To Marion E. Nichols · and also to Dr. Richard Ray for his assistance. I would like to express great thanks to DeDe Hughes and Julie Lyssy of the National Association of Women in

1

WORK-LIFE BALANCE AND ORGANIZATIONAL COMMITMENT OF WOMEN IN CONSTRUCTION IN THE UNITED STATES

By

E. KENT MALONE

A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT

OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA

2010

2

© 2010 E. Kent Malone

3

To Marion E. Nichols

4

ACKNOWLEDGMENTS

I would like to thank my supervisory committee for their guidance. I would like to

express a special note of appreciation and gratitude to Dr. Raymond Issa for his

direction and encouragement as my academic advisor and mentor. To Michael

Schwerin, PhD of RTI International, I would like to express appreciation for permission

and adaptive use of RTI‟s proprietary Quality of Life survey, as well as his guidance,

and also to Dr. Richard Ray for his assistance. I would like to express great thanks to

DeDe Hughes and Julie Lyssy of the National Association of Women in Construction for

their support and efforts, as well as all the NAWIC members from around the country

who participated in the survey. Finally, to Mrs. Marion E. Nichols, I extend my utmost

gratitude and appreciation for her interminable patience, support and encouragement.

5

TABLE OF CONTENTS page

ACKNOWLEDGMENTS .................................................................................................. 4

LIST OF TABLES ............................................................................................................ 7

LIST OF FIGURES ........................................................................................................ 11

ABSTRACT ................................................................................................................... 12

CHAPTER

1 INTRODUCTION .................................................................................................... 14

Need for Research .................................................................................................. 16 Main Research Focus ............................................................................................. 18 Research Questions ............................................................................................... 18

2 LITERATURE REVIEW .......................................................................................... 20

3 RESEARCH METHODOLOGY ............................................................................... 31

Survey Procedure ................................................................................................... 31 Survey Questionnaire ............................................................................................. 32 Regression Analyses .............................................................................................. 39 Development of the Predictive Models.................................................................... 40 Validation of the Predictive Models ......................................................................... 41

4 RESULTS ............................................................................................................... 43

Respondent Demographics and Employment Information ...................................... 43 Factor Analysis ....................................................................................................... 49 Cross-tabulations .................................................................................................... 60 Logistic Regression Analyses ................................................................................. 68

Analysis of Q1a ................................................................................................ 69 Analysis of Q2Ra .............................................................................................. 70 Analysis of Q12Ra ............................................................................................ 72 Analysis of Q15Ra ............................................................................................ 73 Analysis of Q28Ra ............................................................................................ 75 Analysis of Q29Ra ............................................................................................ 77 Analysis of Q30Ra ............................................................................................ 78 Analysis of Q31Ra ............................................................................................ 79

Open-Ended Questions .......................................................................................... 80

5 PREDICTIVE MODELS AND VALIDATION RESULTS FOR EMPLOYEE SATISFACTION AND INTENT TO STAY ............................................................... 93

6

Predictive Model for Satisfaction with Employer ..................................................... 96 Predictive Model for Short-term Employee Commitment ...................................... 100 Predictive Model for Long-term Employee Commitment ....................................... 105

6 CONCLUSIONS AND RECOMMENDATIONS ..................................................... 110

Research Questions and Findings ........................................................................ 111 Study Limitations .................................................................................................. 113 Future Research ................................................................................................... 115

APPENDIX

A SURVEY QUESTIONNAIRE ................................................................................ 117

B LISTING OF INDEPENDENT VARIABLES USED IN THE STEPWISE BACKWARD REGRESSION ANALYSES, INCLUDING ALL QUESTIONS IN THE COMBINED VARIABLES ............................................................................. 133

C VALIDATION TEST RESULTS FOR PREDICTIVE MODEL “SATISFACTION WITH EMPLOYER” .............................................................................................. 138

D VALIDATION TEST RESULTS FOR PREDICTIVE MODEL “SHORT-TERM EMPLOYEE COMMITMENT” ............................................................................... 140

E VALIDATION TEST RESULTS FOR PREDICTIVE MODEL “LONG-TERM EMPLOYEE COMMITMENT” ............................................................................... 141

LIST OF REFERENCES ............................................................................................. 143

BIOGRAPHICAL SKETCH .......................................................................................... 146

7

LIST OF TABLES

Table page 3-1 Questionnaire main section headings and related questions and question set

IDs. ..................................................................................................................... 33

3-2 Survey questions and question set lead-ins, question types, total counts and percentage of total survey responses. ................................................................ 34

3-2 Continued ........................................................................................................... 35

3-2 Continued ........................................................................................................... 36

4-1 Frequency table for Q21 “Which best describes the principal field of work you are in?” ............................................................................................................... 47

4-2 Frequency table for Q22 “Which best describes your occupation?” ................... 48

4-3 Frequency table for Q1 “How satisfied are you with your life overall?” ............... 50

4-4 Frequency table for Q2 “How satisfied are you with your life as an employee of your organization?” ......................................................................................... 51

4-5 Frequency table for question set Q5 “Please indicate how much you disagree or agree with the following statements about your life as a whole.” .................... 51

4-6 Frequency table for question set Q7 “How much to disagree or agree with the following statements regarding your current employer/organization?” ................ 52

4-7 Frequency table for question set Q8 “How satisfied are you overall in each of the following areas?” .......................................................................................... 53

4-8 Frequency table for question set Q9 “How satisfied are you with the following aspects of your job? (Part I: Job satisfaction)” .................................................. 54

4-8 Continued ........................................................................................................... 55

4-9 Frequency table for question set Q10 “How satisfied are you with the following aspects of your job? (Part II: Workplace issues) ................................ 55

4-10 Frequency table for question set Q11 “How satisfied are you with the following aspects of your health and health care?” with recoded IDs for partitioned question subsets for personal health, and personal medical and dental coverage, respectively. ............................................................................ 56

4-11 Frequency table for question set Q13 “How satisfied are you with the following aspects of your marriage or intimate relationship?” ............................. 57

8

4-12 Frequency table for question set Q14 “How satisfied are you with the following aspects of your relationship with your children?” ................................. 58

4-13 Frequency table for question set Q15 “What impact does each of the following areas of your life have on your desire to stay with your current employer?”.......................................................................................................... 59

4-14 Frequency table for question set Q16 “Please select the benefits your employer offers (even if you have declined the particular coverage or benefit.)” with recoded IDs for partitioned question subsets for medical, dental and retirement benefits, respectively. ...................................................... 60

4-15 Contingency table for question Q2 “How satisfied are you with your life as an employee of your organization?” and sub-question Q9-1 “How satisfied are you with your co-workers and peers?” ................................................................ 62

4-16 Contingency table for question Q2 “How satisfied are you with your life as an employee of your organization?” and sub-question Q9-7 “The degree of respect and fair treatment you receive from your superiors.” ............................. 63

4-17 Contingency table for question Q2 “How satisfied are you with your life as an employee of your organization?” and sub-question Q9-8 “The amount of challenge in your job.” ........................................................................................ 63

4-18 Contingency table for question Q2 “How satisfied are you with your life as an employee of your organization?” and sub-question Q9-9 “How satisfied are you with the feeling of accomplishment you get from your job?” ........................ 64

4-19 Contingency table for question Q2 “How satisfied are you with your life as an employee of your organization?” and sub-question Q9-11 “How satisfied are you with the ability to work independently?” ....................................................... 64

4-20 Contingency table for question Q2 “How satisfied are you with your life as an employee of your organization?” and sub-question Q9-15 “How satisfied are you with the amount of responsibility you have?” ............................................... 65

4-21 Contingency table for question Q2 “How satisfied are you with your life as an employee of your organization?” and sub-question Q10-1 “Workplace Issues: How satisfied are you with the physical environment where your work takes place?” ................................................................................................................ 66

4-22 Contingency table for question Q2 “How satisfied are you with your life as an employee of your organization?” and sub-question Q10-2 “Workplace Issues: How satisfied are you with the pace of your work?” ............................................ 66

4-23 Contingency table for question Q2 “How satisfied are you with your life as an employee of your organization?” and sub-question Q10-4 “Workplace Issues: How satisfied are you with the number of quick-response tasks?” ..................... 67

9

4-24 Contingency table for question Q2 “How satisfied are you with your life as an employee of your organization?” and sub-question Q10-6 “Workplace Issues: How satisfied are you with the availability of equipment/software?” ................... 67

4-25 Contingency table for question Q2 “How satisfied are you with your life as an employee of your organization?” and sub-question Q10-7 “Workplace Issues: How satisfied are you with the age of the equipment/software you use in your work?” ................................................................................................................. 68

4-26 Frequency table for Q32 “What are the five most satisfying aspects of working for your current employer?” ................................................................... 81

4-27 Frequency table for Q33 “What are the five least satisfying aspects of working for your current employer?” ................................................................... 83

4-28 Compilation and frequencies of open-ended responses to Q34 “What is the main reason that makes you want to stay with your current employer?” ............ 85

4-29 Compilation and frequencies of open-ended responses for Q35 “What is the main reason that would make you want to leave your current employer?” ......... 86

4-30 Compilation and frequencies of open-ended responses for Q36 “What is the one work-related program or policy that your employer could do to keep you in your current job?” ............................................................................................ 87

4-31 Compilation and frequencies of open-ended responses for Q37 “What is the one nonwork-related program or policy that your employer could do to keep you in your current employment?” ...................................................................... 89

5-1 Summary of the variables eliminated in the backward stepwise regression for model “Satisfaction with Employer” .................................................................... 97

5-2 Analysis of maximum likelihood estimates and predictor variables for model “Satisfaction with Employer.” .............................................................................. 98

5-3 Odds ratio estimates for model “Satisfaction with Employer.” ............................ 99

5-4 Summary of the variables eliminated in the backward stepwise regression for model “Short-term Employee Commitment.” .................................................... 101

5-5 Type 3 analysis of effects for model “Short-term Employee Commitment.” ...... 102

5-6 Analysis of maximum likelihood estimates and predictor variables for model “Short-term Employee Commitment.” ............................................................... 102

5-7 Odds ratio estimates for model “Short-term Employee Commitment.” ............. 104

10

5-8 Summary of the variables eliminated in the backward stepwise regression for model “Long-term Employee Commitment.” ..................................................... 106

5-9 Analysis of maximum likelihood estimates and predictor variables for model “Long-term Employee Commitment.” ................................................................ 107

5-10 Odds ratio estimates for model “Long-term Employee Commitment.” .............. 108

6-1 Summary of response variables that increased respondents‟ job satisfaction. . 111

6-2 Summary of response variables that affected respondents‟ organizational commitment and willingness to stay or leave the employer. ............................. 111

11

LIST OF FIGURES

Figure page 4-1 Frequency of responses for Q38 “What was your age on your last birthday?”

tabulated by age groups. (n=522) ...................................................................... 43

4-2 Respondents‟ age range and counts for each age. (n=522) .............................. 44

4-3 Frequency of responses for Q39 “What is your race?” (n=513) ......................... 45

4-4 Frequency of responses for Q40 “What is the highest level of education you have attained?” (n=518) .................................................................................... 45

4-5 Frequency of responses for Q41 “What is your marital status?” (n=517) .......... 46

4-6 Frequency of responses for Q42 “What is your spouse‟s employment situation?” (n=514)............................................................................................. 46

4-7 Frequency of responses for Q43 “Are there children age 21 or younger living in your household?” (n=516) .............................................................................. 47

4-8 Histogram of the closed and open-ended responses to Q32 “What are the five most satisfying aspects of working for your current employer?” (n=535) .... 82

4-9 Histogram of the closed and open-ended responses to Q33 “What are the five least satisfying aspects of working for your current employer?” (n=531) .... 84

4-10 Histogram of the open-ended responses to Q34 “What is the main reason that makes you want to stay with your current employer?” (n=485) .................. 85

4-11 Histogram of the tabulated open-ended responses to Q35 “What is the main reason that would make you want to leave your current employer?” (n=474) ... 87

4-12 Histogram of the tabulated open-ended responses to Q36 “What is the one work-related program or policy that your employer could do to keep you in your current job?” (n=427) ................................................................................. 88

4-13 Histogram of the tabulated open-ended responses to Q37 “What is the one nonwork-related program or policy that your employer could do to keep you in your current employment?” (n=382) ............................................................... 90

12

Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

WORK-LIFE BALANCE AND ORGANIZATIONAL COMMITMENT OF WOMEN IN

CONSTRUCTION IN THE UNITED STATES

By

E. Kent Malone

December 2010

Chair: R. Raymond Issa Major: Design, Construction and Planning

Existing research on work-life balance and organizational commitment covers

many industries in countries around the globe. Differences in culture, age, gender, job

type or field are often the bases of such studies. Although research on job satisfaction

and work-life balance of women in construction industries has emerged, these studies

have overwhelmingly focused on countries outside of the United States of America.

Therefore, this research focused on job satisfaction, work-life balance and

organizational commitment of women employed in the construction industry in the

United States. Research participants were solicited from the membership of a national

professional organization that is structured to promote and support the advancement

and employment of women in the construction industry.

The aim of this research was to identify variables that affect satisfaction with one‟s

job and employer, as well as overall intention to remain with that employer. Much of the

existing literature is limited to identifying variables that can attract women to jobs, not

necessarily retain them for a long career. The questions of whether job satisfaction

results in enhanced organizational commitment and intention to stay, or if the two

mutually exclusive were explored.

13

The results of the logistic regression analyses indicated a difference in the

commitment of women over different time intervals, as well as differences in satisfaction

with employer benefits when children under the age of 21 were living in the home. The

factors that lead to the most job satisfaction were good working relationships with co-

workers and peers, the degree of respect and fair treatment received from superiors,

the amount of challenge on the job, a feeling of accomplishment gained from the job,

and feeling valued as an employee. Factors that ranked highest in affecting an

employee‟s organizational commitment, were the degree of job-fit to the individual‟s

skills, flexibility and balance between work and personal time, the degree to which the

employee felt valued as an asset to the company/employer, and opportunities (or the

lack of) for advancement.

Finally, three predictive models were developed, tested for significance, and then

validated. The predictive models were “Satisfaction with Employer,” “Short-term

Employee Commitment” and “Long-term Employee Commitment.”

14

CHAPTER 1 INTRODUCTION

In late June, 2009, former General Electric Chief Executive, Jack Welch, drew

interest and criticism when he said, "There's no such thing as work-life balance," during

the Society for Human Resource Management's annual conference. He continued by

stating, "There are work-life choices, and you make them, and they have

consequences,” suggesting that women must make a choice between career

advancement or family interests, as if the two are mutually exclusive. Thus, a woman

who takes time off to raise children or tend to family needs will likely get passed over for

promotion or not be viewed as a team player. Is Welch‟s rather blunt statement simply

a harsh reality, or is there a little more to it than that?

First, we need to look at the term itself: work-life balance (WLB). What does it

mean? The term “balance” suggests there is a formula, or a “right answer” to the puzzle

of partitioning time, effort and attention and allocating the right proportion of each to the

different demands of life, resulting in equilibrium – just like children often attempt to

achieve on the playground teeter-totter. But we know that it is not that simple. We are

not robots that merely carry out a programmed series of tasks in cyclical repetition. Life

is dynamic, characterized by the inevitability of change and the challenge of adaptation

to it. Merrill and Merrill (2003) state that “the challenge is not „balance,‟ it is balancing;

creating the capacity to balance in the changing circumstances of life.” Our challenges

include finding time to do those things we want to do and those things we have to do.

Work, family, intimate relationships, money matters, friendships, leisure time, religious

commitments, etc. may play a role in our efforts to find synergy and balance in our lives.

As such, work-life balance is not a one-size-fits-all formula. It cannot possibly be

15

because we are all different in a countless number of ways. Perhaps it would be more

accurate to call it work-life integration as opposed to “balance”. Without getting too

bogged down in semantics, suffice it to say work-life balance entails a myriad of factors,

but only we can decide for ourselves if our lives are in or out of balance. Fortunately,

there are some common factors that seem to increase a person‟s work-life balance that

employers can control and at the same time, increase the employee‟s job satisfaction.

There have been a number of studies on work-life balance over the past few

decades and it continues to be a topic of great interest, inquiry, and debate. Data is

mounting that shows the lines of demarcation between work and home life has become

increasingly blurred. More companies are recognizing the value and importance of

work-life balance and are implementing policies and initiatives that promote work-life

balance. Certainly, this type of paradigm shift does not happen overnight, but at least

there is mounting evidence that our society is moving in that direction. However, the

philosophy of a company and the attitudes of its managers are paramount in effecting

such a shift and not all companies subscribe to such policies – yet, anyway. Surveys on

traditional gender-specific roles and attitudes about who is supposed to follow what role

in a household (e.g. man = breadwinner; woman = homemaker, nurturer) show distinct

differences between the generations. The attitudes toward traditional gender-specific

roles have shifted markedly in the younger generations as compared to the older baby

boomer and pre-baby boomer generations. While the older baby boomer and the pre-

baby boomer generations were much more inclined to have defined (even rigid)

attitudes toward gender roles, younger baby boomers and especially generation-Xers

were decidedly less inclined to pigeon-hole people according to “traditional” gender

16

roles. Many gen-Xers grew up with single mothers who juggled the task of being the

sole breadwinner and parent. Their perspectives, frames of reference and influences

are quite different from those who grew up three, four, and five decades earlier. The

family dynamic has changed dramatically over the decades, not to mention the social

and cultural influences from the media and entertainment.

Need for Research

Organizational commitment and employee turnover extends beyond WLB

initiatives alone. Synergy and balance between work, family, intimate relationships,

money matters, friendships, leisure time, religious commitments, etc. may play a role,

as well. While work-life balance and organizational commitment studies have been

conducted in various fields, including healthcare, business, and the military, as well as a

few in the construction industry, a review of the literature reveals that there simply have

not been any studies directed specifically toward women in the construction industry in

the United States. Therefore, the goal of this research is to begin to fill that void

As more employers look to adopt work-life balance initiatives, attention needs to

be paid to those initiatives that are the most effective. Previous studies on work-life

balance consistently reported the same types of initiatives being promoted, such as flex-

time, job sharing, alternative career paths, working from home (telecommuting),

compressed work weeks, maternity/paternity leave, time off for dependent care, and

various levels of child and elder care, including on-site or subsidized child or elder care.

But have they worked? Were some more effective than others? Furthermore, do these

initiatives have any effect on employees‟ organizational commitment and willingness to

stay with the employer? Interestingly, work-life balance initiatives are not universally

consistent in their effectiveness across the workforce spectrum. Not surprisingly,

17

perhaps, demands and work-life balance issues differ amongst industries. For example,

a nurse working shifts in a hospital faces different pressures and challenges than an

office manager at a Fortune 500 company. The differences in the working

environments, nature of work, and differing job schedules name just a few.

So what about women in construction and construction related jobs? Significant

amounts of money and effort goes toward recruiting people into the construction and

related industries. Major campaigns are launched annually by many employers, trade

organizations, and professional construction associations that work with local school

systems to educate and motivate K-12 students about the numerous trades and careers

associated with the construction industry. Likewise, numerous efforts are made at the

college level to attract new employees to careers in construction. Many state school

systems, major employers, construction associations, trade and professional

organizations such as Associated Builders and Contractors (ABC), Associated General

Contractors of America (AGC), the National Association of Home Builders (NAHB), and

the National Center for Construction Education and Research (NCCER), just to name a

few, sponsor or participate in national events and expositions at venues around the

country annually as a way to introduce tens of thousands of high school and college

students to a vibrant industry with a nearly insatiable demand for new talent.

But what about those employees already contributing in the construction industry?

What is being done to explore how to keep these employees engaged and committed to

their current employer, as well as serving as ambassadors and mentors to the next

generation of construction employees? From an industry perspective, not much, as a

review of the current literature indicates a focus more on employee attraction than

18

employee retention. Therefore, the existing body of literature on women in construction

related jobs in the United States must be expanded to include studies that identify

factors that not only enhance the employee‟s job satisfaction, but also motivate the

employee to perform well and foster a desire to stay with the employer for the long term.

Main Research Focus

Organizational commitment can be described as an employee‟s involvement with

and motivation for a particular employer. This commitment is characterized by a strong

belief in the goals and values of the organization and a willingness to exert considerable

effort on behalf of the organization, and a strong desire to maintain a working

relationship within the organization. Thus, a person‟s level of organizational

commitment is a reliable predictor of employee turnover. Therefore, the main focus of

this study was to identify work-life balance (WLB) issues and determine their effects on

a female employee‟s overall job satisfaction, organizational commitment and desire to

stay with a particular employer within the construction industry. This study also

attempted to identify WLB factors outside the scope of employer initiatives that enhance

or hinder organizational commitment and turnover intent for women in the construction

industry in the United States.

Research Questions

The aim of this study was to provide employers in the construction industry with

information designed to reduce the potential for turnover of female employees. To that

end, four research questions were analyzed in this study:

Are there identifiable relationships between levels of job satisfaction and overall life satisfaction among women in the construction industry?

Are there identifiable relationships between job satisfaction and employer benefits among women in the construction industry?

19

Are there identifiable demographic or non-work factors that affect employee satisfaction among women in the construction industry?

Is there enough data to construct a cost/benefit matrix?

The construction industry, as a whole, expends tremendous effort and money to

recruit new generations into the myriad of vocations and professions that comprise the

construction industry. However, dissatisfied employees who leave firms can be very

expensive to replace. The cost of reduced productivity during recruitment efforts (not to

mention the hard costs of recruitment itself), moving packages to entice distant

employees, training, and the overall loss of time can reach into the tens of thousands of

dollars for one vacant position. Therefore, finding ways to increase or sustain favorable

organizational commitment may be found by analyzing work-life balance issues and

identifying those factors that impact an employee‟s organizational commitment and

influence their decision to stay or to seek employment elsewhere.

20

CHAPTER 2 LITERATURE REVIEW

Since the end of World War II, the movement of women into the work force has

grown tremendously. In the 1940s, 3 out of 10 women contributed to the work force in

the United States, but during the late 1980s that number had moved to 7 out of 10

(Shank 1988). Presently, women account for nearly half of the U.S. labor force

(Whitmarsh, et al. 2007), but even as far back as 1970, women made up a large chunk

of the working population at just over 43% (U.S. Department of Health and Human

Services, Health Resources and Services Administration 2008). In 2006, women made

up 46.3% of the work force, and grew very slightly in 2007 to 46.4% (U.S. Bureau of

Labor Statistics 2008; Table 10), equal to the rate in 2003 (U.S. Department of Health

and Human Services, Health Resources and Services Administration 2005), indicating a

fairly stable proportion of the overall work force. These figures, however, do not show

the segmenting of jobs relative to “traditional” gender-based jobs or gender-neutral jobs.

The U.S. Bureau of Labor Statistics (BLS) (2008) reported employed persons by

detailed occupation and sex in 2007, and a quick scan shows those occupations which

are gender-based versus gender-neutral. Some examples of female-dominated

occupations (with the percentage of females representing the overall workers in that

occupation shown in parentheses) include dental hygienists (99.2%), preschool and

kindergarten teachers (97.3%), secretaries and administrative assistants (96.7%),

licensed practical and vocational nurses (93.2%), hairdressers, stylists and

cosmetologists (92.9%), bookkeeping, accounting and auditing clerks (90.3), and maids

and housekeepers (89.2%). Examples of gender neutral occupations (with the

percentage of females representing the overall workers in that occupation shown in

21

parentheses) include advertising sales agent (57.5%), real estate brokers and agents

(55.4%), bakers (54.1%), pharmacists (53.3%), retail salesperson (51.5%), computer

operators (51.1%), veterinarians (48.4%), and postsecondary teachers (46.2). Male-

dominated industries (with the percentage of males representing the overall workers in

that occupation shown in parentheses) include construction and extraction occupations

(97.3%), aircraft pilots and flight engineers (95.8%), fire fighters (94.7%), grounds

maintenance workers (94.1%), engineering managers (92.0%), construction managers

(91.9%), architecture and engineering occupations (85.6%), and clergy (84.9%).

Much of the existing literature on WLB (most of which occurred outside the United

States) is in nondescript “business” or “organization” fields or WLB as a psychological

factor in working men and women without reference to a specific field (e.g. Guillaume

and Pochic 2009; Emslie and Hunt 2009; and Greer 2002). A number of studies

illustrate the shift in the “traditional” family dynamic over the past few decades, wherein

the lines of demarcation between gender roles – those of breadwinner and family

care/nurturer – have become blurred to the extent of overlap, causing less distinction

between WLB issues for men and women. One longitudinal study (Nomaguchi 2009)

conducted in the United States between 1977 and 1997 exemplified the social,

demographic and cultural changes occurring in the U.S. as the family dynamic has

undergone metamorphic change on a number of levels, including single-parenthood and

an increasing proportion of women entering the workforce over the past few decades.

The findings of this study were similar to others (e.g. Winslow 2005) and identified four

trends contributing to the increase in work-family conflicts in recent years, as compared

to three decades ago. Compared to 1977, there has been an increase in women in the

22

labor force, an increase in the education levels of the workforce, more perceived

pressure to complete job tasks, and a decrease in personal time in favor of either paid

(work-related) and/or domestic activities of working parents. Although reporting a

pronounced overall increase in work-family conflicts, the Nomaguchi (2009) study

revealed three rather interesting trends (perhaps representative of a changing “sign of

the times”) that actually decreased work-family conflict. It was observed that parents

(specifically) felt an increase in “autonomy and meaningfulness in their jobs”, fathers

spent more time with their children, and parents were less defined by, or recognized

traditional gender roles as compared to 1977. To further support this apparent shift in

attitudes, a recent Finnish study (Forma 2009) found little differences in the effects of

WLB conflicts between men and women, and found the factors that contributed to

difficulties in reconciling work and family were not gender-specific. This study found

that “difficulties in reconciling work and family” were directly linked to decisions to seek

employment elsewhere, either to a different job or a different industry entirely, or

withdraw from the workforce altogether. These, like many other studies, are not

industry or profession-specific.

When specific professions or industries are examined, especially those that

traditionally have been, or still remain male-dominated, such as law, medicine or

engineering/construction there is a shift in WLB issues – or at least a shift in the way in

which these conflicts are handled – and they tend to be more gender-specific. For

example, women who achieved more career advancement in engineering were usually

single, childless or divorced – essentially sacrificing the traditional family in favor of

career advancement (Guillaume and Pochic 2009). The consensus of the literature on

23

WLB issues finds that promotions, whether of men or women are, in a large part,

connected to management‟s perception of a worker‟s “commitment” to their job by

putting work before all else. The engineering industry is known for long hours, inflexible

schedules, and often time spent away from home and is very slow to attract women, as

compared to medicine or law (Greed 2000). Interestingly, while the law profession is

also known for long hours, more women are attorneys than ever before. While slight

gender differences were identified between male and female attorneys, such as female

attorneys with children worked fewer hours than male attorneys, regardless of children

at home, attorneys on the whole worked long hours – either out of a sense of obligation

to justify high pay, an inner drive, or both (Wallace 1997). This study also reports

contrarian information related to common WLB factors affecting workers in other

industries or professions. Unlike other WLB studies, attorneys‟ “domestic situations are

not that important in contributing to feelings that work is invading the nonwork domain.”

Similar findings were reported in a later study (Forstenlechner and Lettice 2008), citing

a lack of interaction and appreciation by senior partners, and a lack of interesting work

as contributing to a lack of job satisfaction, with no significant differences between male

and female attorneys.

Clearly, there is still pronounced segmentation by gender within certain

occupations historically dominated by one sex or the other. While the BLS reported

women in construction and extraction occupations at 2.7%, women made up 9.4% of

the employed persons in the U.S. construction industry in 2007 (U.S. Bureau of Labor

Statistics 2008; Table 14). Nonetheless, at 46.4% of the work force in 2007, women still

represent a very small percentage of the work force in construction. The „construction

24

industry‟, as defined by the Employment Service (1990) in the U.K. is “…one that

employs workers in two main categories: (i) managers and professionals, who plan,

organize, advise on specialist functions or field activities, direct and coordinate all

activities and resources involved with construction operations, and (ii) construction

trades, who construct, install, finish, maintain and repair internal and external structures

of domestic, commercial and industrial buildings and civil constructions.” This definition

also fits within the scope of the construction industry in the U.S., but it should be noted

that the definition should include those employees in support roles, such as secretarial

and clerical, who also serve the construction industry.

According to existing literature with respect the male/female employment rates, the

construction industries in the U.S. and U.K. are fairly consistent with each other; even

when categorized according to occupations within the construction industry. One study

in the United Kingdom reported women making up 49.5% of the overall workforce, but

represented only 13% within the construction industry (Fielden et al. 2000). The role of

women in construction-related jobs tended to be more secretarial or clerical in nature

(Table 3-1). Despite the tremendous increases, percentagewise, of women in various

construction-related occupations, as well as a decrease in others from 1971 through

1991, the overwhelming majority of women in construction still tend to be in the capacity

of support staff (Fielden et al. 2000; Agapiou 2002).

There have been several studies in the U.S. and the U.K. to try to identify and/or

explain the cause or causes of the underrepresentation of women in the construction

industries in these countries (e.g. Agapiou 2002; Caven 2006; and Fielden et al. 2001).

25

One explanation may be that women simply do not have a history of employment in the

male-dominated construction industry (Watts 2007).

This study does not attempt to examine reasons for women‟s underrepresentation

in the construction industry, gender discrimination, or the presence or absence of

discrimination policies in the workplace, as other studies have focused on these. One

such study examined women and underrepresented minorities (URMs) in the

engineering and construction fields and the effect of subtle discrimination, which is often

more difficult to identify and address, yet it often leads to the employee leaving the firm

(Yates 2001). The focus of this study is to examine work-life balance and organizational

commitment from the perspective of the female employee in building construction in the

U.S. in an effort to identify a matrix of employer attitudes and/or actions and/or

employer-sponsored WLB initiatives and employee benefits, as well as non-work issues

that may increase or decrease a female employee‟s organizational commitment.

Although many companies sponsor WLB initiatives, some studies suggest they

may be a double-edged sword, essentially penalizing an employee for utilizing the very

initiatives designed to improve the employee‟s job satisfaction and organizational

commitment. In her Harvard Business Review article, Schwartz (1989) proposed two

classifications of women in the work force: „career-primary‟ and „career-and-family‟.

Career-primary are “women who perform as aggressively and competitively as men”

and are willing to make sacrifices in their personal lives in favor of making the most of

opportunities that promote career advancement; whereas career-and-family oriented

women, while still desirous of serious careers, are willing to sacrifice some

compensation and/or advancement as a tradeoff for more personal and family time

26

(Schwartz 1989). This proposal gave rise to the rather spirited „mommy track‟ debate,

wherein the utilization of family-friendly policies and making it to top management may

be regarded as mutually exclusive (Schwartz 1996). Several articles, which recently

followed Schwartz‟s 1989 publication, addressed this issue and found no clear evidence

supporting or rejecting the assertion of mutual exclusivity. One article in Newsweek

(Miller and Tsiantar 1991) reported family-work initiatives as “piece-meal” in their use

and that corporate response to the mommy track issue has been underwhelming, citing

a survey from New York-based Families and Work Institute, as well as a study from

Wright State University that showed that a woman was ten times more likely to lose her

job from taking maternity leave than for other types of medical leave. One company,

Corning, found that despite the existence of family-friendly policies, few employees

actually utilized them. Van Campbell, the vice-chairman of Corning stated “They (the

employees) tell us they think it‟s too risky; they‟re concerned that they won‟t be viewed

as serious” (Miller and Tsiantar 1991). Interestingly, the same article reported turnovers

at Corning to be reduced by half after the implementation of family-friendly policies.

Since then, empirical research has probed the issue of WLB initiatives, their use, effects

and consequences. Several studies, including a Fortune 500 engineering firm (Perlow

1995), female university faculty (Finkel, et al. 1994) and a study of 80 major U.S.

corporations (Galinsky et al. 1993) consistently reported employees‟ reluctance to utilize

WLB initiatives because they feared a negative impact on their long-term success and

advancement possibilities with their employer would result. Subsequent studies,

however, demonstrated that employees are more willing to utilize employer-sponsored

WLB initiatives when they are made aware of such initiatives and management actively

27

supported such initiatives; which in turn, raised employee commitment and reduced

turnover intention (Thompson et al. 1999; Smith and Gardner 2007).

While these prior studies provide an overall historical perspective with respect to

businesses in general and the attitudes and affects of the employer and employee, the

focus of this study is not to attempt to compare or contrast work-life balance and

organizational commitment across genders, nor does it assume the factors that may

enhance or hinder a female employee‟s organizational commitment in the construction

industry are gender-exclusive. Other studies have compared the utilization of WLB

initiatives and found that more women utilize WLB initiatives than men (Smith and

Gardner 2007) as well as more working parents than non-parents (Thompson et al.

1999), and that women with children are more disadvantaged with respect to

advancement (Burke 1999). This study will, however, provide a point of reference by

which to compare prior studies and/or make future evaluations by providing data

derived exclusively from a female population in construction-related occupations in the

U.S. as of the date of the survey.

Research suggests that the most successful organizations will be those who

recognize that top talent comes in both genders and acknowledge women as important

contributors and work to develop their skills and talents (Schwartz 1989; Hewlett and

Luce 2005). Studies conducted in the late 1970s and 80s still reported traditional

attitudes and mindsets that are completely gender-oriented; the idea that men are the

breadwinners and their wives should be in a supportive role, responsible for household

and familial duties, thus allowing the man to devote his concentration on achieving

success in the workplace (Kanter 1977; Weiss 1990). Although the number of

28

traditional families has certainly decreased since the 1950s and 60s with more married

women and single parents entering the work force, the traditional societal attitudes of

the male breadwinner still exist and are rewarded. A study of M.B.A. holders in

management positions in the early 1990s found a difference in income between

traditional family men (those whose spouses were not employed) and post-traditional

family men (those whose spouses were employed), and single men (Schneer and

Reitman 1993). No difference in pay was observed between married and single

women. Schneer and Reitman (1993) reported that traditional family men earned 20%

more than post-traditional or single men, suggesting that societal expectations on

gender roles at work and home are still that of “men acquiring human capital to provide

for a family, wives helping their husbands, and men following socially acceptable

patterns.” Burke (1997), like many other studies, found consistency in the beliefs of

married women with children in that they could have a more successful, upwardly

mobile career at the expense of child or familial obligations, or a more stagnated career

overshadowed by children and/or family obligations – essentially affirming Schwartz‟s

(1989) implication that women‟s career and family aspirations are inherently mutually

exclusive.

Are the tides turning on these traditional gender-prescribed work and family roles

from the perspective of employers and managers, as well as employees? A review of

the literature suggests, yes, albeit at a slow and inconsistent pace across industries.

Moreover, the philosophy of a company and the attitudes of its managers are

paramount. Over the past two decades, there has been an increase in awareness and

as a result, an increase in studies related to work-life balance, organizational

29

commitment, and employee turnover intention. Previous studies on WLB initiatives

consistently reported the same employer initiatives such as flex-time, job sharing,

alternative career paths, working from home (telecommuting), compressed work weeks,

maternity/paternity leave, time off for dependent care, and various levels of child and

elder, including on-site or subsidized child or elder care (e.g. Smith and Gardner 2007;

O‟Neil et al. 2008). The construction industry, on the whole, experiences a large degree

of turnover. “The industry supersectors (according to the North American Industry

Classification System) with the highest annual rates, on average between 2001 and

2004, were arts, entertainment and recreation; accommodations and food services;

construction; and retail trade” (Stephens 2005). In 2001, the construction industry

experienced a non-seasonally adjusted quit rate of 27.4% and in 2004, only a slight

reduction at 25.2% (Stephens 2005).

Organizational commitment and employee turnover extends beyond WLB

initiatives alone. Synergy and balance between work, family, intimate relationships,

money matters, friendships, leisure time, religious commitments, etc. may play a role,

as well. While work-life balance and organizational commitment studies have been

conducted in various fields, including healthcare, business, and the military, as well as a

few in the construction industry, a review of the literature reveals that there simply have

not been any studies directed specifically toward women in the construction industry.

Therefore, the goal of this research was to begin to fill that void. A matrix of cost/benefit

items was created based on observed responses identifying the employer-sponsored

WLB initiatives that provide the maximum increase in organizational commitment and

reduce turnover intent at the least cost to the employer, as well as those that represent

30

a significant cost, but have little impact on employees‟ commitment or turnover intent.

Identifying WLB factors outside the scope of employer initiatives that enhance or hinder

organizational commitment and turnover intent were examined, as well.

31

CHAPTER 3 RESEARCH METHODOLOGY

In late 2008, an Internet-based organizational climate survey was opened to

members of the National Association of Women in Construction (NAWIC); a

professional organization of nearly 5,000 members and comprised exclusively of

women in construction and related fields. The goal of the survey was to better

understand how various factors in the respondent‟s life impact satisfaction with work

and life. Instead of simply asking about the respondent‟s satisfaction with their job,

supervisor/manager, and employer, the survey included other aspects of life that are

likely to affect the respondent‟s work, as well as life outside of work. As such, the

survey was purposefully candid and probative in an effort to produce the most

substantive and accurate results.

Survey Procedure

To promote awareness about the survey and encourage participation, NAWIC

administrators announced the survey to their members in two newsletters, as well as at

the organization‟s annual conference in the fall of 2008, just prior to the launch of the

survey. To help ensure respondents‟ privacy, as well as facilitate data collection, the

survey was Web-hosted by Qualtrics, Inc., an online survey host. When the survey was

opened in late November, 2008, each NAWIC member received a link to the survey site

in an email sent out by NAWIC‟s home office. To help further ensure respondents‟

privacy, the membership listserv was not shared with any person or entity outside

NAWIC. No person or entity associated with this study received a list of the members‟

names or individual email addresses. The survey did not ask for any personally

identifiable information, and respondents‟ computer IP addresses were not maintained.

32

Based on the results of pre-testing, the survey took between 20 and 30 minutes,

on average, to complete and survey site statistics reported a trimmed mean of 23

minutes. Respondents were permitted to logoff the survey and return to complete it

later; however, no previously reported information could be accessed or changed. The

survey was closed early January 2009. It was reported by a NAWIC administrator that

4,185 emails with the link to the survey had been sent to members requesting their

participation. The total number of respondents was 744, nearly 18% of the email

recipients.

Survey Questionnaire

The survey questionnaire used in this study was adopted from a lengthy, validated

survey developed by a private consulting firm in the United States that is used to assess

the satisfaction of members of each branch of the U.S. military. Written permission was

obtained to use this proprietary survey and adapt it to this specific study. After careful

evaluation of each section and question, the researcher eliminated certain questions

and modified others, as well as arranging the order of each question section to fit the

context of this study‟s population. A copy of the adapted survey was downloaded from

the survey host website, Qualtrics, and is attached as Appendix A. It was downloaded

in an un-modifiable format and attached as a JPG image, so the corresponding question

IDs assigned to each question and question set are missing. However, the question IDs

referred to in this study follow the same sequence as the questions presented in the

survey. Another limitation of the downloaded format is the exclusion of variables listed

in drop-down menus in the online survey. As such, some of the questions toward the

end of the survey appear not to have any response options.

33

The survey consisted of eleven major sections (Table 3-1): Global Quality of Life,

Organizational Commitment, Life Domain Satisfaction, Life Domain Aspect Satisfaction,

Life Domain Impact on Commitment, Employer Benefits Impact, Employment

Information, Retention Intent, Employer Attractiveness, Your Thoughts, and

Demographic Information. Several sections were broken down in to subsections, which

asked very detailed information. The terms “employer,” “organization,” and “company”

were used interchangeably throughout the survey and are, likewise, used

interchangeably in this study. There were a total of 139 response items using Likert-

Table 3-1. Questionnaire main section headings and related questions and question set IDs.

Section Number Section Heading Related Questions/Question Sets

1 Quality of Life Q1–Q6 2 Organizational Commitment Q7 3 Life Domain Satisfaction Q8

4 Life Domain Aspect Satisfaction Q9–Q14

5 Life Domain Impact on Retention (Commitment) Q15

6 Employer Benefits Impact Q16–Q18 7 Employment Information Q19–Q27 8 Retention Intent Q28–Q31 9 Employer Attractiveness Q32–Q33 10 Your Thoughts Q34–Q38 11 Demographic Information Q39–Q43

type, semantic differential scale, open-ended, closed-ended with both single and

multiple-answers, and dichotomous questions. Table 3-2 lists the question ID and

corresponding question or lead-in question for the question sets, but not the entire

survey questionnaire. The full ranges of response items within the question sets are not

included in the table. However, Table 3-2 can be compared to the full survey

questionnaire in Appendix A.

34

Table 3-2. Survey questions and question set lead-ins, question types, total counts and percentage of total survey responses.

ID Question/Question Set Type Count (%)

Q1 How satisfied are you with your life overall?

Semantic Differential

719 (96.64%)

Q2 How satisfied are you with your life as an employee of your organization?


707 (95.03%)

Q3 How do you feel about your life at the present time?


709 (95.3%)

Q4 Which point on this scale best describes how you feel about your life as a whole at this time?


707 (95.03%)

Q5 Set

Please indicate how much you disagree or agree with the following statements about your life as a whole.

Likert 686 (92.2%)

Q6 Think of a friend that you know well and who is about your age. How does your life compare to your friend‟s?


680 (91.4%)

Q7 Set

How much do you DISAGREE or AGREE with the following statements regarding your CURRENT employer/organization?

Likert 649 (87.23%)

Q8 Set

How satisfied are you OVERALL in each of the following areas?


643 (86.42%)

Q9 Set

How SATISFIED are you with the following aspects of your job? (Part I: Job Satisfaction)


623 (83.74%)

Q10 Set

How SATISFIED are you with the following aspects of your job? (Part II: Workplace Issues)


608 (81.72%)

Q11 Set

How SATISFIED are you with the following aspects of your Health and Health Care?


605 (81.32%)

Q12 How SATISFIED are you with the amount of leisure time you have?


602 (80.91%)

Q13 Set

How SATISFIED are you with the following aspects of your Marriage/Intimate Relationship?


594 (79.84%)

Q14 Set

How SATISFIED are you with the following aspects of your Relationship with your Children?


588 (79.03%)

Q15 Set

What impact does each of the following areas of your life have on your desire to stay with your CURRENT employer?


564 (75.81%)

35

Table 3-2. Continued


Q16 Set

Please select the benefits your employer offers (even if you have declined a particular coverage/benefit).

Closed-ended multiple answer

549 (73.79%)

Q17 Given that many employer-sponsored health care benefits require an employee contribution toward the cost of the coverage, how would you rate the FAIRNESS of your required contribution against the QUALITY of your employer-sponsored health care benefits?

Closed-ended 545 (73.25%)

Q18 What is the ONE benefit you would like your employer to provide that is NOT currently offered to employees?

Open-ended 482 (64.78%)

Q19 How many years have you been working in the construction industry (or a construction-related field)?


Q20 How many years have you worked at your CURRENT place of employment?


Q21 Which best describes the principal FIELD of work you are in?


Q22 Which best describes your OCCUPATION?


Q23 In terms of number of employees, how large is your current employer?


Q24 In terms of annual dollar volume/productivity, how large is your current employer?


Q25 How many days total have you been away from home during the last 12 months on a work-related assignment?


Q26 Were you promoted within the past 12 months?


Q27 Are you required to work overtime? Closed-ended 529 (71.1%)

Q28 How likely is it that you will stay with your CURRENT employer, at least until you are eligible to retire?


529 (71.1%)

Q29 How likely is it that you will remain with your current employer SIX MONTHS from now?


529 (71.1%)

Q30 How likely is it that you will remain with your current employer TWELVE MONTHS from now?


522 (70.16%)

36

Table 3-2. Continued


Q31 How likely is it that you will remain with your current employer FIVE YEARS from now?


527 (70.83%)

Q32 What are the five MOST satisfying aspects of working for your current employer?

Rank Order Multiple Choice w/Open-ended

535 (71.91%)

Q33 What are the five LEAST satisfying aspects of working for your current employer?

Rank Order Multiple Choice w/Open-ended

531 (71.37%)

Q34 What is the MAIN REASON that makes you want to STAY with your current employer?

Open-ended 485 (65.19%)

Q35 What is the MAIN REASON that would make you want to LEAVE your current employer?

Open-ended 474 (63.71%)

Q36 What is the one WORK-RELATED program or policy that your employer could do to keep you in your current employer?

Open-ended 427 (57.39%)

Q37 What is the one NONWORK-RELATED program or policy that your employer could do to keep you in your current employer?

Open-ended 382 (51.34%)

Q38 What was your age on your last birthday?


Q39 What is your race? Closed-ended 518 (69.62%)

Q40 What is the highest level of education you have attained?


Q41 What is your marital status? Closed-ended 517 (69.49%)

Q42 What is your spouse's employment situation?


Q43 Are there children age 21 or younger living in your household?

Dichotomous 516 (69.35%)

The first section, Global Quality of Life, asked questions related to overall

satisfaction with the respondent‟s life and also as an employee of their organization.

Response choices ranged from very dissatisfied to very satisfied, coded 1 through 5

respectively, with 3 representing a neutral response. The same scale was applied to

questions with response choices ranging from strongly disagree to strongly agree.

37

The second section, Organizational Commitment, asked several questions about

how much respondents agreed or disagreed with statements concerning their feelings

toward their employer. Questions such as the respondent‟s sense of belonging and

willingness to spend the rest of their career with their current employer had response

choices ranging from strongly disagree to strongly agree, coded 1 through 5

respectively, with 3 being neutral.

Quality of life is influenced by a number of factors, such as one‟s job, how work

and non-work facets of life overlap, friendships, personal relationships, and others.

Section three, Life Domain Satisfaction, asked how satisfied or dissatisfied respondents

were with various aspects of their life, such as their current job overall, work-life

balance, personal health, standard of living, relationships with friends and family, as well

as intimate relationships. Response choices ranged from very dissatisfied to very

satisfied, coded 1 through 5 respectively, with 3 being neutral. The response choices

also included “does not apply.”

Section four, Life Domain Aspect Satisfaction, consisted of four subsections: Job

Satisfaction, Workplace Issues, Health Care (medical and dental), Marriage/Intimate

Relationships, and Relationships with Children. Response choices ranged from very

dissatisfied to very satisfied, coded 1 through 5 respectively, with 3 being neutral. The

response choices also included “does not apply.”

Section five, Life Domain Impact on Commitment, used the same variables,

response choices and coding as section three, Life Domain Satisfaction, but asked

about how the various aspects that impact the respondent‟s life impact their desire to

stay with or leave their organization. It is often the case that a person may be satisfied

38

or dissatisfied with a particular aspect of their life, but it has very little impact on their

satisfaction with their job or their desire to stay with or leave an organization. These

questions are used to better understand which factors may influence employees‟ plans

to stay with or leave an organization.

Section six, Employer Benefits Impact, consisted of a set of dichotomous

questions. Respondents were provided a list of employer benefits, which included

preventive care, major medical coverage, prenatal and maternity care, prescription

coverage, chiropractic care, psychological/emotional care, dental coverage, and three

types of retirement/profit-sharing plans. Respondents were asked to select yes or no to

the question of whether each type of benefit was offered by the employer; even if the

respondent did not opt for a particular benefit.

Sections seven through nine, Employment Information, Retention Intent, and

Employer Attractiveness used single-answer, multiple-answer, and dichotomous

questions. Employment Information contained questions regarding the respondent‟s

length of time with their current employer, length of time in the construction industry,

size of the organization in terms of annual dollar volume/productivity, size of the

organization in terms of number of employees, the respondent‟s principle field of work,

as well as occupation. Retention Intent contained questions assessing the respondent‟s

attitude toward their desire to remain with their employer over various time intervals;

thus, their overall commitment to the organization. In this context, Retention Intent, is

better termed “Commitment,” so the factors that affect an employee‟s desire to remain

with their current employer will be referred to as Employee Commitment.

39

Section ten, Your Thoughts, consisted of free-response, short answer questions.

They included asking respondents to state the main reason that makes them want to

stay with their employer, as well as the main reason that would make them want to

leave. Respondents were asked to state one work-related program or policy that their

employer could do or implement to keep them in their current job. Respondents were

also asked to state one nonwork-related program or policy the employer could do or

implement to keep them in their job.

The last section, eleven, was Demographic Information wherein respondents were

asked to report their age, race, highest level of education attained, marital status,

spouse‟s employment status, and if children under the age of 21 lived in the home.

Since the survey was distributed only to current members of NAWIC, the sample

population was made up exclusively of women.

Regression Analyses

Questions that were selected as dependent variables were recoded from scaled

responses to binary and include “R” in the question IDs. Very satisfied and satisfied

responses were combined and coded as 1. Very dissatisfied and dissatisfied were

combined and coded as 0. Neutral and "does not apply" responses were coded as

missing. All questions that were converted to binary scores for use in regression

analyses followed the same protocol with 0 used as the negative response and 1 used

as the positive response. The first regression models using this recoded data indicated

too many missing cases. The way this issue was resolved was to include the neutral

responses with the positive responses; the logic being that the respondent is either

dissatisfied or not dissatisfied. Therefore, responses that were not dissatisfied, or not

otherwise negative, were coded as 1. Since the recoding of scaled variables to binary

40

variables was already done, albeit, having omitted the neutral responses, each of these

was modified to include the neutral responses. The question IDs then gained an “a” to

denote the inclusion of neutral responses along with positive responses for that

question or question set. For example, Q2 recoded to binary, but omitting the neutral

responses was labeled Q2R. Q2R modified to include the neutral responses in the

binary recodes was labeled Q2Ra. The only exception to recoding was with “does not

apply” or “I don‟t know” responses. They were still coded as missing, although the

frequency of these responses for each questions used in the regression models was

low.

Development of the Predictive Models

Logistic regressions were run on the independent variables that appeared to have

the most relevance to the dependent variables “satisfaction with the employer”, “long-

term intention to stay with the employer” and “short-term intention to stay with the

employer.” Statistical Analysis Software (SAS) version 9.2 was used to run the

regression analyses to determine if any of the independent variables were significant

predictors of satisfaction for each of the dependent variables. A series of stepwise

backward regressions, using the PROC LOGISTIC analysis in SASv9.2, were

conducted on each set of predictor variables. Each run of the analyses produced a

table showing the “Analysis of Maximum Likelihood Estimates.” Those variables with

the highest Pr > ChiSq values (probability Chi square), indicating the least likely fit to the

predictive model were systematically eliminated. These backward eliminations of least-

predictive variables continued until the “Analysis of Maximum Likelihood Estimates”

identified a set of variables with distinct predictor chi square values at or below the

alpha level of 0.05.

41

A confidence level of 95% (p≤0.05) was selected for the statistical analyses.

However, in most of the logistic regression analyses conducted it was observed that Pr

> ChiSq values were either below 0.10 or above 0.20, indicating variables either had a

fairly strong predictive value or not, relative to p≤0.05. The variables identified as

predictors in each predictive model are discussed in Chapter 4. Some of the analyses

reported in Chapter 4 include Pr > ChiSq values ≤0.10, which correspond to a 90%

confidence level. While these are not statistically significant at the selected 95%

confidence interval, they are included in this study to identify those variables that

indicated a trend toward significance at the 95% confidence level, which may be useful

in future studies.

Validation of the Predictive Models

The final predictive models were developed from ideal predictor variables with

observed Pr > ChiSq values ≤ 0.05, which satisfied the 95% confidence level. Each

predictive model was then evaluated for significance. Model significance was confirmed

when the Likelihood Ratios from the cross-validation analysis were p≤0.05, representing

significance at the 95% confidence level. Predictive models were considered valid

when the independent data set (or validation set) resulted in 80% or more fit to the

model.

Roughly 80% of the data were randomly selected for the predictive model training

set and used in the cross-validation process. The remaining 20% were set aside as the

validation set for testing the predictive model. The training set was cross-validated

using SASv9.2. The cross-validation was conducted using the “leave-one-out” principle

(LOOCV in SAS) because this method is best suited to smaller data sets, such as those

in this study. Model significance was confirmed when the Likelihood Ratios from the

42

cross-validation analysis were p≤0.05, representing significance at the 95% confidence

level. Predictive models were considered valid when the independent data set (or

validation set) resulted in 80% or more fit to the model. This means that for any given

predictive model, it would accurately predict the outcome at least 80% of the time.

43

CHAPTER 4 RESULTS

The aim of this study is not simply to try and identify factors that might be

predictors of job satisfaction of women in building construction fields in the United

States, but also to attempt to identify factors that increase the worker‟s desire to stay

with her employer. Furthermore, this study seeks to determine if high job satisfaction

and organizational commitment are correlated, such that high job satisfaction may be a

predictor of commitment, or if the two are mutually exclusive. To this end, several types

of data analyses were performed, as well as the reporting of frequency data and

summary statistics.

Respondent Demographics and Employment Information

Respondents‟ ages ranged from 21 years of age to 75 years of age, with a mean

of 44.5 years. The responses were categorized according to age group and the

response frequencies are shown in Figure 4-1. The actual counts by age are shown in

Figure 4-2.

Figure 4-1. Frequency of responses for Q38 “What was your age on your last birthday?” tabulated by age groups. (n=522)

44

Figure 4-2. Respondents‟ age range and counts for each age. (n=522)

45

Nearly 90% of respondents to the question of race reported their race as white,

while fewer than 4% were Hispanic/Latino, and only 1.5% were African American

(Figure 4-3).

Figure 4-3. Frequency of responses for Q39 “What is your race?” (n=513)

Nearly a third of the respondents reported having some college, and another third

had bachelor‟s degrees. The third highest reported level of education (13.9%) was an

AA or AS degree (Figure 4-4).

Figure 4-4. Frequency of responses for Q40 “What is the highest level of education you have attained?” (n=518)

46

Figure 4-5 shows that over 57% of those responding to the question of marital

status were married, 21% were single, with the remainder reporting being separated,

divorced or widowed.

Figure 4-5. Frequency of responses for Q41 “What is your marital status?” (n=517)

The majority of respondents reported either having a spouse that worked full-time

or no spouse in the household (Figure 4-6).

Figure 4-6. Frequency of responses for Q42 “What is your spouse‟s employment situation?” (n=514)

47

Over two-thirds of the respondents reported having no children under the age of

21 residing in the home (Figure 4-7).

Figure 4-7. Frequency of responses for Q43 “Are there children age 21 or younger living in your household?” (n=516)

Respondents were asked to report on their employment information; both their

field of work, as well as their occupation. Over 21% of the respondents reported

working in the building construction/contracting or general contracting fields (Table 4-1).

Table 4-1. Frequency table for Q21 “Which best describes the principal field of work you are in?”

(n=534) Frequency

Architecture

2.62%

Banking/Finance/Lending

1.50%

Building Construction/Contracting (office, retail, multi-family, etc.) 6.93%

Civil Engineering

1.87%

Construction Engineering

3.18%

Construction Management

16.48%

Construction Safety

1.87%

Design/Build

1.31%

Education

2.43%

General Contracting

14.61%

Heavy/Civil/Highway Construction

3.37% Industrial Construction (power generation, petrochemical plants, manufacturing plants, etc.) 1.50%

Residential (detached) Construction

2.25%

Sales/Leasing/Property Management 1.69%

Specialty Contractor (HVAC, plumbing, electrical, etc.) 13.67%

Other (not listed) 24.72%

48

Nearly 16.5% of the respondents reported working in the construction management field

and 13.7% reported working in specialty contracting fields, such as HVAC, plumbing

and electrical. Table 4-2 lists the types of occupations respondents reported having.

Table 4-2. Frequency table for Q22 “Which best describes your occupation?”

(n=538) Frequency

Administrative Support

10.59%

Architect

1.67%

Association Personnel

1.12%

Attorney/Paralegal

0.74%

Bonding/Insurance

1.86%

Bookkeeping/Accounting Clerk 6.13%

Consultant

1.30%

Contract Management

3.16%

Customer Service

0.93%

Data Operations/MIS

0.56%

Designer

2.04%

Engineer

1.67%

Environmental

0.19%

Estimator/Purchaser

2.42%

Executive

4.65%

Finance/Banking

0.56%

Human Resources/Recruiters 3.35%

Inspector

0.19%

Instructor

0.56%

Lending/Credit Management 0.19%

Marketing/Business Development 4.28%

Materials Supplier/Vendor

0.37%

Office Management

12.08%

Owner

6.88%

Project Coordinator

4.09%

Project Engineer

1.67%

Project Management

7.81%

Realty/Property Management/Leasing Agent 0.37%

Safety

2.04%

Sales/Account Executive

4.28%

Student

0.19%

Superintendent/Director

0.74%

Tradeswoman

4.65%

Other (not listed) 6.69%

49

Nearly 23% reported being employed in office management or administrative support

occupations and 13.6% reported working in project management, project coordinator or

project engineer positions. Nearly 7% were owners of their own business and 4.7% of

those responding reported being a tradeswoman.

Factor Analysis

Since the survey contained a large number of response items (139 in all) within

the eleven main sections, it was necessary to conduct a factor analysis to curtail the

possibility of a multicollinearity error in the regression models. The factor analysis also

helped identify questions and sub-questions within question sets that may exhibit high

correlations; either between main questions or within a particular question set. Since a

Pearson Correlation Coefficient of 1 indicates perfect correlation and a Pearson

Correlation Coefficient of 0.000 indicates no correlation whatsoever, questions with very

high Pearson Correlation Coefficient levels (≥0.80) were either combined into a distinct

new variable or one of the questions was eliminated altogether. Sub-questions within

question sets were also reviewed for Pearson Correlation Coefficient levels of 0.80 or

higher. Those with high correlations were either combined into a new response variable

or one of the questions was eliminated altogether. Sub-questions displaying decidedly

low Pearson Correlation Coefficients (

50

response frequencies were still examined for all questions and question sets. Individual

questions Q3, Q4, Q6, Q17, Q24, Q25, Q26 and Q27 were eliminated due to high

correlations with other questions or poor fit. Q24 was omitted from analysis because of

a high frequency of “I don‟t know” responses. Although this question had a response

rate of 71.64%; over 22% of those responding to the question responded “I don‟t know”.

The frequency of responses for the questions and question sets ranging from Q1

through Q16 that were retained for use in analyses are shown in Tables 4-3 through 4-

14.

The first survey question, Q1 “How satisfied are you with your life overall?”

resulted in a low proportion of respondents to that question reporting dissatisfaction

(Table 4-3). The combined frequencies for those who reported being either dissatisfied

Table 4-3. Frequency table for Q1 “How satisfied are you with your life overall?” (n=719) Frequency

Very Dissatisfied 2.64%

Dissatisfied 5.70%

Neutral 11.96%

Satisfied 53.82%

Very Satisfied 25.87%

or very dissatisfied was 8.34%, while those who were not dissatisfied (including neutral

responses) had an overall frequency of 91.65%.

The frequency distribution for the second survey question Q2 “How satisfied are

you with your life as an employee of your organization?” is shown in Table 4-4.

Although there were slightly fewer respondents to question Q2 as compared to question

Q1 (1.70%), the frequency of negative responses was proportionally higher than

question Q1 and the frequency of satisfied responses shifted slightly toward neutral.

51

Table 4-4. Frequency table for Q2 “How satisfied are you with your life as an employee of your organization?”

(n=707) Frequency

Very Dissatisfied 3.82%

Dissatisfied 8.77%

Neutral 16.41%

Satisfied 47.24%

Very Satisfied 23.76%

Question sets Q5 through Q15, exclusive of sets Q6 and Q12, were combined to

create new response variables labeled Q7_C through Q15_C, respectively (Tables 4-6

through 4-14). The “_C” in the question ID denotes a combined variable. Sub-

questions within a set were eliminated, as warranted, in creating the new combined

Table 4-5. Frequency table for question set Q5 “Please indicate how much you disagree or agree with the following statements about your life as a whole.”

ID Question Strongly Disagree

Disagree Neither Agree nor Disagree

Agree Strongly Agree

n

Q5-1 In most ways, my life is close to ideal

2.49% 16.08% 25.29% 46.35% 9.80% 684

Q5-2 The conditions of my life are excellent

1.90% 19.12% 27.30% 40.73% 10.95% 685

Q5-3 I am satisfied with my life

0.73% 10.98% 15.08% 58.27% 14.93% 683

Q5-4 So far, I have gotten the important things I want in life

1.47% 11.14% 16.86% 52.05% 18.48% 682

Q5-5* If I could live my life over, I would change almost nothing

5.99% 36.35% 18.39% 29.20% 10.07% 685

Note: Question IDs with an asterisk (*) were omitted from the analyses.

variables. The frequency of responses to the sub-set of questions for Q5 “Please

indicate how much you disagree or agree with the following statements about your life

as a whole” are listed in Table 4-5. The responses were combined to create a new

variable Q5_C “Global Quality of Life.” Question Q5-5 was considered redundant and

eliminated, as indicated by the asterisk (*) in the question ID.

52

Table 4-6 shows the complete subset of questions for Question Q7 “How much to

disagree or agree with the following statements regarding your current

employer/organization?” Each of these re

Documents

To Marion E. Nichols · and also to Dr. Richard Ray for his assistance. I would like to express great thanks to DeDe Hughes and Julie Lyssy of the National Association of Women in