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THE EFFECTS OF ORGANIZATIONAL COMMITMENT, PROFESSIONAL
COMMITMENT, LIFE-SPAN CAREER DEVELOPMENT, AND
SELF-MONITORING ON JOB SATISFACTION AND JOB
PERFORMANCE AMONG STAFF ACCOUNTANTS
by
PETER JOHN POZNANSKI, B.S., M.S.
A DISSERTATION
IN
BUSINESS ADMINISTRATION
Submitted to the Graduate Faculty of Texas Tech University in
Partial Fulfillment of the Requirements for
the Degree of
DOCTOR OF PHILOSOPHY
Approved
May, 1991
So/ rz
e<
Copyright, 1991, Peter John Poznanski
ACKNOWLEDGMENTS
The participation of the professional accountants at
the office of the public accounting firm which
participated in this study is appreciated. Comments on
early drafts of this study from the accounting doctoral
students at Texas Tech University, notably Michael Shaub,
Randy Stitts, and Gary Caplan, are also appreciated.
Dr. Donald Clancy and Dr. James Wilcox were of great
assistance in the initial development of this study and
the data analysis, even though they were not committee
members.
A study such as this could not be successfully
completed without the assistance and encouragement of an
advisory committee, and the leadership of a committee
chairman. Dr. Don Finn's contributions as chairman have
made the completion of this study possible.
Finally, the continual support from family and
friends throughout the process is greatly appreciated.
Thank you all very much.
11
CONTENTS
ACKNOWLEDGMENTS ii
ABSTRACT v
LIST OF TABLES vii
LIST OF FIGURES ix
I. INTRODUCTION AND BACKGROUND 1 Need for the Study 3 Purpose of the Study 4 Organization of the Study 5
II. LITERATURE REVIEW 7 Job Satisfaction and Job Performance 8
Job Satisfaction in the Accounting Profession 9
Job Performance in the Accounting Profession 14
Organizational and Professional Commitment, Life-Span Career Development, and Self-Monitoring 21 Organizational and Professional Commitment in the Accounting Profession 21
Life-span Career Development 26 Self-Monitoring 32
Chapter Summary 42
III. THE THEORETICAL MODEL, RESEARCH MODEL, AND FORMULATION OF HYPOTHESES 45 The Theoretical Model 45 The Research Model 46 Formulation of the Hypotheses 48 Chapter Summary 54
IV. RESEARCH METHODOLOGY 56 Research Design 56
The Population for the Study 57 Development of the Research Instrument 58 Job Satisfaction Measurement 59 Job Performance Measurement 60 Organizational and Professional Commitment Measurement 62
111
Life-Span Career Development Measurement 63 Self-Monitoring Measurement 64 Research Instrument Distribution and Collection Technique 65
Pretesting the Research Instrument 66 Statistical Technique 71
LISREL Model Specification 72 Chapter Summary 79
V. EMPIRICAL ANALYSIS OF THE DATA 81 Response Information 81
Response Rates 81 Test for Nonresponse Bias 82
Statistical Analysis 84 Testing for Identification 84 Testing the Measurement Model 86 Hypothesis Testing 102 The Structural Model 103 Sequential Chi-square Difference Tests 106 Evaluating the Theoretical Model 114
Summary of the Data Analysis 123
VI. SUMMARY AND CONCLUSIONS 127 Summary of the Findings and Implications 127
Research Objective One 128 Research Objective Two 131 Research Objective Three 132
Contributions 134 Limitations 135 Future Research 136
REFERENCES 138
APPENDICES
A. RESEARCH INSTRUMENT 150
B. RESEARCH INSTRUMENT APPROVAL , 162
C. DEMOGRAPHIC DATA AND DESCRIPTIVE STATISTICS 164
D. LISREL RESULTS FOR INDIVIDUAL HYPOTHESES AND PARAMETERS 167
IV
ABSTRACT
Increasing the level of employee job performance and
job satisfaction is a goal of most organizations. No one
theory or variable has been found to explain job
performance and job satisfaction; however, research
evidence has indicated some correlation between these two
constructs (for example, see Vroom, 1964; Lawler and
Porter, 1967; Ross and Bomeli, 1971; Benke and Rhode,
1980, and Bullen and Flamholtz, 1985).
The importance of maximizing job satisfaction and job
performance among employees within organizations is
continually sought by managers. Maximizing job
satisfaction and job performance may lead to higher
productivity, lower overall costs for the firm, and
reduced turnover of employees.
This study investigated constructs that can affect
job satisfaction and job performance, as well as the
relationship between these two constructs. The research
objectives of this study were to: (1) investigate the
effects of organizational commitment, professional
commitment, life-span career development, and self-
monitoring on job satisfaction and job performance for
staff accountants in public accounting firms; (2)
investigate the relationship between job satisfaction and
job performance of staff accountants in public accounting
firms; and, (3) investigate the relationship among
organizational commitment, professional
commitment, and life-span career development for staff
accountants in public accounting firms.
VI
LIST OF TABLES
2.1 LIFE-SPAN CAREER DEVELOPMENT STAGES AND AGES 28
4.1 SUMMARY OF QUESTIONNAIRE RESPONSE RATES FROM THE PRETEST FOR ALL SUBJECTS 68
5.1 SUMMARY OF QUESTIONNAIRE RESPONSES AND ELIMINATIONS 83
5 . 2 NONRESPONSE BIAS TEST RESULTS 85
5.3 MEASUREMENT STATISTICS FOR THE TWENTY-ONE COMPOSITES 90
5.4 MEASUREMENT STATISTICS FOR THE SIXTEEN COMPOSITES 97
5 . 5 PEARSON CORRELATION COEFFICIENTS 99
5 . 6 POLYSERIAL CORRELATION COEFFICIENTS 100
5.7 PSEUDO TEST STATISTIC FOR THE NULL AND SATURATED MODELS 105
5.8 COMPARISON OF THE NULL -AND SATURATED MODELS 107
5.9 COMPARISON OF THE THEORETICAL AND SATURATED MODELS 110
5.10 COMPARISON OF THE THEORETICAL AND CONSTRAINED MODELS 113
5.11 COMPARISON OF THE THEORETICAL AND UNCONSTRAINED MODELS 115
5.12 GOODNESS-OF-FIT INDICES AND ROOT MEAN SQUARE RESIDUiALS 117
5.13 LISREL VALUES—NONSIGNIFICANT RELATIONSHIPS 119
5 .14 LISREL VALUES—ALL HYPOTHESES 124
C . 1 DEMOGRAPHIC DATA 165
C.2 DESCRIPTIVE STATISTICS 166
Vll
D.l TESTING INDIVIDUAL PHI 168
D.2 TESTING INDIVIDUAL BETAS—WITH PHI 169
D. 3 TESTING INDIVIDUAL GAMMAS—WITH PHI 170
D.4 LISREL VALUES FOR THE HYPOTHESES 171
D.5 LISREL VALUES FOR LAMBDA Y AND LAMBDA X 172
D.6 STANDARDIZED SOLUTIONS 173
Vlll
LIST OF FIGURES
3 .1 Theoretical Model 46
3 . 2 The Research Model For H1-H8 47
3. 3 The Research Model For H9 47
3.4 The Research Model For H10-H12 48
3 . 5 The Research Model For All Hypotheses 55
4.1 LISREL Model 73
4 .2 LISREL Notation And Terminology 75
4 . 3 The Structural Equation 76
4 .4 The Measurement Model For Y Indicants 77
4 .5 The Measurement Model For X Indicants 78
5.1 Respecified Measurement Model For Y Indicants 92
5.2 Respecified Measurement Model For X Indicants 93
5.3 Respecified Measurement Model For Composite Y Indicants 95
5.4 Respecified Measurement Model For Composite X Indicants 96
5 .5 Decision-Tree Framework For SCDTs 108
5.6 Research Model—Results Of Hypothesis Testing.... 126
IX
CHAPTER I
INTRODUCTION AND BACKGROUND
Increasing the level of employee job performance is a
goal of most organizations. No one theory or variable has
been found to explain job performance; however, research
evidence has indicated some correlation between job
performance and job satisfaction (for example, see Vroom,
1964; Lawler and Porter, 1967; Ross and Bomeli, 1971;
Benke and Rhode, 1980, and Bullen and Flamholtz, 1985).
Job satisfaction is a concept that differs across
individuals. Research evidence on job satisfaction can be
divided into categories such as leadership, psychological
needs, effort-reward, management ideology and values, and
job design factors and the content of work. Vroom [1964]
describes job satisfaction as having positive attitudes
towards one's job.
Linking the relationship between job performance and
job satisfaction is difficult because of the numerous
factors that affect the direction and magnitude of the
relationship [Vroom, 1964]. In their study on job
satisfaction and employee turnover, Bullen and Flamholtz
[1985] stated:
Other factors which may affect job satisfaction and turnover that have not been tested by the researchers include performance, ability, personality, and certain other characteristics.
geographical location, and general economic conditions, [p. 289]
A job satisfaction study concluded that job
performance causes job satisfaction [Vroom, 1964, p.
182]. Lawler and Porter [1967] took a position contrary
to Vroom [1964] and hypothesized that job satisfaction
directly affects job performance. In a subsequent study.
Porter and Lawler [1968] then agreed with Vroom [1964]
that job performance causes job satisfaction. Finally,
after offering conflicting theories on the causality
between the two constructs, Lawler [1971] discussed the
difficulty of testing and developing theories of job
satisfaction and job performance.
There have been few studies on the causality between
job satisfaction and job performance among accountants.
Using accountants as subjects for a study on job
satisfaction and job performance, Ross and Bomeli [1971]
stated:
. it is not clear whether high satisfaction with autonomy needs results in high performance and quality or whether high performance and quality result in high satisfaction. [p. 384]
In another study on job satisfaction among accountants,
Benke and Rhode [1980] stated:
. job satisfaction and performance are not necessarily positively related. . . . Consequently, job satisfaction [and] job performance . . . may be interrelated in a complex manner, [pp. 187-88]
While an investigation of causality for the job
satisfaction and job performance question is an important
one, it is an empirically unresolved issue. As a result
of the conflicting evidence the question of causality
between job satisfaction and job performance was not
resolved by this research study. Rather, the relationship
between these two constructs was investigated.
Need for the Study
The importance of maximizing job satisfaction and job
performance among employees within organizations is
continually sought by managers. Maximizing job
satisfaction and job performance may lead to higher
productivity, lower overall costs for the firm, and
reduced turnover of employees. Public accounting firms
experience annual non-partner turnover rates as high as
45%, primarily at the entry-level staff accountant
position [Bao, Bao, and Vasarhelyi, 1986]. Rhode,
Sorensen, and Lawler [1976] reported turnover rates of 85%
for initial hires over a ten year period. Lcimpe and
Earnest [1984] reported an annual turnover rate of 23.9%
for staff accountants who had one to three years'
experience with a firm. Their reported annual turnover
rate was higher than any of the prior five year annual
turnover rates. This indicates that accountants are
leaving firms at earlier stages in their career. The cost
of replacing an entry-level staff accountant has been
estimated at between $10,000 and $15,000 [Bullen and
Flamholtz, 1985]. While attrition may be necessary in the
public accounting profession due to the limited number of
supervisory and managerial positions, early detection of
job dissatisfaction and low levels of job performance,
which can be caused by other factors, can diminish the
premature or unexpected attrition of employees whom the
firm would like to retain. In addition, better
understanding of the relationship between job satisfaction
and job performance may lead to minimizing expenditures to
increase job performance, job satisfaction, and costs
associated with employee turnover.
Purpose of the Study
This purpose of this study was to contribute to the
academic literature in the areas of job satisfaction and
job performance, and provide useful information to
practitioners in public accounting firms. This will be
accomplished by investigating constructs that can affect
job satisfaction [Bullen and Flamholtz, 1985] and job
performance cimong staff accountants in a public accounting
firm. The effects on job satisfaction and job performance
of organizational commitment, professional commitment,
life-span career development, and self-monitoring were
examined. These constructs are discussed in depth in
Chapter II.
The relationships among these constructs are
presented in three research objectives: (1) investigate
the effects of organizational commitment, professional
commitment, life-span career development, and self-
monitoring on job satisfaction and job performance for
staff accountants in public accounting firms; (2)
investigate the relationship between job satisfaction and
job performance of staff accountants in public accounting
firms; and (3) investigate the relationship among
organizational commitment, professional commitment, and
life-span career development for staff accountants in
public accounting firms.
Organization of the Study
This study is further divided into five chapters.
Chapter II is a review of the relevant works for this
study relating to job satisfaction, job performance,
professional and organizational commitment, life-span
career development, and self-monitoring. Chapter III
contains the theoretical model, the research model, and
the development of the hypotheses. In Chapter IV, the
research design, the pretest results of the research
instrument, and statistical tools for this study will be
presented. Chapter V contains the statistical analysis of
this study. In Chapter VI the summary and conclusions are
presented.
CHAPTER II
LITERATURE REVIEW
Much of the research on job satisfaction and job
performance use these constructs as dependent variables
and investigate the impact of numerous independent 1
variables. As for the research evidence, subjects were
chosen typically based on the field or profession under
study. For example, accounting researchers used
accountants, psychologists tended to use students or the
general public, and management researchers used managers
as the subjects for their studies.
Except for self-monitoring, which has been used
primarily in psychological research, the constructs for
this study were selected from existing accounting research
evidence. For example, to determine the effects of
budgetary participation on attitudes and behavior,
Chenhall and Brownell [1988] examined the intervening
effect of role ambiguity on job satisfaction and job
performance. In a study where auditors were the subjects,
Choo [1986] used personality variables to examine their
1 Edwin Locke estimated a conservative figure of 3,350
articles and dissertations on job satisfaction from the period 1957-1972 [Dunnette, 1983]. This indicates the lack of conclusive evidence and continued interest in the area of job satisfaction.
relationship with role stress, and the effect of role
stress on job performance. Rasch and Harrell [1990]
investigated the impact of personal characteristics such
as job satisfaction, on determinants of job turnover.
Ferris [1981] investigated the effect of organizational
commitment on job performance eimong accountants in public
accounting firms. Harrell and Eickhoff [1988] researched
the effect of commitment on the level of job satisfaction
among auditors. The emphasis on accounting related
literature is because the sample under investigation for
this study were staff accountants in a public accounting
firm, and the relationship between this study and prior
research evidence was on constructs that may affect job
satisfaction and job performance.
This literature review is presented in the following
order: (1) job satisfaction and job performance;
(2) professional and organizational commitment, life-span
career development, and self-monitoring; and (3) a
discussion of how new empirical research evidence may
contribute to the accounting body of knowledge and the
accounting profession.
Job Satisfaction and Job Performance
Lawler and Porter [1967] recognized a consistent
relationship between job satisfaction and job performance
This relationship has been explained by the introduction
8
of such variables as intrinsic and extrinsic rewards
[Vroom, 1964], positive and punitive reward behavior [Sims
and Szilagyi, 1975], situational performance constraints
[Phillips and Freedman, 1984], and leadership style and
budgetary participation [Brownell, 1983; Collins, Munter,
and Finn, 1987; Chenhall and Brownell, 1988].
Job Satisfaction in the Accounting Profession
In general, accountants appear to be more satisfied
than other types of employees [Seller and Sapp, 1979]. A
study of job satisfaction among certified public
accountants used the needs hierarchy framework developed
by Maslow [1954] as a test of job satisfaction [Strawser,
Ivancevich, and Lyon, 1969]. The results of the study
were that accountants' needs satisfaction should be
investigated before developing motivational programs.
However, their study utilized a sample of middle- and top-
level accountants in certified public accounting firms.
Therefore, the results may not be considered generalizable
to staff accountants. Ross and Bomeli [1971] gave a
caveat on the Strawser et al. study of the complexities
and ambiguities of the variables job satisfaction and
motivation, which were not covered by Strawser et al. In
a review of previous studies that used Maslow's need
hierarchy, Wahba and Bridwell [1976] found little support
or consistency in the reported results. In fact, some of
the studies rejected Maslow's propositions [Huizinga,
1970; Alderfer, 1972].
Brenner, Carmack, and Weinstein [1971] applied the
Motivation-Hygiene Theory proposed by Herzberg, Mausner,
and Snyderman [1959] to determine which factors influence
job satisfaction among certified public accountants.
Motivation factors (recognition, achievement, work itself,
advancement, and responsibility) affect job satisfaction,
and hygiene factors (salary, company policies, technical
competence, interpersonal relations, and working
conditions) were found to cause job dissatisfaction.
Subjects in the study were randomly selected from the
population of certified public accountants. This
population would include accountants employed in public
accounting firms at different levels in the organization;
thus, the results are not limited only to staff
accountants.
Benke and Rhode [1980] studied personal
characteristics as indicators of job satisfaction. These
personal characteristics were cautiousness, original
thinking, personal relations, vigor, ascendancy,
responsibility, emotional stability, and sociability.
Subjects in the study were at the senior level or higher
in their accounting firms, perhaps providing some
limitation for generalizability to staff accountants.
10
However, their results indicated that personal
characteristics were statistically significant predictors
of job satisfaction for audit and tax specialists in
public accounting firms.
Ferris [1977a] tested perceived environmental
uncertainty and its effect on job satisfaction among staff
accountants (environment is defined as a set of stimuli to
which an organization is exposed and its response). He
hypothesized that environmental uncertainty will inversely
affect job satisfaction. Ferris found that as perceived
environmental uncertainty increased, job satisfaction
decreased.
Jiambalvo and Pratt [1980] hypothesized that the
leader behavior of in-charge auditors can affect the
satisfaction with supervision of their staff assistants.
The considerate style of leadership (mutual trust,
respect, and consideration) had a significant and positive
effect on staff assistants' satisfaction with supervision.
Senatra [1980] investigated the effects of role
conflict and role ambiguity on job satisfaction using
audit seniors in public accounting firms. He hypothesized
that role conflict and role ambiguity are negatively
related to job satisfaction. Senatra reported that only
the relationship between job satisfaction and role
ambiguity were significant and negatively related.
11
Senatra's results conflict with those of other researchers
using the same scale. Teas [1983] and Tracy and Johnson
[1981] reported that role conflict and role ambiguity are
a single measure of stress. Tracy and Johnson noted that
all of the items for role conflict were negatively worded,
while the items for role ambiguity were positively worded,
which may have contributed to the results. If the scales
were unidimensional, all of the items in each scale should
have related similarly to other items not in the scale.
Aranya, Lachman, and Amernic [1982] analyzed the
effects of organizational and professional commitment on
job satisfaction for non-partner chartered accountants.
They reported a statistically significant correlation
between organizational commitment and job satisfaction.
Professional commitment affected job satisfaction
indirectly through organizational commitment.
Harrell, Chewing, and Taylor [1986] examined the
effects of organizational and professional commitment on
job satisfaction. Their model differed from the model
used by Aranya et al. [1982] in that the effects of both
organizational and professional commitment on job
satisfaction were indirect through organizational-
professional conflict. The results of the study were
statistically significant for the multiplicative
interaction of the three variables—organizational
12
commitment, professional commitment, and organizational-
professional conflict.
Harrell and Stahl [1984] utilized McClelland's [1961]
trichotomy of needs theory (need for affiliation, need for
power, need for achievement) to explain job satisfaction
for certified public accountants employed in public
accounting firms. They found statistically significant
positive relationships between job satisfaction, need for
achievement, and need for power among junior-level
accountants in the audit/tax areas, but not among junior-
level accountants in the management consultant area. At
the partner and manager level, the results were also
statistically significant, except for need for achievement
as it related to the number of hours worked per week.
Bullen and Flamholtz [1985] attempted to predict
potential job turnover of non-partners in a certified
public accounting firm. They measured the level of job
satisfaction among non-partners, and then predicted
potential turnover based on the level of job satisfaction.
Bullen and Flamholtz reported statistically significant
results for predicting the probability of turnover based
on the level of job satisfaction. In their research
model, Bullen and Flamholtz theorized that personal and
psychological factors may affect job satisfaction.
However, they did not test these factors.
13
Reed and Kratchman [1987] reported that job
satisfaction was related to job attributes that fulfilled
individual needs, and one of the most important needs,
^^^^-f^lfillinent, can be satisfied through an accounting
position because the position allows for self-expression.
This may suggest a statistically significant correlation
between the constructs life-span career development and
job satisfaction.
While there have been studies on job satisfaction
using public accountants as subjects, these studies are
not all applicable to staff accountants, nor were all the
individual characteristics that can affect job
satisfaction considered. These limitations in empirical
accounting research can be attributed to the all-
encompassing nature of job satisfaction with many
variables, and the different levels and types of
accountants. The results of these empirical studies do
not necessarily conflict, but differ due to the employee
level of the subjects used in the studies (e.g., junior-
level accountants versus managers/partners), and the
variables employed to explain job satisfaction.
Job Performance in the Accounting Profession
Early studies on job performance by accounting
researchers were primarily laboratory experiments. Cook
[1967] found the frequency of feedback (communication)
14
affected the performance of students. Sorensen and Franks
[1972] used student subjects to correlate psychological
factors to performance. They tested personal
characteristics, ability and self-esteem, and how these
characteristics contributed to performance. They found
increasing self-esteem through supportive feedback could
lead to better performance. Decreasing self-esteem, which
occurred when neutral feedback was given, was found to
result in decreased performance.
Studies conducted after the laboratory experiments on
job performance among accountants were quasi-experimental.
Todd, Thompson, and Dalton [1974] reported that a strong
relationship between performance and rewards is necessary
to manage accountants effectively. However, Todd et al.
[1974] did not investigate which performance evaluation
dimensions that are considered important to supervisors
and subordinates.
Ramanathan, Peterson, and Maher [1976] reported that
better communication between supervisors and subordinates
is needed on job performance criteria. Juniors/seniors,
managers/supervisors, and managing partners had different
perceptions of the relative importance of the criteria
used to evaluate performance. Jiambalvo [1982] researched
audit seniors' (subordinates) perceptions of the
importance of performance evaluation dimensions with audit
15
partners' (supervisors) ratings of the importance of these
same dimensions. He reported that there was a difference
in what the subordinates and the supervisors considered
important. Audit seniors "overestimated" the importance
of working with the client's personnel, demonstrating an
area of special competence, and obtaining the respect and
cooperation of the client's personnel. Audit seniors
"underestimated" the importance of revising audit programs
and reviewing the work of the assistants on the audit.
Jiambalvo, Watson, and Baumler [1983] attempted to
determine what comprises a good evaluation of job
performance in a certified public accounting firm. Using
accountants who worked in the audit, tax, and management
services departments as subjects, Jiambalvo et al.
reported significant individual differences in the
contents of a good evaluation of job performance. These
differences were attributed to the subjects' placing too
much importance on evaluation categories that were not
considered important by their supervisors, and too little
importance on areas considered important by their
supervisors. They also reported that there were
differences in performance evaluation decision making
among the audit, tax, and management service areas of the
firm. Even though these studies indicated that
performance evaluations are an important factor in an
16
accountant's behavior, Wright [1980] reported, on average,
only five hours were used to train seniors on job
performance evaluations of subordinates.
In another study, Wright [1982] reported that
technical ability was a primary focus for appraising staff
personnel's job performance. One reason could be the
difficulty in evaluating other factors that are important
in job performance. Arrington, Bailey, and Hopwood [1985]
reported that audit behavior, audit procedures, and audit
tasks were used as judgment factors for evaluating
performance. These studies indicated that there are
differences in the perceived importance of criteria used
in performance evaluations between subordinates and
supervisors, and between areas in public accounting firms.
Ferris [1982] reported that the accounting
organization's ability to adapt to the outside environment
(environment is defined as a set of stimuli to which an
organization is exposed and its response) was directly
related to employee job performance. As the level of
coping with the outside environment increased for the
organization, employee job performance also increased.
However, Ferris used employee performance as a surrogate
measure for the coping effort. He commented that there
could be a potential problem using job performance as a
surrogate measure for the coping effort. This potential
17
problem is because of the effects of other variables that
can affect employees performance not included in the
study, but not the coping effort.
Chow [1983] explored the effects of job standard
tightness and the type of compensation scheme on job
performance. He hypothesized that job performance will be
directly and interactively affected by the compensation
scheme and job standard tightness. There were
statistically significant results for the direct effects
of compensation schemes and job standards tightness on job
performance, in groups where subjects were assigned to
compensation schemes. There were no significant
interactive effects of compensation scheme and job
standard tightness on job performance. Job performance
was enhanced when subjects chose their own compensation
schemes. Chow felt that the results indicated that job
standards and compensation schemes may play significant
screening and motivational roles.
Ferris and Larcker [1983] reported that rated
performance was a function of motivation and
organizational commitment, while rewarded performance
(compensation) was a function of both the interpersonal
attraction between the auditor and his/her supervisor, and
the task-related ability of the individual. This is an
important study because it distinguished between some
18
variables that can affect rated job performance and
rewarded job performance. Rewarded job performance can be
biased based on the interpersonal attraction between the
auditor and supervisor.
A primary difference between the Chow [1983] study
and the Ferris and Larcker [1983] study was the way
compensation schemes were distributed and the experimental
design of the studies. The Chow study was a laboratory
study in which subjects had their choice of compensation
schemes, and these schemes were not based on a
supervisor's recommendation. Ferris and Larcker used a
public accounting firm in which compensation was assigned
based on a number of different factors, one of the primary
factors being a supervisor's recommendation.
There have been studies directly relating the level
of job performance among staff accountants to other
variables. Ferris [1977b] applied expectancy theory to
staff accountants in two public accounting firms and
reported results that showed expectancy theory to be a
poor predictor of job performance. Ferris [1981] studied
the effects of organizational commitment on job
performance. This relationship was hypothesized to be
moderated by an individual's task-related ability, which
is consistent with prior Expectancy Theory research
[Lawler, 1966]. Subjects were junior-level and senior-
19
level auditors who were employed for at least one year by
a large public accounting firm. Ferris reported that
there was no statistically significant relationship for
the moderating effect of task-related ability. Ferris
attributed this result to the limitations in the
measurement of task-related ability. However, junior-
level auditors' performance was influenced by a
willingness to exert effort on behalf of the organization
(organizational commitment).
Jiambalvo [1979] departed from the traditional
expectancy model to investigate performance evaluation and
job effort cimong auditors. He departed from the
traditional expectancy model by dividing it into two
components, and adding sequential steps in the first
component. The first component was the linkage between
efforts and rewards in a sequential evaluation context.
The sequential steps were effort, performance, evaluated
performance, overall evaluation, and rewards. By adding
the three intermediate steps between effort and reward,
Jiambalvo wanted to identify where the effort—>reward
process may break down. The second component was the
decomposition of job effort into performance evaluation
dimensions. Using the sequential evaluation steps,
Jiambalvo reported a large difference between self- and
manager-rated performance. He stated this was
20
"unanticipated theoretically, but is a typical finding in
expectancy studies" (p. 449). Jiambalvo reported that
senior auditors directed their job effort on activities
that were used to evaluate their performance.
Choo [1986] researched the relationship between job
performance and stress among practicing chartered
accountants. Choo found the relationship between job
performance and job stress to be an inverted U-shaped
function. As job stress increased, so did job
performance, to a maximum point; after that point, job
performance decreased as job stress increased.
Like job satisfaction, job performance is an area in
which there have not been many empirical studies that used
staff accountants as subjects. However, there has been a
recent trend to use non-technical individualistic factors
in studies concerning accountants' job performance (for
example, Ferris [1982]; Ferris and Larcker, [1983]; Choo
[1986]; Rasch and Harrell [1990]). This trend indicates a
continued interest in job performance research.
Organizational and Professional Commitment> Life-Span Career Development,
and Self-Monitoring
Organizational and Professional Commitment in the Accounting Profession
Public accounting was accepted as a profession in
1890, when certification of accountants began [Freidson,
21
1973]. The label "professional" has implications for an
individual at the organizational and occupational level.
A level of behavior is expected by the organization
employing the professional, as well as by the external
peer group that makes up the profession [Harrell, Chewing,
and Taylor, 1986]. The extent to which individuals behave
in the expected manner can be reflected in their
commitment to the organization and profession. Commitment
can be defined as: (1) a belief in and acceptance of the
goals and values of the organization and/or profession;
(2) a willingness to exert considerable effort on behalf
of the organization and/or profession; and (3) a desire to
maintain membership in the organization and/or profession
[Aranya, Pollock, and Amernic, 1981a]. The following
studies had results that showed significant relationships
among the variables organizational commitment and
professional commitment, with job satisfaction, job
performance, and career intentions.
Aranya et al. [1981a] reported organizational and
professional commitment to be compatible due to the
positive relationship between the two variables. They
modeled organizational commitment as an independent
variable used to predict professional commitment in
chartered accountants employed at public accounting firms
in Canada. At the level of partner, organizational
22
commitment was reported to be greater than professional
commitment. At firm levels below partner, Aranya et al.
reported that there is lower organizational commitment
than professional commitment. This may indicate that
staff accountants have yet to reach the stage in their
career development to commit to an organization as a
longtime employee, but are committed to a career in public
accounting. Aranya, Lachman, and Amernic [1982] used
professional and organizational commitment as predictors
of job satisfaction. One of the differences between the
Aranya et al. [1982] study and the Aranya et al. [1981a]
study, was the reversal of organizational commitment from
an independent to a dependent variable, and professional
commitment from a dependent to an independent variable.
The results in that study were that professional
commitment precedes organizational commitment, and both
exhibit significant influences on job satisfaction.
Lachman and Aranya [1986] provide further empirical
support that professional commitment precedes
organizational commitment, and that the two constructs are
positively correlated, as previously reported by Aranya et
al. [1982],
Norris and Niebuhr [1983] also supported the
conclusions of Aranya et al. [1981a and 1982], that
organizational and professional commitment are correlated.
23
and that there are statistically significant correlations
between job satisfaction and both professional and
organizational commitment. They reported organizational
commitment to be greatest at the partner level, and
professional commitment to be greater than organizational
commitment at most levels below partner. However, Norris
and Niebuhr used subjects at all levels of different
public accounting firms. Their results merged the
different levels and firms, which makes generalizing the
results to only staff accountants difficult.
Harrell et al. [1986], using internal auditors in
their sample, reported that organizational commitment
positively affects job satisfaction. For individuals who
were members of the Institute of Internal Auditors, a
professional organization, professional commitment was
more positive than for internal auditors who were not
members. As with the Norris and Niebuhr [1983] study, the
generalizability of the results reported by Harrell et al.
is limited because the sample consisted solely of internal
auditors, and not staff accountants in public accounting
firms.
Harrell and Eickhoff [1988] reported higher levels of
organizational commitment and job satisfaction among
auditors who were influence-oriented, or attracted to
working in a competitive environment in which leadership
24
status can be achieved, than those who were not influence-
oriented. They concluded that the auditors who were
influence-oriented had more positive "Big Eight" career
intentions than the auditors who were not influence-
oriented.
Ferris [1981] reported that at junior-level positions
(e.g., staff accountants), organizational commitment
influenced job performance by the individual's willingness
to exert effort on behalf of the organization—that is, to
perform well on the job. At both the senior and junior
staff accountant levels, organizational commitment is
positively related to job performance. For employees
beyond the level of staff accountant, high levels of
organizational commitment were due to a desire to remain
with the firm. Ferris states that these differences are
because of the nature of organizational commitment, which
changes over time. Hence, as an individual becomes more
positively entrenched in his or her career development,
the level of organizational commitment should increase.
Aranya and Ferris [1984] reported that certified public
accountants employed by public accounting firms had higher
levels of organizational and professional commitment,
compared to public accountants working in nonprofessional
organizations. As with the Ferris [1981] study, Aranya
and Ferris reported lower levels of organizational and
25
professional commitment at the staff accountant level than
at the manager and partner levels.
The results of these studies provide an indication
that a relationship exists among the variables job
performance, job satisfaction, career development,
organizational commitment, and professional commitment.
Professional commitment precedes organizational commitment
in an individual's career [Aranya, Lachman, and Amernic,
1982; Lachman and Aranya, 1986], organizational commitment
is an indicator of career intentions [Harrell and
Eickhoff, 1988], and organizational commitment and
professional commitment can affect the level of job
satisfaction [Sorensen and Sorensen, 1974; Aranya,
Lachman, and Amernic, 1982; Harrell and Eickhoff, 1988]
and job performance [Ferris, 1981].
Life-span Career Development
Life-span career development is a concept that
considers an individual's career objectives to be an
ongoing process. As congruence grows between individuals
and their work environment, there is greater satisfaction
on the job and with the chosen career. Super [1963] has
identified attitudes and behaviors that comprise five
stages of vocational development. These five stages are
crystallization, specification, implementation,
stabilization, and status and advancement.
26
Crystallization is the stage in which an individual
formulates thoughts about the type of suitable work for
himself/herself. This stage will usually occur between
the ages of fourteen to eighteen. The second stage is
the specification of a career. This stage requires an
individual to make a specific choice of a career and take
the steps necessary to implement the choice.
Specification will usually occur between the ages of
eighteen to twenty-one. The third stage, implementation,
will usually occur between the ages of twenty-one to
twenty-five. It is during this time that an individual
will enter employment based on the career choice and
complete some training in his/her chosen career. The
fourth stage is stabilization. This stage will usually
occur between the ages of twenty-five to thirty-five. An
individual will settle down within the field of work
he/she has chosen. The last stage is status and
advancement. This will usually occur between the late
thirties to the mid-forties. During this stage, an
individual will attempt to achieve a comfortable and
secure position in the field of work he/she has chosen.
The rate and level of an individual's development in
his/her career is known as vocational maturity. Table 2.1
summarizes these stages.
27
TABLE 2.1 LIFE-SPAN CAREER DEVELOPMENT STAGES AND AGES
Vocational Development Stages Ages
Crystallization 14-18
Specification 18-21
Implementation 21-25
Stabilization 25-35
Status & Advancement 35-49
The age levels for these different stages were
questioned by Super [1981] after further research on
vocational development. He believed that vocational
maturity is not necessarily something that will increase
with age, because of two factors. The first factor is the
changing labor market. The advances in technology make
for uncertain jobs and professions in the future. While
technology has changed the way accountants perform their
jobs (for example, paperless audits), it does not seem
likely that technology will make accounting, an uncertain
profession. Second, there is a lack of empirical evidence
that shows an increasing ability to cope with career
developmental tasks as age increases.
Life-span career development is not specifically
referred to in the accounting literature. However,
researchers in psychology have studied the effects
of career development on job satisfaction and found that
28
vocational maturity generally predicts occupational
satisfaction [Osipow, 1983]. Studies on careers using
accountants as subjects have focused on career intentions
rather than the stage or level of life-span career
development.
Sorensen [1970] hypothesized that there was conflict
between the educational subculture of an accounting
graduate and the professional subculture of the graduate.
Without an understanding of the differences, the graduates
have less chance of fulfilling their career objectives.
This conflict is particularly applicable to staff
accountants, especially those who enter public accounting
upon graduation. This conflict occurs in what would be
considered the implementation stage of vocational
development.
Lengermann [1971] studied professional autonomy among
accountants. Professional autonomy is the freedom allowed
professionals to do their work in the manner they feel is
best, according to the accepted standards of their
profession. Lengermann [1971] reported that professional
autonomy was a positive resource, especially among lower-
level certified public accountants, such as staff
accountants in public accounting firms.
DeCoster and Rhode [1972] reported that younger
accountants were less conservative, more aggressive, and
29
less conforming than older accountants. The variation in
these traits over time could be attributable to Super's
stages of vocational development. Using Holland's [1973]
theory of vocational choice, Aranya, Barak, and Amernic
[1981b] reported accountants to be conventional,
enterprising, and social. Mossholder, Bedeian, Touliatos,
and Barlonan [1985] reported that accountants are
distinguishable in terms of personality, outcome
preferences, and perceived work climate. Zytowski and Hay
[1984] were hesitant to generalize about similarities
found within occupations, including accountants, because
they found differences cimong members of the same
occupation. One of the sources of these differences is
the stage of vocational development.
Lawler, Kuleck, Rhode, and Sorensen [1975] studied
job choice and post-decision dissonance among college
graduates. The study reported negative attitudes that
recent graduates had towards the firms during the initial
employment period. The attractiveness in working at any
public accounting firm decreased after about one year.
There are many reasons for these results, two of which
could be dissatisfaction with the organization or
profession. This would occur during the implementation
stage of vocational development.
30
Dillard [1979] used the variables goal and expectancy
to investigate the occupation-position choice decision
among public accountants. Occupation and position choices
are derived from an individual comparing alternative
occupations and positions to his/her current work
environment. These comparisons lead to an individual
determining his/her goals, and ultimately behavior.
Expectancy is the subjective probability that an
individual could attain the occupation-position he/she
desires. Expectancy is multiplied by the utility an
individual believes the occupation-position will provide,
which gives the expected utility position. Dillard
reported that individuals' occupation-position goals are
significantly related to the position with the highest
expected utility. Individuals will attempt to achieve the
occupation-position that will give them the highest
utility, based on the probability of achieving the
occupation-position.
Reed and Kratchman [1987] reported that job
satisfaction was related to the attributes of the job that
fulfilled individual needs. They further stated that one
of the most important needs, self-fulfillment, can be
satisfied through an accounting position because the
position allows for self-expression. Harrell and Eickhoff
[1988] reported that influence-oriented auditors have more
31
positive feelings toward "Big Eight" career intentions
than other auditors.
There is evidence in the psychological literature
that indicates a correlation between career stage and job
satisfaction [Osipow, 1983]. However, the accounting
literature is lacking empirical research on the stages of
career development and its effect on job satisfaction and
job performance. The first career stage in which job
satisfaction or job dissatisfaction should appear is
during the implementation stage. It is during this stage
that individuals will usually first encounter the work
place that was their career choice.
Self-Monitoring
Self-monitoring is the process by which individuals
observe and control how others perceive them. This is
done by attempting to create images that seem appropriate
for a given set of circumstances [Snyder, 1979]. Self-
monitoring is divided into two conditions, high and low.
A high self-monitor attempts to determine what type of
characteristics a situation calls for, adopts those
characteristics, and then acts accordingly. Low self-
monitors do not attempt to change their characteristics to
adapt to a situation, but act in a manner in which they
are most comfortable. Researchers have shown through
empirical studies that self-monitoring is a good
32
explanatory variable of attitudes and behavior in
different situations.
Because self-monitoring has been shown to explain
attitudes and behavior in different situations, it is a
variable of interest because of the nature of a staff
accountant's work. Staff accountants freguently change
job locations and job supervisors. Their perceived
ability to adapt may influence their level of job
satisfaction. Staff accountants' feelings that they are
adapting sufficiently may lead to greater levels of job
satisfaction. Self-monitoring may also affect perceived
job performance in the same manner as job satisfaction.
Self-monitoring is a behavioral concept that has been
investigated extensively in psychology (e.g., see Snyder
1974, 1979, 1983; Snyder, Berscheid, and Click, 1985;
Snyder and Cantor, 1980; Snyder and Gangestad, 1982;
Snyder, Gangestad, and Simpson, 1983; Snyder and Monson,
1975; Snyder and Simpson, 1984; Snyder and Swann, 1976;
Snyder and Tanke, 1976; Snyder, Tanke, and Berscheid,
1977; Ajzen, Timko, and White, 1982; Briggs, Cheek, and
Buss, 1980). A thorough review of the accounting
literature did not reveal any references to this concept;
therefore, the following literature review on self-
monitoring presents the results from selected
psychological studies.
33
A study of attitude and behavior using self-
monitoring was done by Snyder and Swann [1976]. They
tested whether individuals' behaviors were indicative of
their attitude after they were given an opportunity to
express their opinion on a social issue. There was a
higher covariance between low self-monitors and their
attitude and behavior than high self-monitors.
Snyder and Tanke [1976] further tested consistency
between attitude and behavior among low and high self-
monitors using essay writing. In the first phase of the
study, subjects wrote counterattitudinal essays under two
conditions, choice and no choice. As compared to high
self-monitors, low self-monitors who chose to write
counterattitudinal essays had final attitudes that were
more like their behavior. In the next phase of the study,
subjects were given more choice in their topic so there
would be a wider range of proattitudinal and
counterattitudinal essays. By allowing subjects the
choice of writing counterattitudinal essays, Snyder and
Tanke hypothesized that low self-monitors would be more
likely to change their attitudes than high self-monitors.
Nonparametric tests were used to determine the proportion
of individuals who changed their attitude. Approximately
eighty-three percent of low self-monitors showed a change
in their initial and final attitudes, while only forty-
34
five percent of high self-monitors showed an attitude
change. The results were possibly due to high self-
monitors attributing their essays to the experiment
(situation). Low self-monitors would attribute their
responses to their character (disposition).
Snyder [1983] researched situational and
dispositional individuals and social behavior. Low self-
monitors are likely to be less responsive to situations,
while high self-monitors are likely to be more responsive.
Low self-monitors are characterized by attitude-behavior
consistencies, and seek out situations that will conform
with their current behavior.
Ajzen et al. [1982] also tested differences in
attitudes and behaviors between low and high self-
monitors. One of the results of their experiment showed a
difference in intention-behavior between the two groups.
As compared to that of high self-monitors, the behavior of
low self-monitors was more accurately predicted based on
their intentions. One reason suggested for this finding
is that low self-monitors are not as affected by external
events; therefore, they are more stable and more
predictable.
Kulik and Taylor [1981] investigated how high and low
self-monitors use desirable and undesirable consensus
information to make predictions about their own and
35
others' behavior. Overall, high self-monitors used
consensus information more than low self-monitors.
However, this was significant only for undesirable
information. Rather than use consensus information, low
self-monitors will consider their own opinions to predict
behavior.
Snyder and Gangestad [1982] tested the attitude of
high and low self-monitors who were entering different
social situations. The first phase of their study gave
individuals, both low and high self-monitors, the choice
to enter a situation that required being sociable. In
some cases the type of sociability was prescribed; in
other cases it was not prescribed. It was expected that
high self-monitors would be more willing to enter the
well-defined situation than the less defined situation.
Snyder and Gangestad also expected low self-monitors to
base their decision on their introverted or extraverted
characteristics, not the amount of information given about
the social situation. The evidence supported expectations
regarding high self-monitors. They reported that both
extraverted and introverted high self-monitors were
willing to spend time in the social situations. Neither
extraverted not introverted low self-monitors as a group
were inclined to spend time in the social situations. Of
those individuals who were willing, extraverts were more
36
willing than introverts to spend time in social
situations.
The second phase of their study asked high and low
self-monitors how a situation should be changed so they
would participate in it. High self-monitors more clearly
defined the situation they would be willing to enter than
low self-monitors. Low self-monitors defined the
situation in terms of their introverted and extraverted
characteristics. Snyder and Gangestad concluded that
social behavior can also be a function of the " . . .
processes by which the individual finds himself or herself
in that situation" (p. 134). Snyder [1983] discussed this
in more detail. He felt the situation appeared to
influence the individual, but the more important influence
is the activity of the individual.
In another study, low self-monitors were more
committed in dating relationships than high self-monitors
[Snyder and Simpson, 1984]. Low self-monitors were more
reluctant to change partners, they dated fewer individuals
in the same period of time than high self-monitors, and
the length of and intimacy in a relationship was greater
among low self-monitors. The results were shown to have
two potentially significant implications. First, low
self-monitoring individuals find romantic relationships to
be an important part of what makes their lives meaningful.
37
Second, the results can help one understand other
relationships that go beyond dating, such as marriage.
Snyder and Cantor [1980] tested self-monitoring and
social knowledge. Theoretically, low self-monitors should
be knowledgeable about their own traits, while high self-
monitors would be knowledgeable about the traits of
prototypical individuals. The experiment supported the
theory. Low self-monitors were able to give more
information about their own traits, while high self-
monitors provided more information about the traits of
others. The result suggests that when a certain social
behavior is called for, low self-monitors have more
ability to look to themselves for guidance on how to act.
High self-monitors would consider the person (real or
imagined) whose behavior is appropriate for the situation
as the proper model for their own behavior.
Self-monitoring has been found to be a significant
factor during initial interactions between individuals.
During initial interaction, conversation tends to be
highly structured [Douglas, 1983]. Douglas tested high
and low self-monitors' responses to interaction in an
initial encounter between a male and a female. The
encounters could be typical—a normal conversation—or
atypical, where the individuals were abrasive and previous
mental problems were revealed. High self-monitors
38
generated more responses to the typical conversation than
the atypical conversation. Individuals categorized as
high self-monitors also generated more responses than low
self-monitors who viewed the typical initial encounter.
Low self-monitors' responses to the typical and atypical
conversations were about the same. Overall, responses to
the atypical conversation were similar between the low and
high self-monitors.
Douglas [1983] believed that high self-monitors may
not process more information, but use more information
than low self-monitors. This could lead to friendlier
interaction by high self-monitors than low self-monitors.
To test this hypothesis, he had independent judges rate
the replies of the subjects. High self-monitors were
found to be more likely to have friendly interactions than
low self-monitors. He continued his research in initial
interaction by testing whether cognitive differences are
associated with behavioral differences at different levels
of self-monitoring. Summaries of high self-monitors'
conversations and behavior were different than those of
low self-monitors. High self-monitors tended to view
their conversation as strategic, whereas low self-monitors
saw their conversations as a way of achieving interaction
objectives.
39
Snyder et al. [1985] investigated how the selection
process of one type of initial interaction, dating,
differed between low and high self-monitors. They
hypothesized there would be different approaches between
low and high self-monitors in choosing a dating partner.
Males were given portfolios containing a picture and
information about females they could choose for a date.
The males' process for choosing a partner was studied and
compared to their level of self-monitoring. As
hypothesized, low self-monitors spent more time looking at
the information about the attributes of the female rather
than the pictures. High self-monitors spent more time
looking at the photographs rather than the information.
This could be because the high self-monitors believe that
this was what was expected of them, and then conform their
behavior accordingly. Seventy-five percent of low self-
monitors reported that interior attribution information
was the most important reason for choosing a partner.
Seventy-seven percent of high self-monitors reported the
pictures were the most important factor in making their
selection. Overall, low self-monitors spent more time in
the selection process than high self-monitors, though both
groups looked at about the same number of files.
The results of the Douglas [1983] and Snyder et al.
[1985] studies appear to be contradictory. In the Douglas
40
study, high self-monitors used more information, while in
the Snyder et al. study low self-monitors spent more time
looking at information. However, in the Douglas study an
actual oral exchange of information took place, whereas
the Snyder et al. study had subjects only look at
information.
Interpersonal skills needed to initiate and preserve
a relationship can be discussed in terms of humor
production [Turner, 1980]. High self-monitors produced
more humorous material in terms of both quantity and
quality. This was measured by writing cartoon captions
and group discussions. When a situation calls for a
humorous remark, as can be required when initiating or
maintaining a relationship, the high self-monitor is
better prepared to deliver the remark.
Ickes and Barnes [1977] tested behavior during
initial interactions in same-sex dyadic combinations of
three levels of self-monitoring—low, medium, and high.
The results of any pair who had previously met were
excluded from the data to ensure only initial interactions
were being tested. In both male and female pairs in which
talking occurred, the high self-monitor initiated the
conversation significantly more often than the low self-
monitor. During the initial interaction, dyads in which
low and high self-monitors were paired showed more periods
41
of silence than any other combination of self-monitors.
Female dyads showed more expressive behavior during the
initial interaction than male dyads. Expressive behavior
was measured by gazes, verbalization, and expressive
gestures. Ickes and Barnes felt dyads of high and low
self-monitors had more interaction difficulties than other
pairs. Their results supported the construct of self-
monitoring being concerned with appropriate behavior in
social interaction.
Researchers have shown through empirical studies that
self-monitoring is a good explanatory variable of
attitudes and behavior in different situations. Results
of empirical studies using self-monitoring as a variable
have been supported by the theory of self-monitoring.
However, there has not been published empirical research
using self-monitoring as an explanatory variable for an
individual's satisfaction and performance at work.
Chapter Summary
The large amount of literature on job satisfaction
and job performance shows a continuing interest and a need
for understanding these two constructs (see Footnote 1,
Chapter II). Accounting literature on job satisfaction
and job performance is not as prevalent nor is it focused
on specific accounting occupations or positions in public
accounting firms, as evidenced by this literature review.
42
However, there have been some studies published recently
in the accounting literature on job satisfaction and job
performance [for example, Bullen and Flamholtz, 1985;
Kida, 1985; Arrington et al., 1985; Ferris and Larcker,
1983; Harrell et al., 1986; Choo, 1986; Reed and
Kratchman, 1987].
A research trend in the areas of job satisfaction and
job performance among accountants is to investigate the
effects of personality variables. In their study on job
satisfaction, Bullen and Flamholtz [1985] identified a
large number of factors, including personality variables,
that can be used to study job satisfaction. Choo [1986]
stated that previous studies on auditors tended to focus
on variables other than personality variables that could
be significant in understanding behavior. Rasch and
Harrell [1990] investigated the impact of several personal
characteristics of accounting professionals on
determinants of personnel turnover, including job
satisfaction.
An interesting area for research in accounting is to
study the effects of personality variables on job
satisfaction and job performance among staff accountants.
Chapter III contains the theoretical and research models,
and the hypotheses and justification for testing
43
personality variables that may affect the level of job
satisfaction and job performance among staff accountants
44
CHAPTER III
THE THEORETICAL MODEL, RESEARCH MODEL,
AND FORMULATION OF HYPOTHESES
The Theoretical Model
Gruneberg [1976] broadly categorized job satisfaction
to be associated with the job itself, environmental
factors, and individual factors. Landy, Zedeck, and
Cleveland [1983] used organizational considerations,
individual considerations, and sociopolitical
considerations as the primary factors affecting job
performance. Different theories behind the relationship
between job satisfaction and job performance have been
well-documented (for example, Vroom, 1964; Lawler and
Porter, 1967; Porter and Lawler, 1968; Lawler 1971; Ross
and Bomeli, 1971; Benke and Rhode, 1980; Harrell and
Stahl, 1984; Bullen and Flamholtz, 1985). There is no one
theory to explain this relationship because of the large
number of variables that affect job satisfaction and job
performance.
Vroom [1964] discussed the difficulty of describing
the relationship between job performance and job
satisfaction because of the numerous factors that affect
the direction and magnitude of the relationship. In this
study, the factors of interest are the constructs
45
organizational commitment, professional commitment, life
span career development, and self-monitoring.
The model developed by Bullen and Flamholtz [1985]
shows the complexity of attempting to explain the causes
of job satisfaction because of the numerous variables
affecting this construct. Figure 3.1 is a portion of the
theoretical model developed by Bullen and Flamholtz.
Overall Assessment of
Job Satisfaction /
\
\
/
Area Level
Career Goals Demographic s Other Factors
Figure 3.1. The Theoretical Model
"Other Factors" include performance, personality, and
certain other personal characteristics [Bullen and
Flamholtz, 1985]. Investigating the interrelationships
among the constructs is the primary purpose of this study.
The Research Model
Researchers have theorized and empirically tested the
relationship among job satisfaction, job performance, and
other variables [for example, Bagozzi, 1980a]. The
research model used in this study was adapted from the
Bagozzi [1980a] research model, and based on the theory
proposed by Bullen and Flamholtz [1985]. The first
46
research objective of this study was to investigate the
hypothesized (H) effects of organizational commitment,
professional commitment, life-span career development, and
self-monitoring on job satisfaction and job performance
for staff accountants in public accounting firms. Figure
3.2 is the research model for these relationships.
Professional Commitment Organizational Commitment Life-Span Career Development
Self-Monitoring
Job Satisfaction
Job Performance
Figure 3.2. The Research Model for H1-H8
The second research objective was to investigate the
relationship between job satisfaction and job performance
of staff accountants in public accounting firms. This
relationship is illustrated in Figure 3.3.
Figure 3.3. The Research Model for H9
47
Research objective three was to investigate the
hypothesized relationship among organizational commitment,
professional commitment, and life-span career development
for staff accountants in public accounting firms. These
relationships are illustrated in Figure 3.4.
Professional Commitment
/
\
\
/
Life-Span Career
Development
\ /
\ /
Organizational Commitment
Figure 3.4. The Research Model for H10-H12
Formulation of the Hypotheses
The research objectives stated in Chapter I were to:
(1) investigate the effects of organizational commitment,
professional commitment, life-span career development, and
self-monitoring on job satisfaction and job performance
for staff accountants in public accounting firms; (2)
investigate the relationship between job satisfaction and
job performance of staff accountants in public accounting
firms; and (3) investigate the relationship among
organizational commitment, professional commitment, and
48
life-span career development for staff accountants in
public accounting firms.
The hypotheses for the first research objective are
predicated on the basic theory that there are many
variables such as personality and certain other personal
characteristics that can affect job satisfaction and job
performance. The first four hypotheses are based on the
effects of organizational commitment and professional
commitment on job satisfaction and job performance.
Models illustrating commitment have antecedents that
precede commitment, and job-related outcomes resulting
from the level of commitment individuals possess [Hunt,
Chonko, and Wood, 1985]. These job-related outcomes
include performance and satisfaction [Hunt, Chonko, and
Wood, 1985]. Ferris [1981] hypothesized that
organizational commitment preceded job performance among
auditors. He reported that junior-level auditors'
performance was influenced by a willingness to exert
effort on behalf of the organization. Few empirical
accounting studies have examined the effects of both
organizational and professional commitment on job
satisfaction. Norris and Niebuhr [1983] reported that
organizational and professional commitment were strongly
related to job satisfaction for individuals employed in
public accounting firms. However, the results reported by
49
Norris and Niebuhr [1983] were for all levels of employees
in all functional areas of the firm. The hypotheses, in
alternate form, for the relationship between
organizational and professional commitment with job
satisfaction and job performance are:
HI: Job satisfaction and organizational commitment will be positively related for a staff accountant.
H2: Job performance and organizational commitment will be positively related for a staff accountant.
H3: Job satisfaction and professional commitment will be positively related for a staff accountant.
H4: Job performance and professional commitment will be positively related for a staff accountant.
Super [1981] stated that there is a lack of empirical
studies on vocational maturity in adulthood. To
investigate vocational maturity in adulthood, these
hypotheses are based on the effects of life-span career
development on job satisfaction and job performance. The
rate and level of an individual's development in his/her
career—vocational maturity—has an effect on satisfaction
[Osipow, 1983]. The relationship between job performance
and life-span career development was proposed by Super
[1957] when he stated that,
. the learning of job or position performance is necessarily much more specific than in the learning of occupational performance (and) virtually all workers have some problems of induction and
50
transition when they begin a new job, and in the inexperienced worker these are often of some significance, [p. 119]
The implementation stage of life-span career
development was investigated. Theoretically, the
implementation stage will occur between the ages of
twenty-one to twenty-five. This is the usual age in which
an individual will enter the accounting profession as a
staff accountant, and go through the induction and
transition processes. Super [1957] theorized a
relationship between life-span career development and both
job satisfaction and job performance during the
implementation stage when he stated that
. [recent college graduates] change in search of something more satisfying to themselves [job satisfaction] and in which they are more satisfactory to employers [job performance], [p. 129]
The hypothesized relationships, in alternate form, among
life-span career development, job satisfaction, and job
performance are:
H5: A positive relation exists between job satisfaction and the level of the implementation stage in a staff accountant's life-span career development.
H6: A positive relation exists between job performance and the level of the implementation stage in a staff accountant's life-span career development.
Hypotheses seven and eight are based on the
relationship between job satisfaction and self-monitoring.
51
and job performance and self-monitoring. Self-monitoring
is used in psychology to explain different attitudes and
behaviors involving interactions.
Because of staff accountants' numerous interactions
with others, self-monitoring should be a construct for
inclusion in this study on job satisfaction and job
performance. If staff accountants who are low self-
monitors do not feel that they fit in a continually
changing work environment, they may be less satisfied with
their job. Their perceived level of job performance can
also be lessened by their perceived lack of adaptability.
Douglas [1983] reported that high self-monitors view
conversations (interactions) as being strategic. Staff
accountants who are high self-monitors should be more
strategic and adaptable than low self-monitors, which can
lead to greater levels of job satisfaction and higher
perceived job performance. Ferris [1982] reported that an
accounting organization's ability to adapt to the outside
environment was directly related to employee job
performance. The ability of staff accountants to adapt to
their environment may also affect their level of job
performance and job satisfaction. Hypotheses seven and
eight are presented below in alternate form.
H7: A positive relation exists between the level of self-monitoring and job satisfaction for a staff accountant.
52
H8: A positive relation exists between the level of self-monitoring and job performance for a staff accountant.
The results of previous empirical research studies
show that job satisfaction and job performance tend to
correlate significantly [Bagozzi, 1980]. This hypothesis
results in theorizing a nonrecursive model in which the
interrelationship between the two constructs is
investigated. This differs from a recursive model in
which one of the constructs precedes or "causes" the
second construct. A nonrecursive model is used because
the theories regarding the causal relationship between job
satisfaction and job per*formance are uncertain and
conflicting [Vroom, 1964; Lawler and Porter, 1967; Porter
and Lawler, 1968; Lawler, 1971; Ross and Bomeli, 1971;
Benke and Rhode, 1980]. The second research objective
hypothesizes, in alternate form, the following:
H9: There is a positive nonrecursive relation between a staff accountant's job satisfaction and job performance.
As stated previously, professional commitment has
been found to precede organizational commitment,
supporting hypothesis ten [Aranya, Lachman, and Amernic,
1982; Lachman and Aranya, 1986]. Hypotheses eleven and
twelve are based on the level of satisfaction an
individual has with the career choice of becoming a
certified public accountant. If an individual is
53
satisfied with his/her career choice, professional
commitment and organizational commitment should be
significantly related in a positive manner with life-span
career development. The last research objective
hypothesizes, in alternate form, the following:
HIO: A staff accountant's organizational commitment will be directly predicted by professional commitment.
Hll: There is a positive relation between professional commitment and life-span career development for a staff accountant.
H12: There is a positive relation between life-span career development and organizational commitment for a staff accountant.
Chapter Summary
Figure 3.5 is the research model for the twelve
hypotheses presented in this chapter. These hypotheses
are based on the theoretical model developed by Bullen and
Flamholtz [1985]. In addition to the twelve hypotheses
under investigation, demographic data such as sex, age,
and years as a staff accountant were collected. While
there are no hypotheses presented for the demographic
data, analyses of the data will be conducted. Chapter IV
contains the research design, the results of pretesting
the research instrument, and the statistical analytical
technique for this study.
54
Figure 3.5. The Research Model for all Hypotheses
55
CHAPTER IV
RESEARCH METHODOLOGY
Having discussed the continuing interest in the
relationship between job satisfaction and job performance,
and the constructs that affect job satisfaction and job
performance, this chapter describes the development of the
approach to test the research model. The analyses of the
data are presented in Chapter V.
The three purposes of this chapter are to: (1)
explain the research design; (2) discuss the pretesting of
the research instrument; and (3) introduce the statistical
techniques that were used to analyze the data.
Research Design
This research study is a field study. Kerlinger
[1986] defines field studies as "nonexperimental
scientific inquiries aimed at discovering the relations
and interactions among sociological, psychological, and
educational variables in real social structures" (p. 372).
He further refines his definition to include studies that
pursue relations and test hypotheses that are done in life
situations such as businesses. Field studies can be
either exploratory, seeking what is occurring, or
hypothesis-testing. This study comes under the latter
56
category and its aim is to uncover relationships among the
constructs.
Field studies have several strengths such as realism,
significance, strength of variables, theory orientation,
and heuristic quality. Weaknesses of field studies
include the large number of variables and variance, which
can influence the study and the lack of precision in
measurement [Kerlinger, 1986]. An attempt was made to
control for extraneous variables that may affect the study
by using a single office of a large public accounting
firm. Using only one office of the firm controlled for
the variation that could occur due to spatial
autocorrelation, a problem common to studies that sample
firms in different geographical locations. Types of
variation that are controlled for by using only one firm
include personnel differences, the leadership style of the
managing partner, and the office environment. Measurement
instruments were refined to maximize the precision of the
instruments (see Chapter V).
The Population for the Study
The subjects used in this study are employed at a
national public accounting firm located in a large
midwestern city. The firm categorizes levels within the
organization as partner, manager, or staff. Within the
level of staff are the categories senior and assistant.
57
To test the hypotheses of this study, staff
accountants in a public accounting firm who had at least
six months of public accounting experience were selected.
This limitation on subject selection is imposed because
some training and relevant employment—employment specific
to the chosen career—should occur during the
implementation stage of career development [Osipow, 1983].
Development of the Research Instrument
A research instrument was used in this study to
ensure quantifiable data, maintain equivalency of
responses, and because of the sensitive nature of the
material. In addition to the measurement scales used for
the constructs under study, the research instrument also
included requests for demographic information such as age,
sex, position with the firm, years as a staff accountant,
years with the firm, professional certifications, and
education. The demographic data were used as a screening
tool to ensure that the respondents held both the staff
position in the firm and had at least six months of public
accounting experience, as required for this study.
Participation in the study was voluntary, and no attempt
was made to identify respondents by the demographic data
supplied. A copy of the research instrument, a letter to
the subjects informing them of the study, and a letter
58
from a partner in the firm encouraging them to participate
in the study are presented in Appendix A.
Federal regulations require material that will be
used on human subjects to be reviewed. It is a Texas Tech
University policy to review all research involved with
human subjects. The research instrument was submitted to
the Texas Tech University Committee for the Protection of
Human Subjects for review and approval was received. A
copy of the letter granting approval is presented in
Appendix B.
Job Satisfaction Measurement
The Minnesota Satisfaction Questionnaire (MSQ)
[Weiss, Dawis, England, and Lofquist, 1967] was used to
measure job satisfaction. Price and Mueller [1986] stated
that the MSQ was developed to link both measurement and
theory. This scale has been used in accounting studies to
measure job satisfaction (for example, Brownell, 1983).
Weiss et al. [1967] report construct validity based on
the results of testing the instrument within occupations,
and between different occupations. A general internal
reliability coefficient of .90 is reported [Weiss et al.,
1967, p. 23].
59
Job Performance Measurement
Employee performance can be actual or perceived. It
can be further subdivided into historical, expected, or
aspired performance. In public accounting firms, employee
performance is usually based on a supervisor's judgments
and is supported by the employee's (subordinate)
historical actions.
National public accounting firms are reluctant to let
confidential information such as performance evaluations
be seen or used by individuals outside of the firm. An
alternative is to use self-reported performance
evaluations. Self-reported performance evaluations have
been used in accounting studies (for example, Brownell and
Mclnnes, 1986; Choo, 1986; Chenhall and Brownell, 1988).
A potential bias in the use of self-reported performance
evaluations is the inflation of one's performance or a
leniency in self-evaluation [Prien and Liske, 1962;
Lawler, 1968; Thornton, 1980]. Other studies have shown
the opposite effect in self-rating performance evaluations
[Heneman, 1974; Teel, 1978].
There is also the possibility of bias when
supervisors' ratings are used to measure job performance.
Ramanathan et al. [1976] and Jiambalvo [1982] have
reported that there are differences in the perceived
importance of the criteria used in performance
60
evaluations. This may indicate that in studies where
individualistic factors are related to job performance, an
individual's perceived job performance may better relate
to these factors than a superior's job performance rating.
Ferris and Larcker [1983] reported that rewarded
performance (compensation) was a function of both the
interpersonal attraction between the auditor and his/her
supervisor and the task-related ability of the individual.
Therefore, rewarded job performance may be biased based on
the interpersonal attraction between the auditor and
supervisor. It appears that there is potential for bias
using either supervisor or self-rating performance
evaluations [Landy and Farr, 1983]. Since supervisory
performance evaluations were not made available, and there
is a potential for bias in either self-reported or
supervisory performance evaluations, self-reported
performance scales were used in this study.
The self-reporting performance scale used in this
study was developed by Choo [1986], specifically to
measure accountants' job performance. There was no
statistically significant difference found between self-
reported performance evaluations and supervisor
evaluations. The mean score for self-reported performance
evaluations was .50 less than the mean score reported by
61
superiors [Choo, 1986, p. 26]. This indicates a lack of
leniency bias in the instrument and reported scores.
Organizational and Professional Commitment Measurement
Organizational commitment was measured using the
Organizational Commitment Questionnaire (OCQ) developed by
Porter, Steers, Mowday, and Boulian [1974]. Mowday,
Steers, and Porter [1979] were critical of organizational
commitment scales because they believed most were created
on an a priori basis, with little, if any, reliability and
validity data presented. Using the OCQ, a variety of
analyses were carried out using different samples [Mowday
et al., 1979]. Acceptable levels of reliability and
convergent, discriminant, and predictive validity were
evident for the OCQ. This scale has been used in the
accounting literature for studies measuring organizational
commitment (for example, Aranya et al., 1981a; Aranya et
al., 1982; Norris and Niebuhr, 1983; Aranya and Ferris,
1984).
The Professional Commitment Scale (PCS) developed by
Aranya et al. [1981a] was used in this study. The PCS was
primarily adapted by taking the OCQ and substituting the
word profession for organization. In their study, Aranya
et al. [1981a] reported a coefficient alpha of .87.
62
Nunnally [1978] recommends alpha values of .80 or above to
be good indicators of reliability.
Since the organizational and professional commitment
scales are similar, there is the possible effect of common
method variance on the correlation between the two
measures. Aranya and Ferris [1984] used these two scales
in a study and found the correlation between them did not
indicate a strong response bias.
Bline, Duchon, and Meixner [1991] investigated the
psychometric properties of the professional and
organizational commitment scales used in this study.
Their results provide support that the scales do measure
two different constructs.
Life-Span Career Development Measurement
An individual can be satisfied or dissatisfied with
his or her career choice. Osipow [1983] reports that
dissatisfied individuals would be more likely to consider
a career change than satisfied individuals (p. 220).
Personal interviews or longitudinal studies have been used
to determine an individual's life-span career development
[Osipow, 1983].
An alternative to the interviewing process is to
develop a scale that would measure the level of an
individual's career stage. This study used subjects who
should be in the implementation stage of their career
63
development. Therefore, the scale must contain questions
that will allow the researcher to ascertain whether the
individual is in the implementation stage. The scale
developed for this study is based on Super's [1957] six
descriptors for adjusting to work requirements in the
implementation stage. The six descriptors are technical
competence, the routine or tempo of the work, the work
load, work attitudes and roles, security, and time-in-job
before advancement. The questions were derived from the
characterizations given by Super [1957] for the six
descriptors. The characterizations used for the
questionnaire were limited to those that dealt with career
development, to avoid questions that may measure job
satisfaction.
Self-Monitoring Measurement
Snyder's [1974] Self-Monitoring Scale was used to
measure an individual's level of self-monitoring. This
scale requests the subjects to answer twenty-five true-
false self-descriptive statements. Subjects are then
categorized into a low group or high group based on their
responses to the questions. The technique used to
distinguish between high and low self-monitors is to use a
median cutoff (for example, Snyder, 1974; Douglas, 1983).
The upper fifty-percent are considered high self-monitors
64
of the sample, the lower fifty-percent are considered low
self-monitors of the sample.
Research Instrument Distribution and Collection Technique
The researcher was not allowed the time needed to
meet with all of the subjects at the branch and home
offices, as many of them went to the offices only once a
month because they were at remote areas working on audits.
Therefore, for both the pretest and study, a
representative of the firm distributed the research
instrument, which included a letter from the researcher
describing the study, a letter from a partner in the firm
encouraging subjects to participate in the study, and a
self-addressed stamped envelope to return the research
instrument. This was done through the office manager at
the branch office, and a partner at the home office. For
subjects who did not pick up their mail within-one week of
the distribution of the research instrument, the firm
mailed the research instrument and self-addressed stamped
envelope to their home address. The researcher verified
with the firm's office manager and partner assigned to the
study that this procedure was done. The office manager
and partner sent a follow-up memo requesting completing
and mailing the research instrument to all subjects in
65
both the pretest and study. All completed questionnaires
were mailed directly to the researcher's home.
The distribution of the questionnaires by a
representative of the firm, rather than by both the
researcher and a representative of the firm, controls for
potential experimenter effects. These effects can occur
if the researcher distributes and collects some of the
questionnaires, and a representative of the firm
distributes and collects some of the questionnaires.
Subjects may respond differently to questionnaires based
on the individual who distributes the questionnaires.
This distribution and collection technique has been used
in previous accounting research at public accounting firms
[Sutton and Lampe, 1988].
Pretesting the Research Instrument
Hunt, Sparkman, and Wilcox [1982] list three
categories of items that should be pretested: "(1) items
about the questionnaire itself, (2) items about specific
questions, and (3) items about data analysis" (p. 269).
Converse and Presser [1986] expanded these three
categories into ten specific purposes for pretesting a
questionnaire. The first four purposes are tests for
specific questions: variation (data analysis), meaning,
task difficulty, and respondent interest and attention.
The last six purposes bear on the questionnaire as a
66
whole: flow and naturalness of the sections, the order of
questions, skip patterns, timing, respondent interest and
attention (overall), and respondent well-being.
The research instrument was pretested in a branch
office of the national firm used in this study. The
branch office was located approximately ninety miles from
the home office where this study was conducted. The close
proximity between the offices decreased the possibility of
spatial autocorrelation, which could result from using two
or more offices or firms geographically far apart.
Table 4.1 is the summary of the research instrument
response rates from the pretest. Twenty research
instruments were distributed by the branch office manager
to the staff accountants. Initially, the subjects were
not made aware that they were participating in a pretest;
however, at the end of completing the research instrument,
subjects were requested to list any comments they had
regarding the questions and the overall research
instrument. Subjects were instructed to complete the
research instrument and mail their responses in self-
addressed stamped envelopes, which were provided. These
procedures were used at the branch office to simulate the
conditions that would be employed at the home office for
this study. Within nine days, sixteen of the
questionnaires were returned, of which fourteen were
67
TABLE 4.1 SUMMARY OF QUESTIONNAIRE RESPONSE RATES FROM THE
PRETEST FOR ALL SUBJECTS
1 1 Staff Managers Partners Total
Questionnaires distributed
No Response
Responses
Responses not usable for data analysis
Responses usable for data analysis
20
4
16
2
14
6
1
5
1
4
3
1
2
0
2
29
6
23
3
20
Response rate based on questionnaires distributed 80% 83% 67% 80%
Research instruments were distributed to managers and partners to pretest the life-span career development measurement instrument.
68
usable. Two questionnaires were not usable because the
subjects were employed at the firm for substantially less
than six months. Four managers and two partners completed
questionnaires as part of the pretest. This was to
compare mean responses on the measurement instrument for
life-span career development. Hunt et al. [1982, p. 270]
reported that the size of the pretest sample is not fixed,
and that sample sizes of twelve, twenty, and thirty have
been reported to be satisfactory.
The first purpose of pretesting the specific
questions, variation (data analysis), was met by examining
Pearson correlation coefficients for the constructs
professional commitment, organizational commitment, life
span career development, job satisfaction, and job
performance. No changes were made to the research
instrument based on this analysis. Since self-monitoring
is measured on a dichotomous scale, high or low, it was
excluded, from this analysis. PRELIS and LISREL (linear
structural relations) VII, the statistical packages used
in this study, allow the use of continuous and dichotomous
constructs in the Scime model. However, the number of
responses in the pretest was too small to use LISREL VII.
This posed no problem for this study, since the number of
responses from the home office was large enough to use
LISREL VII.
69
The remaining three purposes of pretesting the
specific questions—meaning, task difficulty, and
respondent interest and attention—were analyzed by
reading the comments provided by the subjects. There were
no comments regarding these three areas of the pretest.
The last six purposes of the pretest—flow and
naturalness of the sections, the order of questions, skip
patterns, timing, respondent interest and attention
(overall), and respondent well-being—were also analyzed
by reading the comments provided by the subjects. Based
on the subjects' responses, two areas that rec[uired
changes in the research instrument were the ordering of
the questions, and the form requesting demographic data
and job titles.
Initially, the questions for organizational and
professional commitment were sequential. Some of the
subjects assumed they were the same questions because of
the similarities between the questions. This was changed
for the research instrument distributed to the home office
by separating the two sets of questions, and inserting a
statement that the questions were not the same as the ones
asked previously. A second change was made regarding the
ordering of the demographic data, and the wording of the
job titles.
70
No other changes were made to the research instrument
after the pretest. On average, it took the subjects
fifteen minutes to complete the research instrument, with
a range of nine minutes to twenty minutes.
Statistical Technique
The constructs under study are latent or unobserved.
In their purest form they are abstract unidimensional
concepts, making them only indirectly measurable [Bollen,
1989]. The latent variable model consists of the
structural equations that summarize the relationships
among the constructs, and the measurement model. The
totality of relationships among the constructs is usually
referred to as the structural equation, and their
measurement as the measurement model. This is misleading
because it indicates that the measurement model is not
structural. While this is not the case, to differentiate
between the relationship among the constructs and the
measurement model, this study will use the traditional
approach of referring to the relationships among the
constructs as the structural model, and the measurement of
these constructs as the measurement model.
The primary statistical tools used to analyze the
data in this study are PRELIS and LISREL VII. PRELIS and
LISREL VII were developed by Joreskog and Sorbom [1988,
1989a, 1989b]. PRELIS is data screening software that can
71
read grouped and patterned data. In addition to data
screening, PRELIS computes correlations and matrices which
can be used as input files for LISREL VII. The necessity
of using PRELIS in this study is that it can compute
correlations and other product moments for continuous and
dichotomous variables that other statistical programs
cannot produce [Joreskog and Sorbom, 1988]. This will
allow the dichotomous construct self-monitoring to be
analyzed with the continuous constructs in this study.
LISREL VII is used to analyze the structural and
measurement models. LISREL VII will minimize the
difference between the sample covariances and the
covariances predicted by the model. An advantage to using
LISREL VII with the data for this study is that it will
integrate measurement concerns with the structural
equation model. This is done by incorporating both the
measured indicator variables with the latent theoretical
concepts into a single structural equation model [Hayduk,
1987, pp. 87-88]. LISREL thus allows for integrating
model development, estimation, evaluation, and
interpretation with measurement concerns [Bohrnstedt,
1983].
LISREL Model Specification
The LISREL model is illustrated in Figure 4.1, and
the LISREL terminology and notations for this study are
72
*l-'n
^t- ^n
^ - ^ i '.6/n
ib.i^yi.i
^)6-'-7
^.6- ^7
Figure 4.1. The LISREL Model
73
presented in Figure 4.2. The model consists of three
latent exogenous constructs (xis)—professional
commitment, life-span career development, and self-
monitoring—which will be predicted outside of the model,
and three endogenous constructs (etas)—organizational
commitment, job satisfaction, and job performance—which
will be predicted within the model. This is done by the
three ecjuations which make up the general structural
equation model. (See Figures 4.3 - 4.5 for the specific
research equations and the general form of these
equations.)
The first equation (Figure 4.3) contains the
hypothesized direct effects among the concepts. These
were estimated by the matrices of structural coefficients
(betas and gammas), the vectors of the endogenous and
exogenous concepts, and a vector of "errors" in the
conceptual model (zeta). The covariances among the zeta
terms will make up matrix psi. Xis will generate a
matrix, phi, which is the covariance among the xis. The
second and third equations (Figures 4.4 and 4.5) link the
conceptual variables to their observed indicators [Hayduk,
1987]. The second equation is the measurement model for
the endogenous indicators, consisting of a matrix of
structural coefficients (lambdas), the vector of the
endogenous concepts, and a vector of "errors" in the
74
S p e c i f i c Terms I n c l u d e d in I h e LISREL Model
^15
><1
P r o f e s s i o n a l Commi tiuen t L i f e S p a n C a r e e r D e v c 1 o p m c n I
S e 1 f - M o n i l o r i ng Orga i i i 2a t i ona i Commi Uiien t J o b S a l i s f a c l i on J o b P e r f o r m a n c e i n d i c a n t s of Piof ess i ona 1 Commi linen I i n d i c a n l s of Life S p a n C a r e e r D e v e l o p m e n t i n d i c a n t s of Se 1 f-Mon i t or i ni; i n d i c a n t s of O r g a n i z a t i o n a l Coimiii tuien t i n d i c a n t s of Job S a t i s f a c t i o n i n d i c a n l s of Job P e r f o r m a n c e
D e f i n i t i o n s of L I S R E L ' S G e n e r a l T e r m s
I Tl X y p q (U n
(xi) (ela)
an unobservable (latent) cxog^enous variable an unobservable (latent) cndogejtous variable an observed indicant of an exogenous variable an observed indicant of an endogenous variable the number of y-variables the number of x-variables the number of T^-variables the number of ^-variables
Parameter Matrices
Ay (Larabda-y)
Ay (Lambda-x)
B (Beta)
r (Gamma)
i (Phi)
Y (Psi)
Sj ( T h e t a - E p s i I o n )
e, (Theta-Dclta)
a pxm among a qxn among a mxm among a mxn among a nxn among a mxm among a pxp among a qxq among
matrix of y ' s and T
matrix of x's and ; matrix of
n matrix of ; ' s and T\ ma t r i X of
the I m a t r i x of
I he
the
the
the
the
the
the T)' s e r r o r m a t r i x of the the y's er r o r m a t r i x of the
the x's er r o r
r e 1 u I i oiisii i ps
re 1 a t i o n s h i p s
r e l a t i o n s h i p s
r e l a t i o n s h i p s
r e i a l i o n s h i p s
r e l a t i o n s h i p s Ierms (C's ) re1ali o n s h i p s lerms ( € ' s ) r e l a l i o n s h i p s Ierms ( 6 ' s )
Figure 4.2. LISREL Notation and Terminology
75
G e n e r a l . Forxc: T] = BT) -K pf * C
S p e c i f i c Foruj
T)
Tl
T)
B. , B:;
0 0 "D
TJ "^ 1 Tl .
Tl • , 0
* '^ 11 • 21 ^ J l
r M V , ,
1
0
1 ' . .
i • 1 ' • I - •
1 ; .
^ : 1 :1 c ;
Figure 4.3. The Structural Equation
76
G e n e r a l :
Spec 1f i c :
Y = Ayt,
> • ' :
yi >i
>5
>-ll
>li >-15 >1T >!l ^15 y V
20 21
yu
>25
> 3 0
>-3l > -3 : > 3 3 >-3< >'3i v.-* n yyi V V
3S 35
•Nl
yr, > • «
• 4i
.1.1 A , ,
^ t , l A., . • • < 1 A . ,
.10 ,1
^11,1
^ i : . i A , , ,
0 u 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
li.l
0 0 0 0 u u 0 0 u 0 u 0 0 0 0
A l , . . t »li
^\', ^ « * . t . A»(( . . . . • . . • « • . A . « ^ . • « • . A . . ^
A l ( 1
A i ; <
A * ' 7 . •^•• A l - 1 . •• •' A i r 1
• . • * A1C 1
• • • •
f3 t . : A * ' ^ , « • • • . • - • • /»• • ^ • •« • *
A , : ,
0*"* 0 0 0 0 0 0 0 0 0 0 0
0 u u 0 0 u 0 u 0 u 0 u 0 0 0 0 0 0 u 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
^1
^ 2
Tl;
* A - -. - ( l .
/..• • • ' • A . ,
A v .
. • • • A | r
A , .
. '•• ^r.. ^ < : .
^u. A , : . '•• A , . . U. ' T .
3 3
! ' i e. «i ^i ^ s ^ j € i
^11 ^ 1 !
^15
•11
^\)
«!1
^33
^2<
^!J
^:i
€„ ^ 3 1 ^31 € . , ^33
^ 3 :
3i
' 3 1 «3?
^ 4 1 ^41 ^ 0 e<3 ^ H
Figure 4.4. The Measurement Model for Y Indicants
77
General:
Specifie:
X = A , ^ ^ 6
10
X ,
x« X .
^ I Xj
^ { X i
^1 X ;
X
X . ^
x,i
^11 ^IJ >^:o >-:i X . .
X.I . . I
^21 X i ;
xi: • «
X . .
^31 X . t
X j j
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Figure 4.5. The Measurement Model for X Indicants
78
measurement model (epsilon). The covariance among the
epsilon terms constitute matrix theta epsilon. The third
equation is the measurement model for the exogenous
indicators, consisting of a matrix of structural
coefficients (lambdas), the vector of exogenous concepts,
and a vector of "errors" in the measurement model (delta).
The covariance among the delta terms constitute matrix
theta delta.
To test the model, a two-step approach is used
[Anderson and Gerbing, 1988]. This approach evaluates the
measurement model separately from the full structural
equation model. The first step is to evaluate the
measurement model for unidimensionality of the measurement
constructs, and respecify the model if necessary [Anderson
and Gerbing, 1988]. The second step is to simultaneously
test the measurement and structural model after
respecification. These steps are presented in Chapter V.
Chapter Summary
The research design, pretesting of the research
instrument, and the statistical techniques used in this
study were presented in this chapter. The research design
is based on field study research [Kerlinger, 1986].
Pretesting the research instrument was conducted as
closely as possible to the distribution and collection
techniques used in this study. There were no significant
79
changes made to the research instrument or planned
distribution and collection techniques based on the
pretest. Based on the constructs being investigated,
structural equation modeling with a two-step approach was
selected to analyze the data, using PRELIS and LISREL VII
Chapter V contains the analyses for this study, including
response rates, testing for nonresponse bias, and
statistical testing of the measurement models and
structural equations.
80
CHAPTER V
EMPIRICAL ANALYSIS OF THE DATA
The study to this point has used the theories of
Bullen and Flamholtz [1985] and Bagozzi [1980] to
construct a research model to investigate the
interrelationships among variables that can affect job
satisfaction and job performance, as well as the
relationship between job satisfaction and job performance
The research design, population, research instrument,
pretest results, and statistical procedures used in this
study were presented in Chapter IV. In the first part of
this chapter the response rates and the test for
nonresponse bias are presented. The second part presents
the statistical analyses used in the study to test the
research model (see Figure 3.5). This analysis includes
testing and refining the measurement models, simultaneous
tests of the measurement and structural models, and tests
of the individual structural coefficients.
Response Information
Response Rates
The study was conducted at a national public
accounting firm located in a large midwestern city. The
distribution and collection of the research instrument
were described in Chapter IV. The firm employed 421
81
accountants classified as staff at the time of this study.
Of these, 312 responded, for a 74% response rate.
Listwise deletion is used in this study, so any
respondents not answering all of the questions, or meeting
the experience requirements for this study were eliminated
(see Statistical Analysis, p. 84). This reduces the data
matrix to a matrix without any missing observations. This
resulted in 31 responses being eliminated for a usable
response rate of 67%. Table 5.1 presents the response and
elimination rates.
Test for Nonresponse Bias
Armstrong and Overton [1977] recommend the best
protection against nonresponse bias is the reduction of
nonresponse itself. However, when nonresponse is present,
subjects who respond late or less readily are assumed to
be more like nonrespondents [Armstrong and Overton, 1977].
In this study, the nonresponse rate was 26%, possibly due
to the distribution and collection techniques. To test
for nonresponse bias, a comparison of the means of early
and late respondents was undertaken. This testing was
done by using multivariate analysis of variance.
Multivariate analysis of variance is used when means on
several different variables are being compared
simultaneously, as in this study [Bray and Maxwell, 1985].
82
TABLE 5.1 SUMMARY OF QUESTIONNAIRE RESPONSES AND ELIMINATIONS
Number Percent
Total Questionnaires Distributed
Questionnaires Returned 1
Questionnaires Eliminated
Usable Responses
421
312
31
281
100%
74%
7%
67%
1 Questionnaires were eliminated for candidates who were
not employed at the firm for at least six months, or who did not answer all of the questions pertaining to the measurement of the constructs. This latter requirement is because of the use of listwise deletion.
83
Table 5.2 presents the nonresponse bias test result.
The null hypothesis for testing nonresponse bias is that
there is no difference in the mean responses between the
early and late respondents. Wilks' Lambda results in not
rejecting the null hypothesis at the .05 level. No
significant nonresponse bias is indicated by the results
of the test statistic.
The demographic data and descriptive statistics are
presented in Appendix C. Statistical tests were conducted
for differences in mean responses for the demographic
data. There were no significant differences between mean
responses based on the demographic data at the .05 level.
Statistical Analysis
Testing for Identification
Equations in a model must be identified if meaningful
results are to be obtained [Fisher, 1966]. Berry [1989]
stated:
An equation is identified if the acquisition of data for a properly chosen infinite sample would be sufficient to determine a unique set of parameters for the equations; if the equation is identified, only one explanation (i.e., one set of parameters) would be consistent with both the data from the infinite sample and the model's restrictions, [p. 25]
LISREL VII checks for the identification of the model by
making tests in the following way [Joreskog and Sorbom,
1989b]:
84
TABLE 5.2 NONRESPONSE BIAS TEST RESULT
Test F-Test PR > F
Wilks' Lambda .9434 .4548
85
The program checks the positive definiteness of the information matrix. (The information matrix is the probability limit of the matrix of second order derivatives of the fit function used to estimate the model.) If the model is identified, the information matrix is almost certainly positive definite. If the information matrix is singular, the model is not identified and the rank of the information matrix indicates how many parameters are identified, [p. 17]
There were no instances of lack of identification in the
model during the statistical analysis using LISREL VII.
Testing the Measurement Model
Anderson and Gerbing [1988] recommend a two-step
approach to be used for structural equation modeling.
This is accomplished by first testing the measurement
model prior to testing the measurement and structural
submodels simultaneously. The reliability and validity of
the measurement instrument can be assessed by testing the
measurement model in a two-step approach.
Because of the large number of indicants used in this
study, composites of the 95 questions used in the
measurement instrument were formed. The use of composites
and single indicators has precedence when using LISREL as
the statistical tool for data analysis (for example, see
Bagozzi, 1980a and 1980b; Gaski, 1986; Howell, 1987).
Questions 1-70 measured the constructs professional
commitment, life-span career development, organizational
commitment, job satisfaction, and job performance. These
86
seventy questions were grouped into twenty composites,
four for each construct. Self-monitoring was measured by
questions 71-95. Based on the responses to these
questions, subjects were numerically categorized as a low
(1) or high (2) self-monitor. Therefore, a total of
twenty-one composite measurement indicants were used for
the six constructs.
Next, the input files were created for analysis using
LISREL. This was accomplished by using PRELIS, the
predecessor analytical software for LISREL. Since self-
monitoring is a dichotomous construct, and the other
constructs are continuous, Joreskog and Sorbom [1988 and
1989a] recommend using the weighted least squares method
for data analysis. This entails the use of listwise
deletion because there are a different number of cases
(observations) involved in the computations if pairwise
deletion is used [Joreskog and Sorbom, 1989a]. PRELIS
computed Pearson product moment correlations among the
constructs professional commitment, life-span career
development, organizational commitment, job satisfaction,
and job performance. Polyserial correlations were
computed between self-monitoring and professional
commitment, life-span career development, organizational
commitment, job satisfaction, and job performance. In
addition to the correlation matrix, PRELIS created the
87
asymptotic covariance matrix to be used as an input file
in the LISREL analyses. This input file is used with the
weighted least squares method so that "an estimate of the
asymptotic covariance matrix of estimated correlations can
also be obtained under the same general assumptions of
non-normality" [Joreskog and Sorbom, 1989a, p. 21].
After the input files were created, LISREL was used
to measure the reliability of the composites. This is
done by constraining to zero all of the parameters that
relate the constructs. Squared multiple correlations are
used to determine the reliability, where values greater
than .50 are considered desirable [Bagozzi and Yi, 1988].
Measurement error for self-monitoring was specified at
.20, producing the squared multiple correlation of .80.
Hayduk [1987] recommends measurement reliabilities to be
fixed rather than free when the researcher is familiar
with the data and measurement quality. As discussed in
Chapter IV, subjects are categorized as high or low self-
monitors based on a median split. Since the median can
differ based on the subjects responding to the research
instrument, it was felt that measurement error was present
and .20 would represent an acceptable amount of
measurement error.
The results are a goodness-of-fit index of .957 and
root mean square residual of .049, both indicating a very
88
good overall fit [Bagozzi and Yi, 1988]. However, job
satisfaction 1 and 2, job performance 4 and life-span
career development 1 and 3 composites did not meet the
desired squared multiple correlation level of .50, so the
measurement model was respecified. The squared multiple
correlations for the twenty-one composites are presented
in Table 5.3.
Respecification was done by using factor analysis to
examine the indicants for low loadings to obtain
candidates for deletion. Indicants that did not have a
factor loading of .30, or had loadings on a factor other
than the common factor for a measurement scale, are
candidates for deletion [Kim and Mueller, 1986]. The
measurement scales for organizational commitment and job
performance did not have any candidates for deletion.
Two indicants for professional commitment, x7 and
xl2, were deleted, since they did not have factor loadings
large enough to warrant inclusion based on the criteria
for deletion. The measurement scale for life-span career
development had four candidates for deletion, xl6, xl7,
x20, and x21. These were deleted because they did not
load on the factor for the construct life-span career
development. These variables each loaded on a different
factor, therefore they did not, as a group, represent a
different construct. Possible reasons for this are that
89
TABLE 5.3 MEASUREMENT STATISTICS FOR THE TWENTY-ONE COMPOSITES
Item Squared Multiple Correlation
Organizational Commitment 1 .717
Organizational Commitment 2 .645
Organizational Commitment 3 .750
Organizational Commitment 4 .755
Job Satisfaction 1 .490
Job Satisfaction 2 .468
Job Satisfaction 3 .721
Job Satisfaction 4 .606
Job Performance 1 .694
Job Performance 2 .766
Job Performance 3 .558
Job Performance 4 .430
Professional Commitment 1 .611
Professional Commitment 2 .590
Professional Commitment 3 .734
Professional Commitment 4 .698
Life-Span Career Development 1 .022
Life-Span Career Development 2 .578
Life-span Career Development 3 .255
Life-Span Career Development 4 .517
Self-Monitoring (error specified at .20) .800
90
the scale, which was created for this study, measured
other stages of life-span career development, or a
construct other than life-span career development. Job
satisfaction had the most indicants deleted, eight. The
squared multiple correlations for two of the composites
were less than .50, which may indicate measurement
problems for this construct. The job satisfaction scale
consists of twenty questions comprising many aspects of an
individual's job. It has a reported internal reliability
coefficient of .90 [Weiss et al., 1967, p. 23]. In this
study, the indicants yl8, yl9, y23, y24, y25, y27, y28,
and y29 did not load on the common factor, nor did they
load on the same factor, which may have indicated some
construct other than job satisfaction being measured. A
possible reason for the measurement problem that occurred
in this study is that the questions were not applicable to
staff accountants. For example, some of the questions
asked about supervising individuals, and subjects trying
their own methods of doing the job. Staff accountants
usually do not supervise, and they are told how to go
about doing the job. The respecified measurement models
for the y and x indicants are presented in Figures 5.1 and
5.2.
The respecified measurement model consists of sixteen
composite measurement indicants for the six constructs.
91
c i e n e r a ; :
S p e c i f i c
A .Ti - e
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V . ' » > 1
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0 0 u 0 u 0 u u 0 u 0 0 u 0 u A i . . , I k , i A ( 1 I)
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/ . 1 ^ • 1 . t f -
Figure 5 . 1 . Respecified Measurement Model Indicants
for Y
92
General:
Speci fie:
X = A , $ + C
X ,
X
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X
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A l . .. Art . t . A f . •. A ,
; . 1 4
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F i g u r e 5 . 2 . Respecified Measurement Model for X Indicants
93
There are three composites for each of the constructs
professional commitment, life-span career development,
organizational commitment, job satisfaction, and job
performance. Each of the three composites are created
from a common factor for each construct. There is one
composite measurement indicant for self-monitoring.
This study minimized the effects of deleting these
indicants by using composites. If the questions that were
deleted did not contribute to the reliability of the
measurement scales, then the new composites should show
increased reliabilities through the recalculated sguare
multiple correlations. By creating new composites based
on the results of the factor analysis, it also makes it
unnecessary to correlate error terms, as these will be
minimized by grouping the indicants into the composite
scales. The respecified measurement models for the
composite y and x indicants are presented in Figures 5.3
and 5.4.
The squared multiple correlations for the respecified
measurement model are presented in Table 5.4. life-span
career development composites 2 and 3 are marginally short
of the desired .50 level, while all of the other
composites exceed .50. The goodness-of-fit index improved
increasing from .957 to .990, and the root mean square
residual has improved by decreasing from .049 to .041.
94
General:
Spec:fie:
Y = A,.T]
1 >> V .
>-4 y^ yi V . • 1 y\
X. x: m •
A..
0' 0 0 0 0 0
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A
0 0
0 0 0 0 0 0 X. 1 . ' .< A . , . *«• A j ^
^1
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1 «
e,
Figure 5.3. Respecified Measurement Model For Composite Y Indicants
95
General:
Speci fie:
1 X,
^ 3 ^ <
^ :
1
X = A P
x: l.l ;i: :.i 3.1
0 0 0 X ^ . XI':
0 0 0 0 0 0 A, ,3
5 , I
tl t
f 0(
>7
Figure 5.4. Respecified Measurement Model For Composite X Indicants
96
TABLE 5.4 MEASUREMENT STATISTICS FOR THE SIXTEEN COMPOSITES
l ni Squared Multiple Correlations
Organizational Commitment 1 .740
Organizational Commitment 2 .836
Organizational Commitment 3 .771
Job Satisfaction 1 .661
Job Satisfaction 2 .689
Job Satisfaction 3 .588
Job Performance 1 .708
Job Performance 2 .717
Job Performance 3 .749
Professional Commitment 1 .739
Professional Commitment 2 .700
Professional Commitment 3 .776
Life-span Career Development 1 .577
Life-span Career Development 2 .452
Life-span Career Development 3 .493
Self-Monitoring (error specified at .20) .800
97
These results indicate an overall improvement in the
measurement model.
Construct validity was examined by the correlations
among the constructs produced with PRELIS, with their
hypothesized relationships. The hypothesized
relationships cimong the constructs were for significant
correlations. Table 5.5 presents the correlations among
five of the constructs. The correlations between job
performance, and professional and organizational
commitment are positive and significant at the .05 level.
The correlation between job performance and life-span
career development is significant at the .01 level. All
of the other correlations are positive and significant at
the .0001 level. This gives evidence for construct
validity.
Table 5.6 presents the polyserial correlations
between self-monitoring, and the composites in the
respecified measurement model for job satisfaction, job
performance, organizational commitment, professional
commitment, and life-span career development. The
composites rather than the individual indicants were used
to attempt to better respecify the measurement model. The
polyserial correlations are not significant for the
hypothesized relationships. Correlations between self-
monitoring and professional commitment, life-span career
98
TABLE 5.5 PEARSON CORRELATION COEFFICIENTS/
PROB > |R| UNDER HO:RHO==0
OC JS JP PC LSCD
Organizational Commitment (OC) 1.000
0
Job Satisfaction (JS) .6216 1.000 .0001 0
Job Performance (JP) 1476 .3244 1.000 .0132 .0001 0
Professional Commitment (PC) 7680 .5671 .1252 1.000
.0001 .0001 .0359 0
Life-Span Career Development (LSCD) 6099 .5630 .1787 .6826 1.000
.0001 .0001 .0026 .0001 0
99
TABLE 5.6 POLYSERIAL CORRELATION COEFFICIENTS/
PROB > |R| UNDER HO:RHO=0
Self-Monitoring
Job Satisfaction 1 .092 / .122
Job Satisfaction 2 .115 / .053
Job Satisfaction 3 -.030 / .615
Job Performance 1 .011 / .856
Job Performance 2 .006 / .924
Job Performance 3 .059 / .325
Organizational Commitment 1 .074 / .215
Organizational Commitment 2 .112 / .056
Organizational Commitment 3 .014 / .815
Professional Commitment 1 .054 / .370
Professional Commitment 2 .144 / .016
Professional Commitment 3 .112 / .061
Life-Span Career Development 1 .009 / .887
Life-Span Career Development 2 .037 / .542
Life-span Career Development 3 -.002 / .967
Self-Monitoring 1.000 / 0
100
development, and organizational commitment are presented
for informational purposes. There are no hypothesized
relationships among these constructs.
Criterion-related validity can be assessed by
examining concurrent validity. Concurrent validity is
relevant in psychological tests for the diagnosis of an
existing status, rather than the prediction of future
outcomes [Anastasi, 1976]. Concurrent validity is used as
a substitute for predictive validity when it is
impractical to extend the validation procedures over time,
as in this study. Questions must be phrased so that they
do not attempt to predict an outcome- The questions used
in this study are not phrased to be predictive.
Evidence of concurrent validity can be obtained by
examining the relationships among the constructs based on
some criteria. For example, professional and
organizational commitment are hypothesized to be
significantly related in a positive direction. The
Pearson correlation coefficient for this relationship is
.768, significant at the .0001 level. The correlations
reported in Table 5.5 give evidence of concurrent validity
among the constructs. The correlations among the
constructs are statistically significant in a positive
direction as hypothesized in this study.
101
Hypothesis Testing
Rather than freeing the individual hypothesized
causal links in the model, referred to as a one-step
approach [Anderson and Gerbing, 1988] (see Appendix D for
the results of this approach), a two-step approach is used
to test the hypotheses. With a two-step approach the
structural model is tested first, and second, a series of
nested structural models are estimated and sequential chi-
square difference tests (SCDTs) are performed [Anderson
and Gerbing, 1988]. This is accomplished by estimating a
null model in which the beta, gamma, and phi parameters
are fixed at zero. This model gives the largest number of
degrees of freedom for any structural model. Next, a
saturated model in which the beta, gamma, and phi
parcimeters are free is then estimated. This model gives
the smallest number of degrees of freedom for any of the
models under consideration. The theoretical (research)
model under investigation is then estimated. Finally, two
additional structural submodels are estimated, which are
the "next most likely constrained and unconstrained
alternatives from a theoretical perspective to the
substantive model of interest" [Anderson and Gerbing,
1988, p. 418]. These five models are referred to as the
null, saturated, theoretical, constrained, and
unconstrained models. These five structural submodels are
102
nested in a sequence such that, for the number of
parameters to be free, the null < constrained
< theoretical < unconstrained < saturated. Sequential
chi-square difference tests for the five nested models are
performed after it is first assessed whether a structural
model exists that would have an acceptable goodness-of-
fit.
Testing a nested sequence of models using a chi-
square difference test rather than testing individual
paths is preferred [Anderson and Gerbing, 1988] and is
recommended in research literature (for example, Bentler
and Bonett, 1980; James, Mulaik, and Brett, 1987; Bollen,
1989). Anderson and Gerbing [1988] cite four strengths
that the two-step approach has over a one-step approach.
These strengths are:
First, it allows tests of the significance for all pattern coefficients. Second, the two-step approach allows an assessment of whether any structural model would give acceptable fit. Third, one can make an asymptotically independent test of the substantive or theoretical model of interest. Finally, the two-step approach provides a particularly useful framework for formal comparisons of the substantive model of interest with next most likely theoretical alternatives, [p. 422]
The Structural Model
To determine if any structural model has an
acceptable goodness-of-fit, a "pseudo" chi-square test
statistic is calculated (Anderson and Gerbing, 1988,
103
p. 418). The pseudo chi-square test statistic is
comprised of the results from two different models, the
saturated and null models. The chi-square value of the
saturated model and the degrees of freedom from the null
model are used to test for significance. The saturated
model has the smallest value for any structural model
since all of the parameters are free, while the null model
has the largest number of degrees of freedom since all of
the parameters are fixed. If this test statistic is
significant, then there is no structural model that would
give an acceptable fit. This is because any alternative
models would have fewer degrees of freedom than the null
model, with a chi-square value greater than or equal to
the saturated model.
Table 5.7 presents the results of the pseudo chi-
square test statistic. The test statistic is significant
which could indicate a misspecification of the measurement
model [Anderson and Gerbing, 1988]. The measurement model
was reexamined by investigating modification indices
obtained in the LISREL output, and attempting to further
refine the composite indices. No further respecification
could be done to obtain a measurement model that would
produce an acceptable pseudo chi-square test statistic.
Anderson and Gerbing [1988] stated:
. . . a researcher can build a measurement model that has the best fit from a content and
104
TABLE 5.7 PSEUDO TEST STATISTIC FOR THE NULL AND SATURATED MODELS
Saturated Model Chi-square Test Value 436.74
Null Model Degrees of Freedom 106
Significance Level < .001
105
statistical standpoint, where respecification may have been employed to accomplish this, and still provide a statistical assessment of the adequacy of the theoretical model of interest, [p. 419]
In this study the measurement model is deemed to have the
"best fit." The improvement in fit of the null versus the
saturated model is highly significant as illustrated in
Table 5.8 [Bentler and Bonett, 1980]. Also, the goodness-
of-fit index of .990 demonstrates that the remaining
improvement of .01 (1.00-.990) that might be obtained if
the measurement model is improved is not significant from
a practical viewpoint [Bentler and Bonett, 1980]. The
next step after the structural model has been tested for
goodness-of-fit is to compare alternative models using
sequential chi-square difference tests (SCDTs).
Sequential Chi-sguare Difference Tests
After the saturated model is evaluated, a decision-
tree approach is used to test sequential chi-square
differences for the models. Figure 5.5 illustrates the
order of testing the nested models for SCDTs [Anderson and
Gerbing, 1988]. The null hypothesis to compare a set of
SCDTs is that there is no significant difference between
two nested structural models based on the difference in
chi-square values and the difference in degrees of
freedom. For each SCDT in which the null hypothesis is
not rejected, the model that is more constrained (i.e.,
106
TABLE 5.8 COMPARISON OF THE NULL AND SATURATED MODELS
Chi Significance Model Square Difference D.F Level
Null 10693.69 — 106 1
Saturated 436.74 10256.95 88 .001
1 Difference in degrees of freedom, 18, with difference
in the chi-square value, 10256.95.
107
MC - MS
sign
accept MC
accept MI
acceoc MU
MC - Ms — ^ accept He
sign
V ns MI - .MU ;^—^ Respecify MU as alternaie
mcd<l Hu'; then Ni - Mu'
sicn .-.s Mu - MS
sicn
^ accept M;
Relax ccnstrai.-t m MU t. a: is next jicst-lixeiy model Mu2; then Mu: - MS.
ns - not significant at specified crctability i*v€2 Sign - significant at specified profcatiiity level Mt - theoretical model MS - saturated acdel MC - constrained model MU - unconstrained model
Figure 5.5. Decision-Tree Framework for SCDTs
108
more fixed parameters) would be accepted. To test the
null hypothesis, a chi-square test statistic value is
calculated for the saturated, constrained, theoretical,
and unconstrained models.
The first SCDT test is between the theoretical and
saturated model. The chi-square values and associated
degrees of freedom are presented in Table 5.9. The five
relationships not hypothesized in the theoretical model
(SM->PC, SM->LSCD, JS->OC, JP->OC, and SM->OC) represent
the five degrees of freedom difference. Since
constraining these causal links does not make a
statistically significant difference at the .001 level,
the hypothesis that there is no significant difference
between the two models is not rejected. Therefore, the
second SCDT is between the theoretical and constrained
models.
Constraining additional parameters should be done
from a theoretical perspective by seeking a "weak-link" in
the theoretical model. One method of constraining or
unconstraining paths is to examine the modification
indices provided by LISREL. The modification index is "a
measure of predicted decrease in chi-square if a single
constraint is relaxed and the model is reestimated"
[Joreskog and Sorbom, 1989b]. Theoretical justification
should be the prime criterion for constraining or
109
TABLE 5.9 COMPARISON OF THE THEORETICAL AND SATURATED MODELS
Chi Significance Model Square Difference D.F Level
Theoretical 447.94 93 1
Saturated 436.74 11.20 88 < .05
1 Difference in degrees of freedom, 5, with difference in
the chi-square value, 11.20.
110
unconstraining paths between constructs. Bagozzi and Yi
[1988] stated:
Changing a model by indiscriminatly freeing parameters suggested by modification indices is of course an example of capitalizing on chance. One should avoid relying on such a practice except perhaps in the most exploratory of studies. As a matter of fact, models should not be modified unless one has theoretical and/or methodological reasons justifying any modification, [p. 81]
An examination of the modification indices resulted in a
decision not to constrain or free any of the paths based
solely on these indices.
Based on prior research that also used professionals
as subjects, the path job satisfaction—>job performance
will be constrained. Bagozzi [1980], using professional
salespeople as subjects, hypothesized that job performance
will influence job satisfaction, but that job satisfaction
will not significantly affect job performance. His
theoretical rationale for the job performance—>job
satisfaction sequence is that an individual will form
positive or negative feelings (job satisfaction) after
outcomes on the job (job performance) are obtained, and
compared to the expected and obtained rewards. Bagozzi
[1980] believed that the job satisfaction—>job
performance sequence was more difficult to justify for two
reasons. First, a person must be aware of his/her
feelings (job satisfaction) and attribute these feelings
to specific aspects of the job (job performance). Second,
111
feelings have many antecedents that may not necessarily be
related to job performance. Bagozzi [1980] reported that
job satisfaction did not have a statistically significant
impact on job performance, and job performance had a
statistically significant impact on job performance.
Table 5.10 shows the result of constraining the job
satisfaction—>job performance path. There is a
statistically significant result that indicates that this
path is significant in the theoretical model and should
not be constrained. The null hypothesis that there is no
significant difference between the two nested structural
models is rejected. These results differ from those
reported by Bagozzi [1980]. An explanation for this could
be the difficulty in explaining causality between these
two constructs (for example, Lawler and Porter, 1967;
Porter and Lawler, 1968; Lawler, 1971; Ross and Bomeli,
1971; Benke and Rhode, 1980).
The next SCDT is between the theoretical and
unconstrained model. As with the constrained model,
parameters that are freed in the unconstrained model
should be done in a theoretical perspective. The
parameter that is freed in the unconstrained model is the
sequence job satisfaction—>organizational commitment. As
in this study, other studies have used organizational
commitment as an antecedent to job satisfaction (for
112
TABLE 5.10 COMPARISON OF THE THEORETICAL AND CONSTRAINED MODELS
JOB SATISFACTION—>JOB PERFORMANCE CONSTRAINED
Chi Significance Model Square Difference D.F Level
Constrained 1008.85 94 1
Theoretical 447.94 560.91 93 < .001
1 Difference in degrees of freedom, 1, with difference in
the chi-scjuare value, 560.91.
113
example, Aranya, Lachman, and Amernic, 1982; Hunt, Chonko,
and Wood, 1985; Harrell, Chewning, and Taylor, 1986).
Still other studies have used job satisfaction as an
antecedent to organizational commitment (for example.
Steers, 1977; Zahra, 1984). In these latter studies, job
satisfaction was classified as an attitudinal variable
that precedes organizational commitment.
Table 5.11 presents the results of the SCDT between
the theoretical and unconstrained models. Freeing the
parameter between job satisfaction and organizational
commitment did not result in a statistically significant
change in the chi-square value based on the change in the
degrees of freedom. The null hypothesis that there is no
significant difference between the two nested structural
models is not rejected. Since this path is not
significant and does not contribute to the explanation of
the construct covariances, the theoretical model would be
tentatively accepted.
Evaluating the Theoretical Model
Even though the theoretical model has been
tentatively accepted using the decision-tree framework for
SCDTs, further evaluation is needed to justify accepting
the theoretical model. Anderson and Gerbing [1988]
recommend practical in addition to statistical
considerations. Also, relationships that were
114
TABLE 5.11 COMPARISON OF THE THEORETICAL AND UNCONSTRAINED MODELS
JOB SATISFACTION—>0R(3ANIZATI0NAL COMMITMENT UNCONSTRAINED
Chi Significance Model Square Difference D.F Level
Theoretical 447.94 93 1
Unconstrained 445.49 2.45 92 > .10
1 Difference in degrees of freedom, 1, with difference in
the chi-square value, 2.45.
115
hypothesized to be statistically significant but were not
should be examined.
Practical considerations involve assessing the
goodness-of-fit for the models, in addition to chi-square
test statistics. This is because the value of the chi-
square test statistic is dependent on the size of the
sample. If the sample is large, significant values can be
obtained even if there are only small discrepancies
between the data and model [Anderson and Gerbing, 1988].
Therefore, goodness-of-fit from a practical standpoint
should be considered along with SCDTs. Table 5.12
presents the results of the goodness-of-fit indices,
adjusted goodness-of-fit indices, and root mean square
residuals for each of the models under consideration.
These three assessments are measures of the overall fit of
the model to the data [Joreskog and Sorbom, 1989a].
Goodness-of-fit indices fall between zero and one,
with a desired value of .90 or greater [Bagozzi and Yi,
1988]. The adjusted goodness-of-fit index adjusts the
goodness-of-fit index for the degrees of freedom in the
model. For all of the models, both the goodness-of-fit
indices and the adjusted goodness-of-fit indices surpass
the desired value of .90. The root mean square residual
is the measure of the average of the fitted residuals
[Joreskog and Sorbom, 1989a]. A root mean square residual
116
TABLE 5.12 GOODNESS-OF-FIT INDICES AND ROOT MEAN SQUARE RESIDUALS
FOR THE THEORETICAL, SATURATED, CONSTRAINED, AND UNCONSTRAINED MODELS
Model Goodness-of • Fit Index
Adjusted Goodness-of- Root Mean Fit Index Square Residual
Theoretical .990
Saturated .990
Constrained .978 (JS—>JP)
Unconstrained .990 (JS—>0C)
986
985
968
986
.044
.041
.047
.043
117
of .05 or less is considered an acceptable value to
indicate a good fit [Bagozzi and Yi, 1988]. For all of
the models, the root mean square residual is less than the
.05 criterion. Considering these additional assessments
of the models, all are acceptable. The differences in the
goodness-of-fit indices, adjusted goodness-of-fit indices,
and root mean square residuals are marginal. Since the
SCDTs favor the theoretical model, and the additional
assessments of the theoretical model are acceptable, the
theoretical model is still chosen over the other models.
Inferences about the relationships between constructs
should be made only if they are based on established
principles of scientific inference [Anderson and Gerbing,
1988]. Theory for the theoretical model was established
in the first four chapters of this study. The values
reported in Appendix D support seven of the twelve
hypotheses posited in this study. The five hypotheses (in
alternate form) that were rejected based on statistical
significance should be investigated for other
possibilities. These hypothesized relationships did not
significantly contribute to the theoretical model. These
five hypotheses and associated values are reported in
Table 5.13.
The first hypothesis not accepted is H4, which
posited a positive relationship between professional
118
TABLE 5.13 LISREL VALUES—NONSIGNIFICANT RELATIONSHIPS
1 Hypothesis Value Significance Level
PC->JP/H4 -.901 > .10
LSCD->JP/H6 -1.008 > .10
SM->JS/H7 1.559 > .05
SM->JP/H8 -.962 > .10
LSCD->0C/H12 -.722 > .10
1 The significance of the values are based on a
comparison to a normal distribution table.
119
commitment and job performance. Ferris [1981] described
conflicting findings on the relationship between
commitment and performance, in which highly committed
employees outperform less committed employees, and other
situations in which these two constructs are unrelated [p.
317], In this study, the lack of relationship may be
attributable to the lack of importance placed on
professional commitment for job performance evaluation.
Ramanathan et al. [1976] reported that managing partners
rated personal professional development as the least
important factor for public accounting firms' success,
while staff accountants would like to see additional
professional-oriented factors used in performance
evaluation. This may indicate that staff accountants do
not perceive professional commitment as being an important
factor in job performance evaluations, even though they
would like to see this considered as an important element
in performance evaluation.
Hypotheses six and twelve theorized a significant
positive relationship between life-span career
development, and job performance and organizational
commitment. The results of this study show that both of
these relationships are not significant. These results
may be explained by prior research.
120
Earnest and Lampe [1987] investigated behavioral
choice processes and turnover, reporting that lower level
auditors compared auditing unfavorably with job
alternatives on two intrinsic and two extrinsic factors.
The intrinsic factors are "the feelings experienced as a
result of working on the types of tasks assigned and as a
result of attainment of the task-related goals" [p. 236].
The unfavorable extrinsic factors are performance-
contingent financial compensation and rewards of adequate
leisure time. The unfavorable comparison of auditing with
alternative jobs may explain the negative relationship
between life-span career development and organizational
commitment. Extrinsic rewards such as those reported by
Earnest and Lampe [1987] are associated with the
organization as a whole. If staff auditors feel that
there are alternative jobs that have better extrinsic
rewards, then there may be dissatisfaction with public
accounting as a career choice, and thus lower
organizational commitment. An additional explanation may
be that some individuals enter the public accounting
profession to meet state experience requirements to be a
licensed certified public accountant.
Harrell and Eickhoff [1988] reported that when an
individual's intrinsic needs are not congruent with the
demands of a work environment, he/she is likely to react
121
negatively to that environment (such as job performance),
and seek a more congruent alternate work environment.
These individuals are more likely to express negative
career intentions than individuals who are influence-
oriented, that is, individuals with relatively high power
needs.
It appears that prior research indicates a
relationship between career intentions, organizational
commitment, and job performance based on intrinsic and
extrinsic factors. In this study, these factors were not
considered and may influence the results of hypotheses six
and twelve.
Hypotheses seven and eight posited a positive
relationship between the level of self-monitoring, and job
satisfaction and job performance. The results of this
study are that there is not a statistically significant
relationship between the level of self-monitoring, and job
satisfaction and job performance. Prior research has not
investigated the relationship between these constructs,
making these hypotheses exploratory.
It appears that accountants, as professionals, have
the ability to adapt, or the appearance of adapting, and
thus there is no effect on their perceptions of how they
perform on the job. The relationship between self-
monitoring and job satisfaction was marginally not
122
significant (<.10) at the .05 level. The lack of
statistical support for this hypothesis indicates that
self-monitoring does not make a contribution as an
attitude towards one's level of job satisfaction.
Summary of the Data Analysis
The results of the sequential chi-scjuare difference
tests support the acceptance of the theoretical model over
alternative models. This series of testing "provides
further understanding of the explanatory ability afforded
by the theoretical model of interest" [Anderson and
Gerbing, 1988, p. 419]. The goodness-of-fit index,
adjusted goodness-of-fit index, and root mean square
residual are very good for the theoretical model. In
addition, Bagozzi [1984] stated that rival hypotheses
should be considered in theory construction, and that
these hypotheses should be tested within the same study.
This study considered rival hypotheses by testing and
comparing the constrained and unconstrained models with
the theoretical model.
Significant relationships were evidenced by the
values obtained from the LISREL output. The alternate
hypotheses for the relationships OC->JS, OC->JP, PC->JS,
LSCD->JS, JS->JP, JP->JS, PC->OC, and PC<->LSCD are
supported by the data. Table 5.14 summarizes the
significant and nonsignificant relationships hypothesized
123
TABLE 5.14 LISREL VALUES—ALL HYPOTHESES
Hypothesis
0C->JS/H1
0C->JP/H2
PC->JS/H3
PC->JP/H4
LSCD->JS/H5
LSCD->JP/H6
SM->JS/H7
SM->JP/H8
JP->JS/H9
JS->JP/H9
PC->OC/H10
PC<->LSCD/H11
LSCD->0C/H12
Value
8.430
-6.253
-2.974
-.901
4.565
-1.008
1.559
-.962
-14.212
37.076
12.024
51.829
-.722
1 Significance Level
.001
.001
.001
> .10
.001
> .10
> .05
> .10
.001
.001
.001
.001
> .10
1 The significance of the values are based on a
comparison to a normal distribution table.
124
in this study. Figure 5.6 presents the research model and
summarizes the results of the individual hypotheses in
terms of significant and nonsignificant relationships.
The results provide insight into the relationships
among the constructs. Job performance and job
satisfaction are affected by the level of organizational
commitment possessed by staff accountants. life-span
career development has been shown to have an effect on job
satisfaction and is significantly related with
professional commitment among staff accountants.
Professional commitment has a significant effect on
organizational commitment and job satisfaction among staff
accountants. There are reciprocal effects between job
satisfaction and job performance for staff accountants.
These findings and their implications, additional areas of
potential research, and the limitations of this study are
discussed in the next chapter.
125
sign - significant at .001 probability level ns - not significant at .001 probability level
Figure 5.6. Research Model—Results of Hypotheses Testing
126
CHAPTER VI
SUMMARY AND CONCLUSIONS
In Chapter V, a two-step approach was used to test
the research model. First, the measurement model was
examined and refined. Next, SCDTs were performed to
assist in choosing the model that theoretically and
statistically provided the best information. Last, other
considerations for choosing the model were examined, such
as goodness-of-fit indices, root mean square residuals,
and individual paths between the constructs.
This chapter summarizes the results of the analyses.
Contributions and limitations of the study are presented,
and recommended areas of future research are given.
Summary of the Findings and Implications
The purpose of this study was to investigate
relationships among the constructs professional
commitment, life-span career development, self-monitoring,
organizational commitment, job satisfaction, and job
performance. The relationships among these constructs
were presented in three research objectives: (1)
investigate the effects of organizational commitment,
professional commitment, life-span career development, and
self-monitoring on job satisfaction and job performance
for staff accountants in public accounting firms; (2)
127
investigate the relationship between job satisfaction and
job performance of staff accountants in public accounting
firms; and (3) investigate the relationship among
organizational commitment, professional commitment, and
life-span career development for staff accountants in
public accounting firms. These research objectives will
be discussed based on the results of this study.
Research Objective One
Job performance and job satisfaction were the primary
constructs in this study. To investigate research
objective one, they were treated as endogenous constructs,
which were affected by organizational commitment,
professional commitment, self-monitoring, and life-span
career development. These relationships were posited in
the first eight hypotheses. The effects of organizational
commitment, professional commitment, self-monitoring, and
life-span career development on job satisfaction will be
discussed first, followed by their effects on job
performance.
Hypothesis seven, the effect of self-monitoring on
job satisfaction was not significant and its implications
were discussed in Chapter V. The remaining three
constructs, professional commitment, organizational
commitment, and life-span career development all had
128
significant effects on job satisfaction (see Appendix D,
Table D.4).
The significant effects of professional and
organizational commitment on job satisfaction among staff
accountants suggests that even at the entry-level
position, staff accountants' attitudes toward the
profession and organization will directly affect their
level of job satisfaction. These results support the
earlier work of Norris and Niebuhr [1983], which showed
significant correlations between professional and
organizational commitment, and job satisfaction. However,
Norris and Niebuhr [1983] used all job levels of public
accounting firms, rather than just staff accountants.
The significant positive relationship between life
span career development and job satisfaction supports
hypothesis five. The result suggests that the further
along individuals are in their implementation stage of
career development, the more satisfied they are with their
job.
Hypotheses four, six, and eight posited a
relationship between job performance and professional
commitment, life-span career development, and self-
monitoring, respectively. These relationships were not
significant, and were discussed in Chapter V.
129
Hypothesis two, the relationship between
organizational commitment and job performance was
significant. These results are partially consistent with
the findings of Ferris [1981] who reported that junior-
level accountants were willing to exert considerable
effort on the job (job performance) on behalf of the
organization, rather than exert effort on the job because
they desired to maintain membership in the organization.
Ferris reported his significant, positive results on the
basis of correlations between the constructs. The
correlations between these two constructs in this study
were also significant and positive. However, under
structural equation modeling, this study reports a
significant but negative relationship between these two
constructs. This may be explained by the high turnover
rates reported in empirical accounting studies (for
example, Bao, Bao, and Vasarhelyi, 1986; Lampe and
Earnest, 1984; Rhode, Sorensen, and Lawler, 1976).
Ferris [1981] reported that nonperformers are
generally not retained by the firm; therefore, there is no
desire to maintain a strong sense of organizational
commitment. In addition, on average, 50% of all employees
leave the firm in the first few years, and less than 25%
attain managerial positions [Ferris, 1981]. Approximately
47% of the respondents in this study had one or more years
130
of experience with the firm. It is possible that some of
the respondents were considering leaving the firm. If
this is true, then there may not be a decrease in job
performance because of the importance of maintaining good
references and professional relationships with the firm,
for future positions outside the firm. Therefore, job
performance can increase with a simultaneous decrease in
the level of organizational commitment.
Research Objective Two
Research objective two was to investigate the
relationship between job satisfaction and job performance
of staff accountants in public accounting firms.
Hypothesis nine posited a significant, nonrecursive
relationship between these two constructs, which was
supported by the results of this study.
The relationship job satisfaction—>job performance
is positive. This suggests that as the level of job
satisfaction increases, so does the level of job
performance. Chapter V discusses the results of treating
this relationship as recursive; that is, no significant
relationship exists in the path job satisfaction—>job
performance.
The relationship job performance—>job satisfaction,
while significant, is negative. This suggests that as job
performance increases, job satisfaction decreases.
131
Job performance may be increasing based on a learning
curve, or some other factors. While staff accountants may
perceive themselves as performing better over time on the
assigned jobs, overall they may not be satisfied with
their jobs. There could be two reasons for these results.
First, it is possible that the same effects discussed
above on job performance and organizational commitment are
occurring in this relationship. While performance is
increasing over time, so is the likelihood of migration
from the firm. Another explanation is that the tasks may
not be as challenging as a staff accountant would like,
and the repetitive nature of the tasks could lead to job
dissatisfaction. Norris and Niebuhr [1983] reported that
job satisfaction decreases for accountants early in their
careers due to the work, self, and home.
Research Objective Three
The third research objective was to investigate the
relationship among organizational commitment, professional
commitment, and life-span career development for staff
accountants in public accounting firms. Hypothesis twelve
posited a positive significant relation between life-span
career development and organizational commitment. This
hypothesis was rejected and discussed in Chapter V.
"Hypothesis ten stated that a staff accountant's
organizational commitment will be directly predicted by
132
professional commitment. This hypothesis was not
rejected, supporting previous empirical studies in
accounting research (for example, Aranya, Lachman, and
Amernic, 1982; Lachman and Aranya, 1986).
Hypothesis eleven posited a significant positive
relation between professional commitment and life-span
career development. This hypothesis was not rejected as
evidenced by the statistically significant covariance
among these two exogenous concepts in matrix phi. This
covariance "parallels the correlation between predictor
variables in multiple regression" [Hayduk, 1987, p. 94].
This suggests that as staff accountants progress further
through the implementation stage of their career
development, their level of commitment to the profession
should also increase.
The use of structural equation analysis to examine
the hypothesized relationships cimong the constructs is a
positive characteristic of this study. A two-step
approach was used, which tests the measurement model prior
to testing the structural submodels. This approach is
considered superior to the traditional approach of testing
individual paths using structural equations [Anderson and
Gerbing, 1988].
The results of the study should also be considered in
light of its limitations and contributions. The next
133
section will discuss these as they apply to the research
design and results of the data analysis.
Contributions
Caplan [1989] discussed the need to examine the
behavior of individuals in public accounting firms. One
of the contributions of this study is the addition to this
body of literature by investigating the relationships of
professional commitment, life-span career development,
self-monitoring, and organizational commitment with job
satisfaction and job performance among staff accountants
in public accounting firms.
Job satisfaction and job performance are constructs
of interest in empirical studies among numerous
disciplines (see footnote 1, Chapter II). The constructs
self-monitoring and life-span career development have not
been used in published empirical studies using job
satisfaction and job performance as endogenous constructs.
Also, a research instrument was developed to measure the
implementation stage of an individual's career
development.
This study used only staff accountants as subjects,
which provides information on a large segment of
professional accountants. For public accounting firms,
this-study provides information that may be useful in
personnel decisions. The importance of maximizing job
134
satisfaction and job performance among employees within
organizations is continually sought by managers.
Maximizing job satisfaction and job performance may lead
to higher productivity, lower overall costs for the firm,
and reduced turnover of employees. While attrition may be
necessary in the public accounting profession due to the
limited number of supervisory and managerial positions,
early detection can diminish the premature or unexpected
attrition of employees whom the firm would like to retain.
In addition, better understanding of the relationship
between job satisfaction and job performance may lead to
minimizing expenditures to increase job performance, job
satisfaction, and costs associated with employee turnover.
Limitations
The subjects were all employees of one office of a
national public accounting firm. As noted earlier, all of
the subjects were staff accountants. This limits the
generalizability of the results to other firms and job
levels.
When nonresponse cannot be eliminated, there is the
possibility of nonresponse bias. Attempts were made to
maximize the response rate by including a stamped self-
addressed envelope, and a letter from a partner in the
firm encouraging participation, with each research
instrument. A follow-up letter was sent to all subjects
135
from a partner in the firm encouraging them to complete
and mail back the research instrument if they had not
already done so. Tests for nonresponse bias were
performed to see if there was a difference between early
and late respondents. While these tests did not indicate
nonresponse bias, it is always possible that nonresponse
bias is present. The overall response rate for this study
was 74%.
Lack of precision in measurement is a possibility in
survey research. With the exception of life-span career
development, the survey questions had been used in
previous empirical studies. While this does not guarantee
reliability and validity, it provides support for the use
of these questions in this study. The questions for life
span career development were created for this study.
Pretesting was undertaken to support the use of these
questions. Attempts were made to respecify the
measurement model to increase the reliability of the
research instrument. Even with due care, the possibility
of measurement error exists when doing survey research.
Future Research
This study can lead to additional research in the
area of job satisfaction and job performance among
accountants. Comparisons can be made between staff
accountants, managers, and partners with the constructs
136
used in this study. Further stages of life-span career
development can be investigated with managers and partners
as subjects. Additional constructs could be used to
investigate job satisfaction and job performance.
The study can be expanded by surveying staff
accountants, managers, and partners employed in public
accounting firms nationwide. This would increase the
generalizability of the results.
Accountants not employed in public accounting could
be used as subjects, and comparisons can be made between
groups. This would include accountants employed in
private industry, not-for-profit organizations, and
education.
Finally, a study of this type could be used to
investigate how the constructs relate to job turnover.
This would entail a longitudinal study, in which a model
predicated on job satisfaction and job performance would
be developed to attempt to predict job turnover.
137
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139
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140
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141
Harrell, A. and R. Eickhoff. "Auditors' Influence-Orientation and Their Affective Responses to The "Big Eight" Work Environment." Auditing: A Journal of Practice & Theory (Spring 1988): 105-118.
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142
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, D. Watson, and J. Baumler. "An Examination of Performance Evaluation Decisions in CPA Firm Subunits." Accounting, Organizations and Society (1983): 13-29.
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143
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144
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145
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146
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147
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149
APPENDIX A
RESEARCH INSTRUMENT
150
FOR YOOa ACTIOH Memorandum
0 All Persoaael DUtribudoQ
Limiud DLstribudon: Partners Maiugers Audit • f TAX • • .MC • f Admin. 0
SuiT t •
•
0
Secrcttries 0 0 0
° TO: All Professional Personnel
FROM:
DISSERTATION QUESTIONNAIRB
Attached is a questionnaire which all office professionals are being asked to complete in order to assist a doctoral student with his dissertation. A high response rate is critical to the success of the dissertatloo. The Firm has committed Its assistance to this project and therefore, I urge each of you to take the time to complete this questionnaire. Thank you for your cooperation.
151
Peter John Poznanski, CPA 3219 Chadwick Drive Rockford, II. 61109
Certified Public Accountants
Dear
Attached is a copy of a questionnaire I will be using in my doctoral dissertation. Your assistance in answering the questions will facilitate my completing the dissertation required for my degree, and contribute to the body of knowledge in accounting.
All of your responses will be kept in the strictest of confidence, known only to myself. In no way will this questionnaire identify you, nor will any attempt be made to identify you by your responses. The first page requesting the demographic information will be detached from the questionnaire when I receive it, and the questionnaires and demographic data sheet will be destroyed as soon as the data is entered into the computer. You can return the completed questionnaire in the attached self-addressed st£unped envelope.
One of the more frustrating aspects of answering a questionnaire of this nature is not knowing the purpose behind the questions. The reason for this is that unconsciously you may bias your responses towards the answers you feel are appropriate rather than your true feelings. While I believe this point is debatable, it is a requirement imposed upon roe for this study. However, the time you take to answer the questions as best you can will greatly enhance the results of this study. This study will culminate four years of my graduate school work, so your responses are very important and very necessary to me.
The data analysis and the dissertation should be completed early next year. I will be sending
a copy of the completed study. If you are interested in receiving a copy of the results please retain my address and contact roe. I will be happy to share a copy of the results with you. Thank you for taking the time to help roe complete ray schooling and study.
Sincerely,
Peter John Poznanski, CPA
152
Demographic Data
1. Age:
2. Sex:
3
4
5
6
7
Number of years in the public accounting profession: __
Years at current Firm:
Position at current Firm (Please circle the appropriate response): ^^ ^^^ixacc
Partner or Principal
Senior Manager
Manager
Senior Consultant
Supervising Senior, Audit
Supervising Senior, Tax
Senior Accountant, Audit
Senior Specialist, Tax
Consultant
Staff Accountant
Tax Specialist
Assistant Accountant
Assistant Tax Specialist
Intern
Preprofessional
Staff Technician
Paraprofessional
Administrative
Other (please specify):
Number of years in current Position:
College Degree(s) and Major and Minor course work for each degree:
8. Are you currently enrolled in a degree program, emd if so which degree are you working on?
9. Professional Certification(s) and the number of years with the Certification (e.g., CPA, two years):
153
Please c i r c l e the nmnber-frorn one to five--which best represents your gersonal fee l ings towards the accounting
Strongly Disagree
1 Disagree
2 Neutral
3 Agree 4
Strongly Agree 5
I am willing to put in a great deal of effort beyond that normally expected m order to help make my profession successful
I talk up this profession with my friends as a great profession to be associated with
I feel very little loyalty to this profession
I would accept almost any type of job assignment in order to keep working in areas that are associated with this profession
I find that my values and the profession's values are very similar...
I am proud to tell others that I am part of this profession
I could just as well be associated with another profession as long as the type of organization in which I worked were similar
Being a member of this profession really inspires the very best in roe in the way of job performance
It would take very little change in my present circumstances to cause me to work in areas that are not associated with this profession
I am extremely glad that I chose this profession over others I was considering at the time I joined
2
2
2
2
2
4
4
4
4
5
5
5
5
5
154
Strongly Disagree
1 Disagree
2 Neutral
3 Agree
4
Strongly Agree
5
There's not too much to be gained by sticking with this profession indefinitely 1
Often, I find it difficult to agree with this profession's policies on important matters relating to its members 1
I really care about the fate of this profession 1
For me this is the best of all professions to be a member of 1
Deciding to be a member of this profession was a definite mistake on my part 1
2
2
2
3
3
3
4
4
4
5
5
5
Please c i r c l e the number--frora one to five—which best represents your personal feelings on your performance of your present job.
Needs Unsatisfactory Improvement Satisfactory Superior Outstanding
1 2 3 4 5
Maintaining quantity of work
Maintaining quality of work
Communicating orally
Communicating in writing
Accepting responsibility and initiating action
Exercising professional skills and care
Following policies and procedures
Planning and organizing work
2
2
2
2
2
2
2
5
5
5
5
5
5
5
155
Needs Unsa t i s f ac to ry Improvement Sa t i s fac tory Superior Outstanding
1 2 3 4 5
Adapting to new or d i f f e r e n t job s i t u a t i o n s 1 2 3 4 5
G e t t i n g along with o the r s in the f i rm. . 1 2 3 4 5
Dealing with c l i e n t s outs ide the f i r m . . 1 2 3 4 5
Supervis ing others 1 2 3 4 5
P l e a s e c i r c l e the number—from one t o five—which best r e p r e s e n t s your personal feel ings towards your accounting c a r e e r .
St rongly Strongly Disagree Disagree Neutral Agree Agree
1 2 3 4 5
My previous education and training have given me adequate preparation for ray current pos i t ion 1 2 3 4 5
I have completed my training for my career 1 2 3 4 5
Ky current job is relevant to my career goals 1 2 3 4 5
I am considering changing careers 1 2 3 4 5
My current career offers job security.. 1 2 3 4 5
I feel that the amount of time that I will be required to stay in ny current position before I am eligible for a promotion is reasonable 1 2 3 4 5
I am satisfied with my career choice to be an accountant 1 2 3 4 5
I am not prepared for my current position 1 2 3 4 5
156
Please circle the number--from one to five--which best represents your personal feelings towards your present job.
Very Dissatisfied
1 Dissatisfied
2 Neutral
3 Satisfied
4
Very Satisfied
Being able to keep busy all the time...
The chance to work alone on the job
The chance to do different things from time to time
The chance to have some prestige in the community because of my job
The way my supervisor handles his/her people
The competence of my supervisor in making decisions
Being able to do things that don't go against my conscience
The way the job provides for steady employment
The chance to do things for other people
The chance to supervise other people...
The chance to do things that make use of my abilities
The way organizational policies are put into practice
My pay and the amount of work I do.
The chances for advancement ,
The freedom to use my own judgment.
The chance to try ray own methods of doing the job
The general working conditions
157
Very ^ Dissa t i s f i ed Dissat i s f ied Neutral Satisfied Sat is f ied
1 2 3 4 5
The way my co-workers get along with each other X 2 3 4
The feedback I get for doing an e f f e c t i v e job 1 2 3 4 s
The feel ing of accomplishment I get from the job ; 1 2 3 4 5
Please circle the number—from one to five—which best 5??h^wh?^h r^^ E^isonal feelings towards the orga^zation with which you are presently employed. Please"nite that
Strongly Disagree
1 Disagree
2 Neutral
3 Agree 4
Strongly Agree 5
I am willing to put in a great deal of effort beyond that normally expected in order to help this organization be successful ,
I talk up this organization with my friends as a great organization to be associated with
I feel very little loyalty to this organization
I would accept almost any ty];>e of job assignment in order to keep lurking for this organization
I find that ny values and the organization's values are very similar.
I am proud to tell others that I an part of this organization
I could just as well be working for a different organization as long as the type of work was similar
4
4
4
4
4
5
5
5
5
5
158
strongly Disagree
1 Disagree
2 Neutral
3 Agree 4
Strongly Agree 5
This organization really inspires the very best in me in the way of job performance 1
It would take very little change in my present circumstances to cause me to leave this organization 1
I am extremely glad that I chose this organization to work for, over others I was considering at the time I joined. 1
There is not too much to be gained by sticking with this organization indefinitely 1
Often, I find it difficult to agree with this organization's policies on important matters relating to its employees 1
I really care about the fate of this organization 1
For me this is the best of all possible organizations for which to work 1
Deciding to work for this organization was a definite mistake on my part 1
3
3
3
3
4
4
4
4
5
5
5
5
The statements on the following pages concern your personal reactions to a number of different situations. No two statements are exactly alike, so consider each statement carefully before answering. If a statement is TRUE or MOSTLY TRUE as applied to you, circle the word True next to the question. If a statement is FALSE or NOT USUALLY TRUE as applied to you, circle the word False next to the question.
I find it hard to imitate the behavior of other people
My behavior is usually an expression of my true inner feelings, attitudes, and beliefs
True
True
False
False
159
At-parties and social gatherings, I do not attempt to do or say things that others will like True False
I can only argue for ideas which I already believe True False
I can make impromptu speeches even on topics about which I have almost no information True False
I guess I put on a show to impress or entertain people True False
When I am uncertain how to act in a social situation, I look to the behavior of others for cues True False
I would probably make a good actor True False
I rarely need the advice of my friends to choose movies, books, or music True False
I sometimes appear to others to be experiencing deeper emotions than I actually am True False
I laugh more when I watch a comedy with others thain when alone True False
In a group of people I am rarely the center of attention True False
In different situations and with different people, I often act like very different persons True False
I aro not particularly good at making other people like roe True False
Even if I aro not enjoying royself, I often pretend to be having a good time. True False
I'm not always the person I appear to be True False
I would not change my opinions (or the way I do things) in order to please someone else or win their favor True False
I have considered being an entertainer. True False
160
In order to get along and be liked, I tend to be what people expect me to be rather than anything else True False
I have never been good at games like charades or improvisational acting True False
I have trouble changing my behavior to suit different people and different situations True False
At a party I let others keep the jokes and stories going True False
I feel a bit aw)cward in company and do not show up quite so well as I should.. True False
I can look anyone in the eye and tell a lie with a straight face (if for a right end) True False
I may deceive people by being friendly when I really dislike them True False
Please circle your responses to the following two questions.
Are you planning to leave the firm at which you are currently employed?
Yes Undecided No
Axe you planning to remain in the public accounting profession?
Yes Undecided No
Thank you very much for your time and assistance.
161
APPENDIX B
RESEARCH INSTRUMENT APPROVAL
162
TEXASXECH 0«f<t ol t rwifch S«r«<ei
8oi «*,'0/U66oci. r«i4t 71*01. IP 35/(BOH N j j
July 10, 1990
Dr. reter John Pozhanski Accounting Campus
Caar OiT. Pozhanski;
The Te.' as Tech University Committee for the Protection of Human Subjec t s has approved your project, "Tne Effects of Orga.'.izat lonal Commitment, Professional Commitment, Life Span Career Oevelopraent, and Self-Monitoring on Job Sat i s fac t icn and Job Performance Among Staff Accountants." The approval v i l l extend for one year from J u l y 31, 1990. You w i l l be reminded of the pending e x p i r a t i o n one month before your approval expires so that you .-nay request an e x t e n s i o n if you wish.
The best of luc)c on your project .
Sincerely,
Jaoes Saith Chairperson, Hunan Subjects Use Coocittee
JS/ah
•4A (qu*i Cop<yc«*^/'^"'"*'<"»« '*<i»0*» 'nuMuifOM'
APPENDIX C
DEMOGRAPHIC DATA AND DESCRIPTIVE
STATISTICS
164
TABLE C.I DEMOGRAPHIC DATA
1 Category Frequency of Responses
Sex-
Age-
Years
Years
Male Female No Response
21 22 23 24 25 26 27 28 29 Over 30 No Response
Professional 1/2-1 1 - 2 2 - 3 3 - 4
Over 4
With Current 1/2-1 1 - 2 2 - 3 3 - 4
Over 4
1 All frequencies
responses.
Accountant-
Firm-
-
total 281, the number of
146 134 1
10 59 57 45 46 28 7 4 6 18 1
151 61 42 20 7
158 65 37 16 5
usable
165
Construct
Organizational Commitment
Job Satisfaction
Job Performance
Professional Commitment
Life-Span Career Development
Self-Monitoring
TABLE DESCRIPTIVE
No.
281
281
281
281
281
281
C.2 STATISTICS
Mean
3.613
3.608
3.481
3.554
3.492
1.491
Std. Dev.
.611
.459
.514
.564
.518
.500
The responses, except for self-monitoring, were made on a five point Likert-type scale, where higher responses indicate stronger levels of the construct. The values for self-monitoring were either 1 (for low self-monitoring) or 2 (for high self-monitoring).
166
APPENDIX D
LISREL RESULTS FOR INDIVIDUAL
HYPOTHESES AND PARAMETERS
167
TABLE D.l TESTING INDIVIDUAL PHI
Model Chi-Square Difference D.F
Significance Level
Null (baseline) 10693.69 106
Relationship and Hypothesis Tested:
PC<->LSCD/H11 10333.55 360.14 105 .001
Significance level based on 1 degree of freedom difference and the change in the chi-square value.
168
TABLE D.l TESTING INDIVIDUAL PHI
Model Chi-Square Difference D.F
Significance Level
Null (baseline) 10693.69 106
Relationship and Hypothesis Tested:
PC<->LSCD/H11 10333.55 360.14 105 .001
Significance level based on 1 degree of freedom difference and the change in the chi-square value.
168
TABLE D.2 TESTING INDIVIDUAL BETAS—WITH PHI
1 Chi- Significance
Model Square Difference D.F Level
Null (baseline) 10333.55 105
Relationship and Hypothesis Tested:
0C->JS/H1
0C->JP/H2
JP->JS/H9
JS->JP/H9
10109.23
10321.76
9641.96
9824.16
224.32
11.79
691.59
509.39
104
104
104
104
.001
.001
.001
.001
Significance level based on 1 degree of freedom difference and the change in the chi-square value.
169
TABLE D.3 TESTING INDIVIDUAL GAMMAS—WITH PHI
Model Chi-Square Difference D.F
Significance Level
Null (baseline) 10333.55 105
Relationship and Hypothesis Tested:
PC->OC/H10
PC->JS/H3
PC->JP/H4
LSCD->0C/H12
LSCD->JS/H5
LSCD->JP/H6
SM->JS/H7
SM->JP/H8
5899.77
10264.41
10323.41
5949.34
10294.33
10263.84
10290.87
10333.43
4433.78
69.14
10.14
4384.21
39.22
69.71
42.68
.12
104
104
104
104
104
104
104
104
.001
.001
.005
.001
.001
.001
.001
> .10
Significance level based on 1 degree of freedom difference and the change in the chi-square value.
170
TABLE D.4 LISREL VALUES FOR THE HYPOTHESES
1 Significance
Hypothesis Value Level
0C->JS/H1
0C->JP/H2
PC->JS/H3
PC->JP/H4
LSCD->JS/H5
LSCD->JP/H6
SM->JS/H7
SM->JP/H8
JP->JS/H9
JS->JP/H9
PC->OC/H10
PC<->LSCD/H11
LSCD->0C/H12
8.430
-6.253
-2.974
-.901
4.565
-1.008
1.559
-.962
-14.212
37.076
12.024
51.829
-.722
.001
.001
.001
> .10
.001
> .10
> .05
> .10
.001
.001
.001
.001
> .10
The significance of the values are based on a comparison to a normal distribution table.
171
TABLE D.5 1 LISREL VALUES FOR LAMBDA Y AND LAMBDA X
Lambda Y
OCl 0C2 0C3 JSl JS2 JS3 JPl JP2 JP3
Lambda
OC 1 127 112
X
JS
1 63 67
JP
1 76 77
PC LSCD SM PCI 1 PC2 102 PC3 108 LSCDl 1 LSCD2 43 LSCD3 37 SM 1
The value 1 indicates that the starting values was set at 1 to link the specific indicator to the concept [Hayduk, 1987].
1 All values are significant at the .001 level.
172
Lambda
OCl 0C2 0C3 JSl JS2 JS3 JPl JP2 JP3
Lambda
PCI PC2 PC3 LSCDl LSCD2 LSCD3 SM
Beta
OC JS JP
Gamma
OC JS JP
TABLE D.6 STANDARDIZED SOLUTIONS
Y OC .862 .915 .880
X PC .862 .839 .883
OC
.671 -.467
PC .884
-.662 -.151
JS JP
.813
.832
.767 •
•
•
LSCD
.761
.677
.708
JS
1.431
LSCD -.057 .906
-.141
841 847 866
SM
.894
JP
-1.007
SM
.131 -.102
173