the antecedents and consequences of the variability in job satisfaction

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THE ANTECEDENTS AND CONSEQUENCES OF THEVARIABILITY IN JOB SATISFACTION

by

LINDSEY M. KOTRBA

DISSERTATION

Submitted to the Graduate School

of Wayne State University,

Detroit, Michigan

in partial fulfillment of the requirementsfor the degree of

DOCTOR OF PHILOSOPHY

2007

MAJOR: PSYCHOLOGY

(Industrial/Organizational Psychology)

Approved by:

______________________________Advisor Date

______________________________

______________________________

______________________________

______________________________



UMI Number: 3277931

3277931

2007

Copyright 2007 by

Kotrba, Lindsey M.

UMI Microform

Copyright All rights reserved. This microform edition is protected against

unauthorized copying under Title 17, United States Code.

ProQuest Information and Learning Company300 North Zeeb Road

P.O. Box 1346 Ann Arbor, MI 48106-1346

All rights reserved.

by ProQuest Information and Learning Company.



© COPYRIGHT BY

LINDSEY M. KOTRBA

2007

All Rights Reserved



ii

DEDICATION

For my husband, Chad. I could never thank you enough.



iii

ACKNOWLEDGMENTS

First and foremost, I would like to thank my advisor, Dr. Boris Baltes. I am

sincerely grateful for the guidance, encouragement and advice that he provided on

the subject of this dissertation. Beyond that, I need to thank him for all of the

opportunities and support he provided me throughout my graduate career. I truly

appreciate everything. Thank you.

I am also grateful to my committee members, Dr. Marcus Dickson, Dr. Ty

Partridge and Dr. Loraleigh Keashly. Their input has been highly valued and I thank

them for their time and interest in this project.



iv

TABLE OF CONTENTS

Chapter Page

DEDICATION....................................................................................................ii

ACKNOWLEDGMENTS .................................................................................. iii

CHAPTERS

CHAPTER 1 – Introduction ....................................................................1

Overview………………………………………………………………..1

Job Satisfaction: A Review……………………………………………2

The Person-Situation Debate…………………………………………4Within Subject Variability in Job Satisfaction: The New Frontier..10

The Present Study……………………………………………………15

The Antecedents of Job Satisfaction Variability…………………..18

The Consequences of Job Satisfaction Variability………………..25

CHAPTER 2 – Method………………………………………………………31

Participants…………………………………………………………….31

Measures………………………………………………………………33

Procedure………………………………………………………………36

CHAPTER 3 – Results………………………………………………………39

CHAPTER 4 – Discussion…………………………………………………..55

TABLESTable 1: Demographic Characteristics of the Sample……………………69

Table 2: Cronbach’s Alpha by Facet: Average of a Random Sample of

Time Points…………………………………………………………70



v

Table 3: Means and Standard Deviations of Facets: Across all

Time Points..……………………………………………………..71

Table 4: Means and Standard Deviations of Frequency Variation for

Each Facet of Job Satisfaction…………………………………72

Table 5: Means and Standard Deviations of Amplitude Variation for

Each Facet of Job Satisfaction…………………………………73

Table 6: Intercorrelations Amongst Study Variables.…………………..74

Table 7: Regressing Job Satisfaction Frequency and Amplitude

Variation on Personality…………………………………………75Table 8: Regressing Job Satisfaction Frequency and Amplitude

Variation on Job Stressor Frequency and Amplitude

Variation…………………………………………………………..77

Table 9: Summary of Hierarchical Regression Analyses Examining

The Moderating Effect of Personality on the Relationship

Between Frequency Variation in Job Stressors and Frequency

Variation in Pay Satisfaction……………………………………..78


the Moderating Effect of Personality of the Relationship

Between Frequency Variation in Job Stressors and Frequency

Variation in Promotion Satisfaction.…………………………….79



Between Frequency Variation in Job Stressors and



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Frequency Variation in Supervisor Satisfaction..……………..80


the Moderating Effect of Personality of the RelationshipBetween Frequency Variation in Job Stressors and

Frequency Variation in Coworker Satisfaction……………….81



Between Frequency Variation in Job Stressors and

Frequency Variation in Nature of Work Satisfaction..………82


The Moderating Effect of Personality on the Relationship

Between Amplitude Variation in Job Stressors and Amplitude

Variation in Pay Satisfaction…………………………………..83




Variation in Promotion Satisfaction..…………………………..84




Variation in Supervisor Satisfaction…………………………..85




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Variation in Coworker Satisfaction……………………………86




Variation in Nature of Work Satisfaction……………………….87

Table 19: Regressing Job Performance on Frequency and Amplitude

Variation in Job Satisfaction……………………………………88Table 20: Regressing Turnover Intentions on Frequency and

Amplitude Variation in Job Satisfaction.………………………89

Table 21: Summary of Hierarchical Regressions Examining the

Impact of Job Satisfaction Variability on Job Performance..90

Table 22: Summary of Hierarchical Regressions Examining the

Impact of Job Satisfaction Variability on Turnover

Intentions…………………………………………………………91

FIGURES

Figure 1: The Moderating Effect of Extraversion on the Relationship

Between the Frequency Variation in Job Stressors and the

Frequency Variation in Promotion Satisfaciton………………92

APPENDICIES

Appendix A: Recruitment Letter………………..…………………………93

Appendix B: Momentary Job Satisfaction Survey...…………………….94



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Appendix C: Reduced Momentary Job Satisfaction Survey..………….97

Appendix D: Reduced Non-Momentary Job Satisfaction Survey..……99

Appendix E: Momentary Job Stressors Scale..………………………..100

REFERENCES…………………………………………….………………………102

ABSTRACT………………………………………………….……………………..113

AUTOBIOGRAPHICAL STATEMENT………………………………………….115



1

CHAPTER 1

INTRODUCTION

Overview

Job satisfaction is one of the most highly researched constructs in

industrial/organizational psychology. In 1992, Cranny, Smith, and Stone estimated

there to be more than 5,000 published articles and dissertations that have, in some

way, examined job satisfaction. In the fifteen years since, job satisfaction has

remained one of the most enthusiastically studied constructs in the organizational

sciences.Why is the topic of job satisfaction so ardently studied? As Locke (1976)

suggests, there are two main reasons why researchers have been systematically

studying the nature and causes of job satisfaction since the 1930s: 1) job satisfaction

can be viewed as an end in itself, since happiness is a goal of life and 2) it

contributes (or is expected to contribute) to other attitudes and outcomes.

Additionally, through the years there have been many different conceptualizations of

job satisfaction. These different conceptualizations have led to different research

methods and many mixed findings, thus furthering the study of job satisfaction as

researchers attempted to definitively define and explain the construct. For example,

in recent years the debate inherent in most job satisfaction literature has centered on

the extent to which job satisfaction is rooted in individual dispositions or in situationalfactors. This debate has lead different researchers in very different directions. Years

of inconclusive research led many researchers to describe the construct of job



2

satisfaction as the comfortable “old shoe”, unfashionable and unworthy of continued

research (Roznowski & Hulin, 1992).

However, recently job satisfaction research has begun to undergo a paradigm

shift which has somewhat revived research in this area and may prove to integrate

past conceptualizations of job satisfaction that were previously viewed as competing.

More specifically, researchers are beginning to understand that by looking at job

satisfaction temporally, they are able to investigate both between individual and

within individual differences and thus better explain the construct (Judge & Ilies,

2004).Given that investigating the intraindividual variability of job satisfaction is

relatively new, there are many questions that remain unanswered. For example, how

is intraindividual variability most comprehensively defined? What causes this within-

person variability and what can explain between-individual differences in within-

individual variability? Further, does variability in job satisfaction predict important

organizational outcomes above and beyond the prediction from mean levels of job

satisfaction? If intraindividual variability in job satisfaction does not predict

performance, for example, beyond mean levels of job satisfaction, then cross-

sectional measurement of job satisfaction may be sufficient. Thus, the intent of the

present study is to identify the predictors and criteria of this newly identified within-

person variation in job satisfaction.

Job Satisfaction: A Review

To better understand the current state of job satisfaction research, it is

important to review how researchers have conceptualized the construct in the past.



3

Job satisfaction researchers have varied greatly in their conceptualizations of the

construct. The most inherent difference between these conceptualizations lies in the

hypothesized causal antecedents of job satisfaction, as will be subsequently

discussed.

Weiss and Cropanzano (1996) suggested that, at that time, all specific

theoretical positions on job satisfaction were variants of three general approaches:

The cognitive judgment approach, the social influences approach and the

dispositional approach. The cognitive judgment approach is rooted in equity theory.

As described by Weiss and Cropanzano (1996), the general structure existing for allcognitive judgment theories is that the work environment is represented as a

concrete or abstract set of features (e.g., pay levels, promotion opportunities, etc.)

and that these features are perceived and compared to some set of standards held

by the job incumbents. In these theories, the degree of match between perceptions

and standards can then be thought of as one’s level of job satisfaction. In contrast,

the social influences approach is much like the cognitive judgment approach in that

job satisfaction is seen as a result of one’s perceptions of some desired standards.

The only difference is that in this latter theory, social information is the source of

input for one’s perceptions and standards (Weiss & Cropanzano, 1996). Finally, the

dispositional approach to job satisfaction is based on the idea that to some degree,

job satisfaction results from one’s general tendencies to feel good or bad, and that

this tendency is unaffected by the specific nature of the job (Weiss & Cropanzano,

1996).



4

As previously mentioned, these three theoretical conceptualizations differ

primarily in the antecedents hypothesized to cause job satisfaction. The cognitive

judgment approach suggests that job satisfaction is a result of individual perceptions

of fulfilled expectations, standards or needs. The social influence approach

hypothesizes that job satisfaction is caused primarily by cues from the social

environment, while the dispositional approach suggests that job satisfaction is a

result of individual tendencies to naturally feel good or bad. More simply, these

theories differ in the extent to which they suggest job satisfaction to result from

individual differences or from the situation. As a result, research on the origin andnature of job satisfaction naturally shifted focus toward determining the extent to

which it is rooted in situations (i.e., reactions to workplace factors) or in dispositions

inherent to individuals. In other words, job satisfaction researchers have spent much

time caught up in a person-situation debate.

The Person-Situation Debate

The Dispositional Approach: There has been much research supporting the

dispositional nature of job satisfaction (Agho, Mueller, & Price, 1993; Arvey,

Bouchard, Segal, & Abraham, 1989; Brief, Burke, George, Robinson, & Webster,

1988; Brief, Butcher, & Roberson, 1995; Connolly & Viswesvaran, 2000; Judge &

Bono, 2001; Judge, Bono, & Locke, 2000; Judge, Heller, & Mount, 2002; Judge &

Hulin, 1993; Judge & Larsen, 2001; Judge & Locke, 1993; Judge, Locke, & Durham,

1997; Judge, Locke, Durham, & Kluger, 1998; Levin & Stokes, 1989; Necowitz, &

Roznowski, 1994; Staw, Bell, & Clausen, 1986; Watson & Slack, 1993). The

dispositional approach views job satisfaction from a top-down perspective, arguing



5

that differences in personality and trait affectivity predispose individuals to be

differentially satisfied with their jobs (Brief, Butcher, George, & Link, 1993).

Many researchers interested in the dispositional nature of job satisfaction

have focused on identifying the personality traits that may be responsible for

determining an individual’s level of job satisfaction. Judge and Larsen (2001) argued

that neuroticism, extraversion, positive affectivity (PA) and negative affectivity (NA)

are the traits that are best suited to predicting job satisfaction. A meta-analysis

conducted by Judge, Heller, and Mount (2002) lends support to this argument.

Additionally, Judge et al. (2002) found neuroticism to be a consistent correlate of jobsatisfaction, and further found the relationships between job satisfaction with

neuroticism and extraversion to generalize across studies.

There is an abundance of research additionally supporting a relationship

between affective dispositions and job satisfaction (Agho, Mueller & Price, 1993;

Brief, Burke, George, Robinson & Webster, 1988; Brief, Butcher, & Roberson 1995;

Connolly & Viswesvaran, 2000; Judge & Hulin, 1993; Judge & Locke, 1993; Levin &

Stokes, 1989; Necowitz & Roznowski, 1994; Staw, Bell & Clausen, 1986; Watson &

Slack, 1993). Dispositional affect can be thought of as a person’s average level of

emotion. Affective disposition is most often thought of as being comprised of two

facets: negative affectivity (NA) and positive affectivity (PA) (Watson, Clark, &

Tellegen, 1988). Watson, Clark, and Tellegen (1988) described individuals high in

NA as, on average, having higher levels of distress, anxiety and dissatisfaction; and

focusing primarily on unpleasant characteristics of themselves, others, and the world.



6

In contrast, individuals high in PA are described as having high levels of energy,

optimism, enthusiasm, and social interest.

Past research has consistently supported a significant and negative

relationship between NA and job satisfaction (Agho, Mueller, & Price 1993; Brief,

Burke, George, Robinson & Webster, 1988; Brief, Butcher, & Roberson 1995; Levin

& Stokes, 1989; Necowitz & Roznowski, 1994; Watson & Slack, 1993). Thus

individuals characterized by distress, unpleasurable engagement, and nervousness

(i.e., individuals high in NA) are likely to have low levels of job satisfaction. Past

research has also supported a significantly positive relationship between PA and jobsatisfaction (Agho, Mueller, & Price, 1993; Watson, & Slack; 1993). Thus individuals

characterized by high energy, enthusiasm, and pleasurable engagement (i.e.,

individuals high in PA) are likely to have high levels of job satisfaction. A meta-

analysis conducted by Connolly and Viswesvaran (2000) found estimated true score

correlations (i.e., corrected correlations) of PA and NA with job satisfaction of .52 and

-.33 respectively. Thus, there is ample evidence to suggest relationships between

both PA and NA and job satisfaction. While other explanations for these relationships

exist (e.g., NA causes individuals to choose less favorable jobs subsequently leading

to lower satisfaction), much of the past research has suggested evidence of the

relationship between affect and job satisfaction to support the assertion that affect

predisposes individuals to be chronically satisfied or dissatisfied.

Judge, Locke and Durham (1997) further used a combination of several traits,

or what they describe as individuals’ core self-evaluations, to explain the

dispositional nature of job satisfaction. Core self-evaluations are described as a



7

broad personality concept that is composed of self-esteem, generalized self-efficacy,

locus of control and neuroticism. Judge et al. (1997) argued that core self-

evaluations are fundamental premises that individuals hold about themselves and

their functioning in the world. Past research has supported a link between core self-

evaluations and job satisfaction (Judge & Bono, 2001; Judge, Bono & Locke, 2000;

Judge, Locke, Durham & Kluger, 1998). For example, Judge, Bono and Locke (2000)

found that core self-evaluations measured in childhood and in early adulthood were

linked to job satisfaction measured in middle adulthood. This suggests that core self-

evaluations can predict job satisfaction over time.Aside from personality and affectivity, some of the research investigating the

dispositional roots of job satisfaction has attempted to identify the extent to which job

satisfaction is genetically determined. For example, monozygotic twins reared apart

were used to investigate the genetic component of job satisfaction (Arvey, Bouchard,

Segal & Abraham, 1989). Results from this study suggest that about 30% of the

observed variance in general job satisfaction is attributable to genetic factors, thus

providing evidence for a biologically-based trait that predisposes individuals to see

positive or negative content in their lives and their jobs.

There is no doubt an abundance of research that supporters of the

dispositional approach use to justify their position. However, other researchers have

utilized different methodologies to support the importance of a situational component

to job satisfaction. This research is subsequently discussed.

The Situational Approach: Several researchers have investigated the

importance of situational factors in predicting job satisfaction (e.g., Gerhart, 1987;



8

Weiss, Nicholas & Daus, 1999). Situational researchers utilize a bottom-up

perspective, arguing that job satisfaction is a result of the things that individuals

experience in their lives at work. Hackman and Oldham’s (1976) Job Characteristics

Model (JCM) is a classic example of a situational approach to job satisfaction. The

JCM focuses on five core job characteristics: task identity, task significance, skill

variety, autonomy and feedback. Two meta-analytic reviews of the literature testing

the relationship between workers’ reports of these job characteristics and job

satisfaction have yielded consistently positive results (Fried & Ferris, 1987; Loher,

Noe, Moeller, & Fitzgerald, 1985). The JCM has been influential to researchers’development of the job satisfaction construct through its emphasis on situational

components.

Also influential, a study conducted in 1987 by Gerhart has been frequently

cited in support of the situational approach. Utilizing a longitudinal field sample of

over 800 individuals, Gerhart found that pay, status, and job complexity added

explanatory power to an equation predicting job satisfaction. In contrast, results did

not support the importance of traits as determinants of job satisfaction. This suggests

that situational factors are not only important predictors, but that they may be more

important than individual traits.

The Staw and Ross (1985) study, which is often cited in support of the

dispositional approach, also provides evidence for situational influences on job

satisfaction. Utilizing a longitudinal data base of over 5,000 individuals, Staw and

Ross obtained a correlation of .44 between combined 1966 and 1969 assessments

of job satisfaction and job satisfaction measured in 1971; leading them to conclude



9

that measures of job satisfaction are stable over a 5-year period. However, the

highest correlation between job satisfaction measures over the five year period was

obtained for those individuals who did not change employer or occupation. For those

individuals whose job situations remained constant, the correlations between 1966

and 1971 job satisfaction was .37. For those individuals whose employer and

occupation changed the correlation between 1966 and 1971 job satisfaction was

reduced to .19. Again demonstrating situational aspects to be important. Additionally,

they also found that beyond the effects of attitudinal stability, there was residual

variance in satisfaction that was related to situational aspects. Thus, these resultsmore accurately suggest the presence of both dispositional and situational influences

on job satisfaction.

Situational factors have also been found to mediate the relationship between

dispositions and job satisfaction. More specifically, Judge et al. (2000) found core

self-evaluations (i.e. dispositions) measured in childhood to predict job satisfaction

later in life; however it was also found that job complexity (i.e. a situational effect)

partially mediated this relationship. Thus again, the importance of both dispositional

and situational factors is suggested.

As should be apparent through this review of the literature, the dispositional

approach and the situational approach both have received empirical support. It is

likely that neither of these approaches alone sufficiently explain an individual’s job

satisfaction. Instead of researchers taking a top-down or a bottom-up approach to

job satisfaction, the focus of research should be toward understanding how individual

dispositions and situational characteristics together create an individual's level of job



10

satisfaction.

Partially because of the conviction with which researchers approached this

person-situation debate, and largely as pointed out by Ilies and Judge (2002),

because of the typical cross-sectional, between-subjects designs that are most

frequently used, it has been particularly difficult to further research on the factors that

influence individuals’ job satisfaction. Additionally, when longitudinal studies were

conducted in the past they were done so over long time frames with very few data

points (e.g., Heller, et al., 2002; Newton & Keenen, 1991; Staw & Ross, 1985; Steel

& Rentsch, 1997; Weaver, 1980). As reviewed above, while we have learned a greatdeal from this past research, there also seems to be a need to move beyond these

traditional approaches in an attempt to better define the causes of job satisfaction.

As a result, several researchers have begun to recognize the importance of

investigating the within- person variation in job satisfaction that may occur over

shorter time frames.

Within Subject Variability in Job Satisfaction: The New Frontier

In traditional approaches to job satisfaction research, time was not considered

an important parameter to consider. However, as suggested by several researchers

(e.g., Ilies & Judge, 2002; Weiss & Cropanzano, 1996), this did not encourage the

investigation of within-individual variation in job satisfaction that may result from

meaningful changes in feelings toward the job. Cross-sectional measurement

assumes that variation around average levels of a construct is randomly distributed

error, which may not be the case. As Kahneman (1999) suggests, the study of

happiness (or satisfaction) can be greatly furthered through obtaining multiple real-



11

time measures of the construct as the assessments occur in the individual’s

environment and are not influenced by memory.

One of the most influential and highly cited definitions of job satisfaction was

provided by Locke (1976). Locke described job satisfaction as an emotional reaction

that “results from the perception that one’s job fulfills or allows the fulfillment of one’s

important job values, providing and to the degree that those values are congruent

with one’s needs” (p. 1307). As suggested by Weiss and Cropanzano (1996), though

this is a popular and accepted definition of job satisfaction, research on job

satisfaction to date had not been conducted in a manner consistent with thisdefinition. Locke’s definition is affective, job satisfaction is viewed as an emotional

reaction to the workplace. Affect levels have been shown to fluctuate over time and

to influence immediate perceptions of job stress (e.g., van Eck, Nicolson, & Berkof,

1998) which likely then influence job satisfaction as well (Weiss & Cropanzano,

1996). Thus, fluctuation is expected and meaningful. However, cross-sectional and

two-time point longitudinal studies have not allowed for the identification of such

fluctuations. Given that this approach suggests individual levels of job satisfaction to

fluctuate as one reacts to the job environment, Weiss and Cropanzano seem to be

employing a situational approach. However, Weiss and Cropanzano also suggest

that these patterns of fluctuation can be easily predicted by personality traits. In

general, it seems to be important to utilize momentary assessments of job

satisfaction in the short-term to be able to capture these fluctuation patterns, but also

different individuals are likely to have different reactive patterns which can be

predicted using personality.



12

Using a different logic but leading to very similar conclusions, Shoda, Mischel

and Wright (1994) developed a complex theory of personality which is helpful in

understanding not only the importance of investigating the intraindividual variability of

job satisfaction, but also for understanding how both individual dispositions and

characteristics of the situation may interact. Shoda et al. (1994) described how

relatively enduring person variables within the individual interact with situational

characteristics to generate patterns of behavior. The structure of the personality

system can remain stable across situations, but the personality state changes readily

when the situational features that are active change (Mischel & Shoda, 1995). Morespecifically, these authors suggest that an individual’s personality can be described

in terms of stable if…then situation-behavior profiles and argue that variations in

intra-individual behavior should be investigated, as they are not “error” but are

instead meaningful reflections of enduring personality processes (Shoda et al.,

1994). Applying this to job satisfaction research, in support of the situational

approach, there is no reason to expect cross-situational consistency in job

satisfaction because different situations evoke different cognitive-affective reactions,

thus there are likely if-then situation-satisfaction profiles. However, these patterns

are enduring and reflect the influence of stable personality traits.

Job satisfaction researchers have also recently supplied evidence suggesting

the importance of examining the intraindividual variability in job satisfaction. Ilies and

Judge (2002) obtained measures of job satisfaction from 27 individuals at four time

points during the day for 19 working days. Using this procedure, it was found that

36% of the variance in job satisfaction was due to variation within individuals, thus



13

suggesting that there is significant within person variability in job satisfaction over

short periods of time. Judge and Ilies (2004) also found state mood to influence state

job satisfaction, and that this effect decays rapidly. An additional recent study sought

to specifically identify the time frame over which individuals significantly vary in their

levels of job satisfaction (Young & Baltes, 2006). Assessing five different constructs

of job satisfaction, Young and Baltes found that while individuals significantly

fluctuated in their levels of job satisfaction between days, between weeks, and

between two week time periods, individuals fluctuate most within the same day. In

addition, utilizing Weiss and Cropanzano’s (1996) Affective Events Theory (AET),Fuller, Stanton, Fisher, Spitzmuller, Russell, & Smith (2003) suggest the relationship

between events and job satisfaction to be mediated by strain, and that this

mechanism likely unfolds during a shorter time frame than one day. In sum, this

previous research supports the assertion that short-term variation in job satisfaction

occurs and that this likely results from reactions to workplace events.

Thus, individuals do seem to meaningfully fluctuate in their levels of job

satisfaction over shorter time frames. Following the logic of Mischel et al. (1994) and

Weiss and Corpanzano (1996), this variability likely results from the appraisal of

different situational events, and these patterns of variability can likely be predicted by

between-subject personality traits. Job satisfaction researchers have begun to

explore the relationships between intraindividual variability and personality. In

particular, Ilies and Judge (2002) found neuroticism to relate to the intraindividual

variability in job satisfaction; additionally, trait affectivity has been suggested as an

important variable to consider when measuring job satisfaction momentarily (Judge &



14

Ilies, 2004; Ilies & Judge, 2004).

The current study is designed to continue the investigation of the role of

personality in predicting intraindividual variability. However, as will be discussed in

more detail below, the current study differs from this previous research in several

important ways. First, additional individual difference variables are included; second,

these relationships are explored at the facet level of job satisfaction; and finally,

these relationships are explored for both frequency and amplitude variability in job

satisfaction.

In addition, following the theory of Mischel et al. (1994) and Weiss andCropanzano (1996) situational change seems to be the likely impetus to job

satisfaction variability; however, no study to date has systemmatically related

momentary assessments of situational change to momentary job satisfaction

change. While Ilies and Judge (2002) and Judge and Ilies (2004) found within-

individual variability in mood to relate to within-individual variability in job satisfaction

no momentary assessment of the situation was included in either study. Further,

Fuller et al. (2003) measured the within-person variation of job satisfaction and

additionally suggested situational change to be important to consider. However, while

Fuller et al. (2003) included an open-ended question requesting participants to

indicate any stressful situations which may have been encountered during the work

day, again, no momentary situational assessment was included; a limitation of

previous research which this study seeks to address.

Finally, as already stated, meaningful within-person variation in job

satisfaction does seem to occur over short time periods. However, current variability



15

research does not address whether this variation predicts important organizational

outcomes (e.g., performance, turnover intentions) above and beyond one’s mean

level of job satisfaction; an additional limitation which the current investigation also

seeks to address. If intraindividual variability in job satisfaction does not predict

important organizational outcomes above and beyond cross-sectional measurements

of job satisfaction, then cross-sectional measurement is likely sufficient for predictive

purposes. Thus, this is an important question to address.

The Present Study

As outlined above, the current study is designed to further explain the role ofpersonality in predicting the within-person variation in job satisfaction, the role of

situational change in predicting the within-person variation in job satisfaction, as well

as to determine whether the variability in job satisfaction predicts organizational

outcomes above and beyond traditional cross-sectional assessments. Further, these

relationships are explored for five different facets of job satisfaction as well as for

multiple conceptualizations of variability.

Within-individual variation can be defined in terms of both frequency and

amplitude changes. In other words, some individuals may change very little in their

levels of satisfaction but these small changes may happen frequently, while other

individuals may experience changes in their levels of job satisfaction that are large in

magnitude, but infrequent. Frequency and amplitude are different conceptualizations

of “variability” and they may have different antecedents and different outcomes.

However, no researcher to date has conceptualized job satisfaction variability in

terms of both frequency and amplitude. Thus, the current study will explore all



16

relationships hypothesized for both frequency and amplitude variability in job

satisfaction.

Additionally, research exploring the predictors and outcomes of job

satisfaction variability has focused on measuring the intraindividual variability of

overall job satisfaction. However, there is evidence that job satisfaction is

multifaceted. Facet measures of job satisfaction assess an individual’s satisfaction

with several different aspects of their jobs (e.g., supervision, coworkers, pay,

benefits). Several researchers using facet measures of job satisfaction have found

the facets to differentially relate to both predictor and criterion variables (e.g., Kinicki,Mckee-Ryan, Scriesheim & Carson, 2002; Iaffaldano & Muchinsky, 1985). Given the

previously reviewed research and theory, it has been suggested that the

intraindividual variability in job satisfaction reflects emotional reactions to the working

environment. Thus it is possible that this variability is different for different facets as

these facets represent different aspects of an individual’s working environment.

More specifically, in the present study, five facets of job satisfaction are

investigated. These facets include satisfaction with supervision, coworkers, pay,

promotion, and the nature of work. These facets of job satisfaction are commonly

investigated in the literature and are most often measured with the Job Descriptive

Index (JDI) (Rain, Lane, & Steiner, 1991). In conducting a meta-analysis on the

construct validity of the JDI, Kinicki, et al. (2002) found test-retest reliability

coefficients to be smaller for the facets of supervision and coworker satisfaction (.56

and .59 respectively) than for the facets of pay, promotion, and nature of work

satisfaction (.65, .63 and .67 respectively). The lower test-retest coefficients suggest



17

that the facets of supervision and coworker satisfaction may be more variable than

the facets of pay, promotion, and the nature of work. Because an individual’s

interactions with supervisors and coworkers are likely less situationally stable than

either pay, promotion or the nature of one’s work, this assertion is consistent with the

theory of Shoda et al. (1994) in suggesting that an affective state (i.e., job

satisfaction) will vary more frequently as a result of more frequent variation in the

situation. Quarstein, McAfee, and Glassman (1992) suggest situational

characteristics such as pay, promotion opportunities, and working conditions to be

relatively stable over time, while supervisors and coworkers can, at times, behaveerratically and thus may be classified as situational occurrences which are more

transitory. This again suggests the importance of assessing variability for different

facets of job satisfaction, as these facets represent different aspects of the work

environment, aspects which are thought to have different degrees of stability. It

therefore seems important to explore the intraindividual variability in job satisfaction

for different facets of job satisfaction.

However, as already discussed, variability can be conceptualized in multiple

ways. Thus while the facets of supervisor and coworker satisfaction may have

greater frequency variation given that these facets are likely less situationally stable,

this does not mean that these facets have greater amplitude variation. In fact,

logically should an individuals’ pay, or promotion opportunities or the nature of one’s

work change in the situation, it is likely that the affective reaction (i.e., job

satisfaction) to these changes would be large in amplitude. Thus, while these facets

may not frequently vary, they may vary with great amplitude. However, given that



18

research has not yet explored frequency vs. amplitude variation in job satisfaction,

no specific hypotheses are made. However, it is loosely expected that the facets of

supervisor and coworker satisfaction will fluctuate with greater frequency, while the

facets of pay, promotion, and nature of work satisfaction will fluctuate with greater

amplitude.

Towards accomplishing the goals of the present study, theoretical evidence is

first reviewed and hypotheses are generated regarding the relationships between the

intraindividual variability of job satisfaction and personality, situational variability, and

organizational variables. These relationships are explored for five different facets of job satisfaction and by defining variability by frequency of change and amplitude of

change.

The Antecedents of Job Satisfaction Variability

Personality: Previous research has suggested that individual dispositions

influence the extent to which individuals are sensitive to situational events (Bowling,

Beehr, Wagner, & Libkum, 2005). Individuals high in neuroticism are described as

having a predisposition to experience anxiety and emotional instability (McCrae &

Costa, 1989). Neuroticism is the personality trait that has been most often suggested

as important to investigate in regard to within-person variability, and past research

has supported its importance to this line of research. For example, by utilizing diary

recordings, Suls, Green, and Hillis (1998) found individuals high in neuroticism to be

more sensitive to stressful events than individuals low in neuroticism while Bolger

and Schilling (1991) found participants high in neuroticism to have more negative

reactions to various daily hassles. Though not specific to job satisfaction, these



19

studies demonstrate neuroticism to impact the extent to which individuals react to

situational occurrences. Further as Ilies and Judge (2002) suggest and support,

neuroticism intensifies one’s affective reactions to work-related stimuli, thus resulting

in higher job satisfaction variability. Thus, previous research has supported the idea

of neuroticism relating positively to job satisfaction variability.

Individuals high in extraversion are described as sociable, talkative, assertive

and active (McCrae & Costa, 1989). Extraversion has also been suggested by

previous researchers to be important to investigate when considering within-person

job satisfaction variability (e.g., Bowling et al., 2005). In prior research, extraversionhas been linked to variability in mood or emotional states (e.g., Hepburn, & Eysenck,

1989; Larsen & Ketelaar, 1991; Velting, & Liebert, 1997). More specifically, these

studies all demonstrated extraversion to relate positively to one’s variability in

positive mood. Mood is at least in part situationally determined, as emotion theorists

generally agree that it is an individual’s appraisal of important events/situations that

trigger emotion and mood (e.g., Frijda, 1986; Levenson, 1994). Thus, like

neuroticism, while these studies do not directly reflect job satisfaction, they

demonstrate that extraversion may impact the extent to which individuals react to

situational occurrences. Given that job satisfaction levels are expected to fluctuate as

individuals react to the job environment, extraversion likely also impacts one’s

variability in job satisfaction. However, the one study that has investigated this

relationship did not find extraversion to significantly correlate with variability in job

satisfaction (Ilies & Judge, 2002). In general, there is mixed prior support for the

hypothesis suggesting extraversion to relate to job satisfaction variability.



20

The personality trait of openness to experience may be important to

investigate as well. Individuals who are high on openness to experience have an

orientation that is creative, curious, and flexible and further have an affinity for

situations involving novelty, diversity, and change (McCrae & Costa, 1989). In other

words, individuals high in openness to experience have a need for variety. Thus it is

possible that individuals high in openness to experience seek out more variable work

situations, and resultingly may have more variable levels of job satisfaction. Previous

research has also supported openness to experience as relating to within-individual

variability in other contexts. More specifically, Velting and Liebert (1997) foundopenness to experience to positively relate to individuals’ within-day mood

fluctuations. Again, using the same logic as presented above, though not directly

measuring job satisfaction, this study provides evidence to suggest that openness to

experience may relate to how individuals react to their environment, and thus may

impact variability in job satisfaction. While, to date, no study has looked at the

relationship between openness to experience and job satisfaction variability, it is

possible that the two are positively correlated.

Both trait positive and negative affectivity (PA and NA) have additionally been

suggested as important to consider when investigating job satisfaction intraindividual

variability (e.g., Bowling et al., 2005). Reviewing past research lends support to the

importance of NA and PA to job satisfaction variability. In 1990, Parkes found

teachers high in NA to show more symptoms of distress in reaction to a stressful

environment than teachers low in NA, suggesting that high NA individuals react more

strongly to the environment than low NA individuals. Similarly, Marco and Suls (1993)



21

found individuals high in NA to be more reactive to negative environmental events.

Also, Brief, Butcher and Roberson (1995) found that the job satisfaction of

individuals high in NA was not as affected by a positive event in the workplace as

was low NA individuals’ job satisfaction. This again demonstrates that trait affect has

an impact on how individuals react to workplace events, but more specifically, the job

satisfaction of high NA individuals is not as strongly affected by positive

environmental change. In fact, research generally suggests individuals high in NA to

more affected by negative events, while individuals high in PA to be more affected by

positive events (Stewart, 1996). In sum, as Weiss and Cropanzano (1996) suggest,affective personality traits seem to act as predispositions, in other words, being high

in PA or NA predisposes individuals to respond to environmental events (either

positive or negative) with more intensity than those low in PA or NA. Given that

previous theory has suggested that different situations evoke different cognitive-

affective reactions, or different situation-satisfaction profiles as well as has

suggested PA and NA to intensify situational reactions, it is likely that NA and PA

relate to within-person job satisfaction variability.

Thus, in sum, a review of the research suggests the following hypotheses.

H1: The personality trait of neuroticism positively relates to intraindividual

variability in job satisfaction.

H2: The personality trait of openness to experience positively relates to

intraindividual variability in job satisfaction.

H3: Dispositional negative affectivity positively relates to intraindividual




22

H4: Dispositional positive affectivity positively relates to intrainidivudal


Further, while theoretically it would seem that extraversion should relate

positively to the intraindivdual variability in job satisfaction, past research has not

supported this relationship (Ilies & Judge, 2002). However, as will be subsequently

discussed, the current study will explore the above hypotheses for different facets of

job satisfaction and for different conceptualizations of variability. Thus, it seems of

value to explore extraversion utilizing this more comprehensive conceptualization of

job satisfaction variability; however, no specific hypotheses are made regardingextraversion.

As previously discussed, past research involving the correlates of

intraindividual variability of job satisfaction has been conducted using overall

measures of the construct. Therefore, it is unknown whether these personality

variables relate differently to job satisfaction variability for different facets of job

satisfaction. Thus these relationships are explored in the current study. Additionally,

it is unknown whether these variables relate in the same way to frequency variability

and amplitude variability. Research conducted by Velting and Liebert (1997) loosely

suggests that differences may exist. More specifically this study demonstrated

openness to experience to relate to both mood fluctuation (i.e., average of highest

daily mood minus lowest daily mood) and mood swing (i.e., standard deviation of

mood across 20 days) while neuroticism related only to mood swing and not to mood

fluctuation. While this study did not assess job satisfaction variability, it does suggest

that personality relates differently to variability depending on how variability is



23

defined. Given the absence of research investigating job satisfaction variability in this

way, no direct hypotheses are made. However, the current study explores whether

there are differential relationships between personality and various

conceptualizations of job satisfaction variability. Further, given that variability may be

modeled differently for different facets of satisfaction, the personality-facet variability

relationships are also explored.

Situational Change: Through reviewing the literature, it was suggested that job

satisfaction variability occurs as individuals react to the environment. However, as

already mentioned, no study investigating the within-person variation in jobsatisfaction has attempted to determine whether momentary situational assessments

relate to momentary job satisfaction assessments. Given that immediate perceptions

of job stress influence job satisfaction (Weiss & Cropanzano, 1996) and that different

situations evoke different cognitive-affective reactions (Mischel & Shoda, 1995) and

thus likely different if-then situation-satisfaction profiles, this seems an important

question to directly assess.

Stress researchers often conceptualize stressors as objective external

conditions, or events that have actually occurred, which create stressful demands on

and threats for individuals (Lazarus, 1990). More specifically, job stressors are

aspects of the working environment that create stress for individuals. A great deal of

research suggests the importance of assessing job stressors in regard to their

relation to job satisfaction. This body of research has consistently supported job

stressors as having significant impacts on individuals’ job satisfaction (e.g., Babakus,

Cravens, Johnston & Montcrief, 1996; Barsky, Thoresen, Warren & Kaplan, 2004;



24

Fisher & Gitelson, 1983; Hartenian, Hadaway & Badovick, 1994; Jamal, 1990;

Kemey, Mossholder & Bedian 1985). Given that environmental job stressors are so

frequently demonstrated as relating to job satisfaction, they seemed a particularly

important aspect of the job situation to investigate in the current study. While cross-

sectional assessments of job stressors have been related to cross-sectional

assessments of job satisfaction, it is unknown whether momentary assessments of

job stressors will relate to momentary assessments of job satisfaction. However,

given the theory from which this study is based, situational variability is expected to

relate to job satisfaction variability thus the following hypothesis can be made:H5: Intraindividual assessments of job stressor variability are positively related

to intraindividual assessments of job satisfaction.

As with the above hypotheses, this relationship will be investigated for both

frequency variability as well as for amplitude variability and for five different facets of

job satisfaction.

Additionally, in discussing personality as it relates to job satisfaction variability,

personality was described as likely being important to job satisfaction variability

through its impact on how individuals react to situations. In other words, the “reaction

to the environment” which likely determines job satisfaction variability is affected by

personality, suggesting a moderation effect. Given that variability in the situation

likely relates to variability in job satisfaction and that personality likely impacts how

individuals react to situations, the following hypotheses can be made:

H6: The relationship between job stressor variability and job satisfaction

variability is moderated by personality such that this relationship is stronger for



25

individuals high in neuroticism than for individuals low in neuroticism.



individuals high in openness to experience than for individuals low in openness to

experience.



individuals high in NA than for individuals low in NA.

H9: The relationship between job stressor variability and job satisfactionvariability is moderated by personality such that this relationship is stronger for

individuals high in PA than for individuals low in PA.

This moderation effect is explored for extraversion as well, however given that

the investigation of extraversion is exploratory, a specific hypothesis is not made.

Additionally, these moderating effects are again investigated for both frequency and

amplitude variation and for each facet of job satisfaction.

The Consequences of Job Satisfaction Variability

An additional goal of the present study was to determine whether the

intraindividual variability in job satisfaction relates to organizational variables above

and beyond cross-sectional assessments of job satisfaction. Thus, possible

relationships between the intraindividual variability of job satisfaction and job

performance and turnover intentions are now explored.

Job Performance: Researchers in the organizational sciences have long found

it important to demonstrate a relationship between job satisfaction and job



26

performance. In fact, the search for this relationship has been referred to as the “holy

grail” of organizational research (Weiss & Cropanzano, 1996). However, despite all

of the effort researchers have expended, many are still unclear regarding how, or

even if, job satisfaction and job performance relate. For example, Fisher (1980),

viewing job satisfaction as a general attitude, suggests that it is unreasonable to

expect job satisfaction to relate to performance. In fact, research has demonstrated

generally small relationships between job satisfaction and performance (e.g., Katzell,

Thompson, & Guzzo, 1992). However, other researchers have found support for a

relationship between job satisfaction and performance. Podsakoff and Williams(1986) for example, found that by making rewards contingent on productivity, the

connection between satisfaction and performance is high. In general, however,

multiple reviews of the literature seem to suggest a positive, but weak, relationship

between job satisfaction and job performance (Fisher, 2003). As Fisher (2003)

discusses, when assessed at the between-person level the average satisfaction-

performance relationship is generally weak and there is no reason to expect general

satisfaction with the job as a whole to relate to sustained high job performance.

There is evidence however, to suggest that within-person assessments of job

satisfaction relate to job performance. Fisher (2003) found momentary task

satisfaction to relate to momentary task performance, which suggests that individuals

are more satisfied with a particular task at moments they are performing the task

well, and are less satisfied with a particular task at moments they are performing less

well. It is important to point out that is impossible to determine from this study

whether pre-existing satisfaction levels influence subsequent performance, or vice



27

versa. While this study specifically investigates task satisfaction and task

performance, it demonstrates that individuals who are more variable in their

satisfaction are also more variable (i.e., less consistent) in their levels of

performance. Given that performance is likely less consistent for individuals with

highly variable levels of job satisfaction it intuitively seems that overall judgments of

performance for such individuals may be lower than for individuals who are

performing more consistently. Additionally, Weiss and Cropanzano (1996) suggest

that emotional responses, whether positive or negative, are generally responsible for

decrements to job performance because the management of emotions requiresresources that could be used for task performance. Though emotions and job

satisfaction are not one and the same, they are related (e.g., Ilies & Judge, 2002)

and it is possible that managing fluctuations in evaluations of the job also

monopolizes resources that could be used for task performance. Thus again

suggesting a likely negative relationship between overall job performance and job

satisfaction variability. Thus, the following hypothesis is made:

H10: Intraindividual variability in job satisfaction is negatively related to overall

evaluations of job performance.

As with the other hypotheses, this hypothesis is additionally investigated at an

exploratory level for five different facets of job satisfaction and for amplitude and

frequency conceptualizations of variability. Do large amplitude changes in levels of

satisfaction have more of an impact on job performance than small but frequent

variations in satisfaction? Does variability for different facets of job satisfaction relate

to performance differently? These are important questions which this study



28

additionally seeks to address.

Turnover Intentions: Job satisfaction is frequently investigated as an important

predictor of withdrawal behaviors such as turnover. A comprehensive meta-analysis

investigating turnover antecedents found job satisfaction to be one of the strongest

predictors of turnover, = -.19 (Griffeth, Hom, Gaertner, 2000). Thus, when

measured cross-sectionally, the two constructs are negatively related.

Research has additionally explored the satisfaction-turnover relationship from

a longitudinal perspective. Lee and Mtichell (1994) proposed an unfolding model of

turnover, which specifies four basic decision paths that individuals follow whendeciding to quit their jobs. What is particularly important regarding this model is that

research has suggested and supported the voluntary turnover process to unfold over

time, to be precipitated by a “shock” such as being offered a different position, and to

involve prior individual experiences (Lee, Mitchell, Holtom, McDaniel, & Hill, 1999

Lee, Mitchell, Wise, Fireman, 1996). The unfolding turnover model suggests that

one’s intentions to turnover do not come about as simply as traditional models which

relate low levels of satisfaction to subsequent turnover would suggest. The

consideration of time, contextual factors, and prior individual experiences are also

important.

Also, understanding the importance of considering time, Boswell, Boudreau,

and Tichy (2005) modeled the variability of job satisfaction as it related to job

change. This study generally suggested job satisfaction to change in relation to

temporal proximity of turnover, thus relating job satisfaction change to turnover.

However, this study did not assess momentary changes in job satisfaction, but



29

assessed job satisfaction at three different points three months apart. Along the

same vein, Kammeyer-Mueller, Wanberg, Glomb, and Ahlburg (2005) suggest that

because turnover antecedents, like job satisfaction, have been shown to be dynamic,

measuring them in a temporal context should enhance our understanding of the

turnover process. As such, Kammeyer-Mueller et al. (2005) assessed job satisfaction

at 5 different time points 4 months apart and found that when measured over time,

change in the facet of work satisfaction becomes an important predictor of turnover.

Again suggesting job satisfaction change to relate to turnover. While these studies

are important, previous research has demonstrated individuals to meaningfully varyin their levels of job satisfaction over shorter time frames than investigated in the

above mentioned studies. Thus, it is still unknown whether the intraindividual

variability in job satisfaction relates to turnover intentions when assessed

momentarily.

The results of Kammeyer-Mueller (2005) suggest change in job satisfaction to

negatively impact turnover. In other words, individuals who changed in their levels of

satisfaction were more likely to turnover. While this study assessed general change

in satisfaction over many months, it is possible that short term change in job

satisfaction (i.e., variability) also negatively impacts turnover such that individuals

who are more variable in their levels of satisfaction are more likely to intend to

turnover than individuals who vary less in their levels of job satisfaction. Thus the

following hypothesis is made:

H11: Intraindividual variability in job satisfaction is positively related to turnover

intentions.



30

Further, Kammeyer-Mueller (2005) only found work satisfaction measured

over time to be an important predictor of turnover, while pay, supervisor and

coworker satisfaction measured over time were not important determinants of

turnover. Thus, there were differences in this relationship depending on facet of job

satisfaction, further supporting the importance of investigating these relationships for

different facets of satisfaction as done in this study. Also, given that the unfolding

turnover model suggests “shocks” to be important predecessors of turnover, it may

be that amplitude variation relates more strongly to turnover than frequency variation.

This possibility is currently explored.Finally as previously mentioned, while these relationships are theoretically

interesting, it is important to assess whether job satisfaction variability predicts job

performance and turnover intentions above and beyond mean levels of job

satisfaction assessed cross-sectionally. Because these indices of variability are

suggested to provide additional information regarding one’s job satisfaction (i.e., a

more comprehensive picture) it is expected that knowledge of the intraindividual

variability in job satisfaction will contribute to the prediction of these organizational

variables above and beyond the variance that is predicted by a cross-sectional

measurement of job satisfaction assessed at the same time as the outcome

variables. Thus, the following hypotheses are made:

H12: Intraindividual variability in job satisfaction predicts overall evaluations of

performance above and beyond cross-sectional assessments of job satisfaction.

H13: Intraindividual variability in job satisfaction predicts turnover intentions

above and beyond cross-sectional assessments of job satisfaction.



31

In sum, the present study suggests neuroticism, openness to experience, NA

and PA and possibly extraversion to positively relate to job satisfaction variability.

Additionally, it is hypothesized that job stressor variability will relate to the variability

in job satisfaction and that this relationship is moderated by personality, and finally,

the current study suggests job satisfaction variability to relate to job performance and

to turnover intentions, and to predict these variables above and beyond a cross-

sectional assessment of job satisfaction. Further, it is suggested that variability can

be conceptualized in different ways and that variability may be modeled differently for

different facets of job satisfaction. Thus, it was of interest to explore the suggestedrelationships for both frequency and amplitude variation and for different facets of job

satisfaction.

CHAPTER 2

METHOD

Participants

Participants in the present study included full-time staff from a large

Midwestern university. A mass recruitment email (see Appendix A) was sent to all

staff at the university in hopes of recruiting one-hundred and twenty-five individuals

to participate. In regard to assessing intraindividual variability, one-hundred and

twenty-five participants is more than sufficient given the success similar studies have

had in identifying intraindividual variability in job satisfaction using far lessparticipants (e.g., Heller, 2003; Ilies & Judge, 2002; Ilies & Judge, 2004). Further as

Warner (1998) states, in time series studies, representatively sampling time is of

utmost importance, thus many time-series studies contain small numbers of



32

participants in order to look at a larger number of time points. In regard to assessing

between subject effects, when =.05, only 44 subjects would be needed to detect a

medium effect (.30, Cohen, 1988) with power = .80 in a regression with five

predictors.

One-hundred and ninety-nine employees responded to the email indicating

their interest in participating. The researcher contacted these interested individuals

via email to explain in greater detail the exact nature of the study and the time

commitments involved with participating. Initially, 132 participants agreed to

participate. However, 31 of these individuals voluntarily withdrew from the studybefore its completion, yielding a final sample of 101 individuals. Thus, power to

detect a medium effect utilizing a regression with five predictors is .99. Participants

received $30.00 compensation for their participation.

Of the 101 individuals, 84.2% are female and 15.8% are male. Regarding

ethnicity, 54.5% of the current sample identified themselves as White/European

American, 33.7% as African American, and 7.9% as Asian. The age of the

participants ranged from 23 to 63, with the average age being 37.91. Additionally,

57.5% percent of the current participants are married or in an exclusive dating

relationship, and 55.4% have children. All 101 participants worked in positions which

allotted them access to the internet throughout each working day (e.g., administrative

assistant, accountant, research coordinator, secretary, housing office coordinator,

office services clerk). All participants worked full-time (ranging from 35-77 hours per

week), with the average number of hours worked per week equaling 41.31. The job



33

tenure of the current sample ranged from 2 months to 37 years. A summary of the

demographic characteristics of the sample can be seen in Table 1.

Measures

Job Satisfaction: Two modified versions of Spector’s 1985 Job Satisfaction

Survey (JSS) were used in the present study. The original JSS contains 4 items for

each of 9 facets of job satisfaction (i.e., supervision, coworkers, communication,

contingent rewards, pay, promotion, fringe benefits, operating procedures, and the

nature of work), resulting in a 36-item scale. Respondents indicate their agreement

with each item on a 6-point Likert scale ranging from 1= disagree very much to 6 =agree very much. Higher scores indicate higher levels of satisfaction.

Because participants were asked to complete the JSS at multiple time points

during the same day, the scale was altered slightly in the present study to make

items momentary in nature (see Appendix B). Additionally, because the participants

in the present study were asked to complete the JSS multiple times a day for several

weeks, a shorter version of the scale was desired. Thus, the JSS was reduced to

include only those job satisfaction facets measured in the JDI (i.e., supervision,

coworker, pay, promotion, and the nature of work). Because the Job Descriptive

Index (JDI) is the most frequently used facet measure of job satisfaction (Rain et al.,

1991), it is particularly important to investigate the within person variability of these

facets. Thus, JSS items measuring communication, contingent rewards, fringe

benefits and operating procedures were removed from the scale for the present

study. The removal of these items resulted in a 20-item scale (see Appendix C).



34

To assess the reliability of the 20-item scale, Cronbach’s alpha was calculated

for each facet separately. To ensure that the scale was reliable throughout the

duration of the study, Cronbach’s alpha was calculated for each facet for a random

1/3 of the time points including: Day 1 morning, Day 2 mid-day, Day 3 mid-day, Day

4 mid-day, Day 5 afternoon, and Day 6 mid-day. The reliability information obtained

from these time points was then averaged within each facet to obtain average facet

reliability. This average reliability information can be seen in Table 2.

Additionally, with the assessment of the outcome variables, participants were

asked to complete a reduced (i.e., 20-item), however non-momentary, JSS. This 20-item JSS can be found in Appendix D. Coefficient alphas for the non-momentary

scale in this study are as follows: .811, .830, .880, .702, and .925 for pay, promotion,

supervisor, coworker and work satisfaction respectively.

Personality: Neuroticism, extraversion and openness to experience were

measured using the 50-item IPIP (Goldberg, 1999). Though not included in this

study, the 50-item IPIP also assess conscientiousness and agreeableness.

Respondents indicated the extent to which each item accurately described them on a

scale ranging from 1-very inaccurate to 5-very accurate. An example item is “I am the

life of the party”. Higher scores on the neuroticism subscale indicate higher levels of

emotional stability (i.e. lower levels of neuroticism). Higher scores on the

extraversion and openness to experience subscales indicate higher levels of both of

these constructs. In the present study, coefficient alphas for the neuroticism,

extraversion and openness to experience subscales are .892, .907 and .806

respectively.



35

Affectivity: The PANAS (Watson, Clark & Tellegen, 1988) was used to assess

positive and negative affect. When responding to the PANAS, participants are asked

to indicate how the feel in general, or on average. The PANAS consists of 50

adjectives that are rated on a 5-point response scale ranging from 1-very slightly/not

at all to 5-extremly. Coefficient alpha for the PA subscale is .948 in the current study,

and is .953 for the NA subscale. Higher scores indicate higher levels of NA or PA.

Job Stressors: Job stressors were assessed using a twenty-item scale

developed by Frone, Russell, and Cooper (1992). The scale is comprised of three

sub-scales: work pressure (i.e., role overload), lack of autonomy, and role ambiguity.Participants responded on a four-point response scale ranging from 1 (almost

always ) to 4 (almost never / never ). In addition, like job satisfaction, because job

stressors were measured multiple times daily for several days, the questions were

altered to be momentary in nature (see Appendix E). Higher scores indicate higher

job stressors.

Additionally, to ensure that the scale was reliable throughout the duration of

the study, coefficient alpha was calculated for each facet for a random 1/3 of the

time points including: Day 1 morning, Day 2 afternoon, Day 3 mid-day, Day 4 mid-

day, Day 5 afternoon, and Day 6 mid-day. The reliability information was then

averaged and the average reliability is .860.

Performance: In order to assess overall job performance, three questions

were developed. These questions were as follows: 1. “If you had a performance

appraisal or review in the past year, please indicate the overall rating you received

for the quality of your work” with participants indicating their response on a scale



36

ranging from 1 = marginal to 5 = above expectations; 2. “Overall what is your usual

performance at work?” with response options ranging from 1 = Consistently below

expectations to 5 = above expectations; and 3. “How do you perform at work relative

to others in your organization (that is, your coworkers)?” with participants responding

on a scale ranging from 1 = well below average to 5 = well above average.

Coefficient alpha for this scale in this study is .728.

Turnover Intentions: A three-item scale developed by Cammann, Fichman,

Jenkins, and Klesh (1979) was used to assess employees' intentions to leave the

organization. Ratings were summated to form an overall score where a highernumber indicates a higher probability of leaving the organization. An example item is

“I will probably look for a new job in the next year” and participants could respond on

a scale ranging from 1-not at all likely to 4-exteremely likely. In the present study,

coefficient alpha for this scale is .902. Higher scores indicate higher intent to

turnover.

Procedure

Upon soliciting participants via email, the researcher sent a follow-up email to

interested individuals. The purpose of this second email was to formally explain the

structure of the study as well as to be sure individuals were fully aware of the time

requirement involved with their agreeing to participate. Individuals were also

informed that compensation would be awarded after the completion of the study.

Further, given that the present study was requesting individuals to indicate their

feelings about their jobs, it was possible that individuals may have felt compelled to

respond in a socially desirable manner in fear that expressing their honest job-



37

related feelings may lead to negative repercussions. This was of particular concern

in the present study as participants were being recruited from the same university in

which the study was being conducted. Such participant reactivity to the study may

reduce construct validity (Shadish, Cook, & Campbell, 2002). In order to increase the

accuracy of participant responses, participants were informed that all responses

would remain confidential.

Before beginning the study, individuals needed to formally consent to

participation. The consent form and some general demographic information (e.g.,

gender, ethnicity, job title) were made available online and participants were sent anemail link leading them to the consent form and demographic information. Upon

consenting and completing the demographic information the online survey further

instructed participants to complete the personality measure, and the measure of

positive and negative affectivity. Participants were given one week from the date the

link was sent to complete this initial information.

Once the consent form, demographic information, and initial surveys were

complete, the 20-item JSS and the job stressors scale were also made available

online to consenting participants. Participants were asked to complete the JSS and

the job stressors scale three times daily; once early in the work morning, again in

mid-afternoon, then again in late afternoon. These daily measurements occurred on

6 different days over a three week period. More specifically, participants completed

the JSS and job stressors scale three times daily on Tuesday and Wednesday of

week 1, on Wednesday and Thursday of week 2, and on Tuesday and Wednesday

of week 3. Previous research has demonstrated the majority of within-person job



38

satisfaction variability to occur within the same day, however the design of the

present study also allows for between day, between week and between two week

variance to be captured (Young & Baltes, 2006). A reminder email providing a link to

the JSS and job stressors scale was sent out to all participants at the time that they

were expected to fill out the momentary surveys. More specifically, each day of the

study a reminder email was sent at 8:00am, 11:00am and 2:00pm with instructions to

complete the survey by 10:00am, 1:00pm and 4:00pm respectively. Each time a

participant visited the survey website, the job stressors scale was presented followed

by the five facets of job satisfaction presented in random order. The momentaryassessments were collected during the last two weeks of February and the first week

of March.

In addition, the participants were provided with paper copies of the reduced

JSS and of the job stressors scale. They were instructed to complete the paper copy

if they were ever to encounter difficulties accessing the survey online. Participants

were additionally instructed to indicate on the top of the paper survey the date and

exact time of survey completion, and to send any completed paper surveys to the

researcher through campus mail.

Once all momentary measurements were complete, participants were sent

one final email. By clicking on the link included in the email, participants were

directed to a website which asked them to indicate if they experienced any traumatic

life events during the course of the study. If participants indicated that they did

indeed experience a traumatic life event, they were asked to describe the event, and

when it occurred. In addition, participants also completed the non-momentary JSS,



39

the turnover intentions scale and the performance scale. Finally, participants also

provided a mailing address, indicating where to send their $30.00 compensation.

CHAPTER 3

RESULTS

Given the extensive time commitment required of the participants in the

current study, several participants did not complete job satisfaction measurements at

every time point. However, no participant was missing more than 3 of the 18 time

points required. Unfortunately, there is as yet no firm guideline for how much missing

data can be tolerated for a sample of a given size (Tabachnick & Fidell, 2001).Again, given the intense nature of the present study, the researcher decided that

completion of 15 of the 18 time points was adequate. Additionally, the amount of

missing data in the current study is less than that found in studies that have utilized

similar measurement procedures. For example, in the Ilies and Judge (2002) study

the maximum number of possible observations across individuals and time periods

was 2052 and data was complete for 1907 or 93% of all observations. In the current

study, the maximum number of observations across individuals and time points was

1818 and data was complete for 1765 or 97% of all observations.

Missing values analyses were conducted in order to further investigate the

nature of the missing data. Little and Rubin (1987) suggested that when data are

missing at random, the chance that a subject’s data are lost is independent of whatthese data would have been had no loss occurred. In order to determine whether

data were missing at random, separate variance t-tests were conducted between the

time points that had 5% or more missing data and job satisfaction scores at all other



40

time points. More specifically, a significant t-statistic would indicate that the missing

cases for that time point are significantly correlated with scores at a different time

point, and thus, are not missing at random. These analyses were conducted

separately for each facet of job satisfaction and for job stressors.

In taking a closer look at missing data at each time point for each facet of job

satisfaction, it became apparent that there were no time points for which 5% or more

of the data were missing. In other words job satisfaction data were present for at

least 96 of the 101 participants for each time point in every facet thus there was no

need to conduct t-tests. However, for the job stressors variable, one time point had6.9% missing data. Therefore, separate variance t-tests were conducted between

this time point and every other time point resulting in 15 t-tests. Using an alpha of .01

none of the t-values were significant, thus data was concluded to be missing at

random.

As will be described in greater detail below, periodogram and harmonic

analyses were used to identify and describe variability in this study. Time-series data

that includes missing values can not be analyzed using periodogram or harmonic

analyses, so it was necessary to replace missing values. In the current study, the

mean of the nearest two points was used to replace missing values. Several

researchers suggest that when the amount of missing data is small (i.e., 5% or less),

one’s choice of technique for replacing missing data seems to make little difference

in the results obtained (Raaijmakers, 1999; Roth & Switzer, 1995). Additionally,

several other common methods for replacing missing data were deemed

inappropriate for the present study. As pointed out by Raaijmakers (1999),



41

substitution based on the item mean is only a good option when there are low

correlations between the missing variable and the other variables under

investigation. This is unlikely in the current study, given that there are variables in

this study that are the same measure taken at different time points. Raaijmakers also

pointed out that regression and hotdeck procedures are difficult to implement if the

variable having the highest correlation with the missing variable also has missing

data. Given that all time points include missing data for at least one case, regression

and hotdeck procedures do not seem appropriate for the current study. Another

common procedure, using the person mean to replace the missing value, additionallyseemed unsuitable for the present study. The current study suggests that individuals

vary over short periods of time, and the person mean substitution method is

inappropriate for scales characterized by varying means (Raaijmakers, 1999). Thus

the mean of the nearest time points was reasoned to be one’s best guess regarding

the value of the missing time point for the current study. This is a conservative

method for estimating missing values as it reduces the variance of the variable

(Tabachnick & Fidell, 2001). This is of particular importance to note in the present

study, as it is the main purpose of this study to investigate the variability of job

satisfaction. Table 3 displays the means and standard deviations of the job

satisfaction facets, after missing values were replaced.

In order to first identify and describe the within person variability in job

satisfaction, periodogram and harmonic analyses were conducted. In brief,

periodogram analyses are used to identify the periodic components that explain the

largest percentage of the variance in a time series. Harmonic analyses then use this



42

identified period to estimate the mean, amplitude and phase that maximize fit to the

observed time series. Both of these procedures will be described in more detail

below.

Before conducting either periodogram or harmonic analyses, it is necessary to

identify and remove any trends in the time series (Warner, 2003). This is important

because any trends that are present will dominant the analyses making it difficult to

detect any cycles that might be present. Regression procedures were used to fit and

remove any linear and/or quadratic trends from the job satisfaction and job stressors

data. Trends were identified and removed separately for every person for every facetof job satisfaction and for the job stressors variable. More specifically, for every

person for every time-series variable, a regression analysis was conducted to predict

the raw time-series data (job satisfaction scores or stressor scores across time) from

the observation number (ranging from 1 – 18). The residuals from this trend analysis

were saved as a new variable and these residuals were used in subsequent

periodogram and harmonic analyses.

As stated before, the main purpose of periodogram analysis is to identify the

periodic components that explain the largest percentage of the variance in a time

series. In periodogram analyses, the overall Sum of Squares (SS) for the time series

is partitioned into a set of N/2, N being the length of the time series, SS components

that correspond to the amount of variance accounted for by different cyclic

components (Warner, 1998). In the current study where the length of the each time

series is 18, the cycle lengths that were fitted to the data include periods of 18/1,

18/2, 18/3, 18/4, 18/5, 18/6, 18/7, 18/8 and 18/9. Or in other words, the overall SS for



43

the time series was partitioned into sums of squares that are accounted for by N/2

(i.e., 9) different cyclic components with periods of 18, 9, 6, 4.5, 3.6, 3, 2.57, 2.25

and 2. Frequency is the inverse of period and is the proportion of a cycle that occurs

during one observation. Frequencies are equally spaced, and thus are orthogonal

(Warner, 1998).

In the current study periodogram analyses were conducted on the time series

residuals. These analyses were conducted separately for each person for each time

series variable (i.e. the five facets of job satisfaction and job stressors). Periodogram

intensities (sums of squares) were used to identify the period that accounted for thelargest proportion of time-series variance. So for example, consider participant #1. If

a relatively large proportion of the variance of participant 1’s coworker satisfaction

time series corresponds to a period of 18/4, than a cycle length of 4.5 is concluded to

best explain variability in person 1’s coworker satisfaction time series. Thus

participants’ frequency scores were identified by finding the period/frequency

components that explained the largest amount of time-series variance for each of the

time series variables. Harmonic analyses were then conducted to further model the

identified cyclic components.

Harmonic analysis is designed to more specifically model a cyclic component.

Using the previously identified period, harmonic analysis estimates the mean, phase,

and amplitude that maximize fit to the observed time series (Warner, 1998). Cosine

and sine functions that represented the previously identified period/cycle were

computed for each person for each time series variable. For example, if the cycle of

participant 1’s coworker satisfaction time series was identified to be 4.5 then, the



44

cosine function was calculated as cos(2time/4.5) and the sine function was

calculated as sin(2 time/4.5). Next, for each person OLS regression procedures

were used with the calculated cos and sin variables as predictors of the residual time

series variables. The mean of the time series is the resulting intercept. The estimated

amplitude was calculated using cosine and sine coefficients. The amplitude estimate

indicates that the cycle has peaks and troughs that are roughly X points above and

below the overall mean. In sum, conducting both periodogram and harmonic

analyses for each person separately and for each time series variable resulted in

frequency and amplitude scores for each individual for each facet of job satisfactionand for job stressors. Tables 4 and 5 display the means and standard deviations of

the frequency and amplitude scores for each facet of job satisfaction. As can be

seen in these tables, the average frequency and amplitude variation scores do not

differ greatly by facet.

Bivariate correlations between study variables can be seen in Table 6. This

initial examination of the data reveals that relationships between study variables are

generally small. However, there are some significant correlations that are worthy of

further mention. Looking at the relationships between personality and job satisfaction

variability, the frequency with which pay satisfaction varies significantly relates to

both NA and neuroticism, and the frequency with which nature of work satisfaction

varies significantly relates to both NA and PA. To elaborate, greater frequency

variation in pay satisfaction relates to lower NA (r = -.21, p < .05) and to higher

emotional stability (i.e. lower neuroticism; r = .21, p < .05). Greater frequency

variation in nature of work satisfaction relates to lower NA (r = -.21, p < .05), to higher



45

PA (r = .29, p < .05) and though not significant, to higher emotional stability (i.e.,

lower neuroticism; r = .20). It should also be pointed out that non-momentary (i.e.

cross-sectional assessments) coworker satisfaction significantly negatively relates to

NA and to neuroticism. Additionally, considering non-momentary nature of work

satisfaction, higher NA and neuroticism (i.e. lower emotional stability) relate to lower

satisfaction and higher PA relates to higher satisfaction. Examining the relationships

between job satisfaction variability and job stressor variability, the only significant

correlation is between the frequency with which coworker satisfaction varies and the

frequency with which job stressors vary such that higher frequency variation in jobstressors relates to higher frequency variation in coworker satisfaction (r = .22, p <

.05). Finally, an initial assessment of the relationships between job satisfaction

variability and organizational outcomes reveals a significant correlation between the

frequency with which nature of work satisfaction varies and performance. More

specifically, higher frequency variation in nature of work satisfaction relates to higher

performance (r = .25, p < .05). It should also be noted that all non-momentary job

satisfaction facets negatively and significantly correlate with turnover intentions and

non-momentary work satisfaction positively relates to performance.

In sum, this initial assessment revealed few significant relationships. However,

while the amplitude with which job satisfaction varies did not significantly correlate

with personality, stressors, nor organizational outcomes, significant relationships

were found between the frequency with which the different facets of job satisfaction

vary and the variables of interest in this study. While these correlations provide a first



46

look at the data, as described below, a series of regressions were conducted to test

the specific hypotheses set forth.

Before presenting the results of these regressions, it should be pointed out

that because large numbers of regressions were needed to fully address the

hypotheses of the current study, the chances of making a Type 1 error were inflated.

Because of this, instead of evaluating the results in terms of their statistical

significance, results were evaluated in terms of their magnitude or strength. In other

words, when conducting multiple tests, as in the current study, there is an increased

chance of erroneously concluding that results are significant. In addition, proceduressuch as the Bonferroni correction, the Šidák-Bonferroni procedure and Holm’s

method that control Type 1 error by adjusting the alpha that should be used for each

individual test lack power (e.g., Keppel & Wickens, 2004). As such, in the current

study statistics were evaluated in terms of effect size. More specifically, Cohen’s f 2

was used to evaluate the R2 of each regression model. By convention, 0.02, 0.15,

and 0.35 are considered small medium and large effects, respectively (Cohen,

1988). Aside from evaluating the regression model as a whole, it is also important to

evaluate the individual predictors. The square of the t value for a predictor i is related

to the increment in R2 due to predictor i (Bring, 1994). So, in the current study, it is

argued that if the t for a predictor was at least 2.23, which roughly means a 5%

percent increase in R2 can be attributed to that predictor, then the effect is worth

talking about. In sum, the current study uses Cohen’s f 2 and the t-statistic to explore

the magnitude of relationships vs. focusing on the statistical significance of the

results.



47

To test hypotheses 1-4 as well as the exploratory aspects of the present

study, ten regressions were conducted to test how the set of predictors (i.e.,

neuroticism, extraversion, openness to experience, positive and negative affectivity)

relate to the each of the ten criteria (i.e., amplitude and frequency scores for each of

five facets of job satisfaction). As previously discussed, because this family of

analyses includes 10 separate tests, the chances of making Type 1 error when

evaluating statistical significance is 40%! Results obtained from these regressions

can be seen in Table 7.

Looking at Table 7, it can be seen that the amount of variability that the set ofpersonality predictors explained in the criteria ranged from 0.3% to 11.4% depending

on the criterion. An examination of the calculated effect sizes reveals that all but one

of the effects are considered small. In the only effect worth reporting, the set of

personality predictors accounting for 11.4% of the variability in the frequency with

which nature of work satisfaction varies (Cohen’s f 2 = .1287), which is approaching a

medium effect size. Looking more closely at the individual predictors in this model,

the t-value for positive affectivity was 2.329. This suggests that roughly a 5.5%

percent increase in the 11.4% of the variability that the set of personality variables

accounts for can be attributed to positive affectivity. Thus, positive affectivity can be

considered an important predictor of the frequency with which nature of work

satisfaction varies. This relationship is positive, suggesting that high levels of PA are

predictive of high levels of frequency variation in nature of work satisfaction. In

addition, while the effect of the overall model was small (f 2 = .0695), openness to

experience was found to be an important predictor to consider in understanding



48

coworker satisfaction frequency variation (t = -2.215). Around a 4.9% increase in the

6.9% of the variance that personality accounts for in coworker satisfaction frequency

variation can be attributed to openness to experience. However, this negative

relationship is contrary to what was expected as it suggests lower levels of openness

to experience to predict higher levels of frequency variation in coworker satisfaction.

In sum, regression analyses did not support hypotheses 1 and 3 which

suggested neuroticism and NA to significantly relate to the intrainidividual variability

in job satisfaction. Yet, as previously discussed, bivariate correlations did reveal

significant relationships between NA and neuroticism and the frequency with whichpay and nature of work satisfaction vary. However, these bivariate relationships were

opposite what was hypothesized and so do not lend further support to hypotheses 1

and 3. Hypothesis 2 was also not supported as results were opposite what was

anticipated. Finally, hypothesis 4 received some support in that positive affectivity

was found to be an important predictor of the frequency with which nature of work

satisfaction varies within individuals.

Hypothesis 5 suggested the intraindividual variability in job stressors to relate

to the intraindividual variability in job satisfaction. Ten regressions were again

conducted to test this hypothesis. More specifically each analysis regressed one of

the ten criteria (i.e., amplitude or frequency scores for five different facets of

satisfaction) on amplitude job stressor variability or frequency job stressor variability

respectively. This family of analyses requires 10 regressions, thus the probability of

committing a Type 1 error was again inflated. Unexpectedly, results provide little

support for hypothesis 5. As can be seen in Table 8, the within-person variability in



49

job stressors never accounts for more than 5% of the variance in the within-person

variability in job satisfaction, regardless of the type of variation (i.e. frequency or

amplitude) and of the facet of job satisfaction being investigated. All effects are

small. Although the overall effect is small, (f 2 = .0515), job stressor frequency

variation seems to be an important predictor of coworker satisfaction frequency

variation (t = 2.250). Thus, there is some support for the notion that higher job

stressor frequency variation predicts higher job satisfaction frequency variation, or

more specifically in this case higher coworker satisfaction frequency variation.

However, job stressor variation was not found to be a predictor of interest for any ofthe other 9 facets of job satisfaction variability. Therefore, hypothesis 5 is not

generally supported.

In order to assess hypotheses 6-9 and the associated exploratory analyses,

which suggest personality to moderate the relationship between job stressor

variability and job satisfaction variability, a series of hierarchical regressions were

performed. Job stressor variability (either amplitude or frequency) and personality

(either neuroticism, extraversion, openness to experience, NA, or PA) were entered

into the first step, and the respective multiplicative term was entered into the second

step of the regression. In addressing these hypotheses and exploratory analyses, a

total of 50 hierarchical regressions were performed (i.e. there are five potential

moderating relationships to test for each of the ten criteria). Because of the 50

regressions required, familywise error was calculated to be an exorbitant .92. As

such, as with the other analyses, results will be interpreted in terms of magnitude

and not in terms of statistical significance. All independent variables were centered



50

before the calculation of interaction terms, as is generally recommended (Cohen,

Cohen, West, & Aiken, 2003). In addition, to obtain the correct standardized

regression coefficients for the interaction terms from SPSS, the regressions were

also run with standardized variables and their respective interaction terms (Cohen et

al., 2003). Results of these hierarchical regressions can be found in Table 9 – Table

18.

Examining the magnitude of the change in R2 from the first step to the second

step of each hierarchical regression, all effect sizes were small (see Tables 9 – 18).

This indicates that none of the 50 interactions investigated had a meaningful impacton the explained variance of the various criteria. In other words, no interactions were

worthy of further exploration. Even so, glancing the through the t-statistics associated

with each interaction term, there was one interaction term for which a 4.33%

increase in R2 could be attributed to the interaction (t = 2.081). This interaction term

of interest can be seen in Table 10. Though, not reaching the 5% that was deemed

an important effect, the interaction seemed worthy of further exploration.

To examine this interaction, an unpublished Microsoft excel spreadsheet

program developed by Bing and LeBreton (2001) that is designed to graph the

regression interactions for two continuous variables was used. This program graphs

continuous interactions using the formulas presented in Cohen and Cohen (1983).

As one can see in Figure 1, the relationship between frequency variation in jobstressors and frequency variation in promotion satisfaction becomes stronger as

extraversion increases. More specifically, the expected positive b-weight (i.e., higher

job stressor variability should lead to more job satisfaction variability) increases from



51

a .06 when one is considering individuals one standard deviation below the mean of

extraversion to .11 when one is considering individuals one standard deviation above

the mean of extraversion. Thus, the moderating effect was in the expected direction

given that the relationship between job stressor frequency variation and promotion

satisfaction frequency variation was demonstrated to be stronger for individuals high

in extraversion. However, given that the moderating effect of extraversion was

examined exploratorily and given that none of the other 49 potential moderating

effects were deemed worthy of exploration, there was no support found for

hypotheses 6-9.Regression was also used to determine whether variability in job satisfaction

(both amplitude and frequency variability) predict the important organizational

outcomes of performance and intent to turnover (hypotheses 10 and 11). More

specifically, to test hypothesis 10, two regressions were conducted. The first

regressed performance on the within-person frequency variation in pay, promotion,

supervisor, coworker and nature of work satisfactions and the second regressed

performance on the within-person amplitude variation of each facet of job

satisfaction.

Looking at Table 19, the model regressing performance on the frequency

variation in pay, promotion, supervisor, coworker and nature of work satisfactions

was approaching a medium effect (f 2 = .1261). In looking at each of the predictors, it

is clear that frequency variation in nature of work satisfaction is driving this effect.

More specifically, t = 2.403 which indicates that roughly 5.77% of the 11.2% of the

variance that the set of predictors explains in job performance can be attributed to



52

the frequency variation in nature of work satisfaction. However, this relationship was

opposite of what was expected in that the greater the frequency with which ones

nature of work satisfaction fluctuated the higher job performance. Therefore, there is

some evidence to suggest that the frequency variation in job satisfaction is an

important predictor of job performance, however, this relationship was opposite of

what was hypothesized. In addition, there was no evidence to suggest that amplitude

variation in job satisfaction is important to the prediction of job performance as this

effect was small (f 2 = .028) and none of the predictors demonstrated worthy influence

on the criterion. Thus, hypothesis 10 was not supported.To test hypothesis 11 intent to turnover was regressed on the within-person

frequency variation of each facet of job satisfaction. Then a second regression was

conducted to regress intent to turnover on the within-person amplitude variation of

pay, promotion, supervisor, coworker and nature of work satisfactions. Results from

these regressions can be seen in Table 20. Results reveal that neither frequency nor

amplitude variation in job satisfaction were important to the prediction of intent to

turnover as the effect sizes associated with each model were small (f 2 = .0194 and f 2

= .0406) respectively. In other words, all of the facets of job satisfaction frequency

variation together only accounted for 1.9% of the variance in intent to turnover while

all of the facets of job satisfaction amplitude variation combined accounted for only

3.9% of the variation in intent to turnover. In addition, no individual facet of job

satisfaction variation (either frequency or amplitude) emerged as important to

consider. Thus hypothesis 11 received no support.



53

In addition, hierarchical regression was used to investigate whether job

satisfaction variability is a significant predictor of these organizational outcomes (i.e.,

performance and intent to turnover) above and beyond ones mean level of job

satisfaction measured cross sectionally. To test these hypotheses (H12 and H13)

non-momentary job satisfaction scores were entered into the first step of the

regression and job satisfaction variability scores (either amplitude or phase) were

entered into the second step. This procedure, allowed for the determination of

whether job satisfaction variability predicts performance and turnover intentions

above and beyond non-momentary assessments. In order to fully address thesehypotheses and exploratory analyses, a total of 4 hierarchical regressions were

performed.

First considered was the impact that frequency variation has on the prediction

of job performance above and beyond cross-sectional assessments of job

satisfaction. Looking at Table 21, it can be seen that in step 1 the non-momentary

facets of job satisfaction explained 10.4% of the variance in job performance. The

frequency variation terms were added in step 2 resulting in the explanation of 21.6%

percent of the variance in job performance. The effect size associated with this

change in R2 (11.2%) can be considered close to medium in strength (f 2 = .1261).

This suggests that the inclusion of the frequency variation terms added meaningfully

to the prediction of job performance. In investigating the individual predictors, it can

be seen that non-momentary nature of work satisfaction and frequency variation in

work satisfaction contribute most to the prediction of job performance (t = 2.750 and t

= 2.655) respectively. Again, because the addition of the frequency terms adds



54

meaningfully to the prediction of job performance, it can be concluded that frequency

variation in nature of work satisfaction adds explanatory power to the equation

predicting job performance above and beyond the contribution of non-momentary

nature of work satisfaction. Thus hypothesis 12 received some support. However, it

is also important to point out that this relationship was not in the expected direction.

Next considered was the potential impact that amplitude variation in job

satisfaction has above and beyond cross-sectional assessments of job satisfaction to

the prediction of job performance. Again looking at Table 21, the non-momentary job

satisfaction measures explained 12.2% of the variance in job performance. Theaddition of the amplitude variation job satisfaction measures only added 3.3% to the

variance explained, which is a small effect (f 2 = .0341). In addition, non-of the

amplitude variation measures added meaningfully to the prediction of job

performance. Therefore there is no evidence to suggest that amplitude variation in

job satisfaction predicts job performance above and beyond non-momentary

assessments of the job satisfaction. When considering amplitude variation,

hypothesis 12 is not supported.

As explained above, to test hypothesis 13 which suggests the variability in job

satisfaction to predict intent to turnover above and beyond non-momentary

assessments of job satisfaction the non-momentary job satisfaction scores were

entered into the first step of the regression and the job satisfaction variability scores

(either amplitude or phase) were entered into the second step. These results can be

seen in Table 22. First considering frequency variation, the five facets of job

satisfaction measured cross-sectionally explained 30.2% of the variance in intent to



55

turnover. Adding in the frequency variation of each facet of job satisfaction only

added 1% to the amount of variance explained, a small effect (f 2 = .0101). Similarly

when considering amplitude variation, the non-momentary job satisfaction measures

together accounted for 32.4% of the variation in intent to turnover, but adding the

amplitude variation predictors only added an additional 1.1% to the variance

explained, again a small effect (f 2 = .0111). Thus, neither frequency nor amplitude

variation in job satisfaction added to the prediction of ones intent to turnover above

and beyond cross-sectional assessments of job satisfaction. In other words, there

was no support for hypothesis 13.DISCUSSION

The present study was conducted to gain a more thorough understanding of

the intraindividual variability in job satisfaction. The present investigation attempted

to contribute to the growing body of literature on within-person job satisfaction

variability in several ways. First, past research has conceptualized variability in terms

of standard deviation (e.g., Ilies & Judge, 2002) and no study to date has explored

both amplitude and frequency conceptualizations of job satisfaction variability.

Someone who varies frequently, but with little magnitude may have the same within-

person standard deviation as an individual who varies with great magnitude but

infrequently. Therefore, the current investigation argued that it may be important to

distinguish between frequency and amplitude variation. As will be discussed in moredetail below, this study reveals that, in fact, this distinction may not be as useful for

modeling short-term variation as originally thought.



56

The current investigation further bolsters research through the inclusion of

multiple variables. On the predictor side, both individual and situational variables

were included. No study thus far has related momentary environmental job stressors

to job satisfaction variability. It was hoped that this study would clarify how individual

dispositions interact with situational characteristics to explain patterns of intra-

individual variability in job satisfaction. Additionally, on the criteria side, by

investigating whether or not variability predicted job performance and turnover

intentions above and beyond more traditional assessments of job satisfaction, this

study aimed to provide some guidance regarding the usefulness of measuring theconstruct momentarily.

In addition, all relationships were explored for multiple facets of job

satisfaction. Previously published research investigating the correlates of job

satisfaction variability has only assessed variability utilizing overall measures of the

construct. Therefore investigating variability at the facet level contributes uniquely to

the job satisfaction literature.

While results of the present study generally did not support the hypotheses

that were set forth, consideration of the results did reveal some interesting findings.

Next is a brief discussion of the relationships that were supported followed by an

exploration of why so many unexpected and non-significant results were obtained.

Personality Predicting Job Satisfaction Variability

It was expected that the personality traits of negative affectivity, positive

affectivity, neuroticism, openness to experience, and possibly extraversion would

influence the frequency and/or amplitude with which individuals vary in their levels of



57

job satisfaction. More specifically, it was expected that individuals high in these

aforementioned personality traits would vary with greater frequency and/or amplitude

given that these personality traits have been shown to intensify individuals’ reactions

to their environment. In addition, it was expected that these relationships may be

different for different facets of job satisfaction as the different facets represent

different aspects of the working environment.

It was surprising to find that positive affectivity was the only personality trait to

relate to job satisfaction variability in the expected way. It was found that having high

levels of positive affectivity is predictive of greater frequency variation in nature ofwork satisfaction. In other words, those characterized as having high levels of

energy, optimism, enthusiasm, and social interest (Watson, Clark, & Tellegen, 1988)

were shown to fluctuate more frequently in their attitudes toward the nature of their

work than those low in PA. Positive affectivity was not found to predict the amplitude

with which individuals fluctuate, thus, PA seems to impact how often individuals

change in their attitudes toward their work but not the magnitude or degree to which

they change their attitudes toward their work. PA was also not predictive of the

variation in any other facet of job satisfaction. This lends some support to the notion

that personality relates differentially to the variation of different facets.

Openness to experience was suggested to be an important predictor of the

frequency with which ones satisfaction with their coworkers varies. In the current

study, this relationship was opposite what was expected in that high levels of

openness to experience were predictive of low levels of frequency variation in

coworker satisfaction. This is not in-line with previous research suggesting that



58

openness to experience relates to increased within-person variability (Velting &

Liebert, 1997). However, because individuals high in openness to experience have

an orientation that is creative, curious, and flexible and further have an affinity for

situations involving novelty, diversity, and change (McCrae & Costa, 1989), it is

possible that they are more accustomed to variable situations, and thus do not react

affectively (i.e., do not change in their levels of job satisfaction). In other words, in

context of the current significant finding, while interactions with coworkers may

fluctuate frequently, individuals high in openness to experience may not react

affectively (i.e. change their attitudes) because they are comfortable with, and in factenjoy, the variable interactions. Openness to experience was not found to relate to

the amplitude of variation and did not relate to any other facet of job satisfaction.

Contrary to expectation neither NA, neuroticism nor extraversion were found

to be important predictors of frequency or amplitude variation for any facet of job

satisfaction. While at the bivariate level, both NA and neuroticism significantly

correlated with the frequency with which pay and nature of work satisfaction varied,

these relationships were opposite what was expected. In other words, it was

hypothesized that individuals high in neuoriticism and NA would be more variable in

their job satisfaction, but correlational analyses suggest the opposite. One potential

explanation for these unexpected bivariate correlations is that individuals who are

high in NA and/or neuroticism have generally very low levels of job satisfaction.

Perhaps, there is not as much room for these individuals to vary in their levels of

satisfaction because they are at the bottom of the job satisfaction spectrum. In the

current study, as well as in previous research, cross-sectional assessments of job



59

satisfaction relate negatively to cross-sectional assessments of both NA and

neuroticism, providing some support for this notion.

It should be pointed out that the only meaningful relationships observed

utilizing regression were observed for the facets of coworker and nature of work

satisfaction. It is possible that one’s coworkers and the actual nature of one’s work

are more salient/observable in the job environment than pay, promotion, or one’s

supervisor. As such, perhaps personality is relating to the variation of these facets

because, in the actual environment individuals are more aware of changes in their

interactions with their coworkers and of changes in their work and thus personality ismore likely to impact how individuals affectively react to these more cognizant

changes. Said differently, maybe these facets are somewhat easier to affectively

react to, thus personality has a stronger influence on them.

Situational Variability Predicting Job Satisfaction Variability

The current study suggested that momentary situational assessments (i.e.

momentary assessments of job stressors), relate to momentary job satisfaction

assessments. This was expected as job satisfaction was suggested to vary as

individuals react to their environments. Surprisingly, there was little support for this

notion. The frequency with which job stressors varied was found to be an important

predictor of the frequency with which satisfaction with coworkers varied, and this

relationship was in the expected direction. So, as the stressors in the job

environment fluctuate with more frequency, satisfaction with coworkers fluctuates

with more frequency as well. Job stressor frequency variation was not found to be an

important predictor of any other facet of job satisfaction variability. So changes in



60

environmental job stressors are more predictive of changing attitudes regarding ones

coworkers than of changing attitudes regarding ones pay, promotion, work or

supervisor. Again, perhaps this is because coworkers are more obvious in the work

environment and thus are more relatable to perceived changes in stressors in the

environment. Job stressor frequency variation did not relate to any other facets of job

satisfaction frequency variation, and it is also important to point out that no significant

relationships were found between the amplitude with which job stressors vary and

amplitude variation in job satisfaction.

It was also expected that personality would moderate the relationship betweenstressor variability and satisfaction variability. This was expected because job

satisfaction was suggested to vary as the situation varies and personality was

suggested to impact how individuals react to situational change. Of the 50 potential

moderating effects, only one was identified as being worthy of further discussion.

More specifically, extraversion was found to moderate the relationship between job

stressor frequency and promotion satisfaction frequency such that this relationship

was stronger for those high in extraversion than for those low in extraversion.

Individuals high in extraversion were expected to react to situational variability more

than those low in extraversion. In the current study, the frequency of situational

change was found to predict the frequency of change in individuals’ attitudes toward

promotion for those high in extraversion. This relationship was not as strong for

those low in extraversion. While this moderating effect was as expected, extraversion

was not found to moderate the relationship between stressor variation and

satisfaction variation for any other facet of satisfaction. In addition, no other



61

personality trait was found to moderate the stressor variation – satisfaction variation

relationship.

The Predictive Power of Job Satisfaction Variability

The final goal of the current study was to identify whether frequency and/or

amplitude variation in job satisfaction is important to the prediction of the important

organizational outcomes of job performance and intent to turnover. To provide more

detail, it was expected that increased variation in the facets of satisfaction would be

predictive of lower job performance and higher intent to turnover.

Results did not generally support the hypotheses set forth. While thefrequency of with which nature of work satisfaction varied was positively related to

job performance, and in fact, was positively predictive of job performance above and

beyond cross-sectional assements of job satisfaction, this was opposite of what was

expected. Given the arguments presented in the current study, it may be that if

nature of work satisfaction is varying with great frequency then the actual nature of

ones work may be changing with great frequency. In other words, there is potentially

greater variety in the nature of ones work. Similar to the concept of skill variety, this

nature of work variability can potentially be conceptualized as a motivator (Hackman

& Oldham, 1976), and thus could potentially result in improved performance.

Therefore, this unexpected result can be, somewhat, theoretically supported. It is

also important to point out that this significant result is again with nature of work

satisfaction, a facet that was also shown to relate to personality. Amplitude variation

in nature of work was not predictive of performance, nor was variation in any other

facet of satisfaction. Job satisfaction variation was also not predictive of intent to



62

turnover.

What Was Learned?

While results of the current study were not generally supportive of the

hypotheses, there are some things that are important to highlight. First, it is likely

important to continue to investigate the intraindividual variability of job satisfaction at

the facet level as the variation of different facets related differentially to the predictors

and criteria in this study. The facets of coworker satisfaction and nature of work

satisfaction seem to be particularly important. As already eluded to, this may

because these facets are the most obvious in the work environment and are thusparticularly important to consider when investigating within-person variation which is

theorized to result from reactions to the environment as impacted by personality.

Second, it should be pointed out that all of the meaningful relationships

discovered involved frequency variation in job satisfaction, none involved amplitude

variation. One potential conclusion is that the frequency with which individuals vary is

likely more important than the magnitude of their variation. Or, perhaps given the

time frame of the current study, meaningful changes in frequency were easier to

capture than meaningful changes in amplitude. In other words, large amplitude

changes may not occur very often and thus may be potentially difficult to accurately

model over short time frames. This provides some indication that the

amplitude/frequency distinction may not be useful for modeling short-term, within-

person attitude variation. And again, because coworkers and the nature of ones work

are more situationally obvious, they are more susceptible to frequent changes vs.

pay, promotion or supervisors which may not be as susceptible to frequent changes.



63

Further lending support to the argument that coworker satisfaction and nature of

work satisfaction are particularly important to consider when investigating short-term

within-person variation.

In addition, these results led to the suggestion of several intriguing

relationships that could be further explored. The first is that individuals high in

openness to experience actually vary less in their levels of job satisfaction because

they are comfortable with situational variability and thus do not react affectively to it.

Second, is that variation in nature of work satisfaction may be indicative of task

variety and therefore may act as a motivator.Despite these broad conclusions and interesting possibilities, it is also

important to address the fact that most of the hypotheses were not supported. It is

possible that the methodology used for modeling variability in the current study is not

as useful as originally thought. More specifically, the periodogram and harmonic

analyses used in the present study model cyclic components in time-series data.

Perhaps instead of restricting the variability that may exist to cyclic components, it

may make more sense for the construct of job satisfaction to model the general

amount of variability that exists in individuals’ scores over time. This could be

accomplished by simply calculating the standard deviation of job satisfaction scores

for each person for each facet. Further, an index of variability such as standard

deviation will capture both frequency and amplitude variation at once. Is it important

to know how frequently someone is varying or does it make more sense to just

understand that one person varies more than another? Distinguishing between

frequency and amplitude variation doesn’t allow for the modeling of someone who is



64

varying frequently and with great amplitude at the same time. Also, as previously

mentioned, it is possible that amplitude variation is more difficult to truly capture over

short-time frames. If the goal of the research is to understand what impacts and what

is impacted by short-term, within person variation in job satisfaction, the frequency

and amplitude distinction may not be important and actually, standard deviation may

be a more inclusive and less restrictive measure of variability.

It is also important to consider how the testing itself may have impacted the

current findings. Practice, familiarity or other forms of participant reactivity impact the

inferences about the observed covariation between the variables of interest(Shadish, et al., 2002). This is of particular concern in the present study given that

participants completed the same measure at multiple time points within the same

day. Individuals may have intentionally altered their responses on subsequent job

satisfaction assessments to either seem consistent or intentionally different from

their previous assessment. However, in order to try and reduce potential participant

reactivity, participants were instructed to think of the job satisfaction at the current

moment in time. It is also important to consider the effects of attrition (Shadish et al.,

2002). There were several participants that did not remain in the study for the

duration and thus were not included as participants. It is possible that different

results would have been obtained had those participants remained.

Additional Limitations and Future Research

As with all empirical research, there are several limitations of the current study

that warrant further discussion. First and foremost, the procedures used to model

frequency and amplitude variation were not as useful as originally expected for



65

understanding short-term within-person variation. The primary goals of the present

study were to gain insight into how personality and situational variables interact to

predict job satisfaction variation and further to better understand the predictive power

of this variation. These were important questions to address given the growing

popularity in assessing job satisfaction intraindividually. Based on the results of the

current study, one may be inclined to suggest that neither personality nor situational

variability are important to the prediction of job satisfaction variability and that job

satisfaction variability is of little importance to the prediction of organizational

outcomes. However, this conclusion may be premature given that there were somemeaningful relationships unveiled and that a different methodology for modeling

variability may have captured variability more accurately. Regardless, the present

study did not provide conclusive evidence regarding the correlates of job satisfaction

variability and additionally raised several interesting questions. It is suggested that

the hypotheses put forth in the current study be investigated utilizing standard

deviation as a measure of variation. Looking at such results in concert with the

results of the current study would provide a more comprehensive picture of the

antecedents and consequences of the within-person variation of job satisfaction.

A second limitation of the present study results from the time frame chosen for

the measurement of job satisfaction. More specifically, the present study modeled

variability in job satisfaction over the course of a three week period. Measurement

using this time frame does not allow for modeling changes that may occur over

longer time frames than three weeks. For example, the chosen measurement period

did not allow for the modeling of changes in amplitude that occur outside of the three



66

week period assessed. However, given that within-person variability seems to

primarily exist within the same day (Young & Baltes, 2006) and that within-person

variability was previously measured over similar time frames (e.g., Ilies & Judge,

2002), it seems that the time frame chosen was appropriate for investigating short-

term within-person variation in job satisfaction.

In addition, participants of the present study consisted of university staff with

continuous access to a computer. Participants primarily worked in clerical and

administrative positions, thus it is not clear whether job satisfaction variability would

be modeled in the same way for other positions (e.g., sales or manufacturingpositions). Thus, future research should also investigate these questions using more

diverse samples.

This study is further limited in that there are likely additional individual

difference variables that are important to the prediction of job satisfaction variability.

For example, locus of control, or the extent to which individuals feel that they are in

control of their own destiny (i.e. have an internal locus of control) vs. holding the view

that things happen randomly or by chance (i.e., have an external locus of control)

may impact the way in which they react to situational change. Thus, locus of control

may be important to consider. There are also many additional organizational

variables that job satisfaction variability may affect (e.g., organizational citizenship

behaviors, organizational commitment). Thus future research should continue to

investigate the individual difference predictors of and outcomes of job satisfaction

variability.



67

Similarly, utilizing a measure of job stressors as a means of assessing the

work environment (i.e., the situation) is, of course, not the only way that the work

environment can be measured. To provide a few examples, future research could

assess situational change by utilizing momentary measures of the five core job

characteristics of Hackman and Oldham’s (1976) job characteristics model. To

provide another possibility, future research could code qualitative self-reports of the

work environment. While these are also potentially interesting methods of assessing

the situation, they are conceptually different from assessing the momentary

environmental stressors present at work. Thus future research should continue toinvestigate how situational change and job satisfaction variability are related for

different operationalizations of situational change.

Summary

Though many of the hypothesized relationships were not supported and this

study is not without limitations, there are a few potentially important take home

points. Frequency variation in job stressors, as well as three of the five personality

traits, were shown to be important in explaining the frequency variation of three

different facets of job satisfaction. Therefore it seems worthwhile to continue to

investigate the roles that personality and situational change play in describing the

within-person variation in job satisfaction. In addition, variation in the facet of work

satisfaction was important to the prediction of job performance above and beyond

mean levels of work satisfaction measured cross-sectionally, lending some support

to the notion that variation in job satisfaction contributes to the prediction of job

performance above and beyond the effects of cross-sectional assessments. Again,



68

while many relationships were not significant, there is some justification for

continuing to investigate the role of within-person variation in predicting

organizational outcomes. Finally, the facets of coworker and nature of work

satisfaction may be particularly important when considering short-term within-person

variation thus research should continue to explore intraindividual variability for

different facets of job satisfaction.



69

Table 1

Demographic Characteristics of Sample Sample Characteristic % of Sample

GenderFemale 84.2Male 15.8

Age (range = 23-54; M = 36.55)35 and Younger 49.5Above 35 50.5

EthnicityWhite/European American 54.5Black/African American 33.7Asian 7.9Hispanic 1.0

Arab/Middle Eastern 1.0Multiracial/Other 2.0Marital Status

Married 50.5Single 30.7Living Together or In Dating Relationship 7.0Divorced or Separated 7.0Engaged 5.0

Parental StatusHas Children 55.4No Children 44.6

Family Income$15,000-$30,000 14.1$30,000-$45,000 22.2$45,000-$75,000 36.4$75,000-$100,000 15.2Above $100,000 12.1

Job Tenure (range = 2 months–37 years; M =5.75 years)1 Year or Less 25.72-3 Years 18.94-5 Years 20.96-7 Years 11.9

8 Years and Above 22.6Highest Graduate DegreeNo Degree Beyond HS 2.0Bachelors 48.5Masters 30.7Doctoral 5.0



70

Table 2

Cronbach’s Alpha by Facet: Average of a Random Sample of Time Points

Facet Average Alpha

Coworker .711

Pay .793

Promotion .831

Supervisor .884

Nature of Work .921



71

Table 3

Means and Standard Deviations of Facets: Across all Time Points

Facet N Mean Standard DeviationPay 1818 2.68 1.11

Promotion 1818 2.47 1.09

Supervisor 1818 4.22 1.32

Coworker 1818 4.29 .99

Nature of Work 1818 4.19 1.28

Note: N = 1818 reflects that means were calculated across all individuals and across all time points for each facet.



72

Table 4

Means and Standard Deviations of Frequency Variation for Each Facet of Job

Satisfaction

Facet N Mean Standard Deviation

PayF 99 .2604 .1303

ProF 97 .2417 .1293

SupF 98 .2693 .1389

CoF 100 .2583 .1298

WrkF 98 .2755 .1339

Note. PayF = Frequency variation in pay satisfaction, ProF = Frequency variation in promotion satisfaction, SupF = Frequency

variation in supervisor satisfaction, CoF = Frequency variation in coworker satisfaction, WrkF = Frequency variation in work

satisfaction



73

Table 5

Means and Standard Deviations of Amplitude Variation for Each Facet of Job

Satisfaction

Facet N Mean Standard Deviation

PayA 98 .4049 .5447

ProA 95 .4753 1.1265

SupA 91 .6417 1.4229

CoA 98 .6037 1.0821

WrkA 97 .6949 1.1441

Note. PayA = Amplitude variation in pay satisfaction, ProA = Amplitude variation in promotion satisfaction, SupA = Amplitude

variation in supervisor satisfaction, CoA = Amplitude variation in coworker satisfaction, WrkF = Frequency variation in work

satisfaction



75

Table 7

Regressing Job Satisfaction Frequency and Amplitude Variation on Personality

Criterion Predictor R2

f 2

B SE B tPay Freq .065 .0695NA -.022 .028 -.108 -.770PA .002 .024 .013 .097

Extra .016 .017 .104 .942ttNeur .017 .021 .118 .838Open -.005 .024 -.021 -.200

Pay Amp .015 .0152NA -.089 .123 -.105 -.723PA -.005 .103 -.007 -.049

Extra .012 .073 .018 .158tt

Neur .004 .090 .007 .050Open .038 .106 .040 .362Pro Freq .036 .0373

NA .024 .029 .119 .825PA -.022 .024 -.121 -.918

Extra .021 .017 .146 1.128ttNeur .026 .021 .175 1.222Open -.008 .025 -.037 -.344

Pro Amp .016 .0163NA -.075 .255 -.044 -.295PA -.050 .217 -.032 -.232

Extra .028 .149 .022 .191ttNeur .093 .186 .074 .501Open -.169 .217 -.086 -.779

Sup Freq .003 .003NA -.007 .032 -.034 -.230PA .001 .027 .007 .049

Extra .006 .018 .041 .353ttNeur -.005 .023 -.028 -.195Open .000 .026 .002 .018

Sup Freq .016 .0163NA -.166 .330 -.076 -.502

PA .097 .277 .048 .351Extra -.067 .197 -.041 -.343ttNeur -.272 .253 -.165 -1.076Open .028 .291 .011 .095



76

Table 7 (continued)

Criterion Predictor R2 f 2 B SE B tCo Freq .064 .0695

NA .011 .028 .054 .388PA .012 .024 .062 .486Extra .022 .016 .149 1.346ttNeur -.011 .021 -.073 -.533Open -.053 .024 -.233 -2.215*

Co Amp .043 .0449NA .039 .241 .024 .163PA .180 .203 .117 .890

Extra .076 .139 .062 .550ttNeur -.083 .174 -.067 -.476Open -.384 .203 -.205 -1.896

Wrk Freq .114 .1287NA -.015 .028 -.075 -.547PA .057 .024 .291 2.329*

Extra -.010 .017 -.062 -.576ttNeur .004 .021 .023 .172Open -.033 .024 -.143 -1.395

Wrk Amp .022 .0225NA .225 .254 .126 .884PA .239 .222 .141 1.077

Extra -.077 .149 -.059 -.517ttNeur .070 .187 .053 .376

Open -.134 .216 -.067 -.619Note. ttNeuroticism is scored such that high scores indicate high emotional stability (i.e. low neuroticism) *p < .05. Pay Freq =

Frequency variation in pay satisfaction, Pay Amp = Amplitude variation in pay satisfaction, Pro Freq = Frequency variation in

promotion satisfaction, Pro Amp = Amplitude variation in promotion satisfaction, Sup Freq = Frequency variation in supervisor

satisfaction, Sup Amp = Amplitude variation in supervisor satisfaction, Co Freq = Frequency variation in coworker satisfaction,

Co Amp = Amplitude variation in coworker satisfaction, Wrk Freq = Frequency variation in work satisfaction, Wrk Amp =

Amplitude variation in work satisfaction, NA = Negative affectivity, PA = Positive affectivity, Extra = Extraversion, Neur =

Neuroticism, Open = Openness to Experience.



77

Table 8

Regressing Job Satisfaction Frequency and Amplitude Variation on Job Stressor

Frequency and Amplitude Variation

Criterion Predictor R2 B SE B tPay Freq .014

Strs Freq .122 .102 .120 1.187Pay Amp .008

Strs Amp .123 .144 .090 .855Pro Freq .004

Strs Freq .064 .102 .064 .627Pro Amp .001

Strs Amp -.104 .298 -.037 -.349

Sup Freq .013Strs Freq .125 .111 .114 1.129Sup Amp .000

Strs Amp -.061 .344 -.019 -.178Co Freq .049

Strs Freq .227 .101 .222 2.250*Co Amp .002

Strs Amp .120 .284 .044 .423Wrk Freq .002

Strs Freq -.050 .108 -.047 -.461Wrk Amp .002

Strs Amp -.123 .297 -.044 -.415Note. *p < .05. Pay Freq = Frequency variation in pay satisfaction, Pay Amp = Amplitude variation in pay satisfaction, Pro Freq

= Frequency variation in promotion satisfaction, Pro Amp = Amplitude variation in promotion satisfaction, Sup Freq =

Frequency variation in supervisor satisfaction, Sup Amp = Amplitude variation in supervisor satisfaction, Co Freq = Frequency

variation in coworker satisfaction, Co Amp = Amplitude variation in coworker satisfaction, Wrk Freq = Frequency variation in

work satisfaction, Wrk Amp = Amplitude variation in work satisfaction, Strs Freq = Frequency variation in job stressors, Strs

Amp = Amplitude variation in job stressors.



78

Table 9

Summary of Hierarchical Regression Analyses Examining the Moderating Effect of Personality on the Relationship Between Frequency Variation in Job Stressors and Frequency Variation in Pay Satisfaction

Moderator Variable R2 R2 f 2 B SE B tNA

Step 1 .055Strs Freq .013 .013 .103 1.034NA -.026 .013 -.203 -2.043

Step 2 .056 .001 .001Strs Freq(StFr) .013 .013 .102 1.022NA -.027 .013 -.207 -1.999(StFr) x (NA) -.002 .013 -.014 -.140

PAStep 1 .035

StFr .013 .013 .097 .956PA .019 .013 .147 1.446Step 2 .035 .000 .000

StFr .013 .013 .098 .954PA .019 .013 .146 1.433(StFr) x (PA) -.001 .013 -.008 -.080

ExtraversionStep 1 .029

StFr .012 .013 .095 .921Extra .016 .014 .124 1.204

Step 2 .063 .024 .024StFr .013 .013 .104 1.020

Extra (Ex) .009 .014 .070 .665(StFr) x (Ex) -.025 .013 -.192 -1.861Neuroticism

Step 1 .059StFr .015 .013 .115 1.161ttNeur .027 .013 .211 2.136*

Step 2 .064 .004 .004StFr .014 .013 .111 1.111Neur (Nr) .013 .013 .228 2.230*(StFr) x (Nr) .008 .012 .069 .676

OpennessStep 1 .016

StFr .016 .013 .125 1.221Open .005 .013 .037 .361Step 2 .018 .002 .002

StFr .016 .013 .127 1.235Open (Op) .007 .014 .054 .494(StFr) x (Op) .007 .014 .050 .462

Note. ttNeuroticism is scored such that high scores indicate high emotional stability (i.e. low neuroticism) *p < .05. f 2 = effectsize for R2. Strs Freq = Frequency variation in job stressors



79

Table 10

Summary of Hierarchical Regression Analyses Examining the Moderating Effect of Personality on the Relationship Between Frequency Variation in Job Stressors and Frequency Variation in Promotion Satisfaction


Step 1 .006Strs Freq .009 .013 .068 .659NA .006 .013 .044 .427

Step 2 .006 .000 .000Strs Freq(StFr) .009 .013 .068 .651NA .005 .014 .042 .393(StFr) x (NA) -.001 .013 -.007 -.068

PAStep 1 .007

StFr .009 .013 .072 .698PA -.007 .013 -.057 -.553Step 2 .031 .024 .025

StFr .007 .013 .055 .534PA -.007 .013 -.052 -.507(StFr) x (PA) .020 .013 .155 1.510


StFr .006 .013 .047 .448Extra .011 .013 .087 .828

Step 2 .055 .044* .046StFr .005 .013 .041 .402

Extra (Ex) .018 .014 .143 1.341(StFr) x (Ex) .028 .013 .217 2.081*Neuroticism

Step 1 .008StFr .008 .013 .063 .611ttNeur .007 .013 .058 .568

Step 2 .013 .005 .005StFr .007 .013 .057 .551Neur (Nr) .010 .014 .075 .711(StFr) x (Nr) .008 .012 .074 .693

OpennessStep 1 .005

StFr .008 .013 .061 .588Open -.003 .014 -.025 -.240Step 2 .020 .015 .015

StFr .008 .013 .063 .606Open (Op) .002 .014 .013 .118(StFr) x (Op) .016 .014 .128 1.192




80

Table 11

Summary of Hierarchical Regression Analyses Examining the Moderating Effect of Personality on the Relationship Between Frequency Variation in Job Stressors and Frequency Variation in Supervisor Satisfaction


Step 1 .013Strs Freq .016 .014 .113 1.110NA -.003 .014 -.090 -.184

Step 2 .020 .007 .007Strs Freq(StFr) .016 .014 .115 1.125NA .001 .015 .005 .045(StFr) x (NA) .011 .014 .085 .797

PAStep 1 .013

StFr .016 .014 .113 1.103PA .002 .014 .129 .129Step 2 .039 .026 .027

StFr .017 .014 .125 1.226PA .000 .014 -.002 -.017(StFr) x (PA) -.023 .015 -.161 -1.586


StFr .015 .014 .110 1.059Extra .003 .014 .025 .243

Step 2 .017 .003 .003StFr .016 .015 .112 1.071

Extra (Ex) .001 .015 .010 .089(StFr) x (Ex) -.008 .015 -.057 -.536Neuroticism

Step 1 .013StFr .016 .014 .114 1.123ttNeur .000 .014 .003 .027

Step 2 .026 .013 .013StFr .016 .014 .117 1.150Neur (Nr) -.004 .015 -.030 -.282(StFr) x (Nr) -.015 .014 -.117 -1.101

OpennessStep 1 .014

StFr .017 .014 .119 1.155Open .004 .014 .032 .315Step 2 .015 .001 .001

StFr .017 .014 1.145 1.145Open (Op) .004 .015 .235 .235(StFr) x (Op) -.003 .015 -.202 -.202




81

Table 12

Summary of Hierarchical Regression Analyses Examining the Moderating Effect of Personality on the Relationship Between Frequency Variation in Job Stressors and Frequency Variation in Coworker Satisfaction


Step 1 .056Strs Freq .030 .013 .228 2.301*NA .010 .013 .080 .811

Step 2 .056 .000 .000Strs Freq(StFr) .030 .013 .228 2.292*NA .011 .013 .084 .818(StFr) x (NA) .002 .013 .016 .151

PAStep 1 .050

StFr .029 .013 .225 2.252*PA -.003 .013 -.024 .807Step 2 .050 .000 .000

StFr .030 .013 .225 2.243*PA -.003 .013 -.025 -.252(StFr) x (PA) -.001 .013 -.011 -.106


StFr .028 .013 .212 2.107*Extra .006 .013 .047 .468

Step 2 .059 .008 .008StFr .027 .013 .209 2.072*

Extra (Ex) .009 .014 .071 .680(StFr) x (Ex) .012 .013 .090 .880Neuroticism

Step 1 .053StFr .029 .013 .222 2.246*ttNeur -.008 .013 -.061 -.617

Step 2 .057 .004 .004StFr .029 .013 .224 2.261*Neur (Nr) -.010 .013 -.080 -.772(StFr) x (Nr) -.008 .013 -.067 -.652

OpennessStep 1 .074*

StFr .026 .013 .202 2.048*Open -.021 .013 -.160 -1.267Step 2 .084 .010 .010

StFr .026 .013 .199 2.025*Open (Op) -.025 .013 -.193 -1.861(StFr) x (Op) -.013 .013 -.104 -1.009




82

Table 13

Summary of Hierarchical Regression Analyses Examining the Moderating Effect of Personality on the Relationship Between Frequency Variation in Job Stressors and Frequency Variation in Nature of Work Satisfaction


Step 1 .048Strs Freq -.008 .014 -.060 -.601NA -.029 .013 -.215 -2.142*

Step 2 .050 .002 .002Strs Freq(StFr) -.008 .014 -.060 -.595NA -.027 .014 -.202 -1.925(StFr) x (NA) .006 .014 .045 .425

PAStep 1 .087*

StFr -.010 .013 -.077 -.786PA .040 .014 .293 2.978**Step 2 .088 .001 .001

StFr -.011 .013 -.078 -.786PA .041 .014 .295 2.949**(StFr) x (PA) .001 .014 .010 .102


StFr -.008 .014 -.056 -.534Extra .006 .014 .044 .044

Step 2 .005 .001 .001StFr -.008 .014 -.057 -.057

Extra (Ex) .007 .014 .053 .053(StFr) x (Ex) .005 .014 .037 .037Neuroticism

Step 1 .041StFr -.006 .014 -.043 -.432ttNeur .027 .014 .197 1.959

Step 2 .041 .000 .000StFr -.006 .014 -.044 -.431Neur (Nr) .027 .014 .201 1.901(StFr) x (Nr) .002 .013 .015 .142

OpennessStep 1 .012

StFr -.008 .014 -.060 -.583Open -.013 .014 -.098 -.950Step 2 .021 .009 .009

StFr -.007 .014 -.055 -.536Open (Op) -.009 .015 -.064 -.586(StFr) x (Op) .014 .014 .103 .952




83

Table 14

Summary of Hierarchical Regression Analyses Examining the Moderating Effect of Personality on the Relationship Between Amplitude Variation in Job Stressors and Amplitude Variation in Pay Satisfaction


Step 1 .023Strs Amp .044 .059 .080 .756NA -.067 .058 -.122 -1.155

Step 2 .029 .006 .006StrsAmp(StAm) -.018 .102 -.033 -.179NA -.071 .059 -.130 -1.219(StAm) x (NA) -.086 .115 -.137 -.746

PAStep 1 .014

StAm .047 .059 .084 .794PA .049 .059 .075 .708Step 2 .030 .017 .017

StAm -.019 .080 -.035 -.244PA .050 .059 .091 .852(StAm) x (PA) .111 .091 .176 1.223


StAm .048 .059 .087 .819Extra .035 .059 .063 .594

Step 2 .024 .012 .012StAm -.047 .108 -.086 -.438

Extra (Ex) .059 .063 .105 .926(StAm) x (Ex) .232 .221 .208 1.050Neuroticism

Step 1 .018StAm .047 .059 .086 .809ttNeur .054 .059 .097 .917

Step 2 .027 .010 .010StAm .013 .069 .023 .186Neur (Nr) .054 .059 .096 .911(StAm) x (Nr) .063 .068 .116 .924

OpennessStep 1 .009

StAm .050 .059 .090 .846Open .020 .059 .036 .338Step 2 .028 .019 .019

StAm .035 .060 .062 .575Open (Op) .015 .059 .028 .262(StAm) x (Op) -.113 .088 -.139 -1.288




84

Table 15

Summary of Hierarchical Regression Analyses Examining the Moderating Effect of Personality on the Relationship Between Amplitude Variation in Job Stressors and Amplitude Variation in Promotion Satisfaction


Step 1 .009Strs Amp -.051 .122 -.045 -.417NA -.096 .121 -.085 -.792

Step 2 .009 .000 .000StrsAmp(StAm) -.031 .214 -.027 -.144NA -.094 .123 -.084 -.770(StAm) x (NA) .028 .241 .022 .115

PAStep 1 .002

StAm -.045 .122 -.040 -.366PA .031 .123 .027 .253Step 2 .002 .000 .000

StAm -.062 .167 -.055 -.369PA .033 .124 .029 .267(StAm) x (PA) .029 .191 .022 .150


StAm -.044 .122 -.039 -.358Extra .024 .122 .022 .200

Step 2 .002 .000 .000StAm -.020 .225 -.018 -.088

Extra (Ex) .018 .134 .016 .133(StAm) x (Ex) -.058 .457 -.026 -.126Neuroticism

Step 1 .011StAm -.047 .121 -.042 -.390ttNeur .114 .123 .100 .929

Step 2 .011 .000 .000StAm -.048 .145 -.042 -.329Neur (Nr) .114 .124 .100 .923(StAm) x (Nr) .001 .143 .001 .004

OpennessStep 1 .010

StAm -.042 .121 -.037 -.344Open .105 .123 -.092 -.854Step 2 .010 .000 .000

StAm -.044 .125 -.039 -.353Open (Op) -.106 .124 -.092 -.853(StAm) x (Op) -.016 .184 -.010 -.088




85

Table 16

Summary of Hierarchical Regression Analyses Examining the Moderating Effect of Personality on the Relationship Between Amplitude Variation in Job Stressors and Amplitude Variation in Supervisor Satisfaction


Step 1 .000Strs Amp -.025 .141 -.019 -.177NA -.001 .143 -.001 -.005

Step 2 .000 .000 .000StrsAmp(StAm) -.040 .248 -.031 -.161NA -.002 .144 -.001 -.011(StAm) x (NA) -.021 .280 -.014 -.074

PAStep 1 .000

StAm -.024 .141 -.019 -.173PA -.008 .146 -.006 -.052Step 2 .001 .001 .001

StAm -.045 .193 -.035 -.233PA -.005 .148 -.004 -.035(StAm) x (PA) .035 .221 .024 .157


StAm -.022 .141 -.017 -.157Extra -.064 .146 -.048 -.438

Step 2 .006 .003 .003StAm -.139 .263 -.108 -.527

Extra (Ex) -.038 .155 -.028 -.242(StAm) x (Ex) .282 .537 .109 .525Neuroticism

Step 1 .012StAm -.018 .140 -.014 -.129ttNeur -.149 .149 -.110 -1.005

Step 2 .015 .033 .034StAm -.062 .167 -.049 -.373Neur (Nr) -.151 .149 -.111 -1.014(StAm) x (Nr) .081 .164 .064 .492

OpennessStep 1 .005

StAm -.027 .140 -.021 -.191Open .096 .147 .071 .652Step 2 .010 .005 .005

StAm -.045 .144 -.035 -.314Open (Op) .090 .147 .068 .614(StAm) x (Op) -.134 .211 -.071 -.634




86

Table 17

Summary of Hierarchical Regression Analyses Examining the Moderating Effect of Personality on the Relationship Between Amplitude Variation in Job Stressors and Amplitude Variation in Coworker Satisfaction

Moderator Variable R2 R2 f 2 B SE B tNA .002

Step 1Strs Amp .050 .116 .045 .426NA .009 .115 .009 .082

Step 2 .013 .011 .011StrsAmp(StAm) -.112 .202 -.102 -.554NA -.002 .116 -.002 -.019(StAm) x (NA) -.223 .228 -.179 -.977

PAStep 1 .004

StAm .044 .116 .040 .381PA .052 .116 .047 .450Step 2 .018 .014 .014

StAm -.074 .158 -.067 -.470PA .068 .116 .063 .588(StAm) x (PA) .200 .180 .158 1.110


StAm .046 .116 .042 .396Extra .051 .114 .047 .444

Step 2 .008 .004 .004StAm -.061 .212 -.055 -.288

Extra (Ex) .080 .125 .074 .642(StAm) x (Ex) .260 .430 .118 .603Neuroticism

Step 1 .002StAm .049 .116 .045 .426ttNeur -.016 .116 -.014 -.134

Step 2 .015 .012 .012StAm -.029 .138 -.026 -.209Neur (Nr) -.016 .116 -.015 -.140(StAm) x (Nr) .143 .135 .132 1.060

OpennessStep 1 .032

StAm .052 .114 .047 .456Open -.187 .112 -.173 -1.667Step 2 .033 .001 .001

StAm .044 .117 .040 .374Open (Op) -.190 .113 -.176 -1.682(StAm) x (Op) -.061 .172 -.038 -.357




87

Table 18

Summary of Hierarchical Regression Analyses Examining the Moderating Effect of Personality on the Relationship Between Amplitude Variation in Job Stressors and Amplitude Variation in Nature of Work Satisfaction


Step 1 .002Strs Amp -.048 .122 -.042 -.391NA .024 .122 .021 .197

Step 2 .008 .005 .005StrsAmp(StAm) -.167 .213 -.146 -.784NA .015 .123 .013 .125(StAm) x (NA) -.164 .240 -.127 -.684

PAStep 1 .006

StAm -.058 .122 -.051 -.476PA .078 .127 .066 .615Step 2 .006 .000 .000

StAm -.059 .166 -.051 -.353PA .078 .128 .066 .609(StAm) x (PA) .001 .191 .001 .005


StAm -.048 .122 -.042 -.392Extra -.043 .121 -.038 -.356

Step 2 .008 .005 .005StAm .072 .223 .063 .325

Extra (Ex) -.077 .132 -.068 -.581(StAm) x (Ex) -.292 .453 -.128 -.645Neuroticism

Step 1 .002StAm -.051 .122 -.045 -.422ttNeur .022 .124 .019 .174

Step 2 .003 .001 .001StAm -.067 .145 -.059 -.463Neur (Nr) .021 .125 .018 .172(StAm) x (Nr) .029 .143 .026 .203

OpennessStep 1 .008

StAm -.048 .121 -.042 -.396Open -.091 .121 -.080 -.756Step 2 .008 .000 .000

StAm -.049 .124 -.043 -.393Open (Op) -.092 .122 -.081 -.752(StAm) x (Op) -.007 .184 -.004 -.035




88

Table 19

Regressing Job Performance on Frequency and Amplitude Variation in Job Satisfaction


f 2

B SE B tPerf .112 .1261Pay Freq .653 .481 .140 1.357Pro Freq -.724 .485 -.155 -1.493Sup Freq .210 .479 .047 .439Co Freq .034 .523 .007 .065Wrk Freq 1.200 .499 .254 2.403*

Perf .028 .0288Pay Amp -.007 .162 -.005 -.045Pro Amp .053 .060 .103 .882Sup Amp .052 .053 .113 .975

Co Amp .031 .073 .051 .424Wrk Amp .041 .066 .072 .617Note. *p < .05. Perf = Job Performance, Pay Freq = Frequency variation in pay satisfaction, Pay Amp = Amplitude variation in

pay satisfaction, Pro Freq = Frequency variation in promotion satisfaction, Pro Amp = Amplitude variation in promotion

satisfaction, Sup Freq = Frequency variation in supervisor satisfaction, Sup Amp = Amplitude variation in supervisor

satisfaction, Co Freq = Frequency variation in coworker satisfaction, Co Amp = Amplitude variation in coworker satisfaction,

Wrk Freq = Frequency variation in work satisfaction, Wrk Amp = Amplitude variation in work satisfaction, Strs Freq =

Frequency variation in job stressors, Strs Amp = Amplitude variation in job stressors.



89

Table 20

Regressing Turnover Intentions on Frequency and Amplitude Variation in Job Satisfaction


f 2

B SE B tTurn Int .019 .0194Pay Freq -.129 .862 -.016 -.149Pro Freq .326 .870 .041 .374Sup Freq -.123 .858 -.016 -.144Co Freq .483 .937 .059 .515Wrk Freq -.822 .895 -.102 -.918

Turn Int .039 .0406Pay Amp .309 .267 .136 1.156Pro Amp -.088 .099 -.103 -.886Sup Amp .006 .088 .008 .073

Co Amp .086 .085 .085 .715Wrk Amp -.017 -.018 -.018 -.156Note. *p < .05. Turn Int = Turnover Intentions, Pay Freq = Frequency variation in pay satisfaction, Pay Amp = Amplitude

variation in pay satisfaction, Pro Freq = Frequency variation in promotion satisfaction, Pro Amp = Amplitude variation in

promotion satisfaction, Sup Freq = Frequency variation in supervisor satisfaction, Sup Amp = Amplitude variation in supervisor

satisfaction, Co Freq = Frequency variation in coworker satisfaction, Co Amp = Amplitude variation in coworker satisfaction,

Wrk Freq = Frequency variation in work satisfaction, Wrk Amp = Amplitude variation in work satisfaction, Strs Freq =

Frequency variation in job stressors, Strs Amp = Amplitude variation in job stressors.



90

Table 21

Summary of Hierarchical Regressions Examining the Impact of Job Satisfaction Variability on Job Performance


R2

f 2

B SE B tPerf .104Step 1

NM Pay .007 .079 .011 .083NM Pro -.049 .079 -.081 -.623NM Sup .031 .059 .062 .526NM Co -.098 .079 -.147 -1.237NM Wrk .167 .059 .323 2.802*

Step 2 .216* .112 .1261NM Pay -.041 .079 -.071 -.527NM Pro -.056 .077 -.093 -.725NM Sup .028 .060 .057 .470

NM Co -.100 .078 -.149 -1.274NM Wrk .159 .058 .308 2.750**Pay Freq .467 .486 .100 .960Pro Freq -.747 .481 -.160 -1.555Sup Freq .257 .471 .057 .545Co Freq .283 .519 .059 .545Wrk Freq 1.345 .507 .285 2.655**

Perf .122Step 1

NM Pay .028 .084 .047 .335NM Pro -.082 .088 -.127 -.932NM Sup .040 .068 .075 .599

NM Co -.101 .083 -.153 -1.225NM Wrk .183 .065 .349 2.820**Step 2 .155 .033 .0341

NM Pay .038 .091 .062 .411NM Pro -.087 .092 -.136 -.951NM Sup .043 .071 .080 .604NM Co -.115 .086 -.174 -1.334NM Wrk .194 .070 .368 2.578**Pay Amp .122 .169 .090 .723Pro Amp .046 .061 .089 .752Sup Amp .056 .052 .122 1.075Co Amp .007 .072 .011 .097

Wrk Amp .049 .066 .087 .747Note. *p < .05., **p < .01, Perf = Job Performance, Pay Freq = Frequency variation in pay satisfaction, Pay Amp = Amplitudevariation in pay satisfaction, Pro Freq = Frequency variation in promotion satisfaction, Pro Amp = Amplitude variation inpromotion satisfaction, Sup Freq = Frequency variation in supervisor satisfaction, Sup Amp = Amplitude variation in supervisorsatisfaction, Co Freq = Frequency variation in coworker satisfaction, Co Amp = Amplitude variation in coworker satisfaction,Wrk Freq = Frequency variation in work satisfaction, Wrk Amp = Amplitude variation in work satisfaction, Strs Freq =Frequency variation in job stressors, Strs Amp = Amplitude variation in job stressors. NM Pay = non-momentary paysatisfaction, NM Pro = Non-momentary promotion satisfaction, NM Sup = Non-momentary supervisor satisfaction, NM Co =Non-momentary coworker satisfaction, NM Wrk = Non-momentary nature of work satisfaction.



91

Table 22

Summary of Hierarchical Regressions Examining the Impact of Job Satisfaction Variability on Turnover Intentions


R2

f 2

B SE B tTurn Int .302**Step 1

NM Pay -.184 .119 -.185 -1.549NM Pro -.101 .119 -.097 -.844NM Sup -.175 .089 -.204 -1.959NM Co -.180 .119 -.158 -1.510NM Wrk -.156 .090 -.177 -1.739

Step 2 .312** .010 .0101NM Pay -.202 .126 -.204 -1.609NM Pro -.112 .124 -.108 -.905NM Sup -.160 .097 -.187 -1.655

NM Co -.200 .125 -.175 -1.596NM Wrk -.158 .092 -.179 -1.709Pay Freq -.496 .777 -.062 -.638Pro Freq -.125 .768 -.016 -.163Sup Freq .622 .753 .081 .825Co Freq .138 .829 .017 .166Wrk Freq .033 .810 .004 .041

Turn IntStep 1 .324**

NM Pay -.176 .123 -.177 -1.432NM Pro -.018 .128 -.017 -.140NM Sup -.197 .098 -.221 -2.008*

NM Co -.205 .120 -.186 -1.704NM Wrk -.202 .095 -.231 -2.132*Step 2 .336** .011 .0111

NM Pay -.147 .134 -.148 -1.099NM Pro -.044 .135 -.041 -.328NM Sup -.217 .104 -.244 -2.085*NM Co -.184 .127 -.167 -1.449NM Wrk -.193 .103 -.221 -1.870Pay Amp .023 .249 .010 .093Pro Amp -.060 .090 -.070 -.671Sup Amp .031 .077 .040 .401Co Amp .080 .106 .078 .754

Wrk Amp -.017 .097 -.018 -.171Note. *p < .05., **p < .01, Turn Int = Turnover Intentions, Pay Freq = Frequency variation in pay satisfaction, Pay Amp =Amplitude variation in pay satisfaction, Pro Freq = Frequency variation in promotion satisfaction, Pro Amp = Amplitude variationin promotion satisfaction, Sup Freq = Frequency variation in supervisor satisfaction, Sup Amp = Amplitude variation insupervisor satisfaction, Co Freq = Frequency variation in coworker satisfaction, Co Amp = Amplitude variation in coworkersatisfaction, Wrk Freq = Frequency variation in work satisfaction, Wrk Amp = Amplitude variation in work satisfaction, Strs Freq= Frequency variation in job stressors, Strs Amp = Amplitude variation in job stressors. NM Pay = non-momentary paysatisfaction, NM Pro = Non-momentary promotion satisfaction, NM Sup = Non-momentary supervisor satisfaction, NM Co =Non-momentary coworker satisfaction, NM Wrk = Non-momentary nature of work satisfaction.



92

Figure 1

The Moderating Effect of Extraversion on the Relationship Between the Frequency

Variation in Job Stressors and the Frequency Variation in Promotion Satisfaction

0.20

0.25

0.30

0.35

0.40

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35Frequency of Variation in Job Stressors

F r e q u e n c y o f V a r i a t i o n i n P r o m o t i o n S a t i s f a c t i o n

Moderate ExtraversionLow ExtraversionHigh Extraversion

.11

.08

.06



93

APPENDIX A

Recruitment Letter

Attention WSU Staff:

I am currently a graduate student collecting data for a research project in

Industrial/Organizational Psychology. Specifically, I am investigating how individuals’

job satisfaction changes over time. This research has important implications for the

study of job satisfaction within my field, as well as for organizations interested in

better understanding the satisfaction of their employees.

I am looking for WSU staff willing to volunteer their time to participate in thisstudy. In order to participate, staff must:

1. Work full time

2. Have continuous access to a computer at work

In general, interested individuals will be asked to complete a 5-minute job

satisfaction survey three times a day on six different business days scattered over a

three week period. This survey will be available on-line, and thus can be accessed

from any computer with Internet access. Volunteers will be compensated $30.00 for

their participation. All information collected during the course of this study will remain

confidential and will only be used for research purposes.

If you are interested, please contact me via email at [email protected].

We can then further discuss your involvement in this study.Thank you,

Lindsey M. Young

Psychology Department



94

APPENDIX B

Momentary Job Satisfaction Survey

1. At this moment, I feel I am being paid a fair amount for the work I do.2. At this moment, there is really too little chance for promotion on my job.

3. At this moment, my supervisor is quite competent in doing his/her job.

4. At this moment, I am not satisfied with the benefits I receive.

5. At this moment, I feel that I receive the recognition that I should for doing a

good job.6. At this moment, many of the rules and procedures make doing a good job

difficult.

7. At this moment, I like the people I work with.

8. At this moment, I feel my job is meaningless.

9. At this moment, communications seem good within this organization.

10. At this moment, I feel that raises are too few and far between.

11. At this moment, those who do well on the job stand a fair chance of being

promoted.

12. At this moment, my supervisor is unfair to me.

13. At this moment, I feel that the benefits we receive are as good as most other

organizations offer.

14. At this moment, I do not feel that the work I do is appreciated.

15. At this moment, my efforts to do a good job are seldom blocked by red tape.



95

16. At this moment, I find I have to work harder at my job because of the

incompetence of people I work with.

17. At this moment, I like doing the things I do at work.

18. At this moment, the goals of this organization are not clear to me.

19. At this moment, I feel unappreciated by the organization when I think about

what they pay me.

20. At this moment I feel that people get ahead as fast here as they do in other

places.

21. At this moment, my supervisor shows too little interest in the feelings ofsubordinates.

22. At this moment, the benefit package we have is equitable.

23. At this moment, there are few rewards for those who work here.

24. At this moment, I have too much to do at work.

25. At this moment, I enjoy my coworkers.

26. At this moment, I feel that I do not know what is going on with the

organization.

27. At this moment, I feel a sense of pride in doing my job.

28. At this moment, I feel satisfied with my chances for salary increases.

29. At this moment, there are benefits we do not have which we should have.

30. At this moment, I like my supervisor.31. At this moment, I have too much paperwork.

32. At this moment, I don't feel my efforts are rewarded the way they should be.

33. At this moment, I am satisfied with my chances for promotion.



96

34. At this moment, there is too much bickering and fighting at work.

35. At this moment, my job is enjoyable.

36. At this moment, work assignments are not fully explained.



97

APPENDIX C

Reduced Momentary Job Satisfaction Survey

1. At this moment, I feel I am being paid a fair amount for the work I do.

2. At this moment, there is really too little chance for promotion on my job.

3. At this moment, my supervisor is quite competent in doing his/her job.

4. At this moment, I like the people I work with.

5. At this moment, I feel my job is meaningless.

6. At this moment, I feel that raises are too few and far between.

7. At this moment, those who do well on the job stand a fair chance of beingpromoted.

8. At this moment, my supervisor is unfair to me.

9. At this moment, I find I have to work harder at my job because of the

incompetence of people I work with.

10. At this moment, I like doing the things I do at work.

11. At this moment, I feel unappreciated by the organization when I think about what

they pay me.

12. At this moment I feel that people get ahead as fast here as they do in other

places.

13. At this moment, my supervisor shows too little interest in the feelings of

subordinates.

14. At this moment, I enjoy my coworkers.

15. At this moment, I feel a sense of pride in doing my job.

16. At this moment, I feel satisfied with my chances for salary increases.



98

17. At this moment, I like my supervisor.

18. At this moment, I am satisfied with my chances for promotion.

19. At this moment, there is too much bickering and fighting at work.

20. At this moment, my job is enjoyable.



99

APPENDIX D

Reduced Non-Momentary Job Satisfaction Survey

1. I feel I am being paid a fair amount for the work I do.

2. There is really too little chance for promotion on my job.

3. My supervisor is quite competent in doing his/her job.

4. I like the people I work with.

5. I feel my job is meaningless.

6. I feel that raises are too few and far between.

7. Those who do well on the job stand a fair chance of being promoted.8. My supervisor is unfair to me.

9. I find I have to work harder at my job because of the incompetence of people I

work with.

10. I like doing the things I do at work.

11. I feel unappreciated by the organization when I think about what they pay me.

12. I feel that people get ahead as fast here as they do in other places.

13. My supervisor shows too little interest in the feelings of subordinates.

14. I enjoy my coworkers.

15. I feel a sense of pride in doing my job.

16. I feel satisfied with my chances for salary increases.

17. I like my supervisor.

18. I am satisfied with my chances for promotion.

19. There is too much bickering and fighting at work.

20. My job is enjoyable.



100

APPENDIX E

Momentary Job Stressors Scale

1. At this moment, I have too much work to do.

2. At this moment, I am unsure about what people expect of me.

3. At this moment, I feel that I am unable to influence my supervisor’s decisions-

even when they affect me.

4. At this moment, I feel that I have a lot of responsibility for the work of others.

5. At this moment, I am working very hard- either physically or mentally.

6. At this moment, I can use my own initiative to do things.7. At this moment, I am under pressure to keep up with new ways of doing things.

8. At this moment, I have to decide things where mistakes could be quite costly.

9. At this moment, I feel I work too many hours.

10. At this moment, I have too little help or equipment to get the job done well.

11. At this moment, I feel my supervisor keeps a close watch on me.

12. At this moment, I have important responsibilities.

13. At this moment, I am confused about exactly what I am supposed to do.

14. At this moment, I feel I am given a lot of freedom to decide how to do my work.

15. At this moment, there are clear, planned goals and objectives that exist for my

job.

16. At this moment, I have the freedom to do as I like on my job.

17. At this moment, I am clear about what needs to be done on my job.

18. At this moment, I feel I am encouraged to make my own decisions.

19. At this moment, I know exactly what is expected of me.



101

20. At this moment, I feel certain about how much or how little authority I have.



102

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ABSTRACT

THE ANTECEDENTS AND CONSEQUENCES OF THEVARIABILITY IN JOB SATISFACTION

byLINDSEY M. KOTRBA

August 2007

Advisor: Dr. Boris Baltes

Major: Psychology (Industrial/Organizational Psychology)

Degree: Doctor of Philosophy

Given the recent increase in the investigation of the intraindividual variability of

job satisfaction (e.g., Ilies & Judge, 2002) the present study sought to further our

understanding of this topic through more comprehensively investigating the potential

predictors and criteria of the frequency and amplitude with which individuals vary in

their levels of job satisfaction over short time frames. It was hoped that by including

both personality (i.e., NA, PA, Neuroticism, Extraversion, and Openness toExperience) and situational predictors (i.e. job stressors), results from this study

would help clarify how individual differences interact with situational characteristics to

explain patterns of within-person variability. In addition, this study also sought to

determine the extent to which job satisfaction variability is important to the prediction

of employee job performance and turnover intentions. Results from the current study

suggest that it may not be useful to distinguish between the frequency and amplitude

with which individuals vary in their levels of job satisfaction over short time frames.

Aside from this general conclusion, the situational predictor and three of the five

personality traits investigated were shown to be important in explaining the frequency



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with which individuals’ coworker, nature of work and promotion satisfaction varied.

Variation in the facet of work satisfaction was also found to be an important predictor

of job performance, and this remained true after accounting for mean levels of work

satisfaction measured cross-sectionally. Finally, results lend some support to

suggest the facets of coworker and nature of work satisfaction to be particularly

important when considering short-term within-person variation. While many of the

hypothesized relationships were not supported, given the current results, it seems

worthwhile to continue to investigate the roles that personality and situational change

play in describing the within-person variation of different facets of job satisfaction aswell as the role of this within-person variation in predicting organizational outcomes.



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AUTOBIOGRAPHICAL STATEMENT

LINDSEY M. KOTRBA

Lindsey Kotrba attended Winston Churchill High School in Livonia, Michigan.

Due to her efforts there she was awarded the Presidential Academic Scholarship

from Wayne State University in Detroit, Michigan where she later attended.

Lindsey earned a Bachelor of Science, graduating Cum Laude with a major in

honors psychology. Her undergraduate thesis entitled “Gender Stereotypes and

Performance Evaluation Accuracy: The Impact of Individual-difference Measures”

was accepted into the 17th

annual conference of the Society forIndustrial/Organizational Psychology.

Lindsey obtained her Master degree from the Department of Psychology

(Industrial/Organizational) at Wayne State University in Detroit, Michigan. Her thesis

entitled “Understanding the Variability of Job Satisfaction” was completed in 2005.

She has remained active in the department through teaching both graduate and

undergraduate behavioral statistics courses as well as introductory I/O psychology

the antecedents and consequences of the variability in job satisfaction

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