Generational differences in workplace behavior

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Generational differences in workplace behavior John Bret Becton1, Harvell Jack Walker2, Allison Jones-Farmer2

1Department of Management and Marketing, College of Business, University of Southern Mississippi 2Department of Management, College of Business, Auburn University

Correspondence concerning this article should be addressed to John Bret Becton, University of Southern Mississippi, Department of Management and International Business, 118 College Dr. #5077, Hattiesburg, MS 39406, USA. E-mail: bret.becton@usm.edu

doi: 10.1111/jasp.12208

Abstract

Popular stereotypes suggest that generational differences among workers present challenges for workplace managers. However, existing empirical research provides mixed evidence for generational differences in important values and attitudes. The current study extends generational effects research by examining differences in actual workplace behaviors. Drawing from commonly held generational stereo- types, the authors hypothesized that Baby Boomers would exhibit (Hypothesis 1) fewer job mobility behaviors and (Hypothesis 2) more instances of compliance- related behaviors in comparison with both GenXers and Millennials, while (Hypothesis 3) GenXers would be less likely to work overtime in comparison with Baby Boomers and Millennials. A sample of 8,040 applicants at two organizations was used to test these predictions. Results provided support for Hypothesis 1 and Hypothesis 3 and partial support for Hypothesis 2, but the effect sizes for these rela- tionships were small. It appears the effects of generational membership on work- place behavior are not as strong as suggested by commonly held stereotypes. Implications for future research and practice are discussed.

Generational differences in workplace behavior

As the average age of the U.S. workforce continues to increase, much attention has focused on the fact that the workforce is largely comprised of three generations (i.e., Baby Boomers, Generation X, and Millennials; Eisner, 2005). The popular press frequently stresses the need for organizations to recruit, reward, and manage these employees differently because of generational differences in attitudes, values, and desires (Jurkiewicz & Brown, 1998; Kupperschmidt, 2000; Macky, Gardner, & Forsyth, 2008). Many have suggested that failure to recognize these differences can lead to negative organizational outcomes such as intergenerational workplace conflict, misunderstanding and miscommunication, poor working relationships, reduced employee productivity, poor employee well-being, lower innovation, and fewer organizational citizenship behaviors (Adams, 2000; Bradford, 1993; Dittman, 2005; Fyock, 1990; Jurkiewicz, 2000; Kupperschmidt, 2000; Smola & Sutton, 2002; Westerman & Yamamura, 2007; Yu & Miller, 2003). As a result, human resource (HR) management specialists, man- agers, and researchers have expressed interest in identifying

ways to manage and work with people from different genera- tions (Cennamo & Gardner, 2008).

Considering the extent to which generational stereotypes are commonly accepted, it is surprising that empirical evi- dence of generational differences is relatively sparse (Twenge, Campbell, Hoffman, & Lance, 2010), and the research that exists is somewhat contradictory. One stream of research sup- ports the general stereotypes concerning generational differ- ences in work values (Cennamo & Gardner, 2008; Smola & Sutton, 2002), personal values (Egri & Ralston, 2004; Lyons, Duxbury, & Higgins, 2007), leadership behaviors (Sessa, Kabacoff, Deal, & Brown, 2007), psychological/personality traits (Twenge & Campbell, 2008), turnover intentions, and organizational commitment (D’Amato & Herzfeldt, 2008; for a complete review of evidence for generational differences, see Twenge, 2010). Another stream of research has found few, if any, generational differences in a variety of employee char- acteristics such as personality and motivation (cf. Hart, Schembri, Bell, & Armstrong, 2003; Jurkiewicz, 2000; Levy, Carroll, Francoeur, & Logue, 2005; Wong, Gardiner, Lang, & Coulon, 2008). More recently, Trzesniewski and Donnellan (2010) found little evidence of generational differences in a variety of traits, attitudes, and behaviors including egotism,

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Journal of Applied Social Psychology 2014, 44, pp. 175–189

self-enhancement, individualism, self-esteem, locus of control, hopelessness, happiness, life satisfaction, loneliness, antisocial behavior, time spent working or watching televi- sion, political activity, the importance of religion, and the importance of social status.

Considering these inconsistent findings, there exists a great deal of controversy about whether or not generational differ- ences exist at all (cf. Arnett, 2010; Roberts, Edmonds, & Grijalva, 2010; Terracciano, 2010), with some suggesting that perceived generational differences are a product of popular culture versus social science (Giancola, 2006). Scholars have also noted that observed generational differences may be explained, at least in part, by age, life stage, or career stage effects instead of generation (Arnett, 2010; Carlson & Gjerde, 2009; Foster, Campbell, & Twenge, 2003; Kohut, 1971; Parry & Urwin, 2011). According to this view, human development is punctuated by different life stages that involve unique cog- nitive, emotional, and behavioral experiences (cf. Levinson, 1980), and differences in attitudes or values that are often attributed to generations may be explained by the nature of jobs held by older workers or their current life cycle. Studies that examine and test generational differences are valuable because generational studies have important applied and theoretical implications (Trzesniewski & Donnellan, 2010). Accordingly, accepting common generational stereotypes without empirical support can have potentially adverse effects on both research and practice. As a result, more gen- erational research is needed.

In this study, we provide further insight into generational effects in the workplace and make a contribution by investi- gating possible generational differences in workplace behav- iors versus values, attitudes, or personality. Specifically, we draw from generational cohort theory (Mannheim, 1952) and common generational stereotypes regarding attitudes and values to examine if generational membership explains differences in several important workplace behaviors (i.e., job mobility, disciplinary action, and willingness to work over- time). The mixed support for generational differences in values, beliefs, etc. reviewed above suggests efforts intended to promote effective management of workers from different generations may not be necessary. However, we argue that it is important to examine possible generational differences in workplace behaviors before arriving at such a conclusion.

We also make a contribution in our analytic approach. One critical issue in most generational differences studies is the age–generation confound. In an attempt to address this issue, some researchers have suggested segmenting generations into “cusp” and “core” cohort groups (Egri & Ralston, 2004) whereby individuals born within the last 5 years of a genera- tion are considered part of the “cusp” group while those born within the remainder of the generation’s birth years are con- sidered part of the “core” group. While this approach provides important insight because it allows researchers to determine if

there are any significant differences in the values/behaviors of the “cusp” and “core” groups of each generation, it also has several limitations. For example, there is no theoretical ration- ale for choosing 5 years to identify the cusp/core group. Addi- tionally, this approach fails to consider that those born in the earlier years of a generation might also be different from those in the middle or the end of a generation. To address these limi- tations, we include a measure of individuals’“relative age”(i.e., the difference in each individual’s age from the mean age of his/her generation) in each of our analyses. This allows differ- ent weighting to be given to those who are far away from the core as defined by the mean of each generation. In other words, someone with a large, positive relative age or large, negative relative age is at the cusp of two generations. While we are unable to completely rule out age, life stage, or career stage effects with this approach, it does provide unique insight into the effects of age increases within each generation.

Generational cohort theory

The concept of generations and their effects have long been discussed by researchers in anthropology, sociology, and social psychology (Hung, Gu, & Yim, 2007). A generation, often called a cohort, consists of people of similar age in a similar location who experienced similar social, historical, and life events (Kupperschmidt, 2000; Mannheim, 1972). These shared experiences (e.g., industrialization, fundamen- tal changes, cataclysmic events, and tragedies) differentiate one generation from another (Jurkiewicz & Brown, 1998) because they have a profound effect on the attitudes, values, beliefs, and expectations of generational groups (Abramson & Inglehart, 1995; Inglehart, 1977, 1990; Inglehart & Norris, 2003). Rogler (2002) proposed that the formation of a gener- ation’s collective identity occurs in the following ways. First, significant events such as disasters, wars, or revolutions chal- lenge the existing social order and lay the foundation for the emergence of a new generation. Second, these events have a stronger effect on the “coming-of-age” group than on other age groups coexisting during the same period of time because people tend to form value systems during the preadult years whereas the values of older generations are already solidified (McCrae et al., 2002). Third, this shared set of values and goals is supported by peers in the same generation and per- sists throughout adulthood (Kupperschmidt, 2000; Macky et al., 2008). In summary, commonly experienced life events have a stronger, more enduring effect on the “coming-of-age” cohort group than on other cohort groups who also experi- enced the same events.

Current generations in the workplace

Researchers generally agree that three generations currently dominate the workforce (i.e., Baby Boomers, Generation X,

176 Generational differences in behavior

and Millennials), although the labels and periods of years those labels encompass vary (Lyons et al., 2007; Sessa et al., 2007). Because no exact age range for each cohort exists, com- paring results of empirical studies of generational differences is difficult. In the passages that follow, we summarize the popular stereotypes related to values and beliefs often associ- ated with Baby Boomers (born between 1945 and 1964), Gen- eration X (born between 1965 and 1979), and Millennials (born in 1980 or later). However, before doing so, we make several notes regarding our summary. First, empirical support for the associated values and beliefs for each genera- tion is lacking and we present them primarily as stereotypes. Second, we note that there is little to no evidence that links important events experienced by generational cohort groups and their stereotypical values/characteristics. Third, the pre- sented stereotypes are associated with Western culture gen- erations. As argued by Parry and Urwin (2011) and discussed in more detail in the future research section of this manu- script, national culture is likely to have a significant influence on generational values, attitudes, and behaviors.

Baby Boomers

Baby Boomers were born between the early 1940s and mid- 1960s (Sessa et al., 2007). Boomers, as they are often called, were the result of the persistently high birth rates in America between 1945 and the 1960s and, as a result, this generation is densely populated (Lyons et al., 2007). Because this generation comprises such a large segment of society, Boomers have had a strong generational presence (i.e., significant influence on society). Events that shaped the Boomers generation include the Vietnam War, the Watergate scandal (Lancaster & Stillman, 2002), Woodstock (Adams, 2000), the civil rights movement, the Kennedy and King assassinations, and the sexual revolu- tion (Bradford, 1993). Boomers are stereotypically described as achievement oriented (O’Bannon, 2001), independent, in control of their own destinies (Mitchell, 1998), respectful of authority (Allen, 2004), loyal and attached to organizations (Hart, 2006; Loomis, 2000), and diligent on the job (Yu & Miller, 2003). Boomers are also often viewed as competitive, and they tend to measure success materially (Eisner, 2005). Some empirical evidence supports many of the stereotypical values associated with Boomers. For example, Egri and Ralston (2004) found that Boomers were higher than both older generations and GenXers in self-enhancement values (e.g., achievement, hedonism, power). Additionally, Boomers were found to be higher in self-reliance, hard work, and work centrality than younger generations (Meriac, Woehr, & Banister, 2010).

Generation X

Generation X, or Gen X (Coupland, 1991), was born between 1965 and 1979 and is defined by life experiences such as the

age of economic uncertainty, recessions, high unemploy- ment, inflation, downsizing, and high divorce rates among their parents (Kupperschmidt, 2000; Lyons et al., 2007). It is also worth noting that many GenXers are the children of compulsive workers which is posited to have had a dramatic impact on the attitudes and values of this generation (Eisner, 2005). The popular press has also noted that many GenXers were school-age children who spent part of their day unsu- pervised at home while their parents worked. Therefore, they are believed to be individualistic, distrustful of corporations, lacking in loyalty, focused on balancing their work and per- sonal lives (Eisner, 2005), financially self-reliant, and entre- preneurial risk takers (de Meuse, Bergmann, & Lester, 2001; Tulgan, 1995). Commonly accepted stereotypes suggest that GenXers are also more likely to leave an employer for more challenging work, a higher salary, or better benefits because they grew up in an era where organizational loyalty and com- mitment were not regularly rewarded with job security (Hays, 1999; Loomis, 2000). Research appears to support this asser- tion as Smola and Sutton (2002) found GenXers to be less loyal, more “me” oriented, expectant of promotion sooner than older generations, and less likely to view work as an important part of one’s life. Other perceived characteristics of this generation include being outcome focused, skeptical (Francis-Smith, 2004), and desiring of specific and construc- tive feedback (Allen, 2004). Empirical support for these ste- reotypical values is limited, but Egri and Ralston (2004) found that GenXers attributed significantly higher impor- tance to openness to change values (e.g., self-direction, stimu- lation) but lower importance to self-enhancement values (e.g., achievement, hedonism, power) than Boomers. Addi- tionally, Meriac et al. (2010) found that GenXers were lower in centrality of work than Boomers.

Millennials

There is little agreement regarding the label for the most recent cohort to enter the workforce. Referred to as Millennials, Nexters (Howe, Strauss, & Matson, 2000), the Net Generation (Tapscott, 1998), and Generation Y (Neuborne & Kerwin, 1999), this generation typically begins with birth years between 1980 and 1983 but has no agreed- upon “cutoff” date for inclusion (Sessa et al., 2007). Millennials are the first “high-tech” generation, having never known life before cell phones, personal computers, and ATMs were commonplace (Mitchell, 1998; Ryan, 2000). Addition- ally, the globalization of society and the marketplace is thought to have had a tremendous impact on their values (Howe et al., 2000). Millennials are the most racially and eth- nically diverse of the four generations (Mitchell, 1998) and, as a result, they are thought to value diversity and change (Patterson, 2005). Common stereotypes for this generation include being distrustful of organizations, having a strong

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desire for meaningful work (Ryan, 2000), holding lifelong learning as a high priority, and viewing family as the key to happiness (Mitchell, 1998). Similar to Boomers, Millennials are thought to feel a strong desire to succeed and measure their own success by the meaningfulness of work (Eisner, 2005). Research findings supporting these contentions are somewhat sparse although Millennials have been found to value leisure more than other generations and work harder than Generation X (Meriac et al., 2010).

Hypotheses

As discussed in the previous passages, there is a growing body of literature that suggests generations are distinctive from one another because social, historical, and life experiences (i.e., life history patterns) affect individuals’ dominant attitudes and values (cf. Beutell & Wittig-Berman, 2008; Cennamo & Gardner, 2008; D’Amato & Herzfeldt, 2008; Egri & Ralston, 2004; Lyons et al., 2007; Sessa et al., 2007; Smola & Sutton, 2002; Twenge & Campbell, 2008). Because life history pat- terns are, in part, a function of one’s generation (i.e., social and cultural events of one’s formative years), many have assumed that generational cohort groups differ in several workplace behaviors because they differ in their formative experiences and resulting values. Our objective is to examine if the three generational cohort groups in Western culture detailed above differ in workplace behavior as predicted by common generational stereotypes.

Job mobility behaviors

Job mobility refers to patterns of intra- and inter- organizational transitions over the history of a person’s career (Hall, 1996; Sullivan, 1999), or a person’s history of changing jobs. Previous research has found that the number of times individuals leave jobs is related to future turnover (Ghiselli, 1974; Judge & Watanabe, 1995; Munasinghe & Sigman, 2004). Recognizing this tendency, some organiza- tions prefer to “screen out” applicants who have changed jobs frequently in the past in order to have a stable workforce (Griffeth & Hom, 2001).

Commonly held stereotypes suggest several reasons why generations may differ in terms of job mobility behaviors. In Western cultures, many older generation employees (e.g., Boomers) entered the workforce when the predominant career management strategy was to enter a firm, work hard, be loyal to the organization, and be rewarded with job secu- rity (Hall, 1996). During this era, one’s career path often entailed a sequence of jobs within a single organization (Levinson, 1978; Whyte, 1956), and employees were described as not only working for organizations but belong- ing to them (Whyte, 1956). However, more recent genera- tions (e.g., Gen X and Millennials) entered the workforce in

an era where downsizing, layoffs, and offshoring were more commonplace. As a result, employee loyalty and commitment were often not consistently reciprocated with job security (de Meuse et al., 2001; Smola & Sutton, 2002; Tulgan, 1995; Twenge & Campbell, 2008), and the career paths of these younger generations are more likely to involve multiple jobs across multiple organizations (Arthur & Rousseau, 1996).

Because of these generational life experiences, many researchers have posited that generations differ in regard to personal values that are related to employer loyalty and deci- sions to terminate employment. Boomers are thought to be more likely to remain loyal and attached to an organization (Hart, 2006; Loomis, 2000; Patterson, 2005) because they believe in lifetime employment, company loyalty, and paying one’s dues to get ahead (Elsdon & Lyer, 1999). On the other hand, GenXers and Millennials are often perceived as willing to leave a job when better opportunities arise or to look for other opportunities when their current employers are not meeting their needs (Crainer & Dearlove, 1999). GenXers are also thought to be less likely to display loyalty to a particular organization because they are more independent, self-reliant (Hart, 2006), and entrepreneurial (O’Bannon, 2001) than previous generations. In fact, Generation X is said to have pioneered the “free agent” workforce, focusing on keeping skills current to improve their security (Eisner, 2005). Simi- larly, Millennials are thought to be comfortable with change and less likely to view job security as an important factor in their careers (Hart, 2006). These reported generational ste- reotypes suggest Boomers will differ from GenXers and Millennials regarding their job mobility behaviors. There- fore, we hypothesize the following:

Hypothesis 1. Boomers will exhibit fewer job mobility behaviors than GenXers and Millennials.

Compliance with work rules and policies

In most organizations, control mechanisms such as work rules, policies, and procedures exist to guide employees in the performance of their jobs. Failure to comply with these rules and policies can be detrimental to organizational success (e.g., litigation, inefficiencies, substandard quality of products or services, etc.), and managers must deal with problem behaviors in the workplace to minimize negative organizational consequences (Orey, 2007; Vardi & Weitz, 2004). Managing such misbehavior often involves taking disciplinary action against employees such as suspension, demotion, and, ultimately, termination. Since models of organizational misbehavior include individual values as antecedents of such behavior (Vardi & Weitz, 2004), it is important to investigate possible generational differences in incidences of rules violations and terminations.

178 Generational differences in behavior

Boomers are often described as having a strong work ethic, highly involved in their jobs (Kupperschmidt, 2000), and dili- gent on the job (Yu & Miller, 2003). Others suggest that most Boomers respect authority (Allen, 2004) and traditional values in the workplace (O’Bannon, 2001). In contrast, younger generations tend to be viewed as fiercely independ- ent (Lancaster & Stillman, 2002; Tapscott, 1998; Zemke, Raines, & Filipczak, 2000), placing little value on tradition and conformity (Lyons et al., 2007). Empirical studies suggest that younger generations are higher in individualistic traits such as self-esteem, assertiveness, and narcissism (Twenge, 2001; Twenge & Campbell, 2001, 2009; Twenge & Foster, 2010; Twenge, Konrath, Foster, Campbell, & Bushman, 2008). There is also some empirical evidence that indicates younger generations are not as concerned with the impres- sion they make on others, are less formal, and are less likely to conform (Cohen, 2007; Twenge & Campbell, 2008). Coupled with the notion that Generation X and Millennials are less loyal to their employers (Hart, 2006), these tendencies may also result in greater disregard for work rules, policies, and procedures. Consequently, the popular stereotypes suggest that older generations are more respectful of work rules than younger generations. By extension, we hypothesize that older generations will be more compliant, resulting in more instances of rules compliance and fewer terminations.

Hypothesis 2. Boomers will exhibit more instances of compliance and experience fewer instances of termina- tion than GenXers and Millennials.

Willingness to work overtime

As discussed earlier, scholars suggest that Generation X is much more concerned with work–life balance (Chao, 2005; Eisner, 2005) than any other generation, and the personal values and goals of GenXers are likely more important than work-related goals (Howe et al., 2000). On the other hand, Boomers and Millennials value material and financial success (Eisner, 2005; Yu & Miller, 2003). Boomers are often described as wanting it all and seeking to get it by working long hours (Eisner, 2005). Researchers suggest that Millennials, raised mostly by Boomers, have experienced powerful pressure from parents to explore financially reward- ing vocational paths (Twenge, 2010). As a result, Millennials are said to be driven by personal achievement and success (Pew Research Center, 2007). Some have made the observa- tion that GenXers “work to live” whereas Boomers “live to work” (Chao, 2005). Empirical evidence also suggests that Generation X values work–life balance. For example, Burke (1994) found that Generation X rated a balanced lifestyle as one of the most important job factors while company perks and community status were the least important. Other studies have drawn similar conclusions and found that family

and personal relationships are more important to Generation X’s personal happiness than their work (Arnett, 2000; Eskilson & Wiley, 1999; Smola & Sutton, 2002). Additionally, the Families and Work Institute (2006) reports that GenXers are more family centric than both Boomers and Millennials.

While work–life balance is related to numerous work behaviors, we argue that willingness to work overtime is one way a greater need for work–life balance is manifested. Since the very nature of overtime involves working more hours than the normal workload, working overtime is likely in direct competition with time devoted to family obligations, hobbies, and activities outside of work (Mayo Foundation for Medical Education and Research, 2008). To test the popular stereotypes suggesting that GenXers differ considerably from other generations concerning the value they attach to work– life balance, we hypothesize that GenXers will exhibit less willingness to work overtime in comparison with Boomers or Millennials.

Hypothesis 3. GenXers will report less willingness to work overtime than Boomers or Millennials.

Method

Sample and procedure

Study participants were job applicants for a variety of posi- tions in two different hospitals located in the southeastern United States. As part of the application process, job seekers completed a biodata questionnaire (to be described in more detail in the Measures section) and an online application that included birth date. A total of 8,128 applicants were available for analysis. The sample consisted of 1,641 (20.2%) Baby Boomers, 4,972 (61.2%) GenXers, and 1,515 (18.6%) Millennials. The mean age of Baby Boomers was 48.5 years old (SD = 4.79), the mean age of GenXers was 30.8 years old (SD = 5.05), and the mean age of Millennials was 21.5 years old (SD = 1.38). The sample consisted of 301 (3.7%) Native Americans, 116 (1.4%) Asian/Pacific Islanders, 237 (2.9%) Hispanics, 3,955 (48.7) African Americans, and 3,211 (39.5%) Caucasians. A total of 308 (3.8%) did not disclose their race. The sample was comprised of 6,828 (83.2%) females and 1,300 (15.8%) males while 83 (1%) failed to provide their gender.

Measures

To measure differences in workplace behaviors among indi- viduals from different generations, we drew from applicant responses to a biodata measure on an employment applica- tion. The instrument used in the present study was developed and validated for use as a selection device in the health care industry (Becton, Matthews, Hartley, & Whitaker, 2009). The

Becton et al. 179

biodata instrument presented 40 multiple-choice questions and scenarios that asked applicants about previous life experiences related to high school, college, and work assign- ments. A sample of items from this instrument was selected for the present study, matching the content of the items to the behaviors of interest.

Job mobility behaviors

Job mobility behaviors were measured via two biodata items. The first item asked applicants to indicate the longest time ever spent in one job and response options included 1 (less than three months), 2 (three to six months), 3 (six months to one year), 4 (one to two years), 5 (two to five years), and 6 (more than five years). To aid in the interpretation of our results, the data were re-coded to reflect a more quantitative measure by calculating the midpoint of each category in months (i.e., 1 = 1.5 months, 2 = 4.5 months, etc.). The second item asked applicants the number of jobs held in the last five years and response options included 1 = one, 2 = two, 3 = three, 4 = four, and 5 = five or more. A summary of mean responses to job mobility behavior items by generation is given in Table 1.

Compliance with work rules

Compliance behaviors were measured using two biodata items. The first item asked applicants to report how their most recent supervisor would rate their attendance. Response options included 1 (bottom 5%), 2 (lower than most), 3 (typical of most people), 4 (higher than most), and 5 (top 5% of all employees).

The second item asked applicants how their most recent supervisor would rate their appearance as it related to adher- ence to dress code. Response options included 1 (never appro- priate), 2 (sometimes appropriate), 3 (usually appropriate), and 4 (always appropriate). A summary of compliance behav- iors by generation is given in Table 2.

Terminations

Terminations were assessed using a biodata item asking the number of times an applicant had been fired in the past. Response options for this question included 1 (never), 2 (I left a job to avoid being fired), 3 (I have been fired once), and 4 (I have been fired at least twice). A summary of terminations by generation is given in Table 3.

Table 1 Job Mobility and Control Variables. Sample Means with Standard Deviations Given in Parentheses

Generation

Job mobility

Age Longest number of months spent in single job

Number of jobs held in the last 5 years

Boomers 72.9 (20.2) 2.0 (1.0) 48.5 (4.8) Gen X 48.5 (24.7) 2.5 (1.1) 30.8 (5.0) Millennials 22.6 (16.6) 2.6 (1.1) 21.5 (1.4) Total 48.6 (27.4) 2.4 (1.1) 32.6 (9.8)

Table 2 Compliance with Work Rules

Generation

Attendance rating

Bottom 5% (%)

Lower than most (%)

Typical of most (%)

Higher than most (%)

Top 5% (%)

Boomers 0.18 0.31 13.73 34.05 51.74 Gen X 0.22 0.60 20.90 33.66 44.62 Millennials 0.00 0.40 17.36 34.92 47.26 Total 0.17 0.50 18.79 33.97 46.55

Generation

Appearance rating

Never appropriate (%)

Sometimes appropriate (%)

Usually appropriate (%)

Always appropriate (%)

Boomers 0.06 0.18 5.24 94.52 Gen X 0.08 0.20 4.89 94.83 Millennials 0.14 0.48 6.77 92.62 Total 0.09 0.25 5.30 94.36

Table values represent the sample percent of a given generation who selected the corresponding column category response.

180 Generational differences in behavior

Willingness to work overtime

Willingness to work overtime was measured with one biodata item. This item asked applicants how often their most recent supervisor would say they were willing to work overtime. Response options included 1 ( never when asked), 2 (rarely when asked), 3 (occasionally when asked), 4 (most times when asked), and 5 (every time when asked). A summary of willing- ness to work overtime by generation is given in Table 4.

Control variables

Scholars have argued that it is difficult to separate the effects of age and generation (Macky et al., 2008; Twenge & Campbell, 2008), and this is a challenge for all generational research (Parry & Urwin, 2011). For example, including age as a covariate is inappropriate because it has a naturally high correlation with generational cohort (Egri & Ralston, 2004). Further, due to the partial nature of coefficients in statistical models, it is not possible to interpret the effect of generation while holding age constant. Thus, in an attempt to explore a potential age confound, we included a control variable labeled “relative age.” Relative age was calculated for each applicant by subtracting the mean age for their generation from their own age, and thus measures the distance from their age to the average of their generation (see Table 1 for a summary of mean age by generation). The “relative age” is computed by subtracting an individual’s age from the mean age of his/her generation. Thus, someone with a “relative age” of 5 is 5 years older than the average for his/her generation. Including this measure as a control variable allowed us to

examine the effects of age increases within each generation and provides insight into the potential age confound. In addi- tion to controlling for relative age in our analyses, we also included (when significant) an interaction term between “relative age” and generation. This allows for possible differ- ences in the slope of the relationship between age and the response variables by generation.

Gender was also included as a control variable because research suggests that males and females differ considerably with respect to job mobility (Booth, Franscesconi, & Garcia-Serrano, 1999; Keith & McWilliams, 1997) and will- ingness to work overtime (Becker & Moen, 1999; Keene & Reynolds, 2005).

Data and analysis

Due to the different response formats associated with our items (i.e., interval, ordinal, etc.), we used a variety of analyses to test our hypotheses. Additionally, several of the response options were selected by a small percentage of participants and we combined these categories with the next response option. We do not believe this adjustment influenced our results considering the model parameters in an ordinal logis- tic regression are invariant to collapsing adjacent categories (Greenland, 1994; Murad, Fleischman, Sadetzki, Geyer, & Freedman, 2003), and doing so when some categories are very sparse can improve the asymptotic fit of the maximum likeli- hood analysis.

The response options for the items relating to job mobility in Hypothesis 1 were measured on an interval scale, thus

Table 3 Terminations

Generation

Employment history

Never been fired (%) Quit since likely to be fired (%) Fired once (%) Fired at least twice (%)

Boomers 78.86 1.91 15.37 3.87 Gen X 80.03 1.79 16.08 2.10 Millennials 87.85 2.06 8.85 1.24 Total 81.22 1.86 14.62 2.30

Table values represent the sample percent of a given generation who selected the corresponding column category response.

Table 4 Willingness to Work Overtime

Generation

Willingness to work overtime

Never when asked (%)

Rarely when asked (%)

Occasionally when asked (%)

Most times when asked (%)

Every time when asked (%)

Boomers 0.24 0.92 11.72 43.28 43.83 Gen X 0.22 0.87 13.31 47.49 38.11 Millennials 0.69 1.31 10.27 47.21 40.52 Total 0.31 0.96 12.44 46.58 39.71

Table values represent the sample percent of a given generation who selected the corresponding column category response.

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hierarchical multiple regression analysis was used to test Hypothesis 1. Hypothesis 2 concerns compliance with work rules and terminations. The response options for each of these questions were ordinal. For the item relating to attend- ance, we combined the first two response options (1 = bottom 5%; 2 = lower than most) with the third response option (3 = typical of most) because these two options were selected by less than 1% of the sample for each category. This recoding resulted in three categories for attendance rating (3 = typical of most or lower; 4 = higher than most; 5 = top 5%) and ordinal logistic regression was used to test for generational differ- ences. Similarly, the response options for appearance ratings were ordinal, and the two lowest categories (1 = appearance is never appropriate; 2 = appearance is sometimes appropriate) were combined with the third response option (3 = appear- ance is usually appropriate). This adjustment created a binary coding of the appearance variable (3 = appearance is not always appropriate; 4 = appearance is always appropriate) and binary logistic regression was used to test Hypothesis 2 with respect to appearance rating. The response options for termi- nations were ordinal (e.g., 1 = never; 2 = I left a job to avoid being fired; 3 = I have been fired once; 4 = I have been fired at least twice) and did not require any adjustment; thus, ordinal logistic regression was used to test Hypothesis 2 with respect to terminations. Finally, we combined the lowest two response options for willingness to work overtime (1 = never work when asked; 2 = rarely work when asked) with the third category (3 = occasionally work when asked) and used ordinal logistic regression to test Hypothesis 3.

Results

Intercorrelations among the study variables are presented in Table 5. The correlations among age, longest number of months spent in a single job, and number of jobs held in the last 5 years were computed using Pearson’s product moment correlation. All correlations involving attendance rating, appearance rating, and employment history were computed using Spearman’s rank correlation. Hypothesis 1 posited that Boomers would exhibit fewer job mobility behaviors than GenXers and Millennials. Table 6 presents the hierarchical regression analysis used to test this hypothesis. Step 1

included only the control variables (i.e., gender and relative age). Step 2 included the controls and main effects for genera- tion (R2 = .34, p < .001). Step 3 included the controls, main effects for generation, and the interaction between relative age and generation (R2 = .014, p < .001). We contend that the relative age × generation interactions provided additional insight by investigating the effects of age increases on the vari- able of interest within each generation. As predicted, the main effect for generation indicated that Boomers reported longer time in one job than GenXers and Millennials. Specifically, when comparing individuals of the same gender and relative age, GenXers spent, on average, 24.16 fewer months on the job (95% CI −25.32, −23.00) than Boomers, while Millennials spent, on average, 50.21 fewer months on the job (95% CI −51.66, −48.76) than Boomers.

The significant relative age × generation interactions imply that the association between relative age and the time spent on the job differs due to generation. For Boomers, each additional year of relative age translates into an average job tenure of .69 months longer (95% CI .48.89). For Gen X, an additional year of relative age translates into 2.11 additional months of job tenure (difference between Boomers and Gen X is 1.42 months, 95% CI 1.18, 1.66). For Millennials, relative age seems even more important to job tenure, and an additional year of age is associated with 3.63 months longer on the job (difference between Boomers and Millennials is 2.94, 95% CI 2.15, 3.74). These results indicate that there are significant job tenure mean differences between Boomers and Gen X and between Boomers and Millennials when controlling for relative age and the inter- action between relative age and generation.

A similar analysis was performed to test for generational differences in the number of jobs held in the last 5 years (see Table 6). The second step of the hierarchical regression that included the main effects showed a significant change in unexplained variability (R2 = .03, p < .001), as did the third step that included the interaction term between generation and relative age (R2 = .02, p < .001). Results revealed that Boomers had fewer jobs in the past 5 years than either GenXers or Millennials. More specifically, GenXers of the same relative age and gender had an average of .45 more jobs (95% CI .39.50) than Boomers, while Millennials averaged

Table 5 Correlation Coefficients among Study Variables

Age Longest number of months spent in single job

Number of jobs held in the last 5 years

Attendance rating

Appearance rating

longest number of months spent in single job 0.565** Number of jobs held in the last 5 years −0.220** −0.272** Attendance rating 0.026* 0.090** −0.056** Appearance rating 0.029** 0.056** −0.014 0.133** Employment history −0.191** −0.160** −0.087** 0.000 0.017

**Correlation is significant at the .01 level. *Correlation is significant at the .05 level.

182 Generational differences in behavior

.55 more jobs (95% CI .48, .63) than Boomers. The significant relative age main effect indicated that an additional year of relative age is related to a .02 decrease in the average number of jobs held in the last 5 years (95% CI −.03, −.01) for Boomers. Additionally, the significant relative age × Gen X interaction suggests that an additional year of relative age resulted in a .04 decrease in the average number of jobs held in the last 5 years when compared to Boomers (difference between Boomers and GenXers is −.02, 95% CI −.04, −.01). Conversely, an additional year of age for Millennials results in an average increase of .18 jobs in the last 5 years as compared to Boomers (difference between Millennials and Boomers is .20, 95% CI .16, .25). Thus, comparable Millennials who are older in their generation tend to have held more jobs in the past 5 years, while comparable Boomers and GenXers who are older in the generation tend to have held fewer jobs, on average, in the past 5 years. These results suggest that there are

still significant mean differences in the number of jobs held in the past 5 years between Boomers and Gen X and between Boomers and Millennials when controlling for relative age and the interaction between relative age and generation. Taken collectively, results of both hierarchical regression analyses for the longest time spent in one job and for the number of jobs held in the past 5 years lend support for Hypothesis 1.

Hypothesis 2 predicted that Boomers would exhibit more instances of compliance with work rules and fewer termina- tions than GenXers and Millennials. Tables 7–9 contain results of the regression analyses used to test the hypoth- esized generational effects on appearance, attendance, and terminations.

Concerning attendance, results indicated that there was overall significance associated with the fitted model contain- ing relative age, gender, and generation as predictors of

Table 6 Regression Analysis of Job Mobility Behaviors

Variable

Longest time in one job Number of jobs in the past 5 years

b 95% CI β R2 ΔR2 b 95% CI β R2 ΔR2

Step 1 .09 .02 Constant 52.59 (51.17, 54.01) 2.45 (2.40, 2.51) Sex (1 = female) −4.75*** (−6.30, −3.20) −.06 −.05 (−.11, .02) −.02 Relative age 1.81*** (1.69, 1.94) .30 −.03*** (−.04, −.03) −.14

Step 2 .42 .33*** .05 .03*** Constant 76.35 (74.92, 77.84) 2.09 (2.02, 2.16) Sex (1 = female) −4.30*** (−5.53, −3.05) −.06 −.07* (−.13, −.00) −.02 Relative age 1.81*** (1.71, 1.91) .30 −.03*** (−.04, −.03) −.14 Gen X −24.16*** (−21.33, 23.00) −.43 .45*** (.39, .50) .20 Millennial −50.20*** (−51.66, −48.74) −.71 .57*** (.49, .64) .20

Step 3 .43 .01*** .07 .02*** Constant 76.45 (75.03, 77.87) 2.10 (2.03, 2.17) Sex (1 = female) −4.41*** (−5.64, −3.18) −.06 −.07* (−.14, −.01) −.03 Relative age .69*** (.48, .89) .12 −.02*** (−.03, −.01) −.09 Gen X −24.16*** (−25.32, −23.00) −.43 .45*** (.39, .50) .20 Millennial −50.21*** (−51.66, −48.76) −.71 .55*** (.48, .63) .20 Gen X × age 1.42*** (1.18, 1.66) .21 −.02*** (−.04, −.01) −.09 Millennial × age 2.94*** (2.15, 3.74) .03 .20*** (.16, .25) .13

Note. For this analysis, the generation variables were coded as Gen X = 1, 0 otherwise; and Millennial = 1, 0 otherwise. *p < .05. **p < .01. ***p < .001.

Table 7 Ordinal Multinomial Regression Analysis of Attendance

Variable β SE b Wald’s X2 eβ (odds ratio) 95% CI eβ

Lower than most people −5.42 .15 1,301.07*** .004 (.003, .006) Typical of most people −1.84 .07 688.65*** .16 (.14, .18) Higher than most −.28 .07 16.86*** .76 (.67, .87) Millennial −.19 .07 8.02** .83 (.73, .94) Gen X −.34 .05 39.36*** .71 (.64, .79) Sex (1 = female) −.21 .06 12.755*** .81 (.73, .91) Relative age .003 .005 .489 1.00 (.99, 1.01)

Note. The last response category, “In the top 5%,” was the reference category. The Boomers category was used as the reference category for genera- tion, and male was used as the reference category for sex. *p < .05. **p < .01. ***p < .001.

Becton et al. 183

attendance behaviors (log likelihood = −8,670.33, χ2 = 56.19, df = 4, p < .001). However, the interaction between relative age and generation was not significant, thus not included in the fitted model. The reported proportional odds ordinal logistic regression model (see Table 7) compares the odds of a respondent selecting the next higher category over the com- bined adjacent and lower categories. Because of the categori- cal nature of the generational variable and gender control variable, the odds for each of these variables are compared relative to a specific reference category. For all logistic regres- sion models in this paper, we selected male as the referent cat- egory for gender and Boomer as the referent category for generation. Thus, for example, the Gen X coefficient (eβ = .71, 95% CI .64, .79) is interpreted as the odds of a Gen X member selecting the next higher attendance category as compared to a Boomer of the same relative age and gender. Because this odds ratio is less than 1, it implies a 29% reduction in the odds of GenXers selecting a higher attendance category compared to Boomers. Similarly, the odds of comparable Millennials responding in the next higher attendance category is .83 that of Boomers (95% CI .73, .94). This implies a 17% reduction in the odds of comparable Millennials rating their attendance in the higher category than Boomers.

Table 8 presents the binary logistic regression results used to test generational differences for the appearance dimension of Hypothesis 2. Again, the relative age × generation interac- tions were not significant and thus excluded from our final model. The final model indicated a significant association between generation and appropriate appearance (log likeli-

hood = −1,719.02, χ2 = 55.23, df = 4, p < .001). The results indicate that when controlling for relative age and gender, Millennials’ odds of responding in the category of “usually appropriate” is 1.4 times higher than that of a Boomer (95% CI 1.05–1.87). However, the odds of GenXers responding in the “usually appropriate” category was not significantly dif- ferent from that of Boomers (eβ = .99, 95% CI .97, 1.01).

Results of the ordinal logistic regression analyses for generational effects on terminations (see Table 9) indicated that there was an association between generation and disci- plinary action (log likelihood = −4,829.8, χ2 = 107.5, df = 4, p < .001). Again, this final model did not include the relative age × generation interactions because they were not signifi- cant in the original model. Our findings revealed that the odds of Millennials selecting the next higher response cat- egory over that of the combined lower categories was .51 times less than Boomers (95% CI .42, .62). However, the odds of GenXers responding in a higher disciplinary category was not significantly different than Boomers (95% CI .81, 1.1).

Taken collectively, results of the three analyses regarding attendance, appearance, and terminations provide partial support for Hypothesis 2. It is important to note that the rela- tive age × generation interactions were not significant in all three analyses, indicating that increases in age within each generation have similar effects on the workplace behavior associated with Hypothesis 2.

Hypothesis 3 predicted that GenXers would be less willing to work overtime than other generations. Table 10 presents the ordinal logistic regression analysis used to test this

Table 8 Binary Logistic Regression Analysis of Appropriate Appearance

Variable β SE b Wald’s X2 eβ (odds ratio) 95% CI eβ

Usually appropriate −2.27 .13 291.28*** .10 (.08,.13) Millennial .34 .15 5.13* 1.40 (1.04,1.87) Gen X −.03 .13 .05 .97 (.78,1.25) Sex (1 = female) −.77 .11 49.03*** .46 (.38,.58) Relative age −.01 .01 1.44 .99 (.97,1.01)

Note. The last response category “always appropriate” was used as the reference category. The Boomers category was used as the reference category for generation, and male was used as the reference category for sex. *p < .05. **p < .01. ***p < .001.

Table 9 Ordinal Multinomial Regression Analysis of Termination

Variable β SE b Wald’s X2 eβ (odds ratio) 95% CI eβ

Never been fired .956 .08 132.7*** 2.60 (2.21,3.06) Left because likely to be fired 1.09 .08 169.5*** 3.00 (2.51,3.48) Fired once 3.26 .11 923.2*** 25.90 (21.00,31.95) Millennial −.68 .10 46.0*** .51 (.42,.62) Gen X −.07 .07 1.1 .93 (.81,1.07) Sex (1 = female) −.44 .07 36.2*** .65 (.56,.75) Relative age .02 .01 12.6*** 1.0 (1.01,1.03)

Note. The last response category “fired twice or more” was used as the reference category. The Boomers category was used as the reference category for generation, and male was used as the reference category for sex. *p < .05. **p < .01. ***p < .001.

184 Generational differences in behavior

prediction. The interaction between generation and relative age was originally included in our model but found to be not significant, and thus excluded from the final model. Our final model indicated an association between generation and willingness to work overtime (log likelihood = −7,963.13, χ2 = 43.71, df = 4, p < .001). Further, results suggested that the odds of selecting the next higher response category over that of the combined lower categories differed significantly between GenXers and Boomers.

More specifically, the odds of GenXers responding in a higher willingness to work overtime category is .82 times lower (95% CI .73–.94), on average, than Boomers. As expected, there was no significant difference between compa- rable Millennials and Boomers in terms of the odds of will- ingness to work overtime. These results provide support for Hypothesis 3 and indicate that GenXers are less likely to work overtime as compared to Boomers and Millennials.

Discussion

The results of the present study suggest that while genera- tional differences exist in some workplace behaviors, the popular generational stereotypes are not always consistent with workplace behaviors. As mentioned earlier, these find- ings deviate from the majority of existing generational differ- ences research in that our study focused on job behaviors versus attitudes or values. We believe our results can be instructive and have important implications for management and HR practices.

Overall, our results suggest that organizations should be cautious in taking the advice of some scholars to implement HR strategies that recognize the unique values and charac- teristics of each generation versus general strategies applied to all generations of employees (D’Amato & Herzfeldt, 2008). Although we did find evidence of some generational differences in workplace behavior, the effects sizes were quite small as evidenced by the small, but statistically sig- nificant changes in R2 in the hierarchical regression analysis, and the odds ratios near 1.0 in the ordinal logistic regression analyses. As such, we tend to agree with others who have argued that the cost of tailoring HR practices to each gen-

eration may outweigh the potential benefits (Kowske, Rasch, & Wiley, 2010). Moreover, we caution practitioners to avoid treating employees simply as members of genera- tions, ignoring the fact that other individual differences likely play a more prominent role in workplace behaviors than generational differences (cf. Twenge, 2010). Rather than developing HR strategies that target specific genera- tions, organizations may be better served by designing greater flexibility into HR practices and strategies in order to address the needs and values of all employees regardless of generational cohort group.

The inclusion of relative age in our analyses also has impor- tant implications. This approach allowed us to compare increases in age within each generation on the investigated workplace behaviors. In terms of our specific findings, the significant relative age × generation interaction effects for job mobility behaviors indicated that increases in age within younger generations (i.e., GenXers and Millennials) had a greater effect on these behaviors than increases in age within the Boomer generation. These results suggest that we should interpret our findings regarding generational differences in job mobility behaviors with caution. More specifically, gen- erational differences in job mobility behaviors may be attrib- uted to age or life stage effects versus a pure generational effect. For example, some scholars argue that human develop- ment is characterized by different life stages that are unique in terms of cognitive, emotional, and behavioral experiences (cf. Levinson, 1980). As such, the nature of jobs held by older workers or their current life cycle may explain the lower job mobility behaviors for Boomers. However, the relative age × generation interactions were not significant for the other workplace behaviors, providing more evidence of generational effects on workplace behaviors. Additionally, inspecting the results of the study seems to suggest that at least some of the differences cannot be explained simply by age. For example, we found that participants from older gen- erations generally reported being fired fewer times than younger generations. If age alone influenced results, we would expect the opposite because older generations have been in the workforce longer and have had more opportu- nities to be fired.

Table 10 Ordinal Multinomial Regression Analysis of Willingness to Work Overtime

Variable β SE b Wald’s X2 eβ (odds ratio) 95% CI eβ

Never or occasionally when asked −2.24 .07 946.86*** .11 (.09,.12) Most times when asked .03 .07 .15 1.03 (.90,1.17) Millennial −.09 .07 1.65 .92 (.80,1.05) Gen X −.20 .05 13.68*** .82 (.73,.91) Female −.30 .06 26.59*** .74 (.66,.83) Relative age −.00 .00 .07 1 (.99,1.01)

Note. The last response category “every time when asked” was used as the reference category. The Boomers category was used as the reference cat- egory for generation, and male was used as the reference category for sex. * p < .05. **p < .01. ***p < .001.

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Limitations and future research

While our study reveals some interesting results, we should note several potential limitations. Due to the cross-sectional nature of our data, we were unable to explicitly test for age, life stage, or career stage effects. While the relative age measure used in our analyses provides unique insight into these issues, we encourage future researchers to further investigate generational differences using other data collec- tion methods such as longitudinal designs. As suggested by an anonymous reviewer, another possibility is for future researchers to use additional individual variables (e.g., number of children, applying for full-time or part-time jobs) as proxies for family or life stage effects. Unfortunately, the field data collection design prevented us from collecting this type of data because participants were applying for actual jobs, and it would be illegal for us to ask specific ques- tions about number of children, marital status, etc. Simi- larly, we echo Parry and Urwin’s (2011) call for future research to explicitly consider other within-generation indi- vidual characteristics such as ethnicity or national culture.

The nature of the data used for analyses presents another possible limitation. We collected data from participants’ self- reported biodata items on an employment application and the accuracy of self-report data is often debated. However, research has shown that the accuracy of biodata can be max- imized by using several strategies. First, the more objective (i.e., verifiable) the biodata items, the greater the accuracy (Becker & Colquitt, 1992; Schrader & Osburn, 1977; Shaffer, Saunders, & Owens, 1986). All items used in the current study were objective and verifiable. Second, informing applicants

their responses are subject to independent verification reduces the likelihood of faking or giving socially desirable answers (Kluger & Colella, 1993). All participants in this study signed an acknowledgment that their responses may be verified and dishonest answers would result in disqualifica- tion from the hiring process. Although the authors feel that adequate measures were taken to ameliorate the effects of faking or giving socially desirable responses, we cannot com- pletely rule out such concerns. Future research would benefit from assessing generational differences in workplace behav- ior using sources such as official employment records of dis- ciplinary action, rules violations, terminations, etc.

A final limitation concerns statistical significance and sample size. While our study did find significant differences between generational cohort groups on several work-related behaviors, our sample size was very large. With large samples, even small effects can be found to be highly significant. Thus, results should be interpreted in light of effect sizes, which were small.

Conclusion

The current study extended previous research on the effects of generational differences in the workplace by investigating actual employee behaviors. While results indicated some gen- erational differences in workplace behavior exist, the effect sizes for these relationships were small. As such, we caution organizations from exerting much effort to redesign practices and policies in an attempt to more effectively manage workers from different generations.

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