EXAMINING THE RELATIONSHIP BETWEEN SELF-ESTEEM AND EXTRINSIC CAREER SUCCESS AMONG NLSY79 YOUNG ADULT RESPONDENTS

EXAMINING THE RELATIONSHIP BETWEEN SELF-ESTEEM

AND EXTRINSIC CAREER SUCCESS AMONG

NLSY79 YOUNG ADULT RESPONDENTS

A Dissertation

Submitted to the Faculty of Argosy University Phoenix

College of Business

In Partial Fulfillment of the Requirements for the Degree of

Doctor of Business Administration

by

Justin P. Barclay

April 2011

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ii




Copyright ©2011

Justin P. Barclay

All rights reserved

iii




A Dissertation


College of Business In Partial Fulfillment of

the Requirements for the Degree of Doctor of Business Administration

by

Justin P. Barclay

April, 2011 Dissertation Committee Approval: Chris Marcum, Ph.D. Date L. A. Pogue, D.M. Claudia A. White, Ph.D. Chris Marcum, Ph.D.

iv




Abstract of Dissertation


College of Business

In Partial Fulfillment of the Requirements for the Degree of Doctor of Business Administration

by

Justin P. Barclay

April, 2011 Chris Marcum, Ph.D. L. A. Pogue, D.M. Claudia A. White, Ph.D. Department: College of Business

v

ABSTRACT

This study tested the theory of a relationship between self-esteem and extrinsic

career success, using data taken from the Bureau of Labor Statistics' National

Longitudinal Survey of Youth (NLSY79ch). Answers were sought as to whether a

relationship exists between self-esteem and extrinsic career success, and whether self-

esteem in combination with job satisfaction also exhibited a relationship with extrinsic

career success. Simple regressions were run for single variable tests, and multiple

regressions for multivariate tests. Self-esteem in simple regressions did reliably impact

extrinsic career success, whereas job satisfaction as a coefficient failed to do so.

Education was found instead to be far more impactful. Additional research to identify

further predictors of this success from similar longitudinal data would be advantageous

for predicting career path.

vi

TABLE OF CONTENTS

Page

TABLE OF TABLES ........................................................................................................ ix TABLE OF FIGURES .........................................................................................................x CHAPTER ONE: INTRODUCTION ..................................................................................1 Purpose and Nature of the Study .........................................................................................1 Self-Esteem and Education ......................................................................................2 Self-Esteem and Occupational Prestige ...................................................................2 Self-Esteem and Career Success ..............................................................................3 Guiding Research Questions ................................................................................................4 Definition of Terms..............................................................................................................4 Education .................................................................................................................4 Extrinsic Career Success ..........................................................................................4 Generation X ............................................................................................................4 Income......................................................................................................................4 Job Satisfaction ........................................................................................................5 Millennials ...............................................................................................................5 Occupational Prestige ..............................................................................................5 Self-Esteem ..............................................................................................................5 The Theory of Self-Esteem and Extrinsic Career Success ......................................5 Theoretical Framework ........................................................................................................6 Assumptions and Limitations ..............................................................................................7 Justification and Significance of the Study ..........................................................................8 CHAPTER TWO: LITERATURE REVIEW ....................................................................10 Identifying Gaps to Elicit Purpose .....................................................................................10 Modern Thinking for Post-Modern Work ..............................................................10 Mintzberg on organizational forms ............................................................11 Schein on organizational development ......................................................12 Gardner on Five Minds for the Future .......................................................13 Establishing a Basis for Career Paths & Self-Regard ........................................................14 Self-Esteem and Extrinsic Career Success ........................................................................15 Appropriateness of Studying Career Paths ...........................................................16 Predicting Employee Inter-Organizational Movement ..........................................17 Self-esteem and Job Satisfaction ...........................................................................18 Self-Esteem as a responsive state ..............................................................19 Self-Esteem as an attribute.........................................................................20 Self-Esteem and the Big-Five Dimensions ................................................21 Self-Esteem as a predictor .........................................................................22 Self-evaluations..........................................................................................24 From self-esteem as source to self-esteem involved..................................25 Self-esteem and program performance ......................................................28

vii

Extrinsic Career Success ........................................................................................29 Avenues of career success inquiry .............................................................32 The self and career success ........................................................................32 Competencies and predictors of career success .........................................37 Career path strategy making ......................................................................38 Career success and talent management ......................................................42 Adding to the Career Paths Knowledge Base ........................................................44 Incorporating Generational and Intergenerational Research .............................................45 Appropriateness of Studying Generation(s)...........................................................45 Intergenerational Research .....................................................................................47 Intergenerational differences in the workplace ..........................................47 Values in intergenerational research ..........................................................50 Channeling intergenerational commitment ................................................53 Incentivizing Intergenerational Commitment ........................................................57 Generation X Research ..........................................................................................58 Generation X as meritocratic individualists ...............................................59 Preparing the workplace for Generation X ................................................63 Adding to the Generational Knowledge Base ........................................................66 Conclusions and Method Appropriateness ........................................................................67 A Review of Method Appropriateness ..................................................................68 Identifying a research method ....................................................................68 Selecting a strategy of inquiry ...................................................................69 Reviewing methods of data collection .......................................................69 CHAPTER THREE: METHODOLOGY ..........................................................................71 Research Design and Instrumentation ...............................................................................71 From Research Questions to Hypotheses ..............................................................72 Null Hypothesis 1 ......................................................................................72 Null Hypothesis 2 ......................................................................................72 Null Hypothesis 3 ......................................................................................72 Null Hypothesis 4 ......................................................................................72 Measures Used in Responding to the Research Questions ....................................73 Self-esteem as an independent variable .....................................................73 Education as an independent variable ........................................................74 Job satisfaction as an independent variable ...............................................74 Occupational prestige as a dependent variable ..........................................74 Income as a dependent variable .................................................................75 Utilization of a Proven Instrument .........................................................................75 Data Collection ......................................................................................................76 Regarding Instrument Reliability ...........................................................................77 Population and Sampling ...................................................................................................78 Selecting a Sampling Strategy ...............................................................................78 Selection Criteria and Population Representativeness ...........................................79 Target Population Description ...............................................................................80 Data Analysis and Interpretation .......................................................................................81 Descriptive Analysis Procedures ...........................................................................82

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Population Reliability via the Internal Consistency of Scales ...............................82 Responding to the Research Questions through Statistical Analysis.....................83 Simple regressions to respond to the first research question .....................83 Multiple regressions to respond to the second research question ..............84 Addressing Assumptions and Limitations of Generalizability ..............................84 CHAPTER FOUR: DATA ANALYSIS AND RESULTS ................................................87 Inclusion Criteria ...............................................................................................................87 Descriptive Statistics ..........................................................................................................89 Internal Consistency of Scales ...............................................................................91 Frequency Distribution ..........................................................................................91 Advancing to Regression Analysis ........................................................................93 Regression Analysis ...........................................................................................................93 Assumptions in Hypothesis Testing ......................................................................95 Test 1, Self-Esteem on Occupational Prestige .......................................................96 Test 3, Self-Esteem and Job Satisfaction on Occupational Prestige ......................97 Test 2, Self-Esteem on Income ..............................................................................98 Test 4, Self-Esteem and Job Satisfaction on Income .............................................99 Including Education Values, Both in Simple and Multiple Regressions .............100 Test 5a, Education on Occupational Prestige ......................................................100 Test 5b, Education and Self-Esteem on Occupational Prestige ...........................102 Test 5c, Education on Income ..............................................................................102 Test 5d, Education and Self-Esteem on Income ..................................................103 Summary of Results .........................................................................................................104 CHAPTER FIVE: DISCUSSION, CONCLUSIONS, AND RECOMMENDATIONS .106 Discussion of Results .......................................................................................................106 Education is Not Merely a Control ......................................................................107 Education and Self-Esteem as Predominantly Complimentary ...........................107 Job Satisfaction Not a Predictor of Extrinsic Career Success ..............................108 Results Pertaining to Research Question 1 ..........................................................109 Results Pertaining to Research Question 2 ..........................................................110 Results Pertaining to Education’s Necessary Emphasis ......................................112 Recommendations for Further Research ..........................................................................113 Conclusions in Relation to Modern Thinking ..................................................................114 REFERENCES ................................................................................................................117 APPENDICES .................................................................................................................140 A. Codebook of Selected Variables ................................................................................141 B. Comprehensive Variable Histograms ........................................................................157 C. Regression Summary Outputs....................................................................................160

ix

TABLE OF TABLES

Table Page 1. Presence of Relevant Versus Available Data Befitting Inclusion Criteria ..................89

2. Descriptive Statistics Concerning Relevant 1998 Survey Data ...................................90

3. Descriptive Statistics Concerning Relevant 2004 Survey Data ...................................90

4. Frequency Distributions for 1998 Self-Esteem, Job Satisfaction, Income, and Duncan

SEI Data .......................................................................................................................92

5. Frequency Distributions for 2004 Self-Esteem, Job Satisfaction, Income, and Duncan

SEI Data .......................................................................................................................92

6. Summary Output When Regressing 1998 Self-Esteem on 2004 Occupational

Prestige .........................................................................................................................96

7. Summary Output When Regressing 1998 Self-Esteem on 2004 Income ....................98

8. Summary Output for Education on Occupational Prestige in a Simple Regression ..101

9. Summary Output for Education on Income in a Simple Regression .........................102

10. Summary Output for Education and Self-Esteem on Income in a Multiple

Regression ..................................................................................................................104

x

TABLE OF FIGURES

Figure Page 1. The Theory of Self-Esteem and Extrinsic Career Success ............................................5

2. Diagram of an Intrinsic Motivation Approach to Career Self-Management ...............33

3. Testing Deconstruction ................................................................................................73

4. Child Sample Sizes by Age and Race/Ethnicity ..........................................................80

5. Completion Rates for NLSY79ch Populations ............................................................81

6. Child Sample Sizes by Age and Race/Ethnicity ..........................................................88

7. Testing Deconstruction ................................................................................................94

8. Residual Plot for Test 1................................................................................................97

9. Residual Plot for Test 2................................................................................................99

10. Residual Plot for Test 5a ............................................................................................101

11. Residual Plot for Test 5b............................................................................................103

1

CHAPTER ONE: INTRODUCTION

Much has been written on self-esteem at work, job satisfaction, and extrinsic

career success. However, little has been written about the relationship between self-

esteem and its direct impact on extrinsic career success. Of the studies that have

analyzed this relationship, none have done so regarding our next generation of corporate

leadership, those from ‘Generation X’. This is at-issue when comparing Generation X

with the Baby Boomer generation, as the research has shown differences in both the

nature of career trajectories, as well as the perspectives on job satisfaction and

organizational loyalty. As the literature continues to amass volumes on driving employee

engagement, elevating job satisfaction, and providing levers for continued empowerment,

understanding must also increase regarding whether this research pertains only to point-

in-time positions, or if it applies across generations and impacts entire career paths.

Purpose and Nature of the Study

The Kammeyer-Mueller et al. (2007) study explored the relationship between

self-esteem and extrinsic career success. To ensure that this research will indeed break

new ground and contribute to the literature, previous studies concerning each of the core

variables has been addressed along with similar analyses.

The purpose of this study will be to test the theory of self-esteem and extrinsic

career success, which relates self-esteem to occupational prestige and income, controlling

for education, among respondents of the Bureau of Labor Statistics' National

Longitudinal Survey of Youth (NLSY79ch). The research will consist of four tests. The

first test will be self-esteem regressed on occupational prestige in a simple regression.

The second will be self-esteem and job satisfaction regressed on occupational prestige in

2

a multiple regression. The third test will be self-esteem regressed on income in a simple

regression. The fourth, will be self-esteem and job satisfaction regressed on income in a

multiple regression. Each will be prefaced by tests concerning the internal consistency of

scales used, the statistics for descriptive analysis, as well as tests for multicollinearity

where necessary; and all four regressions will use a time-series of eight years of survey

data.

Self-esteem and Education.

According to Forsyth, Lawrence, Burnette, & Baumeister (2007) “Theory and

prior research suggest that (a) a positive sense of self–worth and (b) perceived control

over one’s outcomes facilitate constructive responses to negative outcomes” (p. 447). It

is this combined sense of self-worth through self-driven outcomes that forms the basis of

self-esteem & education research over time. From the beginning of experimentation and

corollary research on the combined topic, researchers have assumed that an increase in

one will cause an increase in the other. However, there is some disagreement over which

way the direction lies and whether the combination can be tied to career success.

Self-esteem and Occupational Prestige.

In On Intersubjectivity and Collective Conscience in Occupational Prestige

Research, Guppy (1982) remarked “Recently Social Forces published two significant

contributions to occupational prestige research… Balkwell, Bates, and Garbin (BBG)

sought to test a key assumption in the status attainment research tradition, namely, the

intersubjectivity of occupational prestige evaluations” (p. 1178). How this particular

work became notably relevant to the literature on occupational prestige was its question

of whether the evaluations therein were a result of ‘collective conscience’ or ‘figments of

3

sociological imagination’. While this article did not go on to ultimately put the question

to rest, it did begin the drive toward specificity on agreement regarding occupation, type,

and overall prestige evaluation.

Self-esteem and Career Success.

Although the stance taken is that no direct, longitudinal studies of self-esteem and

extrinsic career success have been done over time, this does not prevent the proliferation

of studies regarding self-esteem and success in general. Feick & Rhdoewalt (1997) write

“A field study was conducted to test the hypothesis that discounted and augmented ability

self-attributions mediate the interactive effects of claimed self-handicaps and academic

success and failure on self-esteem” (p. 147). This study, while specifically targeting self-

handicaps, added substantial weight to the concept of self-attribution in the literature.

Prior to the test discussed in the article, not only had students discussed more of the

obstacles that might lead to their poorer scores on the exam, those poorer scores became a

reality when the graded version was returned to them. While this, and studies like it, did

not contribute to the literature on self-esteem and career success directly, they did

contribute toward the factors mitigating such when a direct correlation between the two

variables could not be established.

A current summary of the literature on self-esteem and career success by

Kammeyer-Mueller, Judge, & Picollo (2007) reads “Because there is an expectation that

individuals with more positive work behaviors will be compensated for their superior

performance (e.g. Judge, Higgins, et al., 1999), it is expected that income will follow” (p.

209). This supports the notion that, while self-esteem and career success are directly

4

related, no pre-existing studies have gone beyond establishing a relationship between

positive work behaviors and superior performance.

Guiding Research Questions

Fundamental to the theory on self-esteem and extrinsic career success, and to the

NLSY79ch dataset, self-esteem and its relationship to the extrinsic career success factors

are considered. The questions for study in this research therefore include:

1. Is there a relationship between self-esteem and extrinsic career success among

respondents?

2. Is there a relationship between self-esteem, job satisfaction, and extrinsic

career success among respondents?

Two observations of particular importance include the fact that prior evidence

reveals self-esteem to be substantially related to career outcomes, and that people

gravitate toward job levels that match their abilities (Kammeyer et al., 2007, p. 217).

These questions are not to confirm or deny a previously established theory. Rather, they

are designed to determine if similar effects can be seen in a more recent survey, which

could lead to potential impacts concerning self-regard and career paths. They are

designed with the intention of beginning to form conclusions about whether current

literature addresses positions in isolation or whether a larger understanding is needed to

address career paths across generations.

Definition of Terms

Education. Highest grade level of formal education completed.

Extrinsic career success. The pairing of occupational prestige and income.

Generation X. Born between 1961 and 1981 (Meister & Willyerd, 2010).

5

Income. Previous year’s income from wages or salary.

Job satisfaction. General rating of job satisfaction.

Millennials. Born between 1977 and 1997 (Meister & Willyerd, 2010).

Occupational prestige. The Duncan Socioeconomic Index (SEI) was used to measure

job complexity and occupational prestige…, which was taken from a number of experts

in the 1950s from Census data on occupational characteristics on the perceptions of the

prestige rating of occupations (Kammeyer-Mueller et al., 2007, p.208).

Self-esteem. Ten items from the 10-item scale developed by Rosenberg (1965)

(Kammeyer-Mueller et al., 2007).

The theory of self-esteem and extrinsic career success. As shown below in Figure 1


Figure 1. The theory of self-esteem and extrinsic career success. Empirically

supported relationships among self-esteem, education, income, and prestige.

Self-Esteem Occupational Prestige

Education Income

A

B (+)

C (+)

D (+)

E (+)

6

Theoretical Framework

Extrinsic career success is a phrase that pays homage to a study done by

Kammeyer-Mueller, Judge, & Piccolo (2007), where work was done to establish a

relationship between self-esteem and its effect on income and occupational prestige.

Therefore, the authors define extrinsic career success as “a construct that includes the

income level of the job as well as the prestige of one’s occupation” (Kammeyer-Mueller,

Judge, & Piccolo, 2007, p. 206). In this landmark study, a dynamic model was tested,

which used varying regressions to analyze the relationships between variables including

self-esteem, education as a control, income, and occupational prestige. It was found that,

while extrinsic career success did not affect self-esteem over time, there was statistically

significant evidence that the reverse was true; self-esteem affected extrinsic career

success instead. This was shown over an eight-year time series and was one of the first

studies to suggest that the repercussions of individual success were related to self-regard.

Indeed, as the significant relationship between self-esteem and income is consistent with

evidence that self-evaluations are positively related to motivation and performance, we

can then begin to research the relationship between self-esteem and extrinsic career

success. Applying this theory to certain populations may give rise to further research in

the future regarding its applications in employee engagement (Kammeyer-Mueller et al.,

2007).

It has been shown that the participants of the Kammeyer-Mueller et al. (2007)

study embodied a relationship between self-esteem and extrinsic career success over an

eight-year period. The participants of this study were respondents of the National

Longitudinal Survey of Youth 1979 (NLSY79). Sponsored by the US Department of

7

Labor, Bureau of Labor Statistics, it was a multi-purpose panel survey that originally

included a nationally representative sample of over 12,000 men and women between the

ages of 14 & 21 at the end of 1978 (BLS, 2006). This population answered questions on

topics ranging from labor market experiences to socioeconomic variables and attitudes.

During the course of this survey, data was collected on self-esteem using Rosenberg’s 10-

item self-esteem scale, as well as annual wages, educational completion and achievement,

and occupational codification that was later translated using the Duncan Socioeconomic

Index to indicate occupational prestige.

Assumptions and Limitations

The research design upon which this study shall be founded is based on a number

of assumptions and limitations. This study assumes that the Bureau of Labor Statistics’

description of NLSY79 data is representative of the generation and is reported to be

accurate, although research will be done on the method by which the sample was chosen

and data collected.

It is also assumed that, as the survey data had been previously collected, and

accessible only through the Bureau of Labor Statistics’ retrieval tool, that the accessible

data is a holistic representation of data collected. The study is limited in scope, in that it

is only intended to answer questions concerning self-esteem, job satisfaction, and

extrinsic career success as they relate to one another and not in isolation.

This study is also limited to respondents of the NLSY79 Young Adult survey,

and will produce results assumed to pertain to this group alone. This study is limited to

those who provided complete responses to the required variables in the years analyzed.

This study was also limited only to those who worked full-time at the time of the survey.

8

As the Duncan Socioeconomic Index will be used to assess occupational prestige, it is

assumed that a strong consensus remains regarding these ratings, and can therefore give a

representative response of prestige. Finally, this study is limited to the potential

relationship(s) of self-esteem and/or job satisfaction on extrinsic career success and will

make no claim as to methodology for impacting levels of either self-esteem and/or job

satisfaction.

Justification and Significance of the Study

Can one’s commitment to position and organization be consistent only when

one’s self-esteem is in agreement with the occupational prestige and income of that

position? “[Job] search behavior, whether it results in turnover or not, is costly because it

absorbs time and energy that might be put to other uses (March & Simon, 1958) and may

engender psychological processes that induce withdrawal behavior and reduce

commitment to the current job and organization (Lock, 1976)” (Bretz Jr., Boudreau, &

Judge, 1994, p. 277). When researching the possible statistical relationship between self-

esteem and extrinsic career success, early results have shown a direct relationship

between increases in self-esteem and resulting increases in occupational prestige and

income as seen in the Kammeyer-Mueller et al. (2007) study. Additionally, those with

lower levels of self-esteem were shown to possess lower levels of occupational prestige

and income as well.

Generation X and Generation Y exhibit different perspectives and expectations

than the Baby Boomer generation. The retention of Generation X members and the

attraction of Generation Y members have proven elusive for many organizations

(Bridgers & Johnson, 2006). This lack of understanding as to the motivational factors

9

begets further inquiry as to whether elevating job satisfaction or employee engagement

alone is enough. Is there a relationship between self-esteem and extrinsic career success

among Generation X workers? The current literature does not sufficiently answer this

question. How do corporations prepare for a generational shift of corporate leadership to

individuals who may exhibit entirely different characteristics than previous generations?

These generations may have behaviors and attitudes about career paths and perceptions of

career success that need to be addressed.

While this research alone will not allow for conclusions germane to this upcoming

generation in its entirety, the respondents of the NLSY79 Young Adult are born into the

years that classify them as members of Generation X. Those studied by Kammeyer-

Mueller et al. and central to their theory were born into the Baby Boomer generation.

This research, therefore, is not to answer questions on Generation X, but to determine

whether further research on this generation is with merit.

10

CHAPTER TWO: LITERATURE REVIEW

In 2008, a qualitative study was performed, which reviewed the differences in

values among four generations across eleven organizations. According to its researcher,

Siebert (2008), “the majority of those interviewed for this dissertation reported wide-

ranging differences in values between the members of the different generations regarding

respect, commitment, work and life balance, expediency, and independence” (p. 3).

While this particular study gave rise to a completed dissertation on conflict and

managerial response, it equally contributed to the literature an understanding of some of

the challenges posed to organizations striving to make sense of the differences which lie

between members of differing generations while at work.

Identifying Gaps to Elicit Purpose

Targeting the efforts of the organization to a committed set of potential employees

for development is integral. To do so requires a proven methodology for predicting

career path prior to determining fit. Literature exists regarding self-esteem, career

success, and intergenerational research each in isolation, but what remains to be explored

are measures of self-esteem and extrinsic career success when studying the Generation X

workforce over time.

Modern Thinking for Post-Modern Work.

This research would be incomplete without ensuring that the conclusions be

drawn from a wide range of similar works and the most relevant research available. This

includes current research on concepts such as organizational development, organizational

form, and perceptions of work in a post-modern working environment, such as that into

which we are entering into today.

11

Mintzberg on organizational forms. As remarked by Mintzberg, Ahlstrand, and

Lampel (1998), “Cognition aside, in reviewing a large body of literature, ten distinct

points of view did emerge, most of which are reflected in management practice… each

has a unique perspective that focuses, like each of the blind men, on one major aspect of

the strategy-formation process” (p. 4). These ten points of view include the Design,

Planning, Positioning, Entrepreneurial, Cognitive, Learning, Power, Cultural,

Environmental, and Configuration Schools. Each school looks at the strategy process

differently and each one includes many sentiments regarding which is the key actor and

what drives strategy. Of particular note in this research is the Environmental School.

The Environmental School depicts the strategy process as being outside of the

organization, and the organization as being more of a ‘mirror’ to what surrounds it. This

aligns with the findings in a review of the literature, which identified research classifying

the Generation X workforce as ‘meritocratic individualists’.

These meritocratic individualists care less about mission, vision, and

organizational loyalty, and more on the alignment of incentivization based on merit. The

work of Mintzberg and others in this regard goes on further to explore organizations as

exhibiting adaptive characteristics based on ‘passive’ leadership, which focuses only on

reshaping the organization to the environment, rather than shaping the environment using

the organization. The consequences of such a premise include both the organization’s

requirement to respond to environmental factors or to be selected out, and they include

the clustering together in distinct ecological-type niches or positions where they remain

until resources become scarce or conditions become too hostile (Mintzberg et. al, 1998).

12

This becomes relevant as Mintzberg’s modern thinking on the post-modern work

environment includes organizations that need to adapt to their surroundings and provide a

deep literary relationship to the meritocratic individualists who make up the Generation X

population and to the NLSY79 Young Adult population specifically.

If we are to structure organizations in a way that is inviting to people who base

success on merit alone, and we now know how dependent that success is on a

combination of education and self-esteem, organizations must be adept at sensing and

adjusting to shifts in aptitude among those who are rising in leadership ranks.

Schein on organizational development. In a recently published article titled A

Corporate Climate of Mutual Help, Edgar Schein, known as MIT’s ‘sage of

organizational culture’ spoke of the need for interdependence to be at the heart

accountability in organizations. Schein (2011) remarked “Better teamwork requires

perpetual mutual helping, [across] boundaries… I don’t see how we’re going to get there

unless we create cultural ‘islands’ – situations in which people can go outside the

organization’s norms and practices and explicitly create [this relationship]” (p. 3). This

recalibrating of organizations speaks to the need to make pointed efforts to reduce or

eliminate the boundaries seen in organizations whereby functions are departmentalized.

Senior leadership does not exercise opportunities to make others ‘feel psychologically

safe’ as Schein describes.

Based on this evaluation, there exists a need to reorganize the organization into

one that exhibits more matrix characteristics, where specialized teams can be created

across cultural boundaries in order to solve the problem at-hand. There is a need to

create a culture of true collaboration, one where the skills of one department, function, or

13

team are not isolated from another based on organization, and one where the organization

itself is not a precursor for how work is done.

As with the research on Generation X, they crave an organization where ample

opportunities to interact abound. They seek opportunities to expand on a pre-existing

skillset by being recruited or potentially self-promoting for projects outside their existing

‘comfort zone’. Meritocratic indeed is the Generation X worker of the post-modern work

environment who can vote on which projects he/she would like to work next quarter, and

which development initiatives he/she would like to take part in as well. In this way,

organizational loyalty is directly impacted by the ability of workers to fulfill a potential

established by self-perception and self-esteem. The coming generation will only identify

with positions that befit self-evaluation, and that equally create opportunities for

consistent growth and challenge.

Gardner on five minds for the future. Howard Gardner is the John H. and Elisabeth A.

Hobbs Professor of Cognition and Education at the Harvard Graduate School of

Education. His text, titled Five Minds for the Future (2006), chronicles the aptitudes that

will be in high demand in the coming future and describes these abilities in greater detail.

These minds include the disciplinary mind, the synthesizing mind, the creating mind, the

respectful mind, and the ethical mind. In order to assess value, one must consider the

world of the future with its ubiquitous search engines, robots, and other computational

devices. The future work force will demand capacities that, until now, have been mere

options (Gardner, 2006). The disciplinary mind is concerned with specificity around a

certain trade or discipline and a deeply rooted expertise upon which much of one’s

remaining actions are built. The synthesizing mind takes in and simultaneously evaluates

14

information from a wide range of sources, much like integrative thinking, which looks

beyond the confines of a discipline and asks from where beneficial information comes

regardless of origin. The creating mind is perhaps the most straightforward since it

concerns the ability to ‘break new ground’ as Gardner puts it. The respectful mind notes

and welcomes differences between human individuals and between human groups and

tries to understand these ‘others’, and seeks to work effectively with them (Gardner,

2006, p. 3). Finally, the ethical mind regards an individual’s ability to balance their

needs in relation to the collective society surrounding him/her.

Recognizing and accepting the differences between these five minds becomes

important since it can be a tumultuous endeavor to understand persons who think

differently. It is easy to misunderstand, to be confused, and to exhibit undetected bias.

Yet, in considering these five minds, we are bestowed with a template with which to

evaluate a person’s ability to contribute to organizational success. This understanding

may allow us to evaluate the best fit for an employee based on self-regard.

Establishing a Basis for Career Paths & Self-Regard

In order to establish a theoretical basis for studying career paths and self-regard,

one must determine what drives the extrinsic career success and the organizational

commitment patterns of the Generation X workforce (Gen-X). One consistency

identified in the prevailing literature is the continued emphasis on the Baby Boomer

generation and its impact on the workforce in this country. As the Baby Boomer

generation reaches its employment horizon, there is a proliferation of research around

succession planning, employee engagement, organizational culture, and the leadership

pipeline as only a few popular topics abound in the popular presses and in the academic

15

literature. This research, including that on Gen-X, as well as the variables inclusive of

the theory of Self-Esteem and Extrinsic Career Success, will form the basis of this review

of the literature. Thus, the sections of this review will include the history of interplay of

the variables of this central theory on self-esteem and extrinsic career success and

germane intergenerational and Gen-X studies. It will also include any literature

contributing to the concepts of predicting organizational commitment and its impacts on

the leadership pipeline. In order to provide a timely basis of comparison, the literature is

from the most recent five years of available research on these topics

Self-Esteem and Extrinsic Career Success

A concise description of the struggle for employee career path stability and the

importance of this stability to organizational longevity and success are described in The

Leadership Pipeline: How to Build the Leadership-Powered Company. According to

Charan, Drotter, & Noel (2011), “Everyone is fighting over a relatively small group of

stars who, even when successfully recruited, tend to move from company to company

with alacrity” (p. 1). They describe The Leadership Pipeline as an approach to

succession planning, which has led to a broad spectrum of succession planning programs

now in-effect among some of the largest organizations currently competing. The

Leadership Pipeline is segmented into six ‘passages’ from managing self to managing

others, from managing others to managing managers, from managing managers to

functional manager, from functional manager to business manager, from business

manager to group manager, and from group manager to enterprise manager (Charan,

Drotter, & Noel, 2011).

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Appropriateness of Studying Career Paths.

The importance of each of these passage transitions includes shifts in focus

including skill requirements, time applications, and work values. These transitions

quickly become pivotal as each passage traversed represents a significant amount of time

invested by both the developing professional and the organization supporting this

transition along the professional’s career path. With each turn, significant investments in

time, capital, and trust permeate the transaction. Yet as this employee develops in skill

and experience, so does the opportunity for movement from company to company as

highlighted by the authors. As Charan, et al. (2011) continues, “Instead of vague

determinations that a company is lacking a talent pool of young leaders, The Pipeline

approach enables you to pinpoint the precise level where problems are occurring and the

skills, time applications, and values at that level where people are coming up short” (p.

132). The Pipeline is an approach that goes beyond assessing the standard knowledge,

skills, and abilities of a given person in a given position. It is a model, which additionally

goes beyond determining the optimal level of results when measuring resource efficacy

alone and forgoes the assessment of an employee’s ability to generate those tangible

results. Instead, it searches the boundaries of what a professional does, knows, and

stands for in order to determine a perfect fit for a range of positions within an

organization. It is believed, however, that this does not come without a potential

shortcoming.

This shortcoming is not in its ability to encompass the process by which a

member of an organization is developed in time for ascension to the next appropriate

rank/passage. Rather, the shortcoming is possibly in its prediction of longevity and

17

success for an individual employee by way of organizational commitment. This is not to

claim that The Leadership Pipeline is not an asset to the organizational development

community or that succession planning as a practice has not tremendously benefited from

decades of work using this model among the Fortune 500 as a notable example alone. It

is to say, however, that not every employee is predictable. Even as the introduction to the

text claims, it is not without movement between organizations regardless of the

investment made by a single company in the defector’s professional development.

Adding a layer of predictability to this inter-organizational movement is of upmost

importance and it arms companies with the ability to be cognizant of where resources

should be allocated. This generational shift has sparked a ‘War for Talent’, which

continues with a level of fervor not seen before among corporate ranks. The potentially

intervening variable of self-esteem, as studied in the theory of Self-Esteem and Extrinsic

Career Success, demonstrates that self-esteem can, not only affect job search and short-

term performance, but also can have effects over a period of years in one’s career


Predicting employee inter-organizational movement.

That predictor, as the theory of Self-Esteem and Extrinsic Career Success,

established a relationship between career paths and self-regard in a prior study among

Baby Boomers where an individual finds one’s self most befitting in an organization

based on self-esteem levels. This was prior to applying The Pipeline development

process to get him/her to that point. It is believed that this theory can do the same thing

among the Gen-X population. As noted by Charan et al., 2011), “Succession planning is

perpetuating the enterprise by filling the pipeline with high-performance people to assure

18

that every leadership level has an abundance of these performers to draw from, both now

and in the future” (p. 167). This process can and should drive the efforts of all who

contribute to an organization’s development. Yet it is only implemented after each level

is populated with those individuals who either feel befitting of that role, or feel they are

on their way to a befitting role as potentially evidenced by the corollary relationship

between self-esteem and occupational prestige over time.

Self-Esteem and Job Satisfaction.

Since self-esteem is a primary driver of the theory of Self-Esteem and Extrinsic

Career Success, it then becomes prudent to seek out what expressions of self-esteem’s

impact have been studied over the relevant past. Studies of this personality trait include

experiments, observations, and case studies on the effects of self-esteem in the areas of

identity, self-worth, grouping, disability, learning, achievement, and success inclusive of

both intrinsic and extrinsic career success. In The Pursuit of Self-Esteem: Contingencies

of Self-Worth and Self-Regulation, Crocker, Brook, Niiya, & Villacorta (2006) describe

“a program of research examining [self-regulation] pitfalls associated with contingent

self-worth and suggest that learning orientations, particularly the willingness to embrace

failure for the learning it affords, foster successful self-regulation even in people with

highly contingent self-esteem” (p. 1749). This research, founded in a meta-analysis of

studies on the intersection of self-worth and self-regulation, covered associations of self-

worth by researching personal/individual validation goals in areas including academics,

appearance, approval, and virtue. The evidence found that the area in which a person

finds him/herself most confident is the same area in which the person is most avid to list

validation goals set to express their value in that area. One such example the study

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provides is of a person who bases their worth on self-virtue, who consequently sought to

validate that they were moral or virtuous more often than others of differing values

(Crocker et al., 2006). The conclusion is then drawn where contingent self-esteem is

predicated on the individual’s performance in the areas most attributed as defining self-

value. These emphasized areas of worth become, not only the strongest measure for self-

induced performance assessment, but also the driver(s) of a person’s overall self-regard.

Self-esteem as a responsive state. Self-esteem can also be influenced by others’

performance as was the case in 2003, when researchers from University College of Cape

Breton measured self-esteem as a predictor of academic success. This was accomplished

by examining the relationship between self-esteem and performance when students had

received information about peers’ success or failure (Covin, Donovan, & Macintyre,

2003). In this study, 120 random Canadian undergraduate students were placed into three

groups. While these groups were all given the same practice questions from the Graduate

Record Examination (GRE), each of the three groups received a different level of

information on the success of prior test-takers on the exam in order to test whether self-

esteem and, therefore, testing ability could be impacted by others’ prior performance. In

addition to the GRE practice questions, all respondents were first given the Rosenberg

10-item, self-esteem scale to measure self-esteem’s impact as a variable to the

relationship of others’ performance and current test performance. Covin, Donovan, &

Macintyre (2003) found that “The present study demonstrates that beliefs about the self

can have complex relationships with behavior – in this case, test performance – and that

the effects of those relationships might relate to the ambiguity of the task at hand” (p.

544).

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Self-esteem as an attribute. To garner an understanding of self-esteem’s current impact,

it also becomes prudent to review its intrinsic origins. One such study was performed in

2007 when Forsyth, Lawrence, Burnette, & Baumeister “predicted that encouraging

students to maintain their sense of self-worth and/or construe their academic outcomes as

controllable would promote achievement” (p. 447). The conclusion of this research was

contrary to its hypothesis, as D and F graded students performed worse as self-esteem

was bolstered. The study targeted those who received a C, D, or F on a psychology

course’s first exam. Of this population, groups were then formed to receive one of two

stimuli over time, where a third control group received none. Based on random

assignment, and on a weekly basis, one student group was given messaging intended to

bolster self-esteem, while the other group received messages pertaining to internal control

and personal responsibility (Forsyth, Lawrence, Burnette, & Baumeister, 2007).

Conducted entirely from email, the study population was contacted via assigned student

email accounts and asked to take part in a study on ‘communication and the use of

email’. Attesting to the communication’s purpose of providing information on academic

performance, each group was given a review question from the week’s in-class material

and they additionally received information on either internal control and personal

responsibility, or messaging intended to bolster self-esteem if in the appropriate,

randomly assigned group. The third group, while still receiving the review question, did

not receive any further information beyond the research question, to serve as an otherwise

unaffected subpopulation. The findings, in using the course’s final examination as the

dependent variable, did not substantiate the initial supposition that bolstering self-esteem

would implicitly support positive academic outcomes. Instead, as described by Forsyth,

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Lawrence, Burnette, & Baumeister (2007), “The pattern of student grades was the

opposite of our predictions, and in fact D and F students in the self-esteem bolstering

condition showed a substantial drop in grades from the midterm (57% correct) to 38% on

the final” (p. 452-453). Later, the authors go on to discuss that perhaps bolstering one’s

self-esteem when no measurable achievements are present can lead to a ‘defensive’

attitude toward outside influence/requirement, thereby eliciting a reaction counter to a

bolstering the effort’s intent. In continuing to explore self-esteem in the academic

environment as a precursor to the workplace, constructs involving self-esteem were also

coupled alongside personality in order to measure achievement.

Self-esteem and the Big-Five dimensions. In addition to concepts such as attribution,

self-worth, and achievement, psychology as a discipline continues the search for

understanding of self-esteem’s relationship with extrinsic outcomes in academic settings

in part by using principles adapted from the Big-Five dimensions. In a study of middle

school students, Hair & Graziano (2003) hypothesized that “personality, self-esteem, and

teachers’ ratings of adjustment during the middle school years predict later life outcomes

during high school” (p. 971-972). Hair & Graziano’s understanding of self-esteem,

however, is not just a detailed account of how self-esteem and personality may predict

later outcomes. Additionally, the authors provide a level of granularity to the personality

construct, such that we may now begin to deconstruct the idea into meaningful segments

of experience while relating it to self-esteem. This gives rise to the potential of finding a

proxy for personality in present-day corporations, where it can then be assessed alongside

self-esteem as was done in this research of middle school learners. The three levels of

personality discussed include Level I or the comparative/decontextualized elements of

22

personality; Level II or contextualized plans, strategies, and concerns; Level III is the life

narrative where sense-making is performed (Hair & Graziano, 2003). The population for

the Hair & Graziano study consisted of 317, south central Texas, middle school students.

Self-reported data was collected on self-esteem and personality and standard scales were

used to obtain measures of the Big-Five personality factors and self-esteem dimensions

(Hair & Graziano, 2003). The findings, as described by Hair & Graziano (2003), include

“Our data suggest early-appearing personality characteristics and aspects of the self in

children are related to how well they adapt later to high school and its academic

environment” (p. 990).

Self-esteem as a predictor. University of Iowa researchers Shepard, Nicpon, and

Doobay (2009) contributed a collegiate level perspective to this building understanding

of what is meant by self-esteem and its potential as an outcomes predictor when they

studied early entrance college students and their responses to self-reported ratings of self-

concept. Twenty-two first-year students enrolled at a large midwestern University were

recruited voluntarily for the study. They were administered the Piers-Harris Children’s

Self-Concept Scale as a pre-test during their first week, and as a post-test during the

initial month of each student’s second semester (Shepard, Foley, Nicpon, & Doobay,

2009). These tests were designed to determine if shifts would occur in self-concept

across time when viewed in relationship to academic achievement, and in early-entrance

collegiate work specifically. Shepard et al. (2009) found that “these aspects of self-

concept may have mildly improved as a result of positive academic experiences,

engagement in more challenging coursework, and interactions with peers who share their

interests, values, and passions” (p. 52). Thus, not only can self-esteem lead to success in

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academic work, but academic work may contribute equally to increases in self-esteem, as

a cycle of self-fulfilled expectations of success continue throughout a learner’s academic

career.

While the above may certainly contribute to the understanding of what positive

self-regard and equally positive academic outcomes may do to elicit an overall positive

experience in a confident learner, antithetical studies also exist where perspectives were

taken regarding those who had less positive experiences. Inclusive of these studies is one

by Zhang, Zhao, & Yu (2009) in the Journal of Social Behavior and Personality. The

intent was to learn more about how playing the role of either low-achiever or higher-

achiever impacted performer self-esteem. As described by the authors Zhang et al.

(2009), “The results of the current study provide powerful evidence for the proposition

that being able to hide socially devalued aspects of the self may enable individuals to

minimize the impact of the devalued identity on others’ judgments” (p. 809). To identify

these potential consequences, 76 low-achievement (LA) adolescents and 75 high-

achievers (HA) were first identified and then administered the Rosenberg Self-Esteem

Scale. The students were then introduced randomly to one of two situations. Each

participant was instructed that an interviewer, described as a respected expert in the field

of education, would like to interview some good students and give advice on learning

strategies (Zhang, Zhao, & Yu, 2009). One of the two groups received these instructions,

while the other was given similar instructions with the words “good student’ substituted

with “low-achieving student”. The results were that those who were instructed to

represent a good student reported higher self-esteem after the interview, and those who

were instructed to play the role of a low-achiever presented with lower self-esteem after

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the interview. These results were consistently measured by the State Self-Esteem Scale,

and were consistent across actual achievement statuses elsewhere. This study showed

that, not only can self-esteem affect academic outcomes, it can even affect the outcomes

based on a fabricated representation.

Self-Evaluations. Self-esteem and outcomes do not present reciprocal affect in the

academic environment alone, however. In a study of Self-Ambivalence and Reactions to

Success Versus Failure, Riketta & Ziegler (2006) presented research, which, “tests the

innovative hypothesis that self-evaluation reactivity traces back to self-ambivalence (i.e.,

the co-presence of positive and negative self-evaluations)” (p. 547). To do so, the

authors first measured self-ambivalence and baseline self-esteem. Then they introduced a

success or failure experience, while following-up with measurement of cognitive self-

evaluation and affective reaction. The study was predicated by how ambivalence was

defined. Ambivalence denotes the co-presence of negative and positive evaluations of

the same target, which is then delineated across two operationalizations of ‘structural

ambivalence’. This deals simply with evaluations of the target and ‘experienced

ambivalence’ dealing with both evaluations of the target and tension resulting from this

awareness (Riketta & Ziegler, 2006). In a randomized experiment of 87 German

students, the population completed an inventory relating to their experienced

ambivalence and then another on structural ambivalence. Then they were tasked with

completing items taken from Raven’s Advanced Progressive Matrices (APM). The

findings, as described by Riketta & Ziegler (2006), include “this research showed that

people with strongly (vs. weakly) ambivalent attitudes toward social groups or toward

consumer goods change their evaluations of these targets more strongly after receiving

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positive or negative information about them” (p. 557). Self-esteem is not only supported

in its ability to affect how one perceives one’s environment, but by the tension provided

by the level of ambivalence, which then can multiply this affect to the extent of

moderating, not only how an individual finds their environment, but how their reaction(s)

to it influences their self-regard as well.

Riketta & Ziegler (2006) commented in a more recent article “People differ in the

extent to which their self-evaluations fluctuate in response to positive and negative

events” (p. 547). This is not to say that self-esteem and career success have yet to be

statistically correlated in any way. This is to say that self-esteem is not a constant and,

therefore, cannot be treated in a single span of time. Thus, in further studies where self-

esteem is evaluated or compared with other variables, a time series must be identified

where fluctuations or changes in self-esteem can be tracked in comparison with changes

to the opposing variable(s) identified.

From self-esteem as source to self-esteem involved. Crocker, Brook, Niiya, &

Villacorta and their study of the contingencies of self-worth and self-regulation

highlighted how contingent self-esteem can define us, and how our own views of

personal performance are predicated on strong attributions of perceived personal

strengths and their performance. Covin, Donovan, & Macintyre showed how others’ past

performance can, not only be seen as a potential indicator for personal, individual

performance, but can actually serve as a precursor to drive task ambiguity when a

disparity between others’ past performance and personal performance exists. Forsyth,

Lawrence, Burnette, & Baumeister proved that self-esteem can, not only be a central

driver for performance, but also can be a central driver of perceptions of performance as

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well. In other words, bolstering the self-esteem of those exhibiting poor academic

outcomes only further reinforced the behavior and drove performance further downward,

causing distance between performer and those representing authority. Hair & Graziano

pushed the boundaries of how we define self-esteem further. They coupled the Big-Five

personality factors alongside a deeper granularity of the contextualization of levels of

personality when in contrast to environment, and they did so in order to study self-

esteem’s application to levels of adaptation and readiness over time. Shepard, Nicpon,

and Doobay measured the self-concept over an early academic career in higher education

in order to determine fit in early college entry. They found that self-esteem was

supported along with further perceptions of growth and development in the learner as a

single, initial semester progressed. Zhang, Zhao, & Yu took these applications of self-

esteem and personality and applied them in an environment where learners were

instructed to portray the performance of others when in an interview setting, while

assessing self-esteem both before and after the event. This study proved that simply

portraying the low-achiever as a low achiever led to lower levels of self-esteem.

Portraying a person as a high-achiever, when this was predominantly not the case in

reality, led to higher levels of reported self-esteem.

Riketta & Ziegler, taking the application of self-esteem, personality, and

performance attribution, measured levels of self-ambivalence when in the context of

highly contingent self-esteem. In so doing, they proved that those characteristics driving

self-worth could moderate highly the perception of environment, relative self-worth, and

fit. What is commonplace throughout these studies is the inclusion of only a small list of

instruments used in measuring perception, self-esteem, and ambivalence. These

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instruments included the Rosenberg Self-Esteem Scale, Duncan’s New Multiple Range

Test, the Psychology Response Recording System (PRRS), the Piers-Harris Children’s

Self-Concept Scale, and Raven’s Advanced Progressive Matrices (APM). The

Rosenberg [10-item] Self Esteem Scale was the instrument used more repeatedly and

consistently when measuring self-esteem. As further supported by Zhang, Zhao, & Yu

(2009), “The Rosenberg Self-Esteem Scale has been widely used to measure individual’s

trait self-esteem” (p. 807).

It may be concluded that self-esteem is both a widely understood concept and a

widely studied concept as well. Measurements such as the Rosenberg Self-Esteem Scale

have been delivering consistently reliable results for over 40 years, and little has changed

the instrument. What continues to evolve, however, is how we apply measurements of

self-esteem to varying environmental attributions. One such application regards self-

esteem among the gifted and involving self-esteem measurements to further study the

feelings and perceptions of this population. Vialle, Heaven, & Ciarrochi (2007)

“examined the relationships among personality factors, social support, emotional

wellbeing, and academic achievement in 65 gifted secondary students, a sample drawn

from a longitudinal study of over 950 students” (p. 569). This study, while focusing on

the gifted, specifically focuses on the differences between relatively low-achieving and

relatively high-achieving learners in this gifted adolescent population. Collected

information included giftedness measures, personality measures, a self-esteem measure

(also using the Rosenberg Self-Esteem Scale), a social support measure, a teacher rating

measure, and academic grades. Containing both pretest and posttest components, the

study invited students to participate in a study on ‘Youth Issues’, where student

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questionnaires were administered during the first half of the school year, and teachers

completed a behavioral checklist and provided grade data at the end of the academic year

(Vialle, Heaven, & Ciarrochi, 2007). The results, covering affective outcomes, social

support, teacher ratings, and academic outcomes, showed a great disparity between the

academic outcomes of gifted students and the expected levels of self-esteem and

emotional health within the grouping. Specifically, while social support was found to be

abundant among those supporting the gifted population, and academic outcomes of the

same population were equally strong, affective outcomes of this group were to the

contrary of those surrounding/supporting the gifted as these levels showed increased self-

reported isolation and dissatisfaction. Vialle, Heaven, & Ciarrochi (2007) described this

by saying “the findings of our research point to the need for educators to be sensitive to

the social and emotional states of gifted adolescents and recognize their vulnerabilities”

(p. 580).

Self-esteem and program performance. Involving self-esteem at the academic level

has been coupled by self-esteem involvements in programs affecting the workplace

environment as well. In a study of self-esteem during a three-year nursing program,

relationships were quantified in terms of both self-esteem throughout the program and its

effects on patient care. Randle (2002), who performed the study, reported, “although the

majority of students start their nurse training with normal self-esteem, they leave the

course with below average self-esteem” (p. 143). This was further defined in detail when

adding the context that ‘professional self-esteem’ remained steady, yet it was ‘global self-

esteem’ which suffered greatly. In a complimentary study, it was evidenced that this

becomes tantamount. Personality plays a major role in research on work behavior and

29

work-related outcomes, and personality traits have been shown to influence individual

and organizational outcomes such as job performance (Zhang & Arvey, 2009).

According to Baumeister and Vohs (2003), ‘‘contemporary self-regulation theories aim

to understand how, over periods of days, weeks, and years, people resist temptations,

persist with effort, and carefully weigh options to choose the optimal course of action to

reach their goals’’ (p. 197). While this is only intended to be a very summarized result of

the overarching literature review on the topic, what the data begin to show is whether

self-esteem can cause changes in academic achievement and vice versa. Although the

literature on this specific relationship alone spans roughly 45 years of research, the

underlying principle is that, while education does not necessarily affect self-esteem, self-

esteem can have an impact on academic achievement when assessed early on. If no

substantial change is seen in trajectory over time, regardless of academic achievement,

initial levels of self-esteem remain.

The theory of Self-Esteem and Extrinsic Career Success looks at these

relationships when assessing self-esteem as a predictor of occupational prestige, and

elicits a call to action in order to better understand the potential that self-regard has to

impact the career paths of the Generation X workforce. To understand this implication,

however, also requires a more detailed review of what is meant by the extrinsic career

success component of the theory of Self-Esteem and Extrinsic Career Success.

Extrinsic Career Success.

The theory of Self-Esteem and Extrinsic Career success purports that the

relationship from self-esteem to extrinsic career success is based on the theory of self-

consistency, which proposes that individuals seek to enact behavior that corresponds to

30

their self-esteem (Kammeyer-Mueller et al., 2007). Yet, in order to explore those

corresponding behaviors, more must be known about how the literature defines extrinsic

career success prior to establishing its intent as the empirical result of such reactions to

self-esteem. The challenge in greater detail is best defined by Heslin (2005) as “Several

avenues for improving the conceptualization and measurement of both objective and

subjective career success are identified... paramount among these is the need for greater

sensitivity to the criteria that study participants, in different contexts, use to construe and

judge their career success” (p. 113). In a study titled Career Success in a Boundaryless

Career World, Arthur, Khapova, & Wilderom (2005) “cover adequacy of research

designs, further dimensions of career success, broader peer group comparisons, deeper

investigation of the subjectively driven person, and seeing new connections between

boundaryless career theory and career success research” (p. 177). The challenge of this

meta-analysis was to synthesize an appropriate sequence in order to ‘bring about a

rapprochement’ between career theory and the research on career success. This study

was predicated on the division between types of career success (objective and subjective)

and on five attributes considered relevant to the research on career success. Where

objective career success was sustainably defined as the unfolding sequence of a person’s

work experiences, subjective career success may be defined as the individual’s internal

apprehension and evaluation of his career across any dimensions important to the

individual (Arthur et al., 2005). Possible dimensions suggested in the research-included

income, employment security, the location of work, and status to name a few. Arthur et

al. (2005) ultimately concluded “Career success research makes inconsistent use of

contemporary career theory, particularly regarding the interdependence of subjective and

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objective career success and how this interdependence unfolds over time. Boundaryless

career attributes of inter-organizational career mobility and extra-organizational career

support have often been neglected” (p. 197).

The impact of disconnects among the characteristics of contemporary career

theory extend beyond objective and subjective career success alone. However,

applications at the physiological and psychological levels abound as well. One such

example as described by Ballout (2007) posits, “The psychological contract is generally

defined in terms of a set of individual beliefs, shaped by the organization, regarding terms

of an exchange agreement between individuals and their organizations” (p. 741). The

distinction of additional attributes becomes meaningful as it is discovered that career

success is, not only based on the worker perceptions of intrinsic and extrinsic success, but

also on the mental and even physical reactions to such success as well. Drawing upon

organizational psychology foundations, these reactions to the perception of career success

extend to a concept described as person-environment (PE) fit. PE fit draws on the

underlying assumption that the degree of fit or match between people and their

environment produces important outcomes or benefits for employees (Ballout, 2007).

Person-job fit or PJ fit entails the relationship between the attributes of the worker and

the attributes of the job. These measures of fit give rise to a deeper understanding of how

conclusions of self-regard play a role in defining how one might assess their fit to either

environment or job. Where these concepts come to a precipice, is in the concept of

person-organization (PO) fit. Described as the compatibility between people and

organizations, manifestations of this congruence include organizational attraction and

employee selection as well as employee commitment, satisfaction, and intention to quit

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(Ballout, 2007). Thus, although one’s self-esteem can be seen as a primary driver within

the theory of Self-Esteem and Extrinsic Career Success, it is largely on how that career

success is defined and impacted as the relationship between this theory and career paths

via perceptions of career success manifest. Once factoring for the psychophysiological

profile of career success, as detailed in a study of the same name, adding a psychological

and physiological level of analysis provides greater insight into extrinsic career success

measures in the form of salary and job position (Kovacs, 2007).

Avenues of career success inquiry. The job market is undergoing large-scale changes

and individual occupational careers are changing as well. A common core in different

conceptualizations of contemporary forms of occupational careers is the assumption that

there is a high need for individuals to regulate their careers strategically (Abele & Wiese,

2008). Advances in studying the motivators of career success have elicited a newfound

understanding of a shift from passive to active career management. This shift has given

rise to avenues of career success inquiry including personality, competencies and

predictors, career path strategy making, and career success’ impact on talent

management.

The self and career success. How career success is both measured and managed has

been largely attributed to perceptions of the self. Quigley & Tymon (2006) developed a

paper, which “proposes a model that depicts how four components of intrinsic motivation

–meaningfulness, competence, choice, and progress – can contribute to career self-

management” (p. 522). In this study, a literature review was performed where six

propositions were first developed and then researched further. These propositions

included stances on the influence of global assessments and interpretive styles, individual

33

initiative and interpersonal facilitation, intrinsic motivation and positive assessment,

career self-management’s relationship with career success, subjective versus objective

career success, and those successes’ cyclical relationship with global assessments and

interpretive styles (Quigley & Tymon, 2006). The findings included the following

proposed integrated model of intrinsic motivation shown in Figure 2.

Figure 2. Diagram of an intrinsic motivation approach to career self-management.

This aforementioned figure depicts an iterative cycle, whereby a feedback loop is

created to provide consistent, recurring feedback regarding one’s career success.

Instigated by four sources of intrinsic motivation, the model shows these four sources as

feeding the actions of one’s self-management of career, deriving both subjective and

objective career success. Further findings from Quigley & Tymon (2006) state “The

model suggests the level at which a person experiences meaningfulness, choice, and

competence, and the progress being made in the experience of each of these factors can

help a person answer the question ‘What’s next?’” (p. 538). In-line with the research on

the implications of self-management, literature published in the Journal of Occupational

and Organizational Psychology details an analysis of the nomological network of general

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self-management strategies, specific self-management strategies and central indicators of

career success, i.e. objective career success, self-referent subjective success, and other-

referent career success (Abele & Wiese, 2008). The study included 1,458 working

professionals who had previously graduated from a large German University. After

being sent a career development questionnaire, researchers received a response from

1,265 or 86.8% of those polled. For these 527 women and 738 men, variables measured

included selection, optimization, career planning, self-referent subjective career success,

other-referent subjective career success, objective career success, grade point average,

and study duration. Abele & Wiese (2008) concluded “different contexts of goal pursuit

need to be taken into account… knowing optimization strategies and being competent in

applying them to a specific context will lead to an optimal outcome both on an objective

and a subjective level” (p. 747). This domain-specific, dichotomous classifications of

objective and subjective career success persist through much of the current literature. In

a study titled Reconceptualizing Career Success, Gunz & Heslin (2005) conclude, “to the

extent that careers are socially constructed, people’s subjective interpretations of success

(in either of its meanings, that of a favorable outcome or simply that which flows from

events) can display patterns of shared understanding amongst people sharing social

contexts” (p. 109). Thus, although objective and subjective career success remain

separately regarded constructs when comparing the self to its regard of career success,

evidence has begun to amass showing that objective career success is not the only

structured form of the outcome. Subjective career success one day may be regarded as

equally structured and/or predictable and, therefore, more apt for thematic study across

larger groups of persons.

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As a potential window into learning more of these thematic elements of subjective

career success, Linda Taylor of Capella University sought to investigate if there was a

relationship between participating in certain social activities and achieving extrinsic

career success through the use of nontraditional business skills (Taylor, 2008). While the

social activities included sporting activities, volunteer activities, and drinking activities,

the nontraditional business skills included networking, mentoring, political skills, and

social skills. Surveying respondents from both a United Way Golf Tournament and an

Annual Conference of the Association of Financial Professionals between 2006 and 2007,

114 online surveys were analyzed for meaningful regression among the aforementioned

variables. Taylor (2008) found that “Participating in these activities and the use of

nontraditional business skills is not meant to take the place of traditional business skills

such as education, work quality, or experience. It can, however, provide the additional

value needed to differentiate an individual from competition and contribute toward career

success” (p. 171). As individuals are involved in these activities both as a precursor to,

and as a stimulant for career success, research on the relationships between the self and

these activities and how the resulting success is attributed to the self must continue.

To understand more of these relationships, we return to the interconnectedness of

objective and subjective career success. Abele & Spurk describe these relationships

(2009) “Whereas a number of studies are concerned with the association between

objective and subjective career success, there is almost no research on their

interrelationship over time” (p. 803). Upon review of variables including ‘time or career

phase’ and ‘specific assessment’ of subjective success, the researchers collected data on

attainment and self-assessment over time. While controlling for GPA, gender, and study

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major, the model looks at changes to attainment and assessment at four intervals, 14

months, three years, seven years, and ten years after graduation (Abele & Spurk, 2009).

To do so, longitudinal data was collected via survey at the intervals described with a

population of 510 women and 715 men consistently responding throughout the five

waves and including a collection period after final exams were passed. Measures for the

study included objective career success, other-referent subjective career success, self-

referent subjective career success, and grade point average.

Using a latent growth curve modeling approach, Abele & Spurk (2009) found:

The influence of subjective success on objective success should not be

underestimated. The size of this influence is larger than of many other

psychological predictors of career success. Subjective success is desirable

for individuals and it seems to be desirable for organizations, too.

Subjectively successful professionals become objectively more successful,

and this is advantageous for both the individual and the organization. (p.

821)

The primary disconnect between these prior evaluations and those of occupational

prestige today deal with the position or occupation held. Prior evaluations of occupation

prestige dealt largely with career trajectory, whereas current measures of occupational

prestige deal largely with classifying position (i.e. garbage collector, dental assistant,

lawyer). Smulyan (2004) describes it saying, “Teaching and medicine, although both

helping professions, have different levels of prestige in society and present aspirants with

different kinds of choices” (p. 231). The particular work referenced by the quoted text

deals with gender and social change. So, even as occupational prestige continues to be

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evaluated both at the level of collective consensus and of current occupation, additional

factors ranging from gender to socioeconomic status to level of difficulty for entry are

beginning to affect its calculation.

Competencies and predictors of career success. While the influences of career success

and its attributions are numerous, what have garnered further specificity are the

competencies and predictors of career success. One such study by Ng, Eby, Sorensen, &

Feldman (2005) further describes this need, “Although several studies have taken broad-

based multivariate approaches to identifying the predictors of career success, there have

not been large-scale systematic attempts to summarize the existing literature” (p. 367).

To do so, Ng et al. performed a comprehensive meta-analysis of the predictors of both

subjective and objective career success. Variables for this study included Human Capital

predictors, Organizational Sponsorship and Socio-Demographic predictors, Stable

Individual Difference predictors, gender as a moderator variable, and common method

bias as a moderator variable. The findings as described by Ng et al. (2005) purport “Our

findings not only highlight the importance of human capital, organizational sponsorship,

socio-demographic, and stable individual difference variables in understanding career

success, but also suggest that researchers may need to examine other predictors and

moderators to more fully understand the complex phenomenon of career success” (p.

399). This was concluded after the evidence supported a conclusion of both the contest-

mobility model and the sponsored-mobility model carrying the potential to aid in

understanding career success. What was also evident included the conclusion that salary,

promotion, and career satisfaction are ‘unique constructs’. This is further supported by

Vos, Clippeleer, and Dewilde (2009), who state “Using structural equation modeling, we

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tested a theoretical model that specified the relationships between career progress goals,

career planning, networking behaviors, and career success” (p. 761). As the authors

hypothesized that “graduates’ networking behaviors will be positively related to objective

career success”, a two-wave longitudinal survey was administered among graduates

completing college and transitioning to the work force. Once regressions were run

against the 269 participants’ response data, results showed that the goal to make career

progress affects graduates’ proactive behaviors and that proactive career behaviors are

related to career success in the early career (Vos et al., 2009). To learn more of the

individual differences in predictive power of such proactive behaviors, research by

Crespo (2007) of Columbia University is mentioned as his work “was designed to more

comprehensively examine individual differences as antecedents to both leadership and

effectiveness and extrinsic career success” (p. 1). To test his hypotheses, Crespo

collected personality data, cognitive ability test data, leadership effectiveness scale data,

job performance data, and salary data. In using sample sizes between 630 and 870

(depending on which hypothesis was being tested), Crespo (2007) found emotional

stability and extroversion were related to extrinsic career success, whereas job

performance did not mediate the relationship between individual difference variables and

extrinsic career success (Crespo, 2007).

Career path strategy making. A shaped career path is a purposeful, explicit goal. How

a career path is shaped depends largely on a number of factors pertaining to the

individual. In some instances later in this review, it will be shown where commonalities

can also be found at the generational level, yet most persist with the individual. One such

study from Kern, Friedman, Martin, Reynolds, & Luong (2009) regards

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conscientiousness, career success, and longevity. As described by the authors,

personality traits such as conscientiousness and achievement motivation may represent

behavioral correlates of the mental processes that partially underlie both career success

and longevity (Kern et al., 2009). For this research, extrinsic (objective) and intrinsic

(subjective) career successes were each considered variables alongside intelligence,

childhood personality, physical health and adjustment, and mortality. In analyzing 693

participants with 66 years of longitudinal data (1940-2006), the authors ran regressions

across the aforementioned variables. Kern et al. (2009) found “Our findings indicate that

career success is indeed relevant to longer life across six decades, but this appears

moderated by childhood variables likely relevant to executive functioning” (p. 160).

As executive functioning has been defined in this study to include careful

planning, impulse control, organization, and reasoning, the implication becomes that

those who exhibit higher levels of executive functioning are more likely to achieve career

success. An ambitious study from Lila Lenoria Carden of Texas A&M University (2007)

titled Pathways to Success for Moderately Defined Careers: A Study of Relationships

Among Prestige/Autonomy, Job Satisfaction, Career Commitment, Career Path, Training

and Learning, and Performance as Perceived by Project Managers studied how new

career paths can be found to be non-linear and can result in undefined professional

advancement opportunities for managers and employees in a variety of contexts (Carden,

2007). To further explore, her research included a 27-item survey instrument and six

variables, including the dependent variable of performance, alongside five independent

variables to include autonomy/prestige, career path, learning and training, job

satisfaction, and career commitment. For those aspects most relevant to career path

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strategy making, an emphasis is placed on the results for that variable, which are included

in this review. The key finding in this instance becomes Carden’s (2007) conclusion

“Moderately defined career professionals that jointly work with organizations to plan,

design, and communicate career paths will be more likely to take ownership of the

process, effectively work to execute the career plans, retain employment in the

organization, and increase performance” (p. 160).

In addition to conscientiousness, executive functioning, and joint planning &

organization accountability for career success, other sources of strategy making can

include exploitation of understood personality traits, and an emphasis in work-family

conflict. To begin with personality, Sutin, Costa, Miech & Eaton (2009) state “The

present research addresses the dynamic transaction between extrinsic (occupational

prestige, income) and intrinsic (job satisfaction) career success and the Five-Factor

Model (FFM) of personality” (p. 71). This research includes an emphasis in

psychology’s contribution to understanding career paths wherein FFM contributes an

understanding of the self as an antecedent to understanding more of what shapes a

person’s career path. To understand what the self through the lens of FFM means

requires an explanation of the components of the model. The FFM is an empirically

derived model of personality that characterizes the individual’s emotional, interpersonal,

experiential, attitudinal and motivational style along five broad dimensions: Neuroticism,

Extraversion, Openness, Agreeableness, and Conscientiousness (Sutin et al., 2009). A

total of 731 participants were selected among the Baltimore Epidemiologic Catchment

Area (ECA) study and measured across variables including personality, occupational

prestige, personal income, and job satisfaction. Upon consideration for FFM, and in

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taking these data into account for the 731 measures respondents, the authors concluded

“Measured concurrently, controlling for sex, ethnicity, age and education, domain-level

personality was associated with income and job satisfaction, but not prestige:

Emotionally stable and conscientious participants reported earning higher incomes and

reported more satisfaction with their jobs” (p. 80). Thus, consistent with the findings

above, conscientiousness continues to contribute largely to career path strategy making’s

success, with emotional stability being added as another key factor to the success of long-

standing plans for career success. Finally, when including elements of work-family

conflict, more can be understood of its relation to organizational effectiveness and

domain-specific determinants. To garner this understanding, Ballout (2006) worked to

“develop and present a tentative framework for understanding the relationships among

antecedents of interrole conflict” (p. 437). The framework reviews ‘individual-specific’

variables such as gender, parental demand, and working spouses, while reviewing such

‘work-specific’ variables as job involvement, job stressors, and job social support. From

these reviews of the germane variables, two resulting conflicts were identified between

FIW (referring to those responsibilities to family which interfere with work roles), and

WIF (referring to those responsibilities to work which interfere with family roles).

Ballout found that organizations need to consider a new ‘infrastructure’ in their career

development models, accounting for balancing work-family relationship and retaining a

more committed workforce; this more holistic approach integrates employees’ career

roles and home lives giving organizations more latitude and credibility and enhancing

productivity (Ballout, 2006).

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Career success and talent management. Over the past generation, talent management

practices, especially in the United States, have been fairly dysfunctional, leading

corporations to lurch from a surplus of talent to shortfalls to surpluses and back again

(Cappelli, 2008). The introductory statement to the HBR article Talent Management for

the Twenty-First Century describes the plight felt by today’s corporations, in an era

where both the supply and demand of talent rest in environments as unstable as the

economy itself. At the precipice of this issue are the considerations for career paths

described thus far. With the greater majority of the aforementioned variables being as

descriptive of personal characteristics as much as organizational, solutions for the merger

of such concepts as career success and talent management become less frequently

available. One solution as proposed by Cappelli (2008) includes “The issues and

challenges in managing an internal talent pipeline—how employees advance through

development jobs and experiences—are remarkably similar to how products move

through a supply chain: reducing bottlenecks that block advancement, speeding up

processing time, improving forecasts to avoid mismatches” (p. 2). Hall (1976)

introduced the concept of the ‘protean career’, characterized by individuals taking the

lead in career management, driven by the change of personal rather than organizational

needs. He even argued that the ‘career’ no longer exists within organizations (Kim,

2005). The meeting place of these ideas may rest in the concept of organizational

interventions. Kim (2005) in Organizational Interventions Influencing Employee Career

Development Preferred by Different Career Success Orientations describes a “study

[which] explores Korean employees’ perspectives on organizational interventions that

influence their career development, according to personal definitions of career success (p.

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48). A sample of 1,000 respondents of a wireless communication company responded to

a survey, which identified career success orientations and preferred organizational

interventions. Kim (2005) describes the findings as “From a practical perspective, at the

organizational level, the findings of this study imply that organizations may want to

design their career mobility systems or performance incentive systems in accordance with

employees’ career orientations” (p. 59).

Where the existing literature becomes scant, is when the task becomes elucidating

what is meant by creating organizational-individual alignment for like-minded career

planning in order to optimize career success in talent management. Research, which has

shed some light on this topic, includes Martin & Schmidt (2010) in How to Keep Your

Top Talent, wherein they list the 10 critical components of a talent development program

(p. 6). These components include (a) explicitly test candidates in three dimensions

(ability, engagement, and aspiration); (b) emphasize future competencies; (c) manage the

quantity and quality of high potentials; (d) forget rote functional or business-unit

rotations; (e) identify the riskiest, most challenging positions; (f) create individual

development plans; (g) reevaluate top talent annually; (h) offer significantly

differentiated compensation; (i) hold regular, open dialogues; (j) replace broadcast

communications about the company’s strategy with individualized messages for

emerging leaders (Martin & Schmidt, 2010).

“We conducted a survey of human resources executives from 40 companies

around the world in 2005, and virtually all of them indicated that they had an insufficient

pipeline of high-potential employees to fill strategic management roles” lament Ready &

Conger (2007) of Make Your Company a Talent Factory. In an industrial environment

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where organizations are forced to forgo contracts, which contribute to either substantial

gain in revenue and/or market share, few organizations have in-place what the authors

call “talent factories”. In these scenarios, they marry functionality, rigorous talent

processes that support strategic and cultural objectives with vitality, emotional

commitment by management that is reflected in daily actions (Ready & Conger, 2007).

While the study speaks to the development and retention of key personnel in adopting

this approach, the further benefit to an organization employing a Generation X workforce

is a further alignment with some of the preferences of the population including

achievement, realism, and conscientiousness emphasized in evidence-based decision

making.

Adding to the Career Paths Knowledge Base.

There is, of course, an existing literature on self-esteem and careers.

Unfortunately, this research does not address the proposition from identity theory that

self-esteem and career success can influence one another (Kammeyer et al., 2007). As

the relationship between self-regard and career paths is not yet fully elucidated, this

research is poised to answer that question for the Gen-X population, thereby delivering an

assessment of how one affects the other. As was described by Hill & Hemp (2008),

“First, they (invisible people) are the well-known “demographic invisibles.” These are

people who, because of their gender, ethnicity, nationality, or even age don’t have access

to the tools—the social networks, the fast-track training courses, the stretch

assignments—that can prepare them for positions of authority and influence” (p. 3). Yet,

to maximize the impact these tools can and should have on our next generation of

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leadership, we must continue to gain more understanding of how self-regard may act as a

predictor of career path(s) over time.

Incorporating Generational and Intergenerational Research

Earlier this year, a text titled The 2020 Workplace: How Innovative Companies

Attract, Develop, and Keep Tomorrow’s Employees Today became widely available. The

central premise of the text regards the changes to the working environment and culture of

the forward-looking organization. Founded in two global surveys of 2,500 employees,

and more than 50 case studies on companies including Deloitte, IBM, and Cisco, the text

provides evidence of the shifts in process, value, and product affecting these

organizations now and in the immediate future (Meister & Willyerd, 2010).

Appropriateness of Studying Generation(s).

Meister & Willyerd (2010) contend that “The organizations that create a

competitive advantage in the 2020 workplace will do so by instituting innovative human

resource practices – by first defining an authentic core set of organizational values and

then augmenting these by leveraging the latest tools of the social Web to reimagine

learning and development, talent management, and leadership practices” (p. 4). This

done, as the authors describe the working environment we currently experience, which

consists of four generations in the workplace simultaneously, and sharing differing sets of

values and beliefs.

The research of Meister & Willyerd (2010) discovered:

What happens in the workplace when these credentials-driven Millenials

(born 1977 to 1997 to include Gen-X) are forced to work side by side with

older coworkers, who may at times view them as out of touch with reality?

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To successfully answer this question and the others raised by having an

age-diverse workforce coexisting in the workplace, it’s important to

develop an understanding of each generation as well as the challenges the

different generations bring to the workplace in terms of communication

styles, career aspirations, and knowledge transfer. Understanding each

generation is critical because employers who adapt the fastest to a

multigenerational workforce will be able to attract the highest-quality

employees when the war for talent is in full swing. (p. 43)

Generational studies remain critical to the study of organizations as those

organizations continue to employ generations whose norms, values, and beliefs shift over

time. The literature abounds with studies of succession planning, career paths, and

extrinsic career success in the Baby Boomer generation. Research is already beginning to

amass concerning Generation Y and those born to the new millennium. Yet, there are

still ample opportunities to contribute to the literature, the study of self-regard and career

paths among Generation X, as both a generation underserved in the literature, and those

destined by time to be our next corporate leaders. This is a generation that seeks self-

reliance, independence, and balance in their lives… often referred to as “latchkey kids” in

youth due to their early self-sufficiency. They are known for thinking like entrepreneurs,

and thriving as independent thinkers (Meister & Willyerd, 2010). To study their habits in

a longitudinal look at the relationship between self-esteem and extrinsic career success is

to better understand and prepare for tomorrow’s corporate leadership.

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Intergenerational Research.

The face of today’s modern workforce is more diverse than at any time in recent

history. Multiple generations are now working side-by-side in organizations requiring

today’s human capital leaders to reexamine how to respond to each generation’s specific

needs in order to create a workforce that is engaged (Blake, 2009). Research pertaining

to the Baby Boomer generation specifically abounds in the scholarly literature and, while

the literature on Gen-X is only now beginning to amass, what exists on intergenerational

research is what is currently under review. Although research pertaining to Gen-X

specifically continues to build, it will be intergenerational research, which provides a

current point of transition to further our understanding of this theory at-work. The

research, which exists on multiple generations in a single study, covers broad areas of

inquiry. These areas include differences among the generations, values held by these

differing generations, and motivation/commitment strategies of the multiple generations

as well.

Intergenerational differences in the workplace. The U. S. Dept. of Labor states that

those 65 and older will grow from 12.4% of the population in 2000 to 20.7% in 2050. It

also states that one of the reasons that boomers will retain positions from which they

would have retired or work under new compromising arrangements is that they are

needed (Lindborg, 2008). It is no surprise that the Baby Boomer generation will remain a

long-term fixture in the American workforce for sometime. What is also apparent are the

differences amassing between this, and its successor generation, Generation X. In a study

of The Correlation of Retention, Masi (2010) studied a population “made up of

participants eighteen or older, with Internet or email access, and was categorized by

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generational age groups” (p. 2). This study on the impact of ‘manager’s behavior on

retention among high potential employees from different generations’ studied a

representative sample of 1,000 qualified participants of differing age categories to see

just how perception dictates retention. Masi (2010) found that “the results described a

medium strength of correlation, r = 0.379, between the decision to leave and the distance

in perceptions between employee and manager” (p. 105). Similarly, as remarked by Pitzl

(2010), “For meaningful and harmonious transition to occur there has to be a more

conscious effort to better understand one another” (p. 28). These differences plague not

only levels of understanding and therefore communication between generations, but they

can affect retention as well.

Dries, Pepermans, and De Kerpel (2008) take this a step further to ask whether

‘satisfied is the new successful’. To determine an evidenced response, the authors

studied a total of 750 people completing a vignette task, thereby rating the success of 32

fictitious people (Dries, et al., 2008, p. 907). To complete this research, a synopsis of the

four generations studied was completed. These generations included the ‘Silent

Generation’, ‘Baby Boomers’, ‘Generation-X’, and ‘Generation-Y’, each holding their

own general and work-related values respectively. Whereas the general values of the

Silent Generation included conformism, the Baby Boomers were summarized to exhibit a

more idealistic tendency. Once Generation-X was reached, equal portions of skepticism

and individualism were listed. The findings from the vignette tasks administered by

Dries, et al., (2008) revealed that “If our design accurately presented the reality of career

evaluation, then, this would mean that the shared social understanding agreed upon by all

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generations tends to validate the internal evaluations individuals make about their own

careers, no matter what their objective characteristics” (p. 923).

Hiring and retaining employees is one of the biggest challenges we face in

organizations today. Add to that what we now recognize as four generations of

employees in today's workforce, and the challenge potentially becomes a recipe for

disaster (Clare, 2009). The author continued with a classification of generations not

unlike the aforementioned, yet specifically highlighting Traditionalists, Boomers, Xers,

and Millenials as the populations of inquiry. Through means of understanding cultural

differences and embracing those differences, Clare (2009) later concludes, “If you are

able to harness the strengths of all the generations and different personality types, the

results can be impressive” (p. 43).

To give these conclusions more empirical foundations, a study titled Generational

Differences in Work Values: Leisure and Extrinsic Values Increasing, Social and

Intrinsic Values Decreasing, “examines the work values of a nationally representative

sample of U.S. high school seniors in 1976, 1991, and 2006 (N = 16,507) representing

Baby Boomers, Generation X (GenX), and Generation Me (GenMe, also known as

GenY, or Millennials)” (p. 1117). Using archival/longitudinal data from the ‘Monitoring

the Future’ project, using a multistage random sampling procedure, students were

surveyed on work centrality and job stability. Results included the conclusion that the

largest change in work values is the increase in the value placed on leisure, which mirrors

what has often been described as GenX and GenMe members’ desire for work–life

balance. These data provide the first quantitative evidence of a generational shift in

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leisure as a salient work value for GenMe relative to GenX and Boomers and for GenX

relative to Boomers (Twenge, Campbell, Hoffman, & Lance, 2010).

Values in intergenerational research. Now, unlike in the 1960s, the conflicts may be

more myth than reality. A growing body of independent research and expert opinion

shows that concerns about a generation gap have been overstated and, surprisingly, the

theory behind it has some gaps in logic that raise serious questions about its value

(Giancola, 2006). The possibility of uncovering such gaps gives rise to the value of

reviewing the literature on held values among intergenerational research. This is not to

suppose emphasis to either conflicting or supporting values, yet is instead to understand

how values among these generations may or may not play a role in understanding more

of the transition from studying Baby Boomer career paths to studying those of Generation

X. Leslie Crickenberger of Walden University studied the ‘Effects of Generations and

Occupations on Job Satisfaction’ using archival NLSY data. This quantitative study

employed a 2X4 factorial design in order to determine any significance between

variables. Insofar as those variables measured included demographics, job satisfaction,

and occupation, the findings from the roughly 1,700 respondent analyses showed that

generation did have a significant (albeit small) affect on job satisfaction. Crickenberger

(2010) concluded that “While the interaction effect between generation and occupation

on job satisfaction was not significant, it is important to note that Generation X teachers

and administrative workers and Generation X production and operating workers were

significantly more satisfied in their jobs than their Baby Boomer counterparts” (p. 80). In

order to understand how integration might be possible, McGuire, By, & Hutchings (2007)

‘present a model and proposes HR solutions towards achieving co-operative generational

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interaction’. The study adapted Park's Theory of Race Relations in order to explain the

distinctiveness of generational work groups and the challenges and opportunities that

these groups present when interacting in organizations. Rashford and Coghlan's cycle of

organizational change, based on the Kübler-Ross grief cycle, was then mapped onto

Park's race relations cycle in order to link generational interaction to emotional reactions

to change over time (McGuire et al., 2007). The findings from this research fell in line

with a conclusion by Glass (2007), who said “The existence of a multigenerational work

force affects two areas of human resources policy and employee development efforts:

retention and motivation” (p. 1). Bolton (2010) also of Walden University, published

research titled Career Motivation Theory: Generational Differences and Their Impact on

Organizations. This dissertation went beyond the confines of simply stating that

something must be done to bridge the differences in value among generations, and went

beyond suggesting a model be forged to do so as well.

Bolton (2010) declared, “The purpose of this study was to fill the gap between

organizational talent management strategies and employee work needs” (p. 1). With a

focus on job security and satisfaction as delineated by Maslow’s Hierarchy of Needs, the

author performed a quantitative/descriptive study of just over 2,000 participants’ data on

the subject. As is commonplace for studies in this realm, the existence of four

simultaneous generations at work was again mentioned. Human resource professionals

and business managers have been bombarded with warnings by popular magazines and

newspapers that more demographic changes are soon to come (Bolton, 2010). While

Maslow’s hierarchy was the theoretical framework chosen, the research questions were

(a) Are there differences in cohort membership, operationally defined as belonging to a

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predetermined age category, on reported career motivation and career decisions?; (b) Is

there a link between career motivation, career decisions and generational cohort

membership based on participant scores on the PSTS?. The PSTS, representative of the

Pew Social Trends Survey, were used to gather data on career motivations and career

decisions. Bolton’s (2010) findings “suggested that Generation Y reported better career

decisions than that of all other generational cohorts, which is inconsistent with other

findings stating that they improve with age and experience” (p. 62). So, while the

approaches to work may vary across generations, continued values around career

decisions only grow strengthened across generational lines.

Since the 1960s, when the term ‘generation gap’ was first coined to describe the

differences between the WWII population (the Silent Generation) and its offspring (Baby

Boomers), generations have been learning how to co-exist (Simons, 2010, p. 29). To this

end, Riescher (2009) of Capella University studied Management Across Time: A Study of

Generational Workforce Groups (Baby Boomer and Generation X) and Leadership. To

learn more of the preferred leadership style, work values, and work attitudes to name a

few of the value of these generations, the author surveyed 942 participants across nine

companies. Drawing on ‘crossover effect’ as well as many suitable theories on studying

generations, Riescher (2009) found “The highest ranked characteristics were honest and

receptive to people and ideas among all age groups.” (p. 82). While career decisions

have ‘improved’ over time, abilities to satisfy Maslow’s lower order levels also continue,

values around trust and being receptive to others persist consistently across generations.

Thus, although Boomers tended to think of themselves as a special generation, different

from those individuals that had come before them, Generation X is typically team-

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oriented, banding together to socialize rather than pairing off (Simons, 2010). The

assumptions made regarding four generations employed in the same organization, sharing

work processes and competing for resources sounds problematic to be sure. Yet

consistencies in values and a penchant for Gen-X to employ a collective style of working

conducive to embracing wisdom should prove beneficial in environments seeking to

channel intergenerational commitment.

Channeling intergenerational commitment. Given the impact of organizational

commitment on critical factors such as turnover, absenteeism, and job satisfaction, it is

important for employers to understand the link between generation and organizational

commitment (Love, 2005). In support of this supposition, Love (2005) “examines

whether there is an actual difference between Generation-X and the Baby Boom

Generation on levels of organizational commitment” (p. 2). While the author cites

organizational commitment to be a common topic of study, she equally concedes to the

importance of its research for researchers and organizations alike. Gender, life cycle

stage, industry sector, job type, tenure and organization of employment have been

presented as covariates in this relationship among 40 private sector organizations, 22

public sector organizations, and 38 not-for-profit organizations surveyed for a total of

over 31,000 of 120,000 surveys returned completed (Love, 2005, p. 128).

Upon examination of the data, Love (2005) found “A number of different

analyses were done to answer this question including ANOVA, ANVOCA, and

regression. In none of these cases did we observe a significant association between

generation and organizational commitment” (p. 183). This runs in stark contrast to

Buetell & Wittig-Berman (2008), who report “Managers and human resource

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professionals need to consider generational differences in work-family program design

and monitor patterns of program usage for each group. Generation X members are

particularly concerned about work/life balance” (p. 1). This latter conclusion further

supported by Klun (2008) who used three case studies on Accenture to show “Members

of Generations X and Y are even more insistent than baby boomers are about balancing

their professional and personal lives—a potential retention issue exacerbated by the

shrinking pool of skilled talent” (p. 1).

Ryan (2009) published Predicting the Relationship Between Employee Perception

of Environmental and Outcome Factors and Job Satisfaction for Baby Boomer and

Generation X Employees in a Healthcare Organization, which looked to perform “a

factor analysis of the raw data from an employee survey at a large nonprofit healthcare

organization to determine whether selected variables that measure employee perception

of work environment and outcome factors in the organization are influenced by

generational cohort” (p. 2). Speaking to the intersection of employing four generations

simultaneously in business yet again, this study includes variables regarding the survey

instrument developed by Chicago-based HR consulting firm, HR Solutions.

Ryan (2009) mentions that the model HR Solutions uses divided the survey data

into the following specific dimensions:

1. Overall job satisfaction/pay satisfaction

2. Benefit satisfaction

3. Supervisory consideration

4. Communication

5. Human resources/personnel/policies

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6. Concern for employees

7. Training and development

8. Strategy and mission

9. Corporate compliance

10. Performance and cooperation

11. New employees

12. Physical working conditions

13. Concern for patient care

14. Technology utilization

15. Supplemental items

Upon review of the data, viewed through the lens of each of the thematic elements

above, Ryan (2009) found “that employee perception of satisfaction with job

opportunities does not vary by generational cohort but rather by the overall work

environment” (p. 62). As further evidence to the consistencies present throughout the

generations, research exploiting the theory of Self-Esteem and Extrinsic Career Success

among the Generation X workforce becomes that much more feasible as consistent

results regarding paths may be expected when controlling for self-esteem.

The question then becomes how to channel organizational commitment, if the

assumption can now be made that organizational commitment is a consistent quality

throughout generations studied. Chan (2005) sought to understand more of this linkage

by studying the Relationship Between Generation-Responsive Leadership Behaviors and

Job Satisfaction of Generations X and Y Professionals. For this research, Chan has

drawn on a wealth of theories to further explain this phenomenon. The theories range

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from Trait Theories to Contingency Theories to Transactional v. Transformational

Leadership and Motivation v. Job Satisfaction Theories. Employing the Multifactor

Leadership Questionnaire 5X (MLQ 5X) and the Job Descriptive Index (JDI)/Job In

General (JIG), 60 Gen-X and 60 Gen-Y professionals participated in the survey process.

While both relationships to job satisfaction and correlations between leadership behaviors

defined the research questions, Chan’s (2005) findings conclude that “Based on the

comparison of the mean scores, it can be inferred that (a) both generational cohorts had

the lowest job satisfaction level regarding their work on present job; (b) their satisfaction

with supervision was slightly higher than how they felt about their work; and (c) overall,

they placed a higher level of satisfaction with job in general” (p. 151).

As reported by Shaul (2007), “this quantitative research study [was purposed

with] the exploration of attitude within and across each generation toward money, which

is one of the least studied and oldest incentives” (p. 6). As the implication was the

retaining of talent, it is thought that the similarities in like-minded values between

generations may begin to separate when money is the reward at stake. In order to learn

more, Shaul surveyed 80 employed participants using the Money Attitude Scale or MAS.

The results indicated significant differences across generations, where Boomers do not

value money as a sign of status and prestige as highly as Gen-X. But Boomers do value

saving money and show significant differences in the retention of money (Shaul, 2007).

Shaul (2007) ultimately concluded, “Perhaps performance needs to be linked more

strongly to benefits as these employees are oftentimes underperforming and just biding

their time until they can leave” (p. 85).

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Incentivizing Intergenerational Commitment.

It may come as no surprise that money transcends otherwise commonplace values.

Only variations in approaches to work can create or equalize the motivation to stay

committed to one’s current organization. Hollman (2008) worked to “determine the

relationship between generational membership, defined as Baby Boomer, Generation X,

and Millennial and affective, continuance, and normative organizational commitment in

one Fortune 100 firm” (p. 4). In order to better understand what each means, the Three-

Component Model Employee Commitment Survey describes affective, continuance, and

normative commitment as components to overall organizational commitment. Affective

commitment can be described as passion or association with the firm. Continuance is the

cost-benefit of staying over choosing to leave an organization. Normative describes duty,

bound by circumstances and creating an obligation. A random sample of 500 survey

responses was collected against measures including statements regarding the three types

of commitment. Findings, as described by Hollman (2008), include “The exploratory

statistical analysis indicates there is no relationship between affective and normative

organizational commitment and generational membership indicating the absence of a

connection between these variables of the study. However, there is a negative relationship

between generational membership and continuance organizational commitment” (p. 80).

What do these implications of organizational commitment type mean when pitting

them against data regarding perceptions of money, as well as perceptions of personal

value? Baby Boomers have been firmly in charge for the past few decades and, as a rule,

they have been willing to operate by a well-understood set of corporate practices and

policies related to compensation, hierarchy, and expectations for the way work ‘works’

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(Erickson, 2010). Erickson (2010) continues saying “Generation Xers, born from 1961

through 1981, have different ideas. They are more apt to reject status-quo definitions of

success and seek their own paths” (p. 63). The author describes a study in which

hundreds of Gen-X interviews have taken place, and the upcoming generation of

leadership ‘views work in a way that current corporate executives rarely understand’.

Intergenerational research, leading to further understanding of how Gen-X differs from

its Baby Boomer counterpart, is helping to shed light on pathways for optimizing both

career path and self-regard. With the success of tomorrow’s organizations in mind,

Erickson describes ‘five context-creating leadership activities well suited for today,

which include (a) increase collaborative capacity; (b) ask compelling questions; (c)

embrace complexity and welcome disruptive information; (d) shape corporate identity;

and (e) appreciate diversity.

Generation X Research

Regardless of whether boomers quit working or stay in the workplace, there is one

prediction that can be made with some certainty: employee turnover will become the key

challenge for managers (Ludwick, 2007). Research regarding the generations is not in

short supply, nor are artifacts alluding to the pending crises regarding generational shifts

in the workplace. What is underserved is the research regarding Generation X (Gen-X)

specifically, and its patterns concerning talent, commitment, and culture. In a study of

business leaders’ core values among the Gen-X population, Kwak (2009) “examined the

alignment of core values in a group of successful Gen X business leaders. Specifically,

this study analyzed core values that tap into a particular generational cohort that

witnessed the impact of vast technological advancements and globalization” (p. 11).

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Beginning with an in-depth review of the literature, core thematic elements were

identified to then translate into a holistic framework for inquiry in order to gather more

in-depth knowledge of levels of congruence between the perceptions/practices of

identified Gen-X leaders and the core values of their inherent organizations. Drawing on

the research frameworks of Collins (2001) and Porras (2007), the researcher created a

survey instrument which assessed both the aforementioned perceptions and practices,

upon which content analysis was performed, to derive 120 meaningful quotations from

the 30 transcripts (Kwak, 2009). The five conclusions derived according to Gen-X

include, Gen-X leaders recognized that nurturing relationships maintained their

organization’s success, that integrity is perceived as a vital value, and that the presence

and alignment of a value system is crucial to success (Kwak, 2009).

Generation X as meritocratic individualists. While by population size, both the

predecessor Baby Boomer population, and the following Millennial population far

outweigh the Generation X grouping. However, this generation is made up of individuals

who are coming into today’s leadership positions, who are poised to replace the Baby

Boomers among executive positions, and who will continue to be among the myriad

successful serial entrepreneurs shaping today’s American economy. What is missing in

the literature is further work on how the values of this generation, the habits of this

generation, and the beliefs of this generation will come to mold the experiences had in the

business environment in coming years.

The theory of Self-Esteem and Extrinsic Career Success proved to be an

invaluable predictor of career path for the Baby Boomers, which constituted the initial

study’s sample population. Yet we could gain from more literature on the Generation X

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population and its impacts in the present and near-term future. Further research would

add to how much we have already come to know of this generation and its beliefs

surrounding career path, success, and self-regard. In a study titled Constructing Career

Scripts: How Members of Generation X Make Sense of their Careers in Business, the

author sought to learn more of how individuals make sense of their careers within

specific cultural contexts and time periods by comparing career scripts mapped to their

own and previous generations (Belden, 2009). In doing so, Belden was researching, not

only how career scripts developed among this population, but was able to understand

more of what workers in this Generation attribute success to as well. Belden concluded

that Generation-X exhibited a unique form of ‘meritocratic individualism’. Boyd (2009)

supports this conclusion with a study, which found this generation to “give short shrift to

some seasoned tenets of corporate conduct, including organizational mission,

organizational politics, and organizational loyalty” (p. 465). In both instances,

commitment, reward, and organizational citizenry are dictated by expectations of

commensurate recognition and/or reward for what is felt to be achievement/merit-based

accomplishments. This is not to say that tenure falls on deaf ears, but it is to say that the

notion that they are expendable entities bolsters the penchant to roam. In an era when

they are apt to be downsized without warning or mercy, they are acutely conscious of

their LIFO status (Boyd, 2009, p. 468).

It was this perception of (false) dichotomy between seeing Gen-X as a group with

low levels of organizational commitment, or as seeing this generation’s long-term

prospects as bleak in an otherwise dismal economy that gave rise to a special report

published by the Journal of Accountancy, which examined “this group's career goals,

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personal values, work-related expectations and work satisfaction, to help employers

attract, retain and advance this next generation” (p. 38). In fact, fully 85% reported that

they really cared about the fate of the organizations for which they worked, and 83% said

that they were willing to put in far more effort than is normally expected in order to help

their organizations succeed (Catalyst, 2005, p. 38). As with the Belden and Boyd studies,

the reality paints a picture more accurately described as a strong sense of realism around

the need to go where opportunities are present, rather than from the basis of a need to

mitigate organizational commitment to the benefit of self-service alone. As was most

accurately described by Goldseker (2009), “Although Gen X’ers are stereotypically

considered ‘slackers,’ most members of their generation would tell you they are actively

seeking meaningful experiences and want to learn by doing. They "work to live," not

"live to work," like generations before them” (p. 118). As stereotypes abound for this

generation, it becomes prudent to then develop a deeper understanding of how better to

define this generation, and to locate germane research on what it means to create a more

meaningful corporate existence, while possibly predicating more favorable career paths

as a result.

One such study, which attempts to make this distinction, is Creating a Gen-X

Friendly Workplace to Retain Key Talent. DeMarco (2008) describes, “The year 2008

and upward, accordingly, will be characterized by the retirement of approximately 75

million baby boomers professionals. To address the [corporate recruitment and retention

difficulty] outcry, companies are advised to focus on collaborative relationships; offer

variety; work in teams; and build a strong corporate communication process” (p. 1). In a

study of voluntary turnover among Gen-X IT professionals, a researcher from the

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University of Phoenix sought to understand why information technology professionals

have been leaving their organizations after three to five years, resulting in increased costs

due to rehiring, retraining, and loss of skill sets and knowledge (Burnes, 2006).

Employing a concurrent mixed method approach, Burnes used a nonexperimental

descriptive design combining an electronic survey and qualitative interview to gather data

on the voluntary turnover as social phenomena. While focusing on the ‘unfolding model

of voluntary employee turnover’, Burnes (2006) found that “employees often feel that the

organization will not retain them beyond 3 to 5 years” (p. 116). In response to this

presumed environment, this study revealed five factors that motivate an information

technology employee toward decision ‘path level 2 or 3’ of the unfolding model of

voluntary employee turnover in the areas of loyalty, communications styles, lack of

keeping up with technology, compensation, and leadership (Burnes, 2006).

Further scholarship into Generation X IT professionals was accomplished by

adding the job satisfaction variable to the research equation. Fismer (2005), also of

University of Phoenix, formulated a phenomenological description of the essential

structure of Information technology (IT) consulting organizations’ internal work

environments, specifically job satisfaction and leadership styles of Generation X leaders

(p. 4). Using interviews as descriptors of experience, and performing a phenomenology

of 20 IT/Gen-X leaders from 66 organizations drafted in-depth profiles. The conclusions

drawn from the content analysis of these 20 profiles, including amassed interview data,

shed light on the emergence of new patterns among professionals when taking this

specified generation into context. Fismer (2005) summarizes by concluding “interviewed

Generation X leaders identified ‘seeking advice from mentors’, ‘choosing a career

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path/having worked for different companies’, and ‘linking education to career’ among

their core behavioral priorities” (p. 144). In addition, their primary values, specifically:

trust, loyalty, teamwork, and respect reflected humanistic thinking and focused on

inspiring their followers’ talents (Fismer, 2005, 144). To further reflect on this list of

pervasive values, Spear (2009) studied the development of Gen-X workers for positions

of executive leadership in the federal government. In this study, its author describes an

‘impending exodus of seasoned leaders’ as more than 50% of the Senior Executive

Service (SES) members as of October 2000 will leave the Federal government by

October 2007 (Spear, 2009). To understand more of what Gen-X leaders need/want from

a development program, questions on training method preferences, subject matter

preferences, and body of knowledge were explored. In a case study, supported by

numerous focus groups, Spear (2009) found that “Understanding future leaders will need

to lead differently, Generation Xers, as evidenced by the participants in the study, will

likely speak candidly about their leadership development interests and pursue

opportunities that prepare them for the leadership challenges of tomorrow” (p. 163).

These findings further support the supposition above that Gen-X workers value

humanistic thinking as well as teamwork when in the face of opportunities for further

collaboration. Anding (2009) also described this scenario as “aspects of an inward

journey resulting in a recommitment to work that allowed for an integration of the

participant's needs for achievement, challenge, and continued learning with more

meaning and authenticity (p. 2).

Preparing the workplace for Generation X. Rousseau (2007), in a preface to his

research on retention strategies and Generation X, comments, “By the time I entered the

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workforce my perspective was much different than that of my baby-boomer parents. I

wanted mutuality. I wanted respect for my contributions. I wanted a fair wage.“ (p. 1).

The workplace of today is in no way a mirror image of organizations past, yet this is also

not to say that today’s organization is fully prepared to receive the Gen-X workforce

either. To that end, Rousseau (2007) cites that “Seventy percent of [Gen-]X’ers stated

they would quit if they thought they could find increased intellectual stimulation

elsewhere” (p. 43). As a result of an exhaustive literature review on the topic of

turnover/retention in today’s organizations, the author also concludes ”Generation X,

while more dynamic than two retention practices, is fundamentally defined by the values

that are associated with the two retention practices described in depth in this paper.

Generation X’ers want work-life balance and meaning” (p. 53).

In recent years, Herzberg’s theory on motivation and McGregor’s theories X and

Y were used to examine attitudes and motivational factors that stimulate and increase

employee satisfaction leading to increased employee recruitment and retention (Lee,

2007). Lee (2007) utilized a mixed method approach to couple a phenomenology with a

questionnaire, which surveyed members of the Society of Louisiana Certified Public

Accountants. These 16 participants allowed Lee (2007) to come to the conclusion that,

not only had recruitment and retention become a cause for concern among accounting

professionals, but also that “Organizations will need to be willing to change current

methods of recruitment and motivation techniques and consider new ways of attracting

and motivating accountants that will entice them to remain with the organization” (p.

133). The author lists ‘organizational structure’ as one viable option for change since

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Gen-X workers were found to be more apprehensive to hierarchy as they found it more a

hindrance than a benefit.

To continue this avenue of research, the Financial Planning Association

published, Serving the Next Generation. The article, published Q1 2009, was “based on a

recent Financial Planning Association survey of 3,022 consumers with over $50,000 in

income or investable assets… focuses on the current behaviors, planning needs, and

benefits of planning to Generation X” (FPA, 2009, p. 1). As a primary takeaway from

this survey, while Generation X's areas of stress are more short term, their goals are long

term; they need a plan to help them become behaviorally future-focused as opposed to

simply thinking long term (FPA, 2009). This financial reality, as implication for an

employment one, is further defended by the supposition that we’ll work for much smaller

organizations that outsource everything but the business’s core area of expertise, and

more than half of us will eventually become contingent workers, employed part time or

as freelancers or consultants (Levit, 2009). Thus, the conclusion drawn is not one of a

pattern of behavior where Generation X is simply a grouping dedicated to freely floating

between intellectually stimulating positions, and instead speaks to a grouping of society

that faces the realities of the current economic times. They accept the harsh truth and

cynicism that invokes a survival instinct, which mitigates any current inclinations to

commit to an organization.

To offer more on the implications of preparing the workplace for Generation X,

Mitchell, McLean, & Turner (2005) provide the following description of those who

comprise this group:

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They have trouble making decisions. They would rather hike the

Himalayas than climb a corporate ladder. They have few heroes, no

anthems, no style to call their own. They crave entertainment, but their

attention span is as short as one zap on the TV dial. They hate yuppies,

hippies, and druggies. They postpone marriage because they dread

divorce. They sneer at Range Rovers, Rolexes, and red suspenders.

Things they hold dear are family life, local activism, national parks, penny

loafers and mountain bikes. They possess only a hazy sense of their own

identity but a monumental preoccupation with all the problems the

preceding generation will leave for them to fix. (p. 26)

Adding to the Generational Knowledge Base.

Despite their best efforts, companies continue to squander what may be their

greatest asset in today’s knowledge economy: the wealth of expertise, ideas, and latent

insights that lie scattered across or deeply embedded in their organizations (Hansen &

Oetinger, 2001). As also noted in The Leadership Pipeline, the successions plans, as well

as hierarchical passage orientations of today, have great potential to contribute to the

success of tomorrow’s organizations as they prepare today’s generations for positions of

leadership. From studies on how organizations are managing the transition between

generations, to research on the values and personalities of these diverse groupings, more

can be understood about how the transition to Generation X leadership will affect the

success and sustainability of today’s companies. By furthering the research on

Generation X self-esteem levels and career path patterns, more can be known of how to

harness the knowledge of those stepping out of positions of leadership and how best to

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prepare for the coming wake of workers centered on independence and meritocracy

among the Gen-X population. As noted by Hansen & Oetinger (2001), “using existing

knowledge to improve performance or combining strands of knowledge to create

something altogether new can help companies respond to a surprising array of challenges,

from fending off smaller, nimbler rivals to integrating businesses shoved together in a

merger” (p. 1).

Conclusions and Method Appropriateness

The implications of the possible finding of a direct relationship between these

factors affect not only the individual as a member of the workforce. They impact the

organizations he or she works for as well. This impact, it is believed, is shown in the

desire to be employed in a position befitting the individual’s self-esteem and, therefore,

perceived worth, resulting in maximum commitment to the current job and organization

only when the position is in alignment with the employee’s expectations of worth. This

essentially gives rise to the need to better understand how self-esteem impacts the

components of extrinsic career success. Until these variables are in alignment, an

employee may exhibit reduced commitment to his or her current position as described

above.

According to Kammeyer-Mueller, Judge, & Piccolo (2007), “many of the

important questions in the literature on self-esteem, social status, and identity have

reciprocal relationships at their core and therefore require repeated measures of self-

image and careers over time” (p. 205). In the same article, Self-Esteem and Extrinsic

Career Success: Test of a Dynamic Model, the authors set out to establish these repeated

measures over time, while determining the efficacy of viewing relationships between

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self-esteem and elements of extrinsic career success. The authors continue saying “An

important note for all of these relationships is that we are focusing our attention on

changes in self-esteem, education, occupational prestige, and income rather than simply

noting zero-order relationships” (Kammeyer-Mueller et al., 2007, p.208).

A Review of Method Appropriateness.

Addressing the deficiencies in the literature concerning self-esteem and extrinsic

career success for the Gen-X workforce requires an analysis of fit for best analyzing the

potential relationship between self-esteem and extrinsic career success, and an analysis of

the intellectual merit or worthiness of such research. To do so, options concerning

research method, strategy of inquiry, and method of data collection are reviewed.

Identifying a research method. Quantitative research is a means for testing objective

theories by examining the relationship among variables; these variables, in turn, can be

measured, typically on instruments, so that numbered data can be analyzed using

statistical procedures (Creswell, 2009). This method is chosen for multiple reasons,

primary of which is the need to select a method, which accommodates the analysis of a

potential relationship as expressed between data on self-esteem and data on extrinsic

career success. Where quantitative analysis is a deductive process using largely

numerical data to express relationships, the qualitative method was not chosen due to its

inductive nature.

As qualitative research concerns the process of making sense through words,

conclusions based on thematic pattern, and induction through participative inquiry, it was

found inappropriate for the present study as more numeric data, longitudinal data is

available. Mixed method research as a final alternative, is an approach to inquiry that

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combines both qualitative and quantitative forms, and involves philosophical

assumptions, the use of qualitative and quantitative approaches, and the mixing of both

approaches in a study (Creswell, 2009). As the aforementioned review of the literature

has determined that the appropriate variables include self-esteem and extrinsic career

success, and as longitudinal data on these variables is available for the target population,

no further qualitative research is invoked.

Selecting a strategy of inquiry. Surveys have broad appeal, particularly in democratic

cultures, because they are perceived as a reflection of the attitudes, preferences, and

opinions of the very people from whom the society’s policymakers derive their mandates

(Rea & Parker, 2005). Upon selection of a quantitative research method, opportunities

for strategy of inquiry commonly include experimentation and survey research. Survey

research provides a quantitative or numeric description of trends, attitudes, or opinions of

a population by studying a sample of that population (Creswell, 2009). As this study

aims to gather representative data from the Gen-X workforce, to then analyze the

potential relationship between self-esteem and extrinsic career success, the strategy of

inquiry must be one suitable for gathering data on such a large population. Where

experiments are suitable in more localized environments, survey data will allow for a

greater capture of representative data, as access to a larger number of respondents is

possible using this strategy of inquiry. Further, data used will be from the Bureau of

Labor Statistics' National Longitudinal Survey of Youth (NLSY) and will therefore be

from a proven, representative sample of the US Generation X workforce.

Reviewing methods of data collection. It is useful to consider the full range of

possibilities of data collection and to organize these methods, for example, by their

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degree of predetermined nature, their use of closed-ended versus open-ended questioning,

and their focus on numeric versus nonnumeric data analysis (Creswell, 2009). While

qualitative methods may employ emerging methods of collection, open-ended interview

and observation data, and/or content analysis using image or text-based artifacts, the

NLSY uses closed-ended, numeric data.

To provide a statement of reliability for good measure, additional instances of

instrument use and reliability assessment were reviewed. One such study from

Crickenberger (2010) states the NLSY79 and therefore NLSY79ch undergo “several

assessments to ensure reliability and validity of the questionnaire... the questionnaire is

reviewed biannually by NLS Technical Review Committee, which is comprised of

multidisciplinary experts in social sciences” (p. 50).

This allows for the numeric representation of demographic, personality,

employment, and income data of the representative sample, and for a period of eight

years. This survey, which incorporates the Rosenberg 10-item self-esteem scale, as well

as questions on position, income, job satisfaction, and formal education, provides the data

necessary to examine a potential relationship between the variables inclusive of the

theory of self-esteem and extrinsic career success.

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CHAPTER THREE: METHODOLOGY

Much literature exists regarding self-esteem, career success, and intergenerational

research, each in isolation and unrelated to one another. However, what remains to be

explored are measures of self-esteem and extrinsic career success over time, relative to

the workforce of Generation X. A review of the literature has revealed value differences

among current workforce generations. This review has also elucidated a potential

relationship between aspects of the varying personalities of different generations and the

stability of career paths, thus exhibiting the potential side effect of compromises to

organizational profitability.

Research Design and Instrumentation

This quantitative, longitudinal study using archival data will test the theory of

self-esteem and extrinsic career success, which relates self-esteem to occupational

prestige and income. This will be done using data collected from respondents of the

Bureau of Labor Statistics' National Longitudinal Survey of Youth - Children & Young

Adults (NLSY79ch). This survey was administered biannually from 1994 through 2008.

This final, archival dataset is now publically available online via the NLS Web

Investigator tool, and is accessible after a free user registration process.

Experimentation, while targeted, does not allow for the longitudinal capture of

self-esteem, job satisfaction, or extrinsic career success information as a survey would

certainly allow. Therefore, research questions under study include:


respondents?

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From Research Questions to Hypotheses.

In order to answer these research questions, this study consists of four hypotheses.

Null hypothesis 1 (H0). There is no significant relationship between self-esteem

and occupational prestige when regarding NLSY79 Young Adult respondents.


and income when regarding NLSY79 Young Adult respondents.

Null hypothesis 3 (H0). There is no significant relationship between self-esteem,

job satisfaction, and occupational prestige when regarding NLSY79 Young Adult

respondents.


job satisfaction, and income when regarding NLSY79 Young Adult respondents.

A summary of the deconstruction from research questions, to statistical tests, to

hypotheses, is provided in Figure 3.

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Figure 3. Testing deconstruction. The study’s tests which will prove, or fail to

disprove, the hypotheses, which answer the research questions.

Measures Used in Responding to the Research Questions.

Variables being studied in research may be classified as objects or as properties,

yet researchers do not literally measure objects or properties, therefore, indicants are

measured instead (Cooper & Schindler, 2003). As the theory of self-esteem and extrinsic

career success draws upon the relationship between self-esteem and both income and

occupational prestige, indicants must be identified to represent these measures.

Self-esteem as an independent variable. NLSY79ch participants answered a series of

items from 4-point, Likert-type, Rosenberg 10-item self-esteem scale (Bureau of Labor

Statistics, 2009). Instructions to each participant included ‘after each statement, please

tell me whether you strongly disagree, disagree, agree, or strongly agree’ (Bureau of

Labor Statistics, 2009). While additional considerations regarding internal consistency

•Test 1: A simple regression of self-esteem on occupational prestige. •Hypothesis 1 (H0): Relationship between self-esteem and occupational prestige is

insignificant. •Test 2: A simple regression of self-esteem on income. •Hypothesis 2 (H0): Relationship between self-esteem and income is insignificant.

Research Question 1: Is there a relationship between self-esteem and extrinsic career success?

•Test 3: A multiple regression of self-esteem and job satisfaction on occupational prestige. •Hypothesis 3 (H0): Relationship between self-esteem, job satisfaction, and

occupational prestige is insignificant. •Test 4: A multiple regression of self-esteem and job satisfaction on income. •Hypothesis 4 (H0): Relationship between self-esteem, job satisfaction, and income

is insignificant.

Research Question 2: Is there a relationship between self-esteem, job satisfaction, and extrinsic career success?

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will be mentioned later in this chapter when regarding reliability, these data are extracted

as questions Q16-5h-a through Q16-5h-j of the survey itself.

Education as an independent variable. Respondents are branched throughout the

‘Regular Schooling’ section according to both enrollment status and highest grade

completed (Bureau of Labor Statistics, 2009). As an ordinal scale, this question asks that

respondents reply with the number of years of formal education completed. These data

are extracted as question Q4-19 of the survey.

Job satisfaction as an independent variable. Although the NLSY79ch was

administered every two years, from 1994 to 2008, a Global Job Satisfaction Item was not

included where data is available until 1998. This question asked how the respondent felt

about his/her job with their present and primary employer (Bureau of Labor Statistics,

2009). These data are extracted as question QES-89.01 of the survey.

Occupational prestige as a dependent variable. The Duncan Socioeconomic Index

(SEI) was used to measure occupational prestige. It is taken from a number of experts in

the 1950s from Census data on occupational characteristics and perceptions of prestige

(Kammeyer-Mueller et al., 2007). In order to utilize the Duncan SEI, the participant,

regarding primary job position, and then converted to an SEI score, first collected an

occupational classification code. The survey used differing question codes for this

variable throughout time since the basis of occupational classification was also evolving.

Specifically, the 1994, 1996, and 1998 survey used the 1970 Census coding frame, while

the 2000 and 2002 surveys used the 2000 Census frame, and the 2004 and forward

surveys used the latest NAICS-based codes (Bureau of Labor Statistics, 2009). These

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data are extracted as questions QES1-55I, QES-55H.01, OCC90.01, and OCC2000.01

respectively through time.

Income as a dependent variable. As a measure of income, the question pertaining to all

wages, salary, commissions, and tips is used for all years 1994 through 2008 (Bureau of

Labor Statistics, 2009). This question is constructed to also include military income as of

2000, and is extracted as question Q15-5 of the survey.

Utilization of a Proven Instrument.

The Kammeyer-Mueller et al. (2007) study explored the relationship between

self-esteem and extrinsic career success and thus provided the first evidence of such a

relationship. The instrument chosen for the study was the National Longitudinal Survey

of Youth 1979 or NLSY79, sanctioned by the Bureau of Labor Statistics and performed

by the Center for Human Resource Research at Ohio State University. The NLSY79 is a

nationally representative probability sample of 12,686 individuals who were between the

ages of 14 and 21 in 1979; each participant has been interviewed since 1979 to assess

labor force experiences, labor market attachment, and investments in education and

training (Kammeyer-Mueller et al., 2007). As described by Crickenberger (2010), “The

NLSY79 sampling criteria were designed to represent 14-21-year-olds living in the

United States. Participants were randomly selected out of a possible 75,000 households

through a two-step process. The two-step process ensured a valid and reliable random

sampling procedure” (p. 40).

While the NLSY79 was found to be valid, reliable, and representative, it was

found to be representative of the generation we now call the Baby Boomers. Recall

instead the Erickson (2010) study which identifies the Generation X population to have

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been born from 1961 through 1981. Consider then instead the NLSY79 Young Adult

(NLSY79ch). As described by the Bureau of Labor Statistics (2009) in their overview of

the NLSY79ch, “Starting in 1994, a different type of interview was initiated for the older

children of the NLSY79 female respondents. This ‘young adult’ data collection has

focused on NLSY79 children who have reached age 15 and over as of the end of the

relevant survey calendar year” (p. 4). This Young Adult questionnaire focused on the

transition to adulthood, with detailed questions on education, employment, training,

health, family experiences, attitudes, interactions with family members, substance use,

sexual activity, non-normative activities, computer use, health problems, and pro-social

behaviors (Bureau of Labor Statistics, 2009). Since the NLSY79ch was the direct result

of follow-up actions to the NLSY79, and since the approach to sampling and data

collection were similar between these instruments, and since the variables collected

included those studied for the population identified for this research, the NLSY79ch has

been selected as the proven instrument for this research.

Data Collection.

Young adults surveyed through 1998 used a CAPI questionnaire modeled on the

main NLSY79 interview along with a paper and pencil self-report booklet. Beginning in

2000, surveys were conducted primarily by telephone interviews, with questions from the

self-report booklet integrated into the computerized instrument (Bureau of Labor

Statistics, 2009). The variations of the National Longitudinal Survey of Youth (NLSY)

have been under study for an extensive period of time and they have withstood thorough

scientific review. As commented by Crickenberger (2010), “both the NLSY79 and the

NLSY97 provide extensive documentation on the background of the study, the research

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design, sampling, data collection, and procedures” (p. 50). This confidence is built not

only upon the strength of evidence supporting procedures used by the researchers at Ohio

State University, but upon in-person interviews, telephonic interviews, and self-reported

survey data as well. The final, archival dataset is now publically available online and

will be downloaded via the NLS Web Investigator tool, which is accessible after a free

user registration process.

Upon accessing the dataset, one must first select all records containing data for

the aforementioned variables. Ensuring these data are at least six years apart, the data

must then be cleaned of all records containing values indicating either ‘missing’ or

‘refused’ responses. Frequencies are then generated on whatever data remains. For those

data, exhibiting a minimum six-year span between independent and dependent variables,

the pairings that generate the highest frequencies are isolated. Once the value for n is

recorded for this simplified dataset, analysis and review ensue.

Regarding Instrument Reliability.

Reliability is concerned with estimates of the degree to which a measurement is

free of random or unstable error. Reliable instruments can be used with confidence that

transient and situational factors are not interfering (Cooper & Schindler, 2003). The

literature regards the NLSY79/NLSY79ch as containing a wealth of data that social

scientists are continuously analyzing within a number of areas of interest, while also

concluding that the survey collects extensive background information on attainment and

wages alike (Price, 2010).

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Population and Sampling

The NLSY79ch was administered with the intent of collecting representative data

from two populations, children and young adults. Upon consideration of the nature of

variables such as income and job satisfaction, focus is placed on the generation

represented by the young adult population, as described in the review of the literature as

Generation X based on date of birth.

Selecting a Sampling Strategy.

According to Cooper & Schindler (2003), “there are several compelling reasons

for sampling, including: (1) lower cost, (2) greater accuracy of results, (3) greater speed

of data collection, and (4) availability of population elements” (p. 179). Evidence was

also reviewed regarding a strategy for the sample selected, and how it is representative of

the general population the research intends to describe, while also providing predictive

power in instances where this means is appropriate. Sampling can take a great many

forms. Yet to describe the theoretical basis for sampling, certain properties when

describing a normal distribution must be taken into account. These properties include (1)

the value of the mean of sample means approaches the true population mean, also

referred to as the Central Limit Theorem; (2) the distribution of sample means will

approximate a normal curve as long as the sample size of each individual sample is

sufficiently large; (3) the standard deviation of the distribution of sample means, or

standard error, is smaller than the standard deviation of the total population (Rea &

Parker, 2005).

The identity of a population under study, the clustering or sampling design of the

population, the sampling strategy of either by probabilistic or convenience origins, and

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the stratification of those sampled must come under review when describing an overall

approach to sampling (Creswell, 2009). As documentation abounds concerning the

sampling approach to NLSY79ch archival data and its collection, it has been commonly

referred to as scientifically sound in the literature. Thus, a description of the target

population, as well as considerations for selection and reliability follow.

Selection Criteria and Population Representativeness.

The young adult data provide an excellent vehicle for examining educational

progressions and transitions into the work force. Schooling and work outcomes among

these young adults can also be compared with the trajectories their mothers took a

generation earlier (Bureau of Labor Statistics, 2009). The sample of NLSY79ch

respondents are the children of NLSY79 participants. Thus, the primary selection criteria

for the instrument was based on the condition of being a descendent of an NLSY79

participant, and further credence is paid to the selection criteria for NLSY79.

The NLSY79 was a nationally representative sample of 12,686 young men and

young women who were 14 to 22-years-of-age when they were first surveyed in 1979.

Data collected during the annual surveys of the NLSY79 chronicled these changes and

they provide researchers with a unique opportunity to study in detail the life course

experiences of a large group of young adults who can be considered representative of all

American men and women born in the late 1950s and early 1960s (Bureau of Labor

Statistics, 2009). This is not to imply that the NLSY79ch sample is therefore

representative of its generation, but it is representative of those born to the Baby Boomer

generation preceding them.

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Target Population Description.

The 1994 National Longitudinal Survey of Youth (NLSY79ch) included an hour-

long interview with the children of NLSY79 mothers who were at least 15-years-of-age

by the end of the interview period. Interviews were completed with 980 of these Young

Adults, out of an eligible sample of 1,111 (Bureau of Labor Statistics, 2009). As this was

a longitudinal study, and the hypotheses of this research look to equally assess on a

longitudinal scale, further detail of population attributes and attrition is explored.

While an initial sample population of 980 was interviewed, the following figure,

Figure 4, depicts evolving sample sizes over time as summarized by the Bureau of Labor

Statistics (2009).

Figure 4. Child sample sizes by age and race/ethnicity. The table above depicts

both those years where larger populations of young adults were surveyed, as well as the

proportion of race/ethnicity differences among the sample. These increases, due in large

part to increases in the number of those who were old enough to be both interviewed and

categorized as ‘Young Adult’, has rendered little effect on the proportion of sample

characteristics.

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Attrition was also explored since it is not feasible to expect a 100% response rate

for this or any similar population. This is an equally imperative measure. While initial

sampling strategy for the NLSY79 population remained representative of an entire

generation nationally, those interviewed as part of NLSY79ch were chosen by birth alone

and, therefore, were at greater risk of providing decreasingly representative data if this

subset were to substantially decrease in response rate. Yet, this was not the case, as

young adults did not need to be living with their mother in order to be eligible for

interview. Therefore, a significant number of ineligible children become eligible when

they enter the young adult ages as parental presence was no longer a requirement. As

provided by the Bureau of Labor Statistics (2009), the following figure, Figure 5, depicts

completion rates relative to this population.

Figure 5. Completion rates for NLSY79ch populations. This table represents the

completion rate percentages of those young adults found to be in-scope.

Data Analysis and Interpretation

As a vast amount of data has been concisely collected, prepared, stored, and is

available for download across the years 1994 through 2008, the parsimony emphasized

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through only succinct statistical analysis allows for clear analyses of these five variables

over the eight survey periods.

Descriptive Analysis Procedures

With any dataset encountered, one must find ways to allow the data to tell their

story. Ordering and graphing data sets often exposes patterns and trends, thus allowing

one to learn more about the data and the underlying situation (Harvard Business

Publishing, 2010). Offering statistics such as mean or median, standard deviation, range

and/or frequency does more than merely describe essential characteristics. Descriptive

statistics, including mean/median, standard deviation, frequency, range and sample

information, will therefore be calculated.

Population Reliability Via the Internal Consistency of Scales.

In order to determine the significance of the study, elements of both validity and

reliability come under question. Various forms of validity include content validity,

predictive or concurrent validity, and construct validity. As for reliability, it is argued

that the researcher should examine whether or not authors report measures of internal

consistency (Creswell, 2009). Measuring internal consistency is a process that has been

performed on this archival data on multiple occasions with multiple and differing results.

Ranging from 0.75 to 0.90, multiple authors have cited multiple coefficient alpha

reliability or Cronbach’s alpha estimates (Crickenberger, 2010). As described by UCLA

Academic Technology Services (2010), “Cronbach's alpha is a measure of internal

consistency, that is, how closely related a set of items are as a group... a ‘high’ value of

alpha is often used as evidence that the items measure an underlying (or latent) construct”

(p. 1).

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As described by Gliem & Gliem (2003), “Based upon the formula _ = rk/[1 + (k -

1)r] where k is the number of items considered and r is the mean of the inter-item

correlations the size of alpha is determined by both the number of items in the scale and

the mean inter-item correlations” (p. 87). The authors continue to establish scores that

are (1) >.9 are excellent; (2) >.8 are good; (3) >.7 are acceptable; (4) >.6 are

questionable; (5) >.5 are poor; and (6) <.5 are unacceptable (Gliem & Gliem, 2003).

Thus, Cronbach’s alpha will be calculated in order to determine the internal consistency

of scales when reviewing the 10-item Rosenberg Self-Esteem Scale and its implications

on internal and population reliability.

Responding to the Research Questions through Statistical Analysis.

At its essence, this research is designed to perform very few actions for the

purpose of answering equally few, pointed questions. Those questions include whether a

relationship exists between self-esteem and extrinsic career success for respondents, and

whether job satisfaction also plays a role. To evaluate, independent variables are

regressed on the dependent variables in order to establish the potential for statistically

significant relationships. Hypotheses 1 and 2 detail simple regressions of self-esteem on

the dependent variables of extrinsic career success separately. Hypotheses 3 and 4 detail

multiple regressions of self-esteem and job satisfaction on the dependent variables of

extrinsic career success separately.

Simple regressions to respond to the first research question. A simple regression,

also known as Pearson Product Moment Correlation Coefficient or Linear Correlation

Coefficient, studies the relationship between a single independent and dependent variable

over time. As described by Triola (2004), “Because the linear correlation coefficient r is

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calculated using sample data, it is a sample statistic used to measure the strength of the

linear correlation between x and y (p. 499). Results will be reported also using

scatterplots, expressions of r value, and expressions of p value. The intention will be to

determine if the test statistic exceeds the critical value in order to either reject or fail to

reject the hypothesis of a relationship (Triola, 2004).

Multiple regressions to respond to the second research question. A multiple

regression equation will be used in order to respond to the second research question,

where multiple independent variables are regressed on each of the dependent variables

included in extrinsic career success. As Triola explains, “A multiple regression equation

expresses a linear relationship between a dependent variable y and two or more

independent variables (x1, x2, …, xk)” (p. 542). Results will also include residual plots,

expressions of adjusted r2 values, and expressions of p values. The intention will be to

reduce the opportunities for multicollinearity, to establish the value of each coefficient as

a predictor variable, and to maximize the efficacy level of the adjusted r2 value.

Addressing Assumptions and Limitations of Generalizability.

The study and use of statistical analysis, by means of evaluating the number of

both independent and dependent variables, as well as determining the types and

distribution of scores on an instrument, play a large part in coming to a clear conclusion

on which statistical tests are appropriate to render judgment against a tested hypothesis

(Cooper & Schindler, 2003; Creswell, 2009; Rea & Parker, 2005; & Triola, 2004). Yet,

even as this is true, attention must be paid to the assumptions and limitations presented by

the research and the data inherent.

85

Assumptions regarding the use of NLSY79ch archival data include the

assumption that responses were coded accurately at the time of data collection.

Assumptions regarding the storage and transfer of data via the Bureau of Labor Statistics’

online Investigator data retrieval tool include the accurate execution of both actions. The

assumption of truthful responses, alongside the assumption of no instances of self-

enhancement bias, persists as well. It is equally assumed that all numerous studies,

which reported acceptable levels of content validity for the instrument’s components

used, were accurately communicated.

Limitations include the inability to perform respondent/nonrespondent checks for

response bias on archival data (Creswell, 2009). Limitations also include the ability to

only include respondents who were employed at the time of survey in order to accurately

record levels of job satisfaction and income. Thus, these persons must also be of

employable age in order to exclude those persons recently turning 15-years-of-age at the

time of the survey and, without an upward limit on age, parental presence was not

required at the time of data collection. Limitations regarding the generalizability of the

sample continue since, although NLSY79 respondents were said to be representative of

the Baby Boomer population, the sample surveyed for NLSY79ch contained only those

born of NLSY79 respondents. This was put into place in order to avoid creating a

nationally representative sample, since this adds a layer of stratification to the sampling

strategy which precludes generalization to all Generation X workers. Thus, this research

is not assumed to lay claim to universally applied conclusions among Generation X

workers. Yet it is with the intent of communicating conclusions based on a large enough

portion of those workers, such that a recommendation can be made as to the potential

86

value of such research on a larger scale. Therefore, this research would not predict the

relationship between self-esteem and extrinsic career success for all Gen-X workers

individually, but it could provide statistical conclusions as to the potential efficacy of

such research.

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CHAPTER FOUR: DATA ANALYSIS AND RESULTS

This research examines the potential relationship between self-esteem and

extrinsic career success among NLSY79 Young Adult respondents. To do so,

longitudinal data was collected for variables including education, self-esteem, job

satisfaction, income, and occupational prestige. Research questions under study include:


respondents?



To answer these questions, both simple and multiple regressions were used to

analyze these potential relationships, by reviewing the statistical significance of their

interaction. To analyze these data, inclusion criteria are first reviewed, followed by

descriptive statistics around the received data, and finally the results of multiple

hypothesis tests via regression analyses are elucidated.

Inclusion Criteria

In order to best understand the inclusion criteria used, a review of the hypotheses

being tested is germane, followed by a review of available populations.


and occupational prestige when regarding NLSY79 Young Adult respondents.


and income when regarding NLSY79 Young Adult respondents.

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job satisfaction, and occupational prestige when regarding NLSY79 Young Adult

respondents.


job satisfaction, and income when regarding NLSY79 Young Adult respondents.

Available populations from which to sample include those listed under ’15 Years

& Older’ in Figure 6, as provided by the Bureau of Labor Statistics.

Figure 6. Child sample sizes by age and race/ethnicity. This figure depicts the

varying sample sizes of the NLSY79ch, organized by year of data collection.

In order to test hypotheses concerning the variables listed for the populations

above, inclusion criteria had to involve significantly disparate years in order to measure

affect over time, and to include the maximum number of respondents from those years

with existent data for the variables listed. This meant that the review of two separate

collection points where respondents were employed, recorded educational attainment, job

satisfaction, self-esteem, as well as income and occupational prestige in an initial and

chosen year at the beginning and end of an extended period. For those years containing

most prevalent data, only respondents that had data entered for all included variables

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could be considered, since any absence of response would compromise the predictive

power of any regression analysis. The following data are therefore included, as

referenced in Table 1.

Table 1

Presence of Relevant Versus Available Data Befitting Inclusion Criteria

1998 2004

Education Self-

Esteem Job

Satisfaction Income Duncan

SEI Self-

Esteem Job

Satisfaction Income Duncan

SEI Included 681 681 681 681 681 681 681 681 681 Available 2,137 2,135 1,221 1,896 1,215 5,013 3,596 4,227 3,599 Note. Included = Respondents with populated response data across all variables under study, identified by a shared ID.

Holding to a minimum period of six years passing between the time when

respondents were initially surveyed, and the terminal year where data is extracted for

regression analysis, the period spanning 1998 and 2004 provided the largest reliable

dataset with which to work. Other date spans, such as 1996 to 2004 (576 records), 1998

to 2006 (77 records), and 1998 to 2008 (673 records) provided a lesser number of

responses to use reliably in analyzing trend.

Descriptive Statistics

Descriptive statistics often depict much more than merely the essential

characteristics of pre-existent data. Instead, descriptive statistics can also begin to lead

the researcher toward an efficacious direction for statistical analysis. As the data

collected for this study include survey responses for the years 1998 and 2004, Table 2

below depicts the descriptive statistics for this first year of data.

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Table 2

Descriptive Statistics Concerning Relevant 1998 Survey Data

1998 Survey Data Education Self-Esteem Job Satisfaction Income Duncan SEI

Mean 10.61 Mean 33.01 Mean 3.11 Mean 2,713.50 Mean 27.27 Median 11 Median 32 Median 3 Median 1,000 Median 19 Mode 12 Mode 30 Mode 3 Mode 0 Mode 44 SD 1.59 SD 4.31 SD 0.82 SD 4,289.95 SD 17.57 Range 9 Range 19 Range 3 Range 40,000 Range 74 Min 6 Min 21 Min 1 Min 0 Min 6 Max 15 Max 40 Max 4 Max 40,000 Max 80 Count 681 Count 681 Count 681 Count 681 Count 681

As the data collected also include the terminal year 2004, Table 3 below depicts

the descriptive statistics for this final year of survey data.

Table 3

Descriptive Statistics Concerning Relevant 2004 Survey Data

2004 Survey Data Self-Esteem Job Satisfaction Income Duncan SEI

Mean 33.16 Mean 3.15 Mean 17,148.67 Mean 35.83 Median 33 Median 3 Median 15,000 Median 44 Mode 30 Mode 3 Mode 0 Mode 44 SD 4.20 SD 0.87 SD 13,053.19 SD 20.66 Range 22 Range 3 Range 75,000 Range 86 Min 18 Min 1 Min 0 Min 7 Max 40 Max 4 Max 75,000 Max 93 Count 681 Count 681 Count 681 Count 681

Upon review of Tables 2 and 3, it becomes clear that these descriptive statistics

can begin to tell us much about the data under review. Examples include job satisfaction

data, whereby a scale of 1 through 4 is employed for this single question. Responses to

this question of whether or not the respondent is satisfied with one’s position include

possible responses such as like it very much, like it fairly well, dislike it somewhat, and

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dislike it very much (Bureau of Labor Statistics, 2009). As job satisfaction has a reported

mean (µ=3.11) in 1998, and mean (µ=3.15) in 2004, data such as these can begin to

report whether one should expect similar trends in occupational prestige over time if the

relationships expressed in the hypotheses hold true. In this instance, occupational

prestige expressed as a Duncan SEI score with mean (µ=27.27) in 1998, and mean

(µ=35.83) in 2004, show that there lies the possibility that further, rigorous analysis may

prove to express a relationship between these variables.

Internal Consistency of Scales.

Another such descriptive statistic, which indicates the merits of exploring this

data further, is the Cronbach alpha estimate. This measure of internal reliability helps to

distinguish the mean inter-item correlation to therefore consider inclusion in the dataset.

Self-esteem is the only such multi-item variable considered, as it stems from an aggregate

index based on the Rosenberg 10-Item Self-Esteem instrument. The values for this alpha

estimate include for 1998 (α=.887) and for 2004 (α=.882). Based on the aforementioned

descriptions of the numeric alpha estimate, totals in the .8 range can be described as

‘good’ or sufficiently reliable (Gliem & Gliem, 2003).

Frequency Distribution.

A final aspect of descriptive statistics, which equally lends itself to indicating

whether further, more rigorous analysis is with merit, concerns frequency distributions.

Since the research questions concern whether self-esteem and/or job satisfaction possess

a relationship with extrinsic career success, pertinent frequencies are compiled, including

those depicted in Tables 4 and 5.

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Table 4

Frequency Distributions for 1998 Self-Esteem, Job Satisfaction, Income, and Duncan SEI

Data

1998 Frequencies Self-Esteem Job Satisfaction Income Duncan SEI

f % f % f % f % 0-10 0 0.0% 1 38 5.6% 0-10k 641 94.1% 0-25 388 57.0%

11-20 0 0.0% 2 79 11.6% 11-20k 33 4.8% 26-50 234 34.4% 21-30 262 38.5% 3 332 48.8% 21-30k 6 0.9% 51-75 58 8.5% 31-40 419 61.5% 4 232 34.1% 31-40k 1 0.1% 76-100 1 0.1%

Table 5

Frequency Distributions for 2004 Self-Esteem, Job Satisfaction, Income, and Duncan SEI

Data

2004 Frequencies Self-Esteem Job Satisfaction Income Duncan SEI

f % f % f % f % 0-10 0 0.0% 1 44 6.5% 0-18.7k 382 56.1% 0-25 276 40.5%

11-20 1 0.1% 2 81 11.9% 18.8-37.5k 261 38.3% 26-50 271 39.8% 21-30 107 15.7% 3 283 41.6% 37.6-56.3 28 4.1% 51-75 117 17.2% 31-40 573 84.1% 4 273 40.1% 56.4-75k 10 1.5% 76-100 17 2.5%

These distributions can already begin to tell much of what relationships may exist

between self-esteem, job satisfaction, and extrinsic career success. Taking examples such

as self-esteem, 1998 scores showed 61.5% of the population scoring in the top quartile,

and an increase to 84.1% of the population scoring the same in 2004. Increases were also

seen in occupational prestige, as 8.6% of the population sampled scored within the top

half of possible SEI scores and, in 2004, this figure increased to 19.7% of the sampled

population scoring similarly.

Advancing to Regression Analysis.

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Prior to performing additional statistical analysis, certain trends and groupings

already begin to become apparent. One such trend involves the distribution of clustered

self-esteem scores versus the distribution of job satisfaction scores. As these are both to

be considered independent variables in further analysis, care will be taken to ensure the

absence of multicollinearity where possible. Furthermore, as self-esteem continues to

increase over time, so did both income and occupational prestige as expressed in Duncan

SEI scores. While histograms alone only report the graphical relationship of value

clustering, this does indicate the potential for further meaningful analysis. Finally, steps

to control for education will be performed at the outset of analysis. Based on the above

descriptive statistics alone, it can be shown that a focus on these four variables can be

considered for pertinent research. This, as consistency at which subpopulations are

distributed among values, indicates a decreased likelihood of the involvement of such

intervening variables.

Regression Analysis

At the crux of answering the two research questions posed, there are four

hypotheses with pointed regression analyses prescribed for each. These are depicted in

Figure 7.

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Figure 7. Testing deconstruction. The study’s tests which will prove, or fail to

disprove, the hypotheses, which answer the research questions.

According to Creswell (2009), “expect the research questions to evolve and

change during the study in a manner consistent with the assumptions of an emerging

design” (p. 131). In order to allow for a fluid design, the order of tests above is being

regarded as equally fluid. Rather than approaching tests 1 through 4 in the sequence

listed above, the tests will instead be reordered according to which dependent variable

was explored. As test 1 and test 3 concern occupational prestige, and as regression

analysis is focused on the prediction of values around the dependent variable, there is a

need for these to be reordered and responded to sequentially. Tests 2 and 4, therefore,

will be addressed sequentially thereafter. An important aspect to consider, which brings

to light why this reorder is meaningful, is that it will allow the researcher the opportunity

to include the control for education per each dependent variable as the tests are

performed. At its peak, the number of tests may need to be doubled in order to

•Test 1: A simple regression of self-esteem on occupational prestige. •Hypothesis 1 (H0): Relationship between self-esteem and occupational prestige is

insignificant. •Test 2: A simple regression of self-esteem on income. •Hypothesis 2 (H0): Relationship between self-esteem and income is insignificant.

Research Question 1: Is there a relationship between self-esteem and extrinsic career success?

•Test 3: A multiple regression of self-esteem and job satisfaction on occupational prestige. •Hypothesis 3 (H0): Relationship between self-esteem, job satisfaction, and

occupational prestige is insignificant. •Test 4: A multiple regression of self-esteem and job satisfaction on income. •Hypothesis 4 (H0): Relationship between self-esteem, job satisfaction, and income

is insignificant.

Research Question 2: Is there a relationship between self-esteem, job satisfaction, and extrinsic career success?

95

accommodate for the effects of this control on the data and its relationship to other

independent variables’ effect on the dependent variable.

Assumptions in Hypothesis Testing.

The first of these tests is Test 1, and it is a simple regression that takes self-esteem

and regresses on occupational prestige. This first test can be interpreted three ways based

on the data present alone. Are we to consider 1998 self-esteem and 1998 occupational

prestige? Are we to test 2004 self-esteem and 2004 occupational prestige? What about

1998 self-esteem and 2004 occupational prestige? Each derivation works to answer a

different question. If 1998 self-esteem was regressed on 1998 occupational prestige,

even in instances where a statistically significant relationship were expressed, this would

be at the expense of questions concerning whether this explains point-in-time values

only, and whether the direction of effect of the statistical relationship is an accurate one.

In the case of testing 2004 self-esteem regressed on 2004 occupational prestige, the same

holds true, as this would equally assess point-in-time values. Therefore, the two

guideposts synthesized from a review of the literature concerning which variables per

which time periods to use include the following:

1. In order to assess the predictive power of the independent variables as base

traits that have a future impact on the dependent variables, the dependent

variables must be based on a time period in the future.

2. As one’s career cannot be immediately impacted by either independent

variable, and instead must be affected over a longer period of time, changes to

income and occupational prestige cannot be assessed in the same time period

as the base trait and be expected to return immediate results.

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Test 1, Self-Esteem on Occupational Prestige in a Simple Regression.

The null hypothesis regarding the first test states there is no significant

relationship between self-esteem and occupational prestige when regarding NLSY79

Young Adult respondents.

The following table, Table 6, depicts the results of regressing 1998 self-esteem

scores on 2004 occupational prestige values, as expressed by Duncan SEI scores.

Table 6

Summary Output When Regressing 1998 Self-Esteem on 2004 Occupational Prestige

Summary Output for 2004 Duncan SEI 95% CI Coefficient P-Value LL UL Intercept 22.45 0.0003 10.458969 34.434364 1998 Self-Esteem 0.41 0.0274 0.0452296 0.7654666

R2 0.0071 Note. N=681. CI=Confidence Interval.

With a coefficient of .41, 1998 self-esteem is said to contribute to variations in

Duncan SEI scores in 2004 0.7% of the time, with an acceptable p-value of .0274 to

discern statistical confidence in an albeit small effect. The residual plot for this

regression is displayed in Figure 8.

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Figure 8. Residual plot for test 1. Residual plot for the test regressing self-

esteem on occupational prestige.

While the effect is limited, it is confident. Further, the residual plot does indicate

that a linear relationship is at-work, and it shows strong tendencies toward homoscedastic

variation in the residuals. These results do prove enough merit to minimally reject the

null hypothesis.

Test 3, Self-Esteem and Job Satisfaction on Occupational Prestige in a Multiple

Regression.

The null hypothesis for this third test states that there is no significant relationship

between self-esteem, job satisfaction, and occupational prestige when regarding NLSY79

Young Adult respondents. Although the regression returns coefficients for self-esteem

and job satisfaction of .40 and .59 respectively, there are numerous issues with this

equation’s ability to account for variation in occupational prestige scores. The most

notable weakness of this regression is the p-value of .5388 for job satisfaction, indicating

-40

-30

-20

-10

0

10

20

30

40

50

60

70

0 5 10 15 20 25 30 35 40 452004

Dun

can

SEI

1998 Self-Esteem

98

an inadequate amount of confidence in this algorithm to be of statistical validity. This

alone leads the researcher to conclude the equation is unable to reject the null hypothesis.

Test 2, Self-Esteem on Income in a Simple Regression.

The null hypothesis for this test states that there is no significant relationship

between self-esteem and income when regarding NLSY79 Young Adult respondents.

Table 7 below reports the summary output for the simple regression, which regresses

1998 self-esteem on 2004 income.

Table 7

Summary Output When Regressing 1998 Self-Esteem on 2004 Income

Summary Output for 2004 Income 95% CI Coefficient P-Value LL UL Intercept 1,945.73 0.6113 -5567.9042 9459.369 1998 Self-Esteem 460.57 0.0001 234.8573 686.28673


With a reported p-value of .0001, 1998 self-esteem does confidently account for a

portion of the variation in 2004 income. As this coefficient is 460.57, this is the

predicted level of change in income for each increased point in self-esteem. With an r2

value of .0231, however, this equation is said to account for only 2.3% of the variation in

the dependent variable. The residual plot for test 2 follows as Figure 9.

99

Figure 9. Residual plot for test 2. Residual plot for the test regressing self-

esteem on income.

Although self-esteem only accounts for 2.3% of variation in income in 2004,

confidence for this coefficient remains high. What is of concern, however, is the

heteroskedastic variation in the residuals. The ever-widening range in income values

evidences this as the value of self-esteem increases along the x-axis. While this figure is

inadequate to report what additional variable(s) is at-work driving this variation in the

residuals, it is clear that self-esteem alone can neither account for a sizeable amount of

variation in income, nor can it clearly explain this variation self-sufficiently with linear

trending. There is enough evidence, however, to reject the null hypothesis based on p-

value alone.

Test 4, Self-Esteem and Job Satisfaction on Income in a Multiple Regression.

The null hypothesis for this test states that there is no significant relationship

between self-esteem, job satisfaction, and income when regarding NLSY79 Young Adult

respondents.

-30000

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100

As with the test for self-esteem and job satisfaction on occupational prestige, the

addition of job satisfaction as an independent variable again reduces the statistical

confident of the respective algorithm in such a way that this regression fails to reject the

null hypothesis. This is accomplished as indicated by the p-value for 1998 job

satisfaction of .87.

Including Education Values, Both in Simple and Multiple Regressions.

Although it is already quite clear that past job satisfaction is not predicting

variation in extrinsic career success at a statistically confident level, this does not negate

the possibility of education taking its place to potentially and confidently predict extrinsic

career success six years later. To begin, the scope of the hypothesis testing for this

research has expanded to include four additional tests. Those tests include:

1. Education regressed on occupational prestige in a simple regression.

2. Education and self-esteem regressed on occupational prestige in a multiple

regression.

3. Education regressed on income in a simple regression.

4. Education and self-esteem regressed on occupational prestige in a multiple

regression.

Test 5a, Education Regressed on Occupational Prestige in a Simple Regression.

Since no pre-existing null hypotheses were elucidated for tests on education, in

order to outline a null hypothesis, education is assumed to have no effect on the

independent variable, as has been the case in similar hypotheses. Table 8 details the

results of this simple regression.

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Table 8

Summary Output for Education on Occupational Prestige in a Simple Regression

Summary Output for 2004 Duncan SEI 95% CI Coefficient P-Value LL UL Intercept (4.42) 0.3887 -14.476718 5.6402032 1998 Education 3.79 0.0000 2.8549016 4.7296655


It is worthwhile to note that, whereas self-esteem had been the only reliable

predictor for occupational prestige in prior tests, education does so with an infinitesimal

p-value, and accounts for a larger variation in occupational prestige. Whereas self-

esteem had accounted for 0.7% of the variation in occupational prestige, education

accounts for 8.5% of the variation. Figure 10 depicts the residual plot for this simple

regression.

Figure 10. Residual plot for test 5a. Residual plot for the test regressing

education on occupational prestige.

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102

Test 5b, Education and Self-Esteem on Occupational Prestige in a Multiple

Regression.

While examining another test where a null hypothesis had not been outlined

previously, this researcher believes the null hypothesis that the independent variables of

education and self-esteem will not have an effect on the dependent variable occupational

prestige as reflected in Duncan SEI scores. It is interesting to note that, although

education in a simple regression accounted for much of the variation not explained by

self-esteem and it helped to alleviate prevalent heteroskedastic variation in the residuals,

once combined in a multiple regression, these independent variables worked together to

produce an inadequate p-value. The p-value of .35 for self-esteem, therefore, lacks the

confidence needed to reject the null hypothesis.

Test 5c, Education Regressed on Income in a Simple Regression.

As with tests 5a and 5b, test 5c regards unplanned research, which regresses

education on income, with the presumed null hypothesis of the independent variable

(education) as having no effect on the dependent variable (income). Table 9 summarizes

the results of this regression.

Table 9

Summary Output for Education on Income in a Simple Regression

Summary Output for 2004 Income 95% CI Coefficient P-Value LL UL Intercept (11,259.09) 0.0005 -17541.149 -4977.0367 1998 Education 2,676.86 0.0000 2091.4163 3262.3084


103

Upon review of the resulting data above, it quickly becomes evident that the

additional tests were worthwhile. Whereas the simple regression of self-esteem on

income accounted for only 2.3% of the variation in income, education accounted for

10.6% of the variation, and at a near-zero p-value. Additionally, the concern around

heteroskedastic variation in the residuals is somewhat alleviated, as evidenced in Figure

11.

Figure 11. Residual plot for test 5b. Residual plot for the test regressing

education on income.

Test 5d, Education and Self-Esteem on Income in a Multiple Regression.

As with other test 5 variations, the null hypothesis is presumed to be that the

independent variables will have no significant effect on the dependent variable. Table 10

depicts the results of this multiple regression.

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Table 10

Summary Output for Education and Self-Esteem on Income in a Multiple Regression

Summary Output for 2004 Income 95% CI Coefficient P-Value LL UL Intercept (19,599.29) 0.0000 -28343.726 -10854.85 1998 Education 2,536.36 0.0000 1944.5372 3128.1915 1998 Self-Esteem 297.84 0.0076 79.570599 516.10106

Adjusted R2 0.1129 Note. N=681. CI=Confidence Interval.

Although the multiple regression that combines education and self-esteem

produced an inadequately confident algorithm to explain variation in the dependent

variable, this test did not render a similar output. Instead, the combined education and

self-esteem algorithm produced an equation with p-values for education and self-esteem

of .0000 and .0076 respectively, and produced an adjusted r2 of .1129, indicating that the

equation explains 11.3% of the variance in income values six years in the future.

Summary of Results

The following tests succeeded in rejecting their corresponding null hypothesis:

• Test 1, self-esteem on occupation prestige in a simple regression (r2=.0071).

• Test 2, self-esteem on income in a simple regression (r2=.0231).

• Test 5a, education regressed on occupational prestige in a simple regression

(r2=.0850).

• Test 5c, education regressed on income in a simple regression (r2=.1061).

• Test 5d, education and self-esteem on income in a multiple regression

(r2=.1129).

The following tests did not reject their corresponding null hypothesis:

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• Test 3, self-esteem and job satisfaction on occupational prestige in a multiple

regression (p>.05).

• Test 4, self-esteem and job satisfaction on income in a multiple regression

(p>.05).

• Test 5b, education and self-esteem on occupational prestige in a multiple regression (p>.05).

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CHAPTER FIVE: DISCUSSION, CONCLUSIONS, AND RECOMMENDATIONS

Tantamount to an efficacious research process, is the preservation of parsimony.

This is also referred to among Physics scholars as being of an ‘elegant’ design or one that

exhibits no more effort or answer than is necessary. The current process is centered on

parsimony. What began by asking the fundamental questions about how the research

around self-esteem, job satisfaction, and extrinsic career success could come together, it

was invariably determined that greater specificity was needed. The purpose was later

elucidated so as to test the theory of self-esteem and extrinsic career success, which

relates self-esteem to occupational prestige and income, controlling for education, among

respondents of the Bureau of Labor Statistics' National Longitudinal Survey of Youth.

The research questions then asked whether self-esteem, and later self-esteem and

job satisfaction in combination, affected extrinsic career success. Longitudinal data over

a six-year span was collected, while employing inclusion criteria, which resulted in the

‘elegant’ review of only 681 survey respondents with education, self-esteem, and job

satisfaction data in 1998, and extrinsic career success data in 2004. These respondents

provided representation of the NLSY79 Young Adult respondent population with

statistical confidence when responding to the research questions.

Discussion of Results

The data depicted trends, which not only affect how this theory of self-esteem and

extrinsic career success is regarded when viewing this population, but also equally affects

how the theory’s variables and the individual impact of each are described. As indicants

for what occurred, three core themes emerged as precursors to that discussion. Education

was found to carry a far greater significance than merely acting as a variable in control

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over the statistics alone. This was the case, as education explained four times the

variance self-esteem did, making it a better predictor of career success. Education and

self-esteem were also found to be complimentary, while education added predictive

power in addition to self-esteem. This occurred without tangible signs of

multicollinearity in the resulting algorithm. Finally, job satisfaction was found not to be

a predictor of extrinsic career success, as this variable failed to add to any regression's

predictive power of extrinsic career success with statistical confidence based on p-value

(p > .05).

Education is Not Merely a Control.

Throughout the literature review, and in the Kammeyer-Mueller et al. (2007)

study, education was regarded as something to control for in the statistics. Thus, the

originally planned, four hypothesis tests to answer the two research questions concerned

self-esteem and job satisfaction, while merely controlling for education. Yet, what has

become clear is the emergent role of education and its impact on the dependent variables.

In instances where self-esteem explained 2.3% of the variance in income six years later,

education accounted for 10.6%. Where self-esteem explained 0.7% of the variation in

occupational prestige six years in the future, education explained 8.5%.

Education and Self-esteem as Predominantly Complimentary

While the multiple regression, which regressed education and self-esteem on

occupational prestige and was unsuccessful, education and self-esteem on income did

indeed generate confident coefficients. No evidence was present of the two variables

exhibiting multicollinearity when regressed on occupational prestige or income, yet these

variables only contributed to predictions of income. As this combination did account for

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11.3% of the variance in income, it is clear that their combined predictive power is with

merit.

Job Satisfaction Not a Predictor of Extrinsic Career Success.

Upon review of over 11,000 records as contained in the NLSY79 Young Adult

dataset, there was an abundance of available response data to use for analysis.

Significant time was spent isolating only those records which had existent values for all

variables in all time periods covered, and could accurately reflect values for education,

self-esteem, job satisfaction, income, and occupational prestige in unison across years

1998 and 2004. These combined records, which excluded all null, missing, and refused

values, brought 11,000 records to 681. Of those complete data, a confident trend for job

satisfaction’s effect on extrinsic career success did not emerge in the dataset.

Whether regarding job satisfaction in a multiple regression in order to explain

variance in income or occupational prestige, insufficient p-values were reached and those

algorithms possessed no predictive power. While other datasets may depict significant

trend when examining the relationship between self-esteem and extrinsic career success

among NLSY79 Young Adult respondents, job satisfaction played no role in adding

predictive power to any variations of the multiple regressions used to explore this

relationship.

With job satisfaction excluded as an independent variable of interest, it is instead

the relationships between education, self-esteem, and extrinsic career success that remain

germane for consideration.

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Results Pertaining to Research Question 1.

The first research question was inspired by the work done by Kammeyer-Mueller,

Judge, & Piccolo, published in 2007. They provided proof for a dynamic model

depicting the relationship between self-esteem and extrinsic career success for Baby

Boomers who responded to the NLSY79 as commissioned by the Bureau of Labor

Statistics. Therefore, the first research question for this research was:


respondents?

Taking data from the NLSY79 Young Adult, this research uses data collected

from respondents born into Generation X to see whether or not the previously established

relationship exists in a new population. To do so, two tests were performed. The first

test, test 1, regressed self-esteem on occupational prestige in a simple regression. With

an r2 of .7%, and a p-value of .0274 for the coefficient, this relationship exists with

statistical confidence. As reviewed in an aforementioned summary, the residual plot for

this simple regression also indicated homoscedastic variation in the residuals. This

indicates that, not only can this variable be considered by itself as having an effect on

occupational prestige, it is likely to be strongly linear as well. Furthermore, with a

coefficient of .41, and lower and upper limits at 95% of .045 and .765 respectively, an

individual’s self-esteem in 1998 can impact his/her occupational prestige value six years

later by just less than half a point for every point increase in self-esteem. Thus, what can

be seen is, not only is there a linear relationship between self-esteem and occupational

prestige, not only can self-esteem be a confident predictor for a portion of the variation in

occupational prestige six years later, but it equally allows for the answer to this research

110

question to be in the affirmative. That is to say that a relationship does exist between

self-esteem and extrinsic career success where occupational prestige is concerned.

Additional to test 1 was test 2, which regressed self-esteem on income across the

same date span. Upon regressing 1998 self-esteem scores on 2004 income values, this

algorithm produced an r2 score of 2.3%. Additionally, with a p-value of .0001, self-

esteem’s coefficient registered as 460.57. This is to say that with every point increase in

self-esteem in 1998, annual income increased by approximately $461 six years later.

With a confidence level registering a p-value of .01%, this other half of the research

question can be confirmed to say that self-esteem also exhibits a relationship with

extrinsic career success in its impact on income. Thus, the first research question is

answered in the affirmative in its entirety. That is to say that a relationship between self-

esteem and extrinsic career success among NLSY79 Young Adult respondents does exist.

For every point increase in self-esteem in the year, occupational prestige increases by .4

and income by approximately $461, both six years in the future.

Results Pertaining to Research Question 2.

Early in this research, one justification was provided that regarded a lack of

understanding as to the motivational factors that beget further inquiry about whether or

not elevating job satisfaction alone was sufficient to ensure organizational loyalty. The

research has also shown a tendency for Generation X workers to migrate between

organizations ‘with alacrity’. To begin to answer whether the two research focal points

of self-esteem and job satisfaction could merge, the second research question was

formed:

111



Tests 3 and 4 were performed to answer this very question. Both were multiple

regressions, where the first was a multiple regression of self-esteem and job satisfaction

on occupational prestige. The second test, test 4, was a multiple regression of self-esteem

and job satisfaction on income. Test 3, that of self-esteem and job satisfaction on

occupational prestige, failed to deliver reliable results. With a p-value of .5388, the job

satisfaction coefficient could never be confidently introduced into the algorithm. Test 4

was equally a failure, as the p-value for job satisfaction was .87 when regressing self-

esteem and job satisfaction on income. Therefore, test 4, as in test 3, was unsuccessful at

integrating a job satisfaction coefficient into the algorithm.

These tests failed to reject the null hypotheses that said there was no effect of self-

esteem and job satisfaction in combination when in relation to extrinsic career success.

While only applicable for the 681 respondents of the NLSY79 Young Adult, this

indicates a greatly decreased likelihood that job satisfaction can be regarded as a

predictor for long-term extrinsic career success. So, while self-esteem in simple

regressions can reliably impact income and occupational prestige six years in the future,

job satisfaction as a coefficient failed to express similar characteristics. Thus, the first

research question of whether a relationship exists between self-esteem and extrinsic

career success was answered in the affirmative. The second research question of self-

esteem and job satisfaction’s relationship with extrinsic career success was not.

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Results Pertaining to Education’s Necessary Emphasis.

As mentioned in prior chapters, a research design must be tailored in a way that

allows for the at-times necessary ability to sense and adjust as patterns in the data

emerge. This was the case with education as a control. The theory of self-esteem and

extrinsic career success holds that there exists a relationship between self-esteem and

extrinsic career success when controlling for education. During the course of the analysis

above, it became clear that education provided much more than this. Rather than being a

factor with which to exercise control to report the net effect of self-esteem on the aspects

of extrinsic career success, education delivered far more pervasive predictive powers

when discussing both of the two aspects of extrinsic career success. As a result, four new

tests were performed. Tests were performed to regress education on income and on

occupational prestige. Tests were also performed to regress education and now proven

self-esteem in combination on income and on occupational prestige.

The two most successful tests were 5a and 5d, if by successful the criteria are

those tests which created the greatest predictive power per aspect of extrinsic career

success. Test 5a regressed education on occupational prestige in a simple regression.

The multiple regression form of this algorithm, which was to include self-esteem, did not

prove worthwhile, as the p-value for this algorithm failed to reach the minimum

confidence level for the self-esteem coefficient (p-value = .35). The simple regression,

however, produced an r2 of .085, predicting 8.5% of the variation in occupational prestige

six years later. With a coefficient of 3.79, it can be shown that, for every additional year

of completed education in 1998, it contributed an additional 3.79 points to a respondent’s

occupational prestige score in 2004.

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Test 5d was equally successful in increasing the predictive power of 1998 data to

2004 outcome. Although a simple regression of education on income produced an

algorithm, which accounted for 10.6% of the variance in income in 2004, the multiple

regression to include self-esteem delivered a statistically confident adjusted r2 value of

.1129. This accounts for 11.3% of the variation in income in 2004, and it does so with

the highest p-value being .0076 between the two variables. There are two initial

conclusions that can be drawn from this. They include the statistical inability to account

for income using education alone for best fit and certainly not doing so based on self-

esteem alone.

Instead, the most pragmatic use of data appears instead to be to predict

occupational prestige using education data of six years past, while combining education

and self-esteem data instead to predict income six years in the future. Yet, prior to

reaching final implications with this data, the following are recommendations for further

research.

Recommendations for Further Research

Even at their most efficient states, the multiple regressions discussed above

account for less than 12% of the variance in extrinsic career success six years in the

future. Additional research to identify further predictors of this success from similar

longitudinal data would be advantageous for identifying a solution with which to predict

career path. Additionally, this research focuses on respondents of the NLSY79 Young

Adult survey. When answering questions regarding Generation X, further research can

be broadened to include a larger, more representative sample of this generation in order

to draw inference on the whole. Finally, while research in this area has been done on

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NLSY79 respondent data, and now the NLSY79 Young Adult respondent data, there also

exists the NLSY97 data, which pertains to respondents otherwise classified as Generation

Y by birth. This could lead to inter-generational research where implications across

generations can be made with proper sampling and statistical analysis.

Conclusions in Relation to Modern Thinking

During the initial review of the literature, it was posited that succession planning

via the establishment of a Leadership Pipeline should drive the efforts of all who

contribute to an organization’s development. Yet, this can occur only after each level is

populated with those individuals who either feel befitting of that role, or who feel they

are on their way to a befitting role as potentially evidenced by the corollary relationship

between self-esteem and extrinsic career success over time. The evidence to support this

relationship is now in existence.

Evidence now exists of the relationship between self-esteem and extrinsic career

success among NLSY79 Young Adult respondents. Evidence also exists now of the

relationship between education and extrinsic career success among NLSY79 Young

Adult respondents. This research has elucidated a relationship between aspects of

personality and the stability of career paths, thus exhibiting the potential side effect of

compromises to organizational profitability when not in alignment. This impact is driven

by one’s self-esteem, and maintains a relationship with one’s income and one’s

occupational prestige. With every year of formal education completed, a person is likely

to earn an additional $2,700 per year, six years into the future. With every year of formal

education complete, an NLSY79 Young Adult respondent’s Duncan SEI score increased

by 3.79 points six years in the future. Self-esteem accounted for an additional $300 per

115

year when coupled with education and an additional $460 gross effect on income over the

same period. Job satisfaction, while perhaps otherwise meaningful, rendered no impact

and expressed no relationship to extrinsic career success among NLSY79 Young Adult

respondents.

Organizations are at a crossroads since they are in the midst of a shift in

leadership from members of the Baby Boomer population to members of Generation X.

The respondents of the NLSY79 cannot tell us all we need to know about Gen-X, but

they can provide us with a glimpse into the attitudes of members of this generation, while

serving to pilot for larger studies inclusive of a representative sample of Generation X

members.

The literature has shown a tendency for this up-and-coming generation to be

incentivized by merit, driven by individualism, while embracing a matrix organization

that puts ceremony aside and concentrates on action. The respondents of the NLSY79

Young Adult are guided by self-evaluation, and they exhibit heightened income and

prestige when self-esteem and education are heightened. The impact of education over

the impact of self-esteem speaks to the emphasis on individual merit, and organizations

of today would benefit from a keen focus on the Five Minds of the Future. While acting

on the research of Mintzberg and others in creating organizations that respond to shifting

environments, and acting on the research of Schein while creating organizations that

exhibit boundaryless operation, respondents of the NLSY79 Young Adult can find

themselves welcome among peers. This welcomed reception is not based on new hire

orientations, which present reams of training material and countless presentations from

numerous department heads. Instead, these are orientations where employees have had

116

self-perception assessed prior to hire, and they are put into roles befitting self and

organization-aligned expectations. They are given endless opportunities to move

forward, to find true passion, and to expand current skillset at a pace set by each one

individually, while serving a responsive and open organization. When Gen-X entered the

workforce, companies were blindsided. Employers never expected Xers to behave

differently from Baby Boomers or that they would have their own unique expectations

about the workplace (Lancaster & Stillman, 2010). The research detailed herein of the

NLSY79 Young Adult Respondents, contributes to the literature by serving as a pilot on

which to base a larger study of the theory of self-esteem and extrinsic career success, and

its impact on a representative sample of the Generation X population.

117

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APPENDICES

141

APPENDIX A

Codebook of Selected Variables

142

C00001.00 [CPUBID] Survey Year: XRND PRIMARY VARIABLE ID CODE OF CHILD PUBLIC IDENTIFICATION CODE OF CHILD UNIVERSE: All children, regardless of age. 11495 1 TO 9999999: See Min & Max values below for range as of this release ------- 11495 Refusal(-1) 0 Don't Know(-2) 0 TOTAL =========> 11495 MISSING(-7) 0 Min: 201 Max: 1267501 Mean: 601312.98 Lead In: None. Default Next Question: C00002.00 -------------------------------------------------------------------------------- C00002.00 [MPUBID] Survey Year: XRND PRIMARY VARIABLE ID CODE OF MOTHER OF CHILD PUBLIC IDENTIFICATION CODE OF MOTHER OF CHILD UNIVERSE: All children, regardless of age. SEE YOUTH REFERENCE NUMBER R( 1.) 11495 1 TO 12686: NLSY79 Public ID ------- 11495 Refusal(-1) 0 Don't Know(-2) 0 TOTAL =========> 11495 MISSING(-7) 0 Min: 2 Max: 12675 Mean: 6013.11 Lead In: C00001.00[Default] Default Next Question: C00003.00 -------------------------------------------------------------------------------- C00053.00 [CRACE] Survey Year: XRND PRIMARY VARIABLE RACE OF CHILD (MOTHER'S RACIAL/ETHNIC COHORT FROM SCREENER) RACE OF CHILD (MOTHER'S RACIAL/ETHNIC COHORT FROM SCREENER) SEE YOUTH REFERENCE NUMBER R( 2147.) 2209 1 HISPANIC 3187 2 BLACK 6099 3 NON-BLACK, NON-HISPANIC

143

------- 11495 Refusal(-1) 0 Don't Know(-2) 0 TOTAL =========> 11495 MISSING(-7) 0 Lead In: C00052.00[Default] Default Next Question: C00054.00 -------------------------------------------------------------------------------- C00054.00 [CSEX] Survey Year: XRND PRIMARY VARIABLE SEX OF CHILD SEX OF CHILD 5870 1 MALE 5624 2 FEMALE ------- 11494 Refusal(-1) 0 Don't Know(-2) 0 Invalid Skip(-3) 1 TOTAL =========> 11495 MISSING(-7) 0 Lead In: C00053.00[Default] Default Next Question: C00055.00 -------------------------------------------------------------------------------- C00057.00 [CYRB] Survey Year: XRND PRIMARY VARIABLE DATE OF BIRTH OF CHILD - YEAR DATE OF BIRTH OF CHILD - YEAR For weighting purposes ONLY, the birthdate for Child ID 851104 was assigned October 2001, which will make the child slightly over 3 years old at the date of interview. The DOB as reported by the mother is missing in the main Youth file. Case ID 341601: YRB was determined to be 2001, not 2002 as previously reported. Case ID 638301: YRB was determined to be 1974, not 1973 as previously reported. Case ID 641702: YRB was determined to be 1997, not 1998 as previously reported. Case ID 812101: YRB was determined to be 1992, not 1993 as previously reported. 1221 1970 TO 1978: < before 1979 527 1979 607 1980 714 1981 703 1982 715 1983 656 1984 675 1985 617 1986 622 1987 581 1988 627 1989 492 1990 424 1991

144

399 1992 345 1993 294 1994 243 1995 228 1996 211 1997 155 1998 127 1999 97 2000 81 2001 43 2002 33 2003 23 2004 16 2005 9 2006 5 2007 3 2008 ------- 11493 Refusal(-1) 0 Don't Know(-2) 0 Invalid Skip(-3) 2 TOTAL =========> 11495 MISSING(-7) 0 Min: 1970 Max: 2008 Mean: 1986.05 Lead In: C00055.00[Default] Default Next Question: C00058.00 -------------------------------------------------------------------------------- Y07099.00 [Q4-19] Survey Year: 1998 PRIMARY VARIABLE HIGHEST GRADE OF REGULAR SCHOOL R HAS COMPLETED What is the highest grade of regular school that you have completed and gotten credit for? 1 1 1ST GRADE 0 2 2ND GRADE 0 3 3RD GRADE 0 4 4TH GRADE 1 5 5TH GRADE 16 6 6TH GRADE 95 7 7TH GRADE 355 8 8TH GRADE 446 9 9TH GRADE 420 10 10TH GRADE 340 11 11TH GRADE 352 12 12TH GRADE 78 13 1ST YEAR COLLEGE 26 14 2ND YEAR COLLEGE 5 15 3RD YEAR COLLEGE 1 16 4TH YEAR COLLEGE 0 17 5TH YEAR COLLEGE 0 18 6TH YEAR COLLEGE 0 19 7TH YEAR COLLEGE 0 20 8TH YEAR COLLEGE OR MORE 1 95 UNGRADED 0 0 None -------

145

2137 Refusal(-1) 0 Don't Know(-2) 1 TOTAL =========> 2138 MISSING(-7) 9357 Lead In: Y07097.00[Default] Y07098.00[Default] Default Next Question: Y07100.00 -------------------------------------------------------------------------------- Y07734.00 [QES-55H.01] Survey Year: 1998 PRIMARY VARIABLE OCCUPATION (CENSUS 3 DIGIT) JOB # 01 What kind of work [do/did] you do. That is, what [is/was] your occupation? (For example: plumber, typist, farmer..) (INTERVIEWER: INITIALIZE SCREEN AND PRESS <ENTER> TO ENTER TEXT. PRESS <F6> FOR DON'T KNOW.) THESE DATA WERE REVIEWED AS PART OF DATA CLEANING AND CODING EFFORTS FOR THE 2000 RELEASE. A SMALL NUMBER OF CASES HAVE UPDATED VALUES. 43 1 TO 195: PROFESSIONAL,TECHNICAL AND KINDRED 26 201 TO 245: MANAGERS,OFFICIALS AND PROPRIETORS 72 260 TO 285: SALES WORKERS 299 301 TO 395: CLERICAL AND KINDRED 59 401 TO 575: CRAFTSMEN,FOREMEN AND KINDRED 2 580 TO 590: ARMED FORCES 84 601 TO 715: OPERATIVES AND KINDRED 181 740 TO 785: LABORERS, EXCEPT FARM 22 821 TO 824: FARM LABORERS AND FOREMAN 370 901 TO 965: SERVICE WORKERS, EXCEPT PRIVATE HOUSEHOLD 53 980 TO 984: PRIVATE HOUSEHOLD ------- 1211 Refusal(-1) 2 Don't Know(-2) 2 Invalid Skip(-3) 4 TOTAL =========> 1219 MISSING(-7) 10276 Min: 3 Max: 984 Mean: 629.94 Lead In: Y07729.00[Default] Default Next Question: Y07739.00 -------------------------------------------------------------------------------- Y08386.00 [QES-89.01] Survey Year: 1998 PRIMARY VARIABLE GLOBAL JOB SATISFACTION JOB # 01 How [do/did] you feel about your job with [Name of employer]? [Do/Did] you like it very much, like it fairly well, dislike it somewhat, or dislike it very much? (CODE ONE ONLY.) 426 1 Like it very much 581 2 Like it fairly well 151 3 Dislike it somewhat

146

63 4 Dislike it very much ------- 1221 Refusal(-1) 1 Don't Know(-2) 0 TOTAL =========> 1222 MISSING(-7) 10273 Lead In: Y08365.00[Default] Y08385.00[Default] Y08360.00[Default] Y08383.00[Default] Default Next Question: Y07483.00 -------------------------------------------------------------------------------- Y09048.00 [Q15-5] Survey Year: 1998 PRIMARY VARIABLE TOTAL INCOME FROM WAGES AND SALARY IN 1997 During 1997, how much did you receive from wages, salary, commissions, or tips from all (other) jobs, before deductions for taxes or anything else? 1117 0 278 1 TO 999 139 1000 TO 1999 84 2000 TO 2999 62 3000 TO 3999 46 4000 TO 4999 30 5000 TO 5999 25 6000 TO 6999 26 7000 TO 7999 10 8000 TO 8999 9 9000 TO 9999 39 10000 TO 14999 20 15000 TO 19999 6 20000 TO 24999 4 25000 TO 49999 1 50000 TO 99999999: 50000+ ------- 1896 Refusal(-1) 5 Don't Know(-2) 238 TOTAL =========> 2139 MISSING(-7) 9356 Min: 0 Max: 50000 Mean: 1367.11 Lead In: Y09047.00[Default] Y09046.00[Default] Default Next Question: Y09049.00 -------------------------------------------------------------------------------- Y09299.00 [Q16-5H-A] Survey Year: 1998 PRIMARY VARIABLE SELF-ESTEEM - I AM A PERSON OF WORTH I feel that I'm a person of worth, at least on an equal basis with others. 17 1 Strongly Disagree 94 2 Disagree 1288 3 Agree 733 4 Strongly Agree -------

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2132 Refusal(-1) 0 Don't Know(-2) 7 TOTAL =========> 2139 MISSING(-7) 9356 Lead In: Y09298.00[Default] Default Next Question: Y09300.00 -------------------------------------------------------------------------------- Y09300.00 [Q16-5H-B] Survey Year: 1998 PRIMARY VARIABLE SELF-ESTEEM - I HAVE A NUMBER OF GOOD QUALITIES I feel that I have a number of good qualities. 15 1 Strongly Disagree 28 2 Disagree 1283 3 Agree 808 4 Strongly Agree ------- 2134 Refusal(-1) 0 Don't Know(-2) 5 TOTAL =========> 2139 MISSING(-7) 9356 Lead In: Y09299.00[Default] Default Next Question: Y09301.00 -------------------------------------------------------------------------------- Y09301.00 [Q16-5H-C] Survey Year: 1998 PRIMARY VARIABLE SELF-ESTEEM - I AM INCLINED TO FEEL THAT I AM A FAILURE All in all, I am inclined to feel that I am a failure. 1011 1 Strongly Disagree 1055 2 Disagree 61 3 Agree 8 4 Strongly Agree ------- 2135 Refusal(-1) 0 Don't Know(-2) 4 TOTAL =========> 2139 MISSING(-7) 9356 Lead In: Y09300.00[Default] Default Next Question: Y09302.00 -------------------------------------------------------------------------------- Y09302.00 [Q16-5H-D] Survey Year: 1998 PRIMARY VARIABLE SELF-ESTEEM - I AM AS CAPABLE AS OTHERS I am able to do things as well as most people. 14 1 Strongly Disagree

148

57 2 Disagree 1298 3 Agree 766 4 Strongly Agree ------- 2135 Refusal(-1) 0 Don't Know(-2) 4 TOTAL =========> 2139 MISSING(-7) 9356 Lead In: Y09301.00[Default] Default Next Question: Y09303.00 -------------------------------------------------------------------------------- Y09303.00 [Q16-5H-E] Survey Year: 1998 PRIMARY VARIABLE SELF-ESTEEM - I FEEL I DO NOT HAVE MUCH TO BE PROUD OF I feel that I do not have much to be proud of. 929 1 Strongly Disagree 1046 2 Disagree 138 3 Agree 21 4 Strongly Agree ------- 2134 Refusal(-1) 0 Don't Know(-2) 5 TOTAL =========> 2139 MISSING(-7) 9356 Lead In: Y09302.00[Default] Default Next Question: Y09304.00 -------------------------------------------------------------------------------- Y09304.00 [Q16-5H-F] Survey Year: 1998 PRIMARY VARIABLE SELF-ESTEEM - I HAVE A POSITIVE ATTITUDE I take a positive attitude toward myself. 20 1 Strongly Disagree 117 2 Disagree 1298 3 Agree 699 4 Strongly Agree ------- 2134 Refusal(-1) 0 Don't Know(-2) 5 TOTAL =========> 2139 MISSING(-7) 9356 Lead In: Y09303.00[Default] Default Next Question: Y09305.00 -------------------------------------------------------------------------------- Y09305.00 [Q16-5H-G] Survey Year: 1998 PRIMARY VARIABLE SELF-ESTEEM - I AM SATISFIED WITH MYSELF

149

On the whole, I am satisfied with myself. 12 1 Strongly Disagree 134 2 Disagree 1377 3 Agree 611 4 Strongly Agree ------- 2134 Refusal(-1) 0 Don't Know(-2) 5 TOTAL =========> 2139 MISSING(-7) 9356 Lead In: Y09304.00[Default] Default Next Question: Y09306.00 -------------------------------------------------------------------------------- Y09306.00 [Q16-5H-H] Survey Year: 1998 PRIMARY VARIABLE SELF-ESTEEM - I WISH I HAD MORE SELF-RESPECT I wish I could have more respect for myself. 514 1 Strongly Disagree 1096 2 Disagree 447 3 Agree 74 4 Strongly Agree ------- 2131 Refusal(-1) 1 Don't Know(-2) 7 TOTAL =========> 2139 MISSING(-7) 9356 Lead In: Y09305.00[Default] Default Next Question: Y09307.00 -------------------------------------------------------------------------------- Y09307.00 [Q16-5H-I] Survey Year: 1998 PRIMARY VARIABLE SELF-ESTEEM - I FEEL USELESS AT TIMES I certainly feel useless at times. 518 1 Strongly Disagree 1170 2 Disagree 414 3 Agree 32 4 Strongly Agree ------- 2134 Refusal(-1) 1 Don't Know(-2) 4 TOTAL =========> 2139 MISSING(-7) 9356 Lead In: Y09306.00[Default] Default Next Question: Y09308.00 -------------------------------------------------------------------------------- Y09308.00 [Q16-5H-J] Survey Year: 1998

150

PRIMARY VARIABLE SELF-ESTEEM - I SOMETIMES THINK I AM "NO GOOD" AT ALL At times I think I am no good at all. 766 1 Strongly Disagree 1118 2 Disagree 231 3 Agree 20 4 Strongly Agree ------- 2135 Refusal(-1) 0 Don't Know(-2) 4 TOTAL =========> 2139 MISSING(-7) 9356 Lead In: Y09307.00[Default] Default Next Question: Y09309.00 -------------------------------------------------------------------------------- Y14917.00 [Q4-19] Survey Year: 2004 PRIMARY VARIABLE HIGHEST GRADE OF REGULAR SCHOOL R HAS COMPLETED What is the highest grade of regular school that you have completed and gotten credit for? 2 1 1ST GRADE 3 2 2ND GRADE 2 3 3RD GRADE 2 4 4TH GRADE 4 5 5TH GRADE 17 6 6TH GRADE 105 7 7TH GRADE 353 8 8TH GRADE 450 9 9TH GRADE 455 10 10TH GRADE 466 11 11TH GRADE 754 12 12TH GRADE 311 13 1ST YEAR COLLEGE 233 14 2ND YEAR COLLEGE 125 15 3RD YEAR COLLEGE 86 16 4TH YEAR COLLEGE 16 17 5TH YEAR COLLEGE 11 18 6TH YEAR COLLEGE 3 19 7TH YEAR COLLEGE 3 20 8TH YEAR COLLEGE OR MORE 2 95 UNGRADED 3 0 None ------- 3406 Refusal(-1) 0 Don't Know(-2) 20 TOTAL =========> 3426 MISSING(-7) 8069 Lead In: Y14915.00[Default] Y14916.00[Default] Default Next Question: Y14918.00 --------------------------------------------------------------------------------

151

Y15283.00 [OCC2000.01] Survey Year: 2004 PRIMARY VARIABLE OCCUPATION (2000 CENSUS 4 DIGIT, 00 CODES) JOB # 01 COMMENT: 2000 CENSUS CODE FOR OCCUPATION 2000 CENSUS CODE FOR OCCUPATION - EMPLOYER (UPDATED IN 2002) 85 10 TO 430: Executive, Administrative and Managerial Occupations 38 500 TO 950: Management Related Occupations 22 1000 TO 1240: Mathematical and Computer Scientists 18 1300 TO 1560: Engineers, Architects, Surveyers, Engineering and Related Technicians 2 1600 TO 1760: Physical Scientists 2 1800 TO 1860: Social Scientists and Related Workers 4 1900 TO 1960: Life, Physical and Social Science Technicians 30 2000 TO 2060: Counselors, Sociala and Religious Workers 11 2100 TO 2150: Lawyers, Judges and Legal Support Workers 86 2200 TO 2340: Teachers 27 2400 TO 2550: Education, Training and Library Workers 44 2600 TO 2760: Entertainers and Performers, Sports and Related Workers 19 2800 TO 2960: Media and Communications Workers 17 3000 TO 3260: Health Diagnosing and Treating Practitioners 148 3300 TO 3650: Health Care Technical and Support Occupations 60 3700 TO 3950: Protective Service Occupations 579 4000 TO 4160: Food Preparation and Serving Related Occupations 166 4200 TO 4250: Cleaning and Building Service Occupations 43 4300 TO 4430: Entertainment Attendants and Related Workers 120 4500 TO 4650: Personal Care and Service Workers 607 4700 TO 4960: Sales and Related Workers 585 5000 TO 5930: Office and Administrative Support Workers 36 6000 TO 6130: Farming, Fishing and Forestry Occupations 218 6200 TO 6940: Construction Trade and Extraction Workers 101 7000 TO 7620: Installation, Maintenance and Repairs Workers 47 7700 TO 7750: Production and Operating Workers 15 7800 TO 7850: Food Preparation Occupations 165 7900 TO 8960: Setters, Operators and Tenders 297 9000 TO 9750: Transportation and Material Moving Workers 7 9800 TO 9830: Military Specific Occupations ------- 3599 Refusal(-1) 1 Don't Know(-2) 0 TOTAL =========> 3600 MISSING(-7) 7895 Min: 10 Max: 9830 Mean: 5126.6 Lead In: Y15278.00[Default] Y15273.00[Default] Default Next Question: Y15288.00 -------------------------------------------------------------------------------- Y15581.00 [QES-89.01] Survey Year: 2004 PRIMARY VARIABLE GLOBAL JOB SATISFACTION JOB # 01 How [do/did] you feel about your job with [name of new employer]([loop number])?

152

[do/did] you like it very much, like it fairly well, dislike it somewhat, or dislike it very much? (CODE ONE ONLY.) 1345 1 Like it very much 1577 2 Like it fairly well 448 3 Dislike it somewhat 226 4 Dislike it very much ------- 3596 Refusal(-1) 1 Don't Know(-2) 3 TOTAL =========> 3600 MISSING(-7) 7895 Lead In: Y15576.00[Default] Y15562.00[1:1] Default Next Question: Y15586.00 -------------------------------------------------------------------------------- Y16384.00 [Q15-5-TOP] Survey Year: 2004 PRIMARY VARIABLE TOTAL INCOME FROM WAGES AND SALARY IN 2003 During 2003, how much did you receive from wages, salary, commissions, or tips from all (other) jobs [-military or civilian-] before deductions for taxes or anything else? THIS VARIABLE HAS BEEN TOP-CODED. THE VALUE OF 174300 REPRESENTS THE MEAN OF THE TOP VALUES. 1091 0 566 1 TO 999 277 1000 TO 1999 208 2000 TO 2999 146 3000 TO 3999 127 4000 TO 4999 123 5000 TO 5999 84 6000 TO 6999 62 7000 TO 7999 91 8000 TO 8999 70 9000 TO 9999 358 10000 TO 14999 257 15000 TO 19999 256 20000 TO 24999 437 25000 TO 49999 74 50000 TO 99999999: 50000+ ------- 4227 Refusal(-1) 22 Don't Know(-2) 771 TOTAL =========> 5020 MISSING(-7) 6475 Min: 0 Max: 174300 Mean: 9057.38 Lead In: Y16382.00[Default] Default Next Question: Y16385.00 -------------------------------------------------------------------------------- Y16465.00 [Q16-5H-A] Survey Year: 2004 PRIMARY VARIABLE

153

SELF-ESTEEM - I AM A PERSON OF WORTH I feel that I'm a person of worth, at least on an equal basis with others. 58 1 Strongly Disagree 276 2 Disagree 2961 3 Agree 1707 4 Strongly Agree ------- 5002 Refusal(-1) 1 Don't Know(-2) 16 TOTAL =========> 5019 MISSING(-7) 6476 Lead In: Y16464.00[Default] Default Next Question: Y16466.00 -------------------------------------------------------------------------------- Y16466.00 [Q16-5H-B] Survey Year: 2004 PRIMARY VARIABLE SELF-ESTEEM - I HAVE A NUMBER OF GOOD QUALITIES I feel that I have a number of good qualities. 23 1 Strongly Disagree 52 2 Disagree 2897 3 Agree 2034 4 Strongly Agree ------- 5006 Refusal(-1) 1 Don't Know(-2) 12 TOTAL =========> 5019 MISSING(-7) 6476 Lead In: Y16465.00[Default] Default Next Question: Y16467.00 -------------------------------------------------------------------------------- Y16467.00 [Q16-5H-C] Survey Year: 2004 PRIMARY VARIABLE SELF-ESTEEM - I AM INCLINED TO FEEL THAT I AM A FAILURE All in all, I am inclined to feel that I am a failure. 2317 1 Strongly Disagree 2541 2 Disagree 131 3 Agree 16 4 Strongly Agree ------- 5005 Refusal(-1) 2 Don't Know(-2) 12 TOTAL =========> 5019 MISSING(-7) 6476 Lead In: Y16466.00[Default]

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Default Next Question: Y16468.00 -------------------------------------------------------------------------------- Y16468.00 [Q16-5H-D] Survey Year: 2004 PRIMARY VARIABLE SELF-ESTEEM - I AM AS CAPABLE AS OTHERS I am able to do things as well as most people. 28 1 Strongly Disagree 117 2 Disagree 3115 3 Agree 1749 4 Strongly Agree ------- 5009 Refusal(-1) 3 Don't Know(-2) 7 TOTAL =========> 5019 MISSING(-7) 6476 Lead In: Y16467.00[Default] Default Next Question: Y16469.00 -------------------------------------------------------------------------------- Y16469.00 [Q16-5H-E] Survey Year: 2004 PRIMARY VARIABLE SELF-ESTEEM - I FEEL I DO NOT HAVE MUCH TO BE PROUD OF I feel that I do not have much to be proud of. 2109 1 Strongly Disagree 2576 2 Disagree 259 3 Agree 59 4 Strongly Agree ------- 5003 Refusal(-1) 4 Don't Know(-2) 12 TOTAL =========> 5019 MISSING(-7) 6476 Lead In: Y16468.00[Default] Default Next Question: Y16470.00 -------------------------------------------------------------------------------- Y16470.00 [Q16-5H-F] Survey Year: 2004 PRIMARY VARIABLE SELF-ESTEEM - I HAVE A POSITIVE ATTITUDE I take a positive attitude toward myself. 20 1 Strongly Disagree 228 2 Disagree 3074 3 Agree 1681 4 Strongly Agree ------- 5003 Refusal(-1) 3

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Don't Know(-2) 13 TOTAL =========> 5019 MISSING(-7) 6476 Lead In: Y16469.00[Default] Default Next Question: Y16471.00 -------------------------------------------------------------------------------- Y16471.00 [Q16-5H-G] Survey Year: 2004 PRIMARY VARIABLE SELF-ESTEEM - I AM SATISFIED WITH MYSELF On the whole, I am satisfied with myself. 41 1 Strongly Disagree 357 2 Disagree 3179 3 Agree 1426 4 Strongly Agree ------- 5003 Refusal(-1) 3 Don't Know(-2) 13 TOTAL =========> 5019 MISSING(-7) 6476 Lead In: Y16470.00[Default] Default Next Question: Y16472.00 -------------------------------------------------------------------------------- Y16472.00 [Q16-5H-H] Survey Year: 2004 PRIMARY VARIABLE SELF-ESTEEM - I WISH I HAD MORE SELF-RESPECT I wish I could have more respect for myself. 1154 1 Strongly Disagree 2706 2 Disagree 997 3 Agree 134 4 Strongly Agree ------- 4991 Refusal(-1) 5 Don't Know(-2) 23 TOTAL =========> 5019 MISSING(-7) 6476 Lead In: Y16471.00[Default] Default Next Question: Y16473.00 -------------------------------------------------------------------------------- Y16473.00 [Q16-5H-I] Survey Year: 2004 PRIMARY VARIABLE SELF-ESTEEM - I FEEL USELESS AT TIMES I certainly feel useless at times. 1223 1 Strongly Disagree 2805 2 Disagree 910 3 Agree 70 4 Strongly Agree

156

------- 5008 Refusal(-1) 3 Don't Know(-2) 8 TOTAL =========> 5019 MISSING(-7) 6476 Lead In: Y16472.00[Default] Default Next Question: Y16474.00 -------------------------------------------------------------------------------- Y16474.00 [Q16-5H-J] Survey Year: 2004 PRIMARY VARIABLE SELF-ESTEEM - I SOMETIMES THINK I AM "NO GOOD" AT ALL At times I think I am no good at all. 1687 1 Strongly Disagree 2789 2 Disagree 491 3 Agree 40 4 Strongly Agree ------- 5007 Refusal(-1) 4 Don't Know(-2) 8 TOTAL =========> 5019 MISSING(-7) 6476 Lead In: Y16473.00[Default] Default Next Question: Y16475.00 --------------------------------------------------------------------------------

157

APPENDIX B

Comprehensive Variable Histograms

158

020406080

100120140160180

6 7 8 9 10 11 12 13 14 MoreEducation - 1998

0

50

100

150

200

250

2.5 5

7.5 10

12.5 15

17.5 20

22.5 25

27.5 30

32.5 35

37.5 40

Mor

e

Self-Esteem Score - 2004

0

50

100

150

200

250

2.5 5

7.5 10

12.5 15

17.5 20

22.5 25

27.5 30

32.5 35

37.5 40

Mor

e

Self-Esteem Score - 1998

0

50

100

150

200

250

300

2 3 4 MoreJob Satisfaction - 2004

0

50

100

150

200

250

300

350

2 3 4 MoreJob Satisfaction - 1998

159

020406080

100120140160180

Duncan SEI Score - 2004

020406080

100120140160180200

Duncan SEI Score - 1998

050

100150200250300350400450500

Annual Income - 1998

020406080

100120140

Annual Income - 2004

160

APPENDIX C

Regression Summary Outputs

161

Summary Output for 2004 Duncan SEI

95% CI

Coefficient P-Value LL UL

Intercept 22.45 0.0003 10.458969 34.434364 1998 Self-Esteem 0.41 0.0274 0.0452296 0.7654666



95% CI


Intercept 20.64 0.0024 7.3197761 33.950492 1998 Self-Esteem 0.40 0.0280 0.0438499 0.7644592 1998 Job Satisfaction 0.59 0.5388 -1.3040042 2.4931394


Summary Output for 2004 Income

95% CI


Intercept 1,945.73 0.6113 -5567.9042 9459.369 1998 Self-Esteem 460.57 0.0001 234.8573 686.28673



95% CI


Intercept 1,643.58 0.6992 -6704.3677 9991.5291 1998 Self-Esteem 460.37 0.0001 234.48305 686.26282 1998 Job Satisfaction 99.17 0.8701 -1091.1232 1289.4631


162


95% CI


Intercept (4.42) 0.3887 -14.476718 5.6402032 1998 Education 3.79 0.0000 2.8549016 4.7296655



95% CI


Intercept (9.10) 0.2046 -23.163114 4.9687913 1998 Education 3.71 0.0000 2.7614738 4.6654527 1998 Self-Esteem 0.17 0.3504 -0.1840048 0.5181805



95% CI


Intercept (11,259.09) 0.0005 -17541.149 -4977.0367 1998 Education 2,676.86 0.0000 2091.4163 3262.3084



95% CI


Intercept (19,599.29) 0.0000 -28343.726 -10854.85 1998 Education 2,536.36 0.0000 1944.5372 3128.1915 1998 Self-Esteem 297.84 0.0076 79.570599 516.10106


Documents

EXAMINING THE RELATIONSHIP BETWEEN SELF-ESTEEM AND EXTRINSIC CAREER SUCCESS AMONG NLSY79 YOUNG ADULT RESPONDENTS