Talkin’ ‘Bout Your Generation: The Impact of Applicant Age and Generation on Hiring-Related Perceptions and Outcomes

Abstract

Two scenario-based studies were conducted to explore the relative impact of a job candidate’s age compared to generational membership on hiring-related perceptions and outcomes. Study 1 used paper stimulus materials and manipulated whether a job candidate was described as 60 years old, a Baby Boomer, 29 years old, or a Gen-Y/Millennial. Graduate student participants evaluated the job candidates across a number of traits and assessed their suitability for the job of Sales Director. Study 2 employed equivalent stimulus materials but was conducted 3 years later using an older and more age-diverse sample and an online data collection methodology. Consistent with hypotheses, there was strong evidence across the 2 studies that job candidates described as 60-year-olds were perceived as the least motivated and adaptable relative to the other job candidates. By contrast, compared to younger job candidates (Gen-Y/Millennial and 29-year-old), job candidates described as Baby Boomers were perceived to have similar levels of motivation across studies and similar levels of adaptability in Study 2. Baby Boomers were also perceived as significantly more motivated and adaptable than older applicants (60-year-old) in Study 2. Finally, both studies provided evidence of an indirect effect of applicant age and generation on hiring outcomes through perceptions of motivation, adaptability, and in Study 1, competence.

It requires only a quick perusal of the covers of some of the most popular business magazines and newspapers to understand U.S. businesses’ keen interest in, and some might suggest obsession with, generational differences. Authors in the popular press suggest that generational differences are ubiquitous and “may be wreaking havoc” in the workplace (e.g., Vozza, 2014). Others assert that what we are seeing in the workplace is “… about more than age” (e.g., Milligan, 2014), and suggest ways to bridge the workplace generation gap and better understand generational stereotypes. This interest in generations and generational differences is in part due to the fact that there are significant numbers of members of four generations working in the workplace today (Green, Eigel, James, Hartmann, & McLean, 2012).

Despite this focus in the popular press, there has been limited academic research on generations and intergenerational dynamics within organizations (North & Fiske, 2015; Perry, Hanvongse, & Casoinic, 2013). Much of the research exploring generations in the workplace has focused on actual differences in employees’ self-reported values, preferences, attitudes, and behaviors relevant to the workplace (e.g., Parry & Urwin, 2011; Twenge, 2010) and found mixed and limited evidence for the existence of generational differences (Costanza & Finkelstein, 2015; Deal, Altman, & Rogelberg, 2010; Lyons & Kuron, 2014). This may be because there is a great deal of diversity within generations leading to more similarities than differences across generations (Green et al., 2012). This may also be due to significant methodological challenges that this research faces, including the use of research methodologies that confound generational differences with other types of differences (e.g., age, period; Lyons & Kuron, 2014). Finally, the generational differences that are found are often modest and may have little practical significance for the workplace (Deal et al., 2010).

What organizational researchers and practitioners have yet to fully explore is whether individuals have generational stereotypes (Perry, Golom, & McCarthy, 2015; Perry et al., 2013). However, it is possible that the forces that have led to the development of age and other salient demographic stereotypes are also contributing to the development of generational stereotypes. Generational stereotypes might account for the persistence of employers’ beliefs that there are actual generational differences regardless of whether these differences actually exist. It is important to explore whether people have and use generational stereotypes that are distinct from age stereotypes for several reasons. First, if we find that there is limited evidence for perceived generational differences, in addition to actual differences, this might suggest that “generation gaps” and interventions designed to address them are another business fad whose time will pass. Second, if age and generational stereotypes are found to be profoundly similar then age discrimination that could result from the use of generational (rather than highly correlated age) stereotypes may be rationalized by employers and legally permissible if decisions appear to be generation rather than age based as U.S. law prohibits age-but not generation-based discrimination. Finally, if there is evidence that age and generational stereotypes are differentiated constructs, we should explore the impact of using generational compared to age stereotypes on work-related outcomes. In light of limited evidence of actual generational differences, a reliance on generational stereotypes could potentially result in misjudgments.

The current research explores the extent to which decision makers have age and generational stereotypes and the consequences of these stereotypes for hiring-related decisions. We conducted two experimental scenario-based studies to assess the extent to which perceptions and hiring-related decisions made about a job candidate differ as a function of whether an applicant is described on the basis of age compared to generational membership. Finally, unlike much previous research, we directly explore the mediating role of stereotypes on the relationship between a target applicant’s age/generation and employment outcomes.

STEREOTYPES

Stereotypes are beliefs about the characteristics, traits, and behaviors associated with individuals who are members of a particular group (Hilton & von Hippel, 1996). Mackie, Hamilton, Susskind, and Rosselli (1996) suggested that stereotypes apply to social groupings that are salient to the perceiver and that “… possible stereotypes are limited only by the number of attributes human observers may see as socially meaningful” (p. 43). Stereotypes develop in many different ways, including being socially transmitted to members of a particular culture (Mackie et al., 1996) and further develop as a result of information about social targets being repeatedly passed from person to person (Martin et al., 2014). Once these stereotypes exist, they can be easily learned and progressively transmitted.

We suggest that perceptions of and expectations about different generations are likely to be socially transmitted in the context of our culture’s heightened attention to generations and as a result of the prevalent societal discourse related to generational differences in the United States in general, and the U.S. workplace more specifically. Further, a greater focus on generations and generational differences today likely makes an individual’s generational membership meaningful and salient. As a result of these processes, it is possible and likely that people have generational stereotypes.

Below, we review the content of age stereotypes and the nascent research on the content of generational stereotypes. The content of these age and generational stereotypes is likely to overlap but differ in important ways because age and generational membership are similar but also different. For example, although membership in generational categories is permanent, membership in age categories (e.g., young, middle-aged, old) is not. This may have implications for how perceivers represent these types of stereotypes cognitively (e.g., how tight the boundaries around these categories are). In addition, although generations are differentiated on the basis of the temporal, historical, and sociological conditions they share and the consequent values they have or are perceived to have, differently aged individuals are often differentiated in part on the basis of their perceived physical competencies.

Older Worker Stereotypes

A good deal of research has explored the content of age stereotypes and the consequences of their use for employment decisions and outcomes (e.g., Bal, Reiss, Rudolph, & Baltes, 201l; Posthuma & Campion, 2009). The majority of this research has tended to focus on older people (Finkelstein, Ryan, & King, 2012) and found that older workers tend to be viewed more negatively than younger workers (Posthuma & Campion, 2009; Truxillo, Cadiz, & Rineer, 2014). For example, in their review of 117 relevant articles and books on age stereotyping in the workplace, Posthuma and Campion (2009) concluded that older workers are generally perceived as having lower ability, less motivation, and being less productive than younger workers. They also found that older workers were perceived as harder to train, less adaptable, less flexible, more resistant to change, and less able to learn. Finally, the same authors found that older workers were perceived to have shorter job tenure and to be more costly to employ.

Although negative stereotypes about older workers tend to be more common, older workers are also associated with some positive stereotypes, including reliable, dependable, honest, trustworthy, and loyal (Perry & Parlamis, 2005; Posthuma & Campion, 2009; Posthuma, Wagstaff, & Campion, 2012). More recent research confirms that people have both positive (knowledgeable, responsible) as well as negative (narrow-minded, set in their ways) stereotypes of older workers (Finkelstein et al., 2012). It is important to point out that despite their pervasiveness, there is limited empirical evidence to support the accuracy of most of these stereotypes (e.g., Beier & Kanfer, 2013; Ng & Feldman, 2012).

Younger Worker Stereotypes

Although older worker stereotypes have received the greatest amount of research attention, there is some limited research exploring younger worker stereotypes (Finkelstein et al., 2012; Truxillo et al., 2014). Younger worker stereotypes have been found and are often assumed to be more positive (e.g., more productive, more motivated, more creative) than older worker stereotypes (Avolio & Barrett, 1987; Perry et al., 2013; Rosen & Jerdee, 1976; Truxillo et al., 2014). However, recent research suggests that younger workers are perceived both positively and negatively (Finkelstein et al., 2012; Truxillo et al., 2014). For example, Finkelstein and colleagues (2012) found that younger workers were perceived as more adaptable, fun, and competitive, but also more materialistic and impulsive. Truxillo and colleagues (2014) suggested that there was some evidence that younger workers are perceived as less trustworthy, less loyal to their organizations, and as engaging in fewer individually focused organizational citizenship behaviors.

Age Discrimination

Age stereotypes are often assumed and sometimes explicitly shown to be a precursor of age discrimination (Diekman & Hirnisey, 2007; Finkelstein & Farrell, 2007; Krings, Sczesny, & Kluge, 2011). For example, in their meta-analytic review of age discrimination research from laboratory and field settings, Gordon and Arvey (2004) found a significant although modest overall effect size such that younger applicants and workers were evaluated more positively than older applicants and workers. In a more recent meta-analysis of the impact of age on work-related outcomes, Bal and colleagues (2011) similarly found significant and moderately sized negative effects of age on selection, advancement, general evaluation, and interpersonal skills outcomes. Further, research suggests that older workers face more obstacles and have fewer opportunities (e.g., for training) than younger workers both in the United States and abroad (Perry & Parlamis, 2005).

Researchers suggest that age stereotypes likely mediate the relationship between worker age and employment outcomes (e.g., Posthuma et al., 2012). However, this relationship is often inferred and infrequently tested (Finkelstein & Farrell, 2007; Krings et al., 2011) with some exceptions (e.g., Chiu, Chan, Snape, & Redman, 2001; Diekman & Hirnisey, 2007; Krings et al., 2011; Richardson, Webb, Webber, & Smith, 2013). For example, Chiu and colleagues (2001) found that the more respondents perceived older workers as being adaptable to change, the more favorable their employment-related views related to training, promotion, and retention. Similarly, Diekman and Hirnisey (2007) found that older workers were perceived as less adaptable than younger workers and this perception predicted hiring bias especially for a position involving change. The authors also explored but found no support for the mediating effect of perceived reliability. They concluded that perceptions of adaptability may be most important for some age-related biases. Richardson and colleagues (2013) found no evidence that perceived reliability, sociability, trainability, or intellectual competence mediated the effect of applicant age on likelihood of hiring. Although age was negatively related to hiring evaluation and perceived trainability and sociability, there was no evidence of a mediated relationship. Finally, Krings and colleagues (2011) found that perceptions of competence and warmth mediated the effects of age on selection-related decisions. Although perceptions that older workers are less competent operated as a mediator as expected, perceptions that older workers are less warm also unexpectedly operated as a mediator. In sum, this research suggests that age-based discriminatory employment decisions and outcomes may be in part a function of the operation of different aspects of age stereotypes.

Generational Stereotypes

Generations are defined as groups of similarly aged individuals who share historical and social experiences at key developmental periods in their lives. These shared experiences create similarities among those in a cohort and distinguish it from other cohorts (Costanza, Badger, Fraser, Severt, & Gade, 2012; Kupperschmidt, 2000). Although the exact definition and birth year ranges used to describe different generations vary, they are generally grouped into three distinct cohorts that are most active in the workforce today: Baby Boomers, Generation-X, and Generation-Y/Millennials (Parry & Urwin, 2011). In the United States, Baby Boomers are individuals born between the end of WWII (1945) and early to mid-1960s, Generation-Xers between early to mid-1960s to mid- to late 1980s, and Generation-Y/Millennials between late 1970s and early 1980s to late 1990s (Green et al., 2012; Lyons & Kuron, 2014).

Perhaps surprisingly, little empirical research has explored the existence of generational stereotypes (Lyons, Duxbury, & Higgins, 2007; Perry et al., 2013) but instead has focused on actual generational differences in individuals’ self-reported values, preferences, attitudes, and behaviors (Perry et al., 2013). Several studies which were not designed to measure generational stereotypes per se, provide some indirect evidence for perceived generational differences (Burke, 2004; Gursoy, Maier, & Chi, 2008; Jovic, Wallace, & Lemaire, 2006). However, these studies are limited both conceptually (e.g., Gursoy et al., 2008, focused on narrow aspects of perceived generational differences) and/or methodologically (e.g., Burke, 2004, potentially confounded age and generational perceptions). Several more recent studies provide more direct evidence for the existence of generational stereotypes (e.g., Lester, Standifer, Schultz, & Windsor, 2012; Perry et al., 2013; Roberto & Biggan, 2014). Because we are interested in the relationship between generational and age stereotypes, our review primarily focuses on research by Perry and colleagues (2013) which explored this relationship directly.

Perry and colleagues (2013) assessed the extent to which people have generational stereotypes that are distinct from age stereotypes as well as the content of these stereotypes. The authors’ research suggests that although there is overlap between age and generational stereotypes, this overlap is far from complete and both age and generational stereotypes also have unique content. The researchers conducted an exploratory study assessing the content of generational stereotypes in a sample of graduate students. They then compared their results from this study with generational stereotypes identified in the practitioner and academic literatures and found some although limited convergence. Overlap between the authors’ exploratory study and academic research was limited because the latter tended to focus on actual versus perceived generational differences. However, in both the exploratory study and the practitioner literature, Baby Boomers were perceived as hardworking, having company loyalty, resistant to change, valuing monetary rewards, and not technologically savvy. In addition, Gen-Y/Millennials were perceived as liking technology to communicate, being multi-taskers, rebellious, technologically savvy, entitled, and valuing work/life balance. However, practitioners also endorsed perceptions of Baby Boomers and Gen-Y/Millennials for which there was no empirical support in the exploratory study. The content of generational stereotypes found in this research (e.g., Baby Boomers are hardworking and technologically deficient, Millennials are tech savvy and entitled) overlaps with content found in other recent studies (Lester et al., 2012; Roberto & Biggan, 2014).

Next, the authors compared the content of the generational stereotypes that emerged from their research and review of the academic and practitioner literatures with the content of age stereotypes identified in the academic literature. These comparisons revealed some overlap, but also important differences in the content of Baby Boomer and older worker stereotypes, and Gen-Y/Millennial and younger worker stereotypes, respectively. For example, Baby Boomers and older workers were similarly perceived as loyal, resistant to change, and not technologically savvy. However, unlike older workers, Baby Boomers were also perceived as competitive, achievement oriented and career driven but not lower in ability to perform tasks, less productive, or less motivated. This is consistent with Weiss and Lang’s (2012) finding that older people (on average in their late 60s and early 70s) have different cognitive representations for their age group compared to their generation. Although generation was more strongly associated with positive characteristics and agency, age group was associated with less positive and more communal characteristics.

Further, Perry and colleagues (2013) found limited overlap between perceptions of Gen-Y/Millennials in the practitioner literature with younger worker stereotypes identified in the academic literature. However, the authors’ exploratory study suggested that similar to younger worker stereotypes, Gen-Y/Millennials were perceived as creative, ambitious, and flexible. The practitioner literature and exploratory study also revealed that unlike younger workers more generally, Gen-Y/Millennials were perceived as particularly tech savvy, rebellious, entitled, and multi-taskers.

In the current research, we explored how perceptions of a target may be differentially influenced when the target is described on the basis of age (29 or 60 years old) compared to generational membership (Gen-Y/Millennial or Baby Boomer). Although 60 year olds can be perceived on the basis of their age, they can also be perceived on the basis of their generational membership (as Baby Boomers) with potentially different implications. This is also the case for 29-year-olds who can be perceived on the basis of their age, or their generational membership (Gen-Y/Millennial). Based on the research conducted on age and generational stereotypes to date, we expect that relative to Baby Boomers, younger workers (29 years old), and Gen-Y/Millennials, older workers (60 years old) will be perceived as the least competent and the least adaptable. Despite the fact that Baby Boomers are older workers, because the former are perceived to be hardworking and achievement oriented and the latter are not, we anticipated that a target described as a Baby Boomer would not be perceived as negatively as the same target described as a 60-year-old. Although Gen-Y/Millennials may be perceived more negatively than younger workers (e.g., more entitled, rebellious; Perry et al., 2013), previous research is less clear on this point as younger workers are also sometimes viewed in negative terms (e.g., Finkelstein et al., 2012). Therefore, we did not anticipate significant differences between a target described as a Gen-Y/Millennial and the same target described as a 29-year-old. Further, we anticipated that perceptions of competence and adaptability would mediate the effects of a target worker’s age/generation on hiring outcomes. Specifically, because the older worker (60-year-old) was expected to be perceived as the least competent and adaptable, we expected these perceptions to result in this target having the poorest hiring-related outcomes. We offer the following hypotheses:

Hypothesis 1: Older applicants (60 years old) will be perceived as less competent and adaptable than Baby Boomer, Younger (29 years old), and Gen-Y/Millennial applicants.

Hypothesis 2: Perceptions of competence and adaptability will mediate the effect of applicant age/generation on hiring-related outcomes such that Older applicants (60 years old) will receive the poorest outcomes relative to Baby Boomer, Younger (29 years old), and Gen-Y/Millennial applicants.

We conducted two scenario-based studies to test the study hypotheses. Together, we believe these two studies provide a strong test of these hypotheses.

STUDY 1

Method

Participants and procedure

We obtained completed stimulus materials from N = 125 participants recruited from graduate level psychology courses at a college in the Northeastern United States. The sample was 63.2% female (n = 79), 35% male (n = 43), and 2.4% (n = 3) unreported. Almost half of the sample was White/Caucasian (49.6%, n = 62), 27.2% were Asian/Asian American (n = 34), 8.8% Hispanic (n = 11), 5.6% African American/Black (n = 7), 4% biracial (n = 5), 2.4% identified as other (n = 3), and 2.4% did not respond (n = 3). In addition, international students comprised almost 30% of the sample (n = 34). The sample was relatively young (M = 27.70, standard deviation [SD] = 4.92) with approximately 5 years of full-time work experience (M = 4.92, SD = 4.34). Further, 42% self-reported as Gen-Y/Millennial, 28.8% Generation X, 0.8% Baby Boomers, 24% did not know to which generation they belonged, and 4% did not respond to this question.

The study used a 4 (applicant demographic: Baby Boomer, 60-year-old, Gen-Y/Millennial, 29-year-old) × 2 (target applicant) × 2 (order of applicant) mixed experimental design with target applicant as a within-subjects factor and applicant demographic and order of applicant as between-subjects factors. Participants read a description for a Director of Sales position. This description was followed by information about two job applicants for this position. Participants were told that the purpose of the research was to better understand how people make employment-related decisions when provided with limited information. To enhance realism, participants were informed that they would be viewing actual job descriptions and applicant resumes with identifying information removed. Candidates were identified by their age (60 or 29 years old) or generation (Baby Boomer or Gen-Y/Millennial). This manipulation was presented in an Human Resources (HR) summary at the top of the applicant profile. Participants were informed that this summary, which also included background information about the applicant’s home town, family life, and experience, was based on HR’s review of the application materials (e.g., cover letter, resume, letters of recommendation).

Following the HR summary, information was provided about the candidate’s job search objective, education, and work experience in the past 5 years. Each participant viewed two target applicants’ profiles, only one of which (Thomas Shannon) was manipulated. The second applicant (Richard Anderson) was a filler applicant whose information remained constant across conditions; no age or generational information was provided about this applicant. The target and filler applicants were described as having comparable objectives, levels of education (the target had a BS in Economics, the filler a BS in Business), and work experience (the target had been a Regional Sales Manager and Sales Manager, the filler a District Manager and Store Manager). The target applicant profile was the same across the applicant demographic conditions except for one sentence in which the manipulation occurred. The order in which the two applicants were presented was counterbalanced. The HR summaries for both applicants, but which contained the experimental manipulation for the target applicant only, are indicated below:

Target applicant HR summary:

Tom is your typical 29-year-old (60-year-old, Baby Boomer, Gen-Y/Millennial). He grew up in Northern Massachusetts and is now married with twins. Tom appears to have been an effective regional and sales manager. He has the potential to develop new business and to effectively manage a sizable number of sales representatives.

Filler applicant HR summary:

Richard is originally from Ohio, and now lives with his wife and two children in the greater metro area. He appears to have good hands-on experience in developing and improving sales for wholesale and retail operations. He has the potential to effectively communicate, negotiate, and manage people.

Following each applicant profile, participants answered questions about the candidate’s traits, suitability, and salary if hired for the position. Following their evaluation of the second applicant, participants answered five fact-based questions about each applicant and two additional questions about the order in which they saw the candidates. Finally, respondents answered demographic questions about themselves. All measures reported in Study 1 and Study 2 were based on participants’ responses to the target applicant.

Independent Variable

Applicant demographic

The target applicant was described on the basis of his age (60 or 29 years old) or generation (Baby Boomer or Gen-Y/Millennial). We chose these ages because they are consistent with how previous research has defined older and younger workers (e.g., Finkelstein et al., 2012; Truxillo, Cadiz, & Hammer, 2015) and these ages clearly fall within the Baby Boomer (60) and Gen-Y/Millennial (29) cohorts.

Dependent Variables

Traits

Participants evaluated the extent to which the applicant possessed each of 26 traits on a 7-point Likert-type scale (1 = not at all, 7 = very much). Ten of the 26 traits were based on the stereotype content model, which suggests that all stereotypes can be described along two dimensions, warmth and competence (Fiske, Cuddy, Glick, & Xu, 2002). We averaged items to create a warmth (α = .80) and competence (α = .88) scale, respectively, based on measures used in previous research (Cuddy, Fiske, & Glick, 2008; Durante, Capozza, & Fiske, 2010; Fiske, Cuddy, & Glick, 2007).

The remaining 16 traits were included because they were strongly associated with age (e.g., loyal) and generational stereotypes (e.g., resistant to change, entitled) based on previous research (Perry et al., 2013). These 16 traits were subjected to an exploratory principal components analysis with varimax rotation. Only traits with factor loadings greater than .6 were retained (Field, 2013). This procedure resulted in two factors with eigenvalues greater than 1, explaining 47.15% of the variance. Six items loaded on the first factor, motivation (motivated, career-driven, ambitious, achievement-oriented, hardworking, dependable), and explained 27.66% of the variance. Four items loaded on the second factor, adaptability (resistant to change [reverse-scored], technology savvy, trainable, adaptable), and explained 19.49% of the variance. We averaged the items that loaded on each factor to create motivation (α = .87) and adaptability (α = .73) scales, respectively.

Liking

Three items assessed the extent to which respondents liked the job applicant on a 7-point Likert-type scale (1 = not at all, 7 = very much). An example item is, “How much do you think you would like this individual”? The items were averaged to form a liking scale (α = .91).

Suitability

Applicant suitability for the position was assessed using five items on a 7-point Likert-type scale. Sample items include, “How qualified is this applicant for this job position”? (1 = not at all qualified, 7 = very qualified), and “How suitable is this applicant for this job position”? (1 = not at suitable, 7 = very suitable). The items were averaged to form a suitability scale (α = .92).

Salary

Participants were told that the average starting salary for the Director of Sales position is approximately $90,000–$110,000 per year. They were then asked to identify the starting salary range they would offer the applicant if he was hired ($85,000–$89,999; $90,000–$94,999; $95,000–99,999; $100,000–104,999; $105,000–109,999; $110,000–114,999).

Control variables

Our sample included a sizable number of international students (27%). Based on previous research that suggests that generational cohorts may be defined differently across cultures, we controlled for participants’ international status (Deal et al., 2010; Parry & Urwin, 2011). In addition, we asked participants to indicate the number of years of full-time work experience they had, and controlled for this in all analyses.

Engagement

Participants were asked five fact-based questions about the target applicant based on the HR summary they read. They also answered an additional two questions regarding the order in which they saw each applicant for a total of seven questions intended to assess how engaged study participants were with the study. An engagement scale was created based on the number of these seven questions the respondent answered correctly. Participants who answered fewer than three (approximately 50%) of these questions correctly were considered insufficiently engaged, and their data were not included in the analyses (n = 5).

Manipulation checks

Participants were asked to indicate both the target applicant’s age and generational membership. We created a two part manipulation check based on their responses to these two questions. The first manipulation check was coded as correct if participants in the age condition accurately indicated the target’s age (60 or 29), and participants in the generation condition accurately indicated the target’s generation (Baby Boomer or Gen-Y/Millennial).

In order for the second manipulation check to be coded as correct, participants in the 29-year-old age condition had to indicate that the target was a member of the Gen-Y/Millennial or Gen-X generation. Those in the 60-year-old age condition had to indicate that the target was a member of the Gen-X or Baby Boomer generation. We accepted membership in the actual generational cohort or adjoining cohort as correct responses because the boundaries between cohorts are often defined differently in the literature and are somewhat porous (Green et al., 2012). Finally, those in the generation conditions (Baby Boomer, Gen-Y/Millennial) had to identify the target applicant as being an age that was within the most broadly defined boundaries of these generational cohorts identified in the literature (Green et al., 2012). Participants in the Baby Boomer condition needed to indicate that the target applicant was 50 years old or older, whereas those in the Gen-Y/Millennial condition needed to indicate that he was ≤35 years old. Forty-nine participants failed to answer both manipulation check questions correctly. Only participants who answered both manipulation check questions correctly were included in the final sample (N = 71).

Results

Applicant demographic

We conducted a 4 (applicant demographic) × 2 (order of applicant) Multivariate analysis of covariance (MANCOVA) on the dependent variables associated with our target applicant, controlling for respondents’ international student status and number of years of work experience. Because we found no main or interaction effects for order of applicant, we report the results of a one-way MANCOVA by applicant demographic on warmth, competence, liking, adaptability, motivation, suitability, and salary controlling for international student status and number of years of work experience. Hypothesis 1 suggested that the 60-year-old applicant would be perceived most negatively and receive the poorest hiring-related outcomes. The MANCOVA revealed a significant effect of applicant demographic, Wilk’s λ = .45, F(21, 161.35) = 2.45, p < .01, partial ɳ² = .23. None of the control variables had a significant multivariate effect on study outcomes. (The same pattern of results was found when we controlled for participant age, gender, and generation as covariates, respectively and together.)

Follow-up univariate tests indicated significant effects of applicant demographic on motivation F(3, 62) = 3.22, p < .05, partial ɳ² = .14; adaptability F(3, 62) = 6.51, p < .01, partial ɳ² = .24; and salary F(3, 62) = 3.02, p < .05, partial ɳ² = .13. Condition means appear in Table 1. A review of the means reveals the lowest perceived motivation for the 60-year-old applicant (M = 5.14). Follow-up pairwise comparisons indicate that the 60-year-old applicant was perceived as significantly less motivated than the Gen-Y/Millennial (M = 6.20, p < .05) but not the 29-year-old applicant (M = 5.58) or the Baby Boomer applicant (M = 5.57). No other mean comparisons were significant. Similarly, the 60-year-old applicant had the lowest mean perceived adaptability (M = 4.08). Pairwise comparisons revealed that the 60-year-old applicant was perceived as significantly less adaptable than the Gen-Y/Millennial (M = 5.42, p < .01) and 29-year-old applicants (M = 5.11, p < .01) but not the Baby Boomer applicant (M = 4.38). The only other significant mean difference was between the perceived adaptability of the Baby Boomer (M = 4.38) and the Gen-Y/Millennial applicant (M = 5.42, p < .05). The Baby Boomer and 60-year-old applicants had the highest mean salaries (M = 3.52, and M = 3.52). Pairwise comparisons indicated that salary was significantly higher for 60 year olds (M = 3.52) and Baby Boomers (M = 3.52) relative to the 29-year-old (M = 2.46, p < .05), but not the Gen-Y/Millennial (M = 3.12) applicant. No other mean comparisons were significant.

Indirect effects

To test Hypothesis 2, we explored whether the traits warmth, competence, adaptability, and motivation mediated effects of applicant demographic on our suitability measure using Hayes and Preacher’s (2014) guidelines for mediation analysis. These authors note that mediation is possible even if there is no effect of the predictor on the mediator, the mediator on the outcome or the predictor on the outcome (Hayes, 2009). Because the independent variable was multicategorical, the most appropriate method is the MEDIATE macro available for SPSS (Hayes & Preacher, 2014).

Results from mediation analyses for three of four potential stereotype mediators (competence, adaptability, motivation) are shown in Tables 2–4. There was no evidence that warmth operated as a mediator. The predictor variable, applicant demographic, was dummy coded and 60-year-old was the reference category. For each mediation model, we first verified that the independent variable (applicant demographic) and the mediator did not interact as required (Hayes & Preacher, 2014). Analyses revealed that one or more of our predictor dummy variables significantly influenced perceptions of adaptability and motivation, and marginally influenced competence. Further, perceptions of competence, adaptability, and motivation significantly influenced perceived suitability. Warmth was not found to influence hiring-related judgments. A bias-corrected 95% bootstrap confidence interval for the indirect effect based on 10,000 bootstrap samples was entirely above zero for one or more of our dummy variables for competence, adaptability, and motivation. These results suggest that the 60-year-old target was perceived as less adaptable relative to the Gen-Y/Millennial and 29-year-old targets and these perceptions contributed to the 60-year-old’s relatively lower perceived suitability for the job. In addition, the 60-year-old target was perceived as less motivated than the Gen-Y/Millennial target and this perception in turn contributed to the 60-year-old target’s relatively lower perceived suitability for the job. Finally, there was some limited evidence that applicant demographic influenced hiring judgments independent of its effect on the three stereotype mediators.

Discussion

Consistent with Hypothesis 1, the 60-year-old applicant had the lowest mean motivation and adaptability, although it was not always significantly different from the other condition means. As expected, the 60-year-old was perceived as significantly less adaptable than both younger job candidates (Gen-Y/Millennial and 29-year-old) and significantly less motivated than the Gen-Y/Millennial candidate. The Baby Boomer applicant was not perceived as significantly less motivated than the two younger job candidates. However, like the 60-year-old, the Baby Boomer applicant was perceived as less adaptable than the Gen-Y/Millennial candidate. There were no significant differences in perceptions of the Baby Boomer and 60-year-old applicant in terms of adaptability or motivation. We might conclude that Baby Boomers, unlike older applicants, have motivation levels that are equivalent to younger applicants (Gen-Y Millennials and 29-year-olds) and adaptability levels that are equivalent to 29-year-olds in this study. Taken as a whole, these results suggest some, but quite weak, evidence that perceptions of Baby Boomers and older workers differ. The two older workers (Baby Boomer, 60-year-old) were assigned higher salaries than the 29-year-old but not the Gen-Y/Millennial. This suggests a potential benefit to being described as a Gen-Y/Millennial compared to a 29-year-old. Consistent with Hypothesis 2, there was strong evidence of an indirect effect of applicant age/generation on hiring judgments through perceptions of adaptability, and motivation and weaker evidence for the role of competence.

STUDY 2

In order to assess the generalizability and robustness of Study 1 results, we conducted a second study 3 years later. We suspected that our results might be stronger in a sample that was likely to be more familiar with and have more developed generational stereotypes. Study 1 employed a graduate student sample that responded to paper stimulus materials. Study 2 was designed to replicate Study 1 and used the same design and equivalent stimulus materials. However, Study 2 targeted a more experienced and older sample that necessitated the use of an online data collection method rather than the paper and pencil materials used in Study 1.

Method

Participants and procedure

Participants were 245 Amazon Mechanical Turk (MTurk) users who completed an online version of the study for $1.00 in compensation. Research suggests that MTurk samples are demographically diverse and yield data that are comparable to traditional sampling methods (Buhrmester, Kwang, & Gosling, 2011). Several methods were used to ensure that MTurk users did not participate in the study multiple times (Mason & Suri, 2012) and were attentive while responding to the study materials (Meade & Craig, 2012). Individuals’ data (n = 20) were not included if they were not U.S. citizens or if they were careless responders. To identify the latter, based on recommendations for online surveys by Meade and Craig (2012), we included two instructed response items (e.g., “Respond with strongly disagree to this item”) and asked respondents whether, in their honest opinion, we should include their data. Respondents who did not respond as instructed or who indicated that their data should not be used were not included in the final sample. This resulted in a sample of N = 225 participants over the age of 18.

The sample was 54.2% women (n = 122), 45.3% male (n = 102), and 0.4% (n = 1) transgender. A large majority of the sample was White (80%, n = 180), 5.3% was Black/African American (n = 12), 5.3% Asian (n = 12), and 5.3% Hispanic/Latino (n = 12). Seven individuals (3.1%) identified as multiple races (3.1%), and 2 as “other” (0.9%). The average age of the sample was 37.18 years (SD = 11.36) with approximately 14 years of full-time work experience (M = 14.37, SD = 10.37). Approximately 61% of the sample worked full-time (n = 138), 21% part-time (n = 48), and 17% indicated they were unemployed (n = 38). Further, 23.1% self-reported as Gen-Y/Millennial (n = 52), 41.8% Generation X (n = 94), 19.1% Baby Boomers (n = 43), and 16% did not know to which generation they belonged (n = 36). Slightly less than half (47.1%, n = 106) had experience hiring employees.

Similar to Study 1, Study 2 used a 4 (applicant demographic: Baby Boomer, 60-year-old, Gen-Y/Millennial, 29-year-old) × 2 (target applicant) × 2 (order of applicant) mixed experimental design with target applicant as a within-subjects factor and applicant demographic and order of applicant as between-subjects factors. Qualtrics was used to host the stimulus materials and survey items. Similar to Study 1, participants were asked to read a Director of Sales job description and were then presented with profiles for two hypothetical job applicants, a target applicant (Thomas Shannon) and a filler applicant (Richard Anderson). The order of the job applicants was randomly determined by Qualtrics. As was the case in Study 1, demographic information about the target applicant was manipulated such that he was identified either by his age (60- or 29-year-old) or generation (Baby Boomer or Gen-Y/Millennial). The filler applicant’s profile was constant across conditions and contained no age- or generation-related information. Qualtrics randomly assigned participants to an applicant demographic condition.

Participants were told that the researchers had partnered with an HR department at a large company to test a new online system for hiring job applicants. Several small changes were made to the Director of Sales job description and applicant profiles from Study 1. First, in order to make the job description more realistic, information about the position being 30% commission-based and requiring at least 5 years of progressively responsible sales experience was added to the description. Second, although no changes were made to the content of the applicant profiles from Study 1, applicant information was slightly reorganized and reformatted so that the profiles appeared more resume-like. Importantly, the experimental procedures for the two studies were similar.

Dependent variables

We used the same measures of warmth (α = .84), competence (α = .92), liking (α = .93), suitability (α = .93), and salary used in Study 1. An exploratory principal components analysis with varimax rotation was conducted on the 16 additional traits not associated with the warmth and competence scales. Three factors emerged with eigenvalues greater than 1, explaining 60.17% of the variance. Traits with factor loadings greater than 0.6 were retained (Field, 2013). Five traits loaded on a motivation factor (motivated, career-driven, ambitious, achievement-oriented, hardworking) and accounted for 24.46% of the variance. Five traits loaded on an adaptability factor (technology-savvy, adaptable, trainable, innovative, multitasker) and accounted for 22% of the variance. Finally, two traits loaded on a dependability factor (loyal, dependable) and explained 13.71% of the variance. Based on these results, we created motivation (α = .90), adaptability (α = .87), and dependability (α = .75) scales, respectively. The motivation scale developed here significantly overlaps with that used in Study 1. The adaptability scale developed here is somewhat different from that found in Study 1 and a dependability scale was not found in Study 1. Analyses in each study were conducted with the two versions of the adaptability measure we created. The pattern of results was the same for both measures in Study 2 and similar but not identical in Study 1.

We used the same procedures as those in Study 1 to calculate an engagement score and to determine the accuracy of participants’ manipulation check responses. Five individuals scored lower than 3 on the engagement measure and 89 failed to answer both manipulation check questions correctly, resulting in a final sample size of N = 131 for the main MANCOVA and mediation analyses.

Results

Applicant demographic

Participant gender and hiring experience were included as control variables based on the results of preliminary MANOVA’s indicating that each variable was related to the set of dependent variables. Next, we conducted a 4 (applicant demographic) × 2 (order of applicant) MANCOVA on the dependent variables associated with our target applicant, controlling for participant gender and hiring experience. Because we found no main or interaction effects for order of applicant, we report the results of a one-way MANCOVA by applicant demographic on warmth, competence, liking, adaptability, motivation, suitability, and salary controlling for participant gender and hiring experience. Hypothesis 1 suggested that the 60-year-old would be perceived the most negatively and receive the poorest hiring-related outcomes. The MANCOVA revealed a significant multivariate effect for our manipulation, applicant demographic, Wilk’s λ = .59, F(24, 339.94) = 2.86, p < .001, partial ɳ² =.16, but not for the control variables. (The same pattern of results was found when we controlled for participant age and generation, respectively and together.)

Follow-up univariate tests indicated significant effects of applicant demographic on motivation, F(3, 124) = 2.83, p < .05, partial ɳ² = .06; and adaptability, F(3, 124) = 9.79, p < .001, partial ɳ² = .19. Condition means are shown in Table 5. A review of the means suggests that the 60-year-old had the lowest motivation and adaptability means and the Gen-Y/Millennial had the highest. Pairwise comparisons (least significant difference) indicated that the 60-year-old applicant (M = 5.76) was perceived as significantly less motivated than the Gen-Y/Millennial (M = 6.27) and Baby Boomer applicants (M = 6.24), but not the 29-year-old applicant (M = 6.10). No other mean comparisons were significant. Similarly, pairwise comparisons revealed that the 60-year-old applicant (M = 4.69) was perceived as significantly less adaptable than the Gen-Y/Millennial (M = 5.77), 29-year-old (M = 5.54), and Baby Boomer applicants (M = 5.42). No other mean comparisons were significant. (In Study 1, a significant difference was found between the Baby Boomer and 29-year-old using the Study 2 adaptability measure. This difference was not significant using the Study 1 measure of adaptability. No other differences were found across the two measures of adaptability.)

Indirect effects

To test Hypothesis 2, we explored whether the traits warmth, competence, dependability, adaptability, and motivation mediated the effects of applicant demographic on our suitability measure using the MEDIATE macro recommended by Hayes and Preacher (2014). There were no significant interactions between our predictor variable and mediators in any of our analyses, which allowed us to proceed with tests for mediation (Hayes & Preacher, 2014). A bias-corrected 95% bootstrap confidence interval for the indirect effect based on 10,000 bootstrap samples was above zero for two or more of our dummy variables for adaptability and motivation. These results suggest that the 60-year-old target was perceived as less motivated than the Gen-Y/Millennial and Baby Boomer targets and these perceptions in turn contributed to the 60-year-old’s relatively lower perceived suitability for the job. In addition, the 60-year-old target was perceived as less adaptable relative to the Gen-Y/Millennial, 29-year-old, and Baby Boomer targets and these perceptions contributed to the 60-year-olds relatively lower perceived suitability for the job. (The pattern of indirect effects was the same regardless of whether the Study 1 or Study 2 adaptability measure was used in Study 2. We could not explore the Study 2 measure of adaptability in Study 1 due to an operand error likely due to bootstrapping a small dataset.) There was no evidence that applicant demographic significantly influenced hiring judgments independent of its effect on motivation. However, applicant demographic significantly influenced suitability independent of its effect on adaptability. There was no evidence of an indirect effect through dependability, competence, or warmth. Results of the significant mediation analyses can be found in Tables 6 and 7.

Discussion

Consistent with Hypothesis 1, the 60-year-old applicant had the lowest mean motivation and adaptability, although it was not always significantly different from the other condition means. The 60-year-old was perceived as significantly less adaptable than both younger job candidates (Gen-Y/Millennial and 29-year-old) and the Baby Boomer candidate. Further, the 60-year-old was significantly less motivated than the Gen-Y/Millennial and the Baby Boomer. The Baby Boomer applicant was not perceived as significantly less motivated or less adaptable than the two younger job candidates. These results suggest that perceptions of Baby Boomers and older workers (60 year old) differ. We might conclude that Baby Boomers are likely to be perceived as more motivated and adaptable than older workers and no less motivated and adaptable than younger workers in this sample. Finally, consistent with Hypothesis 2, there was evidence of an indirect effect of applicant age/generation on hiring judgments through perceptions of adaptability and motivation.

GENERAL DISCUSSION

We conducted two studies to explore the impact of identifying a job candidate as either a 60-year-old, Baby Boomer, Gen-Y/Millennial, or 29-year-old on applicant perceptions and hiring-related outcomes. The first study employed a graduate school sample, whereas the second was conducted 3 years later and employed an MTurk sample that was older, more age diverse, and had more work experience. Across both studies, we found that a target described as an older applicant (60-years-old) was generally perceived to have the lowest levels of motivation and adaptability consistent with Hypothesis 1, whereas the same target was perceived to have the highest levels when described as a Gen-Y/Millennial. More generally, a review of the means suggests that the target was perceived more favorably when described on the basis of his generational membership compared to his age. In addition, consistent with Hypothesis 2, differential perceptions of a candidate’s adaptability, motivation, and competence mediated the impact of the candidate’s age/generation on hiring-related decisions. Finally, evidence for the existence of a Baby Boomer stereotype that is different from an older worker stereotype more clearly emerged in Study 2 than Study 1.

Our manipulation, applicant demographic, had a significant effect on perceptions of a candidate’s adaptability and motivation but not competence, warmth, or liking across both samples, or dependability in Study 2. Our results are consistent with research that finds that older workers are perceived to be less adaptable to change than younger workers (e.g., Chiu et al., 2001; Diekman & Hirnisey, 2007) but inconsistent with research by Krings and colleagues (2011) that found that older workers were perceived as warmer and less competent than younger workers. Further, results from the MANCOVA’s in both studies revealed no direct effect of our manipulation on hiring-related outcomes. This may in part be a function of the nature of the job that we employed (Director of Sales). The job description was intentionally written to not favor candidates of a particular age or generation so that we could more clearly explore the relative impact of age compared to generational stereotypes all else being equal. However, previous research has shown that age bias is more likely when jobs or contexts require traits that are inconsistent with the stereotypic qualities of older workers (e.g., Diekman & Hirnisey, 2007; Perry & Parlamis, 2005). For example, Diekman and Hirnisey (2007) found that older workers were less likely to be hired into companies that were described as dynamic and that age-based perceptions of adaptability mediated this effect. Had our job explicitly been described as one requiring high levels of motivation and adaptability, we might have found a different pattern of results on our job suitability measure.

With respect to the pattern of motivation means, across both studies the target had the lowest mean when he was described as a 60-year-old and the highest mean when he was described as a Gen-Y/Millennial. Further, the 60-year-old candidate was perceived as less motivated than the Gen-Y/Millennial although not the 29-year-old candidate across both samples. It is noteworthy that the Baby Boomer candidate was not perceived to be significantly less motivated than the 29-year-old or the Gen-Y/Millennial candidate in either Study. Finally, the older candidate was perceived as significantly less motivated than the Baby Boomer candidate in Study 2 but not in the graduate student sample in Study 1. This pattern of results suggests that Baby Boomers may be perceived to be significantly more motivated than older workers, and to have levels of motivation equivalent to those of younger workers (both Gen-Y/Millennials and 29-year-olds), unlike older workers.

Second, we explored the impact of our manipulation on perceptions of adaptability. The pattern of means shows that across the two studies, the target was perceived to have the lowest level of adaptability when he was described as a 60-year-old and the highest level when he was described as a Gen-Y/Millennial. Although the pattern of significant differences is remarkably similar with respect to the 60-year-old applicant across the two studies, this was less the case for the Baby Boomer candidate. The 60-year-old candidate was perceived to be significantly less adaptable than both the Gen-Y/Millennial and 29-year-old candidate across both studies regardless of the adaptability measure used. In Study 2, the Baby Boomer was perceived to be significantly more adaptable than the 60-year-old and not significantly different from the 29-year-old or the Gen-Y/Millennial (regardless of the measure of adaptability used). However, adaptability perceptions were more similar than different for the 60-year-old and Baby Boomer applicants in Study 1. This suggests that perceptions about Baby Boomers’ adaptability relative to older applicants may be more context- and sample-dependent.

Third, we explored the impact of our manipulation on starting salary judgments if hired. Results revealed significant effects in Study 1 but not Study 2. Specifically, in Study 1 we observed a significant difference between the older candidates (60-year-old and Baby Boomer) and the 29-year-old in salary if hired, such that the two older candidates would be offered higher salaries. This is not surprising as one would expect a 60-year-old and Baby Boomer to have more experience and thus be more deserving of a higher salary. Interestingly, no significant differences were found between the two older candidates and Gen-Y/Millennials, even though the latter generational cohort includes 29-year-olds. Thus, it appears that younger workers might have an advantage in obtaining a higher salary when they are viewed as Gen-Y/Millennials compared to their chronological age.

Additionally, there is evidence across both studies that motivation and adaptability (both measures) mediate the effect of age/generation on hiring judgments; a weak but significant indirect effect through competence was only found in Study 1. In other words, candidates are perceived to be differentially motivated, adaptable, and competent as a function of being identified as a 60-year-old compared to a Baby Boomer, Gen-Y Millennial, or 29-year-old and these differential perceptions impact hiring judgments. These results are consistent with some previous research exploring age stereotypes and discrimination (e.g., Chiu et al., 2001; Diekman & Hirnisey, 2007). For example, Diekman and Hirnisey (2007) found that older workers were perceived as less adaptable than younger workers and that this perception mediated the effect of age on hiring preferences. Our results are also somewhat consistent with Krings and colleagues’ (2011) finding that competence mediated the effects of candidate age on selection-related decisions.

Lastly, it is noteworthy that we found limited differences between a job candidate described as a Gen-Y/Millennial compared to a 29-year-old. The one difference we did find seems to suggest that Millennials may receive a slight salary advantage relative to 29 year olds. In general, respondents perceived the Gen-Y/Millennial and 29-year-old to be equivalent in terms of their motivation, adaptability, and suitability for the job. Differences might have been found if other types of traits (e.g., entitlement) that did not emerge from our factor analyses had been explored.

Our research makes three contributions to the literature. First, we assessed the relative impact of a job candidate’s age compared to his generational membership on hiring-related outcomes. Our results provide some evidence that there may be fewer negative consequences when a job candidate is identified as a Baby Boomer than an older worker (60-year-old). This was most evident in Study 2, which employed a more age diverse, mature sample that had greater work experience. Second, unlike much previous research, we directly assessed whether stereotypes function as a mediating mechanism explaining the relationship between applicants’ age/generation and hiring judgments (Finkelstein & Farrell, 2007; Krings et al., 2011). We found that stereotypes about a candidate’s adaptability, motivation, and competence (in Study 1) played mediating roles. Third, we explored mediators that have been only infrequently studied (perceived adaptability) or not at all studied (perceived motivation) in previous research (Diekman & Hirnisey, 2007). Diekman and Hirnisey (2007) noted that stereotypes about adaptability typically have not been considered in ageism research but that this dimension may be central to some age-related biases. We are not aware of any research that has explored the role that age-related perceptions of motivation play in employment-related outcomes. Our findings suggest this may be worth exploring.

Theoretical and Practical Implications

Our research suggests that whether employers think about employees in terms of their age or generational membership may have different work-related consequences. Future age-related research should be mindful of this possibility and take care to differentiate the two concepts. Further research exploring the differences between age and generational stereotypes and their implications should be conducted. Although our findings related to older workers were relatively stable across our two studies and measures, and consistent with previous research, our findings related to generational membership were somewhat less stable. This may suggest the need to explore potential moderators of generational effects, including the nature of the job and organizational context, the age and experience of the sample employed, the outcome measures collected, and the mediating mechanisms involved.

Future research describing jobs and organizational contexts in terms that are more and less consistent with generational stereotypes (e.g., requiring more and less motivation and adaptability) may be useful for differentiating the effects of age compared to generational stereotypes on employment outcomes. Future research should also explore additional outcomes (e.g., training and promotion decisions), mediators (e.g., entitlement, perceptions related to physical capabilities), and study participants who may have stronger generational stereotypes due to their exposure to generational issues in a work environment (e.g., HR managers). Study results also suggest that age and generation may have a direct effect on employment outcomes or be mediated by factors other than stereotypes.

Future research should also incorporate middle-aged and Gen-X employees into studies exploring age and generational effects. Finkelstein and colleagues (2012) suggested that research exploring stereotypes about middle-aged workers whose ages span the Generation X and Baby Boomer cohorts is important but scarce. Richardson and colleagues (2013) found that evaluation of both older and younger job applicants was less positive than for those between the ages of 42 and 48. Finally, researchers will need to understand whether the content of generational stereotypes changes as members of these cohorts age. Will Baby Boomers continue to be perceived as more motivated than older workers, even as the former push further into their 70s?

A significant percentage of participants had difficulty associating the correct age with generational labels. This suggests that for some, generational labels may not be as relevant or meaningful as the popular literature would suggest. At the same time, there was a significant percentage of participants for whom these labels were meaningful. To the extent that age and in some cases generational stereotypes are potentially problematic, steps should be taken to reduce employers’ reliance on them. Providing additional job relevant information about workers can reduce reliance on stereotypes (Truxillo et al., 2015). Further, employers’ consciousness should be raised regarding the inaccuracy of common age and generational stereotypes. To the extent that perceptions about employees’ adaptability and motivation mediate the effects of their age and generational membership on employment outcomes, these stereotypes should be challenged by providing employers with specific evidence to the contrary. Researchers also suggest that age and generational diversity may have the most positive and least negative outcomes when managers emphasize greater organizational focused goals and identities (North & Fiske, 2015).

Research suggests that older workers are vulnerable to stereotype threat in which they worry about confirming negative beliefs about their abilities resulting in their lowered performance (North & Fiske, 2015). Weiss and colleagues (Weiss, 2014; Weiss & Lang, 2012) found that older people have two types of age-related identities, one based on their chronological age and another based on their generational membership. Their research suggests that older adults shift their self-categorization from a negative social identity (age group) to a positive one (generation) and that this is adaptive and positively contributes to older people’s sense of well-being. Taken together, this research suggests that older workers could be encouraged to make their generational identities more salient than their age identities to avoid problems of stereotype threat and increase their sense of well-being. Further, for their part, employers should be careful not to present work-related tasks in stereotype-relevant ways that trigger negative age and/or generational stereotypes.

Limitations

A relatively high percentage of respondents in both studies failed to answer the manipulation check questions correctly. A closer review of manipulation check responses revealed that a higher percentage of Study 2 respondents were able to accurately identify the target’s age in the generation condition and the correct generation of the candidate in the age condition. For example, 56% of Study 2 respondents in the Baby Boomer condition correctly indicated the age of the target compared to 34% of Study 1 respondents. Similarly, 76% of Study 2 respondents in the Gen-Y/Millennial condition correctly indicated the age of the target compared to 54% of Study 1 respondents. Further, a greater percentage of respondents in Study 1 indicated they did not know the generation to which they belonged (24%) compared to Study 2 (16%). These differences may suggest that respondents in Study 2 had stronger and more differentiated generational stereotypes than our graduate student sample in Study 1. Consistent with this, when the target applicant was described as a Baby Boomer he was perceived to be significantly more motivated and adaptable than when he was described as a 60-year-old in our MTurk sample, but not in our graduate student sample. The MTurk sample was on average older, more age-diverse, and had more work experience. This may have contributed to a greater familiarity with generational issues in the workplace and consequently stronger generational stereotypes. Future research is needed to determine whether and which raters have stronger generational stereotypes and whether this may explain why some of our participants were better able to respond to our manipulation check questions than others. We should also point out that we made some small changes to the job description in Study 2 in order to make it more realistic. It is possible that these changes also contributed to the stronger effects found in Study 2. However, we can be reasonably certain that differences in results across the two studies were not due to differences in the perceived age of Baby Boomers across the studies (55 in Study 1, 56 in Study 2) or Gen-Y/Millennials (30 in Study 1, 29.5 in Study 2).

The two scenario-based studies asked study participants to make judgments about hypothetical applicants about whom they had limited information. Although this allowed for greater experimental control, these applicants were likely less realistic for our decision makers which may have affected study findings. Given the limited empirical research conducted on generational stereotypes and their implications to date, we thought that this trade-off was a reasonable one. Stereotypes and stereotypic processes like the ones we found in the current study are likely to influence judgments where there is uncertainty about job candidates’ competence as is often the case in actual hiring situations.

Finally, we identified our target applicant as 60 years old in our older applicant condition and as 29 years old in our younger applicant condition. This choice was based on how previous research has operationalized older and younger employees and applicants and the age ranges associated with our two generations of interest (Finkelstein et al., 2012; Truxillo et al., 2015). However, it is possible that we might have found different results had we chosen different age points. For example, evidence for older worker stereotypes may have been even stronger if we had chosen to focus on older, old workers (e.g., past the traditional retirement age of 65). Similarly, evidence of differences between the Baby Boomer and 60-year-old condition may have been less apparent if we had used a younger, old age (e.g., 52 vs. 60).

Conclusion

To this point, academic research has generally explored the extent to which there are actual generational differences in self-reported work values (e.g., autonomy, work conditions) and work attitudes (e.g., job satisfaction, organizational commitment). This often cross-temporal and cross-sectional research has made it difficult to isolate the effect of age, period, and cohort and has found limited and mixed evidence for generational differences (Costanza & Finkelstein, 2015). In contrast, the current research used experimental methodology to explore how others perceive a target’s traits and characteristics on the basis of his age compared to his generational membership. Our results across both studies and dependent variables suggest that describing individuals on the basis of their generational membership (e.g., Baby Boomer, Gen-Y/Millennial) in general has more positive implications than describing them on the basis of their age (e.g., 29 years old, 60 years old). Further, although not our direct focus, our research found limited evidence of perceived generational differences. Baby Boomers and Gen-Y/Millennials were generally perceived as more alike than different and received comparable employment outcomes.

Our results may be a function of the types of differences studied (traits compared to values and attitudes) and the methodology employed (experimental) compared to previous research. We suspect that the work experience and age of our respondents played a role in how developed generational stereotypes were and contributed to the relatively stronger results found in Study 2. In a parallel fashion, strength of generational identity, the extent to which people identify with their generation, may similarly influence the extent to which generational differences in actual values are found. Perhaps where individuals have a strong generational identity, generational cohorts may be meaningful, actual differences more apparent, and at the same time well-developed generational stereotypes more likely. To the extent that generational stereotypes have some basis in actual generational differences, our research raises questions about the existence of generational differences. At the same time, our research makes clear that the concept of generational stereotypes is meaningful and differentiated from the concept of age stereotypes.

ACKNOWLEDGMENTS

The authors would like to thank Duoc Nguyen and Ginevra Drinka for collecting the data and Brittany Chambers for assisting with data entry and the analyses for Study 1.

REFERENCES

Author notes