Journal of Business and Psychology

, Volume 32, Issue 3, pp 301–315 | Cite as

Generational Differences in Work Ethic: Fact or Fiction?

  • Keith L. Zabel
  • Benjamin B. J. Biermeier-Hanson
  • Boris B. Baltes
  • Becky J. Early
  • Agnieszka Shepard
Original Paper

Abstract

Even though stereotypes suggest that older generational cohorts (e.g., Baby Boomers) endorse higher levels of work ethic than younger generations (e.g., Millennials), both the academic literature and popular press have found mixed evidence as to whether or not generational differences actually exist. To examine whether generational differences exist in work ethic, a dataset was compiled (k = 105) of all published studies that provided an average sample age and average work ethic score, with each sample becoming an observation, and being assigned a generational cohort based upon the average age of the sample. Three hierarchical multiple regressions found no effect of generational cohort on work ethic endorsement. In two of the three phases, results found a main effect of sample type, such that industry samples had higher work ethic endorsement than student samples. Implications for applied practitioners and future research streams for generational and work ethic research are discussed.

Keywords

Work ethic Generational differences Twenty-first-century skills Aging 

Generational Differences in Work Ethic: Fact or Fiction?

At the present time, an unprecedented percentage of the US workforce consists of members from the Baby Boomer generation (Bureau of Labor Statistics 2014). A number of factors, such as decreasing fertility rates, broken retirement systems, and increasing life expectancy due to medical advances, have caused nations to consistently increase their retirement ages. All these factors have motivated individuals to continue working and delay retirement (Finkelstein et al. 2015). Given that Baby Boomers, Generation X, and Millennial generations will continue working together for decades, it is of vital importance to determine whether generational differences exist in the Protestant work ethic (PWE) endorsement, an important enabler of twenty-first-century skill development.

PWE originated in the writings of Max Weber (1958), who argued that egalitarian principles, a disdain of leisure activities, and the belief in the importance of hard work were responsible for economic successes seen in the USA and Europe during the turn of the twentieth century. Although it was originally conceptualized as being associated with the Protestant denomination of Christianity, the current conceptualization of PWE does not involve any specific religious orientation. Those with high PWE place work central to their life, avoid wasting time, and are ethical in their dealings with others (Miller et al. 2002). As examples, PWE has been associated with engaging in a greater number of work-related behaviors while commuting to work on a train (Greenberg 1978). In addition, PWE has been associated with increased job satisfaction, organizational commitment, and job performance (Meriac et al. 2013), as well as decreased social loafing (Smrt and Karau 2011) and conscientiousness (Christopher et al. 2008a).

In their development of a multifaceted PWE measure, Miller et al. (2002) developed seven smaller facets of PWE, including centrality of work, hard work yields successful outcomes, morality/ethics, wasting time, avoiding leisure activities, delaying gratification, and self-reliance. Centrality of work refers to the importance of work to one’s meaning in life. Hard work refers to the extent to which one believes that working hard will yield desirable outcomes. Morality/ethics refers to the extent to which individuals should be moral and ethical when dealing with others. Wasting time refers to one’s belief that time is a precious commodity that should not be wasted. Avoiding leisure activities refers to the extent one prefers work over leisure activities. Delaying gratification refers to the extent to which one is willing to postpone immediate rewards for larger future research rewards. Finally, self-reliance is the extent to which one strives to be independent from others. We argue that PWE is an important precursor to collaborative solving, and a key component that keeps individuals moving forward in the face of obstacles, which often occurs during collaborative problem-solving and other twenty-first-century skills and activities. In the following sections, we outline the most common twenty-first-century skills, their link to PWE, and the implications generational differences in PWE have on twenty-first-century skills.

The most common twenty-first-century skills include collaboration, problem solving, and the ability to perform non-routine and interactive tasks (Neubert et al. 2015). Five types of collaborative problem-solving skills have been identified by Griffin et al. (2012), including participation, perspective taking, social regulation, task regulation, and learning and knowledge building. Several of these skills require high PWE endorsement for optimization of twenty-first-century skills. For example, individuals with higher levels of centrality of work should be more likely to persevere and complete tasks in the face of obstacles than those with low centrality of work. Thus, centrality of work should be positively associated with the participation dimension of collaborative problem solving.

Similarly, the problem-solving skill of task regulation requires organizing, setting goals, resource management, flexibility and ambiguity, collecting elements of information, and systematicity (Griffin et al. 2012). Organizing and setting goals often requires that one is internally motivated to complete tasks, which is consistent with high PWE, especially the facet of centrality of work. Furthermore, the creation and organization of smaller goals to create larger goals requires a mindset of delaying gratification, another facet of PWE. To complete multiple projects with multiple deadlines often requires that employees put in long hours with the belief that their hard work will yield desirable outcomes, another facet of PWE.

In addition to the collaborative problem-solving skills, collaboration with others is a key piece of problem solving in the twenty-first century. According to Griffin et al. (2012), collaboration involves the components of communication, cooperation, and responsiveness. Since cooperation and responsiveness require actions and the creation of a division of labor by team members, it is important to cooperate that one places work central to their life and avoids wasting time. In addition, projects requiring twenty-first-century skills often take a long time to complete, meaning that individuals with higher levels of delay of gratification—a facet of PWE—may be more likely to take the proper steps to cooperate and be responsive.

Several authors have discussed the importance of studying the precursors or enablers of twenty-first-century skills. For example, Riggio and Saggi (2015) argue that interpersonal communication skills are vital to collaborative problem solving and are an exemplar of the “soft skills” (p. 283) that are vital to the success of collaborative problem solving. Indeed, Robles (2012) surveyed 90 executives to determine the top ten “soft skills” required for business success. Results suggested integrity, communication, interpersonal skills, teamwork skills, and work ethic as the top ten “soft skills” required for success. This is similar to Riggio and Saggi (2015), who argued a “soft skill” required for success is having a moral and ethical orientation. Given that living a moral and ethical life is a facet of PWE, there is a clear link between moral and ethical behavior, PWE, and the “soft skills” that are required as precursors to using twenty-first collaborative problem-solving skills. Furthermore, the enablers of collaborative problem solving, such as participation and task regulation, are regulated best through the use of placing work central to one’s life, avoiding wasting time, delaying gratification, and living a moral and ethical life, all facets of PWE. Thus, it is clear that PWE is an important precursor for enabling twenty-first-century skills.

Empirical research has already found that generational differences exist in pride in craftsmanship (Smola and Sutton 2002), intrinsic and extrinsic rewards at jobs (Twenge et al. 2010), and job satisfaction and turnover intentions (Costanza et al. 2012; Kowske et al. 2010). Within the PWE literature, one of the most contested academic and applied research questions is whether or not generational differences exist in PWE endorsement. Several empirical and popular press articles have examined generational differences in PWE, with conflicting results.

Five studies have examined generational differences in PWE, with three finding little to no generational differences in PWE (Hite et al. 2015; Khosravi 2014; Real et al. 2010) and the others finding generational differences that do exist in PWE (Jobe 2014; Meriac et al. 2010). Furthermore, a recent issue of the journal Industrial and Organizational Psychology included a focal issue (Costanza and Finkelstein 2015) and commentaries devoted entirely to whether or not generational differences exist in work values. In their focal article, Costanza and Finkelstein (2015) argue that it is difficult to study true generational differences in workplace values due to the overreliance of cross-sectional data, operational definitions of the different generations (e.g., Baby Boomers), and the difficulty in distinguishing generational effects from aging, period, and cohort effects. They conclude stating “there is little solid empirical evidence supporting the existence of generationally based differences” (p. 321). While this focal article and commentaries address possible improvements in generational theory and methodology, the suggested techniques were not actually applied to an empirical study, as the purpose of the journal is to provide ideas and hypotheses for how to improve research in a given area. To apply some of the methodological suggestions from Costanza and Finkelstein (2015), this study employed a unique methodology to examine whether generational differences exist in PWE.

Indeed, to examine whether generational differences existed in PWE, we completed a comprehensive analysis of all published studies that have ever measured and reported PWE and reported the average age of the sample. Each sample that met the inclusion criteria of the study became a study observation and was assigned a generational cohort based upon the average age of the sample. The analysis was completed in three phases. As the analysis moved from Phase 1 to Phase 3, stricter controls were put in place to ensure that in Phase 3, nearly all participants of the included studies were part of the generational cohort assigned to it. In each phase, the independent variable was generational cohort and dependent variable was PWE.

If generational differences in PWE are found, there are important implications for human resource management activities (e.g., talent management and succession planning) and how organizations and academics should structure organizational interventions to increase productivity, motivation, innovation climate, and many other types of twenty-first-century skills. If generational differences in PWE are not found, the implication is that future research should reconsider examining the relationship between generations and PWE, as well as generational differences in work attitudes. This study will shed light on the validity of generational differences in PWE, as academic studies and popular press articles have both offered conflicting findings.

Determining whether PWE differences exist by generations have important implications for twenty-first-century skills, given that PWE is an important soft skill and precursor to twenty-first-century skills. Specifically, supporting traditional stereotypes, if Baby Boomers endorse higher levels of PWE than Millennials, training and development of twenty-first-century skills should focus on twenty-first-century skills unrelated to PWE (e.g., perspective taking, knowledge building; Griffin et al. 2012). On the other hand, if there are no generational differences in PWE, organizations should still take PWE into account when developing employees’ twenty-first-century skills, but not change the program based solely upon the generational consistency of the workforce. In the next section, we outline the three most studied generational cohorts in the USA, with the understanding that there is an active discussion in the literature about the events that shaped each generation and the years that reflect each generation.

Generational Cohorts

Generational cohorts have been defined as “an identifiable group that shares birth years, age location, and significant life events at critical development stages” (Kupperschmidt 2000, p. 66). Given that different types of historical events happen at different points in time, each generational cohort develops a unique personality and set of values based upon the experiences of their generational cohort. Kupperschmidt (2000) points out that even though there is without question individual differences within generations, there tends to be relative agreement among generational members in areas such as work values and personality.

Baby Boomers

The beliefs and attitudes of Baby Boomers were shaped by events such as the Vietnam War (Kupperschmidt 2000), lack of support for troops returning from that war (Smola and Sutton 2002), as well as the push for Civil Rights for African-Americas (Kupperschmidt 2000) and assassinations of prominent leaders (e.g., President Kennedy, Senator Robert Kennedy, Dr. Martin Luther King Jr.; Smola and Sutton 2002). Baby Boomers challenged, protested, and often rejected social norms (Kupperschmidt 2000). Baby Boomers have been described as born in times of economic expansion where they had beliefs of entitlement. As young adults, they challenged social norms and defined maturity as childlessness, and dual careers. Furthermore, Baby Boomers viewed technology as a commodity and viewed work as a meaningful part of life that led to self-fulfillment (Kupperschmidt 2000). Baby Boomers place work as central to their lives and often have difficulty separating it from their other life priorities (e.g., family; Lester et al. 2012). Indeed, Baby Boomers are believed to be fiercely loyal to their employer (Wong et al. 2008), which may be an extension of the loyalty shown by their parents toward one another. Typically, Baby Boomers are defined as those born between 1946 and 1964 (Meriac et al. 2010).

Generation X

The beliefs and attitudes of Generation Xers were shaped by the first Iraq War (Smola and Sutton 2002), President Bill Clinton’s sex scandal (Smola and Sutton 2002), a climate of school shootings such as the one in Littleton, CO (Smola and Sutton 2002), reality television shows (Kupperschmidt 2000), and the HIV epidemic (Smola and Sutton 2002). Generation Xers have been described as being born in poor economic conditions where independence was stressed. As young adults, they extended adolescence and had a tendency to leave home and come back (Kupperschmidt 2000) and defined maturity as a hesitance to commit to long-term relationships (O’Bannon 2001). This hesitancy may be due to the increasing US divorce rates that began to occur during their childhood (Wong et al. 2008). Furthermore, Generation Xers viewed technology as a fact of life and placed more of an emphasis on balancing one’s work and social life (Kupperschmidt 2000; O’Bannon 2001). At work, Generation Xers strive to work independently and autonomously from others and strive for work–family balance (Twenge et al. 2010). Typically, Generation Xers are defined as those born between 1965 and 1980 (Meriac et al. 2010).

Millennials

The beliefs and attitudes of Millennials have been shaped by the terrorist attacks of 9/11, second Iraq war, and election of America’s first African-American president. Given the Millennial generation is rather new to the workforce, much less research or conceptualization of the Millennial generation has been done compared to the Generation X and Baby Boomer generations. Millennials have been described as being full of promise, confident, team-oriented, achievement-oriented, conventional, pressured to excel, and having lived a sheltered life (Howe and Strauss 2000). Zemke et al. (2000) describe the core values of Millennials as optimism, civic duty, confidence, achievement, sociability, morality, street smarts, and the importance of diversity. More than other generations, Millennials value work–life balance, the freedom that technology enables one to work from anywhere, and working in collaborative, team-oriented environments (Lancaster and Stillman 2002). Millennials value job security less than other generations (Hart 2006) and have a strong desire to understand why decisions were made the way they were, whereas other generations believe in a more hierarchical organizational structure (McCrindle and Hooper 2006; Wong et al. 2008). Furthermore, Millennials are stereotyped by Baby Boomers to be entitled (Deal et al. 2010). Typically, Millennials are defined as those born between 1981 and 1999 (Meriac et al. 2010).

Although there is general agreement about the experiences each generation had in the USA, there is wide disagreement on the birth years that correspond to each generation. For example, as reported by Parry and Urwin (2011), Baby Boomers have been operationalized as those born between 1946 and 1964 (Chen and Choi 2008; Parker and Chusmir 1990; Smola and Sutton 2002), 1943 and 1960 (Appelbaum et al. 2005; Gursoy et al. 2008; Jurkiewicz and Brown 1998), 1946 and 1961 (Cennamo and Gardner 2008), and 1946 and 1962 (Jurkiewicz 2000). Generation Xers have been operationalized as those born between 1965 and 1979 (Cennamo and Gardner 2008; Lyons et al. 2007), 1965 and 1977 (Chen and Choi 2008), and 1961 to 1980 (Gursoy et al. 2008; Lamm and Meeks 2009). Finally, Millennials have been operationalized as those being born 1980 and later (Cennamo and Gardner 2008; Lyons et al. 2007), and 1981 to 2000 (Gursoy et al. 2008; Lamm and Meeks 2009).

In addition to specific birth years, the experiences that shaped one’s generation depend on the culture one grows up in. Therefore, the experiences, and even the number of generations, differ by country. For example, Nakai (2015) describes the Dankai generation in Japan, which is the equivalent to the Baby Boomer generation in the USA, and operationalized as those born between 1947 and 1949. In another example, Deal et al. (2012) describe how apartheid and its end have shaped formation of and influence South African generations. In addition, Deal et al. (2010) explain how generations within Israel are shaped by the beginning and end of wars. Because there are no standard definitions of the number of generations, events that shaped generations, or birth years that correspond to generations globally, we decided to only examine US generational differences in this study. However, as international research on generational differences in PWE continues to grow (e.g., Cogin 2012), this methodology should be applicable in the near future, once enough studies outside of the USA on generational differences in PWE have been completed.

Generational Cohorts and PWE

Because Baby Boomers view work as a meaningful part of life leading to self-fulfillment, theory suggests Baby Boomers endorse high levels of PWE. In addition, since Baby Boomers were born in a period of economic expansion, theory suggests Baby Boomers believe that simply by working hard, one can create a better life for themselves and their family (Kupperschmidt 2000). On the other hand, Generation Xers grew up in a time when battlefields were not Vietnam or Cuba, but rather American cities such as Detroit and Pittsburgh. Indeed, Zemke et al. (2000) argued Generation X developed a survival mentality, perhaps because during their childhood America seemed to fail in many areas (e.g., economically, politically). Since Generation Xers grew up in a time of economic reduction as opposed to expansion, they may endorse lower levels of PWE than Baby Boomers. Indeed, previous research found that Baby Boomers endorsed higher levels of self-reliance, morality/ethics, hard work, centrality of work, the belief in not wasting time, and delay of gratification (all dimensions of PWE) compared to Millennials, and in most cases, Generation Xers.

Perhaps the biggest difference between Millennials and other generations is the importance in understanding how to use technology in all phases of life (e.g., Meriac et al. 2010). On the whole, however, there is not as much as theory on the differences between Millennials, the Baby Boomers, and Generation Xers compared to the amount of theory on the differences between Baby Boomers and Generation Xers. This is mostly because the Millennial generation is still rather young, and many of its younger members may not have yet entered the workforce.

Previous popular press articles and research reflect the lack of refinement on differences between Baby Boomers, Generation Xers, and Millennials in PWE. Numerous popular press articles have discussed generational differences in work ethic, with some articles concluding that Baby Boomers endorse higher levels of work ethic than Millennials (e.g., Housel 2015; Marikar 2013), whereas others claim that no generational differences exist (e.g., Hartman 2014; Rampell 2011). Furthermore, at least five studies have examined generational differences in PWE with mixed results. Several studies have found little to no generational differences in PWE (e.g., Hite et al. 2015; Khosravi 2014; Real et al. 2010). Other studies have found Baby Boomers endorse higher levels of PWE than Generation X and Millennials (Meriac et al. 2010). Other studies have found Millennials endorse higher levels of PWE than Generation X and Baby Boomers (Jobe 2014).

Real et al. (2010) examined generational differences in PWE using samples of individuals in the construction/building trades industry. They found few meaningful differences in PWE between the three generations on the seven PWE dimensions. Millennials endorsed higher levels of PWE than the two other generational cohorts on the PWE dimensions of hard work yielding desirable outcomes and centrality of work, where Baby Boomers had higher levels of PWE than the other two generational cohorts on the PWE dimension of avoiding wasting time. Overall, there were few practically significant differences between the generations on PWE dimensions. In addition, Real et al.’s (2010) analysis of comments illustrated that Baby Boomers tended to believe that Millennials were very good at working hard with new technology, but hated physical labor. Khosravi (2014) examined generational differences on the two PWE dimensions of centrality of work and leisure in a sample of employees. She found no generational differences between the generational cohorts on endorsement of these two factors. Hite et al. (2015) examined generational differences on the seven PWE dimensions in a sample of undergraduate and graduate students. Results suggested Baby Boomers endorsed higher levels of self-reliance but lower levels of delay of gratification than Millennials. The differences between the three generational cohorts on the other PWE dimensions were not significant.

Regarding the two studies that have found generational differences in PWE, Meriac et al. (2010) examined generational differences on the seven PWE dimensions among samples of Millennial and Generation X students and Baby Boomer employees. They found that Baby Boomers endorsed higher levels of all PWE dimensions (with the exception of leisure) than Generation X and Millennials. Finally, Jobe (2014) examined generational differences on the seven dimensions of PWE in a sample of hospital employees. Results indicated Millennials endorsed higher levels of the PWE dimensions of leisure, hard work, and delay of gratification than Baby Boomers.

It is unquestionable that generational differences in PWE, if they exist, have important implications for how to structure workplace interventions and other types of talent management initiatives. If generational differences in PWE do not exist, it would prompt future research to focus on aspects of generational differences in the workplace other than PWE and to focus on possible generational differences in other skills important for the twenty-first century. Due to the conflicting results that exist on generational differences in PWE, it is important to approach this question from a new perspective. Therefore, the current study examines generational differences in PWE by comparing the mean level of PWE reported in all published studies that have ever measured and reported PWE, using average age of the sample as a proxy by which to determine generational cohort. Because we examined all possible published studies for inclusion (based on inclusion criteria), this study maximized statistical power, even though the final sample of studies that met inclusion criteria was seemingly small. Relying largely on Kupperschmidt’s (2000) theory of generational differences, as well as popular press articles (e.g., Housel 2015; Marikar 2013) and Meriac et al.’s (2010) findings, the following hypotheses are offered:

H1

Baby Boomer samples have higher PWE means than Millennial samples.

H2

Baby Boomer samples have higher PWE means than Generation X samples.

H3

Generation X samples have higher PWE means than Millennial samples.

Method

Literature Search

A literature search on both PsycINFO and Google Scholar was initially conducted using the following terms: Generational Differences, Protestant Work Ethic, and Work Ethic. This literature review identified eight primary measures of PWE used in the extant literature, as outlined by Furnham (1990). The different PWE measures include Goldstein and Eichhorn’s (1961) 4-item measure, Blood’s (1969) 8-item measure, Mirels and Garrett’s (1971) 19-item measure, Hammond and Williams’ (1976) 6-item measure, Buchholz’s (1978) 8-item measure, Ray’s (1982) 18-item measure, Ho and Lloyd’s (1984) 7-item measure, and Miller et al.’s (2002) 65-item measure. A cited reference search on Google Scholar for published articles and dissertations as of November 2015 was utilized to identify and retrieve relevant articles for coding. This search also revealed that Mirels and Garrett’s (1971) study was cited most (598 citations), followed by Blood (1969; 475 citations), Buchholz (1978; 213 citations), Miller et al. (2002; 185 citations), Ray (1982; 96 citations), Ho and Lloyd (1984; 78 citations), Goldstein and Eichhorn (1961; 76 citations), and finally Hammond and Williams (1976; 50 citations). Starting with the earliest PWE measure (i.e., Goldstein and Eichhorn 1961), all studies that cited Goldstein and Eichhorn (1961; n = 76) were downloaded and considered for inclusion in this study. Next, we proceeded to move to the next PWE measure in chronological order (i.e., Blood 1969) and downloaded all articles that cited Blood (1969; n = 598), considering them for inclusion. We repeated the same process until it was complete for all eight PWE measures. Given many studies cited multiple PWE measures, the final sample of studies considered for inclusion included 1386 distinct studies from eight different PWE measures.

Inclusion Criteria

Studies were considered for inclusion if they (a) used a US sample, (b) reported the average age of the sample or reported that all participants were undergraduates or part of only one generational cohort, (c) gave enough information to determine the response range used in the PWE measure, and (d) reported the average PWE score in the study. Non-US samples were omitted due to (1) the potential confounding effect of culture (i.e., work ethic may have different meanings in different cultures: Deal et al. 2010) and (2) the lack of comparative generational cohorts in other parts of the world.

In total, 91 distinct studies with 121 means met these qualifications and were considered for inclusion. As an example of why the number of studies and means is different, Chudzicka-Czupala et al. (2015) reported separately the PWE means and average ages of both an industry sample and student sample. Therefore, we were able to use the one study with two separate PWE means as part of the analysis. Further review of the 91 studies and 121 means revealed that several studies utilized the same sample in different publications (i.e., Christopher 1999; Christopher and Schlenker 2005; Gonsalves and Bernard 1983, 1985a, b; Parkhurst et al. 2011; Parkhurst 2013). To avoid double counting, we included the earlier published study in each case and removed the other duplicate from inclusion in our analyses.

Next, several studies were excluded for several different reasons. Two studies and three PWE means were excluded because their samples were high school age or younger (Iso-Ahola and Buttimer 1982; Levy et al. 2006). One study was excluded because the PWE mean reported in the study did not make sense given the measure reported in the Methods section (Blau 2001). The aforementioned exclusions resulted in remaining 85 distinct studies with 113 PWE means considered for inclusion.

It is important to note that we initially conceptualized this study as a meta-analytic investigation examining the relationship between age and PWE. Upon investigating the literature, however, we found a very limited number of studies that provided information to directly examine this relationship (k = 18). That is, the majority of the studies found examined work ethic in relation to a variety of non-age-related outcomes, reporting age only in the demographic sample information and precluding traditional meta-analytic analyses that examine bivariate correlations (cf. Hunter and Schmidt 1990). This finding forced us to reconsider our approach and to abandon these traditional techniques. While we recognize that we have sacrificed the ability to ask some interesting questions (i.e., examining potential moderators), our approach of coding studies represents a novel solution that allows us to test our fundamental theoretical question of whether there are generational differences in PWE endorsement.

Coding of Studies

The following information was coded in each study: (a) sample size, (b) PWE measure used, (c) reliability of PWE measure, (d) average age of the sample, (e) range of ages for the sample, (f) sample type (i.e., student vs. industry), (g) the mean level of PWE reported in the study, and (h) the response range used to measure PWE. To classify each PWE mean into a generational cohort, we subtracted the average age of the sample from the year the study was published to determine, on average, what year the average participant in the sample was born. We then used that corresponding year to determine the generational cohort of that sample. For example, Christopher et al. (2008) reported an average age of 42 years and mean PWE score of 4.94 on a 1–7 response range. Since the study was published in 2008, we subtracted 42 from 2008 to determine that the average participant in the sample was born in 1966. Since those born in 1966 are part of Generation X, this study would be considered a sample of Generation Xers. We also examined whether information existed in the Methods section that could help refine the year data was actually collected. As one example, Meriac et al. (2009) published their article in 2009, but stated that data collection occurred from 1996 to 2002 in their methods section. Therefore, we subtracted the average age of the sample from 1996 to 2002 as opposed to 2009 to determine the generational cohort to ascribe the PWE mean to.

Although a rather large amount of disagreement exists within the literature on the exact birth years of each cohort (see Parry and Urwin 2011, for a review), Baby Boomers’ studies were those in which the average participant in the sample was born between 1946 and 1964. Generation X studies were those in which the average participant in the sample was born between 1965 and 1980. Millennial studies were those in which the average participant in the sample was born between 1981 and 1999. The same conceptualization has been used in several other studies (e.g., Lancaster and Stillman 2002; Meriac et al. 2010). Assigning a generational cohort for each PWE mean based upon the aforementioned process revealed seven studies with an average age year earlier than 1946, which is defined as the Traditionalist generation as opposed to Baby Boomer generation. Because these seven studies (Adams and Rau 2004; Chonko 1983; Dobson and Morrow 1984; Greenberg 1978; Hooker and Ventis 1984; Jones 1984; and Kidron 1978) were part of the Traditionalist generation as opposed to Baby Boomer generation, they were excluded from further analyses. This resulted in a final total of 77 distinct studies with 105 PWE means that were included in the study analyses. Because nearly all 77 studies did not report the relationship (e.g., bivariate correlation) between age and work ethic needed to perform a meta-analytic investigation, a three-phased approach was used instead. This process determined whether there was an effect of generational cohort on PWE, using the average age of the sample and publication year of the study to determine generational cohort, and is explained in detail on pages 21–23.

Standardization of PWE Means and Coding Decisions

PWE mean scores had to be standardized to the same 7-point response range. Indeed, 46 of the 105 PWE mean scores used a 5-point response range to measure PWE. In addition, one study used a 4-point response range (Garcia 2003), one study used a 9-point response range (Ganster 1981), and six studies utilized a 6-point response range. Transformations were made to standardize scores from 5-point, 4-point, 9-point, and 6-point response ranges to a 7-point response range, using the following transformations, respectively, Y = (1.5x) − 0.5; Y = (2x) − 1; Y = (0.75x) + 0.25, and Y = (1.2x) − 0.20, where Y equals the transformed 7-point score and x equals the PWE score on the original scale. There were several studies that reported the sample included graduates and/or undergraduates who were employed (e.g., Miller and Konopaske 2014; Mudrack 1993; Tang et al. 2005). Often, these were samples of MBA students. Because these entire samples consisted of students, it was decided to count these as student samples as opposed to industry samples.

Analysis Strategy

The analysis was completed in three phases. In each phase, hierarchical multiple regression analyses were conducted to determine whether there were significant differences in PWE endorsement between generational cohorts, controlling for type of sample (student vs. industry) and scale length (on the PWE measure used in the study). The difference between each phase was the number of PWE means and studies included in the analysis, based upon the percentage of the study sample that we could be sure actually belonged to the generational cohort ascribed to. Phase 1 included all 105 aforementioned PWE means that met all inclusion criteria. Phase 2 included a subset of the original 105 PWE means where plus or minus one standard deviation of the average age of the study sample belonged to the generational cohort ascribed to it. Phase 3 included a subset of the original 105 PWE means where plus or minus two standard deviation of the average age) of the study sample belonged to the generational cohort ascribed to it. The use of three phases allowed simultaneously for comparison of results with more statistical power at Phase 1 and less statistical power at Phases 2 and 3, but greater validity at Phases 2 and 3, given it was clear in the last phase that a great majority of the sample was in the generational cohort ascribed to it.

Phase 1

Phase 1 involved conducting hierarchical multiple regression analyses on the aforementioned 105 PWE means. By subtracting the average age of the sample from the year the study was published, 38 PWE means were categorized as Baby Boomer samples, 31 PWE were categorized as Generation X samples, and 36 were categorized as Millennial samples. Of the 105 PWE means, 49 were categorized as industry samples and 56 were categorized as student samples. While Generation X had a rather even distribution of industry and student samples (17 vs. 14, respectively), Baby Boomers had many more industry samples (29) than student samples (9), and Millennials had many more student samples (33) than industry samples (3).

Phase 2

Phase 2 involved conducting hierarchical multiple regression analyses on a subset of the samples used in Phase 1. To determine the PWE means to include in Phase 2, we examined the standard deviation of the average sample age of all PWE means included in Phase 1, as well as the average sample age, to determine the age range of the sample that fell within one standard deviation of the average age (plus or minus one standard deviation). As an example, the sample included in Kidron’s (1978) study had an average age of 26 years and standard deviation of three years. Therefore, using one standard deviation above or below the average as a guide, the majority of participants included in this study were between the ages of 23 and 29 years of age. Subtracting these ages from the year of publication indicates a majority of participants were born between the years 1949 and 1955. Since the range of these years fell completely within the Baby Boomer generation, this study was included as a Baby Boomer study in Phase 2. In many ways, Phase 2 is a more precise analysis of Phase 1, as the majority of all studies included for analysis had a majority of their sample belonging to the generation ascribed to it.

After examining all 105 studies for inclusion in Phase 2, 55 studies met the aforementioned inclusion criteria. Seventeen PWE means were categorized as Baby Boomer samples, 7 PWE were categorized as Generation X samples, and 31 were categorized as Millennial samples. Of the 55 PWE means, 16 were categorized as industry samples and 39 were categorized as student samples. While Baby Boomers and Generation X had a rather even distribution of industry and student samples (9 vs. 8, respectively, for Baby Boomers; 4 vs. 3, respectively, for Generation X), Millennials had many more student samples (28) than industry samples (3).

Phase 3

Similar to Phase 2, Phase 3 involved conducting hierarchical multiple regression analyses on a subset of the samples used in Phase 2. To determine the PWE means to include in Phase 3, we examined the standard deviation of the average sample age, as well as the average sample age, to determine the age range of the sample that fell within two standard deviations of the average age (plus or minus two standard deviations). As an example, the sample included in Parkhurst et al.’s (2011) study had an average age of 22 years and a standard deviation of 1 year. Therefore, using two standard deviations above or below the average as a guide, the great majority of participants included in this study were between the ages of 20 and 24 years of age. Subtracting these ages from the year of publication indicates that a great majority of participants were born between the years 1987 and 1991. Since the range of these years fell completely within the Millennial generation, this study was included as a Millennial sample in Phase 3.

After examining all 55 studies for inclusion in Phase 3, 44 studies met the aforementioned inclusion criteria. Fourteen PWE means were categorized as Baby Boomer samples, 7 PWE were categorized as Generation X samples, and 23 were categorized as Millennial samples. Of the 44 PWE means, 14 were categorized as employee samples and 30 were categorized as student samples. While Baby Boomers and Generation X had a rather even distribution of industry and student samples (7 vs. 7, respectively, for Baby Boomers; 4 vs. 3, respectively, for Generation X), Millennials had many more student samples (20) than employee samples (3). There were several studies (e.g., Hite et al. 2015; Khosravi 2014; Real et al. 2010) that reported PWE endorsement by different generational cohorts as part of their results. These studies were included in all three phases of the analysis.

Results

Phase 1

All studies included as part of Phase 1–3 analyses can be found in “Appendix.” In addition, each study included as part of the Phase 1–3 analyses can be found in the reference section, with an asterisk (*) at the end of the reference. To determine the extent to which generational cohort differences exist in PWE endorsement, hierarchical multiple regression analyses were conducted. In order to control for the effects the length of the PWE scale and type of sample used (industry vs. sample) might have on PWE endorsement, sample type was controlled for in Step 1 and length of PWE scale was controlled for in Step 2. To test Hypotheses 1 and 2, generational cohort was entered on Step 3 by two dummy variables (Generation X and Millennials), with Baby Boomers serving as the referent group.

Multiple regression analyses revealed that in Step 1, type of sample (industry vs. student) did not contribute significantly to the regression model, F (1, 103) = 3.30, p = .07. Results suggested that in Step 2, length of PWE scale contributed significantly to the regression model, F (1, 102) = 5.86, p = .02, accounting for an additional 5.3 % of the variance in PWE endorsement over and above Step 1. Results indicated a negative relationship existed between length of PWE scale and PWE endorsement (B = −.11, SE = .04), with studies utilizing lower response ranges (e.g., 5-point) reporting higher PWE endorsement than studies utilizing higher response ranges (e.g., 7-point scales). Contrary to Hypotheses 1 and 2, results suggested in Step 3 that no significant differences in PWE endorsement existed between Generation X and Millennials with the referent group of Baby Boomers, F (2, 100) = 1.03, p = .36. Results of the Phase 1 hierarchical regression can be found in Table 1.
Table 1

Phase 1 hierarchical regression of generational cohort on PWE endorsement

 

ΔR2

B (β)

SE

Step 1

Sample typea

.031

.17 (.18)

.09

Step 2

Scale length*

.053*

−.11 (−.23)

.04

Step 3

Generational Cohort

.019

  

Gen X versus baby Boomerb

 

.14 (.13)

.12

Millennial versus Baby Boomerb

 

.18 (.18)

.14

Gen X versus Millennialc

 

−.04 (−.04)

.13

Total R2

.102

  

* p < .05

aCoded as 0 = Student, 1 = Industry

bFrom the first multiple regression where generational cohort was represented as two dummy variables with Baby Boomers serving as the referent group

cFrom the second multiple regression where generational cohort was represented as two dummy variables with Millennial serving as the referent group

To test Hypothesis 3, the same hierarchical multiple regression analyses were conducted. The only change was that the referent group switched to Millennial, and Generation X and Baby Boomer were entered on Step 3. Contrary to Hypothesis 3, results from Step 3 suggested no significant differences in PWE endorsement existed between Generation X with the referent group of Millennials, F (2, 100) = 1.03, p = .36. As seen in Table 4, the PWE means of studies coded as Baby Boomer (M = 4.54, SD = 0.41), Generation X (M = 4.64, SD = 0.44), and Millennial (M = 4.61, SD = 0.58) were remarkably similar.

Phase 2

To determine the extent to which generational cohort differences exist in PWE endorsement, hierarchical multiple regression analyses were conducted. Similar to Phase 1 analyses, sample type was controlled for in Step 1 and length of PWE scale was controlled for in Step 2. To test Hypotheses 1 and 2, generational cohort was entered on Step 3 by two dummy variables (Generation X and Millennials), with Baby Boomers serving as the referent group.

Multiple regression analyses revealed that in Step 1, type of sample (industry vs. student) contributed significantly to the regression model, F (1, 53) = 4.82, p = .03. Results indicated studies with industry samples reported higher levels of PWE than studies with student samples (B = .33, SE = .29), accounting for 8.3 % of the variance in PWE endorsement. Results suggested that in Step 2, length of PWE scale did not contribute significantly to the regression model, F (1, 52) = 0.05, p = .83. Contrary to Hypotheses 1 and 2, results suggested in Step 3 that no significant differences in PWE endorsement existed between Generation X and Millennials with the referent group of Baby Boomers, F (2, 50) = 0.18, p = .84. Results of the Phase 2 hierarchical regression can be found in Table 2.
Table 2

Phase 2 hierarchical regression of generational cohort on PWE endorsement

 

ΔR2

B (β)

SE

Step 1

Sample typea*

.083

.33 (.29)

.15.

Step 2

Scale length

.001

−.02 (−.03)

.07

Step 3

Generational cohort

.007

  

Gen X versus Baby Boomerb

 

−.09 (−.06)

.24

Millennial versus Baby Boomerb

 

.05 (.05)

.19

Gen X versus Millennialc

 

−.14 (−.09)

.23

Total R2

.091

  

* p < .05

aCoded as 0 = Student, 1 = Industry

bFrom the first multiple regression where generational cohort was represented as two dummy variables with Baby Boomers serving as the referent group

cFrom the second multiple regression where generational cohort was represented as two dummy variables with Millennial serving as the referent group

To test Hypothesis 3, the same hierarchical multiple regression analyses were conducted. The only change was that the referent group switched to Millennial, and Generation X and Baby Boomer were entered on Step 3. Contrary to Hypothesis 3, results from Step 3 suggested no significant differences in PWE endorsement existed between Generation X with the referent group of Millennials, F (2, 50) = 0.18, p = .84. As seen in Table 4, the PWE means of studies coded as Baby Boomer (M = 4.70, SD = 0.32), Generation X (M = 4.64, SD = 0.46), and Millennial (M = 4.60, SD = 0.63) were remarkably similar.

Phase 3

To determine the extent to which generational cohort differences exist in PWE endorsement, hierarchical multiple regression analyses were conducted. Similar to Phases 1 and 2, sample type was controlled for in Step 1 and length of PWE scale was controlled for in Step 2. To test Hypotheses 1 and 2, generational cohort was entered on Step 3 by two dummy variables (Generation X and Millennials), with Baby Boomers serving as the referent group.

Multiple regression analyses revealed that in Step 1, type of sample (industry vs. student) contributed significantly to the regression model, F (1, 42) = 5.63, p = .02. Results indicated studies with industry samples reported higher levels of PWE than studies with student samples (B = .34, SE = .14), accounting for 11.8 % of the variance in PWE endorsement. Results suggested that in Step 2, length of PWE scale did not contribute significantly to the regression model, F (1, 41) = 0.12, p = .74. Contrary to Hypotheses 1 and 2, results suggested in Step 3 that no significant differences in PWE endorsement existed between Generation X and Millennials with the referent group of Baby Boomers, F (2, 39) = 0.07, p = .93. Results of the Phase 3 hierarchical regression can be found in Table 3.
Table 3

Phase 3 hierarchical regression of generational cohort on PWE endorsement

 

ΔR2

B (β)

SE

Step 1

Sample typea*

.118

.34 (.34)

.14

Step 2

Scale length

.002

−.02 (−.05)

.07

Step 3

Generational cohort

.003

  

Gen X versus Baby Boomerb

 

−.06 (−.05)

.22

Millennial versus Baby Boomerb

 

.01 (.02)

.18

Gen X versus Millennialc

 

−.08 (−.06)

.21

Total R2

.124

  

* p < .05

aCoded as 0 = Student, 1 = Industry

bFrom the first multiple regression where generational cohort was represented as two dummy variables with Baby Boomers serving as the referent group

cFrom the second multiple regression where generational cohort was represented as two dummy variables with Millennial serving as the referent group

To test Hypothesis 3, the same hierarchical multiple regression analyses were conducted. The only change was that the referent group switched to Millennial, and Generation X and Baby Boomer were entered on Step 3. Contrary to Hypothesis 3, results from Step 3 suggested no significant differences in PWE endorsement existed between Generation X with the referent group of Millennials, F (2, 39) = 0.07, p = .93. As seen in Table 4, the PWE means of studies coded as Baby Boomer (M = 4.66, SD = 0.29), Generation X (M = 4.64, SD = 0.46), and Millennial (M = 4.56, SD = 0.55) were remarkably similar.
Table 4

PWE means and standard deviations by generational cohort across three phases

 

k

Mean PWE

SD PWE

Phase 1

 Baby Boomers

38

4.54

.41

 Generation X

31

4.64

.44

 Millennials

36

4.61

.58

Phase 2

 Baby Boomers

17

4.70

.32

 Generation X

7

4.64

.46

 Millennials

31

4.60

.63

Phase 3

 Baby Boomers

14

4.66

.29

 Generation X

7

4.64

.46

 Millennials

23

4.56

.55

Discussion

The purpose of this study was to examine whether generational differences exist in PWE endorsement by creating a dataset of all published studies that had reported an average sample age and average PWE score, and creating generational cohorts by subtracting the average sample age from the year the study was published. Analyses were conducted in three phases, with each phase offering more precise measurement of generational cohorts. Results using hierarchical multiple regression analyses were consistent across all three phases. In each phase, contrary to Hypotheses 1–3, there was no effect of generational cohort on PWE endorsement. Contrary to many popular press articles and Meriac et al.’s (2010) finding, results suggest there are no generational differences in PWE. These findings support other studies that have found no generational differences in variables related to PWE endorsement (e.g., hours worked; Families and Work Institute 2005; Jovic et al. 2006; Staff and Schulenberg 2010). Findings also support Costanza and Finkelstein’s (2015) recent contention that little actual empirical evidence exists that generational differences exist in work attitudes like PWE.

There are several meaningful implications of this study’s methodology and findings. First, this study utilized a novel approach to measure generational differences in workplace attitudes that can be utilized to measure generational differences across a number of workplace attitudes (e.g., organizational commitment, job satisfaction). Furthermore, the finding that generational differences in PWE do not exist suggests that organizational initiatives aimed at changing talent management strategies and targeting them for the “very different” Millennial generation may be unwarranted and not a value-added activity. We argue in the introduction that PWE is a key enabler of twenty-first-century skills. The finding that generational differences do not exist in PWE suggests that twenty-first-century skills should not be affected by any generational differences in PWE. Organizational interventions aimed at building twenty-first-century skills should not be concerned with generational differences in PWE as part of the intervention.

Limitations

There are several limitations of the current study. First, the generational cohorts were created by subtracting the average age of the sample from the year the study was published. Especially in Phase 1, it is very possible that a study classified as a Baby Boomer study (for example) has a greater proportion of Generation X participants relative to Baby Boomers. We felt it was important to include Phase 1 in order to increase statistical power. In addition, we completed Phases 2 and 3 to mitigate the limitations associated with the Phase 1 analysis. Indeed, in Phases 2 and 3, it is clear that a majority and great majority, respectively, of participants actually belonged to the generational cohort ascribed to it. Furthermore, the results were consistent across all three phases of the analysis. A second limitation is that only studies with participants from the USA were included. This was necessary because the number and type of generational cohorts differ by national country. A third limitation is that this study included only studies that measured PWE and not more broadly studies that measured work ethic or work values for analysis. Therefore, it is possible that generational differences may exist in more broadly defined “work values” or “work ethic.” Although the latter two limitations decreased the included sample size, the limitations increased the internal validity of the study and the confidence with which we can conclude that results suggest generational differences do not exist in PWE.

Future Research

Across multiple phases of the analysis, there was significant effect of sample type (industry vs. student) on PWE endorsement, with industry samples endorsing significantly higher levels of PWE than student samples. One possible explanation for these findings is that once entrenched in the workforce, individuals’ meaning of hard work and work centrality changes from when they are a student. Another possible explanation is social desirability. Individuals likely have the desire to appear hard working to others. While this effect could occur for both student and industry samples, it is likely amplified in industry samples, where participants may have the feeling that their survey results can be viewed by management or co-workers, even when they are reassured this is not the case. Future studies should examine the effect of social desirability on PWE endorsement for both industry and student samples.

Together, the significant main effect of sample type and nonsignificant effect of generational cohort on PWE endorsement have important implications for future research. Results suggest future studies should collect data from only one sample type (i.e., industry or student) when making comparisons between different generational cohorts. Otherwise, found effects could be driven by the type of participant sample as opposed to the generational cohort. Also, future studies should examine generational differences in PWE cross-culturally. Given PWE originated in the writings of German sociologist Max Weber (1958), who explained that PWE was responsible for economic growth seen in both Europe and the USA during the twentieth century, it seems reasonable to test whether generational differences exist in European nations. Indeed, no known studies have examined generational differences in PWE in European nations. Results from this study, which used a comprehensive and unique methodology, suggest that there are actually no generational differences in PWE, a finding which has important implications for academic researchers and practitioners alike.

Supplementary material

10869_2016_9466_MOESM1_ESM.docx (52 kb)
Electronic supplementary material 1 (DOCX 52 kb)

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Keith L. Zabel
    • 1
  • Benjamin B. J. Biermeier-Hanson
    • 2
  • Boris B. Baltes
    • 1
  • Becky J. Early
    • 1
  • Agnieszka Shepard
    • 1
  1. 1.Wayne State UniversityDetroitUSA
  2. 2.Radford UniversityRadfordUSA

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