrast, the findings indicated that
meaningfulness, responsibility, and knowledge of results were partial mediators
of the remaining hypothesized relations between the core job dimensions and
general job satisfaction, growth satisfaction, and internal work motivation. In
addition, the feedback-internal work motivation relationship was not mediated
by knowledge of results. Finally, the endings provided support for Hypothesis
3. All three CPS were not necessary to maximize the explanation of outcome
variance, and the CPS accounted for significant amounts of outcome variance
beyond the core job dimensions. Study 2 was designed to further examine the
Study 1 finding that the CPS were partial mediators of the core job dimensionsoutcomes relations.
STUDY 2
Methods
Sample and Data Cdection
The Study 2 sample consisted of 90 policy processing and customer service
employees of a major Southeastern insurance company. The subjects
represented 100% of the employees in this functional area. The subjects
performed three categories of jobs, namely management and supervision (N
= 8), policy processing and issuing (N = 70), and customer service ( N = 12).
Median age and years of education were 28.5 and 12 years, respectively. Seventythree percent of the sample was female. Sixty-four percent of the subjects had
been in their current jobs two years or less, and 51% had been with the
organization five years or less.
Measures
The Study 2 data were collected through surveys. Subjects completed the
surveys in large group sessions away from the work area and were guaranteed
anonymity of their responses through minimum identification requirements.
Core job dimensions. Scales from the revised Job Diagnostic Survey
(JDS) were used to measure five core job dimensions (Idaszak & Drasgow,
1987). The measures and their internal consistency reliabilities were: (1) skill
variety ( a! = .76); (2) task identity (a = .76); (3) task significance (o = .77);
(4) autonomy (a, = .90); and (5) feedback from the job (Q = 69).
Critical psychological states. For the CPS, the original JDS items were
used (Hackman & Oldham, 1980). The scales and their internal consistency
coefficients were: (1) meaningfulness (a = .81), responsibility ((u = .83), and
knowledge of results (a = 80).
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Outcome variables. Two outcome measures from the original JDS
(Hackman & Oldham, 1980) were completed by respondents: (1) general job
satisfaction ((Y= .85); and (2) internal work motivation (a = .90). In addition,
job search intentions were assessed by having employees respond with l=(O
to 20%), 2=(21 to 40%), 3=(41 to 60%), 4=(61 to 80%), or 5=(81 to 100%)
to the question: “What is the probability that you will be involved in a search
for a job outside the company during the next 12 months?”
Model Development
and Analysis
Based on Anderson and Gerbing’s (1988)“two-step" approach (discussed briefly
below) for evaluating competing theoretical structural models, five nested “job
characteristics models” were estimated using LISREL VII (Joreskog & S&born,
1989). Differences among the nested models are summarized in Table 6. Model I
represented the least restricted or saturated structural model. For the saturated
model, all possible paths among this “job characteristics model’s” components were
estimated. The paths from skill variety, for example, to all three CPS were estimated,
as were the paths from skill variety to all of the outcome variables. The paths from
the remaining core job dimensions to the CPS and outcomes were all freed in a
similar manner. This model was estimated to provide goodness of fit indices
(discussed below) for the best possible fitting structural model.
Model II represented the next least restricted model in the sequence. This
model estimated the core job dimensions’ direct and indirect effects on personal
and work outcomes. Direct effects were estimated by freeing the paths from
the core job dimensions directly to the personal and work outcomes. The
indirect effects were estimated by freeing the paths from the core job dimensions
to their speczjied CPS and freeing the paths from the CPS to the outcomes.
Model II was based on Hackman and Oldham’s (1976) finding and the Study
1 finding that the CPS may be partial rather than complete mediator variables.
Model III represented the original job characteristics model and the next
model in the sequence (see Figure 1). For Model III, only the core job
dimensions’ indirect effects on personal and work outcomes were estimated.
The paths from the core job dimensions to their specified CPS were freed, as
were the paths from the CPS to the outcome variables.
Model IV excluded the mediating role of the CPS from the job characteristics model. Only the core job dimensions and the outcome variables were
Table 6.
Model
I
II
III
IV
V
Note:
Study 2 Model Differences
Structural Specifications
Paths among all job characteristics model components.
Paths from: (a) CJD to outcomes; (b) CJD to CPS; (c) CPS to outcomes.
Paths from: (a) CJD to CPS; (b) CPS to outcomes.
Paths from CJD to outcomes.
Structural null model.
CJD = core job dimensions; CPS = critical psychological states.
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RENNANDVANDENBERG
included in this model. Paths from the core job dimensions to the outcome
variables were estimated. Model IV was based on job characteristics
model
research that has excluded the mediating role of the CPS and estimated only
the core job dimensions’ direct effects on personal and work outcomes.
Lastly, Model V represented the structural null or most restricted model
in the sequence. For Model V, all paths among the job characteristics model’s
components were fixed to zero.
Covariance matrices and information
about each scale’s reliability and
variance were used as input for the LISREL program (Podsakoff,
Williams
& Todor, 1986; Renn, 1989). Two-stage least squares and maximum-likelihood
procedures yielded initial and final parameter estimates, respectively. The latentto-manifest parameter for each variable was fixed to the square root of the
reliability (internal consistency coefficients) for each measure, and the value one
minus the reliability times a variable’s variance was used to represent residuals.
This technique provided the means to incorporate measurement error into the
analysis prior to estimating the structural models.
Models Comparison
Sequential Chi-Square Difference Tests (SCDTs).
SCDTs were used to
compare statistically the fit of the five nested structural models. Specifically,
the five models were compared via a decision-tree framework similar to a
framework provided by Anderson and Gerbing (1988, p. 420). In general, the
framework required a sequential a priori comparison of the chi-square values
and associated degrees of freedom of two models-one
more restricted than
the other. The models were compared in an priori sequence to determine if
restricting a set of parameters to equal zero statistically reduced a model’s power
to account for covariance among the model’s constructs (Anderson & Gerbing,
1988; Bentler & Bonett, 1980; James et al., 1982; Williams & Hazer, 1986). The
null hypothesis for each paired models comparison was no significant difference
between the chi-square values of the least and more restricted models. A rejected
null hypothesis, as indicated by the SCDT, provides statisticaz support for the
least restricted of the two models. Anderson and Gerbing indicated, however,
that statistically significant differences between models may be found during
these comparisons even when there are trivial differences between the amounts
of construct
covariance
explained by each model. Thus, they suggested
comparing the models on a practicaZ as well as statistical basis. To this end,
we used the parsimonious fit index to judge the practical significance of each
model (James et al., 1982). These as well as other fit indexes used to judge the
fit of the five models are described below.
LISREL ‘s Goodness of Fit Indexes. The overall fit of each model to the
data was assessed with LISREL’s chi-square statistic, Goodness of Fit Index
(GFI), Adjusted Goodness of Fit Index (AGFI), and Root Mean Square
Residual (rmsr). In general, a nonsignificant chi-square, large GFI and AGFI,
and small rmsr values are associated with better fitting models.
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~~crerne~~aZ
Fit Index (IFI). The IF1 was used to judge the relative fit
of competing models to the data in relation to the structural null model (Bollen,
1989). The IF1 has the same advantage of accurately reflecting model fit as the
normed fit index (Bentler & Bonett, 1980) and has the additional advantages
of performing better with small samples and having a smaller sampling variance
(Bentler, 1990). The range of IF1 values is generally between O-l, with larger
values reflecting better fitting models.
Parsimonious Fit Index (PFI). The PFI was used to compare the
practical significance and efficiency of the five models (James et al., 1982). The
PFI represents a model’s ability to explain construct covariance given the
number of freely estimated parameters. Even when there is statistical support
for a least restricted model (i.e., a model with more freely estimated parameters),
the more restricted model may be judged superior from a practical standpoint
based upon a superior PFI value. A superior relative PFI indicates that a model
is more parsimonious or efficient than a competing model in explaining an
acceptable amount of construct covariance (Anderson & Gerbing, 1988, p. 421).
Signifkance of Parameter Estimates. The significance of the parameter
estimates for each model was determined by a statistic approximating the tdistribution. Estimates with t-values of 2.0 or greater are significant at or beyond
the p < .05 level.
Descriptive statistics for the manifest variables are shown in Table 7. The
goodness of fit indexes for Models I-V are presented in Table 8. As seen in
Table 8, of the theoretical models examined (Models II-IV), the two models
that included the CPS provided better fits to the data than did the model that
excluded the CPS (Model IV). In brief, Models II and III had the smallest chisquare and rmsr values, and the largest GFIs, AGFIs, IFIs, and PFIs. Both
models also had the largest ratio of the number of significant obtained to
hypothesized path coefficients.
The models were subjected to an a priori series of SCDTs: (1) Model III
(job characteris tics model with CPS) versus Model I (fully saturated model),
~2~~~~~~~
= 294.6,~ < .Ol; (2) Model IV (CPS excluded) versus Model III, x2&rffi)
= 77.1, p < -01; (3) Model III versus Model II (core job dimensions direct and
indirect effects through CPS), X2dirrtr>)
= 274.0,~ < .Ol; and (4) Model II versus
Model 1, X*&K(~)
= 20.5, p < .Ol.As expected, the SCDTs indicated that Model
I (fully saturated model) provided a statistically better fit to the data than did
the other models. More important, however, were the results for the theoretical
models (Models II-IV). The results indicated that, next to the fully saturated
model (Model I), Model II provided the best fit to the data. Further, Model
II’s PFI value indicated that it was the most parsimonious of all models,
including Model I. Thus, from a statistical and practicaZ standpoint, the model
comparisons provided the greatest support for Model II.
Comparing Model II directly to Model III (original job characteristics
model) provided additions support for Model II. Specifically, Model II’s
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1.8
4.1
5.4
4.8
5.0
4.8
3.9
3.1
5.3
4.4
4.3
1. Search intentions
General satisfaction
3. Internal motivation
4. Meaningfulness
5. Responsibility
6. Knowledge of results
7. Skill variety
8. Task identity
9. Task significance
10. Autonomy
11. Job feedback
Correlations
greater than .21 are significant
NCHP: N = 90. Decimals omitted from correlation
2.
M
-24
-02
-24
-01
-25
-01
-10
-14
-10
-08
I
47
45
36
22
25
06
17
38
27
2
Deviations,
matrix.
at p < .05 (one-tailed).
1.1
0.9
1.1
1.0
1.1
1.6
1.6
1.4
1.7
1.3
1.2
SD
Means, Standard
Variable
Table 7.
16
22
16
07
03
07
17
14
3
51
16
55
32
49
45
27
4
and Intercorrelations
33
36
40
26
42
27
5
II
14
07
19
52
6
12
61
54
26
7
04
35
21
8
for Study 2 Variables
43
29
9
32
10
-
I1
CRITICAL
PSYCHOLOGICAL
Tabie 8.
297
STATES
Goodness of Fit Indexes
Fit Indexes
df
xz
P
rmsr
GFI
AGFI
IFI
PFI
Paths
19.4
40.0
314.0
391.1
.20
.05
.OOl
IV
::
36
37
.06
.09
.14
.33
.95
.92
.80
.68
.80
.I4
.62
.29
1.0
.96
.43
.27
.32
.43
.32
-21
18/39
16129
6/ 14
2115
Null
61
520.5
.44
.64
.23
-
-
Model
I
II
III
.OOl
.OOl
-
Nore: N= 90. df= degrees of freedom; x2 = chi square; rmsr = root mean square residual; GFI = goodness
of fit index; AGFI = adjusted goodness of fit index; IFI = incremental fit index; PFI = parsimonious
fit index; Paths = ratio of significant obtained to predicted parameters.
Table 9.
Path
(I) SV-M
(2) TI-M
(3) TS-M
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
(13)
(14)
(15)
A-R
F-K
M-S
M-IM
M-S1
R-S
R-IM
R-S1
K-S
K-IM
K-S1
sv-s
Nore:
Obtained Parameter Estimates for Model II
Estimate
Path
Estimate
.08
.40*
.58*
.51*
.63*
.75*
.03
-.54*
.16
.08
-.I0
.06
.07
-.42*
.48*
(16) SV-IM
(17) sv-SI
(18) TI-S
(19) TI-IM
(20) TI-SI
(21) TS-S
(22) TS-IM
(23) TS-SI
(24) A-S
(25) A-IM
(26) A-SI
(27) F-S
(28) F-IM
(29) F-S1
3.30*
-.22*
.78*
.58*
-.23
1.25*
2.28*
-.62*
.52”
.36
-.I7
.49*
.56*
-.25
Each path combination
should be read as “from” one variable “to” the other.
SV = skill variety; TI = task identity; TS = task significance; A = autonomy; F = feedback; M
= meaningfulness;
R = responsibility;
K = knowledge of results; S = general satisfaction; IM =
internal motivation; SI = search intentions.
Estimates greater than one due to scaledifferences.
* p < .05.
goodness of fit indexes were superior to those of Model III. And according
to Model II’s PFI value, its superior fit over Model III was not due to relaxing
parameters (James et al., 1982). The SCDTs (discussed above) also showed that
Model II provided a statistically better fit to the data than does Model III. Model
II also had a higher ratio of the number of significant obtained to hypothesized
path coefficients than does Model III. Table 9 shows the LISREL estimates
of the path coefficients for Model II.
In summary, the goodness of fit indexes associated with Models I-V
indicated that the two job characteristics models that included a mediating role
for the CPS provided better fits to the data than did the model that excluded
the CPS’ mediating role. Of the two models including a mediating role for the
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..................
...........
.
,_.’
Note:
N = 90. Ali paths shown are significant at or beyond p < .05. Solid paths represent significant paths
from original job characteristics
model. Dotted paths represent significant paths representing the
core job dimensions’ direct effects on persona1 and work outcomes.
Figure 2. Best-Fitting Job Characteristics Model
CPS, the model comparisons and the ratios of the number of significant
obtained to hypothesized path coefficients provided their greatest support for
the job characteristics model that represented the CPS as partial rather than
complete mediator variables. Thus, the Study 2 results validated the Study 1
finding that the CPS were partial rather than complete mediators of the core
job dimensions-outcomes relations. Figure 2 depicts the job characteristics
model (Model II) that received the greatest support in Study 2.
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STUDY 1 AND STUDY 2
General Discussion
The primary question driving this research was: Do the CPS make a
significant contribution to the job characteristics model’s ability to explain basic
work processes, or are the CPS an unnecessary component of the job
characteristics
model whose exclusion would make the theory more
parsimonious? With regard to this underlying question, the findings from both
studies indicated that the CPS contributed significantly to the job characteristics
model’s explanatory power, and thus, should not be excluded from the theory.
Although they supported the inclusion of the CPS, the findings did not support
the CPS’ inclusion as was originally hypothesized and depicted in the job
characteristics model. The findings did not support the requirement that all three
CPS need to be experienced to maximize the explanation of work outcomesa finding that was consistent with our hypothesis and with the findings of past
research (Arnold & House, 1980; Hackman & Oldham, 1976). In addition, the
findings did not support the CPS’ role as complete mediators of the core job
dimensions-outcomes relations (as depicted in the job characteristics model).
Findings from both studies demonstrated that the core job dimensions had
direct and indirect effects (through the CPS) on the outcome variables. This
finding is subject to at least two interpretations, both of which have implications
for future job characteristics model research.
First, the core job dimensions’ direct effects on personal and work
outcomes could represent an individual’s immediate affective response to a job
stemming from the momentary activation of certain cognitions (Feldman &
Lynch, 1987). Namely, researchers note (e.g., Vandenberg & Seo, 1992) that
certain stimuli in the work environment (in this case job dimensions) cause both
an immediate affective response to that stimuli, and the stimulation of cognitive
processes that reflect a more piecemeal careful assessment of the implications
the stimuli have for the individual (see also, Lord, 1991). This more careful
assessment is not immediate but in the long run causes an individual to alter
his or her immediate reactions to the stimuli. Within this perspective, the core
job dimensions direct effects may represent an individual’s immediate affective
reaction to a job. By contrast, the core job dimensions’ indirect effects through
the CPS may represent an individual’s more thought out and long term
assessment of the job. Testing this interpretation of the core job dimensions
direct and indirect effects goes beyond the limits of the present cross-sectional
data. However, this interpretation could be tested by collecting multiple waves
of measures in a longitudinal study. With such longitudinal data, researchers
could test this interpretation by analyzing the core job dimensions’lagged effects
(through the CPS) apart from their immediate effects on personal and work
outcomes.
Second, that meaningfulness, responsibility, and knowledge of results did
not explain the core job dimensions’ total effects on the present outcomes leaves
room for other “psychological states” to mediate these relations. Gardner and
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Cummings (1988), for example, hypothesize that activation theory may explain
why core job dimensions influence personal and work outcomes (see also
Hackman & Oldham, 1976; Scott, 1966). Drawing from activation theory,
Gardner and Cummings postulate that enriched or “high impact” jobs (as
reflected in higher levels of the core job dimensions) may stimulate higher
activation levels (potential “CPS”), which, in turn, lead to positive affect and
behavioral efficiency (better personal and work outcomes). By contrast,
monotonous or “low impact” jobs may depress activation levels, which, in turn,
lead to negative affect and lower performance. Fox and Feldman (1988) provide
some support for activation level as a potential mediating CPS. They found
that arousal {operation~ized as attention state) mediated the relationship
between skill variety, task identity, and autonomy and general job satisfaction,
effort, and performance.
Fried and Ferris’ meta analysis led them to also suggest that other
psychological states unspecified by the job characteristics model may mediate
the relationship between the core job dimensions and performance (1987, p.
312). They found that, of the five core job dimensions, task identity and job
feedback had the strongest associations with performance. However, they also
found that experienced meaningfulness and knowledge of results-the
hypothesized mediators of these two job dimensions, were not related to
performance. Since a hypothesized mediator of the relationship between an
independent and a dependent variable must affect the dependent variable (Step
3 of the Baron and Kenny approach described above), Fried and Ferns’ findings
appear to indicate that experienced meaningfulness and knowledge of results
do not mediate, respectively, the relations between task identity and job
feedback and performance.
Thomas and Velthouse (1990) identified “CPS” (they labeled “task
assessments”) unspecified by the job characteristics model that may mediate
the relations between these core job dimensions and performance. They
theorized that perceived impact (Abramson, Seligman & Teasdale, 1978),
competence (Bandura, 1977), and choice (decharms, 1968) mediate the
relationship between interventions (e.g., job design or redesign) and behavior
(e.g., motivation and performance). Of these three potential CPS, it seems
plausible that perceived impact could mediate the relationship between task
identity and pe~ormance, and that competence may mediate the relationship
between job feedback and performance. Perceived impact represents “the degree
to which behavior is seen as ‘making a difference’ in terms of accomplishing
the purpose of the task” (Thomas & Velthouse; 1990: p. 672). Task identity
may prompt perceived impact because it represents the degree to which a job
requires the completion of an entire piece of work. Specifically, successful
completion of an entire task without assistance from others would be expected
to result in the belief that one’s work behaviors made the sole and significant
difference (i.e., had high impact on) in the quality and quantity of work output.
In turn, high perceived impact would be expected to lead to increased
motivation and improved work performance (Abramson et al., 1978).
Competence-a
concept similar to Bandura’s (1977) concept of self-efficacy,
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represents “the degree to which a person can perform task activities skillfully
when he or she tries”(Thomas & Velthouse, 1990, p. 672). Both the development
of competence and the knowledge of one’s competence may derive from job
feedback. Job feedback provides direct and clear information about work
effectiveness (Hackman & Oldham, 1980). Thus, positive feedback stemming
from high work effectiveness should lead to the belief that one can perform
a task effectively or competently. The belief that one is competent at a task,
in turn, has been linked to greater effort and persistence during task performance
(Bandura, 1977). Examining the potential mediating effects of perceived impact
and competence between task identity and job feedback and performance may
lead to a clearer understanding of why these two job dimensions relate more
strongly to performance than do skill variety, task significance, and autonomy,
job dimensions that may not prompt these “CPS.” In sum, despite which of
these two interpretations future research demonstrates to be the more accurate,
it is clear from the present findings that more research is needed on the
motivational underpinnings of the job characteristics model to provide a better
understanding of how and why job dimensions affect personal and work
outcomes.
Although based on two diverse samples and methodologies, the present
findings are not without limitations. Some may view the exclusion of the growth
need strength moderator as a limitation. As noted earlier, however, studies
indicate that the relations among the job characteristics model’s components
can be adequately tested without the growth need strength moderator (Graen
et al., 1986; Johns et al., 1992; Teigs et al., 1992). Further, the Fried and Ferris
(1987) meta-analysis demonstrates that growth need strength’s moderating
effects have been largely artifactual, except in the case of the core job
dimensions-performance relationship. Nonetheless, the present findings would
be strengthened if they were replicated by future research that included the
growth need strength moderator. The present findings were derived from crosssectional research designs and paper-and-pencil measures. Common method
variance, thus, may have inflated the present results. Glick, Jenkins & Gupta
(1986), however, show that core job dimensions have significant associations
with outcomes after common method variance is controlled. The Fried and
Ferris (1987) meta-analysis suggests that common method variance is not as
much of a threat to job characteristics model research as previously believed.
Further, to test for the potential effects of common method variance in Study
2, we ran a Hogan and Mar-tell (1987) test (see also, Vandenberg & Scarpello,
1990). This test revealed that a single-factor model-representing
common
method variance, produced a poorer tit to the data than did the fully-saturated
model (Model I) and the target model (Model II as shown in Figure 2) (results
available from the authors upon request). Therefore, common method variance
does not appear to be a likely alternative explanation for the present findings
supporting the partial mediating role of CPS.
Data in Study 2 were collected in partial fulfillment of the
1st author’s dissertation requirements. The authors wish to thank Emin
Acknowledgment:
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Babakus, Rabi Bhagat, John Miner, and Lynn M. Shore for their assistance
in preparing this manuscript. The first author thanks Paul M. Swiercz for
assistance in collecting the Study I data. We are also greatly indebted to and
thank three anonymous reviewers for their invaluable input and patience.
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