Journal of Applied Psychology 2003, Vol. 88, No. 3, 529 –537
Copyright 2003 by the American Psychological Association, Inc. 0021-9010/03/$12.00 DOI: 10.1037/0021-9010.88.3.529
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Work Attitudes and Decisions as a Function of Manager Age and Employee Age Lynn M. Shore
Jeanette N. Cleveland
Georgia State University
Pennsylvania State University
Caren B. Goldberg George Washington University
Research has shown the importance of employee age relative to coworker age in determining attitudes, performance, and career-related opportunities. The authors used chronological and subjective measures of employee and manager age to determine whether employee age relative to the manager has an impact on these same outcome variables. One hundred eighty-five managers and 290 employees completed surveys. The strongest and most consistent age effects were observed for interactions between employee and manager chronological age. Both the magnitude and pattern of the employee–manager age interactions varied by self- and manager-rated outcome measures of work attitudes, performance and promotability assessments, and developmental experiences. Results are discussed in light of the relational demography and career timetable literatures.
Traditionally, managers were likely to be older and more experienced than most of the individuals they supervised. It is now increasingly common (e.g., because of reorganizations and mergers) to find older workers reporting to younger managers. Although there has been much research on the simple relationship between employee age and important work decisions and outcomes (Rhodes, 1983; Waldman & Avolio, 1986), more recent research suggests that it is important to consider contextual influences, such as the ages of others in the employee’s work environment (Murphy & Cleveland, 1995). Several previous studies (e.g., Cleveland & Shore, 1992; Cleveland, Shore, & Murphy, 1997; Ferris, Judge, Chachere, & Liden, 1991) have shown that work attitudes and evaluations of older and younger workers are affected by the ages of their coworkers. The present study extends that line of research by examining the effects of another important aspect of the work environment—the manager’s age. Two distinct conceptualizations have emerged in the literature that provide a basis for making predictions about the influence of manager age relative to employee age in the work context, including relational demography (Riordan & Shore, 1997; Tsui, Xin, & Egan, 1995) and Lawrence’s (1988) career timetable. Below, we describe both theoretical approaches and their implications for making predictions about the role of manager age.
Relational Demography as a Theoretical Underpinning of Employee–Manager Relationships Organizational demography research investigates the relationship between demographic variables and organizational outcomes (Lawrence, 1988). Studies of relational demography, which use comparisons of demographic characteristics of individuals to predict outcomes at the individual level of analysis (Ferris et al., 1991; Perry, Kulik, & Zhou, 1999), are particularly relevant to the present research. The logic behind relational demography is based on the similarity–attraction paradigm (Byrne, 1971; Riordan & Shore, 1997). This research proposes that the greater the similarity between an individual and members of his or her work unit, the more attracted the individual is to the members of the unit. As a result, the individual will have more positive work attitudes and experiences. Conversely, when the individual is dissimilar from members of the unit in terms of salient demographic characteristics (e.g., age), the person is likely to have more negative work experiences. Relatively little research in relational demography has focused on manager– employee dyads. However, Tsui et al. (1995) suggested that similarities and differences in employee–manager attributes, such as age, are important in understanding leader– subordinate relationships, as they serve as the basis for (a) forming interpersonal attraction and (b) inferring managerial perceptions of employee performance and employee perceptions of managerial supportiveness. Thus, the effect of employee age on managers’ perceptions of their employees may depend in part on the manager’s age. Leader–member exchange research (Graen & Scandura, 1987; Graen & Uhl-Bien, 1995) also suggests that manager– employee age differences may lead to a poor quality exchange relationship
Lynn M. Shore, Department of Management, Georgia State University; Jeanette N. Cleveland, Department of Psychology, Pennsylvania State University; Caren B. Goldberg, Department of Management Science, George Washington University. Correspondence concerning this article should be addressed to Lynn M. Shore, Department of Management, 35 Broad Street, P.O. Box 4014, Robinson College of Business, Georgia State University, Atlanta, Georgia 30302-4014. E-mail:
[email protected] 529
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because of the manager’s expectation of supervision problems. In turn, low-quality exchange relationships are expected to result in higher turnover, lower employee performance ratings, and lower satisfaction and commitment levels (Graen & Uhl-Bien). Liden, Wayne, and Stillwell (1993) provided evidence that perceived demographic similarity of superiors and subordinates is positively associated with leader–member exchange quality. This finding, coupled with other studies that have linked demographic similarity with superiors’ rating of employees’ performance (Antoinette, 1992; Judge & Ferris, 1993; Lagace, 1990; Tsui & O’Reilly, 1989), suggests that manager– employee age differences may be an important predictor of work attitudes and behaviors. In particular, relational demography theory predicts that employees who are similar in age to their managers will have more positive work attitudes and experiences than will employees who are dissimilar in age to their managers.
Career Timetables as a Theoretical Underpinning of Employee–Manager Relationships Whereas relational demography proposes a symmetrical matching process in which matches result in more favorable outcomes than do mismatches, findings of other researchers (Perry & Bourhis, 1996) suggest that a symmetrical matching process may not operate for age. Lawrence (1987, 1988) proposed the notion of career timetables. Her research suggests that there are clear norms regarding where one should be on the organizational chart at a given age. Individuals who are promoted at a rate consistent with their peer group are considered “on time,” those who are promoted more rapidly than their peer group are considered “ahead of time,” and those who are promoted less often than their peer group are viewed as “behind time.” Although the latter two groups both represent target-referent mismatches, in contrast to relational demography’s treatment of all mismatches as equal, the career timetable approach makes very different predictions about these two mismatched groups. Lawrence (1987, 1988) showed that ahead of time employees are viewed as “fast-trackers,” who are rewarded for their ambition; behind time employees are seen as “dead wood,” who are penalized for their satisfaction with mediocrity. Although Lawrence’s (1987, 1988) work focused on the work group as a referent, it is likely that the presence of a young manager may contribute to the perception of an older employee as being behind time. For example, status incongruence between an older employee and a younger manager may yield very different social interactions than the same age difference between a younger employee and an older manager because the latter does not violate organizational age norms (Lawrence, 1988). When employees are older than their managers, they may perceive that their situation violates the career timetable associated with managerial positions (Perry et al., 1999). They are also likely to perceive a lower level of support and consideration from their managers, managers may perceive a lower level of loyalty and contribution from employees, and there may be less liking of one another (Tsui et al., 1995). In short, the career timetable perspective suggests that employees who are younger than their managers will have the most favorable work experiences, whereas employees who are older than their managers will experience the least favorable outcomes. Of interest, Perry et al.’s (1999) study examining the impact of employee age relative to the manager on self-rated citizenship, self-rated work change, and absenteeism found little support for either the rela-
tional demography or career timetable framework. However, the present study uses a much broader array of criteria (attitudes, behaviors, and training and development) and both employee- and manager-based measures, allowing for a more extensive comparison of the two frameworks.
Operationalizing Age: Chronological and Subjective Although chronological age is a useful way to measure age, a number of studies (e.g., Cleveland & Shore, 1992; Cleveland et al., 1997) have shown that measures of subjective age add to our understanding of how age might influence organizational outcomes. Subjective age refers to how old or young the individual perceives him- or herself to be (Barak, 1987; Riordan, 2000; Steitz & McClary, 1988). It reflects the age group with which the individual feels closest, either directly (i.e., on the basis of chronological age) or indirectly (i.e., on the basis of shared characteristics, such as appearance and interests; Cleveland & Shore, 1992). Although chronological and subjective age are correlated, differences occur across the life span, with greater discrepancies at older ages (Kastenbaum, Derbin, Sabatini, & Artt, 1972; Steitz & McClary, 1988). Research also suggests that individuals’ life events (e.g., health, socioeconomic status) and whether age has positive or negative associations (e.g., wisdom, maturity, or functionality) may determine when subjective and chronological age differ (Steitz & McClary, 1988). Because little research has examined the influence of subjective age for working adults, in addition to chronological age, we use both employee-rated subjective age and manager-rated subjective age. The comparison of chronological and subjective age measures is exploratory because neither theory nor research suggests specific predictions for working adults.
Hypotheses in the Present Study The theory and research reviewed suggests specific predictions about how manager age and employee age jointly influence important work outcomes. Relational demography and career timetable approaches both predict negative effects of mismatches involving employees who are older than their managers. Specifically, employees who are perceived to be older than their manager may be more likely to be in the out-group and, thus, evaluated negatively. Hypothesis 1: Employees who are chronologically or subjectively older than their manager will receive more negative evaluations and less training and development than workers who are similar in age or younger than their manager. Unlike the negative relationships typically shown in research linking employee age to evaluations and development opportunities, research on attitudes generally shows that older workers have more positive attitudes than do younger workers (Rhodes, 1983). More recently, researchers (Maurer, 2001; Salthouse & Maurer, 1996) suggested that older workers often receive negative signals from their managers, which may undermine their positive attitudes. Both relational demography and career timetable theories posit that older employees with younger managers will have more negative attitudes than will older employees with older managers, suggesting that manager age will moderate the generally positive attitudes among older employees because older employee–younger manager dyads defy age norms.
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Hypothesis 2: Manager age (chronological or subjective) will moderate the generally positive association between employee age (chronological or subjective) and work attitudes, such that older employees with younger managers will have less favorable attitudes than will older employees with older managers.
Method Employees of a large multinational firm in the southeastern United States completed surveys measuring attitudes, ratings of job performance, employee developmental experiences, and demographic information. In addition, their managers were asked to complete a survey to assess the employee’s commitment, performance, and developmental experiences and to provide demographic information about themselves.
Sample Participants were 185 managers (158 men, 27 women) and their employees (233 men, 57 women). The average age of the employees was 44.16 years and of the managers was 48.67 years. For managers, 14% were women and 7% were non-White. A wide variety of organizational jobs were represented, and the occupational breakdowns of employees were as follows: 32% managers, 7% professionals, 7% technicians, 5% sales, 6% clerical, 40% skilled craft, and 3% semiskilled operatives and service workers. Although a handful of managers rated more than one employee, the great majority of managers (81%) rated only one employee. To ensure an adequate number of older employees, we stratified the population of employees by age and tenure and randomly sampled employees within each age stratum. The response rate was approximately 73% for the employees. After identifying the employees who would comprise our sample, we sent surveys to their managers (response rate ⫽ 57%).
Procedure The surveys were mailed to participants along with a cover letter, computer answer sheets, and a preaddressed (to Lynn M. Shore) return envelope. The cover letter stressed that all responses would be confidential and that a summary of results would be given to the organization and to participants. Participants were told that the survey was a collaborative effort involving their employer and Lynn M. Shore. Two weeks after the initial administration, managers and employees received a postcard requesting that they return the survey if they had not already done so.
Measures Work attitudes. Three attitude measures from the employee survey used 5-point scales (1 ⫽ strongly disagree, 5 ⫽ strongly agree). They included a three-item overall job satisfaction scale (Seashore, Lawler, Mirvis, & Cammann, 1982), a three-item supervisor satisfaction scale (Seashore et al., 1982), and a nine-item organizational commitment scale (Mowday, Steers, & Porter, 1979). Managers were asked to assess the employee’s affective commitment to the organization (four items; 1 ⫽ disagree completely, 5 ⫽ agree completely; Shore, Barksdale, & Shore, 1995). Performance and potential. Self-ratings of job performance were based on two items that assessed employees’ absolute (1 ⫽ performs consistently below expectations, 5 ⫽ consistently exceeds expectations) and relative (1 ⫽ well below average, 5 ⫽ well above average) performance. Employees rated their career future using the five-item subscale of the Index of Organizational Reactions (Smith, 1976). Anchors for each item are worded differently; however, in all cases, 1 is the least favorable and 5 is the most favorable response anchor. Using seven items, managers were asked to evaluate the employee relative to other people they supervise on performance areas such as
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problem solving and work quality (1 ⫽ well below average, 5 ⫽ well above average). The manager survey also included one question each on promotability and managerial potential (5 ⫽ high potential or likelihood of promotion). Developmental experiences. Employees and managers were asked about the developmental experiences received by the employee from the manager during the last year (a no–yes response format in which no ⫽ 0 and yes ⫽ 1). The items included whether the employee received training to improve job skills, activities to help advance the employee’s career, and feedback on career potential within that organization. One summative scale was created to represent the manager’s assessment and another to represent the employee’s assessment of developmental experiences. Age. Employees provided their own chronological age (ECA) and subjective age (ESA). Subjective age was measured with a four-item scale that asked people to indicate on a 5-point scale (1 ⫽ 16 –25, 2 ⫽ 26 –35, 3 ⫽ 36 – 45, 4 ⫽ 46 –55, 5 ⫽ 56 –75) the age that most closely corresponds to (a) the way they generally feel, (b) the way they look, (c) the age of people whose interests and activities are most like theirs, and (d) the age that they would most like to be. We asked managers to provide their own chronological age (MCA) and subjective age (MSA). As described below, we constructed interaction terms involving ECA (or ESA) and MCA (or MSA).
Analytic Strategy We constructed a series of hierarchical regression models to test the hypotheses. Cross product terms were formed using all possible employee– manager combinations of the age measures. There were four distinct models: In the ECA ⫻ MCA model, employee and manager chronological ages were combined into cross products; in the ECA ⫻ MSA model, employee chronological age was combined with manager-rated subjective age; in ESA ⫻ MCA, employee subjective age was combined with manager chronological age; and in ESA ⫻ MSA, employee and manager subjective ages were combined. In each equation, the employee age measure (chronological or subjective) was entered first, the manager age measure (chronological or subjective) was entered second, and the cross product of the relevant employee age and manager age measures was entered third. To help interpret significant interactions, we present figures depicting the regression of each criterion on employee age as a function of two levels of manager age (Aiken & West, 1991). As recommended by Cohen and Cohen (1983), when plotting interactions involving continuous variables, the two simple regression lines depict the relation between employee age and the criterion at one standard deviation above and one standard deviation below the mean of manager age. Cleveland and Shore (1992) reported significant interactions between the age of the target employee and the ages of coworkers. To minimize the possibility that manager– employee age differences might be confounded with age differences between an employee and his or her coworkers (e.g., an older employee might be older than the manager and older than most coworkers), we reran these analyses entering coworker age as a control variable. Employees answered a single item in which they indicated whether, compared with members of their own work group, they would describe themselves as younger, about the same age, or older (coded as 1, 2, and 3, respectively). We also used gender and race as controls. Analyses with and without these control variables yielded highly similar outcomes and because analyses that include unnecessary control variables can yield biased estimates of regression parameters, we focused on analyses without these controls.
Results Means and standard deviations for and intercorrelations among the age measures and the criterion measures are shown in Table 1. Reliabilities are presented on the diagonal of Table 1.
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532 Table 1 Means, Standard Deviations, and Correlations Variable 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18.
Employee chronological age Employee subjective age Manager chronological age Manager subjective age Job satisfaction Supervisor satisfaction Organizational commitment Manager-rated affective commitment Employee-rated job performance Manager-rated job performance Manager-rated promotability Manager-rated managerial potential Employee-rated career future Employee-rated training & development Manager-rated training & development Employee age relative to work group Employee sex Employee race–ethnicity
M
SD
1
2
3
44.16 2.72 49.70 3.13 4.07 3.64 3.99 3.89 4.11 3.52 2.03 2.15 3.76 0.51 0.90 2.01 1.20 4.70
11.91 0.86 7.45 0.64 0.66 1.03 0.59 0.87 0.61 0.75 1.18 1.10 0.83 0.76 0.99 0.55 0.40 1.03
.85** .24** .13 .18** .01 .14* .11 .07 ⫺.03 ⫺.19** ⫺.11 ⫺.05 ⫺.26** ⫺.24** .39** ⫺.19** .12*
(.89) .24** .14* .16** .04 .13* .16* ⫺.01 ⫺.06 ⫺.23** ⫺.10 ⫺.04 ⫺.28** ⫺.22** .49** ⫺.16** .12*
.76** .11 ⫺.03 .01 .02 ⫺.03 ⫺.08 ⫺.20** ⫺.16* ⫺.06 ⫺.14 ⫺.05 .02 ⫺.11 .02
4
(.79) .10 ⫺.01 .05 .04 ⫺.10 ⫺.10 .26** ⫺.14* .05 ⫺.04 ⫺.06 .04 ⫺.11 .05
5
(.80) .43** .64** .21** .21** .20** .10 .14 .62** .15* ⫺.05 .02 ⫺.03 ⫺.01
6
(.88) .34** .33** .03 .26** .13 .15* .55** .22** .05 ⫺.01 ⫺.07 ⫺.04
7
(.89) .23** .23** .12 .09 .05 .57** .14* ⫺.07 .01 .01 .02
Note. Diagonal elements in parentheses represent reliabilities. Values in bold are test–retest reliabilities; all others are internal consistency reliabilities. * p ⬍ .05. ** p ⬍ .01.
Hierarchical regression analyses are presented in Table 2. The interaction of employee age and manager age accounts for a significant amount of variance in work attitudes, ratings of performance and potential, and developmental experiences. However, the strength of the interaction effect depends, in part, on the specific pairing of chronological and subjective age measures examined. The strongest and most consistent effects are shown for interactions between MCA and ECA (⌬R2 ⫽ .01–.28, M ⫽ .09; nine interactions are significant), followed by interactions between ESA and MCA (⌬R2 ⫽ .00 –.31, M ⫽ .07; seven interactions are significant), interactions between ECA and MSA (⌬R2 ⫽ .00 –.14, M ⫽ .05; eight interactions are significant), and the least consistent effects shown for ESA and MSA (⌬R2 ⫽ .00 –.07, M ⫽ .02; five interactions are significant). Because the patterns are similar across models, we highlight the findings of the model with ECA and MCA, as this model has the strongest, most consistent results.
Performance and Promotability Inspection of Table 2 indicates that interactions between manager age and employee age consistently predict performance and promotability, suggesting support for Hypothesis 1. An examination of Figure 1 shows that for employee-rated performance, younger employees have the highest ratings when their manager is young, and the lowest ratings when their manager is old. Older employees show the opposite pattern, suggesting partial support for Hypothesis 1. Specifically, age differences between employee and manager appear to have a negative effect and not just for older employees. It is important to note that career future shows the same pattern as for employee-rated performance. In contrast, Figure 2 shows that older and younger managers evaluate younger employee performance similarly but that older employees receive lower performance ratings from older managers than from younger managers. This pattern is the opposite of expectations. Finally, manager-rated potential (see Figure 3) and promotability show similar patterns and are consistent with predictions in Hypothesis 1. Specifically, younger managers evaluate younger employees
more highly than they evaluate older employees, whereas older managers rate younger and older employees similarly.
Developmental Experiences Results of the regression analyses indicate that the interactions between manager age and employee age significantly predict both self- and manager-ratings of development. Figure 4 shows the pattern for manager-rated development (employee-rated development is very similar), which is consistent with predictions in Hypothesis 1. That is, older managers treat older and younger employees similarly, but younger managers provide much more development to younger than to older employees.
Work Attitudes As indicated in Table 2, interactions between employee and manager chronological age account for significant variance in measures of two work attitudes, employee-rated job satisfaction and organizational commitment, supporting Hypothesis 2. However, these cross products do not significantly predict employee ratings of supervisor satisfaction or manager ratings of affective commitment. The pattern of the significant interactions for organizational commitment and job satisfaction are both quite similar to the pattern depicted in Figure 1 for employee-rated performance. This pattern suggests that employee satisfaction or commitment is higher when the employee and manager are similar in age (i.e., both younger or older) and lower when the employee and manager have more dissimilarity in age.
Discussion The results of the present study support prior research suggesting the importance of conceptualizing the age construct as reflecting both person (i.e., employee chronological and subjective age) and context variables (manager chronological and subjective age) in the work setting (Cleveland & Shore, 1992; Lawrence, 1988).
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8
(.85) .10 .57** .21** .39** .24** .03 .09 .04 ⫺.11 .16*
9
(.69) .19** .13 .13 .14* .01 ⫺.07 ⫺.04 .06 .06
10
(.90) .43** .60** .25** .09 .08 ⫺.10 ⫺.03 .15*
11
12
(.71) .48** .15* .08 .19** ⫺.21** .02 .07
(.91) .18* .04 .15* ⫺.15* ⫺.15* .07
13
14
(.82) .22** .03 ⫺.02 .01 .02
We found that Employee Age ⫻ Manager Age context interactions were useful for predicting work criteria. As a whole, this pattern of findings suggests the need for research on aging to consider the age of the individual within the age context, defined both by managerial and work group ages. Hypothesis 1 received some mixed support using the two criterion sets: (a) ratings of developmental experiences and (b) ratings of performance, promotability, and career future. Hypothesis 1 was clearly supported by both self-rated and manager-rated development. The fewest development opportunities were reported by both employees and managers when the employee was older and the manager was younger. The pattern of results for manager-rated potential and promotability also were consistent with predictions because older employees with younger managers received the lowest ratings. The pattern of results for manager-rated performance was not consistent with
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.14 ⫺.03 .18* ⫺.08
15
16
17
⫺.17* .01 .04
⫺.11 .10
⫺.21**
18
expectations because older employees received the lowest evaluations from older managers and the highest evaluations from younger managers. Finally, for employee-rated performance and career future, dissimilarity in employee–manager age seemed to produce the lowest ratings and similarity in employee–manager age produced the highest ratings. This pattern of results suggests that managers and employees may view differences in age differently. With the exception of performance, manager ratings conform to the view set forth in the career timetables and relational demography literature (Lawrence, 1987, 1988; Tsui et al., 1995), which predict that employees who are older than their managers will suffer negative consequences. However, employee ratings of career future and performance suggest support consistent exclusively with relational demography, which predicts that all mismatches generally yield more negative results.
Table 2 Regressions ECA
ECA ⫻ MCA
MCA
Variable
⌬R2
b
⌬R2
b
⌬R2
Supervisor satisfaction Job satisfaction Organizational commitment Manager-rated affective commitment Employee-rated job performance Manager-rated job performance Manager-rated promotability Manager-rated managerial potential Employee-rated career future Employee-rated training & development Manager-rated training & development
.00 .03** .02* .01 .01 .00 .04** .01 .01 .10** .08**
⫺.09** ⫺.16** ⫺.12** .03 ⫺.10** .07* ⫺.15** ⫺.13** ⫺.20** ⫺.25** ⫺.21**
.00 .00 .00 .00 .00 .00 .02* .02* .00 .01 .00
⫺.08** ⫺.12** ⫺.10** .02 ⫺.08** .05* ⫺.13** ⫺.12** ⫺.16** ⫺.19** ⫺.15**
.01 .18** .14** .00 .09** .03* .04** .04** .16** .16** .06**
b .002** .003** .002** .000 .002** ⫺.001* .003** .002** .004** .005** .004**
Total R2 .01 .21** .16** .01 .08** .03 .10** .07** .17** .27** .14**
Note. b values represent unstandardized coefficients from full regression model. ECA ⫽ employee chronological age; MCA ⫽ manager chronological age. * p ⬍ .05. ** p ⬍ .01.
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Figure 1.
Employee age and manager age in relation to employee-rated performance.
Figure 2.
Employee age and manager age in relation to manager-rated performance.
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Figure 3.
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Employee age and manager age in relation to manager-rated potential.
What, then, does the evidence overall suggest with regard to Hypothesis 1? Our data suggest support for the relational demography and career timetable prediction that employees who are older than their managers suffer negative consequences when
Figure 4. Employee age and manager age in relation to manager-rated development.
examining data most relevant to the career—promotability, managerial potential, and development. Of particular note is that this pattern is consistently supported when the criterion data is provided by the managers, who can have a strong influence on the careers of their employees. Furthermore, for the promotability, potential, and development criterion data provided by the managers, we also found evidence supporting relational demography’s proposition that similarity leads to positive outcomes. However, this was only the case for younger employees working for younger managers. Older managers treated older and younger employees similarly. For Hypothesis 2, we predicted that manager age would moderate the relationship between employee age and work attitudes. Consistent with expectations, employee age–manager age interactions predicted job satisfaction and organizational commitment, suggesting the moderating role of manager age. However, counter to expectations, neither supervisor satisfaction nor manager-rated affective commitment was predicted by these interactions. Of interest, employee-rated job satisfaction and organizational commitment conformed to the same pattern as did employee-rated performance and career future. This robust pattern, where similarity in employee–manager age for both younger and older employees yielded the highest self-ratings, is quite striking and suggests greater support for relational demography when the criteria are provided by the employee than when the criteria are provided by the manager. In contrast, the pattern of results for the attitudinal data raises questions as to why supervisor satisfaction did not conform to expectations, particularly because the similarity– attraction paradigm (Byrne, 1971), which is often argued to be the basis for demographic similarity effects, would predict greater
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liking of and satisfaction with the manager when employees and managers are similar in age. An alternative explanation for relational demography that better fits the pattern of results in the present study is social identity theory, in which individuals attach value to categories in which they belong (Riordan, 2000). According to Riordan (2000), two basic components underlie an individual’s social identity: (a) self-enhancement (the need for high self-esteem) and (b) self-continuity (the need to maintain the continuity of social identities across time and situations). The self-enhancement associated with increased similarity in age between employee and manager may increase the employee’s selfperceived job performance and career future. Age similarity may also enhance employees’ affective reactions to work as shown by higher job satisfaction and organizational commitment because of the desire of individuals to associate with others who represent key parts of their social identification, such as their age. Our findings are consistent with both Tsui et al.’s (1995) and Ferris et al.’s (1991) argument that relational demography is an important consideration in the exchange relationship that defines the vertical dyad between employee and manager. Furthermore, the findings support the view that relational demography theory needs to consider both directional and nondirectional demographic differences (Perry et al., 1999; Riordan & Shore, 1997). In contrast to the predictions of relational demography, our results do not consistently support the view that similarity in age yields the most positive results. Rather, our pattern of results for manager-rated criteria of promotability, potential, and development clearly support Lawrence’s (1987, 1988) career timetable framework, but chiefly for older employees with younger managers. Being behind time (older than the manager) yields the most negative results for older employees. Each of the criterion sets showed somewhat different patterns of results, suggesting that a single paradigm, such as relational demography or career timetables, may not fully explain the role of manager age as a contextual variable at work. Our results suggest that employees and managers respond differently to their age differences. Except for development, the other self-rated criteria showed that age similarity yielded the highest ratings. For manager-rated criteria, only job performance did not conform to the pattern whereby older employees with younger managers suffered negative consequences. Clearly, both theory and research need to address these discrepancies in employee and managerial perceptions. It is also important to note that the pattern of findings for subjective and chronological age measures was similar but that the chronological age measures were more strongly related to most of the criteria. Although subjective and chronological age were highly intercorrelated (r ⫽ .85 for employees, and r ⫽ .76 for managers), we believe there should be continued use of this measure in age research. Consistent with recommendations by Riordan (2000), the results suggest at least two factors that may determine when subjective age is a useful predictor of important work outcomes: (a) the specific work outcomes measured (e.g., attitudes, retirement, performance ratings) and (b) the specific referent involved (e.g., work group composition, manager, organization composition). Prior research on working adults showed that when the referent is work group age composition, employee subjective age provides additional explanation beyond employee chronological age for criteria such as health and planned retirement (Cleveland et al., 1997) and on-the-job training and mana-
gerial potential (Cleveland & Shore, 1992). These findings, along with ours, suggest that subjective age may be most useful in a work setting when the referent is work group composition rather than managerial age and for explaining criteria that are associated with aging, like health and retirement; however, for most criteria, chronological age is a better predictor than subjective age. Three aspects of these data enhance the potential contributions of our findings. First, there are different patterns of findings depending on the criterion variable. This suggests that response biases associated with survey data are less of a concern in this study. Second, the sample size was adequate and the measures were psychometrically sound. Finally, age was operationalized using both chronological age and subjective age measures. In contrast, even though promotability and managerial potential had acceptable test–retest reliabilities, they were single-item measures. In addition, participants worked in a single organization, suggesting the importance of replication to determine the generalizability of results. Our results suggest that the joint consideration of employee and manager age is a useful predictor of work attitudes and decisions. An important next step in this area would be to consider some organizational variables that might make age disparities more salient. For example, Perry and Finkelstein (1999) suggested that organizational factors, such as structures, values, and technology, set the stage for age discrimination. It is also important to determine whether older workers contribute to the lower levels of career development and opportunities that we found because of factors such as lowered self-efficacy (Maurer, 2001). Future researchers may wish to consider the role these variables play in heightening the salience of age norm violations in manager– employee dyads.
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Received April 6, 2000 Revision received July 17, 2002 Accepted July 17, 2002 䡲
