Does It Drive Employee Engagement and Reduce Turnover Intention? Jennifer C

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Fulfillment of the employee psychological contract in a healthcare system: Does it drive employee engagement and reduce turnover intention?

Jennifer C. Bonilla

A dissertation submitted to the graduate faculty

in partial fulfillment of the requirements for the degree of

DOCTOR OF PHILOSOPHY

Major: Hospitality Management

Program of Study Committee: Bob Bosselman, Co-major Professor Eric D. Olson, Co-major Professor Brad Shrader SoJung Lee Joan Su

The student author, whose presentation of the scholarship herein was approved by the program of study committee, is solely responsible for the content of this dissertation. The Graduate College will ensure this dissertation is globally accessible and will not permit alterations after a degree is conferred.

Iowa State University

Ames, Iowa

2018

DEDICATION

I would like to thank my personal network and my family for supporting me during my two years of intensely devoted study.

To my mom, whom I can thank for always setting the bar high and inspiring me to believe that I could be a CEO or anything else my heart desired. To my husband of 25 years, Victor, and our daughters, Stephanie, Lindsay, and Emma: I know that I have been distant, stressed, and mostly unavailable while juggling the pursuit of a full-time graduate degree and a full-time administrative faculty role, with the latter tasking me to launch a new executive graduate program for UNLV and obtain first-time program accreditation.

Your encouragement and understanding during this period have meant the world to me.

If you plan on getting a terminal degree, please do not procrastinate in making it a reality; it does not get easier as you get older. I only hope that I can provide the same level of support, girls, while you continue to pursue your educational goals. With the completion of my fourth and final (!) degree, I can assure you that the dedication to your studies will require you also to tap into extensive support networks to succeed but will always provide satisfaction that surpasses both the investment and the sacrifices.

Finally, to my 16-year-old flat-coated retriever, Coal, who sat tirelessly by my side for endless months while I researched, wrote, and rewrote my work. He never wavered and was able to hang on until a week before Prelims. I continued with the project on after his passing, with the same steadfast devotion for the additional 10 months required to see the dissertation through to completion. iii

TABLE OF CONTENTS

Page

LIST OF FIGURES……………………………………………………………………...vii

LIST OF TABLES……………………………………………………………………...viii

NOMENCLATURE………………………………………………………………………ix

ACKNOWLEDGEMENTS ...... x

ABSTRACT……………………………………………………………………………..xii

FOREWORD ...... xiv

CHAPTER 1. INTRODUCTION ...... 1

Shortage and Burnout ...... 1 Burnout: Employee Implications………..………………………………………………...2 Burnout: Industry Implications ...... 3 Burnout: Financial Implications ...... 4 Growth of the Healthcare Industry ...... 6 Labor Shortage and Succession Crisis ...... 7 The War for Talent ...... 8 Multigenerational Influences in the Workplace ...... 10 Problem Statement ...... 10 Purpose of Study ...... 11 Significance of Study…………………………………………………………………….12

Industry Implications ...... 12 Theoretical Implications...... 13 Delimitations ...... 14 Key Terms...... 14 Organization of the Dissertation ...... 16

CHAPTER 2. LITERATURE REVIEW ...... 17

Chapter Overview ...... 17 Motivational Theories ...... 19 Maslow’s Theory ...... 19 Herzberg’s Theory ...... 19 Skinner’s Behavior Modification Approach (1938) / McGregor’s Theory X and Theory Y (1960) ...... 21 Vroom’s Expectancy Theory (1964) ...... 21 iv

Social Exchange Models...... 22 Social Exchange Theory (SET) ...... 22 Organizational Support Theory (OST) ...... 23 Reciprocity Theory ...... 244 Psychological Contract Theory (PCT) ...... 25 Employee Commitment and Organizational Performance ...... 29 Organizational Commitment ...... 29 Employee Engagement ...... 30 The Healthcare Work Environment and Burnout ...... 31 Employee Loyalty and Turnover ...... 333 Competitive Advantage of Top United States Companies ...... 35 Competitive Advantage of Top United States Healthcare Companies ...... 367 Talent Management Practices ...... 37 Employment Contracts ...... 39 Shifting Expectations of the New Workforce ...... 422 Employee Expectations of the Psychological Contract ...... 42 Benefit Preferences of Employees ...... 45 Educational Assistance Benefits (EAB) ...... 488 Cost of College Versus Tuition Assistance Caps…………………………………….51 EAB Employee Participation Rates………………………………………………….55

EAB Policy Structure……………………………………………………………56

Restitution Obligation and Enforceability…………………………………………...58 Use of Third-Party Administrators………………………………………………...59 Return on Investment (ROI)………………………………………………………61 Unique Models for Tuition Assistance Programs in Hospitality and Tourism…..63 Hypotheses Context and Theoretical Underpinnings ...... 65 HRM Practices and Organizational Performance ...... 65 PCF ...... 66 Benefits and PCF ...... 67 PCF and Employee Engagement ...... 67 Turnover Intention ...... 68 PCF and Turnover Intention ...... 68 Employee Engagement ...... 68 Employee Engagement and Turnover Intention ...... 69 Hypothesis and Conceptual Model ...... 70

CHAPTER 3. METHODS ...... 71

Sampling and Study Design ...... 71 Study Sample ...... 72 Internal Review Board Approval ...... 74 v

Survey Instrument ...... 75 Demographic Questions ...... 76 Reliability and Validity ...... 76 Reliability………………………………………………………………………...77 Validity…………………………………………………………………………..77

Confirmatory Factor Analysis (CFA) Testing…………………………………...78

Common Method Bias ...... 79 Reliability & Validity Testing Conducted Within Study………………………...80 Construct Validity………………………………………………………………..80

Pilot Survey Process ...... 80 Data Collection Process ...... 81 Data Analysis Process ...... 82

CHAPTER 4. RESULTS...... 85 Study Respondents………………………………………………………………………85 Demographic and Job Classification Profile…………………………………….86 Measurement Model ...... 91 Assumptions ...... …96 Study Results………………………………………………………………...... 99 Regression 1…………………………………………………………………….100 Regression 2…………………………………………………………………….100 Summary of Hypotheses……………………………………………………… 102 Chapter Summary………………………………………………………………103 CHAPTER 5. DISCUSSION…………………………………………………………..104 Summary of Findings ...... 103 Interpretation of Findings ...... 104 Practical Implications……………..………………………………………….....104 Theoretical Implications………..…….…………………...……………………106

PCF ...... 106 Employee Engagement………………………………………………………….107 Turnover Intention………………………………………………………………108 Study Limitations ...... 107 Future Research Opportunities...... 108

REFERENCES…………………………………………………………………………112

APPENDIX A. INTERNAL REVIEW BOARD AUTHORIZATION ...... 138 vi

APPENDIX B: INFORMED CONSENT DOCUMENT ...... 139

APPENDIX C. EDUCATION ASSISTANCE BENEFIT PLAN/TUITION ASSISTANCE PLAN (EAB/TAP SURVEY INSTRUMENT ...... 142 vii

LIST OF FIGURES

Page

Figure 1. Number of healthcare jobs by year (in thousands). (2016). Bureau of Labor Statistics...... 7

Figure 2. Maslow’s hierarchy of needs (Pullen, 2014, n.p.)...... 20

Figure 3. Herzberg’s two-factor model (Pullen, 2014)...... 21

Figure 4. Which benefits are most valued by job seekers? (Jones, 2017)...... 47

Figure 5. Cost of 4-year undergraduate colleges. (College Board, 2016)...... 52

Figure 6. Hypothesized model...... 70

Figure 7. Normal P-P plot for Regression 1...... 97

Figure 8. Normal P-P plot for Regression 2...... 97

Figure 9. Scatter Plot for Regression ……………………………………………………98

Figure 10. Scatter Plot for Regression 2…………………………………………………98

viii

LIST OF TABLES

Page

Table 1 U.S. Employers Offering 100% Tuition Reimbursement ...... 55

Table 2 Sample Characteristics…………………………………………………………. 88

Table 3 Factor Loadings for Constructs………………………………………………….94

Table 4 Results of Adjusted Measurement Model ...... 95

Table 5 Means and Standard Deviations for Study Variables…………………………...96

Table 6 Pearson Correlations Between Study Variables ...... 99

Table 7 Linear Regression Predicting Engagement…………………………………….100

Table 8 Hierarchical Multiple Linear Regression Predicting Turnover Intention……...101

Table 9 Summary of Hypothesis………………………………………………………..103

NOMENCLATURE

EAB Educational Assistance Benefits

PCB Psychological Contract Breach

PCF Psychological Contract Fulfillment

PCT Psychological Contract Theory

SET Social Exchange Theory

TAP Tuition Assistance Plan

ACKNOWLEDGEMENTS

Until one travels the doctoral path, it is impossible to understand the demands this journey dictates or the sacrifices necessary to achieve a Doctor of Philosophy degree. As

I sought to answer a lifelong leadership question of mine, “What makes people tick and why do they stay true to an organization?”, I pursued this study and leveraged a vast network of both academic and industry contacts and those closest to me for support. I am appreciative of the many people who supported me in my doctoral journey and without whose support I might not have persevered.

My Co-Major Professors, Dr. Bob Bosselman and Dr. Eric Olson, provided immeasurable support as I learned to navigate academia following 30 years in industry.

Their valuable insights, patience, and encouragement made such a difference as I struggled with process and theoretical ambiguities and self-doubts. My remaining committee members, Dr. Brad Shrader, Dr. SoJung Lee, and Dr. Joan Su, each added a unique perspective, and, collectively, they enhanced my critical thinking and my ability to articulate my thoughts in a more cohesive way.

I want to extend my sincere gratitude to the healthcare leaders at the sponsoring organization, all of whom were responsive and supportive throughout the study. Their spirit of inquiry in the interest of improving employee engagement was admirable throughout the process. I am also grateful for the participation of respondents in the study, who willingly partook in the survey and provided a critical vantage of their mindset relative to their employer and their expectations related to professional development support. xi

I also want to thank my employer, the Department of Healthcare Administration and Policy at the University of Nevada, Las Vegas (UNLV), and my boss, Dr. Chris

Cochran, who provided me with a motivational and intellectually stimulating environment in which to work while I pursued my Doctor of Philosophy degree at Iowa

State University. Dr. Cochran also repeatedly urged me to keep my “eye on the prize.”

Dr. Gina Sully, friend and director of the UNLV Writing Center, was another source of inspiration as a highly courageous and funny confidante who also traveled this path later in life. Finally, my research partnership with scholars at the William F. Harrah Hotel

College at UNLV, led by Dr. Stowe Shoemaker, has been rewarding as I forge a path in interdisciplinary research in healthcare and hospitality.

Finally, to my highly creative, encouraging, and inspiring “Millennial” friend, Dr.

Eve Krahe: Thank you for always being my sounding board and helping me see the value in transferring my executive skills into the academic world.

xii

ABSTRACT

Attracting and retaining talent is a significant differentiator for healthcare companies during this time of growth, transformation, talent shortage, and burnout within the industry. The need to attract and retain skilled workers has spawned the development of strategic talent management functions to drive business performance. Delivering psychological contract fulfillment for employees may be a major differentiator for healthcare employers seeking to deliver business outcomes. Today’s multigenerational workforce shows signs of reduced employee engagement and stronger turnover intention, and it is challenging traditional engagement and retention strategies. Scant research has been conducted to support the rationale for fulfilling the psychological contract to deliver business outcomes in a healthcare environment.

The purpose of this project was to evaluate perceptions of a healthcare system’s employees to discern whether the impact of employees’ psychological contract fulfillment affects business outcomes. Using social exchange theory and evaluating employees’ attitudes toward their employer based on the tenets of psychological contract theory, the data analysis was completed using linear regression and a hierarchical multiple linear regression.

The study showed that employees claiming PCF impacted employee engagement, and those with the strongest fulfillment tended to have the highest level of engagement.

Engaged, fulfilled employees were less inclined to claim turnover intention. This study provides industry insight into employee perceptions about their employer relationship, and related business outcomes during a time of intense competition for talent, rising compensation and benefits costs for employers, and the need to meet the insatiable xiii expectations of today’s disloyal workforce. A company’s ability to deliver on employees’ PCF is causally linked to higher levels of engagement and the reduction of turnover intention. This should be explored further due to the study’s findings that employee engagement is a significant negative predictor of turnover intention. PCF can have a material impact on business outcomes. The research adds to PCF research and related business outcomes in a healthcare system.

Keywords: psychological contract fulfillment, employee engagement, turnover intention, healthcare

xiv

FOREWORD

Homans’ (1958) seminal research in social exchange theory has proven so profound that it holds true in the business world some sixty years later:

Persons that give much to others try to get much from them, and persons that get much from others are under pressure to give much to them. This process of influence tends to work out at equilibrium to a balance in the exchanges. For a person engaged in exchange, what he gives may be a cost to him, just as what he gets may be a reward, and his behavior changes less as profit, that is, reward less cost, tends to a maximum. Not only does he seek a maximum for himself, but he tries to see to it that no one in his group makes more profit than he does. The cost and the value of what he gives and of what he gets vary with the quantity of what he gives and gets (Homans, 1958, p. 606).

CHAPTER 1. INTRODUCTION

The healthcare industry faces a complex problem: Industry growth and retirement trends have exacerbated labor demands and competition for employees, while at the same time the dwindling labor force experiences burnout and rising turnover (Kreitler, Toren,

& Barak, 2016). Solving this problem requires that innovative talent management strategies be implemented in efforts to attract and retain the most skilled people as the talent pool shrinks, staffing needs grow, and employees demand more.

Shortage and Burnout

A shortage of all healthcare employees (nurses, physicians, and other healthcare practitioners) has created a labor crisis, with mass retiree activity already under way

(Salka, 2016). “The United States has 15,230 fewer primary care doctors than it needs”

(“Think It’s Hard to See a Doctor?”, 2012, n.p.), and demand for nurses will exceed supply by nearly 30% by 2020 (Randall Andrews & Dziegielewski, 2005). According to

Candy aka Gypsy Nurse (2016), “the nursing industry workforce was projected to grow from 2.71 million in 2012 to 3.24 million in 2022, which represents an increase of

526,800 or 19%” (n.p). “Seven hundred thousand nurses are predicted to retire or leave the labor force by 2024” (Grant, 2016, n.p.). These clinician shortages create risk of burnout among staff and can partially be addressed by adopting custom coverage models that provide greater staffing during peaks, such as flu season (DeCapua, 2016). Proactive and comprehensive solutions must be implemented if stakeholders are to understand and counteract associated risks of burnout in response to projected volume demands.

Industry growth and retirement trends have exacerbated labor demands.

Competition for employees among healthcare companies is intense because of the growth 2 of the healthcare sector and a restricting labor market. Compounding the nursing shortage, employee satisfaction has waned, with the current employee population more complex because of the emergence of a multigenerational workforce. Robert Half

Management Resources (2010) described the multigenerational workforce as “comprising three generations: Baby Boomer (born 1946–1964); Generation X (born 1965–1978); and

Generation Y or Millennial (born 1979–1999)” (n.p.). A consensus exists that the roughly

76 million Americans within the Millennial group warrant workplace adaptations because of their unique expectations (Laird, Harvey, & Lancaster, 2015).

Burnout: Employee Implications

Within the backdrop of changing workforce dynamics, nurses are becoming increasingly unhappy at work (Rondeau, Williams, & Wagar, 2009). According to

Monegain (2013), 60% of healthcare industry workers say they are burned out in their career, and 82% of these employees said they would leave their companies if the ideal opportunity surfaced. Burnout, initially conceptualized by Freudenberger (1974) as being tied to “excessive work involvement and the consequential excessive depletion of energetic and social resources” (as cited in Halbesleben, 2008, p. 8), remains highly prevalent in healthcare by “exhaustion and cynicism traits” (Schaufeli, Bakker, & Van

Rhenen, 2009, p. 895), “detachment from the job,” and “a sense of ineffectiveness and lack of accomplishment are also recognized” (Maslach, Schaufeli, & Leiter, 2001, p.

399).

Signs of burnout include illness, fatigue, feelings of underappreciation, work avoidance and absenteeism, lack of engagement and reduced productivity, and insensitivity to patients (Fink, n.d.). Engagement has been defined as how “people employ and express 3 themselves physically, cognitively, and emotionally during role performances” (Kahn,

1990, p. 694), and is often absent when burnout exists. Employee engagement was related to Psychological Contract Fulfillment (PCF), which materializes when a company meets its employee obligations and positive employee behaviors occur (Karagonlar, Eisenberger

& Aselage, 2016). This development of the relationship is an evolution of social exchange

(Karagonlar et al., 2016). “Social exchange theory has been one of the most influential conceptual paradigms for understanding workplace behavior” (Cropanzano & Mitchell,

2005, p. 874) and was represented when “workers seek a mutually beneficial and just relationship with their organization” (Chin & Hung, 2013, p. 845).

Physicians are experiencing burnout at twice the rate of other American workers, with more than 50% of them exhibiting symptoms. Among residents and medical students, burnout and depression are highly prevalent (Dyrbye et al, 2017). A 2012 study of 188 nurses showed that 50% of nurses had a propensity to demonstrate burnout symptoms, and all reported professional underachievement in their workplaces and signs of emotional fatigue associated with burnout (Ribeiro et al., 2014). Burnout was more prevalent among younger generations of nurses, who are less accepting of work environments that are not aligned with their own values (Hayes et al., 2012). Recruiting replacement nurses into organizations suffering from shortages has proven challenging

(Hayes et al., 2012), so preventing turnover when signs of burnout surface has been a priority for industry employers experiencing rapid transformation.

Burnout: Industry Implications

The industry faces a growing demand to improve patient outcomes, which are now government mandated and tied to financial reimbursement (Ogden, 2010). The 4 monumental restructuring of the healthcare delivery system prompted by the Affordable

Care Act, has resulted in elevated expectations of all healthcare stakeholders to comply with both increased patient volumes and regulatory demands intended to improve access and care quality while reducing cost (Anderson, 2014). Engaging employees has been moved to the back burner, as cost controls, quality initiatives, and driving innovation have become paramount in healthcare (Hilton & Sherman, 2015). An increasingly complex regulatory climate has been compounded by patient volume, with “nearly 89 million seniors expected to flood the healthcare system by 2050, with 68% of them suffering from more than one chronic condition” (Grant, 2016, n.p.). These dynamic industry changes provide both opportunity and risk in engaging an overwhelmed workforce at risk of burnout and turnover.

Burnout: Financial Implications

The financial burden of employee burnout significantly affects healthcare; the hard costs of turnover are obvious. Burnout has become more than just an emotional phenomenon exhibited by millions of healthcare workers—it also collectively costs the industry more than $200 million tied to voluntary terminations, medical errors, and missed shifts (DeCapua, 2016). The turnover of a single physician represents at least a

$200,000 cost for a healthcare company, according to B.E. Smith Corporation (2017). It costs at least $58,400 to replace each nurse—1 to 1.5 times the salary of the employee— which adds up to a loss of more than $5 million annually for the average hospital, or

$373,200 for every percentage point increase or reduction to the turnover rate within a healthcare company (Bean, 2016). According to Nursing Solutions, Inc. (2015), hospitals absorb average costs of turnover ranging from $5.2 million to $8.1 million, and 5 healthcare turnover rates are the third highest of all professions, behind only banking and hospitality (Goodman, 2016), with 43% of new nurses exiting the healthcare industry within 3 years of graduating. Turnover rates are highest in long-term care facilities because of their notoriously lower wage rates and difficult working conditions (Antwi &

Bowblis, 2016) and range from 50–100% annually.

The damaging attributes of burnout run counter to the American Hospital

Association’s (2014, n.p.) charge to industry to maintain an engaged workforce due to its critical importance to healthcare companies, with its ability to drive high quality clinical outcomes and patient satisfaction. With a significant negative effect on the effectiveness of companies (Chin & Hung, 2013), turnover, whether due to retirement or worker dissatisfaction, has been shown to disrupt healthcare operations. Burnout has also been linked to higher medical error rates (DeCapua, 2016). Soft costs with implications for medical error rates, patient mortality rates, medical malpractice suits, absenteeism, productivity and reduction in effort, increased referrals, the ordering of more tests, hospital-acquired infections, and higher employee turnover (Dyrbye et al., 2017) are difficult to quantify. The related instability in healthcare environments posed by turnover also creates risk to patient care (Duffield, Roche, Dimitrelis, Homer, & Buchan, 2015).

The consistency and dedication demonstrated by a stable staff was better able to meet individualized care needs of patients, equating with improved quality of life, according to the American Healthcare Association (2018). Nurse and patients often build relationships during the care cycle, and the bonds built are linked to better clinical outcomes (Antwi &

Bowblis, 2016). 6

Burnout also has direct correlation with job dissatisfaction and “more than a 200 percent increased-odds of intent to leave” (Dyrbye et al., 2017, p. 2). Among workers who regularly feel burned out, 45% express turnover intention, or intent to leave their organization within 24 months (Monegain, 2013). Forty-four percent of employees maintain that their employers do not care about them (Harmeling, 2013), prompting higher turnover intention. Scholars also support the correlation between turnover intention and actual turnover rates (Cohen, Blake, & Goodman, 2016). Companies need to proactively take notice of employees’ intentions and try to make noticeable improvements that can influence retention rates, thereby reducing the expenditure of time and effort needed to replace disenchanted employees.

Growth of the Healthcare Industry

Representing one of the nation’s largest employment sectors, the healthcare industry has been the subject of countless growth projections over the past decade. This industry was projected to generate 3.2 million jobs from 2008 to 2018; this growth was said to be unprecedented—no other sector was expected to experience such an increase during this period (Bishow, 2007). The healthcare and social assistance major sector was anticipated to “become the largest job sector during this decade of projection, overtaking state and local government major job sectors and the professional and business services major job sector. Healthcare and social assistance was projected to increase its employment share from 12% in 2014 to 13.6 % in 2024" (Bureau of Labor Statistics

2015, n.p.). In fact, “healthcare created more jobs than any other sector in 2016, helping to drive total annual job growth to 2.2 million” (Livingston, 2017, n.p.), as can be seen in

Figure 1. This rapid growth and shifts in the broader labor market have added further 7 challenges for the healthcare industry. These include competition with other service industry employers and insufficient time to build effective succession plans to counter the loss of departing legacy staff.

Figure 1. Number of healthcare jobs by year (in thousands). (2016). Bureau of Labor Statistics.

Labor Shortage and Succession Crisis

Unfortunately, the United States has been unable to keep pace with the demand for healthcare workers. As Dell and Hickey (2002, p. 7) noted, “the Bureau of Labor

Statistics projected a goal of six million employees by 2008, and peak levels far surpassing this level between 2015 and 2025.” This phenomenon has been generated by the ongoing exit of some 78 million Baby Boomers from the workforce and has placed a significant strain on many healthcare systems (Gigante, 2010). With the departure of 8

Baby Boomers from the workplace, the loss of institutional knowledge has become problematic. Institutional knowledge was defined as knowledge of experienced staff who are deemed critical to deliver core functions necessary for business continuity (Hardar,

2013), and its loss creates risks for healthcare businesses related to loss of knowledge as leaders retire (McGraw & Burr, 2011). Complex healthcare environments demand continuity of care and legacy expertise lest quality be placed in jeopardy (Peterson,

2015). In most companies, “systems for the transfer of knowledge are woefully underdeveloped” (James, McKechnie, & Swanberg, 2011, p. 174). Membership in the

American College of Healthcare Executives, a prominent professional association for healthcare executives that has nearly fifty thousand members, has reflected this retirement cliff crisis within healthcare, reporting that more than 46% of its membership was over 50 years of age (“Age wave: Retiring Baby Boomers create succession planning imperative”, 2014).

Relying on Boomers in the workplace has resulted in a lack of leadership development for other generations that followed them. Companies that have failed to invest in their entire employee base and build an effective succession plan also risk lower productivity and lack of employee loyalty (Chavez, 2011). Succession involves

coaching and development of prospective internal or external successors to take up key positions in an organization through an organized process of assessment and training. It ensures a smooth transition of power for key leadership roles but can be challenging to prioritize when significant talent competition exists. (“Definition of ‘Succession Planning,’ 2017, n.p.)

The War for Talent

The labor crisis’ trends, driven by an older and departing workforce, resulted in a

War for Talent, creating intense pressure on businesses to recruit, retain, and train key staff members (Michaels, Handfield-Jones, & Axelrod, 2001) and has been felt acutely in 9 the healthcare industry. But the healthcare sector has not shouldered this burden alone. A global study (Collings & Mellahi, 2009) of 40 companies in various industries revealed in insufficient pipeline to meet job demands and substantiate the earlier projection of the

War for Talent, demonstrating a sustained crisis.

The War for Talent term was coined by McKinsey & Co. when it made an ominous warning to industry, that a talent shortage was on the horizon (Michaels et al.,

2001). In fact, by 2020, employers in the world’s richest nations are forecast to be short as many as 18 million college-educated workers (Klemp, 2014, n.p.). Industry sits at a critical juncture, and companies are recognizing the link between talent management and company performance, and that their ability to attract and retain a shrinking labor pool provides a critical competitive advantage for them (Michaels et al., 2001). Today, the situation has become worse than when the talent crisis was first identified (Michaels et al., 2001) due to a combination of the looming retirement of the Baby Boomer generation and the declining birth rate in many Western countries. Two subsequent surveys predicted that senior executives expected this intensification of competition for talent over time (McCormick, 2016).

The War for Talent affects all American industries but coupled with the unique pitfalls of the healthcare employment environment relative to growth, employee stress, and burnout, it presents risks related to employee loyalty and turnover. Understanding the distinctive pressures experienced by healthcare workers was the first step in developing tailor-made strategies and policies that will help industry leaders win the War for Talent. Employers are deploying a variety of benefit packages to attract and retain their workforces, with Educational Assistance Benefits (EAB) programs defined as 10 governing “an employee benefit in which an employer pays for an employee's educational expenses or provides tuition reductions or scholarship grants to an employee's spouse or dependent children” (SHRM, 2015, n.p.) being offered by most healthcare companies.

Multigenerational Influences in the Workplace

The War for Talent age requires that stakeholders recognize changing workforce demographics. Today’s workforce has been noted as multigenerational, with three primary generations being represented: Baby Boomers, Generation X, and Generation Y.

Effective management of multiple generations can offer a competitive advantage for healthcare providers (Sherman, 2006). Diverse mindsets and preferences in communication approaches are apparent in a multigenerational environment, and flexibility in managing ever-changing technology and work pattern differences are key to avoiding conflict among workers (“How to Manage Different Generations,”, 2009).

Having the ability to solve problems by drawing on various perspectives within a multigenerational team can be beneficial in addressing healthcare’s difficult challenges, and so the “development, mentoring and retention of employees so that they stay and reach their full potential” (Wagner, 2017, p. 18) should be a priority for today’s companies.

Problem Statement

In the health sector, employees provide a competitive advantage for companies, and the likelihood of their PCF can be improved by offering an appealing benefits package (Saleem & Saleem, 2013), which includes EAB and a variety of other incentives.

An opportunity exists to more closely examine how PCF, employee engagement and 11 turnover intention are interrelated. The significant increase in turnover rates must be aggressively addressed if the burnout and turnover phenomenon were to be eradicated

(Leiter, Price, & Laschinger, 2010). Employee benefits continue to be valued by employees, businesses, and society due to their correlation with delivering workforce and financial goals of companies (Rappaport, 2013). The majority of employee engagement literature in healthcare typically focuses on nurse participants only, rather than on the broad spectrum of job roles employed in this industry. In addition, the mechanism by which these benefits are deployed, operationalized, and perceived by employees vis-à-vis burnout and turnover was not well understood. PCF and employee engagement creation has the potential to reduce turnover intention, which can create valuable benefits to industry relative to financial performance and customer satisfaction.

Purpose of Study

The purpose of this project was to examine the value of employee PCF in a health system, and how it relates to business outcomes. This study used the construct of social exchange theory, specifically that of PCF. This research focused on determining how

PCF impacts employee engagement and turnover intention. EAB, operationalized in this study’s survey instrument as Tuition Assistance, represents the contractual relationship an employee has with her/his employer regarding the receipt of continuing education reimbursement (Jenkins, 1993). Specific research objectives were to: a) determine the relationship of PCF on employee engagement, b) determine the relationship of PCF on turnover intention, and c) determine the relationship of employee engagement on turnover intention.

Significance of the Study

Research has been lacking in the employee benefits arena, despite the significance of its cost implications to organizations and the resulting relationship impact it has on company employees (Dulebohn, Molloy, Pichler & Murray, 2009). Healthcare companies may be able to ameliorate burnout and turnover in staff with benefits strategies, and thus improve business outcomes. An awareness of psychological contracts on the part of employees and of their expectations of employer reciprocity through competitive EAB plans and the effective administration of these plans can act as the conduit. “Little research has been carried out on factors that inﬂuence the strength of the relationship between PCF and outcomes important for employees and the organization”

(Karagonlar et al., 2015, p. 24). Given the scant research evaluating healthcare system employees’ PCF and its potential outcomes of employee engagement and turnover intention, the study serves industry and academia alike.

Industry Implications

“A fundamental purpose of organizational behavior research is to generate findings that are of practical use to organizations”, as observed by Irving and Montes

(2009, p. 444). With healthcare leaders grappling with the evaluation of their benefit plans relative to competitors and within a backdrop of rising employee expectations and finite budget dollars, this study can provide insight about PCF impacts employee engagement and turnover intention. For industry, the research creates visibility around employees’ reciprocity obligations and highlights the causal relationship between professional development and organizational commitment of employees. This study can serve healthcare employers by providing tangible evidence about an EAB investment, and the appropriate plan structure needed to create engaged employees. By better 13 understanding employee motivation, employers can prioritize employment professional development benefits that will increase employees’ likelihood of remaining loyal to the organization, thereby improving employer outcomes.

Theoretical Implications

For academia, the study adds to existing literature on social exchange theory, turnover intention, and employee engagement in the workplace. This addition was important because “despite important consequences of work engagement, scholarly research on the construct is inadequate” (Agarwal, Datta, Blake-Beard, & Bhargava,

2012, p. 209). This study uniquely addresses a broad range of healthcare employees and how they perceive their employer in the context of specific benefits offered. The majority of employee engagement literature in healthcare typically focuses on nurse participants only, rather than on the broad spectrum of employees in this industry.

Existing literature does not delve into employees’ attitudes about benefits, their linkage with PCF, and the corresponding business outcomes. The existing literature defining the causes of PCF in the workplace (Rodwell, Ellershaw, & Flower, 2015) and the reasons for the high rate of voluntary employee turnover (Memon, Salleh, & Baharom, 2016) has been insufficient. Much can be learned from varying demographics within the workforce, and this study may spawn additional discussions around a material gap, with

“empirical evidence and theoretical justification for generational differences specifically linking work values and work attitudes lacking in the current literature” (Lub, Matthijs

Bal, Blomme, & Schalk, 2016, p. 654). 14

Delimitations

Research limitations stemming from study timing and selection of participants must be noted. The fact that the study focused on employees from only one hospital system may limit its generalizability. In addition, this was a cross-sectional study, with data collected during a single period. It therefore cannot be determined whether time was a confounding variable because reciprocity attitudes may change over time and be based on shifting relationships and expectations. Data collection was limited to EAB applicants’ self-reported perceptions only; views of employees who were non-EAB applicants and employer/management views were not within the research scope of this study. Participating employees may still have felt compelled to shield their actual attitudes during their survey response processes, despite having been informed that their responses would remain confidential.

Key Terms burnout – “psychological syndrome in response to chronic interpersonal stressors on the job with dimensions including overwhelming exhaustion, feelings of cynicism and detachment from the job, and a sense of ineffectiveness and lack of accomplishment”

(Maslach, Schaufeli & Leiter, 2001, p. 399) educational assistance benefits (EAB) – “according to IRS regulation 601.201, these benefits are the payment, by an employer, of expenses incurred by or on behalf of an employee for education of the employee (including, but not limited to, tuition, fees, and similar payments, books, supplies, and equipment), and the provision, by an employer, of courses of instruction for such employee (including books, supplies, and equipment)”

(Cornell Law School, n.d., n.p.) 15

employee engagement – “people employ and express themselves physically, cognitively,

and emotionally during role performances” (Kahn, 1990, p. 694)

entitlement - “a mindset of deserving success, promotions, admiration, and commendation without demonstrating the merit, high performance or qualifications to warrant such rewards” (Holderness, Olsen & Thornock, p. 42)

perceived organizational support (POS) – creates “agreement in the degree of support

that the employee would expect of the organization in a wide variety of situations.”

(Eisenberger et al., 1986, p. 501)

psychological contract (PC) – the way in which an employee perceives the reciprocal

relationship that they have with their employer organization (Rousseau, 1989)

psychological contract breach (PCB) – “the cognition that the organization has failed to

meet one or more obligations within the scope of the psychological contract whereas the

employee has fulfilled his or her obligations” (Matthijs,Bal, Chiaburu, & Jansen, 2010,

p.253)

psychological contract fulfillment (PCF) - develops when a company delivers on its staff

obligations and positive employee behaviors result (Karagonlar, Eisenberger & Aselage,

2016).

reciprocity – “if a person receives a benefit, the receiving party should respond in kind”

(Cropanzano & Mitchell, 2005, p. 876)

social exchange theory – “workers seek a mutually beneficial and just relationship with

their organization” (Chin & Hung, 2013, p. 845)

turnover – “dividing the number of employees who are no longer employed by the total

number of employees still employed for a reporting period” (Hayes et al., 2012, p. 888) 16 turnover intention – “conscious and deliberate willfulness to leave an organization’ (Tett

& Meyer, 1993, p. 262)

War for Talent – “a critical driver of corporate performance; a company’s ability to attract, develop and retain talent will be a major competitive advantage far into the future”

(Michaels, Handfield-Jones & Axelrod, 2001, p. 2)

Organization of the Dissertation

This dissertation has five chapters. Chapter one provides an introduction and includes the Abstract, Growth of the Healthcare Industry, Labor Shortages and

Succession, The War for Talent, the Problem Statement, the Purpose of the Study,

Significance of the Study, and Delimitations. Chapter two covers the Healthcare Industry and its Employees, Psychological Contract theory, Employee Engagement, Employee

Loyalty and Turnover, and EAB. In Chapter three, the Methods section, the Population and Sample are discussed, along with the Survey Instrument, the Data Collection Process, and the Data Analysis. Chapter four provides Pilot Results, Study Respondents,

Demographic Profile of Participants, Construct Validity and Reliability, Assumptions,

CFA results, Study Results, a Summary of Hypotheses, and a Chapter Summary. Chapter five provides a Discussion Overview, incorporating a Summary of Findings, an

Interpretation of Findings, the Implication of the Findings, the Limitations of the Study, and Opportunities for Future Research.

CHAPTER 2. LITERATURE REVIEW

Chapter Overview

This section has been organized into four parts: a summary of motivational theories; an overview of social exchange models; an assessment of employee commitment and organizational performance; and insights into the healthcare work environment and corresponding burnout and turnover intention among its employees.

Seminal work in motivational theory, for example, Maslow (1943) and Herzberg

(Herzberg, Mausner & Snyderman,1959; Herzberg, 1968), provides valuable insights into human behavior. More recently, Gillet, Huart, Colombat, and Fouquereau (2013) evaluated the impact of work motivation theory on engagement. Recognition has emerged that understanding the framework of motivational theory and social exchange relationships leads to knowledge of employee expectations of and attitudes about employers. Psychological contract has also been found to “play an important role in employee motivation” (Chang, Hsiu, Liou & Tsai, 2013, p. 2121).

The early work of social exchange relationships, social exchange theory (SET)

(Blau, 1964; Homans, 1958), and related models, such as organizational support theory

(Eisenberger, Huntington, Hutchinson, & Sowa, 1986), reciprocity (Blau, 1964;

Cropanzano & Mitchell, 2005; Ruben, 2012), and psychological contract theory

(Levinson, Price, Munden, Mandl, & Solley, 1962), became the basis for social contracts.

Social contracts, psychological contracts included, have existed across industries and over time, and their origins and attributes have been extensively evaluated by social scientists (Ruben, 2012). According to Bakker and Leiter (2010), psychological contract 18 studies have increased substantially in recent years because of the wide acceptance of its increasing value in dissecting and comprehending employment relationships.

The promissory element of psychological contracts includes “expectations that emanate from perceived implicit or explicit promises by the employer” (Robinson, 1996, p. 575). A psychological contract can potentially be breached or eroded “when an employee perceives that their employer is failing to deliver on their obligations to the employee” (Robinson, Kraatz, & Rousseau, 1994, p. 140). Under these conditions, “the employee can attempt to recoup these costs by increasing perceived entitlements or decreasing perceived obligations, or both” (p. 141). This framework’s utility in exploring human motivation and workplace exchanges was the rationale for its selection, and PCF linkages with business outcomes were assessed quantitatively in the context of this framework. The broader social exchange constructs are foundational to the research, although this study focuses primarily on psychological contract theory and PCF.

What follows are an exploration of motivational theories and social contract models that reflect the scholarship relevant to this work. An examination of employee engagement, organizational performance, loyalty, turnover, and burnout in the healthcare environment follows, lending currency to the work in an organizational context.

Research specifically about the competitive advantage of top companies across industries and within healthcare, talent management, shifting expectations of employees, and the intricacies of EAB set the stage for the specificities of this work; and finally, psychological contract theory, breach of the contract, and other complexities of this type of social contract related to tuition reimbursement will be presented. 19

Motivational Theories

Over many decades, leaders have embraced a variety of theoretical approaches in their attempts to more effectively motivate employees. “Motivation is a psychological process providing the origin for stimulation, direction, and persistence of behavior”

(Jehanzeb, Rasheed, Rasheed & Aamir, 2012, p. 274)). These approaches include

Maslow’s theory (1943), Herzberg’s theory (Herzberg, et al.,1959; Herzberg, 1968),

Skinner’s behavioral modification approach (1938), McGregor’s theory X and theory Y

(1960), and Vroom’s expectancy theory (1964). Motivational theories also have been used to explain turnover (Meyer, Vandenberghe, & Becker, 2004). Focusing on activities that more effectively motivate employees has been linked to business performance

(Luthans & Sommer, 2005). Understanding what motivates people in the workplace has been crucial in creating effective reward systems that will deliver business outcomes.

Maslow’s Theory

Maslow’s theory (1943) specified five categories of human needs (see Figure 2), including physiological and psychological needs and deficit and growth needs (Pullen,

2014, n.p.). With all needs organized into a hierarchical format, the lower-order needs

(food, oxygen, etc.) were situated at the bottom of the hierarchy, with mid-level needs

(friends, safety, etc.) established in the hierarchical center, and finally, high-level needs

(prestige, potential attainment, etc.) resting at the top of the hierarchy.

Herzberg’s Theory

Herzberg’s theory (Herzberg, et al., 1959; Herzberg, 1968) introduced a two- factor model (see Figure 3) of job satisfaction and motivation. Herzberg’s two-factor theory of motivation (hygiene and motivation factors) was based on the concept that two 20 separate sets of factors “play a role in both the presence of employee job satisfaction and employee motivation elements and the absence of an employee’s hygiene factors”

(Pullen, 2014, n.p.). Achievement, responsibility, and professional growth, deemed intrinsic to the job and to motivation, enhance job satisfaction. Elements such as salary, job security, and supervision are hygiene factors that may at best prevent motivational problems, and, when lacking, lead to dissatisfaction (Bakker & Leiter, 2010).

Figure 2. Maslow’s hierarchy of needs (Pullen, 2014, n.p.).

Figure 3. Herzberg’s two-factor model (Pullen, 2014).

Skinner’s Behavior Modification Approach (1938) / McGregor’s Theory X and Theory Y (1960)

Skinner (1938) asserted that he could modify behavior through reward and discipline. Decades later, divergent philosophies emerged, with theory X and theory Y representing opposite approaches of effective leadership. Theory X managers expect the worst from their employees and believe that structure, controls, and punishment will bring out the best in people. Conversely, McGregor (1960) built upon the higher levels of Maslow’s hierarchy, deeming employees to be responsive to praise, respect, and the ability to be creative at work, based on theory Y (Getz & Page, 2016).

Vroom’s Expectancy Theory (1964)

Vroom (1964) drew a correlation between employees’ emotions and outcomes, suggesting that desire for the outcome will drive an employee’s motivation to work toward a goal (Getz & Page, 2016). Vroom’s valence-instrumentality-expectancy model

(VIE) measured how outcomes were viewed on their own and in conjunction with other outcomes, along with correlations between efforts and outcomes. Actions are deemed to be triggered by “valence (anticipated satisfaction), instrumentality (the belief that performance will lead to rewards), and expectancy” (Locke & Latham, 2002, p. 706).

Widely studied, VIE has generated many conflicting interpretations since its formation, 22 and the model was deemed to have greater legitimacy in its individual components than in the entire model (Van Eerde & Thierry, 1996). Understanding the dynamics of employee motivation will continue to be paramount for companies, with managers valuing the relationship between motivation and obligations and recognizing the importance of employee motivation for remaining at the forefront of competition

(Heshmati & Jed, 2015).

Social Exchange Models

Social Exchange Theory (SET)

Homans (1958), Blau (1964), and Emerson (1976) were the groundbreaking early researchers in SET and shared a widely accepted and still evolving framework that summarized relational behaviors (Chadwick-Jones, 1976). Blau viewed social exchange as the reward activity related to others’ reactions. Implied was a “two-sided, mutually contingent, and mutually rewarding process involving ‘transactions’ or simply

‘exchange’” (Emerson, 1976, p. 337). “Social exchange theory has been one of the most influential conceptual paradigms for understanding workplace behavior” (Cropanzano &

Mitchell, 2005, p. 874) and was represented when “workers seek a mutually beneficial and just relationship with their organization” (Chin & Hung, 2013, p. 845). Social exchange involves the idea that reciprocal favors are done with an assumption that later returns will occur (Aryee, Budhwar, & Chen, 2002). Specificity relative to the return may not be articulated, because social exchange rests on a more discretionary expectation. The motivation for the exchange is also paramount, and the actors must view the exchange as charitable rather than based on self-interest (Karagonlar et al.,

2016). 23

Application of SET in the workplace rests on the assumption that SET represents appealing actions of the company directed at its employees. Emerson noted that the nomenclature of social exchange theory has evolved to include “reward, reinforcement, cost, value, utility, resource, comparison level, transaction, profit, outcome, etc.—[and] is an unconsolidated blend of ordinary speech and the technical vocabularies of research disciplines, notably psychology and economics” (Emerson, 1976, p. 337). Social exchange theory has advanced with the works of Bentein and Guerrero (2008), who positioned it as a structure which explains one’s workplace from an individual perspective (Jepsen, 2010). It also serves to establish reciprocal obligations from the employee. Conversely, work attitudes can become negative in response to unfavorable treatment (Ko & Hur, 2014). Other related concepts have evolved from SET, including organizational support theory, reciprocity theory, and psychological contract theory.

Organizational Support Theory (OST)

According to Baran, Rhoades-Shanock, and Miller (2012), organizational support theory (OST) considers the evolution, type, and results from perceived organizational support (POS). Organizational support theory, based on the norms of reciprocity, stipulates that employees trade work effort to their organization for tangible returns or benefits (Eisenberger et al., 1986).

Organizational support theory defines how organizational commitment was created in the workplace through a fervent loyalty towards the company’s mission and objectives; the interest in exerting effort on an employer’s behalf; and a strong commitment to remain within an organization (Scheible & Bastos, 2012). The theory stipulates that employees perceive how their company cares about them, and this 24 perception was termed perceived organizational support (POS). Employee attitudes, including job satisfaction, are linked to POS, with human resource practices being a major antecedent (Kurtessis et al., 2017).

Reciprocity Theory

Gouldner’s (1960) norm of reciprocity theory (NRT) dictates that employees value feeling appreciated by their company and harbor positive attitudes toward their job and the organization, in return. Therefore, deploying managerial practices that strive to increase employees’ positive perceptions about their company’s support results in employees’ developing favorable attitudes toward their employer (Akgunduz & Sanli,

2017).

The social contract was based on norms of reciprocity, the social glue that helps to sustain society and transverses numerous contexts (Ruben, 2012). Between two parties, reciprocation means a “give-and-take” situation, with one transfer being conditional on another (Cropanzano & Mitchell, 2005). A “going rate” established for social exchange varies widely and was based on supply and demand (Blau, 1964). Reciprocity mandates a balance of all stakeholders’ inputs and rewards in the relationship (Adams, 1965), or that there is equity in an individual’s own investments vs. the rewards received (Price,

1977). It still holds true today that “when employees receive “economic or socio- economic benefits from their organization, they feel obligated to respond in kind . . . with discretionary role behavior” (Alfes, Shantz, Truss, & Soane, 2013, p. 333).

Reciprocation of obligations by employers typically results in employees exhibiting positive behavioral traits, including commitment and intention to stay; conversely, failure 25 of employers to reciprocate will cause employees to contribute less effort (Lub et al.,

2016).

Lack of reciprocity, dissatisfaction, and burnout. During the last two decades, interest in employee stress, burnout, health, and safety has increased, in part because of concerns over effects on employees of meeting the intense demands of a global economy

(Baran et al., 2012). Burnout develops when an imbalance of exchanges occurs between an employee and employer (Bakker, Schaufeli, Sixma, Bosveld, & Van Dierendonck,

2000). Perceptions of a lack of reciprocity can result from feelings about reward and fairness, two of the six domains of workplace environment. Insufficient reward tends to increase the odds of employees’ chances for burnout (Maslach & Leiter, 2008). A longitudinal healthcare study on implications of lack of reciprocity that spanned a decade demonstrated that high effort in low-reward environments creates employee dissatisfaction (Enberg, Ohman, & Keisu, 2015).

Psychological Contract Theory (PCT)

Levinson et al. (1962) first introduced the theory of PCT, which has continued to evolve. Rousseau (1989) initially described the psychological contract (PC) as “an individual’s belief regarding the terms and conditions of a reciprocal exchange agreement between that focal person and another party” (p. 123). Individuals “develop psychological contracts that comprise beliefs about that to which they are entitled given perceived promises from employers” (Robinson, 1996, p. 575). These contracts are subjective, largely because of differences in cognitive ability among individuals, the many data points that comprise the agreement, and the passage of time since 26 conversations and observations have occurred (Shore & Tetrick, 1994). Psychological contracts evolve over time (Collins, 2010).

The PC can be explicitly or implicitly communicated by colleagues, managers, recruiters, observations, and company policies (Karagonlar et al., 2016). It forms the basis for how an individual employee documents the respective contributions to the relationship over its cycle (Coyle-Shapiro & Kessler, 2000), and it serves to stabilize an employee’s acclimation to a company, thereby reducing risk of dissatisfaction and turnover (Shore & Tetrick, 1994). Although the greater sense of security benefits the employee’s psyche, the employer values operating with less oversight because of the mutual understanding that has been created by convincing employees that they “control their destiny” (Shore & Tetrick, 1994, p. 93).

In today’s climate, companies face intense pressure to innovate if their goal is to survive. This pressure to innovate produces a continually evolving relationship between the workplace parties (Scheible & Bastos, 2012), as do employee views of the psychological contract. According to Peng, Jien, and Lin (2016), employee perceptions of their contract are attributed to many factors, including the personality traits of employees, how the contract was constructed, and elements of the organizational environment. Employees can feel compelled by their employers to do far more than their baseline jobs, which results in an expectation that employers will provide greater entitlements to their employees (Umar & Ringim, 2015). More recently, researchers have postulated that “people build mental schemas about their psychological contracts based on this broad range of formative experiences and propose how each generational cohort’s formative experiences impact the psychological contract and related outcomes” (Lub et 27 al., 2016, p. 654). The contract has become more complex, in lockstep with a rapidly changing global business climate.

Psychological Contract Fulfillment (PCF). PCF represents the degree to which a company meets its obligations to an employee, from the employee’s vantage, and it serves to build upon the social exchange element, resulting in positive employee behaviors (Karagonlar et al., 2016). Employees measure fulfillment in five categories—

(a) company policies; (b) workplace environment; (c) career development; (d) job specifications; and, (e) rewards— and they differ in how they respond to fulfillment (Lub et al., 2016). Employees understood that the nature of this exchange relationship was driven by their participation and that results accrued in equivalent benefits (Wu & Chen,

2015). PCF builds trust among stakeholders and has been tied to reduced stress, lower levels of emotional fatigue, and to greater job satisfaction, wellbeing, and organizational commitment (Rodwell et al., 2015). An inverse relationship exists between PCF and turnover intention (Collins, 2010), and PCF has also been shown to create greater trust between employees and their organizations (Gardner, Huang, Niu, Pierce, & Lee, 2015).

The inverse of PCF was identified as psychological contract breach.

Psychological Contract Breach (PCB). Psychological contract breach represents the organizational failure to deliver on an expected obligation, whether written or unwritten (Robinson et al., 1994) and thus the converse of fulfillment. The literature does not address how PCB may impact an employee’s PCF (Walker, 2013). Breach in a contract “undermines the trust an individual has in that employing organization” (Ruben,

2012, p. 329). 28

When PCB occurs, the possibility arises of negative consequences in both the short-term and long-term employees’ behaviors (Ng, Lam, & Feldman, 2010; Priesemuth

& Taylor, 2016). These consequences result from the employees’ emotional response to what they deem to be a violation (Morrison & Robinson, 1997). Employees do not necessarily respond with negative behaviors each time an employee perceives that his or her employer has reneged on its obligations (O’Donohue, Martin, & Torugsa, 2015).

Experiences of breach make individuals more mindful as they seek to control future negative consequences through a process of renegotiation (Cassar, Buttigieg, & Briner,

2013). As Turnley, Bolino, Lester, and Bloodgood (2003, p. 192) noted, “how an employee chooses to respond to getting less than promised is likely to be determined by both the magnitude of the discrepancy and by the individual’s attribution regarding why the discrepancy occurred.”

Once a breach has occurred, and an employee recognizes that their employer has failed to deliver on its promises, a psychological contract violation or adverse behavior can result from the breach, preceding other adverse consequences (Suazo & Stone-

Romero, 2010), such as mistrust, declining job satisfaction, and turnover (Priesemuth &

Taylor, 2016). Breach of the psychological contract diminishes job satisfaction, employee commitment, employee job performance, and turnover intention. When an organization fails to demonstrate caring behaviors to employees, then employees no longer feel an obligation to demonstrate positive behavior in the workplace (Restubog,

Hornsey, Bordia, & Esposo, 2008). 29

Employees reciprocate when their employers fail to fulfill promises, and this adaptive behavior results in less effort being expended and lower performance (Lub et al.,

2016). The best-selling book Thriving on Chaos explains:

Involvement by all and non-adversarial relations must necessarily rest on a cornerstone of trust, which in turn, can only be engendered by total integrity. If a promise (even a minor one) is not kept, if ethics are compromised, and if management behaves inconsistently, then the strategies necessary for survival today simply can’t be executed (Peters, 1987, p. 519).

Understanding how and why employees perceive breaches in their psychological contract and what organizations can do to prevent this perception will help improve organizations’ performance and outcomes by allowing them to deliver PCF.

Employee Commitment and Organizational Performance

Linkages between human resource practices and company performance, derived from talent management strategies and business outcomes, are documented by Strategic

Human Resource Management (SHRM). A correlation between people-management practices and organizational performance exists; this influence was indirect and dependent on the influence of these practices on employees (Elorza, Aritzeta, &

Ayestaran, 2011).

Organizational Commitment

Commitment was defined by the American Heritage Dictionary (n.d.) as

“something pledged, especially an engagement by contract involving financial obligation” with employees’ commitment to their companies being directly influenced by how companies demonstrate loyalty to their people (Eisenberger et al., 1986). A strong commitment to employers stems from employee alignment with goals and vision, and from their trust in the organization and their-co-workers, causing them to demonstrate 30 positive behaviors (Cesario & Chambel, 2017). Mowday, Porter & Steers (1982) provided the seminal research of organizational commitment, which was evolved by

Meyer and Allen (1991), among others. Jenkins (1993) labeled “organizational commitment as a strong predictor of turnover” (p. 84), and Scheible and Bastos (2012) saw it as a more stable basis than job satisfaction in predicting turnover. Positive attitudes toward an organization have been shown to reduce turnover (Lee, Hom, Eberly,

& Li, 2017). Employees tend to deliver reciprocal behavior based on observations of organizational commitment being demonstrated by their employers (Eisenberger et al.,

1986). Watson Wyatt International reported 147% higher shareholder returns to companies with a high level of employee commitment (as cited in Whitener, 2000). How an employee perceives the company and the work itself, are believed to be determinants of organizational outcomes, although they can be mutually exclusive employee traits

(Cesario & Chambel, 2017).

Employee Engagement

Employee engagement was initially defined as investment and authenticity of an employee’s personal engagement associated with his or her experience in the workplace

(Bailey, Madden, Alfes, & Fletcher, 2017). Employee or work engagement today has been defined as “a positive, fulfilling, work-related state of mind characterized by vigor, dedication and absorption” (Schaufeli, Bakker, & Salanova, 2006, p. 74). The term employee engagement has often been used interchangeably with the term job satisfaction.

“Job satisfaction has been defined as the measurement of an employee’s total feeling and attitudes towards their job” (Graham, 1982, p. 68). Engagement was believed to draw employees toward their work (Nimon, Shuck, & Zigarmi, 2016). 31

This topic has been extensively researched, and Gallup reports its close ties to financial performance, customer engagement and productivity outcomes, despite some

70% of employees believed to not be engaged at work (Sorenson & Garman, 2013).

Superior work performance was directly correlated with employee engagement (Cesario

& Chambel, 2017).

Because “engaged employees are vital for survival, sustainability and growth, organizational leaders increasingly cultivate this state among employees” (Agarwal et al.,

2012, p. 209). With its high stakes, employee engagement now has the attention of corporate chief executive officers and their teams, and companies are focused on workplace design, company culture, and flexibility in benefits offerings in the interest of improving engagement (Brown, Bersin, Gosling, & Sloan, 2016). Employee perceptions of opportunities for development afforded them by their employers demonstrate a positive correlation with engagement (Fletcher, 2016). What employees actually receive is more important than what they expect to receive with the finding that “delivered inducements contributing more to the prediction of employee satisfaction than did expected inducements” (Irving & Montes, 2009, p. 441). Creating a shared management responsibility for engagement with transparent reward mechanisms was vital to the development of a culture of engagement (Agarwal et al., 2012).

The Healthcare Work Environment and Burnout

Occupational burnout, driven by the significant and unique demands of a healthcare environment, can hinder quality improvements and patient satisfaction.

Burnout among healthcare workers, mainly medical staff, has become an occupational hazard, with its rate reaching between 25% and 75% in some clinical specialties 32

(Portoghese, Galleta, Coppola, Finco, & Campagna, 2014). Emergency room and primary care doctors risk burnout at a 50% rate over the course of their careers (Shanafelt

& Noseworthy, 2017).

Compliance demands and workplace elements alike, create unique pressure on nurses and doctors that contributes to burnout. These factors include shift requirements and long hours, multitasking, lack of management and of peer support, sleep deprivation, patient and family threats and the potential for violence, role ambiguity exposure to infectious diseases and biohazards, staff shortages, death, threat of malpractice, limited advancement opportunities (National Institute for Occupational Safety and Health, 2008).

“Burnout has been described as a psychological phenomenon encompassing chronic exhaustion, cynicism, and inefficacy that occurs due to chronic workplace stress”

(Portoghese et al., 2014, para. 2).

Six aspects of work-life act as the most important antidotes to burnout: a manageable workload, rewards, a sense of community, fairness, autonomy, and values.

When an employee discovers a mismatch between his or her expectations and the structure or process within the occupational environment, burnout was more likely to arise as a response to an inability to influence workplace stressors. Maslach and Leiter

(2008) proposed that leaders who are devising organizational interventions consider policies and practices that can shape the six aspects of work-life (Portoghese et al., 2014).

When burnout was not identified, or interventions not proactively adopted, employees and the organization can be adversely affected. In many studies, burnout has been linked to numerous deviant responses at work, including job dissatisfaction, lack of loyalty, turnover intention, and turnover itself (Maslach & Leiter, 2008). Burnout has 33 also been found to cause vacancy rates, with “24.2% of all hospitals having an RN vacancy rate higher than 10%” (NSI Nursing Solutions, Inc., 2015, p. 6).

Employee Loyalty and Turnover

Regardless of work-life interventions put in place by an organization, the foundational issue remains that employees are less loyal to their employers today than they have been in the past. As Elegido (2012, p. 496) explained, “Loyalty is a deliberate commitment to further the best interests of one’s employer, even when doing so may demand sacrificing some aspects of one’s self-interest beyond what would be required by one’s legal and other moral duties.” A decline in loyalty among employees and their companies may be attributed to rapid change and disruption in the workplace that has been represented by acquisitions, restructuring, and downsizing (Turnley et al., 2003).

Changing workplace demographics also add to the complexity of impacts tied to workplace disruption. This pattern has continued as the century has progressed, with nearly two-thirds of survey participants at companies with 1,000 or more workers considering employee loyalty to be in decline (Douglas, 2015). Companies can anticipate that at least 15% of their workforce was contemplating departure at any given time and will in fact depart if the unfavorable conditions they perceive are not mitigated (Mamun

& Hasan, 2017). “The leading reason for employees looking for external positions was higher compensation/pay (56%), followed by better overall benefits (29%) and career advancement opportunities (21%)” (SHRM, 2017).

Employers must determine what drives employees to have more loyalty toward their employers. Organizational commitment, an attitudinal affective relationship with one’s company, has been shown in research studies “to be a significant predictor of 34 turnover” (Jenkins, 1993, p. 84) and a more stable construct than job satisfaction in predicting turnover. Turnover was calculated by “dividing the number of employees who are no longer employed by the total number of employees still employed for a reporting period” (Hayes et al., 2012, p. 888).

The global nurse shortage was exacerbated by high turnover, according to

Rodwell et al. (2015). Nurse turnover drives significant organizational costs, and the cost of reducing turnover was found to be much less than the cost of turnover itself (Jones &

Gates, 2007; Mamun & Hasan, 2017). Mediocre and stellar employees, at the opposite ends of the spectrum in a workforce, have a greater inclination to leave their company voluntarily (Lee et al., 2017). When an employee resigns voluntarily, the company incurs more than the employee’s first year’s salary in recruitment and training costs. Other ramifications of turnover also manifest in the workplace. Voluntary turnover can elicit copycat behavior from peers, creating a spiral effect (Lee et al., 2017). In addition,

“turnover can sap the morale of remaining employees, add administrative time, and is disruptive to both organizational culture and structure” (Waldman, Kelly, Arora, & Smith,

2004, p. 6).

“One of the reasons that retention has been such a chronic problem in healthcare is that the work can be highly stressful, and the skills employed can be easily transferred to another similar organization” (PRWeb Newswire, 2014, n.p.). Because of the damage that lack of organizational commitment and turnover wreak on organizations, it has become important to understand why employees are less committed than in the past.

Ballard (2014) observed that layoffs, benefit cuts, and job insecurity caused by the 2009 recession damaged the employee–employer relationship, and employees have not 35 forgotten. Employer loyalty vanished as companies slashed benefits and laid off workers over successive years (Bradt, 2015). Shifting norms of professional obligation resulted, with the social contract valuing loyalty to oneself rather than to a collective (Rubin,

2012).

With self-loyalty now predominant, organizations are laser-focused on understanding how to appeal to employees to create mutual obligation and to reduce turnover. Turnover was recognized to be less likely in healthcare organizations that are focused on identifying as strong employers-of-choice (Rondeau et al., 2009); and with the employee–employer relationship at risk, organizations are seeking to demonstrate this attribute. Dissecting talent acquisition and retention strategies in America’s best companies can unlock the secret to keeping people and overcoming both work environment shortcomings and changing workforce expectations.

Competitive Advantage of Top United States Companies

Contemporary companies are faced with highly competitive and quickly transforming environments. Dynamic market factors including a global economy, technology, economic and political volatility, cyber-security risks have vastly impacted competition (Luthans & Sommer, 2005). The targeted investments in their talent management strategies made by many organizations has helped them drive the needed transformation to address the new global economic challenges. These strategies can help offset complex competitive issues and have been tied to broader business outcomes than merely tactically working to retain talent and fill open positions. The impact on employee attitudes of implementing human resource management (HRM) policies as part 36 of a broader talent management strategy was validated by Stroh and Caligiuri (1998) in their study of 60 multinational corporations.

Understanding the competitive differentiation that a company’s employees creates can determine the ultimate success of an organization. The strongest companies demonstrated human resource strategies that were closely linked to their company’s broader business strategy. Effective organizational structures and human resource strategy alignment fosters cumulative and differentiated skill sets in their employees that are not readily duplicated by competitors (Lewis & Heckman, 2006).

Nonstrategic hiring activities implemented without the necessary structure was sure to have detrimental results (Bock, 2015). But companies embark on a losing strategy when they attempt to compete on salary and benefits alone in our highly competitive market (Bryant & Allen, 2013). Companies across industries that are recognized for their top talent, listed in Fortune’s “100 Best Companies to Work For”

(2017) bolster their strategies with a more comprehensive approach and more strategic practices including (a) compensation and benefits; (b) recognition; (c) diversity; (d) communication; (e) camaraderie; (f) employee development; (g) advancement opportunities; and, (h) leadership practices, and delivery of stronger stock returns annually than their peers (Edmans, 2016). This holistic human resource strategy commitment was equally applicable to serving the stakeholders of America’s best healthcare companies.

Competitive Advantage of Top United States Healthcare Companies

Multiple entities generate top healthcare employer lists each year with a focus on providing these companies with recognition and to support recruitment efforts. Fortune 37

(2017) recently listed “The 30 Best Workplaces in Healthcare” based on feedback from thousands of employees. Respondents prized transparency and family environments at work, and they cited training-centric organizations twice as often as a “great place to work” (Frauenheim & Russell, 2017). Hospitals on this list had higher-than-average

Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) ratings and lower voluntary turnover scores (Peters, 2017). HCAHPS scores are the nationally recognized patient satisfaction scores that help hospitals to both manage government reimbursements and build their brands with consumers, demonstrating the linkage between happy employees and satisfied patients.

Most of the 30 highlighted companies are providing EAB of some kind, and those most coveted companies have a best practice providing educational opportunities in the workplace for employee convenience. Given increased linkages to outcomes, healthcare companies are committed to investing in their talent strategy to provide the necessary structure and resources to support their top talent, who will drive patient satisfaction.

Talent Management Practices

Talent management (TM), pioneered by human resource specialists and built on the base of long-term Human Resource Management (HRM) strategies, was bolstered by the War for Talent (Christensen, Hughes & Rog, 2008). However, a review of the TM literature highlights ambiguity about definition, scope, and the overarching objectives of this segment of human resources, and the industry would benefit greatly from a definition that has industry consensus (Lewis & Heckman, 2006).

TM has been viewed by some as an organizational mindset present in companies where employees are at the core of the culture: a source of clear advantage with 38 competitors (Christensen, Hughes & Rog, 2008). Collings and Mellahi (2009) defined strategic talent management as

activities and processes that involve the systematic identification of key positions which contribute to the organization’s sustainable competitive advantage, the development of a talent pool of high potential and high performing incumbents to fill these roles, and the development of a differentiated human resource architecture to facilitate filling these positions with competent incumbents and to ensure their continued commitment to the organization (p. 305).

Despite conflicting definitions and scant literature, documentation of the linkage among talent management and human resource protocols, and business performance was evident (Lengnick-Hall, Lengnick-Hall, Andrade, & Drake, 2009; Whitener, 2000; Fey,

Bjorkman, & Pavlovskaya, 2000; Delery & Doty, 1996;)), warranting an investment in talent management (Collings and Mellahi, 2009). Commitment from employees has largely been built on human resource practices (Whitener, 2000), which help an employer signal an interest in investing in their people, which may in turn create greater employee engagement (Alfes et al., 2013). Strong talent management systems and human resource practices within companies are thought to trigger employee motivation and extra effort

(Gittell, Seidner, & Wimbush, 2010). These systems and practices must comprehensively address all traditional human resource areas, including compensation and benefits, role specifications, learning and development, management oversight, succession planning, work-life balance, and employee loyalty. This broad range of organizational factors that drive employee retention has demonstrated a propensity to lower turnover intention, enhance productivity, and produce more loyal and satisfied employees (Coetzee & Stoltz,

2015).

Varying approaches, however, are required when it comes to designing and deploying a talent management strategy. Different talent strategies and management 39 approaches are being driven by the multigenerational workforce (Lub et al., 2016).

Creating unique strategies with differential treatment for top performers has also come into vogue (Christensen, Hughes & Rog, 2008), with the belief that significant rewards should come to top performers. This approach can improve retention of top-tier performers, but it must be handled ethically to avoid appearances of favoritism or discrimination.

Powerful TM and patient satisfaction linkages are now emerging. “When talent management teams prioritize recruiting and retaining high-quality employees, their organizations are in a stronger position to deliver high-quality care—translating into high levels of patient safety and satisfaction and overall organizational excellence” (PRWeb

Newswire, 2014, n.p.). Motivating employees to become more committed to their organizations is essential to performance, and companies are seeking new ways to develop the right type of organizational climate to increase motivation.

Employment Contracts

Astutely developed talent management architecture requires matching key positions with the right employees and overseeing their long-term loyalty to the company

(Collings & Mellahi, 2009). Commitment-based talent management practices, which can include employment contracts, create an organizational culture that motivates employees to deliver on the strategic imperatives of the organization, thereby enhancing performance (Gittell et al., 2010). Employers assume obligations when promises are made overtly to applicants and employees, or when a perception of a promise exists

(Rodwell et al., 2015). The old, implied employment contract where employees worked 40 for a single employer over their lifetimes has become a remnant of the past (Elegido,

2012).

Work-motivation ideologies of the past eighty years were part of a traditional social contract that evolved in American workplaces, producing stability in employment rates that Americans came to expect (Rubin, 2012). The American Dream emerged, promising limitless opportunity to those who worked hard (Chetty et al., 2017), and these workplace norms created mutual loyalty between workers and their employers. In contrast, “modern economic conditions put a premium on employer flexibility and employee mobility and have rendered an implied contract unviable” (Elegido, 2013, p.

495). Competition, demographic changes, and business globalization have additionally created the need for different types of jobs, companies, and products, which have also affected the employment relationship (Van der Vaart, Linde, & Cockeran, 2013). In many cases, employers benefit from having unpaid access to their people around the clock.

Employees have adjusted to the new normal of 24/7 access by their employers and customers, even though many organizations offer no returns or guarantees for a seemingly endless work day (Rubin, 2012). This shift has, however, vastly changed the employees’ view of their employers—and of the relationships overall. Disruption in the traditional employment contract has been driven by employers’ failures to live up to promises and commitments (Turnley et al., 2003).

With this market evolution, two types of employment contracts have emerged: a social contract and a psychological contract. A social contract was initially established on the set of norms, practices, and expectations deemed appropriate for stakeholders in workplace relationships. Some elements of this contract were driven by tradition, and 41 much of it remains protected by law, such as the Fair Labor Standards Act (FLSA). The old social contract was derived from taken-for-granted behaviors of social units and societal norms. Today, the social contract has forced companies to adapt to viewing their employees as volunteers and to the realization that given employees’ constant access to online websites, recruiters, and opportunities, employers must demonstrate greater appreciation in the form of a rewarding career and an investment for which they may not receive a return (Brown et al., 2016).

The psychological contract represents how individuals and companies view their relationship, and how expectations and assumptions that set the tone between employee and employer (Edwards & Karau, 2007) are established. It turns out that “the primary vehicle managers have for making firms successful is the psychological contracts they create with workers” (McDermott, Conway, Rousseau, & Flood, 2013, p. 290).

Psychological contracts represent unique workplace dynamics. Companies strategically use employee benefit policies and programs to provide guidance to their employees about the employee–employer relationship (Ko & Hur, 2014). Relational signals shared by company leaders and the informal organization may create confusion that complicates employee–employer efforts to meet the commitments to which they believe they are psychologically tied. Formal management of psychological contracts can also produce substantial improvement in employee performance and overall job satisfaction (Ho,

Rousseau, & Levesque, 2006). The dynamic evolution of workplace contracts was an inevitable outcome of the War on Talent and can prove to be a differentiator for companies seeking a competitive edge in meeting the shifting expectations of today’s workforce. 42

Shifting Expectations of the New Workforce

Shifting expectations of workers about their employers and workplaces have been attributed to this new global workplace and to advancing technology, but also to the multigenerational workforce. There are currently three primary generations in the workplace, according to Robert Half Management Resources (2010): Baby Boomer (born

1946–1964), Generation X (born 1965–1978), and Generation Y or Millennial (born

1979–1999). Today’s leaders are tasked with managing the widely varying expectations, values, and capabilities of the multigenerational workforce they serve (Wagner, 2017).

Employees of different generations have varying perspectives on the employee relationship and on their psychological contract, largely because of formative experiences

(Lub et al., 2016). Companies that have strategically modified their approach to meet the needs of a multigenerational workforce will reduce employee turnover, improve patient satisfaction, and deliver better patient outcomes (American Hospital Association, 2014).

Given the new workplace dynamics, employers will do well to tailor employee loyalty tactics which cater to a multigenerational workforce, and to continue to study which employer benefits are most valued by employees of all ages.

Employee Expectations of the Psychological Contract

Benefit expectations can vary among different employee groups, but they have certainly become more robust over time, based on what employees believe they are entitled to (Getz & Page, 2016). The phenomenon of entitlement has surged in recent years in both academia and industry, increasing the potential for negative impacts for employees, group interactions, organizational effectiveness, and workplace function, which in turn creates excessive costs (Jordan, Ramsay, & Westerlaken, 2016). Brummel 43 and Parker (2015) noted the lack of consensus about the definition of the word entitlement, but it was described by Holderness, Olsen, and Thornock (2016) as “a mindset of deserving success, promotions, admiration, and commendation without demonstrating the merit, high performance or qualifications to warrant such rewards” (p.

42). Entitlement behaviors surface as the result of an employee’s perceptions of privilege claims in a variety of settings (Tomlinson, 2013).

Entitlement research, largely focused on Generation Y or Millennial workers, has also been associated with professional athletes, company executives, educational environments, and college graduates, and was not unique to the United States

(Tomlinson, 2013). Research on Millennials shows that this group has expectations of being treated better than their older co-workers (Klimchak, Carsten, Morrell, &

McKenzie, 2016) and that its members have a “stronger sense of self-esteem and tend to be more narcissistic” (Miller & Konopaske, 2014, p. 808). Millennials have higher expectations of employers, tend to exhibit lower levels of commitment, and have no qualms about departing when their expectations go unmet (Lub et al., 2016). Conflict can arise among employees with different behaviors, values, and expectations, and it has been amplified with the trend of older nurses returning to the workplace due to their having longer life spans and dwindling retirement incomes (Sherman, 2006).

Parents raising the “trophy generation” and teaching approaches in recent decades are often blamed for the resulting narcissism and entitlement of an entire generation, but these behaviors are negatively correlated with performance or capability based on standardized tests (Laird et al., 2015). In addition to parents, corporations, with their ineffective performance management programs and their indulgence of this needy 44 generation with attention and excessive rewards and recognition, have also been blamed for enabling entitlement (Jordan et al., 2017).

Millennial expectation of rapid promotion was also validated by Smola and

Sutton (2002), who conducted a 1974 employee research study again in 1999, with the newer study revealing this expectation. Gen Y also expect to have authority and control in the workplace because of the power position they have historically held while growing up (Hurst & Good, 2009).

The construct of heightened entitlement surfaces through negative performance outcomes in the workplace, such as conflict and low satisfaction. Entitlement perceptions are widely recognized as powerful; they can affect how employees judge whether their employers have met the obligations of their psychological contract (Naumann, Minsky, &

Sturman, 2002). Although entitlement creates many challenges for leaders, scant literature exists on its workplace impact (Harvey, Harris, Gillis, & Martinko, 2014); however, one study found that “inverse relationships exist between entitlement and job satisfaction” (Miller & Gallagher, 2016, p. 114). Entitlement and turnover intention, conversely, are positively related (Laird et al., 2015). Millennials value personal development and their employers’ fulfillment of obligations more than their older counterparts do; nonetheless, the presence of these factors will not ensure Millennials’ loyalty (Lub et al., 2016).

The level of conflict in a company depends partly on how the company responds to changing employee expectations. As one research team put it, “The demanding nature of (this generation) regarding their career expectations and aspirations could be considered as being a catalyst for change which might result in more flexibility and 45 choice” (Barron, Leask, & Fyall, 2014, p. 246). Companies are increasingly trying to adjust to the changes an entitled mindset produces in the psychological contract of the new generation. According to Miller and Konopaske (2014), company employment protocols have changed considerably in response to employee entitlement, and the new generation’s workplace expectations are increasingly being met with accommodations.

Despite this, corporate practices such as recognition and performance feedback are deemed “out of step with this cohort” (Laird et al., 2015, p. 94). Controversy exists with organizations catering to employee expectations and granting perks to employees to create favorable reactions and improved employee satisfaction (Irving & Meyer, 1994,

1995; Irving & Montes, 2009). When companies “put their money where their mouth is,” employee engagement rises. Researchers must still more closely study entitlement, both to understand its origin and how it intensifies and to more effectively support today’s leaders in managing its related behavioral challenges by adopting theory and tactics to target entitled workers (Klimchak et al., 2016).

Benefit Preferences of Employees

Job seekers now prize benefits over their base pay (Greenfield, 2015), with the predominant members of this group being classified as “Millennials.” Millennials were predicted to become the predominant generation in the workforce by 2015; and by 2030, this highly educated, tech-savvy generation is expected to make up three-quarters of the available workforce (Mitchell, 2013). Companies may need to have an acute understanding of the motivational drivers of this new workforce if they are to become an employer of choice, engage the workforce, and keep turnover down. One study reports that “fringe benefits are critical to attract, retain and motivate employees who may 46 continue to work for organizational success” (Mamun & Hasan, 2017, p. 67). Employees at companies that offer excellent benefits are six times less likely to quit their positions than are those working for companies whose employees rate the benefits as mediocre

(Spencer & Gevrek, 2016). Millennials who feel that they have a voice in the workplace are less likely to depart their companies if they are not promoted quickly, and they greatly value training and development (Graves, 2012). Valuing job mobility over job security, this generation prizes growth over traditional incentives (Hurst & Good, 2009).

Consistent with Millennials, nurse executives of multiple generations highly ranked being valued and respected as professionals, along with career advancement opportunities, among other factors, as most important (Hayes et al., 2012). Some healthcare companies have already reacted to the newly emerging employee expectations and have consequently increased pay and benefits (Rondeau et al., 2009), because they recognize that insufficient reward increases their clinicians’ odds of burnout (Maslach &

Leiter, 2008). Understanding how employees prioritize rewards and incentives helps drive a comprehensive compensation and benefits program, a critical element of any engagement strategy.

The benefit preferences of Millennials are shared by two other generations in the workforce. According to “Top 20 Employee Benefits” (2017), about 60% of people report that they strongly consider benefits and perks when deciding whether to accept a job offer. The survey also found that 80% of employees would choose additional benefits over a pay raise. A full 87% of Millennials say professional development opportunities or career growth strategies are a top priority for them as they evaluate benefit packages

(Adkins, 2016). U.S. companies are beginning to understand how employees prioritize 47 benefits, with “16% of organizations increasing professional and career development benefits, and 14% increasing flexible working benefits in 2017” (SHRM, 2017). A recent study of 2,000 U.S. workers highlights how benefits are valued by job seekers, as shown in Figure 4 (Jones, 2017).

Figure 4. Which benefits are most valued by job seekers? (Jones, 2017).

Nearly half of this study’s respondents said that they would value student loan assistance and tuition assistance if they were offered as benefits, and employers reported that they value the outcomes of these benefit offerings (Jones, 2017). Employers offering these types of benefits should frequently highlight their investments in employees’ fiscal 48 health, using recruitment messaging to prospective employees and other internal employee communications to existing employees, because of their powerful motivational value among workers (Harmeling, 2013). Incorporating concrete valuation of EAB to the employee was a critical part of this messaging. As an example, the value of a college degree over a lifetime has been estimated at roughly one million dollars, based on a salary premium of about $15,000 annually for a college graduate versus a high school graduate (“Going for the Gold,” 2018). This was compelling information to provide to employees and applicants in promoting the developmental opportunities a company offers.

Educational Assistance Benefits (EAB)

Companies provide training in many forms, including advancing employee job knowledge and skills through EAB, defined as “a contractual arrangement between employer and employee that outlines specific terms under which the employer may pay for the employee's continuing education” (“Tuition Reimbursement”, 2018). Training was defined as

a set of planned activities on the part of an organization to increase job knowledge

and skills or to modify the attitudes and social behavior of its members in ways

consistent with the goals of the organization and requirements of the job (Landy,

1985, p. 306).

These collective investments in the professional development of employees range from

$16 billion to $55 billion, with this expenditure on the rise (Benson, Finegold, &

Mohrman, 2004). Lumina Foundation, 2016, reported that the number could be closer to

$180B when combining all talent development, training initiatives, and EAB. Training 49 investments made by companies for their employees have been shown to reduce turnover intention and to cause “employees to reciprocate through desirable work-related behaviors” (Memon et al., 2016, p. 411).

This professional development investment has often been made through EAB offerings that offset the high cost of a college education. Mercer, a global human resources consultancy, lumps together the coverage for certifications, training, and education in quantifying the benefit value, and EdAssist (2017), an administrator of EAB plans, maintains that EAB’s popularity was being driven by a full-employment market and the pressure to constantly enhance employee skills (Berman-Gorvine, 2017).

Accordingly, 61% of employers today offer a college assistance benefit for undergraduate programs, although these assistance programs vary considerably by company and across industries (Cherry, 2014).

Employers’ motivations for offering tuition investments vary. Employers’ frustration with the skill set of new graduates entering the workforce has become the norm, with only 11% of employers demonstrating satisfaction with their new hires’ skill sets (Craig, 2016), meaning ongoing training was needed. More than two-thirds of employers believe that employees entering the workforce after college will require more professional development to meet the critical-thinking, decision-making, teamwork, and written and oral communication skill demands of the modern business world (Hart

Research Associates, 2015).

Participating employers usually promote educational benefits to improve the loyalty of their existing employees, according to more than half of those employers surveyed (Held, 2017). Employers are also striving to enhance employee satisfaction, 50 keep employees current on newly emerging industry skill sets, and attract emerging talent to the company (Held, 2017). Productivity has been determined to be higher in EAB recipients, which was appealing to employers funding the education (Capelli, 2002).

Best-in-class companies are motivated to use EAB as part of their talent management strategy, recognizing it as a holistic element of employee engagement. The Internal

Revenue Service has provided an added financial incentive of up to $5,250 annually per employee to companies that add a tax-deductible element to their employee investments.

EDAssist (2017), an EAB plan administrator, highlights PepsiCo, among other major multinationals, in a case study for its strategic placement of EAB in its strategic talent management and development platform, demonstrating its overall benefit to employees.

With companies devoting significant amounts of their training and development dollars to EAB (ASTD, 2012), industry will benefit from quantifying the value of this investment—specifically, by determining the correlation of this employee benefit with employee engagement. Top outcomes of EAB are anecdotally reported to be the

“retention of existing employees (45%), keeping employees current on emerging skill sets (44%), enhancing satisfaction and loyalty (39%), and attracting future talent (16%), according to a recent survey of the International Foundation of Employee Benefits Plans"

(Held, Mrkvicka, & Stich, 2015, p. 6). Providing developmental opportunities to staff helps drive employee engagement (Fletcher, 2016) and reduces employees’ turnover intention (Mamun & Hasan, 2017).

Healthcare companies, specifically, recognize the value of instituting EAB plans.

Employers are seeking a more educated workforce to enhance their competitive advantage. More than half of human resource professionals are expecting a rise in 51 demand for candidates with a bachelor’s degree, while 41% of managers project an increase in the requirements for a master’s, doctoral, or terminal degree (Milford, 2014).

In a survey of 500 healthcare professionals, 69% observed an increased focus in their companies relative to employee education and development to facilitate the delivery of improved employee retention, and to improve patient safety rates (PRWeb Newswire,

2014).

EAB plans can also create administrative challenges for employers. Among the most common barriers to extending these benefits are employee disinterest and high costs. Plans must be carefully constructed to gain management support, ensure that compensated education applies to job roles, and provide the projected return, particularly with a less-loyal employee population. Global conglomerates can struggle with developing a universal EAB plan, which creates additional administrative challenges.

PepsiCo, as an example, values its single company-wide policy but reports having a streamlined and consistent process for how it administers and manages the program as a major success factor (EdAssist, 2017). More than two-thirds of employers discover that they experience problems when offering educational benefits (Held, 2017), rationalizing scrutiny of their administration, or outsourcing the activity altogether. While employers openly discuss challenges of offering EAB plans, their employees struggle to pay for college because of the rising costs of college education.

Cost of college versus tuition assistance caps. As companies seek to hone technical and leadership skills, they have found that providing tuition reimbursement to employees has been an excellent avenue to achieve this goal while increasing staff loyalty. Employees value tuition reimbursement because of the high cost of college 52 education and because ongoing professional development was important to most employees for career advancement purposes. College costs continue to rise more quickly than inflation rates, with four-year schools’ undergraduate tuition costs ranging from

$9,410 to $32,405 annually, excluding room and board, books, and transportation, according to the College Board’s 2016 Annual Survey of Colleges (see Figure 5).

Figure 5. Cost of 4-year undergraduate colleges. (College Board, 2016).

Tuition assistance covers a variety of programs, from one-day classes, to community college courses, to undergraduate and graduate degree programs. Bachelor’s degrees are most commonly covered (88%), then graduate degrees (87%), and associate’s degrees are at the lowest rate of coverage (69%, Miller, 2015). According to the

Association for Talent Development’s (ASTD, 2012), State of the Industry Report, companies spent $21.9 billion on EAB. This was an increase of 11% since 2010, representing 14.3% of the $86.5 billion spent on learning. This amounted to 83% of the organizations surveyed in the prior year offering some form of EAB to their staff

(Zillman, 2016, n.p.). 53

A wide range of caps is used in conjunction with EAB, and varying rationales were used by employers to set dollar limits on this almost standard benefit. Because the

IRS permits employers to allow deductions of up to $5,250 annually per staff member,

$5,250 tends to be a popular limit on employer-funded EAB plans for undergraduate and graduate studies, according to the Washington Post (“Best Employer Graduate Tuition

Reimbursement Programs,” 2016). Employees are eligible for the same deduction when receiving a maximum of $5,250 per year for tuition expenses from their respective employers and will likely find this benefit increasingly valuable, given the pending changes to taxation of graduate student tuition waivers (Figueroa, 2017). Many companies offering tuition reimbursement typically provide employees with about a thousand dollars per calendar year to pay for college. Yet, the average 4-year public college costs nearly ten times that amount annually (Roepe, 2016). As a result, employees need to seek multiple avenues to fund their educations, particularly at the graduate level. At this level, 44% of students take out loans, 25% have programs funded or partially funded by employers, and 20% have assistantships, while at the doctoral level, 50% of students have assistantships, 32% rely on loans, and just 13% are paid for by employers (Logue, 2012).

Some employers, seeking to prove that they are top-notch organizations, offer unlimited plans, albeit this is highly unusual. Six employers, as noted in Table 1, fall into this rare category. Although many of these are investing more than a million dollars per year in their program, the overall employee population in each of these companies is generally quite small. Participation rates in companies with more liberal EAB policies, however, do tend to surpass the average participation rates of companies that tend to 54 conform to the IRS limits of $5,250 or that provide even lower rates of coverage

(Zillman, 2016).

Table 1 U.S. Employers Offering 100% Tuition Reimbursement # of Participating Total Annual Cost of Tuition Company Name Employees Employees Reimbursement in 2015 Acuity 1,157 11.8% $99,000 Boston Consulting Group 2,943 10% Not disclosed ARI 1,431 9% $1,000,000 Burns & McDonnell 4,839 2.5% $755,000 EY 35,138 Not recorded Not recorded TD Industries 2,025 92%a $1,020,00 Note. Source: Zillman (2016). aMost employees required to take mandated certificate programs.

With Zillman (2016) reporting on just six U.S. companies offering 100% tuition reimbursement to their employees, it is unlikely that tuition will be reimbursed at this level by many other companies in the future. This degree of reimbursement remains rare and is most likely to be offered by a short list of coveted companies that have always prioritized employee benefit packages (Roepe, 2016).

Many companies choose not to subscribe to the 100% subsidy for tuition because they want their employees to have some accountability. The author of this study has experienced working with four major global corporations and has observed that all prefer their employees to have some “skin in the game”, causing them to offer partial EAB reimbursements with annual caps. Employers also quickly eliminate these benefits when times get tough (Landes, 2012) and are slow to return them to the benefits plan following a recession. 55

In addition to appealing to employees with the correct dollar amount of coverage, employers also need to make the reimbursement process for general and tuition expenses relatively quick and easy. An online survey determined that 73% of travelers had to wait

5 weeks on average to receive expense funds from their employers (Deluna, 2015). It would be tragic for an employer to offer a strong tuition reimbursement program and then have the process break down at point-of-payment, creating ill-will among recipients

(Deluna, 2015). The author of this study, drawing from her extensive experience in leading major U.S. corporations and having worked closely with most of the Fortune 500 companies, has observed past practices of corporations choosing to institute highly restrictive EAB plan policies and reimbursement practices in the interest of controlling expenditures. Strong EAB plans should employ effective administrative processes for application and payment and should boast strong participation or utilization rates.

EAB employee participation rates. Despite the significant portion of overall professional development costs and high dollar value investment attributed to EAB, participant or use rates are very low: less than 5% of the average company’s workforce

(Miller, 2015). A study of a major healthcare corporation showed a 5.8% utilization rate for its EAB Program, with the majority of the 2200 respondents categorized as Gen Xers and 77% of them female (Lumina Foundation, 2016). EdAssist (2017), a tuition assistance administrator for corporations that supports more than a million employees in tuition assistance programs, tracks companies that prepay tuition and notes that 40% of their customers prepay tuition for employees and experience an average 6.9% program use rate. The remaining 60% of companies that reimburse tuition after transcripts are submitted by employees see an average 4.1% program use rate, demonstrating that when 56 employees must initially pay “out of pocket” for their tuition expenses, participation goes down. New hires also typically participate at a greater rate than existing employees

(Manchester, 2012).

Speculation exists that companies strive to control participation rates and costs, with “confusion about the program’s value, difficulty in figuring out how to manage it and lack of internal promotion combine to keep participation low” (Scholarship America, n.d., n.p.). The low participation rates of this valuable benefit are curious and can be attributed to EAB policies, such as reimbursement after courses are completed, dependence upon the grade received, limitations to job-related subjects, and requirements for the employee to stay with the employer for a specified period after completing a degree (Breed, 2018).

Manipulation of participation rates by some companies warrant a broader assessment of

EAB policies, and how these policies are perceived by employees.

EAB policy structure. Education assistance benefits policies vary widely by industry and company size and should be linked to budget and program goals (Berman-

Gorvine, 2017). Some EAB plans cover only a small percentage of the costs incurred by students and are restricted to only a small group of classes, while some companies boast very liberal policies with no limitations. Bachelor and GED programs cost less than

MBA degrees and tend to result in better retention of employees upon degree completion

(Hassell, 2017), which can influence company policies on degree eligibility. A company’s EAB turnover rates are affected by how an EAB policy was structured

(Manchester, 2006), and turnover increases significantly upon completion of a company- sponsored graduate degree (Benson et al., 2004). Policies related to payment timing vary as well, with some plans paying schools directly; but this was an emerging benefit and 57 many employers still require employees to front the funds, earn a qualified grade, and then submit a reimbursement request (Berman-Gorvine, 2017).

Some degree of loyalty was expected of employees prior to their receiving a benefit, with more than half of American companies requiring an employee to complete one year of employment before they can receive such benefits (Cappelli, 2002). Both work performance and educational performance standards must generally be met before an employee was eligible for tuition reimbursement, and some companies require repayment if the employee quits his or her job shortly after completing the educational program.

New developments in workplace benefits related to a twist on conventional EAB has emerged with significant demand from employees to help them address their mounting student debt. “A growing focus by employers on a comprehensive approach to employee wellness, including financial health, reinforces the relevance of a student loan repayment benefit” (Oliver Wyman Corporation, 2017, p. 3). American Student

Assistance (2017) advised that the greatest financial stressor of today’s employees was their college loans, with 31% of employees in a recent study reporting that loans from college debt were far more problematic than home or car loans. Ninety percent of students with debt said a student loan repayment benefit would positively impact their decision to accept an offer, recommend an employer, or stay at their job

(Gradifi, n.d.). American Student Assistance’s study (2017), encompassing 52 employees and 541 human resource managers, revealed that 59% of millennials valued employer student loan repayments over employer 401k contributions, but only 16% of employers currently offer this prized benefit. Argento (2017) evaluated progressive companies 58 offering this new benefit and found that many of them offer $1,200 per year to help their employees pay off student loans. The federal government has agencies which reimburse up to $10,000 annually for an employee’s college debt, and the benefit caps out at

$60,000 (Argento, 2017). It was common practice for participating employers to reduce risk by paying the creditor directly for the loan repayment, according to Argento (2017), rather than compensating the employee for this benefit.

The new trend of employees valuing student loan repayment assistance benefits exemplifies the need for employers to continue to monitor the changing needs of employee populations and to change benefits plans to reflect this demand. Another area of exploration in EAB concerned dependents’ eligibility for EAB. Instituting or increasing tuition may have a strong ROI (Spencer & Gevrek, 2016), and being offered with a variety of related benefits such as student loan repayment or dependent coverage may provide employees with powerful incentives to stay with their respective employers.

Finally, scant research has been conducted on how EAB policies and their administration affect business outcomes, including EAB recipients’ attitudes toward their employer. Companies do realize the value of EAB, however, as was proven during the most recent recession, when 79% of companies maintained their EAB programs despite having to make cuts in many other employee benefit categories (IOMA, 2009).

Companies that demonstrate such a commitment to their workforces may expect something in return, particularly when the employment market becomes more robust.

Restitution obligation and enforceability. College courses, taken as part of an

EAB reimbursement plan, typically focus on general skills training that can easily be transferred to competitors, giving such training the potential to drive turnover 59

(Manchester, 2012). EAB recipients earning associate’s and bachelor’s degrees who demonstrate turnover intention will not be deterred with promotions, and those earning graduate degrees will have a greater interest in voluntary departure than will nonparticipants, whether promoted or not (Benson et al., 2004). Some 50% of employers accordingly require their employees to pay back their EAB reimbursement if they leave the company within a specified time after completing their degree (Miller, 2015). This was done through a written and enforceable agreement, so that the respective employers can control related retention rates and receive benefit from their investment, rather than allowing their competitors to benefit from it (Abramson & Hutman, 2008). Restitution obligations can “ameliorate intention to quit and act to hold a person in a job” (Firth,

Mellor, Moore, & Loquet, 2004, p. 181), while also creating alienation between the parties involved.

Use of third-party administrators. The evolution of EAB over recent decades has added to its administrative complexity. Although not all companies struggle with the administration of EAB, some fail to recognize that their administration processes could be improved with third-party support. Customized software can help in verifying educational receipts and speeding reimbursement to employees, but third-party administrators can also provide strategic value by sharing national benchmarking data, coordinating on policy creation and revisions, and developing recruitment and retention messaging for the programs (Berman-Gorvine, 2017). Some of these firms provide valuable coaching and mentoring to adult learners and can support the increase of 60 retention and graduation rates for employer-sponsored educational programs (Hassell,

2017).

Participant retention can be another value-add of third-party administrators.

Retaining students in their employer-sponsored programs can also be challenging, because of high rates of participation by nontraditional students who face conflicting demands of personal obligations and parents that may not appreciate the value of college, and may inadvertently undermine the employees’ efforts (Peters, Hyun, Taylor, & Varney,

2017). Nontraditional students are defined as having one or more of the following characteristics: (a) no high school diploma, (b) been out of school for several years,

(f) single parent (Peters et al., 2017). Strategies to retain this group of students, who replicate typical healthcare employee demographics, include building awareness of the shifting definition of nontraditional students, recognizing different learning styles, valuing proper academic preparation, providing an effective support network, and frequently advising communication with the use of varied technology (Peters et al.,

2017). Some third-party administrators have robust retention service offerings, while in other cases employers must deploy their own EAB recipient retention plans to preserve their investment and to prevent employees from quitting college prior to obtaining degrees.

The recent emergence of the student loan repayment assistance benefit was the genesis for Gradifi, a company which provides an end-to-end student loan repayment administrative service solution for companies offering the benefit to employees

(gradifi.com, n.d.). Gradifi (n.d.) claims that forty million American have a significant 61 student loan burden, and that their solution helps students pay off this debt with the help of their participating employer, thirty percent faster. The company offers services including loan repayment, student savings and loan refinancing plans to corporations. As this benefit becomes more common, a variety of competing companies are bound to provide a variety of services to simplify the eligibility, reimbursement and restitution processes required to support this evolving benefit.

Costs of outsourcing EAB administration vary and incumbent upon a participating organization to understand its own program needs, administrative cost structures, and resource availability before determining the need to engage a third party in this area.

This assessment should be part of a broader analysis of total EAB expenditures and must incorporate an evaluation of the hard and soft benefits that a company receives from offering an EAB plan.

Return on investment (ROI). Employers are also looking for ways to quantify their return on investment for tuition expenditures, which can be difficult because of a lack of records and multiple variables that drive employees’ engagement and retention rates. Furthermore, “many retention efforts are based on managerial gut instinct rather than research evidence” (Bryant & Allen, 2013, p. 171). No methodology for measuring the ROI of EAB existed until recently; and with the recent protocols established, other organizations will be able to measure the ROI of their programs to determine whether investments are sound (Lumina Foundation, 2016).

The general premise that EAB anecdotally reduces turnover was a sufficiently sophisticated measure for some employers to initiate EAB programs, with the assumption that lower turnover rates would help to subsidize program costs. Lower turnover rates 62 alone save money for employers and reduce recruitment, hiring, and training expenses

(Cappelli, 2002). Ensuring that an EAB program was part of an overarching talent management strategy with a focus on filling strategic openings, enhancing employee skills, or improving retention helps a company create a policy that dictates the type of programs that are reimbursable and the positions of employees that may be eligible

(Hassell, 2017).

The newest research for discerning the value associated with tuition reimbursement must be more substantive than an anecdotal or public relations statement and must be used to assess the actual ROI or rate of return of such programs. A rate of return supplies information about the efficiency of capital (Magni, 2015). Ninety-six percent of CEOs surveyed in a 2010 study showed that they had a high degree of interest in “the investments and impacts of their company’s Learning and Development initiatives” (Lumina Foundation, 2016). For one company, Cigna, that benefit was reported to be at least 129% between 2012 and 2014. For each EAB dollar invested by

Cigna, this healthcare payer covered their initial investment and reaped a return of an additional 129% of their TM funds (McCann, 2016). This study was the first of its kind in any industry and has already gained the attention of businesses around the country.

Moving from a cost center to an investment mentality was a huge evolution in the thought process for EAB administrators (McCann, 2016). In addition to company financial returns, the study also validated mobility of EAB recipients; it found 10% were more likely to be advanced and 7.5% were more likely to receive internal transfers

(McCann, 2016). Entry-level EAB recipients had strong compensation gains as well, with nearly a 60% wage hike over a 36-month period following the EAB acceptance 63

(Lumina Foundation, 2016). Although investing in the learning and development of workers creates costs for organizations, the clear link between that investment and the recruitment and retention of a demanding multigenerational workforce positions companies that make the investment for financial success (Schlitzkus, Schenarts, &

Schenarts, 2010).

This type of ROI data will help human resource departments continue to offer and bolster tuition reimbursement plans because they have hard data to present to their chief financial officers to tangibly support investment decisions. Substantiation of investments and EAB design innovations can also come from environmental scanning across sectors, including in other service industries, such as hospitality and tourism.

Unique models for EAB in hospitality and tourism. The healthcare industry can benefit from looking to the hospitality and tourism industry, which has similar workplace attributes, for benchmarks in EAB policies and practices. This service industry faces unique challenges in attracting and retaining large numbers of entry-level employees, much like the healthcare field, and recognizes the linkage between employee engagement and customer satisfaction. EAB was highlighted as a core employer strategy to support the advancement and retention of employees in a study sanctioned by the

President’s High Growth Job Training Initiative (DTI Associates, Inc., 2006).

The hospitality and tourism industry has made recent strides in implementing cutting-edge EAB programs, including Hilton Hotel’s 100%-reimbursed employee GED

Program, launched in 2015 for all full-time employees who have completed 6 months of service or more (Miller, 2015). Marriott provides tuition reimbursement even at the graduate level, and InterContinental Hotels (IHG) provides EAB reimbursement and 64 flexible schedules for staff so that they can attend college (Peltier, 2014). Disney

Corporation pays liberal reimbursement per credit hour, all expenses for books, and up to

$100 per course taken for applicable materials required (Zhang, 2014).

Hospitality and other service employers are embracing a new model of educational partnership to deliver EAB to their employees. According to Otto (2014), more than one-fifth of companies contracted with academic institutions, as did government employers. Employees have fewer options regarding academic programs as a result, but they may find the classes more tailored to their needs and more beneficial to their professional development (Otto, 2014). The latest industry partnership has been launched with Pearson and its AcceleratED Pathways program, with ten hotel companies contracting on behalf of their 1500 locations to offer complimentary degree programs to their employees (AHLA, 2018).

JetBlue and Starbucks have both implemented new tuition assistance programs tied to single universities that they have respectively sought partnerships with. The

JetBlue Scholars Program, in partnership with Thomas Edison State University, requires eligible employees to pick up $3,500 of the tuition expenses while the corporation pays the balance. Employees who have 2 years of tenure with the company and have completed 15 college credits are eligible for the program (Kieler, 2016). JetBlue had not yet announced any program outcomes as of 2018.

Starbucks provided its employees a traditional EAB program until June 2014 that offered up to $1,000 a year to cover education-related costs, but the company found that this benefit was insufficient for engaging its workforce (Roepe, 2016). The new program, Starbucks College Achievement Plan, partnering solely with Arizona State 65

University’s online programs in 40 approved majors, was flexible and covers all costs beyond those paid by university grants or scholarships and federal loans. Employees qualifying for the Starbucks program must work at least 20 hours each week. Employees are not required to stay at Starbucks following graduation or to pay any restitution to

Starbucks when they depart to another employer. The Starbucks program has had 7,000 enrollees since 2014; the first Starbucks class of 120 employees graduated in 2016, and an additional 260 graduated the next year (Dahlstrom, 2017). Starbucks has reported improved retention and promotion rates among its participating employees, although it has not disclosed these metrics (Roepe, 2016).

Hypotheses Context and Theoretical Underpinnings

The literature review above demonstrates that engagement and retention of employees has been a complex and dynamic undertaking. From the shifting expectations of a multigenerational workforce, to organizations’ desired 24/7 contract with employees, to psychological contract theory, one can begin to understand the intricacies of the relationship between a company and its employee. What follows are an explanation of the context of the hypotheses of the project and the theoretical underpinnings that inform them, beginning with protocols in human resource management and the relationship these have on company performance and moving through the mapping of PCF, employee engagement and turnover intention variables.

HRM Practices and Organizational Performance

“High performance” or “high commitment” Human Resource Management

(HRM) practices, including offering equitable and competitive compensation and training and development tactics, are intended to “motivate employees to adopt discretionary 66 behaviors in line with organizational goals” (Giauque, Anderfuhren-Biget, & Varone,

2013, p. 126). Human Resource Management has “evolved to being seen as a strategic partner and value-added contributor to the overall effectiveness of the organization . . . contribut(ing) to the work climate, performance, and overall effectiveness of the organization” (Luthans & Sommer, 2005, p. 328). Creating and deploying effective

HRM practices, such as flexible incentives for professional development, helps a company exceed expectations of their workforce and helps deter employees from exiting to a competitor (Lim & Ling, 2011). High-performance organizations provide professional development for their employees to drive motivation and enhance skills (Ma

& Chang, 2013). Adopting HRM practices that foster employee engagement has been beneficial to organizations (Caesens, Stinglhamber, & Marmier, 2016). Best-in-class employers must be proactive in benchmarking and communicating their practices so that employees perceive them as differentiators as opposed to what competitors offer

(Gardner et al., 2015).

PCF

Coyle-Shapiro and Kessler’s (2000) 8-item PCF scale was used in in the survey instrument to measure PCF. Samples of statements to which participants were requested to respond included: “I receive the necessary training to do my job well”; “I receive support when I want to learn new skills”; and “I have good career prospects.” Morrison and Robinson (1995) and Robinson et al. (1994) used similar scales and demonstrated good reliability and validity. 67

Benefits and PCF

“In terms of offering and fulfilling psychological contracts,” reported Gardner et al. (2015), “employers must ensure that they are offering a sufficiently rewarding employment experience” (p. 948) that meets employees’ expectations. Employers can create greater employee satisfaction when providing employee developmental opportunities (Coetzee & Stoltz, 2015). Employees often perceive the psychological contract differently from their employers, and these perceptions can either be highly motivational to employees or cause disgruntlement (Robinson, 1996). Employees have a low tolerance level when they are unable to reconcile what they expect to receive versus what they ultimately receive (Lester & Kickul, 2001).

PCF and Employee Engagement

Hypothesis 1 states that PCF has an impact on employee engagement. Employee behaviors are improved when companies deliver on extrinsic commitments (such as

EAB) to employees (Lester & Kickul, 2001). When obligations are met, workers become more engaged and productive; moreover, engaged employees perform discretionary behaviors at no additional cost to the employer (Kasekende, 2017). Failure on the part of the company to fulfill the psychological contract results in reduced employee engagement. The relational contract was found to be more likely to be linked with engagement than was the transactional contract (van Elste & Meurs, 2015). 68

Turnover Intention

The researcher used Irving et al.’s three-item (1997) scale, which was widely validated by applying Meyer, Allen and Smith’s (1993) three-dimension organizational commitment model across numerous industries to measure turnover intention. Irving et al. found that “the overall fit indexes for the 3-factor model exceeded .90” (p. 447). Scale items included: “I intend to stay in this job for the foreseeable future”; “I will probably look for a new job within the next year”; and “I do not intend to pursue alternate employment in the foreseeable future.” “An increased focus on internal and external validity in all empirical studies can only help the field of educational research by helping investigators to be more reflective at every stage of the research process” was asserted by

Onwuegbuzie (2000, p. 54).

PCF and Turnover Intention

Hypothesis 2 states that PCF has a negative relationship with turnover intention.

When employees’ psychological contracts are fulfilled, they are less interested in leaving their employers, even in an environment of increased mobility (Lester & Kickul, 2001).

The reason is that “employees’ motives to stay with their employing organizations are often grounded in perceived guarantees from the organization” (Rodwell et al., 2015, p.

689).

Employee Engagement

The researcher employed Schaufeli et al.’s (2006) scale to measure employee engagement. Schaufeli et al. showed that this 9-item scale has good reliability and lower survey abandon rates. Statements requiring response included: “At my job, I feel strong 69 and vigorous” and “I get carried away when I am working.” Engaged employees stay with their employers, while just 12% of disengaged employees made the same claim”

(Christensen, Hughes & Rog, 2008, p. 750). Excessively high employee engagement, although no specific measure exists for it, was not beneficial to turnover intention.

Caesens et al. (2016) challenged the assumption that employees who were strongly engaged would not consider leaving their organizations; these researchers have determined that excessive employee engagement does not heighten a reduction in turnover intention.

Employee Engagement and Turnover Intention

Hypothesis 3 states that employee engagement has a negative relationship with turnover intention. Organizations whose employees are engaged “have greater profitability, shareholder returns, productivity, and customer satisfaction” (Memon et al.,

2018, p. 408). Employees are motivated by receiving rewards, which in turn increases engagement and reduces turnover intention (Caesens et al., 2016; Kasekende, 2017). In one study, “sixty-six percent of highly engaged employees reported . . . an intention to

Hypothesis and Conceptual Model

“A hypothesis is a statistical procedure to obtain a statement on the truth or falsity of a proposition, based on empirical evidence; this is done within the context of a model, in which the fallibility or variability of this empirical evidence is represented by probability” (Cook & Weisberg, 1999, p. 7121).

This study contains the following three hypotheses:

H1: PCF has an impact on employee engagement.

H2: PCF has a negative relationship with turnover intention.

H3: Employee engagement has a negative relationship with turnover intention.

The conceptual model that depicts this study can be seen in Figure 6.

Figure 6. Hypothesized model.

Conceptual models are popular in healthcare research and often show causal linkages of numerous variables with the rationale for why human phenomena occur

(Kim, Kaye, & Wright, 2001) in this rapidly changing environment. In this model, PCF was the independent or predictor variable and was hypothesized to be related to its dependent variables, employee engagement and turnover intention.

CHAPTER 3. METHODS

The methods chapter includes a methodology summary of the research design along with the data collections and analysis process used to test the selected hypotheses.

An electronic survey instrument was used in this cross-sectional study of healthcare workers to ascertain the relationships between psychological contract perception and employee outcomes (employee engagement and turnover intention). The chapter provides an overview of the sampling and study design process, the survey instrument, data collection, and analysis.

Sampling and Study Design

Leveraging psychological contract theory, the original study design was to evaluate EAB applicants’ attitudes toward their healthcare employer, using EAB as the independent variable. Using this variable, the study intent was to understand the mediating effect of PCF on the relationship between accepted EAB applicants and their self-reported employee engagement and turnover intention. During the study, EAB had to be eliminated as the independent variable due to one-sided analysis resulting from the very low percentage of rejected applicants (8.6% of respondents) returning survey responses. The PI additionally attempted to conduct focus groups and in-person interviews with individual rejected applicants, but no one responded to the multiple requests for feedback. Psychological contract was then modified to become the independent, rather than mediating variable, with employee engagement and turnover intention retaining their model position as dependent variables.

A cross-sectional study was selected because of its efficiency, and its advantages—(a) cost-effectiveness; (b) a quick data collection process; and, (c) ability to 72 determine attributes of a large population from a subset—were substantiated by Creswell

(2009). Cross-sectional studies have their limitations, and Raineri, Humberto Mejia-

Morelos, Francoeur, and Paille (2016) cautioned, “Cross-sectional studies warrant methodological precautions to limit and control for common method variance. In contrast, longitudinal designs have an advantage in that they can verify the stability of the observed mediation effects over time” (p. 56). A longitudinal study was not selected because of time and expense constraints and because this study was based on the sponsoring company’s interest in checking the pulse of its employees through a one-time survey assessment process while keeping employees’ identities confidential.

Study Sample

A large nonprofit healthcare system in the Western part of the United States was selected for the study. This system was chosen because it was representative of large

U.S. healthcare systems and its research-oriented culture, its linkage with a major medical school, and its patient- and employee-centric culture. This healthcare entity has more than twenty community-based hospitals in multiple states, with an employee population exceeding forty-eight thousand employees. Its interest in the study stems from its strong focus on employee engagement and its annual EAB investment ranging from $3.7–$4.9 million between 2011 and 2016.

The corporation has actively offered an EAB Program to its employees for more than seven years and has conducted annual employee engagement surveys throughout this period. The hospital system’s goals in offering an EAB Program were to enhance patient care, improve employee recruitment and retention, and prepare employees for promotional opportunities within the company as part of its succession plan and by 73 advancing their job skills. Eligible educational programs included associate’s degrees, bachelor’s degrees, master’s degrees, doctoral degrees, and post-graduate certificate programs. Employee eligibility for the program was based on the employee’s having worked for the corporation for at least 6 months, being a full-time or part-time employee, attending a regionally accredited institution, acquiring pre-approval of reimbursement, completing the educational component in a timely manner, and currently undergoing no corrective action for performance issues. A maximum reimbursement of $5,250 per year, consistent with Internal Revenue Service (www.irs.gov) limits for tax-deduction status for both employees and employers, was made available to employees, according to the company policy.

The healthcare system uses an EAB decision matrix to review applications. The matrix was used to evaluate applicants based on a point system tied to the following criteria: company tenure, degree pursued and field of study, most recent performance rating, talent mapping (leadership positions only), corporate talent initiatives special focus, facility talent initiative special focus, and facility prioritization of applicants.

The study was conducted by having hospital system’s Human Resources department administer an online survey on behalf of the principal investigator (PI) in the fall of 2017. The company identified healthcare employees in 27 job classifications who were current or past EAB recipients, or who had applied to the company’s EAB plan at any time since 2011 and who had been rejected. The total target population was 1,200.

In anticipation of missing data, including nonresponse, a sufficient population should be used to “allow for collection of data from more than the required sample to adjust for the expected amount of data” (Fichman & Cummings, 2003, p. 282). Because the 74 organization was able to provide qualified participants, screening validation was not required by the PI prior to survey distribution.

Internal Review Board Approval

A draft survey was initially created by the PI. The PI provided the draft instrument to the healthcare organization, and the human resources team added a few questions to the survey, predominantly pertaining to the company’s EAB policy and administrative practices, and organizational commitment. An informed consent document was included at the beginning of the survey to introduce the study purpose to respondents, and to confirm that the study was voluntary and that their anonymity was ensured. The survey instrument and informed consent document were reviewed by the two doctoral committee co-chairs and approved to submit to Iowa State University’s

(ISU’s) Institutional Review Board (IRB) Office for approval to ensure respondents’ rights were protected (Creswell, 2009). To this end,

The IRB advises investigators in designing research projects that minimize potential harm to participants, reviews all planned research involving human participants prior to initiation of the research, approves research that meets established criteria for protection of human participants, and monitors approved research to ascertain that participants are being protected. (Iowa State University Institutional Review Board, n.d.)

These documents were submitted with an IRB exemption form; full IRB review was not requested because of the study’s design, which did not include studying vulnerable populations or revealing individual responses to the employer. To clarify the informed consent information and survey purpose, the PI distributed the draft Informed

Consent document and survey to a dozen colleagues for general feedback. The colleagues were selected based on their having extensive industry and academic experience, and all had a strong familiarity with EAB programs. All participants reported 75 that questions were clear, concise, and unambiguous. The IRB Office granted the researcher approval to proceed with the survey under the exempt study parameters in

October 2017, which was prior to a pilot survey being conducted.

Survey Instrument

The study questions were designed to collect interval data with a focus on the following key metrics: employee engagement scores, employee turnover intention, and

PCF perceptions. The online survey (see Appendix C) contained 53 questions, including an attention check question, a question that provided respondents an opportunity to provide subjective feedback, and general demographic questions. Attention checks, developed by Likert (1932) to avoid receiving stereotyped responses, help improve data quality (Abbey & Meloy, 2017).

The study continued in a linear fashion. First, the Informed Consent document was provided to explain the study’s purpose and to confirm anonymity of participants.

Next, the survey section began with a series of five general questions clarifying respondents’ submittal of an EAB application, whether they had applied and been accepted into the program, whether they had graduated from their degree program as of the survey date, and whether they had received a promotion from the organization post- graduation. Determining whether a respondent had participated in the EAB was a dichotomous variable, and for those who stated that they had not participated, this response ended their involvement in the survey process.

The next two major sections included a series of questions that were focused on employee views related to EAB polices and program administration, and employee entitlement. The sponsoring organization chose these questions based on its interest in 76 understanding employee perceptions of the company’s EAB-related policies and administrative practices, and unique generational views. Results from these two sections, along with a training question and two turnover question responses were evaluated separately from the main study and provided to the sponsor. The PI incorporated an attention check in the instrument, requiring respondents to enter the number “10” in a text box. Attention check questions are generally used to isolate respondents who are not reading questions carefully or are answering questions too quickly and could adversely affect response quality (Vannette, 2017). Next, eight questions were listed that represented the PCF scale (Coyle-Shapiro & Kessler, 2000). A three-question Turnover

Intention Scale (TIS-3; Irving, Coleman, & Cooper, 1997) and a nine-question Employee

Engagement Scale (Utrecht Work Engagement Scale UWES-9; Schaufeli et al., 2006) comprised the next two sections, which were followed by an opportunity for respondents to write subjective comments about the EAB. The final portion of the survey was dedicated to demographic questions.

Demographic questions. Eight general demographic and job classification questions about age, gender, marital status, race, tenure, title, education level, and salary range were included at the end of the survey. The demographic questions were requested to be included by the sponsoring organization as part of their standard protocol, although the responses were excluded from the data analysis. This project included both a pilot study and a main study. The survey tool can be observed in Appendix C.

Reliability and Validity

The reliability and validity of both the study and the measurement models affect study conclusions, and measures must be taken to address reliability and validation 77 concerns. Throughout the research process, threats must continually be examined by investigators to allow for correction, as found by Creswell (2009):

Internal threats are experimental procedures, treatments or experiences of the participants that threaten the researcher’s ability to draw correct inferences from the data about the experiment’s population. External validity threats arise when experimenters draw incorrect inferences from the sample data to other persons, other settings, and past or future situations (p. 162).

The reliability and validity of a survey tool provide confidence that bias and data distortion issues are absent (Fitzner, 2007).

Reliability

Litwin (1995) noted that “reliability is a statistical measure of how reproducible the survey instrument’s data are” (p. 6), and was dependent on consistent measurement

(Fitzner, 2007). When examining for reliability issues, it was important to minimize error. Random error can occur in the sampling process, and measurement error can be attributed to the instrument selected for the population (Litwin, 1995). Creswell (2009) also disclosed the potential for response bias arising in response to participation rates; such bias can be exposed by respondent/nonrespondent analysis (Creswell, 2009).

Validity

Validity of the survey is equally important. Hammersley (1987) introduced validity as “the property of a measure that allows the researcher to say that the instrument measures what he says it measures” (p. 73). “An experiment is deemed to be valid, inasmuch as valid cause-effect relationships are established, if results obtained are due only to the manipulated independent variable (i.e., possess internal validity) and are generalizable to groups, environments, and contexts outside of the experimental settings

(i.e., possess external validity)” (Onwuegbuzie, 2000, p. 6). According to Winter 78

(2000), construct validity controls data type and the data collection process. The use of previously validated constructs helps establish validity in the study design phase, and then “the ability to generalize findings to wider groups and circumstances is one of the most common tests of validity” (p. 10) following analysis.

Construct validity risks can be assessed through criterion validity, discriminant validity and convergent validity (Henseler, Ringle & Sarstedt, 2015). Criterion validity checks for alignment with your device and other methodologies in measuring similar attributes and their outcomes, while convergent validity validates if there was strong correlation with the same item being measured in different ways (Fitzner, 2007).

Discriminant validity confirms the unique nature of a construct (Hair, Black, Babin &

Anderson, 2006), and commonly exists in latent variable model studies (Farrell, 2010).

Lower correlation levels result in statistical validation (Henseler et al., 2015), and “to satisfy this requirement, each construct’s average variance extracted (AVE) must be compared with its squared correlations with other constructs in the model” (Henseler et al., 2015, p. 116). Hair et al., 2006 maintain that in this comparison, “the variance extracted estimates should be greater than the squared correlation estimate” (p. 778), to avoid having “predictive power over dependent variables” (Farrell, 2010, p.324).

Confirmatory Factor Analysis (CFA) Testing

Nunkoo (2015) explains how reliability and validity testing fit in the broader process, “of extreme importance is ensuring the reliability and validity of the measurement model, and then once the assessment is deemed reliable and valid, the structural model is tested” (p. 2). The selection of confirmatory factor analysis (CFA) as the statistical methodology can be used to assess the selected measurement scales’ 79 reliability and validity (Carmines & Zeller, 1979). Al-Refaie (2015) provided an alternate tool to CFA for this purpose, observing, “Cronbach’s alpha can be used to assess scale reliability” (p. 298). Once CFA was estimated, it was vital to determine that the model closely matches the observed data (Albright, 2008); “failure to reject the null is therefore a sign of a good model fit” (p. 5).

Common Method Bias

Common method bias poses a significant risk in cross-sectional studies and was defined as “systematic error variance shared among variables, introduced as a function of the same method and/or source” (Richardson, Simmering, & Sturman, 2009, p. 763); focused effort was required to avoid it. This systemic error can result in conclusions that mislead stakeholders (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). Due to the risk posed by common method bias, a thorough assessment of the research setting was warranted throughout the study to statistically mitigate bias potential (Podsakoff et al.,

2003). Common method bias has generally been attributed to measurement error rather than to study construct selection, and failure to test for common method bias and correct through study design and statistical methodology can lead researchers to inaccurate conclusions (Min, Park, & Kim, 2016). Common method bias has the potential to increase or decrease the relationships among constructs (Podsakoff et al., 2003). As

Podsakoff et al. (2003) noted,

Conditions often present in behavioral research which are most likely to create method biases are present in studies in which the data for both the predictor and criterion variable are obtained from the same person, in the same measurement context and with similar item characteristics. (p. 885)

Reliability and Validity Testing Conducted within Study

Conducting a face validity test with peers, the employer organization and committee; conducting common method bias testing; incorporating an informed consent process; maintaining anonymity of respondents; employing a sufficient sample size exceeding 20 cases for each predictor variable; conducting a pilot study; and selecting validated scales from disparate sources tested by discriminant validity, and with CFA and

Cronbach’s Alpha (using Statistical Package for the Social Sciences or SPSS AMOS, version 24), all contribute to greater validity and reliability in this study.

Construct Validity

Construct validity, aligning measuring procedure with the hypothesis (Fitzner,

2007), heightens study accuracy. Valid and reliable constructs, not deemed excessively correlated based on discriminant validity testing, were selected in this study to improve the validity and reliability of the study findings. Constructs included PCF, employee engagement and turnover intention.

Pilot Survey Process

Qualtrics, a leading online survey tool, was selected to design and distribute the survey. The draft Qualtrics survey instrument was distributed by the healthcare company’s Human Resources Department to 40 randomly selected EAB applicants as a pilot phase on 2 days preceding the main study, because of strict timelines mandated by the sponsoring organization. Ten applicants, or 25% of the pilot population, responded to the survey, representing a diverse demographic except for gender. Eighty-seven percent of pilot survey respondents were female. One respondent’s survey was deemed ineligible and eliminated because the applicant denied having applied to the EAB program at the 81 company. The raw data of the remaining 9 applicants were reviewed. The mean duration for survey completion was 7.57 minutes, shorter than the anticipated time of 10–15 minutes, which resulted in reducing the time estimate for survey completion on the informed consent document for the main study. All respondents except one answered all survey questions. The sole partial respondent failed to answer the age and education questions. A question confirming whether an applicant’s application was approved or rejected was added to the survey post-pilot because the sponsoring corporation was unable to provide data filtered by acceptance status. The sponsor preferred that this information be self-reported to provide additional protection of anonymity in the survey process. The pilot survey did not afford the delineation of applicant acceptance or rejection, representing a material difference from the main study survey and preventing a statistical analysis from being conducted on the pilot data. An attention check question was added to the main study survey following the pilot survey process, to improve the survey reliability (Vannette, 2017).

Data Collection Process

The main study survey was conducted, following noted revisions, between

November 30 and December 8, 2017. One reminder notice was sent via email from the sponsoring organization to the sample population on December 4 to encourage them to participate. Survey participants were advised that they could choose to participate, that their individual responses would be kept confidential, and that their responses would have no impact on their current or future eligibility for EAB or on their employment generally. Respondents were informed that data would be tabulated in aggregate to be shared with the Human Resources Department and the company leadership team so that 82 the corporate EAB policies and administration practices could be reviewed. After the survey period, the Human Resources Manager from the organization emailed the raw data to the PI; this data contained no personally identifiable information, in concert with IRB regulations.

Data Analysis Process

A multistep data analysis process proceeded, including: (a) data cleansing;

(b) validity and reliability testing (CFA and Cronbach’s alpha); (c) model fit assessment

(CFI, root mean square error of approximation (RMSEA), NFI, IFI, and PNFI;

(d) assumption testing (normality, homoscedasticity, independence, and absence of multicollinearity); (e) correlation matrix assessment; and (f) hierarchical multiple linear regression with sensitivity analysis.

A code book was first established to represent raw data, with numerical values assigned to all Likert scale responses and demographic information so that responses could be loaded into SPSS 24. Next, data were screened for data entry errors, and missing data were addressed. Study design and analysis processes should be thoughtful so that missing data do not adversely affect results. Missing data rates in social behavioral research have been commonly 15–20%; when data are missing, it “introduces bias in parameter estimation and weakens the generalizability of the results” (Dong &

Peng, 2013, pp. 1–2). Because of the potential for missing data among responses, it was important that the sample size be substantive enough to compensate for nonresponses

(Fichman & Cummings, 2003). Although list-wise deletion (LD) was once popular, its use was now much less prevalent, and multiple-imputation (MI) was a sound alternative

(Dong & Peng, 2013). Multiple-imputation was defined by Newman (2014) as “a state- 83 of-the-art missing data routine when partial respondents exceed 10%” (p. 397); it was conducted with SPSS. Descriptive statistics were next evaluated to establish means and standard deviation calculations for survey dimensions along with frequencies and percentages for the independent variable and the survey demographic questions.

Validity and reliability testing of the primary study variables was then conducted, using CFA and Cronbach’s alpha. The development of CFA addressed a gap in Cohen’s

(1968) multiple regression method, with an ability to measure latent constructs (Marsh,

Morin, Parker & Kaur, 2014). Cronbach’s (1951) reliability test determines the degree of error that it contains. According to Tavakol and Dennick (2011, para.3), “Internal consistency describes the extent to which all the items in a test measure the same concept or construct and hence it is connected to the inter-relatedness of the items within the test.”

Determining the presence of correlation among the variables should precede the regression analysis. “Correlation does not prove causation; however, the absence of correlation implies the absence of the existence of a causal relationship,” noted Cohen,

Cohen, West, and Aiken (2013, p. 7). Parametric testing was conducted using Pearson’s correlation coefficient to test for validity and provide r statistic and statistical significance for interval-level variables. The latter determines whether the correlation was caused by random sampling error. Validation of the correlation between model variables must be conducted prior to using regression techniques to demonstrate causation (Kim et al.,

2001). Pearson’s correlation has been the most popular means of quantifying a relationship between two variables, with “correlation and prediction being closely connected concepts” (Hayes, 2013, p. 28). 84

To test hypotheses and provide greater insights after the correlation analysis, hierarchical multiple linear regression analysis was conducted (Rebekic, Loncaric, &

Petrovic, 2015). Analysis proceeded using SPSS Version 24 to validate the causal relationships among variables. In organizational behavior research, hierarchical regression was often chosen as the mode of statistical analysis (Rosopa & Stone-Romero,

2008), particularly where “theoretically based hypotheses” (Petrocelli, 2003, p. 9) are present. Hierarchical regression was described as a “sequential analysis process, whereby predictor variables are added to analysis in stages, and their effects are evaluated after controlling for other variables” (Lewis, 2007, p. 10). A detailed analysis of the findings may be found in Chapter 4.

CHAPTER 4. RESULTS

Study results are summarized in Chapter Four, beginning with an overview of main study respondents and their demographic characteristics. Validity, reliability, and assumption testing was conducted next, following by correlation and regression results.

Study Respondents

A total of 298 employees, elected to participate in the survey in November and

December 2017, representing a 25% response rate. The instrument was developed using a 5-point Likert (1932) scale, which included “an equal number of favorable and unfavorable statements in surveys so that respondents may determine their level of agreement with a subject” (McIver & Carmines, 1981, 22–23). No variance in regression analysis results regardless of the point-scale chosen (Dawes, 2008).

Thirty-five of the respondents failed to complete the Informed Consent section or declined to accept it, which was termed a unit-level non-response (Dong & Peng,

2013). Seventeen additional respondents failed to complete the survey in its entirety, termed an item non-response (Dong & Peng, 2013), or abandoned it immediately after agreeing to give their informed consent. All respondents answered the attention check question correctly. Respondents who did not provide the necessary consent or who chose not to respond to the survey were removed from the dataset, resulting in a total of 244 net participants or 20.33% of the total population of 1200.

MI was selected to address missing data, recognizing that Dong & Peng (2013) stipulate a 15-20% missing rate common in this type of study. Data from the net respondents were assessed with the missing completely at random (MCAR) test (Little,

1988) conducted in SPSS. This analysis tests the null hypothesis that the actual pattern of 86 missing values was not significantly different from an expected pattern of values that are missing completely at random. The result of the MCAR test was not significant, χ2(138)

= 156.26, p = .137, showing that the data can be assumed to be missing completely at random. Based on guidance from Hair, et al., (2010) for MCAR data, missing values were imputed using the regression method in SPSS, employing the SPSS Imputation command.

Demographic and Job Classification Profile

Table 2 displays frequencies and percentages for categorical variables and sample characteristics. Most of the participants were women (n = 204, 83.6%), White (n = 195,

79.9%), and married (n = 186, 76.2%). The largest proportion of participants was between 35 and 44 years old (n = 87, 35.7%). The most common level of education among participants was a bachelor’s degree (n = 112, 45.9%), and the most common income bracket was $60,000 to $89,999 (n = 118, 48.4%). Most participants indicated that they had graduated from their program (n = 151, 61.9%). Of the participants who answered the question about receiving a promotion, the largest proportion indicated that they had not been promoted (n = 88, 36.1%). Finally, the largest proportion of participants had a job classification of RN (n = 86, 35.2%) or that of Manager/Supervisor

(n = 68, 27.9%), and most participants had either 4–9 years of experience (n = 81, 33.2%) or 10–14 years of experience (n = 80, 32.8%).

Table 2

Sample Characteristics

Variable Frequency Percent

Type of educational program

Certificate Program 5 2.0

Associate's Degree 18 7.4

Bachelor's Degree 111 45.5

Master's Degree 104 42.6

Other 6 2.5

Missing/No response 0 0.0

Graduation status

Yes 151 61.9

No 19 7.8

Program still in process 74 30.3

Missing/No response 0 0.0

Promotion status

Yes 61 25.0

No 88 36.1

Promotion is in process 2 0.8

Missing/No response 93 38.1

Table 2. (continued)

Variable Frequency Percent

Gender

Male 29 11.9

Female 204 83.6

Other 2 0.8

Missing/No response 9 3.7

Race

African American 8 3.3

Asian 5 2.0

Hispanic 11 4.5

White 195 79.9

Mixed race 13 5.3

Missing/No response 12 4.9

Marital status

Single (never married) 24 9.8

Married 186 76.2

Separated 3 1.2

Widowed 3 1.2

Divorced 21 8.6

Missing/No response 7 2.9

Table 2. (continued)

Variable Frequency Percent

Age

18 to 24 years 1 0.4

25 to 34 years 39 16.0

35 to 44 years 87 35.7

45 to 54 years 66 27.0

55 to 64 years 41 16.8

Missing/No response 10 4.1

Job classification

Manager/Supervisor 68 27.9

Director 29 11.9

VP/C-suite 2 0.8

LPN/CNA 3 1.2

RN 86 35.2

Other Clinical Role 44 18

Missing/No response 12 4.9

Tenure

1-3 years 14 5.7

4-9 years 81 33.2

Table 2. (continued)

Variable Frequency Percent

10-14 years 80 32.8

15 years + 63 25.8

Missing/No response 6 2.5

Education level

Completed some high school 1 0.4

High school graduate 1 0.4

Completed some college 17 7.0

Associate's degree 31 12.7

Bachelor's degree (e.g. BA, BS, BBA) 112 45.9

Master's degree (e.g. MBA, MHA, MPA) 74 30.3

Terminal degree (e.g. MD, JD, PhD) 1 0.4

Other advanced degree beyond a Master's degree 1 0.4

Missing/No response 6 2.5

Salary range

Less than $30,000 8 3.3

$30,000 to $59,999 45 18.4

$60,000 to $89,999 118 48.4

$90,000 to $119,999 51 20.9

Table 2. (continued)

Variable Frequency Percent

$120,000 to $149,999 4 1.6

$150,000 to $179,999 3 1.2

$180,000 + 1 0.4

Missing/No response 14 5.7

Measurement Model

The validity and reliability of the measures for the main study variables (i.e., psychological contract, employee engagement, and turnover intention) were examined using discriminant validity, confirmatory factor analysis (CFA) and Cronbach’s alpha, respectively. The CFA was conducted using SPSS AMOS. A measurement model was constructed for latent variables of psychological contract (represented by eight observed variables), employee engagement (represented by nine observed variables), and turnover intention (represented by three observed variables). Discriminant validity was conducted, calculating average variance extracted (AVEs). AVEs of .50 or greater indicate good validity (Fornell & Larcker, 1981). Covariances between each latent variable were modeled. Fit indices (CFI, RMSEA, χ2/df, NFI, IFI, and PNFI) were computed to assess the measurement model fit. A CFI of .90 or greater and an RMSEA of .08 or less, a χ2/df less than 5, a NFI of .95 or greater, an IFI of .90 or greater, and a PNFI greater than .50 indicate good fit (Meyers, Gamst, & Guarino, 2016; Schumacker & Lomax, 2010; Ko,

2015; Paek, Schuckert, Kim & Lee, 2015). 92

It was more challenging to obtain a good model fit when working with a larger sample size (Gaskin, 2011), and the initial measurement model did not demonstrate good fit (CFI = .78, RMSEA = .12, χ2/df = 4.76, NFI = .74, IFI = .79, PNFI = .65).

Modification indices were examined to determine whether model fit could be improved.

The modification indices showed that three pairs of error terms for latent variable indicators could be correlated to result in a better model fit, and AMOS provided a list of covariances that could be added to improve model fit. Covariances were added for the error terms for the following pairs of items based on the modification indices of the initial model: psychological contract questions 5, 6, 7 and 8, and engagement questions 1 and 2.

The revised model demonstrated improved fit (CFI = .87, RMSEA = .10, χ2/df = 3.22,

NFI = .83, IFI = .88, PNFI = .72), approaching or exceeding required standards for good model fit. The AVE in this measurement model for psychological contract was .33, falling below the recommended threshold. To correct for this, the model was revised by dropping lower loading items from the psychological contract scale to achieve an AVE of

.5 or higher. This correction process resulted in a decision to remove psychological contract questions 5 through 8. The resulting model demonstrated improved fit (CFI =

.94, RMSEA = .08, χ2/df = 2.42, NFI = .90, IFI = .94, PNFI = .75), approaching or exceeding required standards for good model fit. The resulting AVE for psychological contract changed from .33 to .56. To further improve the fit of the model, items with loadings less than .60 (psychological contract questions 3 and 4, and engagement questions 6, 7, and 9) were removed, and negatively-worded survey items (turnover intention questions 1 and 3) were reverse coded to resolve for issue with negative loadings. The resulting model demonstrated improved fit (CFI = .98, RMSEA = .06, 93

χ2/df = 1.88, NFI = .96, IFI = .98, PNFI = .70), exceeding required standards for good model fit. Factor loadings are presented in Table 3, and the AVEs, squared correlations,

Cronbach’s alphas, and composite reliabilities of the final measurement model are presented in Table 4. The AVEs for psychological contract, turnover intention, and engagement were .88, .72, and .64 respectively, indicating that the constructs had good convergent validity. The squared correlations among constructs were all below the

AVEs, indicating discriminant validity. Cronbach’s alphas and composite reliabilities were all higher than .70, demonstrating sufficient reliability (George and Mallery, 2016).

Table 3

Factor Loadings for Constructs

Constructs Factor Loading Mean Std. Deviation Skewness Kurtosis

Psychological Contract 1 0.89 2.98 1.18 0.06 -1.09

Psychological Contract 2 0.98 3.07 1.18 -0.05 -1.13

Turnover Intention 1 0.91 2.23 1.05 0.77 0.09

Turnover Intention 2 0.85 2.55 1.25 0.43 -0.88

Turnover Intention 3 0.78 2.63 1.16 0.25 -0.95

Employee Engagement 1 0.76 3.42 0.93 -0.38 -0.34

Employee Engagement 2 0.81 3.57 0.89 -0.63 -0.06

Employee Engagement 3 0.88 3.94 0.88 -1.12 1.64

Employee Engagement 4 0.88 3.87 0.90 -0.99 0.97

Table 3. (continued)

Factor Loadings for Constructs

Employee Engagement 5 0.79 3.57 1.01 -0.66 -0.20

Employee Engagement 8 0.67 3.98 0.81 -0.86 1.16

Table 4

Results of Adjusted Measurement Model

Construct Psychological Turnover Intention Employee

Contract Engagement

Psychological 0.88 .17 (-.42) .06 (.24)

Contract

Turnover Intention 0.08 0.72 .32 (-.56)

Employee 0.05 0.06 0.64

Engagement

Cronbach's Alpha 0.94 0.88 0.92

Composite 0.94 0.88 0.91

Reliability

Notes: The values of AVE are along the diagonal. Squared correlations among latent constructs are above the diagonal. Correlations among latent constructs are within parentheses. Standard errors among latent constructs are below the diagonal.

Composite scores were created by averaging the responses to the items pertaining to each variable, except in the case of psychological contract where the responses to the items were combined in concert with the recommendation of the instrument authors 95

(Coyle-Shapiro & Kessler, 2000). Means and standard deviations of the composite scores computed for each measure are displayed in Table 5.

Table 5

Means and Standard Deviations for Study Variables

Variable Number of Items M SD

Psychological contract 2 6.06 2.29

Engagement 6 3.73 0.76

Turnover intention 3 2.47 1.04

Assumptions

Assumptions of hierarchical multiple linear regression were tested in this study to confirm reliability and validity. The statistical assumptions of hierarchical multiple linear regression include normality, homoscedasticity, independence, and absence of multicollinearity (Hair et al., 2010; Stevens, 2009; Tabachnick & Fidell, 2013). The assumption of normality mandates observation of normal P-P plots (see Figures 7 and 8) and that the testing demonstrate that regression residuals are normally distributed. No significant data deviations were observed from the normal line (diagonal), indicating that assumption of normality was met. The assumption of homoscedasticity mandates that the data be approximately evenly distributed across variables’ values; this was tested by visual observation of scatterplots of residuals (Gaskin, 2015), as shown in Figures 9 and

10. The data were approximately evenly distributed along the fit line, indicating that assumption of homoscedasticity was met. Additionally, survey respondents only responded to the survey one time each, so independence was met. 96

Figure 7. Normal P-P plot for Regression 1.

Figure 8. Normal P-P plot for Regression 2. 97

Figure 9. Residuals versus predicted values for Regression 1.

Figure 10. Residuals versus predicted values for Regression 2. 98

Finally, hierarchical multiple linear regression requires that independent variables not be overly correlated with one another. Multiple regression requires testing for presence of multicollinearity to avoid the potential for the correlation of hypotheses to be positive definite (Fichman & Cummings, 2003). Multicollinearity reduces predictive strength (Hair et al., 2010) and potentially creates “wide swings in parameter estimates

. . . and the numerical solution of a model, which can prove severe and sometimes crippling” (O’Brien, 2007, p. 673). Multicollinearity was evaluated using variance inflation factors (VIFs). The VIF, which affects tolerance, defines degree of variance among independent variables, and a strong dependence increases the variance (O’Brien,

2007). The VIFs for all regressions were below 10 (see Tables 7 and 8), which Stevens

(2009) suggested as ideal for regression coefficients.

Study Results

Prior to conducting the primary analyses, a correlation matrix was constructed for the main study variables (see Table 6).

Table 6

Pearson Correlations Between Study Variables

Variable 1 2

1. PCF -

2. ENG .25* -

3. TI -.38* -.49*

Note. PCF = Psychological contract fulfilment; ENG = Engagement; TI = Turnover intention. *p < .01. 99

Regression 1

To address Hypothesis 1, which states that PCF has an impact on employee engagement, a linear regression was conducted. The dependent variable in this analysis was employee engagement. The independent variable in this analysis was psychological contract. The results of the regression are displayed in Table 7.

Table 7.

Linear Regression Predicting Engagement

Std. Variable B Beta t Sig. VIF Error

Psychological contract 0.09 0.02 0.25 4.09 < 1.00

.001

The results of the regression were significant, F(1, 242) = 16.74, p < .001, R2 =

.07, indicating that psychological contract was significantly related to engagement.

Psychological contract was significant positive predictor (B = 0.09, p < .001), indicating that participants with high psychological contract tended to have high engagement. The regression significance indicates that Hypothesis 1 was supported.

Regression 2

To address Hypotheses 2 and 3, which respectively suggest that PCF has a negative relationship with turnover intention, and that employee engagement has a negative relationship with turnover intention, a hierarchical multiple linear regression was conducted. Hierarchical multiple linear regression was chosen for this study because 100 it supports the PI’s need to determine the added influence of different sets of predictor variables (Tabachnick & Fidell, 2013). In standard multiple linear regression, all predictor variables are entered in the model concurrently, which does not allow the PI to establish if significantly more variance in the outcome is explained by one independent variable rather than what is explained by another independent variable. The dependent variable in this analysis was turnover intention. Psychological contract was entered in the first step of the regression, and engagement was entered in the second step of the regression. The results of the regression are displayed in Table 8.

Table 8

Hierarchical Multiple Linear Regression Predicting Turnover Intention

Std. Variable B Beta t Sig. VIF Error

Step 1

Psychological contract -0.17 0.03 -0.38 -6.37 < 1.00

.001

Step 2

Psychological contract -0.12 0.03 -0.27 -4.92 < 1.07

.001

Engagement -0.57 0.08 -0.42 -7.51 < 1.07

.001

The results of the regression at Step 1 were significant, F(1, 242) = 40.58, p <

.001, R2 = .14, demonstrating that psychological contract was significantly related to 101 turnover intention. The addition of engagement at Step 2 contributed 16% additional explained variance, which was a significant increase (p < .001). The overall regression model at Step 2 was significant, F(2, 241) = 53.16, p < .001, R2 = .31, indicating that the collective set of variables at Step 2 was significantly related to turnover intention.

Psychological contract (B = -0.12, p < .001) and engagement (B = -0.57, p < .001) were significant in the final step, indicating that participants with high psychological contract and engagement tended to have low turnover intention, representing an inverse relationship. The regression significance at steps 1 and 2 demonstrate that Hypotheses 2 and 3 were supported. An examination of the standardized estimates revealed that engagement (Beta = -0.42) was the most influential predictor at the final step.

Summary of Hypotheses

The survey analysis supported Hypotheses 1-3. The specific findings were as follows, as depicted in Table 9:

H1: PCF has an impact on employee engagement. This hypothesis was supported

by Regression 1, which showed that PCF was a significant positive predictor

of engagement.

H2: PCF has a negative relationship with turnover intention. This hypothesis was

supported by Regression 2, which showed that PCF was a significant negative

predictor of turnover intention and has an inverse relationship.

H3: Employee engagement has a negative relationship with turnover intention.

This hypothesis was supported by Regression 2, which showed that

engagement was a significant negative predictor of turnover intention.

102

Table 9

Summary of Hypotheses

Hypothesis Analysis Result Hypothesis Conducted Supported? H1. PCF has an impact Linear Overall regression was Yes on employee engagement. regression significant, and PCF was a (Model 1) significant positive predictor at α = .05 H2. PCF has a negative Hierarchical Overall regression was Yes relationship with turnover multiple significant, and PCF was a intention. linear significant negative predictor regression at α = .05 (Model 2)

H3. Employee Hierarchical Overall regression was Yes engagement has a multiple significant, and engagement negative relationship with linear was a significant negative turnover intention. regression predictor at α = .05 (Model 2)

Chapter Summary

This chapter presented the results of the data analysis conducted to address the hypotheses of the study. Characteristics of the sample were described, and the validity and reliability of the measures for the study variables were presented. The statistical assumptions of the analyses were tested and fulfilled. A linear regression and a hierarchical multiple linear regression were conducted to address the hypotheses. The results of the regression analyses supported Hypotheses 1-3. Chapter 5 will contain a discussion of these findings, including limitations and recommendations for future research.

103

CHAPTER 5. DISCUSSION

This chapter provides a summary discussion based on the study results. This introduction summarizes the study purpose and then follows with a summary of findings, interpretation and implications of findings, study limitations, and future research opportunities.

The purpose of this research was to evaluate perceptions of a healthcare system’s

EAB applicants to discern whether their PCF has been fulfilled, and how this impact related to business outcomes. Using a social exchange theory construct and evaluating employees’ attitudes toward their employer through the lens of psychological contract theory, the data analysis was completed using a linear regression and hierarchical multiple linear regression analysis. This study has important implications for the healthcare industry, which currently faces burnout, turnover, and staff shortages driven by increased volume and retention issues. In addition, the study has important theoretical implications due to the scant PCF research on business outcomes in the healthcare field.

Summary of Findings

All three study hypotheses were supported. PCF is a significant positive predictor or employee engagement, with the study showing that employees who expressed PCF had higher levels of employee engagement. Those with the strongest fulfillment tended to have the highest level of engagement. Engaged, fulfilled employees were less inclined to claim turnover intention. These findings are consistent with those of Caesens et al.

(2016) and of Kasekende (2017), which showed that employees are motivated by receiving rewards, which in turn increases engagement, and reduces turnover intention. 104

Interpretation of Findings

Practical Implications of Study

As companies compete heavily for talent, it is important that they understand how to increase employee loyalty to deliver business outcomes. This study further substantiates investment in programs and policies that serve to create PCF. Practitioners must find ways to sustain PCF among employees and understand its impact on employee engagement and its inverse relationship with turnover intention. Because “engaged employees are vital for survival, sustainability and growth, organizational leaders increasingly cultivate this state among employees” (Agarwal et al., 2012, p. 209).

There are three major ways that organizations can impact outcomes through employee development and other human resource practices. Gallup suggests

“Administering an (engagement) survey to at least 1000 people with a response rate of

80% or higher, and to demonstrate a clear link between engagement and business outcomes” (as cited in O’Boyle & Harter, 2015, n.p.). SHRM (2017) cautions that employee surveys can create expectations for employees, so survey purposes and timelines for change should be proactively communicated. “Conducting an audit of all

HRM in relation to evidence-based practices” (Christensen-Hughes & Rog, 2008, p. 755) was advised.

Benchmarking against other companies, ensuring that rewards align with company mission and values, regularly assessing costs and benefits, and ongoing program and evaluation are all best benefits practices for organizations to deploy (SHRM,

2017). Maintain a consistent process for measuring engagement and empower leaders who could affect engagement (Barnett, 2015). 105

Organizations in healthcare and other complex, compliant-heavy, transformative service industries can leverage these findings to drive business outcomes, as this study provides insight about how employee benefits, policies and practices impact PCF, employee engagement and turnover intention. In addition, this research “answers repeated calls for more effective collaboration between academic researchers and practitioners” (James et al., 2011, p. 190).

Theoretical Implications of Study

This study contributes to the scant PCF literature in healthcare and how it impacts business outcomes. The existing literature defining the causes of PCF in the workplace

(Rodwell, Ellershaw, & Flower, 2015) and the reasons for the high rate of voluntary employee turnover (Memon, Salleh, & Baharom, 2016) has been insufficient. Study results were consistent with the findings of Caesens et al. (2016) and of Kasekende

(2017), although their studies were not based exclusively on healthcare employee perceptions. No other studies were identified which evaluated the influence of PCF on employee engagement and turnover intention outcomes in a healthcare setting.

However, “a significant body of work in other disciplines demonstrates relationships between work engagement and positive organizational outcomes” (Keyko, Cummings,

Yonge & Wong, 2016, p. 143).

This research area also provides ample opportunity for scholars and industry to partner in advancing studies in this area. Future studies should examine if demographic factors play a role in relationships among the variables. More research is warranted particularly in the arena of turnover intention, due to varying response to context, such as industry type (Lee et al., 2017). 106

PCF

The literature states that endeavoring to fulfill PCF can help employers retain employees (Van der Vaart et al., 2013; van Stormbroek & Blomme, 2015) This study corroborated these findings. PCF was shown to be a significant positive predictor of engagement, in accordance with H2, and has a negative relationship with turnover intention, in accordance with H3. Failure to fulfill the psychological contracts resulted in reduced employee engagement. When employees’ contracts are fulfilled, they are less interested in leaving their employers, even in an environment of increased mobility

(Lester & Kickul, 2001). This finding is material in a full employment market, where employees are in high demand. Employees are seeking employers that recognize their individualized differences and are willing to personalize the employment experience in return for reciprocal loyalty (Karagonlar et al., 2016). Promises made by corporate recruiters must also be evaluated to understand whether they are establishing realistic expectations with new hires and how this initial interaction sets the tone for PCF (Collins,

2010). Evaluating employee expectations must continue beyond the recruiting phase, and throughout the employee’s tenure with a company (van Stormbroek & Blomme, 2015).

Employee Engagement

“Sixty-six percent of highly engaged employees reported in a study an intention to stay with their employers, while just 12% of disengaged employees made the same claim,” reported Christensen Hughes and Rog (2008, p. 750). Engaging a workforce clearly pays dividends relative to employee retention. This study confirmed past research findings focused on employee engagement (Memon et al., 2016; Firth et al., 2004). 107

Concrete evidence linking engagement with company financial outcomes provides incentive for organizations to invest in engagement (Schaufeli et al, 2009).

These investments must be customized to target employee needs. “A ‘one-size fits all’ approach to employee engagement might not be the most effective”, and

“managers should find out what resources and benefits are most desired by employees and most likely to create a sense of obligation that is returned with greater levels of engagement.” (Saks, 2006, p. 614). Yohn (2018) concurs that building employee loyalty in generic ways and targeting all employees homogenously was typically not effective.

Creating a shared management responsibility for engagement with transparent reward mechanisms was vital for developing a culture of engagement (Agarwal et al., 2012).

Turnover Intention

Role stagnation and lack of a clear career path are instrumental in driving turnover intention (Chamberlain, 2017), and employers can positively impact both these engagement risks by supporting employee development efforts for their people. Training investments made by companies for their employees have been shown to reduce turnover intention and cause “employees to reciprocate through desirable work-related behaviors”

(Memon et al., 2016, p. 411).

Study Limitations

This study was limited to a cross-sectional study within one U.S. healthcare system, which likely limits its generalizability. A 2-week data collection period was not sufficient to unequivocally demonstrate causality (Karatepe & Demir, 2014). The sample size, while sufficient for this study, was not conducive to extensive sub-group analysis, which a larger sample size could afford. Although the survey sample included employees 108 from 27 job classification, the respondents were predominantly middle-aged, female registered nurses. It could be argued that the high percentage of nursing respondents make the findings more generalizable due to their vast numbers in healthcare organizations and other sectors, and the role that they serve relative to outcomes. In addition, data was self-reported.

A disproportionate share of respondents were recipients or accepted applicants

(91.4%), rather than rejected applicants. This participation element required additional analysis to improve the model fit and confirm the accuracy of the findings.

Albeit reflective of the sponsoring organizations’ demographics, the lack of diversity among respondents was a limitation that did not allow for a more comprehensive assessment of Millennial PCF perceptions. Theory can be advanced significantly by closely studying the millennial workforce that is 76 million strong.

Because of significant conflicting projects in the sponsoring organization, the PI was not afforded a sufficient gap between running pilot and main studies to analyze data and make instrument changes, given that main study survey dates immediately followed pilot completion. Completion of the survey was conditional upon following the employer’s protocols and timing restrictions.

Future Research Opportunities

This study may provide a basis for additional research on the impact of EAB benefits within the context of broader business outcomes across industry sectors.

Additional research can determine if EAB, offered in conjunction with other benefits, was proven to be a predictor of PCF, or if EAB has the potential to positively impact employee engagement with or without the mediating influence of PCF. Careful study 109 design will be necessary to ensure relatively equal representation from accepted and rejected applicants, to better understand the value of EAB. Further evaluation of rejected applicants and their employer perceptions are needed, and these participants must be handled with sensitivity to encourage their participation.

The perpetual nature of the psychological contract requires its ongoing study, and interpretations by the stakeholders involved vary, warranting additional research (Wu &

Chen, 2015). More must be understood about the causes of PCF in the workplace

(Rodwell et al., 2015) if companies are to continue to drive levels of employee engagement and reduce turnover intention. PCF allows employees to deliver better on- the-job performance, according to Turnley et al. (2003). “Future research can examine the influence of perceived organizational support, leader–member exchange, or human resource management practices on psychological contract types to integrate organizational support theory and social exchange theory with psychological contracts theory” (Chang et al., 2013). Evaluating psychological contract breach and its impact on employee engagement and turnover intention may be valuable in understanding how employees perceive having their benefit requests rejected. Declining employee loyalty also makes delving into this research area more important for employers (Turnley et al.,

2003), because the reduction of turnover intention can have dramatic impacts on business outcomes. It would also be interesting to learn whether pay increases that follow degree completion by EAB recipients was linked with PCF. Finally, the importance of understanding the implications of employee engagement on healthcare quality and patient safety means the topic warrants more research (Simpson, 2008), particularly because regulatory influences continue to increase the demand for accountability in these areas. 110

Replicating this study in other settings, in varying contexts, and with diverse demographics will further test variable relationships and contexts (Karagonlar et al.,

2016; Lee et al., 2017). Conducting a longitudinal study in another industry sector, across multiple companies, may prove more revealing relative to generational nuances with EAB, “as longitudinal studies comparing different generations at specific life stages may show that there are actually more similarities than differences among generations at various life stages (i.e., baby boomers during establishment, Generation Y during establishment, etc.)” (Dulebohn et al., 2009, p. 88). Future research studies can also evaluate other outcomes, such as employee productivity and performance, boss perceptions and attendance.

As workplace demographics continue to shift, ample opportunity exists “for human resource managers to manage a multi-generational workforce with potentially different perspectives on the employment relationship and on how employees perceive the psychological contract they have with their organization” (Lub et al., 2016, p. 653).

Replicating this study in an employment setting largely composed of millennials may provide unique insights about changing employee perceptions. Observations could be made as to whether Millennials are less likely to demonstrate PCF and employee engagement and are more likely to voice turnover intention, and whether they are fulfilled by EAB investments of their employers. Employers can increase the loyalty of their workforces by understanding employee perceptions, and by proactively creating and administering policies which become competitive differentiators in their battles to win the

War on Talent. 111

REFERENCES

30 best workplaces in healthcare. (2017, April 12). Fortune. Retrieved from http://fortune.com/2017/04/12/best-companies-health-care/

100 hundred best companies to work for. (2017). Fortune. Retrieved from http://fortune.com/best-companies/

Abbey, J., & Meloy, M. (2017). Attention by design: Using attention checks to detect inattentive respondents and improve data quality. Journal of Operations Management, 53(56), 63–70. doi:10.1016/j.jom.2017.06.001

Abramson, G. A., & Hutman, D. (2008). Tuition assistance for a transitory workforce: How to avoid getting an “education” when you pay your employees’ tuition. Employee Benefit Plan Review, Sept. Retrieved from https://www.lexology.com /library/detail.aspx?g=8016b2f8–3e45–4ba6-bccc-0a79b59bad2c

Adams, J. (1965). Inequity in social exchange. Advances in Experimental Social Psychology,2, 267-299. doi:10.1016/S0065-2601(08)60108-2

Adkins, A. (2016, May 11). What millennials want from work and life. Gallup. Retrieved from http://www.gallup.com/businessjournal/191435/millennials-work-life.aspx

Agarwal, U., Datta, S., Blake- Beard, S. & Bhargava, S. (2012). Linking LMX, innovative work behaviors and turnover intentions: The mediating role of work engagement, Career Development International, 17(3), 208-230. doi: 10.1108/13620431211241063

Age wave: Retiring Baby Boomers create succession planning imperative. (2014). Becker’s Hospital Review. Retrieved from https://www.beckershospitalreview .com/hospital-management-administration/the-age-wave-retiring-baby-boomers- create-succession-planning-imperative.html

Akgunduz, A., & Sanli, S. (2017). The effect of employee advocacy and perceived organizational support on job embeddedness and turnover intention in hotels. Journal of Hospitality and Tourism Management, 31, 118–125. doi:10.1016 /j.jhtm.2016.12.002

Albright, J. (2008). Confirmatory factor analysis using AMOS, LYSROL and MPLUS. The Trustees of Indiana University. Retrieved from http://www.iu.edu/~statmath /stat/all/cfa/cfa2008.pdf

Alfes, K., Shantz, A.D., Truss, C., & Soane, E. C. (2013). The link between perceived human resource management practices, engagement and employee behavior: a moderated mediation model. International Journal of Human Resource Management, 24(2), 330–351. doi:10.1080/09585192.2012.679950 112

Al-Refaie, A. (2015). Effects of human resource management on hotel performance using structural equation modeling. Computers in Human Behavior, 43, 293–303. doi:10.1016/j.chb.2014.11.016

American Healthcare Association. (2018). Staff stability. Retrieved from https://www.ahcancal.org/quality_improvement/qualityinitiative/Pages/Staff- Stability.aspx

American Heritage Dictionary. (n.d.) https://ahdictionary.com/word/search.html?q=commitment

American Hospital Association, Committee on Performance Improvement. (2014). Managing an intergenerational workforce: Strategies for healthcare transformation. Chicago, IL: Health Research & Educational Trust Retrieved from http://www.aha.org/managing-intergenerational-workforce

American Hotel & Lodging Association (AHLA). (2018). Hotel industry partners with Pearson to offer debt-free college degrees to employees. Retrieved from https://www.ahla.com/press-release/hotel-industry-partners-pearson-offer-debt- free-college-degrees-employees

American Psychological Association. (2010). Publication manual of the American Psychological Association (6th ed.). Washington, DC: American Psychological Association.

American Student Assistance. (2017). Millennials clamoring for student loan repayment benefit from employers. Retrieved from http://www.asa.org/wp- content/uploads/2017/06/asa_young_worker_and_student_debt_survey_report.pdf

Anderson, A. (2014). The impact of the Affordable Care Act on the healthcare workforce. Retrieved from https://www.heritage.org/health-care- reform/report/the-impact-the-affordable-care-act-the-health-care-workforce

Antwi, Y., & Bowblis, J. (2016). The impact of nurse turnover on quality of care and mortality in nursing homes: Evidence from the great recession. Upjohn Institute Working Paper, 15–249. Klamazoo, MI: W.E. Upjohn Institute for Employment Research. doi:10.17848/wp15–249

Argento, A. (2017). Seventeen companies that help employees pay off their student loans. Student Loan Hero. Retrieved from https://studentloanhero.com/featured/companies-that-pay-off-student-loans/

Aryee, S., Budhwar, P., & Chen, Z. (2002). Trust as a mediator of the relationship between organizational justice and work outcomes: Test of a social exchange model. Journal of Organizational Behavior, 23(3), 267–285. doi:10.1002/job.138

ASTD. (2012). State of the industry report. Retrieved from https://www.td.org /Publications/Research-Reports/2012/2012-State-of-the-Industry 113

Bailey, C., Madden, A, Alfes, K., & Fletcher, L. (2017). The meaning, antecedents and outcomes of employee engagement: A narrative synthesis. International Journal of Management Reviews, 19, 31–53. doi:10.1111/ijmr.12077

Bakker, A., & Leiter, M. (2010). Work engagement: A handbook of essential theory and research. New York, NY: Psychology Press.

Bakker, A., Schaufeli, W., Sixma, H., Bosveld, W., & Van Dierendonck, D. (2000). Patient demands, lack of reciprocity, and burnout: A five-year longitudinal study among general practitioners. Journal of Organizational Behavior, 21(4), 425–441. Retrieved from https://www.deepdyve.com/lp/wiley/patient-demands-lack-of- reciprocity-and-burnout-a-five-year-EzZs0AhSKP

Ballard, D. (2014). Employee distrust is pervasive in U.S. workforce. [Press Release]. American Psychological Association. Retrieved from http://www.apa.org/news /press/releases/2014/04/employee-distrust.aspx

Baran, B., Rhoades-Shanock, L., & Miller, L. (2012). Advancing organizational support theory into the twenty-first century world of work. Business Psychology, 27, 123– 147. doi:10.1007/s10869–011–9236–3.

Barnett, J. (2015). The number one driver of employee engagement is…well, that depends. Talent Management and HR. Retrieved from https://www.tlnt.com/the- no-1-driver-of-employee-engagement-is-well-it-depends/

Barron, P., Leask, A., & Fyall, A. (2014). Engaging the multigenerational workforce in tourism and hospitality. Tourism Review, 69(4), 245–263. doi:10.1108/TR-04– 2014–0017.

Bean, M. (2016). Three factors driving high turnover at your hospital, and what to do about them. Becker’s Hospital Review. Retrieved from https: //www.beckershospitalreview.com/human-capital-and-risk/3-factors-driving-high- turnover-at-your-hospital-and-what-to-do-about-them.html

Benson, G., Finegold, D., & Mohrman, S. (2004). You paid for the skills, now keep them: Tuition reimbursement and voluntary turnover. Academy of Management, 47(3), 315–331. Retrieved from http://www.jstor.org/stable/20159584

Bentein, K., & Guerrero, S. (2008). The employment relationship: Current research avenues. RI/IR, 63(3), 409–424. doi:10.7202/019095ar

Berman-Gorvine, M. (2017). Take cobwebs off employee tuition policies. Managing Benefits Plans, 19(1), 10–11. Retrieved from http://bi.galegroup.com/

B.E. Smith Corporation. (2017). High cost of leadership turnover. Retrieved from: https://www.besmith.com/trends-and-insights/articles/high-cost-leadership- turnover/ 114

Best employer graduate tuition reimbursement programs: Guide to graduate education. (2016). Washington Post. Retrieved from http://www.washingtonpost.com/sf /brand-connect/wp/enterprise/best-employer-graduate-tuition-reimbursement- programs/

Bishow, J. L. (2007). Supplemental pay in the healthcare industry: overtime pay, bonuses and shift differential. U.S. Bureau of Labor Statistics. Retrieved from http://www.bls.gov/opub/cwc/cm20100716ar01pl.htm

Blau, P. (1964). Exchange and power in social life. New York, NY: Wiley.

Bock, L. (2015). Insights from inside Google: Work rules that will transform how you live and lead. New York, NY: Hachette Book Group.

Bradt, G. (2015). How to win the war for talent in 2015. Forbes Magazine. Retrieved from http://www.forbes.com/sites/georgebradt/2015/01/07/how-to-win-the-war- for-talent-in-2015/#27b0c37f19da

Breed, M. (2018). The many benefits of an employer tuition reimbursement program and policy. Money Crashers. Retrieved from https://www.moneycrashers.com /benefits-employer-tuition-reimbursement-program-policy/

Brown, D., Bersin, J., Gosling, W., & Sloan, N. (2016). Engagement: Always on. Deloitte Insights. Retrieved from https://dupress.deloitte.com/dup-us- en/focus/human-capital-trends/2016/employee-engagement-and-retention.html

Brummel, B. J., & Parker, K. N. (2015). Obligation and entitlement in society and the workplace. Applied Psychology, 64, 127–160. doi:10.1111/apps.12023

Bryant, P., & Allen, D. (2013). Compensation, benefits and employee turnover: HR strategies for retaining top talent. Compensation and Benefits Review, 45(3), 171– 175. doi:10.1177/0886368713494342

Bureau of Labor Statistics. (2015). Employment projections: 2014–2024. Retrieved from https://www.bls.gov/news.release/pdf/ecopro.pdf

Caesens, G., Stinglhamber, F., & Marmier, V. (2016). The curvilinear effect of work engagement on employees’ turnover intentions. International Journal of Psychology, 51(2), 150–155. doi:10.1002/ijop.12131

Candy aka Gypsy Nurse. (2016). The nursing workforce: Is there still a nursing shortage. Retrieved from http://www.thegypsynurse.com/blog/nursing-workforce-still- nursing-shortage/

Cappelli, P. (2002). Why do employers pay for college? National Bureau of Economic Research. Retrieved from https://pdfs.semanticscholar.org/e9d0 /a519ae559ca245c609bf75cb32ba1450fdda.pdf 115

Carmines, E. G., & Zeller, R. A. (1979). Reliability and validity assessment. Beverly Hills, CA: Sage.

Cassar, V., Buttigieg, S., & Briner, R. (2013). Causal explanations of psychological contract breach characteristics. Psychologist-Manager Journal, 16(2), 85–106. doi:10.1037/h0094949.

Cesario, F., & Chambel, M. J. (2017). Linking organizational commitment and work engagement to employee performance. Knowledge and Process Management, 24(2), 152–158. doi:10.1002/kpm.1542

Chadwick-Jones, J. (1976). Social exchange theory: Its structure and influence in social psychology. New York: Academic Press

Chamberlain, A. (2017). Why do employees stay? A clear career path and good pay, for starters. Harvard Business Review. Retrieved from https://hbr.org/2017/03/why- do-employees-stay-a-clear-career-path-and-good-pay-for-starters

Chang, H.-T., Hsu, H.-M., Liou, J.-W., & Tsai, C.-T. (2013). Psychological contracts and innovative behavior: A moderated path analysis of work engagement and job resources. Journal of Applied Psychology, 43(10), 2120-2135. doi: 10.1111/jasp.12165

Chavez, J. (2011). The case for succession planning. Nursing Leadership, 23(2), 68–79.

Cherry, T. (2014). Rejuvenating tuition reimbursement programs. Human Resource Magazine, 79–86. Retrieved from https://www.shrm.org/hr-today/news/hr- magazine/Pages/0614-tuition-assistance.aspx

Chetty, R., Grusky, D., Hell, M., Hendren, N., Manduca, R., & Narang, J. (2017). The fading American dream: Trends in absolute income mobility since 1940. Science, 356(6336), 398–406. doi:10.1126/science.aal4617

Chin, P-L., & Hung, M-L. (2013). Psychological contract breach and turnover intention: The moderating roles of adversity quotient and gender. Social Behavior and Personality: An International Journal, 41(5), 843. doi:10.2224/sbp.2013.41.5.843

Christensen Hughes, J., & Rog, E. (2008). Talent management: A strategy for improving employee recruitment, retention and engagement within hospitality organizations. International Journal of Contemporary Hospitality Management, 20(7), 743–757. doi:10.1108/09596110810899086

Coetzee, M., & Stoltz, E. (2015). Employees’ satisfaction with retention factors: Exploring the role of career adaptability. Journal of Vocational Behavior, 89, 83– 91. doi:10.1016/j.jvb.2015.04.012

Cohen, J. (1968). Multiple regression as a general data-analytic system. Psychological Bulletin, 70(6), 426-443. Retrieved from 116

https://pdfs.semanticscholar.org/c5f7/8049809e4112ec5feecea20ab2099a03e59c. pdf

Cohen, G., Blake, R., & Goodman, D. (2016). Does turnover intention matter? Evaluating the usefulness of turnover intention rate as a predictor of actual turnover rate. Review of Public Personnel Administration, 36(3), 240–263. doi:10.1177/0734371X15581850

Cohen, J., Cohen, P., West, S., & Aiken, L. (2013). Applied multiple regression/correlation analysis for the behavioral sciences. Mahwah, NJ: Routledge.

College Board. (2016). Average estimated undergraduate budgets, 2015–2016. Retrieved from https://trends.collegeboard.org/college-pricing/figures-tables/average- estimated-undergraduate-budgets-2015–16

Collings, D., & Mellahi, K. (2009). Strategic talent management: A review and research agenda. Human Resource Management Review, 19, 304–313. doi:10.1016 /j.hrmr.2009.04.001

Collins, M. D. (2010). The effect of psychological contract fulfilment on manager turnover intentions and its role as a mediator in a casual, limited-service restaurant environment. International Journal of Hospitality Management, 29, 736–742. doi:10.1016/j.ijhm.2010.03.005

Cook, R., & Weisberg, S. (1999). Applied regression including computing and graphics. New York, New York: Wiley.

Cornell Law School. (n.d.). Legal Information Institute. Retrieved from https://www.law.cornell.edu/cfr/text/26/1.127-2

Coyle-Shapiro, J., & Kessler, I. (2000). Consequences of the psychological contract for the employment relationship: A large scale survey. Journal of Management, 37(7), 903–931. doi:10.1111/1467–6486.00210

Craig, R. (2016). Tuition assistance programs: The secret employee benefit. Forbes. Retrieved from https://www.forbes.com/sites/ryancraig/2016/11/03/tuition- assistance-programs-the-secret-employee-benefit/#67215b4742cf

Creswell, J. (2009). Research design: Qualitative, quantitative, and mixed methods approaches (3rd ed.). Thousand Oaks, CA: Sage.

Cronbach, L. (1951). Coefficient alpha and the internal structure of tests, Psychometrika, 16, 297-334. Retrieved from https://link.springer.com/content/pdf/10.1007/BF02310555.pdf 117

Cropanzano, R., & Mitchell, M. (2005). Social exchange theory: An interdisciplinary review. Journal of Management, 31(6), 874–900. doi:10.1177 /0149206305279602

Dahlstrom, L. (2017). Starbucks ASU Partner Forum celebrates graduates, family and community. Retrieved from https://news.starbucks.com/news/starbucks-asu- partner-forum-celebrates-graduates-family-and-community

Dawes, J. (2008). Do data characteristics change according to the number of scale points used? An experiment using 5-point, 7-point and 10-point scales. International Journal of Market Research, 50(1), 61–78. Retrieved from https: //pdfs.semanticscholar.org/b75b/5ccdb2db7ddd8c62e74633b6ef34345cef5a.pdf

DeCapua, M. (2016). Five ways to address clinician burnout. Becker’s Hospital Review. Retrieved from https://www.beckershospitalreview.com/quality/5-ways-to- address-clinician-burnout.html

Definition of ‘Succession Planning.’ (2017). Economic Times. Retrieved from http://economictimes.indiatimes.com/definition/succession-planning

Delery, J., & Doty, D. (1996). Modes of theorizing in strategic human resource management: Tests of universalistic, contingency, and configurational performance predictions. The Academy of Management Journal, 39(4), 802-835. Retrieved from http://www.jstor.org/stable/256713 Dell, D., & Hickey, J. (2002). Sustaining the talent quest: Getting and keeping the best people in volatile times. The Conference Board. Retrieved from https: //www.conference-board.org/publications/publicationdetail.cfm ?publicationid=581

Deluna, J. (2015). Long reimbursement periods may decrease employee retention. Business Travel News, 32(11). Retrieved from http://bi.galegroup.com/

Dong, Y., & Peng, C-Y. (2013). Principled missing data methods for researchers. SpringerPlus, 2(1), 222. doi:10.1186/2193-1801-2-222

Douglas, G. (2015). Half of managers believe employee loyalty has fallen, survey says. HR Focus, 2, 11–12. Retrieved from https://www.bna.com/half-managers- believe-n17179922040/

DTI Associates, Inc. (2006). Hospitality industry: Identifying and addressing workforce challenges. Retrieved from https://www.doleta.gov/BRG/pdf/Hospitality %20Report%20-%20FINAL.pdf

Duffield, C. M., Roche, M. A., Dimitrelis, S., Homer, C., & Buchan, J. (2015). Instability in patient and nurse characteristics, unit complexity, and patient and system outcomes. Journal of Advanced Nursing 71(6), 1288–1298. doi:10.1111 /jan.12597 118

Dulebohn, J., Molloy, J., Pichler, S. & Murray, B. (2009). Employee benefits: Literature review and emerging issues. Human Resource Management Review, 19(2), 86- 103. doi:10.1016/j.hrmr.2008.10.001

Dyrbye, L. N., Shanafelt, T. D., Sinsky, C. A., Cipriano, P. F., Bhatt, J., Ommaya, J., . . . Meyers, D. (2017). Burnout among healthcare professionals: A call to explore and address this underrecognized threat to safe, high-quality care. NAM Perspectives. Discussion Paper, National Academy of Medicine, Washington, DC. Retrieved from https://nam.edu/burnout-among-health-careprofessionals-a- call-to-explore-and-address-this-underrecognized-threat-to-safe-high-quality-care

EdAssist. (2017). How to get employees to continue learning. Retrieved from https://www.edassist.com/resources/blogroll/post/modern-tuition-assistance

Edmans, A. (2016). 28 years of stock market data shows link between employee satisfaction and long-term value. Harvard Business Review. Retrieved from https://hbr.org/2016/03/28-years-of-stock-market-data-shows-a-link-between- employee-satisfaction-and-long-term-value

Edwards, J., & Karau, S. (2007). Psychological contract or social contract? Development of the Employment Contracts Scale. Journal of Leadership & Organizational Studies, 13(3), 67–78. doi:10.1177/10717919070130030601

Eisenberger, R., Huntington, R., Hutchinson, S., & Sowa, D. (1986). Perceived organizational support. Journal of Applied Psychology, 71(3), 500–507. Retrieved from http://classweb.uh.edu/eisenberger/perceived-organizational-support/

Elegido, J. (2012). Does it make sense to be a loyal employee? Journal of Business Ethics, 116, 495–511. doi:10.1007/s10551–012–1482–4

Elorza, U., Aritzeta, A., & Ayestaran, S. (2011). Exploring the black box in Spanish firms: The effect of the actual and perceived system on employees’ commitment and organizational performance. International Journal of Human Resource Management, 22(7), 1401–1422. doi:10.1080/09585192.2011.561956

Emerson, R. (1976). Social exchange theory. Annual Review of Sociology, 2, 335–362. Retrieved from http://www.communicationcache.com/uploads/1/0/8/8/10887248 /social_exchange_theory_-_1976.pdf

Enberg, B., Ohman, A., & Keisu, B. (2015). Work experiences among healthcare professionals in 2002 and 2012 – a 10-year follow up. Physiotherapy, 101(1), e361-e362. doi:10.1016/j.physio.2015.03.575

Farrell. A. (2010). Insufficient discriminant validity: A comment on Bove, Pervan, Beatty, and Shiu (2009). Journal of Business Research, 63, 324-327. doi:10.1016/j.busres.2009.05.003 119

Fey, C., Bjorkman, I. & Pavlovskaya, A. (2000). The effect of human resource management practices on firm performance in Russia. International Journal of Human Resource Management, 11(1), 1-18. Retrieved from http://eds.a.ebscohost.com.proxy.lib.iastate.edu/ehost/pdfviewer/pdfviewer?vid=1 &sid=7bdd8412-a757-4f19-9f50-66a7335055e0%40sessionmgr4006

Fichman, M., & Cummings, J. (2003). Multiple imputation for missing data: Making the most of what you know. Organizational Research Methods, 6(3), 282–308. doi:10.1177/1094428103255532

Figueroa, A. (2017). Here’s how the new tax plan could hurt graduate students. Retrieved from https://www.npr.org/sections/ed/2017/11/14/563130814/heres-how-the-new- tax-plan-could-hurt-graduate-students

Fink, J. (n.d.). Five signs of burnout. Nursing Link. Retrieved from http://nursinglink.monster.com/benefits/articles/2481–5-signs-of-burnout?page=3

Firth, L., Mellor, D., Moore, K., & Loquet, C. (2004). How can managers reduce employee intent to quit? Journal of Managerial Psychology, 19(2), 170–187. doi:10.1108.02683940410526127

Fitzner, K. (2007). Reliability and validity: A quick review. The Diabetes Educator, 33(5), 775-776, 780. doi: http://journals.sagepub.com.proxy.lib.iastate.edu/doi/pdf/10.1177/0145721707308 172

Fletcher, L. (2016). How can personal development lead to increased engagement? The role of meaningfulness and perceived line manager relations. International Journal of Human Resource Management, 1–24. doi:10.1080 /09585192.2016.1184177

Fornel, C. & Larcker, D. (1981). Evaluating structural equation models with unobserved variables and measurement error. Journal of Marketing Research, 18, 39-50. doi: 10.2307/3151312

Frauenheim, E., & Russell, T. (2017). Want to build a resilient team? The best healthcare employers have answers. Fortune. Retrieved from http://fortune.com/2017/04/12 /best-health-care-companies-advice/

Frazier, P., Barron, K., & Tix, A. (2004). Testing moderator and mediator effects in counseling psychology research. Journal of Counseling Psychology, 51(1), 115– 134. doi:10.1037/0022–0167.51.1.115

Freudenberger, H. J. (1974). Staff burn-out. Journal of Social Issues, 30, 159–165. doi:10.1111/j.1540–4560.1974.tb00706.x 120

Gardner, D. G., Huang, G-H., Niu, X., Pierce, J., & Lee, C. (2015). Organization-based self-esteem, PCF, and perceived employment opportunities: A test of self- regulatory theory. Human Resource Management, 54(6), 933–953. doi:10.1002/hrm.21648

Gaskin, J. (2011, March 25). Model fit during a confirmatory factor analysis (CFA) in AMOS [video file]. Retrieved from https://www.youtube.com/watch?v =JkZGWUUjdLg

Gaskin, J. (2015, April 28). Plotting homoscedasticity in SPSS [video file]. Retrieved from https://www.youtube.com/watch?v=WrQ1O_He63Q

George, D., & Mallery, P. (2016). SPSS for Windows step by step: A simple guide and reference, 11.0 update (14th ed.). Boston, MA: Allyn and Bacon.

Getz, D., & Page, S. (2016). Event studies: Theory, research and policy for planned events. New York, NY: Routledge.

Giauque, D., Anderfuhren-Biget, S., & Varone, F. (2013). HRM practices, intrinsic motivators, and organizational performance in the public sector. Public Personnel Management, 42(2), 123–150. doi:10.1177/0091026013487121

Gigante, S. (2010). How Boomers will impact the healthcare industry. CNBC. Retrieved from http://www.cnbc.com/id/35524106

Gillet, N., Huart, I., Colombat, P., & Fouquereau, E. (2013). Perceived organizational support, motivation, and engagement among police officers. Professional Psychology: Research and Practice, 44(1), 46–55. doi:10.1037/a0030066.

Gittell, J., Seidner, R., & Wimbush, J. (2010). A relational model of how high- performance work systems work. Organization Science, 21(2), 490–506. doi:10.1287/orsc.1090.0446

Going for the gold in education. (2018). Military.com. Retrieved from https://www.military.com/education/getting-your-degree/going-for-the-gold-in- education.html

Goodman, A. (2016). Nurse turnover rate infographic. Streamline Verify. Retrieved from https://www.streamlineverify.com/nurse-turnover-rate/

Gouldner, A. (1960). The norm of reciprocity: A preliminary statement. American Sociological Review 25, 161-178. Retrieved from http://www.jstor.org/stable/pdf/2092623.pdf?refreqid=excelsior:3bd6a835435996 8306c54042a29112ea

Gradifi is gratitude (n.d.). Gradifi. Retrieved from https://www.gradifi.com/about 121

Graham, G. H. (1982). Understanding human relations. The individual, organizations, and management. Chicago, IL: Science Research Associates.

Grant, R. (2016, February 13). The U.S. is running out of nurses. The Atlantic. Retrieved from https://www.theatlantic.com/health/archive/2016/02/nursing-shortage /459741/

Graves, J. (2012). Millennial workers: Entitled, needy, self-centered? U.S. News & World Report. Retrieved from https://money.usnews.com/money/careers/articles/2012 /06/27/millennial-workers-entitled-needy-self-centered

Greenfield, R. (2015). Benefits are the new salary. Bloomberg. Retrieved from http://www.bloomberg.com/news/articles/2015–06–30/benefits-are-the-new- salary

Hair, J., Black, W., Babin, B., & Anderson, R. (2006). Multivariate data analysis (6th ed.). Upper Saddle River, NJ: Pearson Prentice Hall

Hair, J., Black, W., Babin, B. & Anderson, R. (2010). Multivariate data analysis (7th ed.). Upper Saddle River, NJ: Pearson Prentice Hall.

Halbesleben, J. R. (2008). Handbook of stress and burnout in healthcare. Retrieved from https://ebookcentral.proquest.com/lib/iastate/reader.action?docID=3021699&quer y=

Hammersley, M. (1987). Some notes on the terms 'validity' and 'reliability’. British Educational Research Journal, 13(1), 73-81. doi: 10.1080/0141192870130107

Hardar, G. (2013, September 15). Transferring institutional knowledge to millennials. Public Manager, 40–42. Retrieved from https://search-proquest- com.proxy.lib.iastate.edu/docview/1448425906/fulltext/DC55AEF0DB5F4A3CP Q/1?accountid=10906 .

Harmeling, J. (2013). The ROI on employee benefits. Benefits Magazine, 50(6), 48–51. Retrieved from https://www.ifebp.org/pdf/prmktg/benmagjune2013.pdf#search =roi%20on%20educational%20assistance%20benefits

Hart Research Associates. (2015). Falling short? College learning and career success. AAUW. Retrieved from https://www.aacu.org/leap/public-opinion-research/2015- survey-results

Harvey, P., Harris, K., Gillis, W., & Martinko, M. (2014). Abusive supervision and the entitled employee. Leadership Quarterly, 25, 204–217. doi:10.1016 /j.leaqua.2013.08.001

Hassell, B. (2017). Three steps to increase ROI on education benefits. Chief Learning Officer. Retrieved from http://www.clomedia.com/2017/04/17/3-tips-increase-roi- education-benefits/ 122

Hayes, A. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. New York, NY: Guilford Press.

Hayes, L. J., O’Brien-Pallas, L., Duffield, C., Shamian, J., Buchan, J., Hughes, F., . . . North, N. (2012). Nurse turnover: A literature review – an update. International Journal of Nursing Studies, 49, 887–905. doi:10.1016/j.ijnurstu.2011.10.001

Held, J. (2017). Benefit trends: EAB. Benefits Magazine, 52(11), 8–9. Retrieved from http://eds.a.ebscohost.com/

Held, J., Mrkvicka, N., & Stich, J. (2015). Educational assistance benefits: 2015 survey results. Retrieved from https://www.ifebp.org/pdf/educational-assistance-survey- results.pdf

Henseler, J., Ringle, C. & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43, 115-135. doi:10.1007/s11747-014-0403-8

Herzberg, F. (1968). One more time: How do you motivate employees? Harvard Business Review, Jan.Feb., 53-62. Retrieved from https://s3.amazonaws.com/academia.edu.documents/33572556/herzbergmotivatio n.pdf?AWSAccessKeyId=AKIAIWOWYYGZ2Y53UL3A&Expires=151963007 3&Signature=ktNgUrM8vBzwWm6joEfk60VjZlo%3D&response-content- disposition=inline%3B%20filename%3DHBR_01JAN68.pdf

Herzberg, F., Mausner, B. & Snyderman, B. (1959). The motivation to work. (2d ed.). New York: Wiley.

Heshmati, B., & Jed, S. (2015). Relationship of psychological contract and employees’ job engagement: An investigation of the millennium generation and the impacts of various generations. International Letters of Social and Humanistic Sciences, 62, 16–26. Retrieved from https://illiad.lib.iastate.edu/

Hilton, N., & Sherman, R. (2015). Promoting work engagement: One medical center’s journey. Nurse Leader, Dec., 52–57. doi:10.1016/j.mnl.2015.03.013

Ho, V., Rousseau, D., & Levesque, L. (2006). Social networks and the psychological contract: Structured holes, cohesive ties, and beliefs regarding employer obligations. Human Relations, 59(4), 459–481. doi:10.1177/0018726706065370

Holderness, D. K., Olsen, K., & Thornock, T. (2016). Managing entitled employees. Strategic Finance, 98(4), 40–46. Retrieved from https://search-proquest-com/

Homans, G. (1958). Social behavior as exchange. American Journal of Sociology, 63(6), 597–606. doi:10.1086/222355 123

How to manage different generations. (2009). Wall Street Journal. Retrieved from http://guides.wsj.com/management/managing-your-people/how-to-manage- different-generations/tab/print/

Hurst, J., & Good, L. (2009). Generation Y and career choice: The impact of retail career perceptions, expectations and entitlement perceptions. Career Development International, 14(6), 570–593. doi:10.1108/13620430910997303

IOMA. (2009). Most tuition aid programs hold steady on recession. Managing Benefits Plans. Retrieved from www.ioma.com/HR

Iowa State University, Office for Responsible Research. (n.d.). Humans – Institutional Review Board. Retrieved from https://www.compliance.iastate.edu /committees/irb

Irving, P. G., Coleman, D. F., & Cooper, C. C. (1997). Further assessments of a three- component model of occupational commitment: Generalizability and differences across occupations. Journal of Applied Psychology, 82(3), 444–452. Retrieved from http://psycnet.apa.org/

Irving, P. G., & Meyer, J. P. (1994). Re-examination of the met-expectations hypothesis: A longitudinal analysis. Journal of Applied Psychology, 79, 937–949. doi:10.1037/0021–9010.79.6.937

Irving, P. G., & Montes, S. M. (2009). Met expectations: The effects of expected and delivered inducements on employee satisfaction. Journal of Occupational and Organizational Psychology, 82, 431–451. doi:10.1348/096317908X312650

James, J. B., McKechnie, S., & Swanberg, J. (2011). Predicting employee engagement in an age-diverse retail workforce. Journal of Organizational Behavior, 32(2), 173– 196. doi:10.1002/job

Jehanzeb, K., Rasheed, M., Rasheed, A. & Amir, A. (2012). Impact of rewards and motivation on job satisfaction in banking sector of Saudi Arabia. International Journal of Business and Social Science, 3(21), 272-278. Retrieved from http://www.ijbssnet.com/journals/Vol_3_No_21_November_2012/29.pdf

Jenkins, J. M. (1993). Self-monitoring and turnover: The impact of personality on intent to leave. Journal of Organizational Behavior, 14(1), 83–91. doi:10.1002 /job.4030140108

Jepsen, D. (2010). A social exchange model of the employment relationship based on keeping tally of the psychological contract. Employment Relations Record, 10(2), 20–45. Retrieved from http://minerva.mq.edu.au:8080/vital/access/manager /Repository/mq:14036

Jones, C., & Gates, M. (2007). The cost and benefits of nurse turnover. Online Journal of Issues in Nursing, 12(3), 5–5.1. doi:10.3912/OJIN.Vol12No03Man04 124

Jones, K. (2017). The most desirable employee benefits. Harvard Business Review. Retrieved from https://hbr.org/2017/02/the-most-desirable-employee-benefits

Jordan, P., Ramsay, S., & Westerlaken, K. (2016). A review of entitlement: Implications for workplace research. Organizational Psychology Review, 7(2), 122–142. doi:10.1177/2041386616647121

Kahn, W.A. (1990). Psychological conditions of personal engagement and disengagement at work. Academy of Management Journal, 33, 4, 692-724. Retrieved from http://eds.a.ebscohost.com.proxy.lib.iastate.edu/ehost/pdfviewer/pdfviewer?vid=1 &sid=ec50e4af-6479-495a-b7d7-8f277f518dba%40sessionmgr4007

Karagonlar, G., Eisenberger, R., & Aselage, J. (2016). Reciprocation wary employees discount PCF. Journal of Organizational Behavior, 37, 23–40. doi:10.1002 /job.2016

Karatepe, O. & Demir, E. (2014). Linking core self-evaluations and work engagement to work-family facilitation: A study in the hotel industry. International Journal of Contemporary Hospitality Management, 26(2), 307- 323. Retrieved from https://doi.org/10.1108/IJCHM-01-2013-0008

Kasekende, F. (2017). Leader-member exchanges and psychological contract: testing for interaction effects. Journal of Management Development, 36(7), 959–972. Retrieved from https://doi.org/10.1108/JMD-06–2016–0105

Keyko, K., Cummings, G., Yonge, O., & Wong, C. (2016). Work engagement in professional nursing practice: A systematic review. International Journal of Nursing Studies, 61, 142–164. doi:10.1016/j.ijnurst.2016.06.003

Kieler, A. (2016). How does JetBlue’s new employee college tuition program compare to others? Retrieved from https://consumerist.com/2016/04/18/how-does-jetblues- new-employee-college-tuition-program-compare-to-others/

Kim, J-S., Kaye, J., & Wright, L. (2001). Moderating and mediating effects in causal models. Issues in Mental Health Nursing, 22(63), 63–75. doi:10.1080 /01612840121087

Klemp, G. (2014). Five ways to win today’s war for talent. Fast Company. Retrieved from http://www.fastcompany.com/3035836/hit-the-ground-running/5-ways-to- win-todays-war-for-talent

Klimchak, M., Carsten, M., Morrell, D., & MacKenzie, W. (2016). Employee entitlement and proactive work behaviors: The moderating effects of narcissism and organizational identification. Journal of Leadership and Organizational Studies, 23(4), 387–396. doi:10.1177/1548051816636790 125

Ko, J., & Hur, S. (2014). The impacts of employee benefits, procedural justice, and managerial trustworthiness on work attitudes: Integrated understanding based on social exchange theory. Public Administration Review, 74(2), 176–187. doi:10.1111/puat12160

Ko, W-H. (2015). Constructing a professional competence scale for foodservice research and development employees from an industry viewpoint. International Journal of Hospitality Management, 49, 66–72. doi:10.1016/j.ijhm.2015.06.002

Kreitler, S., Toren, A., & Barak, F. (2016). Stress vulnerability and quality of life in healthcare workers. Personality and Individual Differences, 101, 492. doi:10.1016 /j.paid.2016.05.199

Kurtessis, J., Eisenberger, R., Ford, M. T., Buffardi, L. C., Stewart, K. A., & Adis, C. S. (2017). Perceived organizational support: A meta-analytic evaluation of organizational support theory. Journal of Management, 43(6), 1854–1884. doi:10.1177/0149206315575554

Laird, M., Harvey, P., & Lancaster, J. (2015). Accountability, entitlement tenure and satisfaction in Generation Y. Journal of Managerial Psychology, 30(1), 87–100. doi:10.1108/JMP-08–2014–0227

Landes, H. (2012). Tuition reimbursement: A benefit for some employees and employers. Forbes. Retrieved from https://www.forbes.com/sites/moneybuilder/2012/07/20 /tuition-reimbursement-a-benefit-for-some-employees-and- employers/#5f68bc7076c5

Landy, F. (1985). Psychology of work behavior. Homewood, IL: Dorsey Press.

Lee, T., Hom, P., Eberly, M. & Li, J. (2017). Managing employee retention and turnover with 21st century ideas. Organizational Dynamics, 631, 1–11. doi:10.1016 /j.orgdyn.2017.08.004

Leiter, M. P., Price, S. L., & Laschinger, H. S. (2010). Generational differences in distress, attitudes and incivility among nurses. Journal of Nursing Management, 18, 970–980. doi:10.1111/j.1365–2834.2010.01168.x

Lengnick-Hall, M., Lengnick-Hall, C., Andrade, L. & Drake, B. (2009). Strategic human resource management: The evolution of the field. Human Resource Management Review, 19, 64-85.

Lester, S., & Kickul, J. (2001). Psychological contracts in the 21st century: What employees value most and how employers are responding to expectations. Retrieved from http://eds.a.ebscohost.com/

Levinson, H., Price, C., Munden, K., Mandl, H., & Solley, C. (1962). Men, management and mental health. American Sociological Review, 28(6), 1050–1051. Retrieved from http://psycnet.apa.org/ 126

Lewis, M. (2007). Stepwise versus hierarchical regression: Pros and cons. Paper presented at the annual meeting of the Southwest Educational Research Association, February 7, 2007, San Antonio, TX.

Lewis, R., & Heckman, R. (2006). Talent management: A critical review. Personnel Decisions International, 16, 139–154. doi:10.1016/j.hrmr.2006.03.001

Likert, R. (1932). A technique for the measurement of attitudes. Archives of Psychology, 22(140), 55.

Lim, B., & Ling, F. (2011). Contractors’ human resource development practices and their effects on employee soft skills. Architectural Science Review, 54:3, 232–245. doi:10.1080/00038628.2011.590056

Little, R. (1988). A test of missing completely at random for multivariate data with missing values. Journal of the American Statistical Association 83, 1198–1202. doi: 10.1080/01621459.1988.10478722

Litwin, M. (1995). How to measure survey reliability and validity. Thousand Oaks, CA: Sage.

Livingston, S. (2017). Healthcare drives yearly job growth. Modern Healthcare. Retrieved from http://www.modernhealthcare.com/article/20170106/NEWS /170109951?template=print

Locke, E. A., & Latham, G. P. (2002). Building a practically useful theory of goal setting and task motivation: A 35-year odyssey. American Psychologist, 57(9), 705–717. doi:10.1037/0003–066X.57.9.705

Logue, A. (2012, February 24). Piled higher and deeper: Graduate student debt runs out of control. University Business. Retrieved from https://www.universitybusiness .com/article/piled-higher-deeper

Lub, X. D., Matthijs Bal, P., Blomme, R. J., & Schalk, R. (2016). One job, one deal…or not: Do generations respond differently to PCF? International Journal of Human Resource Management, 27(6), 653–680. doi:10.1080/09585192.2015.1035304

Lumina Foundation. (2016). Talent investments payoff: Cigna realizes return on investment from tuition benefits. Retrieved from https://www.luminafoundation .org/files/resources/talent-investments-pay-off-cigna-full.pdf

Luthans, K., & Sommer, S. (2005). The impact of high performance work on industry- level outcomes. Journal of Managerial Issues, 17(3), 327–345. Retrieved from http://eds.b.ebscohost.com/

Ma, C-C. & Chang, H-P. (2013). Training transfer in the Taiwanese hotel industry: Factors and outcomes. Social Behavior and Personality, 41(5), 761–776. doi:10.2224/sbp.2013.41.5.761 127

Magni, C. A. (2015). Aggregate return on investments for investments under uncertainty. International Journal of Production Economics, 165, 29–37. doi:10.2139 /ssrn.2335148

Mamun, C., & Hasan, N. (2017). Factors affecting employer turnover and sound retention strategies in business organization: a conceptual view. Problems and Perspectives in Management, 15(1), 63–71. doi:10.21511/ppm.15(1).2017.06

Manchester, C. (2012). General human capital and employee mobility: How tuition reimbursement increases retention through sorting and participation. IL Review, 65(4), 951–974. doi:10.1177/001979391206500408

Marsh, H. W., Morin, A. J. S., Parker, P., & Kaur, G. (2014). Exploratory structural equation modeling: An integration of the best features of exploratory and confirmatory factor analysis. Annual Review Clinical Psychology, 10, 85–110. doi:10.1146/annurev-clinpsy-032813–153700

Maslach, C., & Leiter, M. (2008). Early predictors of job burnout and engagement. Journal of Applied Psychology, 93(3), 498–512. doi:10.1037/0021–9010.93.3.498

Maslach, C., Schaufeli, W. B., & Leiter, M. P. (2001). Job burnout. Annual Review of Psychology, 52, 397–422. doi:10.1146/annurev.psych.52.1.397

Maslow, A. H. (1943). A theory of human motivation. Psychological Review, 50(4), 370- 396. Retrieved from http://dx.doi.org/10.1037/h0054346

Matthijs Bal, P., Chiaburu, D. & Jansen, P. (2010) Psychological contract breach and work performance: Is social exchange a buffer or an intensifier? Journal of Managerial Psychology, 25(3), 252-273. Retrieved from https://doi.org/10.1108/02683941011023730

McCann, D. (2016). Cigna gets 129% ROI on tuition reimbursement costs. CFO.com. Retrieved from http://ww2.cfo.com/training/2016/04/cigna-gets-129-roi-tuition- reimbursement-costs/

McCormick, I. (2016). Winning the war for talent: The competition is only getting tougher. NZ Business + Management, 30(6), M12–M13. Retrieved from http://www.eccltd.co.nz/sites/default/files/Winning_War_for_talent.pdf

McDermott, A., Conway, E. Rousseau, D. M., & Flood, P., (2013). Promoting effective psychological contracts through leadership: The missing link between HR strategy and performance. Human Resource Management, 52, 289–310. doi:10.1002/hrm.21529

McGraw, A., & Burr, M. (2011). Changing demands: The workforce of yesterday, today and tomorrow. Cornell HR Review. Retrieved from http://www.cornellhrreview .org/changing-demands-the-workforce-of-yesterday-today-and-tomorrow/ 128

McGregor, D. M. (1960). The human side of enterprise. New York, NY: McGraw-Hill.

McIver, J., & Carmines, E. (1981). Unidimensional scaling. Issue 24 in Quantitative Applications in the Social Sciences. Newbury Park, CA: Sage

Memon, M., Salleh, R., & Baharom, M. (2016). The link between training satisfaction, work engagement and turnover intention. European Journal of Training and Development, 40(6), 407–429. doi:10.1108/EJTD-10–2015–0077

Meyer, J. P., & Allen, N. J. (1991). A three-component conceptualization of organizational commitment. Human Resource Management Review, 7, 61-89. doi: 10.1016/1053-4822(91)90011-Z

Meyer, J., Allen, N. & Smith, C. (1993). Commitment to organizations and occupations: Extensions and tesr of a three-component conceptualization. Journal of Applied Psychology, 78(4), 538-551. Retrieved from https://www.researchgate.net/profile/John_Meyer16/publication/211391140_Com mitment_to_Organizations_and_Occupations_Extension_and_Test_of_a_Three- Component_Conceptualization/links/5a312c810f7e9b2a2838d328/Commitment- to-Organizations-and-Occupations-Extension-and-Test-of-a-Three-Component- Conceptualization.pdf

Meyer, J., Vandenberghe, C., & Becker, T. (2004). Employee commitment and motivation: A conceptual analysis and integrative model. Journal of Applied Psychology, 89(6), 991–1007. doi:10.1037/0021–9010.89.6.991

Meyers, L., Gamst, G. & Guarino. A. (2016). Applied multivariate research: Design and interpretation. New York: Sage Publishing.

Michaels, E., Handfield-Jones, H., & Axelrod, B. (2001). The war for talent. Boston, MA: Harvard Business School Press.

Milford, M. (2014, September 13). Getting a college degree on the company’s dime. The News Journal. Retrieved from http://www.delawareonline.com/story/money /business/2014/09/12/getting-college-degree-companys-dime/15524599/

Miller, B., & Gallagher, D. (2016). Examining trait entitlement and using the self-other knowledge asymmetry model. Personality and Individual Differences, 92, 113– 117. doi:10.1016/j.paid.2015.12.030

Miller, B., & Konopaske, R. (2014). Dispositional correlates of perceived work entitlement. Journal of Managerial Psychology, 29(7), 808–828. doi:10.1108 /JMP-12–2012–0386

Miller, S. (2015). Educational assistance programs lead to career success. Society for Human Resource Management. Retrieved from https://www.shrm.org /resourcesandtools/hr-topics/benefits/pages/educational-assistance.aspx 129

Min, H., Park, J., & Kim, H. J. (2016). Common method bias in hospitality research: A critical review of literature and an empirical study. International Journal of Hospitality Management, 56, 126–135. doi:10.1016/j.ijhm.2016.04.010

Mitchell, A. (2013). The rise of the millennial workforce. Wired. Retrieved from https://www.wired.com/insights/2013/08/the-rise-of-the-millennial-workforce/

Monegain, B. (2013). Burnout rampant in healthcare. Healthcare IT News. Retrieved from http://www.healthcareitnews.com/news/burnout-rampant-healthcare

Morrison, E. W., & Robinson, S. L. (1997). When employees feel betrayed: A model of how psychological contract violation develops. Academy of Management, 22(1), 226–256. doi:10.5465/AMR.1997.9707180265

Mowday, R., Porter, L.& Steers, R. (1982). Employee organization linkages. San Francisco, CA: Academic Press.

National Institute for Occupational Safety and Health. (2008). Exposure to stress: Occupational hazards in hospitals. Retrieved from https://www.cdc.gov /niosh/docs/2008–136/pdfs/2008–136.pdf

Naumann, S., Minsky, B., & Sturman, M. (2002). The use of the concept “entitlement” in management literature: A historical review, synthesis, and discussion of compensation policy implications. Human Resource Management Review, 12, 145–166. doi:10.1016/S1053–4822(01)00055–9

Newman, D. (2014). Missing data: 5 practical guidelines. Organizational Research Methods, 17(4), 372–411. doi:10.1177/1094428114548590

Ng, T., Lam, S., & Feldman, D. (2010). Psychological contract breaches, organizational commitment, and innovation-related behaviors: A latent growth modeling approach. Journal of Applied Psychology, 94(4), 744–751. doi:10.1037/a0018804

Nimon, K., Shuck, B., & Zigarmi, D. (2016). Construct overlap between employee engagement and job satisfaction: A function of semantic Equivalence? Journal of Happiness Studies, 17, 1149–1171. doi:10.1007/s10902–015–9636–6

NSI Nursing Solutions, Inc. (2015). National Healthcare Retention and RN Staffing Report. Retrieved from http://www.nsinursingsolutions.com/Files/assets /library/retention-institute/NationalHealthcareRNRetentionReport2015.pdf

Nunkoo, R. (2015). Structural equation modeling, tourism. Encyclopedia of Tourism. doi:10.1007/978–3-319–01669–6_191–1

O’Boyle, E., & Harter, J. (2015). Forty organizations leading the world in employee engagement. Gallup. Retrieved from http://www.gallup.com/opinion/gallup /182432/organizations-lead-world-employee-engagement.aspx 130

O’Brien, R. (2007). A caution regarding rules of thumb for variance inflation factors. Quality & Quantity, 41, 673–690. doi:10.1007/s11135–006–9018–6

O’Donohue, W., Martin, A., & Torugsa, N. (2015). Understanding individual responses to failure by the organization to fulfil its obligations: Examining the influence of psychological capital and psychological contract type. Human Resource Management Journal, 25(1), 131–147. doi:10.1111/1748–8583.12055

Ogden, G. (2010). Talent management in a time of cost management. Healthcare Financial Management, 64(3), 80–84. Retrieved from http://www.hfma.org/hfm/

Oliver Wyman Corporation (2017). The student loan repayment benefit: Opportunities to serve a pressing financial need. Retrieved from: https://www.gradifi.com/

Onwuegbuzie, A. (2000). Expanding the framework of internal and external validity in quantitative research. Paper presented at the Annual Meeting of the Association for the Advancement of Educational Research (AAER), 1-63. Retrieved from https://files.eric.ed.gov/fulltext/ED448205.pdf

Otto, P. (2014). Employers partner with academic institutions to create specialized programs. ebn. Retrieved from https://www.benefitnews.com/news/employers- partner-with-academic-institutions-to-create-specialized-programs

Paek, S., Schuckert, M., Kim, T., & Lee, G. (2015). Why is hospitality employees’ psychological capital important? The effects of psychological capital on work engagement and employee morale. International Journal of Hospitality Management, 50, 9–26. doi:10.1016/j.ijhm.2015.07.001

Peltier, D. (2014). The double-edged sword of the hospitality graduate degree debate. Skift. Retrieved from https://skift.com/2014/11/10/the-double-edged-sword-of- the-hospitality-graduate-degree-debate/

Peng, J. C., Jien, J. J., & Lin, J. (2016). Antecedents and consequences of psychological contract breach. Journal of Managerial Psychology, 31(8), 1312–1326. doi:10.1108/JMP-10–2015–0383

Peters, K. (2017). How the best healthcare workplaces are supporting employees in challenging times. Great Place to Work. Retrieved from https://www.greatplacetowork.com/blog/914-how-the-best-healthcare- workplaces-are-supporting-employees-in-challenging-times

Peters, L., Hyun, M., Taylor, S., & Varney, J. (2017). Advising non-traditional students: Beyond class schedules and degree requirements. Voices of the Global Community. Academic Advising Today. Retrieved from http://www.nacada .ksu.edu/Resources/Academic-Advising-Today/View-Articles/Advising-Non- Traditional-Students-Beyond-Class-Schedules-and-Degree-Requirements.aspx

Peters, T. (1987). Thriving on chaos. New York, NY: Harper & Row. 131

Peterson, K. (2015). Recognition: Is it just a bunch of fluff, or is it the right stuff? Journal of Pediatric Nursing, 31(2), 228–229. doi:10.1016/j.pedn.2015.12.007

Petrocelli, J. (2003). Hierarchical multiple regression in counseling research: Common problems and possible remedies. Measurement and Evaluation in Counseling and Development, 36, 9–22. Retrieved from http://citeseerx.ist.psu.edu/viewdoc /download?doi=10.1.1.583.2449&rep=rep1&type=pdf

Podsakoff, P., MacKenzie, S., Lee, J-Y., & Podsakoff, N. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. doi:10.1037/0021– 9010.88.5879

Portoghese, I., Galleta, M., Coppola, R. C., Finco, G., & Campagna, M. (2014). Burnout and workload among healthcare workers: The moderating role of job control. Occupational Safety and Health Research Institute. Retrieved from http://www.e- shaw.net/article/S2093–7911(14)00041–9/pdf

Preacher, K., & Hayes, A. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments and Computers, 36(4), 717–731. doi:10.3758/BF03206553

Price, J. L. (1977). The study of turnover (1st ed.). Ames: Iowa State University Press.

Priesemuth, M., & Taylor, R. (2016). The more I want, the less I have left to give: The moderating role of psychological entitlement on the relationship between psychological contract violation, depressive mood states, and citizenship behavior. Journal of Organizational Behavior, 37, 967–982. doi:10.1002 /job.2080

PRWeb Newswire. (2014, May 1). Survey data reveals key healthcare talent management objectives and challenges. Retrieved from http://www.prweb.com/releases/2014 /08/prweb12120154.htm

Pullen, M. (2014). Keeping employees satisfied: Theories of motivation and work. LinkedIn. Retrieved from https://www.linkedin.com/pulse/20140831143438- 248587420-work-and-satisfaction-the-intersection-of-herzberg-s-two-factor- theory-and-maslow-s-hierarchy-of-needs/

Randall Andrews & Dgiegielewski. (2005). The nurse manager: Job satisfaction, the nursing shortage and retention. Journal of Nursing Management, 13, 286-295.

Raineri, N., Mejia-Morelos, J. H., Francoeur, V., & Paille, P. (2016). Employee eco- initiatives and the workplace social exchange network. European Management Journal, 34(1), 47–58. doi:10.1016/j.emj.2015.10.006 132

Rappaport, A. M. (2013). Business case for employee benefits. Benefits Quarterly, 29(1), 8–14. Retrieved from http://annarappaport.com/wp-content/uploads/2013 /12/bqBusCareforBenefits2013Q1.pdf

Rebekic, A., Loncaric, Z., & Petrovic, M. (2015). Pearson’s or Spearman’s correlation coefficient – Which one to use? Poljoprivreda, 21(2), 47–54. doi:10.18047 /poljo.21.2.8

Restubog, S., Hornsey, M., Bordia, P., & Esposo, S. (2008). Effects of psychological contract breach on organizational citizenship behavior: Insights from the group value model. Journal of Management Studies, 45(8), 1377–1400. doi:10.1111 /j.1467–6486.2008.00792.x

Ribeiro, V., Filho, C. F., Valenti, V., Ferreira, M., de Abreu, L., Dias de Carvalho, T., . . . Ferreira, C. (2014). Prevalence of burnout syndrome in clinical nurses at a hospital of excellence. International Archives of Medicine, 7(22), 1–7. Retrieved from https://link.springer.com/content/pdf/10.1186%2F1755–7682–7-22.pdf

Richardson, H. A., Simmering, M. J., & Sturman, M. C. (2009). A tale of three perspectives: Examining post hoc statistical techniques for detection and correction of common method variance. Organizational Research Methods, 12(4), 762–800. doi:10.1177/1094428109332834

Robert Half Management Resources. (2010). Managing a multi-generational workforce. Retrieved from https://edcowdrey.files.wordpress.com/2013/08/managing-a- multigenerational-workforce-by-rhmr.pdf

Robinson, S. (1996). Trust and breach of the psychological contract. Administrative Quarterly, 41(4), 574–599. doi:10.2307/2393868

Robinson, S., Kraatz, M., & Rousseau, D. M. (1994). Changing obligations around the psychological contract: A longitudinal study. Academy of Management Journal, 37, 137–152. Retrieved from http://amj.aom.org/content/37/1/137.abstract

Rodwell, J., Ellershaw, J., & Flower, R. (2015). Fulfill psychological contract promises to manage in-demand employees. Personnel Review, 44(5), 689–701. doi:10.1108 /PR-12–2013–0224

Roepe, L. (2016). Why it’s worth it for JetBlue and Starbucks to pay for employees’ college education. Fast Company. Retrieved from http://www.fastcompany.com /3059433/why-its-worth-it-for-jet-blue-and-starbucks-to-pay-for-employees- college-education

Rondeau, K., Williams, E., & Wagar, T. (2009). Developing human capital: What is the impact on nursing turnover? Journal of Nursing Management, 17, 739–748. doi:10.1111/j.1365–2834.2009.00988.x 133

Rosopa, P., & Stone-Romero, E. (2008). Problems with detecting assumed mediation using the hierarchical multiple regression strategy. Human Resource Management Review, 18(4), 294–310. doi:10.1016/j.hrmr.2008.07.009

Rousseau, D. M. (1989). Psychological and implied contracts in organizations. Employee Responsibility and Rights Journal, 2, 121–139. doi:10.1007/BF01384942

Ruben, B. (2012). Shifting social contracts and the sociological imagination. Social Forces, 91(2), 327–346. doi:10.1093/sf/sos122

Saks, A. (2006). Antecedents and consequences of employee engagement. Journal of Managerial Psychology, 21(7), 600–619. doi:10.1108/02683940610690169

Saleem, I., & Saleem, A. (2013). New evidence in an old debate: Investigating the relationship between compensation factors and organizational effectiveness. Journal of Business Strategies, 7(1), 31–42. Retrieved from https: //www.researchgate.net/profile/Irfan_Saleem2/publication/259823319_New_evid ence_in_an_old_debate_Investigating_the_relationship_between_compensation_f actors_and_organizational_effectiveness/links/55c12bb908ae092e96684083.pdf

Salka, S. (2016, May 2). The future of healthcare – Staffing shortage crisis. Healthcare Business Daily News. Retrieved from https://www.dotmed.com/news/story /29468?p_begin=0

Schaufeli, W. B., Bakker, A. B., & Salanova, M. (2006). The measurement of work engagement with a short questionnaire. A cross-national study. Educational and Psychological Measurement, 66(4), 701–716. doi:10.1177/0013164405282471

Schaufeli, W. B., Bakker, A. B., & Van Rhenen, W. (2009). How changes in job demands and resources predict burnout, work engagement, and sickness absenteeism. Journal of Organizational Behavior, 30, 893–917. doi:10.1002 /job.595

Scheible, A., & Bastos, A. (2012). An examination of human resource management practices: Influence on organizational commitment and entrenchment. Brazilian Administrative Review, 10(1), 57–76. doi:10.1590/S1807–76922012005000011

Schlitzkus, L., Schenarts, K., & Schenarts, P. (2010). Is your residency program ready for Generation Y? Journal of Surgical Education, 67(2), 108–111. doi:10.1016 /j.jsurg.2010.03.004

Scholarship America. (n.d.). Tuition assistance: The ‘secret’ benefit that boosts employee retention. Retrieved from https://blog.scholarshipamerica.org/tuition- assistance-the-secret-benefit-that-boosts-employee-retention

Schumacker, R. E., & Lomax, R. G. (2010). A beginner's guide to structural equation modeling (3rd ed.). New York, NY: Routledge Academic. 134

Shanafelt, T., & Noseworthy, J. (2017). Executive leadership and physician well-being: Nine organizational strategies to promote physician engagement and reduce burnout. Mayo Clinic Proceedings, 92, 129–146. doi:10/1016 /j.mayocp.2016.10.004

Sherman, R. (2006). Leading a multigenerational nursing workforce: Issues, challenges and strategies. OJIN: The Online Journal of Issues in Nursing, 11(2), Manuscript 2. doi:10.3912/OJIN.Vol11No02Man02

Shore, L. M., & Tetrick, L. E. (1994). The psychological contract as an explanatory framework in the employment relationship. In C. L. Cooper & D. M. Rousseau (Eds.), Trends in organizational behavior (pp. 91–109). Oxford, England: John Wiley and Sons.

Simpson, M. (2008). Engagement at work: A review of the literature. International Journal of Nursing Studies, 46, 1012–1024. doi:10.1016/j.ijnurstu.2008.05.003

Skinner, B. (1938). The behavior of organisms; an experimental analysis, by B. F. Skinner ...(The Century psychology series). New York, London: D. Appleton- Century Company, Incorporated.

Smola, K., & Sutton, C. (2002). Generational differences: Revisiting generational work values for the new millennium. Journal of Organizational Behavior, 23, 363–382. doi:10.1002/job.147

Society for Human Resource Management (SHRM). (2015). Designing and managing educational assistance programs. Retrieved from https://www.shrm.org/resourcesandtools/tools-and- samples/toolkits/pages/educationalassistanceprograms.aspx

Society for Human Resource Management (SHRM). (2017). 2017 Employee benefits: Remaining competitive in a challenging talent marketplace. Retrieved from https://www.shrm.org/hr-today/trends-and-forecasting/research-and- surveys/Documents/2017%20Employee%20Benefits%20Report.pdf

Sorenson, S., & Garman, K. (2013). How to tackle U.S. employees’ stagnating engagement. Gallup. Retrieved from http://news.gallup.com/businessjournal /162953/tackle-employees-stagnating-engagement.aspx?version=print

Spencer, M., & Gevrek, D. (2016). Labor supply and productivity responses to non-salary benefits. Personnel Review, 45(5), 1047–1068. doi:10.1108/PR-02–2015–0050

SPSS Software. (2017). SPSS (Version 24) [Online computer software]. Retrieved from http://www-01.ibm.com/support/docview.wss?uid=swg24041224

Stevens, J. P. (2009). Applied multivariate statistics for the social sciences (5th ed.). Mahwah, NJ: Routledge Academic. 135

Stroh, L., & Caligiuri, P. (1998). Strategic human resources: A new source of employee advantage in the global arena. International Journal of Human Resource Management, 9(1). doi:10.1080/095851998341161

Suazo, M., & Stone-Romero, E. (2010). Implications of psychological contract breach: A perceived organizational support perspective. Journal of Managerial Psychology, 26(5), 366–382. doi:10.1108/02683941111138994

Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics (6th ed.). Boston, MA: Allyn & Bacon.

Tavakol, M., & Dennick, R. (2011). Making sense of Cronbach’s alpha. International Journal of Medical Education, 2, 53–55. doi:10.5116/ijme.4dfb.8dfd

Tett, R. & Meyer, J. (1993). Job satisfaction, organizational commitment, turnover intention and turnover: Path analyses based on meta-analytic findings. Personnel Psychology, 46, 259-293. doi: 10.1111/j.1744-6570.1993.tb00874.x

Think it’s hard to see a doctor now? Just wait. (2012). Bloomberg Business Week. Retrieved from http://eds.b.ebscohost.com/

Tomlinson, E. C. (2013). An integrative model of entitlement beliefs. Employee Responsibilities and Rights Journal, 25, 67–87. doi:10.1007/s10672–012–9208–4

Top 20 Employee Benefits & Perks for 2017. (2017, February 7). Glassdoor. Retrieved from https://www.glassdoor.com/blog/top-20-employee-benefits-perks/

Tuition reimbursement. (2018). Salary.com. Retrieved from https://www.salary.com /tuition-reimbursement/

Turnley, W., Bolino, M., Lester, S., & Bloodgood, J. (2003). The impact of PCF on the performance of in-role and organizational citizenship behaviors. Journal of Management, 29(2), 187–206. doi:10.1177 /014920630302900

Umar, S., & Ringim, K. (2015). Psychological contract and employee turnover intention among Nigerian employees in private organizations. Management International Conference, Slovenia, May 28–30, 2015. Retrieved from http://www.fm- kp.si/zalozba/ISBN/978-961-266-181-6/86.pdf

Van der Vaart, L., Linde, B., & Cockeran, M. (2013). The state of the psychological contract and the employees’ intention to leave: The mediating role of employee well-being. South African Journal of Psychology, 43(3), 356–369. doi:10.1177 /0081246313494154

Van Eerde, W., & Thierry, H. (1996). Vroom’s expectancy models and work-related criteria: A meta-analysis. Journal of Applied Psychology, 81(5), 575–586. doi:10.1037/0021–9010.81.5.575 136 van Elste, D. & Meurs, D. (2015). Positive management: The relationship between the psychological contract, employee engagement and organizational commitment. Journal of Positive Management, 6(4), 39-52. Retrieved from https://search- proquest-com.proxy.lib.iastate.edu/docview/1808331287?accountid=10906

Vannette, D. (2017). Using attention checks in your survey may harm data quality. Qualtrics. Retrieved from https://www.qualtrics.com/blog/using-attention-checks- in-your-surveys-may-harm-data-quality/ van Stormbroek, R. & Blomme, R. (2015). Psychological contract as precursor for turnover and self-employment. Management Research Review, 40(2), 235-250. doi: 10.1108/MRR-10-2015-0235

Vroom, V. H. (1964). Work and motivation. New York, NY: Wiley

Wagner, K. (2017). Harnessing the strength of a multigenerational workforce to leverage opportunities. Healthcare Executive, Nov./Dec., 32(6), 8–18. Retrieved from https://www.nxtbook.com/nxtbooks/ache/he_20171112/index.php?startid=10#/12

Waldman, J., Kelly, F., Arora, S., & Smith, H. (2004). The shocking cost of turnover in healthcare. Healthcare Management Review, 29(1), 1–7. Retrieved from http://www.protectmasspatients.org/docs/Shocking%20Cost%20of%20RN %20Turnover.pdf

Walker, A. (2013). Outcomes associated with breach and fulfillment of the psychological contract of safety. Journal of Safety Research, 47, 31–37. doi:10.1016 /j.jsr.2013.08.008

Whitener, E. (2000). Do “high commitment” human resource practices affect employee commitment? A cross-level analysis using hierarchical linear modeling. Journal of Management, 27(5), 515–535. doi:10.1177/014920630102700502

Windish, D., & Diener-West, M. (2006). A clinician-educator’s roadmap to choosing and interpreting statistical tests. Journal of General Internal Medicine, 21(6), 655– 656. doi:10.1111/j.1525–1497.2006.00390.x

Winter, G. (2000). A comparative discussion of the notion of 'Validity' in qualitative and quantitative research. The Qualitative Report, 4(3), 1-14. Retrieved from http://nsuworks.nova.edu/tqr/vol4/iss3/4

Wu, C-M., & Chen, T-J. (2015). Psychological contract fulfilment in the hotel workplace: Empowering leadership, knowledge exchange, and service performance. International Journal of Hospitality Management, 48, 27–38. doi:10.1016 /j.ijhm.2015.04.008

137

Yohn, D. (2018). Engaging employees starts with remembering what your company stands for. Harvard Business Review. Retrieved from https://hbr.org/2018/03/engaging-employees-starts-with-remembering-what-your- company-stands-for

Zhang, M. (2014). 15 companies that will help pay your college tuition. Business Insider. Retrieved from http://www.businessinsider.com/companies-that-will-pay-for- your-tuition-2014–6

Zillman, C. (2016). These six companies give their employees unlimited tuition reimbursement. Fortune. Retrieved from http://fortune.com/2016/03/04 /companies-employees-tuition-reimbursement/

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APPENDIX A. INTERNAL REVIEW BOARD AUTHORIZATION

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APPENDIX B: INFORMED CONSENT DOCUMENT

Topic of Study: Healthcare Employee TAP Perceptions

Investigator: Jennifer Bonilla, MHI, MBA, FACHE

This form describes a research project. It has information to help you decide whether you wish to participate. Research studies include only people who choose to take part—your participation is completely voluntary. Please discuss any questions you have about the study or about this form with the investigator before deciding to participate.

Introduction The aim of this study is to examine employee perceptions of their employer’s Educational Assistance or Tuition Assistance Benefits Plan. Data from this research will be used by the investigators for scholarly activities, such as fulfilling dissertation requirements for a doctoral degree, research conference proceedings and journal articles. Information provided will be anonymous. Please take your time in deciding if you would like to participate.

You are being invited to participate in this study because our records indicate that you have applied for your employer’s Educational Assistance Benefit Plan (Tuition Assistance) at some point during your tenure with the company. You should only participate in this research if: (a) you are 18 years or older; (b) if you are an active employee; (c) if you have applied to company’s Tuition Assistance Plan at any time during your employment with the company, whether you received any benefits or not.

Description of Procedures If you agree to participate, your participation will involve completing a web-based questionnaire. You will be asked about your feelings and perceptions about the Tuition Assistance Plan from an employee perspective. The survey is expected to take about 4–8 minutes to complete. No personal information will be collected.

Risks or Discomforts While participating in this study, there are no known risks/discomforts.

Benefits If you decide to participate in this study, there will be no direct benefit to you. It is hoped that the information gained in this study will assist educators and employers in understanding the perceptions of employers relative to workplace TAP. 140

Costs and Compensation You will not have any costs from participating in this study, and you will not receive compensation from this study.

Participant Rights Participating in this study is completely voluntary. You may choose not to take part in the study or to stop participating at any time, for any reason, without penalty or negative consequences. You can skip any questions that you do not wish to answer.

If you have any questions about the rights of research subjects or research-related injury, please contact the IRB Administrator, (515) 294–4566, [email protected], or Director, (515) 294–3115, Office for Responsible Research, Iowa State University, Ames, Iowa 50011.

Confidentiality Records identifying participants will be kept confidential to the extent permitted by applicable laws and regulations and will not be made publicly available. However, federal government regulatory agencies auditing departments of Iowa State University, and the Institutional Review Board (a committee that reviews and approves human subject research studies) may inspect and/or copy study records for quality assurance and data analysis. These records may contain private information.

To ensure confidentiality to the extent permitted by law, the following measures will be taken:

All data files and documents pertaining to this research will be completely held confidential under password protected computer files. Any survey information obtained will only be provided to company in aggregate, and no individual survey responses will be shared.

Questions You are encouraged to ask questions at any time during this study. For further information about the study, contact Jennifer Bonilla, 480–717–1965, [email protected]. 141

Consent and Authorization Provisions By clicking the ACCEPT button below, you indicate that you voluntarily agree to participate in this study, that the study has been explained to you, that you have been given time to read the document and that your questions have been satisfactorily answered.

⃝ Agree

⃝ No, I will not participate in this study (upon selecting this option please click submit).

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APPENDIX C. EDUCATION ASSISTANCE BENEFIT PLAN/TUITION

ASSISTANCE PLAN (EAB/TAP SURVEY INSTRUMENT)

Format: MS Word for transfer to Qualtrics

1. Have you ever applied to the Tuition Assistance Plan (TAP) at any point during your employment with the company? (Note: “yes” response applies to all applicants, whether you were accepted into the program or not.) o Yes o No If no on Q1, please discontinue survey.

2. Was your TAP application accepted and did you receive tuition assistance benefits? o Yes o No o Don’t know

3. During the most recent time you applied for TAP through your employer, what type of educational program was it associated with? o Certificate Program o Associate’s degree (AA) o Bachelor’s degree (e.g. BA, BS, BBS, etc.) o Master’s degree (MBA, MHA, MPH, etc.) o Other

4. Did you graduate? o Yes o No o Program still in process

If “yes” on Q3, go to Q3; otherwise, go to Q4.

5. Have you ever been promoted following the completion of your employer- supported tuition program (i.e. after graduating)? o Yes o No o Promotion is in process

***Use 5-point Likert Scale for questions 5–34: 1=strongly disagree 2=disagree 3=neither agree or disagree 4=agree 5=strongly agree

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6/1. Tuition assistance policy is easy to understand.

6/2. Tuition assistance application is easy to submit.

6/3. I was notified about my application status in a timely manner.

6/4. The EdAssist Portal was easy to use during my application experience.

6/5. I think the Tuition Assistance Program selects employees fairly.

6/6. I am aware that EdAssist provides online and phone customer support to help employees with their applications.

6/7. The culture at my organization makes me want to work here for a long time.

7/1. I honestly feel I’m just more deserving than others

7/2. Great things should come to me.

7/3. If I were on the Titanic, I would deserve to be on the first lifeboat.

7/4. I demand the best because I’m worth it.

7/5. I do not necessarily deserve special treatment.

7/6. I deserve more things in my life.

7/7. People like me deserve an extra break now and then.

7/8. Things should go my way.

7/9. I feel entitled to more of everything.

8. Paying attention and reading questions carefully in a survey are essential to creating valid survey results. If you are paying attention, mark “10” below:

9/1. I am fairly paid compared to employees doing similar work in other organizations

9/2. I receive fair pay for the responsibilities that I have in my job.

9/3. I receive pay increases to pay my standard of living.

9/4. I receive competitive fringe benefits (Beneplace discounts, etc.)

9/5. I receive the necessary training to do my job well.

9/6. I receive support when I want to learn new skills. 144

9/7. I have long term job security.

9/8. I have good career prospects.

10. The training that I receive is up-to-date. (add “Does not apply” response option.)

11/1. I intend to stay in this job for the foreseeable future

11/2. I will probably look for a new job within the next year.

11/3. I do not intend to pursue alternate employment in the foreseeable future.

12/1. At my work, I feel bursting with energy.

12/2. At my job, I feel strong and vigorous.

12/3. I am enthusiastic about my job.

12/4. My job inspires me.

12/5. When I get up in the morning, I feel like going to work.

12/6. I feel happy when I am working intensely.

12/7. I am proud of the work that I do

12/8. I am immersed in my work.

12/9. I get carried away when I am working.

13. The conditions at my company make me want to work here for a long time.

14. Would you like to share other thoughts/comments about your experience with the Tuition Assistance Plan? ______

Demographic Questions:

15. What is your gender? o Male o Female o Other

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16. Which ethnicity do you most identify with? o African American o Asian o Hispanic o Pacific Islander o White o Mixed race

17. What is your marital status? Single (never married) o Married o Separated o Widowed o Divorced

18. What is your age range? o 18 to 24 years o 25 to 34 years o 35 to 44 years o 45 to 54 years o 55 to 64 years o Age 65 or older

19. Select the job classification that fits you best: o Manager/Supervisor o Director o VP/C-suite o LPN/CNA o RN/ o MD o Other Clinical Role

20. How long have you worked in the health care industry? o Less than one year o 1–3 years o 4–9 years o 10–14 years o 15 years +

21. What is your highest education level completed? o Completed some high school o High school graduate o Completed some college o Associate’s degree o Bachelor’s degree (e.g. BA, BS, BBA) o Master’s degree (e.g. MBA, MHA, MPA) 146

o Terminal degree (e.g. MD, JD, PhD) o Other advanced degree beyond a master’s degree

22. What is your current salary range? o Less than $30,000 o $30,000 to $59,999 o $60,000 to $89,999 o $90,000 to $119,999 o $1290,000 to $149,999 o $150,000 to $179,000$180,000 +