The Health Care Manager Volume 33, Number 1, pp. 4–19 Copyright # 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins
Employee Age and Tenure Within Organizations Relationship to Workplace Satisfaction and Workplace Climate Perceptions Robert Teclaw, PhD; Katerine Osatuke, PhD; Jonathan Fishman, PhD; Scott C. Moore, PhD; Sue Dyrenforth, PhD This study estimated the relative influence of age/generation and tenure on job satisfaction and workplace climate perceptions. Data from the 2004, 2008, and 2012 Veterans Health Administration All Employee Survey (sample sizes >100 000) were examined in general linear models, with demographic characteristics simultaneously included as independent variables. Ten dependent variables represented a broad range of employee attitudes. Age/generation and tenure effects were compared through partial 2 (95% confidence interval), P value of F statistic, and overall model R2. Demographic variables taken together were only weakly related to employee attitudes, accounting for less than 10% of the variance. Consistently across survey years, for all dependent variables, age and age-squared had very weak to no effects, whereas tenure and tenure-squared had meaningfully greater partial 2 values. Except for 1 independent variable in 1 year, none of the partial 2 confidence intervals for age and age-squared overlapped those of tenure and tenuresquared. Much has been made in the popular and professional press of the importance of generational differences in workplace attitudes. Empirical studies have been contradictory and therefore inconclusive. The findings reported here suggest that age/generational differences might not influence employee perceptions to the extent that human resource and management practitioners have been led to believe. Key words: age, employee attitudes, employee surveys, generation, tenure
N CROSS-SECTIONAL STUDIES, age and generation effects are inseparable. Knowing a person’s age points to his/her generation, and
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Author Affiliations: National Center for Organization Development, Veterans Health Administration (Drs Teclaw, Osatuke, Fishman, Moore, and Dyrenforth), Cincinnati, and Department of Psychology, Miami University (Dr Fishman), Oxford, Ohio. This material is based on work supported by the Department of Veterans Affairs. Any opinions, findings, conclusions, or recommendations expressed in this article are those of the research investigators and do not necessarily represent the view of the Department of Veterans Affairs or the US government. The authors report no conflicts of interest. Correspondence: Robert Teclaw, PhD, National Center for Organization Development, Veterans Health Administration, 11500 Northlake Dr, Suite 230, Cincinnati, OH 45249 ([email protected]). DOI: 10.1097/01.HCM.0000440616.31891.2d
vice versa. This article examines the relative effects of tenure and age (and indirectly generation) on several important response variables. Although age is used as a predictor, the conclusions also apply to generational effects, as with no, or only small age effects, there can be no large generational effects. Generational differences at work have received much attention in the literature.1-4 This topic has theoretical implications that reflect the potential of generational studies to demonstrate or invalidate broad cultural influences in shaping personal attitudes and behaviors.5 Terracciano6 reviewed conundrums faced by generational differences research in the context of studying adult personality cross-sectional, longitudinally, and cross-nationally. Empirical studies of generational differences have been inconclusive; widely different conclusions likely reflect heterogeneity in researchers’ fields, methods, and reasons for examining crossgenerational issues.7
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Workplace Satisfaction and Climate Perceptions Effects of age on employee perceptions have been examined in their own right without considering generations.8-10 In a meta-analysis of 802 articles, Ng and Feldman11(p677) concluded that the relationship between age and job attitudes is ‘‘generally significant and weak to moderate in strength.’’ The topic of generational differences also has important pragmatic implications, most prominently for human resource (HR) management and planning. Compared with the scientists’ perspective, separating age and generation effects (eg, in cross-sectional studies) is less important for HR specialists, because their tasks are mainly within the present, and the relevant differences are therefore those observed today, with or without generalization to other historical periods. The generational differences of current concern to HR are the demographic trends: suggesting a growing workforce presence of the elderly and younger workers. The pressing nature of these pragmatic concerns makes it challenging to wait for conclusive scientific results (cf. Eckersley7(p79)): ‘‘We cannot wait for scientific proof, which may always remain beyond our reach, before taking political action in health, education, and the media.’’ Descriptions and interpretations of workers’ generational differences, based typically on anecdotal accounts or opinions, therefore abound in the popular press targeting managers and HR professionals. Although the available empirical evidence shows more variation in individual behaviors and attitudes within than between generations (eg, Macky et al12), many popular articles assume otherwise; they formulate psychological profiles of specific generations and detailed recommendations of how to harmonize them at work. Empirical research on generational aspects pertaining to workplace includes 2 relevant, somewhat competing foci: differences across birth cohorts, usually assessed through age (eg, see Kupperschmidt2), and differences reflecting tenure, or career stage.13 Evidence was examined and compared for these approaches in an employee census survey of workplace perceptions and satisfaction at the Department of Veterans Affairs.
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EFFECTS OF GENERATIONAL DIFFERENCES VERSUS ORGANIZATIONAL TENURE AT THE WORKPLACE Studying demographic differences in the workplace generally involves 2 strategies.3 One, based on age, suggests that workers’ birth generation affects workplace climate and job satisfaction because generational differences inherently shape perceptions, thus leading to potential conflicts.2 Given the challenges of longitudinal data collection,6 this strategy typically involves cross-sectional studies, with collapsing age and cohort effects. Another, stage-based, strategy of studying generational differences suggests that perceptions change with time, such that the amount of experience on the job shapes employee perceptions of their work environment.13 A generation is a group of individuals sharing birth years, birth location, and significant life events.2 These similar life experiences are thought to distinguish generations from each other.14 The 2 most prevalent generations in today’s workforce are the baby boomers and generation X.3 The next generation entering the workforce is known as the millennials, generation Yers, or the next generation.15 Differences between baby boomers and Xers have been presented as important; for example, understanding them has been described as promoting productivity, innovativeness, and corporate citizenship,2 and ignoring them has been claimed to create workplace conflicts based on misunderstandings.1 Many of these conclusions do not appear empirically driven; for example, see Karp et al,16 Kupperschmidt,2 and O’Bannon.17 A modest amount of empirical research supports generational differences at work. Westerman and Yamamura18 found higher overall job satisfaction in baby boomers than in younger generations and that these latter had greater need of goal- and system-driven work environments. Smola and Sutton3 compared baby boomers’ and Xers’ work values. In their sample from 53 US companies (predominantly manufacturing but including 17 service organizations), they found a generational effect, with generation X less loyal to the company and more focused on personal goals. Work values
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of baby boomers also changed as a function of time spent within the organization, thus lending support to both generational and tenure effects. Jurkiewicz13 examined generational differences in work motivation in 241 employees from various work departments in 5 MidWestern municipalities. Only 3 of the 15 categories differed across generation: 2 in the direction opposite from the expectations based on the popular literature descriptions of Xers’ job expectations. Jurkiewicz concluded that the claim of generational differences reflects commonly held assumptions more than any real differences among the actual workers and argued that employees’ experience on the job is more central to workplace differences than generational distinctions. Similarly, Trimble’s19 investigation of missionaries found that organizational tenure was a stronger predictor of work commitment, job satisfaction, and turnover intention than was age, defined as Xers versus older generations. Within salesmanship research, investigators’ attempts to connect age with job performance also have been unsuccessful.20 Hafer20 reported initial support for a stage-based approach as more useful than generational, but noted this evidence was not robust and called for more research. Two recent meta-analyses have increased our understanding of the relationships among age/generation, tenure, and various dependent variables. Costanza et al4 found moderate to nonexistent relationships between generational membership and workplace outcomes. Ng and Feldman11 found moderate to weak relationships between age and dependent variables. However, meta-analyses have potential problems, most notably publication bias effects and a dependence on the quality of the primary-level studies.21 In addition, the clinical trials literature demonstrated that meta-analyses and large randomized clinical trials do not necessarily agree.22 Several theoretical explanations have been offered for age/generational differences in employee attitudes. One such explanation is socioemotional selectivity theory.10 According to this theory, as people age, they transition from seeking novel information to achieving positive emotional states,23 and this transition could account for older workers’ more favorable
job attitudes. Kacmar and Ferris8 used career stage and development theory, according to which young workers attempt to fit in, middle age workers are productive, and older workers begin to disengage, to underpin their study of the age-job satisfaction relationship. Ng and Feldman11 applied socioemotional selectivity theory to understand the age-job attitudes relationship but also recommended other theoretical approaches; for example, continuous increases in agreeableness and conscientiousness over one’s life course would suggest higher satisfaction and better job attitudes for older workers.24 These authors also suggested alternative theories for an age-job attitudes relationship, such as the life-span life-stage model of Super et al,25 in which older workers are more concerned about nonwork roles and are thus less likely to be dissatisfied. In practice, it is quite difficult to suggest a theory of why age/generation might not be associated with work attitudes and even harder to test such theories. One can, however, test whether the age-attitude relationship even exists to the extent of significantly predicting employee attitudes, and that is the purpose of this study. If there is no meaningful age-job attitude relationship, then the question of developing a theoretical underpinning for that relationship becomes moot. Addressed in the Discussion is the seeming contradiction between this study’s results and conventional wisdom about generational differences. FOCUS OF THIS STUDY The motivation to study the relative importance of age and tenure on employee attitudes had as its source the qualitative analysis of interview transcripts of Veterans Health Administration (VHA) workgroups conducted at the VHA National Center for Organization Development. Employees were interviewed as part of climate assessments at their workplaces (eg, medical centers, hospitals, clinics) in the context of planning organizational interventions. In confidential interviews that organizational consultants conducted with randomly selected employees representing at least 10% of participating workplaces, participants were asked to discuss in an open-ended format any strengths,
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Workplace Satisfaction and Climate Perceptions weaknesses, and desired changes in their workplace. The data were used for intervention planning (within sites) and for summarizing overall themes of employee comments (across sites). Based on these data (1118 employee interviews representing 28 workgroups at 19 facilities), respondents occasionally mentioned organizational tenure (or similar terms) and made comments on differences in coworkers’ perceptions and attitudes related to these factors. Age/ generation and any related differences were, however, rarely if ever brought up. The difference in the relative frequency of age and tenure mentioned in the employee comments about their workplace might have gone unnoticed except for the appearance in professional (nonempirical) publications at that time of a large number of articles emphasizing the importance of generational differences in the workplace and urging managers and HR professionals to take these differences into account. We decided to approach the question quantitatively using an employee survey with well over 100 000 respondents, enough to detect small effects of multiple demographic variables simultaneously. This study explored the relative importance of differences in workplace perceptions and job satisfaction among VHA employees in different age groups, considering their organizational tenure level. Data from the VHA All Employee Survey (AES) were used to compare employee perceptions of their workplace across age (and indirectly, generational) categories and tenure categories, with additional analyses of gender, supervisory status, occupation, ethnic, and racial differences. Previous experience with these data sets suggested that employee attitudes would show statistically significant relationships to individual demographic variables given the large samples, regardless of the effect size. Also from previous analyses, we knew that all of the demographic variables considered here were not independently distributed in the AES data sets. Therefore, it was decided to evaluate the effects of multiple demographic variables simultaneously. To not do so would have repeated some of the limitations of most of the previous studies on age/generation and tenure effects on employee attitudes and perceptions: namely, that any relationships reported could
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have been due to the confounding effects of other demographic variables. The large number of respondents enabled inclusion of all demographic items in the survey as predictor variables in the models without significant loss of power. This allowed a direct comparison of effect sizes for all demographic variables and, in this context, evaluating the influences of age/ generation and tenure, the major focus of this study. The dependent variables (see Methods) are consistent with those used in prior studies, which examined the effects of age, birth cohort, generation, and/or organizational tenure. Ng and Feldman11 classified the dependent variables from 802 empirical studies (published and unpublished) on the age/generation and tenure relationship with employee attitudes into 35 categories and 3 overarching groupings: taskbased, people-based, and organization-based attitudes. Our selection of dependent variables sought to maximize the chances of finding significant effects of age and/or tenure, if they existed. Our intention was to preemptively address potential limitations in generalizability of our findings regarding a relationship with age/ generation and employee attitudes because we did not consider enough and or the ‘‘right’’ outcome variables. We therefore represented the types of outcomes examined in previous research (ie, studies classified by Ng and Feldman11), including studies that found significant effects of demographic variables, which our study attempted to replicate using a larger data set. We specifically included measures representing task-based, people-based, and organization-based attitude groupings, in order to evaluate several types of dependent variables for potential effects of age and tenure and to explore differences in effect patterns corresponding to these types of variables. Our hypotheses were based on the results of qualitative analysis of Veterans Affairs (VA) employee interviews and also on prior empirical reports that described tenure as a ‘‘more consistent and stable predictor of job satisfaction than chronological age’’26(p33) and a 22-study metaanalysis, which found that ‘‘controlling for tenure, employee age has a small and unimportant moderating effect on the commitmentperformance correlation.’’27(p1187)
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THE HEALTH CARE MANAGER/JANUARY–MARCH 2014 1. Hypothesis 1: Age/generation has little relationship to employee attitudes, when other demographic characteristics are controlled. 2. Hypothesis 2: Tenure or time with the organization is related to employee attitudes, when other demographic characteristics are controlled. 3. Exploratory hypothesis 3: Demographic characteristics show differences in pattern of effects depending on the particular outcome variable.
METHODS The data consisted of VHA hospital employees’ ratings of workgroup climate and job satisfaction provided in the 2004, 2008, and 2012 VHA All Employee Survey (AES, copy available upon request). The AES is a voluntary, confidential annual survey of all VA employees (see Table 1 for number of respondents and response rates). AES respondents rate their job satisfaction and agreement with specific descriptions of workplace climate using Likerttype scales with response options from 1 to 5 (‘‘not at all satisfied’’ to ‘‘very satisfied’’ for satisfaction ratings; ‘‘strongly disagree’’ to ‘‘strongly agree’’ for workplace climate ratings). Summary scores based on item ratings are broadly shared within VHA and support and workforce development planning nationally, regionally, and locally (eg, AES scores inform HR strategies within specific hospitals and clinics). All Employee Survey respondents included multipleracial, ethnic, geographic, and occupational groups, representing the diverse workforce. The VHA employs more than 280 000 workers
over all 50 states, in rural and metropolitan areas, in various work settings, for example, patient care, administrative, research, fiscal, and others. Examined were the AES items that met these criteria: (a) were used in previous studies of age and tenure effects on employee attitudes,11 (b) were hypothesized as potentially sensitive to the demographic differences within the focus of our study, (c) served as an annual basis for workforce-targeted action planning within VHA, and (d ) were identified as reliable, valid dimensions of VHA employees’ workplace perceptions in previous research with the AES.28-31 The specific categories and items of interest (numbers in brackets indicate the number of studies using that dependent variable in Ng and Feldman’s11 meta-analysis) included task-based attitudes (overall job satisfaction [388], satisfaction with pay [52], satisfaction with work itself [41], and satisfaction with promotion [36]), people-based attitudes (satisfaction with coworkers [36], satisfaction with supervisors [41], relationship conflict [14], and coworker support [38]), and organizationbased attitudes (organizational identification [26] and perceived organizational support [75]). Table 2 lists the AES items used in the analyses. Also examined were scores across VHA employee age categories. The survey question used to distinguish among these was ‘‘What is your age?’’ with response options including less than 20 years, 20 to 29, 30 to 39, 40 to 49, 50 to 59, and 60 years or older. The youngest age category was not used in the analyses because that age included much lower numbers of employees and large variance in responses.
Table 1. Response Rates and Number of Respondents Used in Analyses, Veterans Health Administration (VHA) All Employee Survey
Year
Overall Survey Response Rate
N (VHA Hospital Employees)
n (After Removal of Responses From Employees 20 years and age between 20 and 30 years).
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Table 2. All Employee Survey Items Used in This Study Task-based attitudes 1. Overall satisfaction: Compared with what you think it should be, what is your current overall level of satisfaction with your job? 2. Satisfaction with pay: Compared with what you think it should be, how satisfied are you with the amount of pay that you receive? 3. Satisfaction with work itself: Compared with what you think it should be, how satisfied are you with the type of work that you currently do? 4. Satisfaction with promotion: Compared with what you think it should be, how satisfied are you with the number of opportunities for promotion? People-based attitudes 1. Satisfaction with coworkers: Compared with what you think it should be, how satisfied are you with the relationships you have with your coworkers? 2. Satisfaction with supervisors: Compared with what you think it should be, how satisfied are you with the quality of direct supervision you receive? 3. Relationship conflict: Disputes or conflicts are resolved fairly in my work group. 4. Coworker support: The people I work with can be relied on when I need help. Organization-based attitudes 1. Organizational identification: I feel a strong personal connection with the mission of Department Veterans Affairs. 2. Perceived organizational support: Department Veterans Affairs cares about my general satisfaction at work. Survey items listed in Table 1 were rated on a Likert-type scale. Response options ranged from 1 to 5, corresponding to 1: not at all satisfied, 3: neither satisfied nor dissatisfied, 5: very satisfied’’ (for satisfaction ratings) and to 1: strongly disagree, 3: neither agree nor disagree, 5: strongly agree (for workplace perception ratings, which include all other items in the table). ‘‘Don’t know’’ was an available option for workplace perception ratings (but not for satisfaction ratings). It was treated as missing data for the purposes of this study.
Tenure was measured by asking ‘‘How long have you been with the VA?’’ with response options including less than 6 months, 6 months to 1 year, 1 to 2 years, 2 to 5 years, 5 to 10 years, 10 to 15 years, 15 to 20 years, and more than 20 years. The other predictors included race (6 levels), occupation (51 levels), gender, and ethnicity, all as class variables, and supervisory status (5 levels) as a numeric variable. Interaction terms were entered in initial models; they were either not significant or contributed little to overall R2 and were therefore excluded from the final models. Because the 10 dependent variables are considered one at a time, relationships among dependent variables due to common method bias32 should not be an issue in the analysis. General linear model regression (PROC GLM; SAS Institute, Cary, North Carolina) was used to assess the effects of age and tenure on the dependent variables. The amount of variance explained by the overall model was reported as R2. The statistical significance of the F test for each independent variable (IV) was determined by its P value in the type III sum-ofsquares table. Effect sizes for each of the IVs were determined by partial 2 with 95% confidence limits. Separate models were run for each
of the 10 dependent variables and 3 survey years. Given a U-shaped relationship of workplace attitude ratings to both tenure and age in previous research,8,9 the square of these variables was included in the model. Other demographic characteristics were expected to be associated with the dependent variables, so they were included to control for their effects, thus simultaneously evaluating the relative effect sizes of all demographic variables.
RESULTS For each of the 10 dependent variables, results across years were very consistent for overall model R2, dependent variable F test P value, and partial 2 (Figures 1-10). Overall model R2 values ranged from 0.03 for many dependent variables to 0.10 for satisfaction with promotion (Figure 4) for the 2004 AES. When considered as the only predictors, demographic characteristics explained only a small amount of variance in the 10 dependent variables. P values were always .05). Year = 2012: overall model R2 = 0.034; P < .0001 for all IVs except ethnicity (P > .05). Note: Error bars = 95% confidence interval (CI) for partial 2. Missing error bars are undefined.
Figure 2. Effect size for demographic variables regressed on ‘‘satisfaction with pay,’’ Veterans Health Administration, All Employee Survey 2004-2012. Year = 2004: overall model R2 = 0.081; P < .0001 for all independent variables (IVs). Year = 2008: overall model R2 = 0.078; P < .0001 for all IVs. Year = 2012: overall model R2 = 0.069; P < .0001 for all IVs. Note: Error bars = 95% confidence interval for partial 2. Missing error bars are undefined.
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Figure 3. Effect size for demographic variables regressed on ‘‘satisfaction with work itself,’’ Veterans Health Administration, All Employee Survey 2004-2012. Year = 2004: overall model R2 = 0.032; P < .0001 for all independent variables (IVs) except ethnicity and age (P > .05). Year = 2008: overall model R2 = 0.034; P < .0001 for all IVs except ethnicity and age (P < .01). Year = 2012: overall model R2 = 0.033; P < .0001 for all IVs except age (P < .05). Note: Error bars = 95% confidence interval for partial 2. Missing error bars are undefined.
Figure 4. Effect size for demographic variables regressed on ‘‘satisfaction with promotion,’’ Veterans Health Administration, All Employee Survey 2004-2012. Year = 2004: overall model R2 = 0.098; P < .0001 for all independent variables (IVs) except ethnicity (P > .05). Year = 2008: overall model R2 = 0.099; P < .0001 for all IVs. Year = 2012: overall model R2 = 0.095; P < .0001 for all IVs except ethnicity (P < .01). Note: Error bars = 95% confidence interval for partial 2. Missing error bars are undefined.
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Figure 5. Effect size for demographic variables regressed on ‘‘satisfaction with coworkers,’’ Veterans Health Administration, All Employee Survey 2004-2012. Year = 2004: overall model R2 = 0.029; P < .0001 for all independent variables (IVs) except ethnicity (P > .05). Year = 2008: overall model R2 = 0.032; P < .0001 for all IVs except ethnicity (P < .05). Year = 2012: overall model R2 = 0.031; P < .0001 for all IVs except ethnicity (P > .05). Note: Error bars = 95% confidence interval for partial 2. Missing error bars are undefined.
Figure 6. Effect size for demographic variables regressed on ‘‘satisfaction with supervisors,’’ Veterans Health Administration, All Employee Survey 2004-2012. Year = 2004: overall model R2 = 0.033; P < .0001 for all independent variables (IVs) except ethnicity (P > .05). Year = 2008: overall model R2 = 0.032; P < .0001 for all IVs. Year = 2012: overall model R2 = 0.029; P < .0001 for all IVs. Note: Error bars = 95% confidence interval for partial 2. Missing error bars are undefined.
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Figure 7. Effect size for demographic variables regressed on ‘‘relationship conflict,’’ Veterans Health Administration, All Employee Survey 2004-2012. Year = 2004: overall model R2 = 0.069; P < .0001 for all independent variables (IVs) except ethnicity (P > .05). Year = 2008: overall model R2 = 0.065; P < .0001 for all IVs except ethnicity (P < .01). Year = 2012: overall model R2 = 0.059; P < .0001 for all IVs except ethnicity (P < .01). Note: Error bars = 95% confidence interval for partial 2. Missing error bars are undefined.
Figure 8. Effect size for demographic variables regressed on ‘‘coworker support,’’ Veterans Health Administration, All Employee Survey 2004-2012. Year = 2004: overall model R2 = 0.047; P < .0001 for all independent variables (IVs) except gender (P > .05). Year = 2008: overall model R2 = 0.045; P < .0001 for all IVs except gender (P < .05). Year = 2012: overall model R2 = 0.044; P < .0001 for all IVs except gender (P > .05). Note: Error bars = 95% confidence interval for partial 2. Missing error bars are undefined.
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Figure 9. Effect size for demographic variables regressed on ‘‘organizational identification,’’ Veterans Health Administration, All Employee Survey 2004-2012. Year = 2004: item not used in this year’s survey. Year = 2008: overall model R2 = 0.053; P < .0001 for all independent variables (IVs) except gender and age-squared (P > .05). Year = 2012: overall model R2 = 0.052; P < .0001 for all IVs except gender (P > .05) and age-squared (P < .01). Note: Error bars = 95% confidence interval for partial 2. Missing error bars are undefined.
Figure 10. Effect size for demographic variables regressed on ‘‘perceived organizational support,’’ Veterans Health Administration, All Employee Survey 2004-2012. Year = 2004: item not used in this year’s survey. Year = 2008: overall model R2 = 0.057; P < .0001 for all independent variables (IVs) except gender (P > .05). Year = 2012: overall model R2 = 0.055; P < .0001 for all IVs except gender (P > .05). Note: Error bars = 95% confidence interval for partial 2. Missing error bars are undefined.
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Workplace Satisfaction and Climate Perceptions F tests (P > .05), whereas age and age-squared had 1 and 2 nonsignificant instances, respectively. For all years and all dependent variables, effect sizes for tenure and tenure-squared were much larger than effect sizes for age and agesquared. With 1 exception (satisfaction with pay in 2004; Figure 2), none of the 95% confidence limits overlapped, suggesting that the observed effect size advantage of tenure over age was not due to chance. For most of the dependent variables, age and age-squared had only a negligible explanatory effect. The highest partial 2s for age and age-squared were 0.0020 and 0.0024, respectively, for satisfaction with promotion, 2004 (Figure 4). Regarding the hypotheses for this study 1. Hypothesis 1: Age/generation will have little relationship to employee attitudes, when other demographic characteristics are controlled. The results support this hypothesis. Age and age-squared had a statistically significant relationship with most of the dependent variables in most years; nevertheless, the magnitude (partial 2) of effect was not meaningful, never approaching 1%. 2. Hypothesis 2: Tenure or time with the organization is related to employee attitudes, when other demographic characteristics are controlled. This hypothesis was supported; tenure and tenure-squared were always statistically significantly associated with the dependent variables (P .0001). Effect sizes were intermediate between the most strongly associated demographic variable, occupation, and the very weekly associated variables, age, agesquared, gender, and ethnicity. 3. Exploratory hypothesis 3: Demographic characteristics will show important differences in pattern of effects depending on the particular outcome variable studied. This hypothesis was partially supported. Although the relative importance of the various demographic predictors was similar for all dependent variables, the magnitudes of the effect differed depending
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on the dependent variable. Whether these differences were big enough to reach the threshold of ‘‘important’’ has not been definitively settled except possibly for ‘‘satisfaction with pay’’ (Figure 2) and ‘‘satisfaction with promotion’’ (Figure 4). DISCUSSION In the current study, the researchers were fortunate to have access to multiyear data sets similar to or even greatly exceeding the size of typical meta-analytic studies, which allowed evaluation of the generational differences thoroughly and systematically. This may well be the first study to examine generational differences in an extremely large data set, representing a diverse sample of respondents over multiple years. We assessed effects of generational differences on multiple dependent variables in multiple years of data were assessed, with an adequate power to evaluate the significance and effect sizes of the differences controlling for alternative explanations, for example, other demographics. The study examined the relative impact of generational differences (using age category as a proxy) and tenure at a given organization on aspects of job satisfaction and workplace climate ratings. It was found that VA tenure had a larger effect on these outcomes than employee age did and that effects were small for both. Previous studies (eg, Kupperschmidt2 and Jurkiewicz13) presented some evidence for both birth cohort and workplace tenure as predictors of employees’ perceptions. While our study also demonstrated a greater relevance of tenure compared with age, putting both of these in the context of considerably larger effects of other demographics suggested that generational differences at work are overall not important. The strategy of using age category as a proxy for generation has limitations (as it collapses year of birth effects with age effects, ascertaining the influence of one factor does not necessarily prove the influence of the other). However, because no age effects or only small age effects were consistently found, this evidence does suggest no large generational effects are present.
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The methods used in this study lend much confidence to this conclusion. First, the data reflect a very large and extremely diverse sample of multiple racial, ethnic, geographic, and occupational groups (eg, nurses, doctors, psychologists, chaplains, education specialists, food service and housekeeping employees, executives, clerks, police officers, and many others), representing employee diversity within VA, the second largest federal employer in the United States. Second, effect sizes of tenure and age considering other, possibly confounding, demographics were compared. Third, all quantitative comparisons were replicated in 3 years of data across a 9-year period, which verified the stability of the findings. With the exception of race, the demographic variables most related to the dependent variables represented acquired (occupation, tenure, tenure-squared, and supervisory status) rather than innate (gender, ethnicity, age, and age-squared) categories. This could reflect the relatively larger influences of organizationally based differences (the first group of demographics) compared with personally based differences (the second group). The meaning of these differences was outside the scope of this study; their more precise interpretations require further research. How should the results be interpreted in light of Ng and Feldman’s11 802 meta-analysis, which found moderate effects of age on multiple employee attitudes? The present approach offers several advantages. The largest sample size was 158 971 respondents in 2012. The largest populations of the meta-analysis were 151 105 respondents spread over 388 different studies for ‘‘overall job satisfaction’’ and 108 315 respondents from 296 studies for ‘‘affective commitment.’’ Twelve of the remaining 33 outcome variables were represented by populations under 10 000. One of the usual justifications for meta-analyses is that sample sizes from individual studies are often too small to address the research question. This study uses a population size exceeding (and for many outcomes, greatly exceeding) the population from the meta-analysis. In addition, the population, although diverse in organizational roles, occupations, geographic locations within the
United States, and other demographics, comes from a single large organization. This is an advantage for answering the research question, but a disadvantage for generalizing the findings. It is unlikely, however, that age is not an important predictor of employee attitudes in a large health care organization, but it is everywhere else. In any case, we do not claim that these results apply to other contexts, only that they bring into question the commonly held belief that age/generation is an important predictor of employee attitudes. An additional difference between our study and Ng and Feldman’s11 meta-analysis is the way of approaching potentially moderating variables. The meta-analysis by necessity considered moderators one at a time, which reduced the population as not all studies examined all potential modifiers. We controlled for several potential modifiers simultaneously using the full population. It was also possible to control for multicolinearity among predictors; the results for each predictor were conditioned on the simultaneous presence of all of the others. Finally, both the meta-analysis and the present study used data sets from different years. The meta-analysis found smaller effects of age in more recent studies (after 1999 to after 2003, depending on outcomes). We found quite stable results across 2004. The effect of age on employee attitudes could have been higher in the past, explaining the different results. Limitations of this study included the following. First, differences between age effects and cohort effects (eg, comparisons of individuals of similar age but living in different historical time periods) were not examined. However, the concept of generational differences, which was of central interest to this study (reflecting its importance to the practicing HR professionals), by definition collapses the 2 notions (age and cohort); therefore, this limitation did not impede the ability to examine the concept. Second, the quantitative data set, the VHA AES, was not specifically designed to measure our variables of study (birth generations and organizational tenure effects). However, the dependent variables were selected consistently with the type of variables typically used in empirical investigations of age, cohort,
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Workplace Satisfaction and Climate Perceptions generation, and tenure—including studies that reported significant effects of age and tenure on these variables (eg, see Luchman et al10). This suggests relevance of the selected dependent variables to the topic of study and thereby for generalizability of the findings. Third, the results pertain to age effects on employee attitudes. Possibly, some relevant age/generational differences among coworkers (eg, informality or preference for social networking) were not reflected in the items we chose or in the AES items in general. However, to the extent that employee surveys inform HR practices, this study’s findings are important. The AES has an established reputation of conveying employee input within VA: developing action plans from AES results is part of VA managers’ performance measures. So, while possibly not capturing every generationally relevant aspect of the workplace, this survey reflects what the largest federal health care organization considers directly actionable and has been ‘‘using’’ for actions since 2004. Fourth, age or tenure scaled as years was not available for this study. The coarseness of these measures could have minimized their relationships to the outcomes. The purpose, however, was to compare their relative effects, and because age and tenure were similarly scaled, scale coarseness likely did not greatly influence the related conclusions. Finally, the findings are based on an all-employee survey within a large, government health care system. The nature of the work and of the employer could minimize age effects that might be augmented in another context. If so, at a minimum, HR professionals should use caution in applying a ‘‘one size fits all’’ approach to multigenerational issues. Prior studies have made a convincing business case for attending to employees’ experience of workplace climate (eg, see Carr et al,33 Garman et al,34 Harter et al,35 Laschinger et al36). This motivates an interest in describing specific influences on workplace perceptions and incorporating these into workforce policies. Based on present results, key influences on workplace perceptions likely do not include the workers’ generation or organizational tenure. The very modest effect sizes of these variables when examined
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with other demographics suggest no pragmatically meaningful effects. The statistically significant effect of age (and, by proxy, generational differences) should be considered in perspective of, first, larger effects of being a new versus tenured employee within the organization (irrespectively of one’s birth cohort) and, second, in the context of other demographic characteristics demonstrating by far larger effects than either age and tenure (eg, occupation). Anyone who has interacted with someone much older or younger cannot help but notice differences in affect and attitudes. Quite possibly, one would not find instant rapport with oneself from an earlier or later time in life. One explanation for this study’s findings (no meaningful difference) is that age/generational differences in demeanor and preferences, although possibly real, may be irrelevant when forming and expressing attitudes about work. For example, younger workers might prefer a more informal, social media–driven workplace, but this does not impact their satisfaction with pay or coworker support. The few longitudinal studies available3,37,38 did note generational differences among workers, which seems to refute our conjecture. An interpretation that reconciles this inconsistency, however, is that, according to our results, age/generation differences in work attitudes may stem from the confounding effects of uncontrolled demographics. Studies that did not control for these confounds, especially tenure, could therefore be reporting spurious associations. If age/generational difference in work attitudes is very small, why are they given so much credence among HR professionals? Like us, other researchers of cohort and generational effects have raised the possibility that beliefs into generational differences may reflect judgments based on extremely memorable exemplars, that is, availability bias.5 These beliefs, once formed, may be maintained by confirmatory biases whereby people selectively attend to statements and observations that confirm their already existing opinions. Thus, the intensity of perceived differences between the generations of workers may, at least partly, reflect social cognition biases rather than true differences between members of generational groups.5
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REFERENCES 1. Fyock CD. America’s Work Force Is Coming of Age. Toronto, ON, Canada: Lexington Books; 1990. 2. Kupperschmidt BR. Multigeneration employees: strategies for effective management. Health Care Manag. 2000;19(1):65-76. 3. Smola KW, Sutton CD. Generational differences: revisiting generational work values for the new millennium. J Org Behav. 2002;23:363-382. 4. Costanza DP, Badger JM, Fraser RL, Severt JB, Gade PA. Generational differences in work-related attitudes: a meta-analysis. J Bus Psychol. 2012;27(4):375-394. 5. Trzesniewski KH, Donnellan MB. Rethinking ‘‘generation me’’: a study of cohort effects from 1976-2006. Perspect Psychol Sci. 2010;5(1):58-75. 6. Terracciano A. Secular trends and personality: perspectives from longitudinal and cross-cultural studies— commentary of Trzesniewski & Donnellan (2010). Perspect Psychol Sci. 2010;5(1):93-96. 7. Eckersley R. Commentary on Trzesniewski and Donnellan (2010): a transdisciplinary perspective on young people’s well-being. Perspect Psychol. Sci. 2010; 55(1):76-80. 8. Kacmar MK, Ferris GR. Theoretical and methodological considerations in the age-job satisfaction relationship. J Appl Psychol. 1989;74(2):201-207. 9. Clark A, Oswald A, Warr P. Is job satisfaction U-shaped in age? J Occup Organ Psychol. 1996;69(1):57-81. 10. Luchman JN, Kaplan SA, Dalal RS. Getting older and getting happier with work: an information-processing explanation. Soc Indic Res. 2012;108(3):535-552. 11. Ng TWH, Feldman DC. The relationship of age with job attitudes: a meta-analysis. Pers Psychol. 2010;63(3): 677-718. 12. Macky K, Gardner D, Forsyth S. Generational differences at work: introduction and overview. J Manag Psychol. 2008;23(8):857-861. 13. Jurkiewicz CE. Generation X and the public employee. Public Pers Manage. 2000;29(1):55-74. 14. Jurkiewicz CE, Brown RG. GenXers vs. boomers vs. matures: generational comparisons of public employee motivation. Rev Public Pers Admin. 1998;18:18-37. 15. Jennings AT. Hiring generation X. J Account. 2000; 189(2):55-59. 16. Karp H, Sirias D, Arnold K. Teams: why generation X marks the spot. J Qual Participation. 1999;22(4): 30-33. 17. O’Bannon G. Managing our future: the generation X factor. Public Pers Manage. 2001;30(1):95-109. 18. Westerman JW, Yamamura JH. Generational preferences for work environment fit: effects on employee outcomes. Career Dev Int. 2007;12(2):150-159. 19. Trimble DE. Organizational commitment, job satisfaction, and turnover intention of missionaries. J Psychol Theol. 2006;34(4):349-360. 20. Hafer JC. An empirical investigation of the salesperson’s career stage perspective. J Pers Sell Sales Manage. 1986;6(November):1-7.
21. Aguinis H, Pierce CA, Bosco FA, Dalton DR, Dalton CM. Debunking urban myths and urban legends about meta-analysis. Organ Res Methods. 2011;14(2): 306-331. 22. LeLorier J, Gregoire G, Benhaddad A, Lapierre J, Derderian F. Discrepancies between meta-analyses and subsequent large randomized, controlled trials. N Engl J Med. 1997;337(8):536-542. 23. Carstensen LL, Fung HH, Charles ST. Socioemotional selectivity theory and the regulation of emotion in the second half of life. Motiv Emotion. 2003;27(2): 103-123. 24. Roberts BW. Mroczek D. Personality trait change in adulthood. Curr Dir Psychol Sci. 2008;17(1):31-35. 25. Super DE, Savickas ML, Super CM. A life-span lifestage approach to career development. In: Brown D, Brooks L, eds. Career Choice and Development. 2nd ed. San Francisco, CA: Jossey-Bass; 1990:197-261. 26. Bedeian A, Ferris G, Kacmar KM. Age, tenure, and job satisfaction: a tale of two perspectives. J Vocat Behav. 1992;40(1):33-48. 27. Wright T, Bonett D. The moderating effects of employee tenure on the relation between organizational commitment and job performance: a meta-analysis. J Appl Psychol. 2002;87(6):1183-1190. 28. Carameli KA, Yanchus NJ, Judkins S, Osatuke K, Dyrenforth S. Employee Job Satisfaction: How Intrinsic and Extrinsic Determinants Differ Across Healthcare Occupations. Poster presented at the annual national conference by the Academy of Health in Seattle, WA, June 12-14, 2011. 29. Meterko M, Osatuke K, Mohr D, Warren N, Dyrenforth S. Civility: the development and psychometric assessment of a survey measure. In: Nagy M (moderator). Measuring and Assessing Workplace Civility: Do ‘‘Nice’’ Organizations Finish First? Panel presented at the 67th annual meeting of the Academy of Management, Philadelphia, PA, August 8, 2007. 30. Nagy MA. Using a single-item approach to measure facet job satisfaction. J Occup Org Psycho. 2002; 75(1):77-86. 31. Osatuke K, Moore SC, Ward C, Dyrenforth SR, Belton L. Civility, Respect, Engagement in the Workforce (CREW): nationwide organization development intervention at Veterans Health Administration. J Appl Behav Sci. 2009;45(3):384-410. 32. Conway JM, Lance CE. What reviewers should expect from authors regarding common method bias in organization research. J Bus Psychol. 2010;25(3): 325-334. 33. Carr JZ, Schmidt AM, Ford JL, DeShon RP. Climate perceptions matter: a meta-analytic path analysis relating molar climate, cognitive and affective states, and individual level work outcomes. J Appl Psychol. 2003;88(4):605-619.
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Workplace Satisfaction and Climate Perceptions 34. Garman AN, Corrigan PW, Morris S. Staff burnout and patient satisfaction: evidence of relationships at the care unit level. J Occup Health Psychol. 2002; 7(3):235-241. 35. Harter JK, Schmidt FL, Hayes TL. Business-unit-level relationship between employee satisfaction, employee engagement and business outcomes: a meta-analysis. J Appl Psychol. 2002;87(2):268-279. 36. Laschinger HKS, Finegan J. Using empowerment to build trust and respect in the workplace: a strategy
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for addressing the nursing shortage. Nurs Econ. 2005;23(1):6-13. 37. Kowske BJ, Rasch R, Wiley J. Millenials’ (lack of ) attitude problem: an empirical examination of generational effects on work attitudes. J Bus Psychol. 2010;25(2):265-279. 38. Twenge JM, Campbell SM, Hoffman BJ, Lance CE. Generational differences in work values: leisure and extrinsic values increasing, social and intrinsic values decreasing. J Manage. 2010;36(5):1117-1142.
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Employee Age and Tenure Within Organizations Relationship to Workplace Satisfaction and Workplace Climate Perceptions Robert Teclaw, PhD; Katerine Osatuke, PhD; Jonathan Fishman, PhD; Scott C. Moore, PhD; Sue Dyrenforth, PhD This study estimated the relative influence of age/generation and tenure on job satisfaction and workplace climate perceptions. Data from the 2004, 2008, and 2012 Veterans Health Administration All Employee Survey (sample sizes >100 000) were examined in general linear models, with demographic characteristics simultaneously included as independent variables. Ten dependent variables represented a broad range of employee attitudes. Age/generation and tenure effects were compared through partial 2 (95% confidence interval), P value of F statistic, and overall model R2. Demographic variables taken together were only weakly related to employee attitudes, accounting for less than 10% of the variance. Consistently across survey years, for all dependent variables, age and age-squared had very weak to no effects, whereas tenure and tenure-squared had meaningfully greater partial 2 values. Except for 1 independent variable in 1 year, none of the partial 2 confidence intervals for age and age-squared overlapped those of tenure and tenuresquared. Much has been made in the popular and professional press of the importance of generational differences in workplace attitudes. Empirical studies have been contradictory and therefore inconclusive. The findings reported here suggest that age/generational differences might not influence employee perceptions to the extent that human resource and management practitioners have been led to believe. Key words: age, employee attitudes, employee surveys, generation, tenure
N CROSS-SECTIONAL STUDIES, age and generation effects are inseparable. Knowing a person’s age points to his/her generation, and
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Author Affiliations: National Center for Organization Development, Veterans Health Administration (Drs Teclaw, Osatuke, Fishman, Moore, and Dyrenforth), Cincinnati, and Department of Psychology, Miami University (Dr Fishman), Oxford, Ohio. This material is based on work supported by the Department of Veterans Affairs. Any opinions, findings, conclusions, or recommendations expressed in this article are those of the research investigators and do not necessarily represent the view of the Department of Veterans Affairs or the US government. The authors report no conflicts of interest. Correspondence: Robert Teclaw, PhD, National Center for Organization Development, Veterans Health Administration, 11500 Northlake Dr, Suite 230, Cincinnati, OH 45249 ([email protected]). DOI: 10.1097/01.HCM.0000440616.31891.2d
vice versa. This article examines the relative effects of tenure and age (and indirectly generation) on several important response variables. Although age is used as a predictor, the conclusions also apply to generational effects, as with no, or only small age effects, there can be no large generational effects. Generational differences at work have received much attention in the literature.1-4 This topic has theoretical implications that reflect the potential of generational studies to demonstrate or invalidate broad cultural influences in shaping personal attitudes and behaviors.5 Terracciano6 reviewed conundrums faced by generational differences research in the context of studying adult personality cross-sectional, longitudinally, and cross-nationally. Empirical studies of generational differences have been inconclusive; widely different conclusions likely reflect heterogeneity in researchers’ fields, methods, and reasons for examining crossgenerational issues.7
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Workplace Satisfaction and Climate Perceptions Effects of age on employee perceptions have been examined in their own right without considering generations.8-10 In a meta-analysis of 802 articles, Ng and Feldman11(p677) concluded that the relationship between age and job attitudes is ‘‘generally significant and weak to moderate in strength.’’ The topic of generational differences also has important pragmatic implications, most prominently for human resource (HR) management and planning. Compared with the scientists’ perspective, separating age and generation effects (eg, in cross-sectional studies) is less important for HR specialists, because their tasks are mainly within the present, and the relevant differences are therefore those observed today, with or without generalization to other historical periods. The generational differences of current concern to HR are the demographic trends: suggesting a growing workforce presence of the elderly and younger workers. The pressing nature of these pragmatic concerns makes it challenging to wait for conclusive scientific results (cf. Eckersley7(p79)): ‘‘We cannot wait for scientific proof, which may always remain beyond our reach, before taking political action in health, education, and the media.’’ Descriptions and interpretations of workers’ generational differences, based typically on anecdotal accounts or opinions, therefore abound in the popular press targeting managers and HR professionals. Although the available empirical evidence shows more variation in individual behaviors and attitudes within than between generations (eg, Macky et al12), many popular articles assume otherwise; they formulate psychological profiles of specific generations and detailed recommendations of how to harmonize them at work. Empirical research on generational aspects pertaining to workplace includes 2 relevant, somewhat competing foci: differences across birth cohorts, usually assessed through age (eg, see Kupperschmidt2), and differences reflecting tenure, or career stage.13 Evidence was examined and compared for these approaches in an employee census survey of workplace perceptions and satisfaction at the Department of Veterans Affairs.
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EFFECTS OF GENERATIONAL DIFFERENCES VERSUS ORGANIZATIONAL TENURE AT THE WORKPLACE Studying demographic differences in the workplace generally involves 2 strategies.3 One, based on age, suggests that workers’ birth generation affects workplace climate and job satisfaction because generational differences inherently shape perceptions, thus leading to potential conflicts.2 Given the challenges of longitudinal data collection,6 this strategy typically involves cross-sectional studies, with collapsing age and cohort effects. Another, stage-based, strategy of studying generational differences suggests that perceptions change with time, such that the amount of experience on the job shapes employee perceptions of their work environment.13 A generation is a group of individuals sharing birth years, birth location, and significant life events.2 These similar life experiences are thought to distinguish generations from each other.14 The 2 most prevalent generations in today’s workforce are the baby boomers and generation X.3 The next generation entering the workforce is known as the millennials, generation Yers, or the next generation.15 Differences between baby boomers and Xers have been presented as important; for example, understanding them has been described as promoting productivity, innovativeness, and corporate citizenship,2 and ignoring them has been claimed to create workplace conflicts based on misunderstandings.1 Many of these conclusions do not appear empirically driven; for example, see Karp et al,16 Kupperschmidt,2 and O’Bannon.17 A modest amount of empirical research supports generational differences at work. Westerman and Yamamura18 found higher overall job satisfaction in baby boomers than in younger generations and that these latter had greater need of goal- and system-driven work environments. Smola and Sutton3 compared baby boomers’ and Xers’ work values. In their sample from 53 US companies (predominantly manufacturing but including 17 service organizations), they found a generational effect, with generation X less loyal to the company and more focused on personal goals. Work values
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THE HEALTH CARE MANAGER/JANUARY–MARCH 2014
of baby boomers also changed as a function of time spent within the organization, thus lending support to both generational and tenure effects. Jurkiewicz13 examined generational differences in work motivation in 241 employees from various work departments in 5 MidWestern municipalities. Only 3 of the 15 categories differed across generation: 2 in the direction opposite from the expectations based on the popular literature descriptions of Xers’ job expectations. Jurkiewicz concluded that the claim of generational differences reflects commonly held assumptions more than any real differences among the actual workers and argued that employees’ experience on the job is more central to workplace differences than generational distinctions. Similarly, Trimble’s19 investigation of missionaries found that organizational tenure was a stronger predictor of work commitment, job satisfaction, and turnover intention than was age, defined as Xers versus older generations. Within salesmanship research, investigators’ attempts to connect age with job performance also have been unsuccessful.20 Hafer20 reported initial support for a stage-based approach as more useful than generational, but noted this evidence was not robust and called for more research. Two recent meta-analyses have increased our understanding of the relationships among age/generation, tenure, and various dependent variables. Costanza et al4 found moderate to nonexistent relationships between generational membership and workplace outcomes. Ng and Feldman11 found moderate to weak relationships between age and dependent variables. However, meta-analyses have potential problems, most notably publication bias effects and a dependence on the quality of the primary-level studies.21 In addition, the clinical trials literature demonstrated that meta-analyses and large randomized clinical trials do not necessarily agree.22 Several theoretical explanations have been offered for age/generational differences in employee attitudes. One such explanation is socioemotional selectivity theory.10 According to this theory, as people age, they transition from seeking novel information to achieving positive emotional states,23 and this transition could account for older workers’ more favorable
job attitudes. Kacmar and Ferris8 used career stage and development theory, according to which young workers attempt to fit in, middle age workers are productive, and older workers begin to disengage, to underpin their study of the age-job satisfaction relationship. Ng and Feldman11 applied socioemotional selectivity theory to understand the age-job attitudes relationship but also recommended other theoretical approaches; for example, continuous increases in agreeableness and conscientiousness over one’s life course would suggest higher satisfaction and better job attitudes for older workers.24 These authors also suggested alternative theories for an age-job attitudes relationship, such as the life-span life-stage model of Super et al,25 in which older workers are more concerned about nonwork roles and are thus less likely to be dissatisfied. In practice, it is quite difficult to suggest a theory of why age/generation might not be associated with work attitudes and even harder to test such theories. One can, however, test whether the age-attitude relationship even exists to the extent of significantly predicting employee attitudes, and that is the purpose of this study. If there is no meaningful age-job attitude relationship, then the question of developing a theoretical underpinning for that relationship becomes moot. Addressed in the Discussion is the seeming contradiction between this study’s results and conventional wisdom about generational differences. FOCUS OF THIS STUDY The motivation to study the relative importance of age and tenure on employee attitudes had as its source the qualitative analysis of interview transcripts of Veterans Health Administration (VHA) workgroups conducted at the VHA National Center for Organization Development. Employees were interviewed as part of climate assessments at their workplaces (eg, medical centers, hospitals, clinics) in the context of planning organizational interventions. In confidential interviews that organizational consultants conducted with randomly selected employees representing at least 10% of participating workplaces, participants were asked to discuss in an open-ended format any strengths,
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Workplace Satisfaction and Climate Perceptions weaknesses, and desired changes in their workplace. The data were used for intervention planning (within sites) and for summarizing overall themes of employee comments (across sites). Based on these data (1118 employee interviews representing 28 workgroups at 19 facilities), respondents occasionally mentioned organizational tenure (or similar terms) and made comments on differences in coworkers’ perceptions and attitudes related to these factors. Age/ generation and any related differences were, however, rarely if ever brought up. The difference in the relative frequency of age and tenure mentioned in the employee comments about their workplace might have gone unnoticed except for the appearance in professional (nonempirical) publications at that time of a large number of articles emphasizing the importance of generational differences in the workplace and urging managers and HR professionals to take these differences into account. We decided to approach the question quantitatively using an employee survey with well over 100 000 respondents, enough to detect small effects of multiple demographic variables simultaneously. This study explored the relative importance of differences in workplace perceptions and job satisfaction among VHA employees in different age groups, considering their organizational tenure level. Data from the VHA All Employee Survey (AES) were used to compare employee perceptions of their workplace across age (and indirectly, generational) categories and tenure categories, with additional analyses of gender, supervisory status, occupation, ethnic, and racial differences. Previous experience with these data sets suggested that employee attitudes would show statistically significant relationships to individual demographic variables given the large samples, regardless of the effect size. Also from previous analyses, we knew that all of the demographic variables considered here were not independently distributed in the AES data sets. Therefore, it was decided to evaluate the effects of multiple demographic variables simultaneously. To not do so would have repeated some of the limitations of most of the previous studies on age/generation and tenure effects on employee attitudes and perceptions: namely, that any relationships reported could
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have been due to the confounding effects of other demographic variables. The large number of respondents enabled inclusion of all demographic items in the survey as predictor variables in the models without significant loss of power. This allowed a direct comparison of effect sizes for all demographic variables and, in this context, evaluating the influences of age/ generation and tenure, the major focus of this study. The dependent variables (see Methods) are consistent with those used in prior studies, which examined the effects of age, birth cohort, generation, and/or organizational tenure. Ng and Feldman11 classified the dependent variables from 802 empirical studies (published and unpublished) on the age/generation and tenure relationship with employee attitudes into 35 categories and 3 overarching groupings: taskbased, people-based, and organization-based attitudes. Our selection of dependent variables sought to maximize the chances of finding significant effects of age and/or tenure, if they existed. Our intention was to preemptively address potential limitations in generalizability of our findings regarding a relationship with age/ generation and employee attitudes because we did not consider enough and or the ‘‘right’’ outcome variables. We therefore represented the types of outcomes examined in previous research (ie, studies classified by Ng and Feldman11), including studies that found significant effects of demographic variables, which our study attempted to replicate using a larger data set. We specifically included measures representing task-based, people-based, and organization-based attitude groupings, in order to evaluate several types of dependent variables for potential effects of age and tenure and to explore differences in effect patterns corresponding to these types of variables. Our hypotheses were based on the results of qualitative analysis of Veterans Affairs (VA) employee interviews and also on prior empirical reports that described tenure as a ‘‘more consistent and stable predictor of job satisfaction than chronological age’’26(p33) and a 22-study metaanalysis, which found that ‘‘controlling for tenure, employee age has a small and unimportant moderating effect on the commitmentperformance correlation.’’27(p1187)
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THE HEALTH CARE MANAGER/JANUARY–MARCH 2014 1. Hypothesis 1: Age/generation has little relationship to employee attitudes, when other demographic characteristics are controlled. 2. Hypothesis 2: Tenure or time with the organization is related to employee attitudes, when other demographic characteristics are controlled. 3. Exploratory hypothesis 3: Demographic characteristics show differences in pattern of effects depending on the particular outcome variable.
METHODS The data consisted of VHA hospital employees’ ratings of workgroup climate and job satisfaction provided in the 2004, 2008, and 2012 VHA All Employee Survey (AES, copy available upon request). The AES is a voluntary, confidential annual survey of all VA employees (see Table 1 for number of respondents and response rates). AES respondents rate their job satisfaction and agreement with specific descriptions of workplace climate using Likerttype scales with response options from 1 to 5 (‘‘not at all satisfied’’ to ‘‘very satisfied’’ for satisfaction ratings; ‘‘strongly disagree’’ to ‘‘strongly agree’’ for workplace climate ratings). Summary scores based on item ratings are broadly shared within VHA and support and workforce development planning nationally, regionally, and locally (eg, AES scores inform HR strategies within specific hospitals and clinics). All Employee Survey respondents included multipleracial, ethnic, geographic, and occupational groups, representing the diverse workforce. The VHA employs more than 280 000 workers
over all 50 states, in rural and metropolitan areas, in various work settings, for example, patient care, administrative, research, fiscal, and others. Examined were the AES items that met these criteria: (a) were used in previous studies of age and tenure effects on employee attitudes,11 (b) were hypothesized as potentially sensitive to the demographic differences within the focus of our study, (c) served as an annual basis for workforce-targeted action planning within VHA, and (d ) were identified as reliable, valid dimensions of VHA employees’ workplace perceptions in previous research with the AES.28-31 The specific categories and items of interest (numbers in brackets indicate the number of studies using that dependent variable in Ng and Feldman’s11 meta-analysis) included task-based attitudes (overall job satisfaction [388], satisfaction with pay [52], satisfaction with work itself [41], and satisfaction with promotion [36]), people-based attitudes (satisfaction with coworkers [36], satisfaction with supervisors [41], relationship conflict [14], and coworker support [38]), and organizationbased attitudes (organizational identification [26] and perceived organizational support [75]). Table 2 lists the AES items used in the analyses. Also examined were scores across VHA employee age categories. The survey question used to distinguish among these was ‘‘What is your age?’’ with response options including less than 20 years, 20 to 29, 30 to 39, 40 to 49, 50 to 59, and 60 years or older. The youngest age category was not used in the analyses because that age included much lower numbers of employees and large variance in responses.
Table 1. Response Rates and Number of Respondents Used in Analyses, Veterans Health Administration (VHA) All Employee Survey
Year
Overall Survey Response Rate
N (VHA Hospital Employees)
n (After Removal of Responses From Employees 20 years and age between 20 and 30 years).
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Workplace Satisfaction and Climate Perceptions
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Table 2. All Employee Survey Items Used in This Study Task-based attitudes 1. Overall satisfaction: Compared with what you think it should be, what is your current overall level of satisfaction with your job? 2. Satisfaction with pay: Compared with what you think it should be, how satisfied are you with the amount of pay that you receive? 3. Satisfaction with work itself: Compared with what you think it should be, how satisfied are you with the type of work that you currently do? 4. Satisfaction with promotion: Compared with what you think it should be, how satisfied are you with the number of opportunities for promotion? People-based attitudes 1. Satisfaction with coworkers: Compared with what you think it should be, how satisfied are you with the relationships you have with your coworkers? 2. Satisfaction with supervisors: Compared with what you think it should be, how satisfied are you with the quality of direct supervision you receive? 3. Relationship conflict: Disputes or conflicts are resolved fairly in my work group. 4. Coworker support: The people I work with can be relied on when I need help. Organization-based attitudes 1. Organizational identification: I feel a strong personal connection with the mission of Department Veterans Affairs. 2. Perceived organizational support: Department Veterans Affairs cares about my general satisfaction at work. Survey items listed in Table 1 were rated on a Likert-type scale. Response options ranged from 1 to 5, corresponding to 1: not at all satisfied, 3: neither satisfied nor dissatisfied, 5: very satisfied’’ (for satisfaction ratings) and to 1: strongly disagree, 3: neither agree nor disagree, 5: strongly agree (for workplace perception ratings, which include all other items in the table). ‘‘Don’t know’’ was an available option for workplace perception ratings (but not for satisfaction ratings). It was treated as missing data for the purposes of this study.
Tenure was measured by asking ‘‘How long have you been with the VA?’’ with response options including less than 6 months, 6 months to 1 year, 1 to 2 years, 2 to 5 years, 5 to 10 years, 10 to 15 years, 15 to 20 years, and more than 20 years. The other predictors included race (6 levels), occupation (51 levels), gender, and ethnicity, all as class variables, and supervisory status (5 levels) as a numeric variable. Interaction terms were entered in initial models; they were either not significant or contributed little to overall R2 and were therefore excluded from the final models. Because the 10 dependent variables are considered one at a time, relationships among dependent variables due to common method bias32 should not be an issue in the analysis. General linear model regression (PROC GLM; SAS Institute, Cary, North Carolina) was used to assess the effects of age and tenure on the dependent variables. The amount of variance explained by the overall model was reported as R2. The statistical significance of the F test for each independent variable (IV) was determined by its P value in the type III sum-ofsquares table. Effect sizes for each of the IVs were determined by partial 2 with 95% confidence limits. Separate models were run for each
of the 10 dependent variables and 3 survey years. Given a U-shaped relationship of workplace attitude ratings to both tenure and age in previous research,8,9 the square of these variables was included in the model. Other demographic characteristics were expected to be associated with the dependent variables, so they were included to control for their effects, thus simultaneously evaluating the relative effect sizes of all demographic variables.
RESULTS For each of the 10 dependent variables, results across years were very consistent for overall model R2, dependent variable F test P value, and partial 2 (Figures 1-10). Overall model R2 values ranged from 0.03 for many dependent variables to 0.10 for satisfaction with promotion (Figure 4) for the 2004 AES. When considered as the only predictors, demographic characteristics explained only a small amount of variance in the 10 dependent variables. P values were always .05). Year = 2012: overall model R2 = 0.034; P < .0001 for all IVs except ethnicity (P > .05). Note: Error bars = 95% confidence interval (CI) for partial 2. Missing error bars are undefined.
Figure 2. Effect size for demographic variables regressed on ‘‘satisfaction with pay,’’ Veterans Health Administration, All Employee Survey 2004-2012. Year = 2004: overall model R2 = 0.081; P < .0001 for all independent variables (IVs). Year = 2008: overall model R2 = 0.078; P < .0001 for all IVs. Year = 2012: overall model R2 = 0.069; P < .0001 for all IVs. Note: Error bars = 95% confidence interval for partial 2. Missing error bars are undefined.
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Workplace Satisfaction and Climate Perceptions
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Figure 3. Effect size for demographic variables regressed on ‘‘satisfaction with work itself,’’ Veterans Health Administration, All Employee Survey 2004-2012. Year = 2004: overall model R2 = 0.032; P < .0001 for all independent variables (IVs) except ethnicity and age (P > .05). Year = 2008: overall model R2 = 0.034; P < .0001 for all IVs except ethnicity and age (P < .01). Year = 2012: overall model R2 = 0.033; P < .0001 for all IVs except age (P < .05). Note: Error bars = 95% confidence interval for partial 2. Missing error bars are undefined.
Figure 4. Effect size for demographic variables regressed on ‘‘satisfaction with promotion,’’ Veterans Health Administration, All Employee Survey 2004-2012. Year = 2004: overall model R2 = 0.098; P < .0001 for all independent variables (IVs) except ethnicity (P > .05). Year = 2008: overall model R2 = 0.099; P < .0001 for all IVs. Year = 2012: overall model R2 = 0.095; P < .0001 for all IVs except ethnicity (P < .01). Note: Error bars = 95% confidence interval for partial 2. Missing error bars are undefined.
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THE HEALTH CARE MANAGER/JANUARY–MARCH 2014
Figure 5. Effect size for demographic variables regressed on ‘‘satisfaction with coworkers,’’ Veterans Health Administration, All Employee Survey 2004-2012. Year = 2004: overall model R2 = 0.029; P < .0001 for all independent variables (IVs) except ethnicity (P > .05). Year = 2008: overall model R2 = 0.032; P < .0001 for all IVs except ethnicity (P < .05). Year = 2012: overall model R2 = 0.031; P < .0001 for all IVs except ethnicity (P > .05). Note: Error bars = 95% confidence interval for partial 2. Missing error bars are undefined.
Figure 6. Effect size for demographic variables regressed on ‘‘satisfaction with supervisors,’’ Veterans Health Administration, All Employee Survey 2004-2012. Year = 2004: overall model R2 = 0.033; P < .0001 for all independent variables (IVs) except ethnicity (P > .05). Year = 2008: overall model R2 = 0.032; P < .0001 for all IVs. Year = 2012: overall model R2 = 0.029; P < .0001 for all IVs. Note: Error bars = 95% confidence interval for partial 2. Missing error bars are undefined.
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Workplace Satisfaction and Climate Perceptions
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Figure 7. Effect size for demographic variables regressed on ‘‘relationship conflict,’’ Veterans Health Administration, All Employee Survey 2004-2012. Year = 2004: overall model R2 = 0.069; P < .0001 for all independent variables (IVs) except ethnicity (P > .05). Year = 2008: overall model R2 = 0.065; P < .0001 for all IVs except ethnicity (P < .01). Year = 2012: overall model R2 = 0.059; P < .0001 for all IVs except ethnicity (P < .01). Note: Error bars = 95% confidence interval for partial 2. Missing error bars are undefined.
Figure 8. Effect size for demographic variables regressed on ‘‘coworker support,’’ Veterans Health Administration, All Employee Survey 2004-2012. Year = 2004: overall model R2 = 0.047; P < .0001 for all independent variables (IVs) except gender (P > .05). Year = 2008: overall model R2 = 0.045; P < .0001 for all IVs except gender (P < .05). Year = 2012: overall model R2 = 0.044; P < .0001 for all IVs except gender (P > .05). Note: Error bars = 95% confidence interval for partial 2. Missing error bars are undefined.
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THE HEALTH CARE MANAGER/JANUARY–MARCH 2014
Figure 9. Effect size for demographic variables regressed on ‘‘organizational identification,’’ Veterans Health Administration, All Employee Survey 2004-2012. Year = 2004: item not used in this year’s survey. Year = 2008: overall model R2 = 0.053; P < .0001 for all independent variables (IVs) except gender and age-squared (P > .05). Year = 2012: overall model R2 = 0.052; P < .0001 for all IVs except gender (P > .05) and age-squared (P < .01). Note: Error bars = 95% confidence interval for partial 2. Missing error bars are undefined.
Figure 10. Effect size for demographic variables regressed on ‘‘perceived organizational support,’’ Veterans Health Administration, All Employee Survey 2004-2012. Year = 2004: item not used in this year’s survey. Year = 2008: overall model R2 = 0.057; P < .0001 for all independent variables (IVs) except gender (P > .05). Year = 2012: overall model R2 = 0.055; P < .0001 for all IVs except gender (P > .05). Note: Error bars = 95% confidence interval for partial 2. Missing error bars are undefined.
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Workplace Satisfaction and Climate Perceptions F tests (P > .05), whereas age and age-squared had 1 and 2 nonsignificant instances, respectively. For all years and all dependent variables, effect sizes for tenure and tenure-squared were much larger than effect sizes for age and agesquared. With 1 exception (satisfaction with pay in 2004; Figure 2), none of the 95% confidence limits overlapped, suggesting that the observed effect size advantage of tenure over age was not due to chance. For most of the dependent variables, age and age-squared had only a negligible explanatory effect. The highest partial 2s for age and age-squared were 0.0020 and 0.0024, respectively, for satisfaction with promotion, 2004 (Figure 4). Regarding the hypotheses for this study 1. Hypothesis 1: Age/generation will have little relationship to employee attitudes, when other demographic characteristics are controlled. The results support this hypothesis. Age and age-squared had a statistically significant relationship with most of the dependent variables in most years; nevertheless, the magnitude (partial 2) of effect was not meaningful, never approaching 1%. 2. Hypothesis 2: Tenure or time with the organization is related to employee attitudes, when other demographic characteristics are controlled. This hypothesis was supported; tenure and tenure-squared were always statistically significantly associated with the dependent variables (P .0001). Effect sizes were intermediate between the most strongly associated demographic variable, occupation, and the very weekly associated variables, age, agesquared, gender, and ethnicity. 3. Exploratory hypothesis 3: Demographic characteristics will show important differences in pattern of effects depending on the particular outcome variable studied. This hypothesis was partially supported. Although the relative importance of the various demographic predictors was similar for all dependent variables, the magnitudes of the effect differed depending
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on the dependent variable. Whether these differences were big enough to reach the threshold of ‘‘important’’ has not been definitively settled except possibly for ‘‘satisfaction with pay’’ (Figure 2) and ‘‘satisfaction with promotion’’ (Figure 4). DISCUSSION In the current study, the researchers were fortunate to have access to multiyear data sets similar to or even greatly exceeding the size of typical meta-analytic studies, which allowed evaluation of the generational differences thoroughly and systematically. This may well be the first study to examine generational differences in an extremely large data set, representing a diverse sample of respondents over multiple years. We assessed effects of generational differences on multiple dependent variables in multiple years of data were assessed, with an adequate power to evaluate the significance and effect sizes of the differences controlling for alternative explanations, for example, other demographics. The study examined the relative impact of generational differences (using age category as a proxy) and tenure at a given organization on aspects of job satisfaction and workplace climate ratings. It was found that VA tenure had a larger effect on these outcomes than employee age did and that effects were small for both. Previous studies (eg, Kupperschmidt2 and Jurkiewicz13) presented some evidence for both birth cohort and workplace tenure as predictors of employees’ perceptions. While our study also demonstrated a greater relevance of tenure compared with age, putting both of these in the context of considerably larger effects of other demographics suggested that generational differences at work are overall not important. The strategy of using age category as a proxy for generation has limitations (as it collapses year of birth effects with age effects, ascertaining the influence of one factor does not necessarily prove the influence of the other). However, because no age effects or only small age effects were consistently found, this evidence does suggest no large generational effects are present.
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The methods used in this study lend much confidence to this conclusion. First, the data reflect a very large and extremely diverse sample of multiple racial, ethnic, geographic, and occupational groups (eg, nurses, doctors, psychologists, chaplains, education specialists, food service and housekeeping employees, executives, clerks, police officers, and many others), representing employee diversity within VA, the second largest federal employer in the United States. Second, effect sizes of tenure and age considering other, possibly confounding, demographics were compared. Third, all quantitative comparisons were replicated in 3 years of data across a 9-year period, which verified the stability of the findings. With the exception of race, the demographic variables most related to the dependent variables represented acquired (occupation, tenure, tenure-squared, and supervisory status) rather than innate (gender, ethnicity, age, and age-squared) categories. This could reflect the relatively larger influences of organizationally based differences (the first group of demographics) compared with personally based differences (the second group). The meaning of these differences was outside the scope of this study; their more precise interpretations require further research. How should the results be interpreted in light of Ng and Feldman’s11 802 meta-analysis, which found moderate effects of age on multiple employee attitudes? The present approach offers several advantages. The largest sample size was 158 971 respondents in 2012. The largest populations of the meta-analysis were 151 105 respondents spread over 388 different studies for ‘‘overall job satisfaction’’ and 108 315 respondents from 296 studies for ‘‘affective commitment.’’ Twelve of the remaining 33 outcome variables were represented by populations under 10 000. One of the usual justifications for meta-analyses is that sample sizes from individual studies are often too small to address the research question. This study uses a population size exceeding (and for many outcomes, greatly exceeding) the population from the meta-analysis. In addition, the population, although diverse in organizational roles, occupations, geographic locations within the
United States, and other demographics, comes from a single large organization. This is an advantage for answering the research question, but a disadvantage for generalizing the findings. It is unlikely, however, that age is not an important predictor of employee attitudes in a large health care organization, but it is everywhere else. In any case, we do not claim that these results apply to other contexts, only that they bring into question the commonly held belief that age/generation is an important predictor of employee attitudes. An additional difference between our study and Ng and Feldman’s11 meta-analysis is the way of approaching potentially moderating variables. The meta-analysis by necessity considered moderators one at a time, which reduced the population as not all studies examined all potential modifiers. We controlled for several potential modifiers simultaneously using the full population. It was also possible to control for multicolinearity among predictors; the results for each predictor were conditioned on the simultaneous presence of all of the others. Finally, both the meta-analysis and the present study used data sets from different years. The meta-analysis found smaller effects of age in more recent studies (after 1999 to after 2003, depending on outcomes). We found quite stable results across 2004. The effect of age on employee attitudes could have been higher in the past, explaining the different results. Limitations of this study included the following. First, differences between age effects and cohort effects (eg, comparisons of individuals of similar age but living in different historical time periods) were not examined. However, the concept of generational differences, which was of central interest to this study (reflecting its importance to the practicing HR professionals), by definition collapses the 2 notions (age and cohort); therefore, this limitation did not impede the ability to examine the concept. Second, the quantitative data set, the VHA AES, was not specifically designed to measure our variables of study (birth generations and organizational tenure effects). However, the dependent variables were selected consistently with the type of variables typically used in empirical investigations of age, cohort,
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Workplace Satisfaction and Climate Perceptions generation, and tenure—including studies that reported significant effects of age and tenure on these variables (eg, see Luchman et al10). This suggests relevance of the selected dependent variables to the topic of study and thereby for generalizability of the findings. Third, the results pertain to age effects on employee attitudes. Possibly, some relevant age/generational differences among coworkers (eg, informality or preference for social networking) were not reflected in the items we chose or in the AES items in general. However, to the extent that employee surveys inform HR practices, this study’s findings are important. The AES has an established reputation of conveying employee input within VA: developing action plans from AES results is part of VA managers’ performance measures. So, while possibly not capturing every generationally relevant aspect of the workplace, this survey reflects what the largest federal health care organization considers directly actionable and has been ‘‘using’’ for actions since 2004. Fourth, age or tenure scaled as years was not available for this study. The coarseness of these measures could have minimized their relationships to the outcomes. The purpose, however, was to compare their relative effects, and because age and tenure were similarly scaled, scale coarseness likely did not greatly influence the related conclusions. Finally, the findings are based on an all-employee survey within a large, government health care system. The nature of the work and of the employer could minimize age effects that might be augmented in another context. If so, at a minimum, HR professionals should use caution in applying a ‘‘one size fits all’’ approach to multigenerational issues. Prior studies have made a convincing business case for attending to employees’ experience of workplace climate (eg, see Carr et al,33 Garman et al,34 Harter et al,35 Laschinger et al36). This motivates an interest in describing specific influences on workplace perceptions and incorporating these into workforce policies. Based on present results, key influences on workplace perceptions likely do not include the workers’ generation or organizational tenure. The very modest effect sizes of these variables when examined
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with other demographics suggest no pragmatically meaningful effects. The statistically significant effect of age (and, by proxy, generational differences) should be considered in perspective of, first, larger effects of being a new versus tenured employee within the organization (irrespectively of one’s birth cohort) and, second, in the context of other demographic characteristics demonstrating by far larger effects than either age and tenure (eg, occupation). Anyone who has interacted with someone much older or younger cannot help but notice differences in affect and attitudes. Quite possibly, one would not find instant rapport with oneself from an earlier or later time in life. One explanation for this study’s findings (no meaningful difference) is that age/generational differences in demeanor and preferences, although possibly real, may be irrelevant when forming and expressing attitudes about work. For example, younger workers might prefer a more informal, social media–driven workplace, but this does not impact their satisfaction with pay or coworker support. The few longitudinal studies available3,37,38 did note generational differences among workers, which seems to refute our conjecture. An interpretation that reconciles this inconsistency, however, is that, according to our results, age/generation differences in work attitudes may stem from the confounding effects of uncontrolled demographics. Studies that did not control for these confounds, especially tenure, could therefore be reporting spurious associations. If age/generational difference in work attitudes is very small, why are they given so much credence among HR professionals? Like us, other researchers of cohort and generational effects have raised the possibility that beliefs into generational differences may reflect judgments based on extremely memorable exemplars, that is, availability bias.5 These beliefs, once formed, may be maintained by confirmatory biases whereby people selectively attend to statements and observations that confirm their already existing opinions. Thus, the intensity of perceived differences between the generations of workers may, at least partly, reflect social cognition biases rather than true differences between members of generational groups.5
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