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Relation of Group Performance to Age

Journal of Applied Psychology 2008, Vol. 93, No. 2, 392– 423 Copyright 2008 by the American Psychological Association 0021-9010/08/$12. 00 DOI: 10. 1037/0021-9010. 93. 2. 392 The Relationship of Age to Ten Dimensions of Job Performance Thomas W. H. Ng The University of Hong Kong Daniel C. Feldman The University of Georgia Previous reviews of the literature on the relationship between age and job performance have largely focused on core task performance but have paid much less attention to other job behaviors that also contribute to productivity.
The current study provides an expanded meta-analysis on the relationship between age and job performance that includes 10 dimensions of job performance: core task performance, creativity, performance in training programs, organizational citizenship behaviors, safety performance, general counterproductive work behaviors, workplace aggression, on-the-job substance use, tardiness, and absenteeism. Results show that although age was largely unrelated to core task performance, creativity, and performance in training programs, it demonstrated stronger relationships with the other 7 performance dimensions.
Results also highlight that the relationships of age with core task performance and with counterproductive work behaviors are curvilinear in nature and that several sample characteristics and data collection characteristics moderate age–performance relationships. The article concludes with a discussion of key research design issues that may further knowledge about the age–performance relationship in the future. Keywords: age, aging, older workers, job performance, meta-analysis

According to the Bureau of Labor Statistics, the median age of the American workforce has been increasing over the last 30 years—35 years old in 1980, 37 years old in 1990, 39 years old in 2000, and 41 years old in 2006. This trend is also evident worldwide. For instance, International Labor Organization (2005) statistics indicate that young adults between the ages of 20 and 24 were the largest segment of the working population in 1980. However, by 1990 the 30 –34 age group was the largest segment of the working population, and today the largest segment of the world’s working population is the age 40 – 44 cohort.
Older workers are becoming an increasingly important concern for organizations for reasons beyond their sheer numbers. The shift to an older workforce has caused many organizations to spend more money on succession planning, pension benefits, health insurance, and medical benefits (Beehr & Bowling, 2002; Paul & Townsend, 1993). In addition, numerous organizations have concerns (and/or stereotypes) that older workers may exhibit lower productivity (Avolio & Waldman, 1994; Greller & Simpson, 1999; Hassell & Perrewe, 1995; Lawrence, 1996).
For instance, compared with younger workers, older workers are stereotyped as being less physically capable, as more likely to have problems getting along with coworkers, as preferring to invest more time in their families than in their jobs (Fung, Lai, & Ng, 2001; Paul & Townsend, 1993), as less technologically savvy, and as less willing to adapt quickly in volatile environments (Isaksson & Johansson, 2000; Riolli-Saltzman & Luthans, 2001). Thomas W. H.
Ng, School of Business and Economics, The University of Hong Kong, Pok Fu Lam, Hong Kong; Daniel C. Feldman, Terry College of Business, The University of Georgia. Correspondence concerning this article should be addressed to Thomas W. H. Ng, School of Business and Economics, The University of Hong Kong, Pok Fu Lam, Hong Kong. E-mail: [email protected] hku. hk 392 Previous research has produced mixed results, however, regarding the precise relationship between age and job performance.
In the three most-cited quantitative reviews of this literature, one found a moderate-sized positive relationship between age and performance (Waldman & Avolio, 1986), one found that age was largely unrelated to performance (McEvoy & Cascio, 1989), and the third found that the age–performance relationship took an inverted-U shape (Sturman, 2003). We believe that one reason for these mixed results is that much of the previous research on the age–performance relationship has focused rather narrowly on the performance of core task activities.
As a result, past research has not closely examined the broad spectrum of behaviors that comprise “job performance” and the multiple ways in which age is related to work effectiveness. Over the past 2 decades, organizational researchers have been examining numerous other job-related behaviors that also legitimately fall under the rubric of job performance. These include the following: creativity, performance in training programs, organizational citizenship behaviors (OCBs), safety performance, counterproductive work behaviors, on-the-job substance use, workplace aggression, tardiness, and absence.
Although most of these job behaviors could not be called core task activities per se (Organ, 1988), they do significantly affect organizational productivity by shaping the organizational cultures and environments in which core task performance takes place (Borman & Motowidlo, 1997). As such, examining a broader and more inclusive set of job performance measures may help clarify the complex relationship between age and performance. Mixed results on the age–performance relationship may also be partially attributable to the differing nature of research samples and data collection characteristics (Lawrence, 1996; S.
R. Rhodes, 1983). For instance, research samples may vary in terms of the types of jobs workers perform, and as such, results may vary depending upon which skills older workers are required to utilize. AGE AND JOB PERFORMANCE 393 Similarly, because the nature of the work environment has changed substantially over the past 30 years, studies on the age–performance relationship conducted in the 1970s may have yielded very different results than studies conducted more recently. In addition, there may be differences in results depending upon whether data were collected cross-sectionally or longitudinally.
For example, the effect of intraindividual aging on performance observed in longitudinal studies may be smaller in magnitude than the effect of broad age group differences observed in cross-sectional studies at any one point in time. Thus, examining the potential moderating effects of sample and data collection characteristics is not only important for research methodology purposes but for theoretical and practical reasons too. It allows us to identify the conditions under which age is likely to have positive, zero, or negative associations with various components of job performance.
In the following section of the article, then, we briefly address some definitional issues, consider the results of previous quantitative reviews of the age–performance relationship, and discuss how the current study extends these previous reviews. Next, we present the results of an extended meta-analysis and provide evidence on the relationships between age and 10 performance dimensions. In the subsequent section, we examine the moderating effects of sample and data collection characteristics and also explore potential curvilinear relationships between age and performance dimensions.
Finally, in the concluding section, we discuss the implications of our findings for future research and the management of older workers. Theoretical Background Definitional Issues Age versus aging. Age is a continuous variable and is used as such in our analyses. When we refer to age differences, we are referring to group-level differences between individuals at one age and individuals at another age. It is important to note here that, similar to previous quantitative reviews in this area of research (McEvoy & Cascio, 1989; Waldman & Avolio, 1986), the goal of the current meta-analysis is not to isolate the effects of aging per se.
That is, we are not directly examining the intraindividual aging process itself and how it relates to job performance. Instead, our goal is to examine the relationships between age and job performance dimensions across different cohorts and research contexts. For instance, is age, on average, related to job performance after taking into consideration different sample characteristics and research conditions? Is the relationship between age and core task performance stronger or weaker than the relationship between age and citizenship behavior? These are the kinds of questions we attempt to address here.
Older workers. Who is considered an “older worker” has been debated in the literature for quite some time. In the retirement literature, older workers are often identified by having reached retirement age or by years until reaching retirement age (Beehr, 1986; Doeringer, 1990). Moreover, as Cleveland and Shore (1992) have noted, age can be defined in terms of an employee’s chronological age, the employee’s subjective age (the individual’s self-perception of age), the employee’s social age (others’ perceptions of the employee’s age), and the employee’s relative age (the egree to which the individual is older than others in the work group). Thus, the meaning of “old” depends, to some extent, on the demographic profiles of an organization or occupation (Shore, Cleveland, & Goldberg, 2003). Another definition that is frequently used in this literature is the legal definition of “older worker” provided by the U. S. Age Discrimination in Employment Act of 1967 (ADEA). This act prohibits discrimination against workers who are 40 years old or above.
Although our data analyses use continuous measures of age wherever possible, in our discussion of “older workers” in the text, we generally rely on the ADEA definition for a variety of reasons. First, previous meta-analyses of age in the applied psychology literature have also utilized 40 years old as the cutoff age (Thornton & Dumke, 2005). Second, unlike authors in disciplines like gerontology and sociology (e. g. , Lindenberger & Baltes, 1997) who use high cutoff ages to make fine distinctions between the “young elderly” and “old elderly” (e. g. under and over age 85), scholars in the organizational sciences are particularly attuned to the fact that the age range in the active workforce is typically 16 – 65 years old (International Labor Organization, 2005). Thus, at least in terms of making a dichotomous split in the workforce, 40 years old appears to be an acceptable cutoff to distinguish between younger and older workers. Third, careers researchers have observed that age 40 typically marks the end of career establishment stage and the start of career maintenance stage (Super, 1980).
As such, the chronological age of 40 often represents a major transition in career stages as well. Finally, defining older workers as 40 or above has some practical benefits because it directly aligns research findings regarding older workers to management implications regarding ADEA compliance in hiring, termination, performance evaluation, and promotion decisions. Undoubtedly over time, the definition of “older worker” will change. For example, the amendment of ADEA (by the Older Workers Benefit Protection Act of 1990 and the Civil Rights Act of 1991) to prohibit mandatory retirement ages may ultimately push back the age t which people retire (although labor statistics have not indicated any increases in retirement age as of yet). Even more likely, gains in life expectancy will change our conceptions of who is “middle-aged” and who is “old. ” For our current purposes, though, the definition of older workers as being age 40 or older is consistent with both previous research and legal definitions and has the benefit of being “objectively” determined and verifiable across researchers and contexts. Previous Reviews of the Age–Performance Relationship
Three major quantitative reviews of this literature have been published in the last 25 years. Waldman and Avolio’s (1986) review is the earliest meta-analysis in this area. The authors identified 13 empirical studies containing 40 samples. They found that age was positively related to productivity measures of job performance (. 27). On the other hand, age was weakly but negatively related to supervisor ratings of job performance ( . 14). Furthermore, Waldman and Avolio found that the relationship between age and supervisor-rated job performance was stronger for nonprofessionals ( . 8) than for professionals ( . 05). Peer ratings of job performance were related to age at . 10. In sum, Waldman and Avolio (1986) illustrated that the sign of the relationship between age and task performance varies depend- 394 NG AND FELDMAN ing upon which measure of performance is being utilized, who does the performance ratings, and what kinds of jobs workers hold. To the extent that there is a drawback to this meta-analysis, it is the lack of availability of a large number of studies at that time.
Meta-analyses that include too few cumulative studies may contain second-order sampling errors (Hunter & Schmidt, 1990). Addressing this drawback, McEvoy and Cascio (1989) identified 65 empirical studies (containing 96 samples) conducted on the relationship between age and performance. Across these 96 samples, the authors found that the mean correlation between age and job performance was quite low (. 06) and that the confidence intervals contained the value of zero. Unlike Waldman and Avolio (1986), McEvoy and Cascio found that type of performance rating (productivity vs. upervisory rating) and job type (professional vs. nonprofessional) did not moderate the relationship between age and performance. The different results observed in these two meta-analyses may be attributable to the different sets of studies the researchers considered, as McEvoy and Cascio located a wider range of empirical studies than Waldman and Avolio had included. Sturman’s (2003) meta-analysis hypothesized that the relationships of performance with three age-related variables (chronological age, job experience, and organizational tenure) were in the form of an inverted-U shape.
With respect to the age–performance relationship, Sturman found that the corrected effect size across 115 empirical studies was . 03. Although this effect size is very small, he did find that this relationship was indeed an inverted-U shape. That is, age was positively related to job performance when age was low but was negatively related to job performance when age was high ( 49 years old). Below, we highlight the main evidence supporting these three different perspectives on the age–performance relationship.
Whereas earlier research on older workers largely focused on the negative relationship between age and task performance (S. R. Rhodes, 1983), more recently researchers have been examining the ways in which age can facilitate task performance or, at the minimum, not adversely affect it (Ebner, Freund, & Baltes, 2006; Kanfer & Ackerman, 2004). As a result, we have a much richer picture now of how age is positively or negatively related to core task performance but not as complete a picture of how age relates to a broad spectrum of other performance measures. unctions, that is, monitoring and controlling attention, suppressing irrelevant information, utilizing analytical reasoning, and updating information in working memory. Older individuals were found to perform much more poorly on this test battery than their younger counterparts. In general, M. G. Rhodes’s results suggest that older individuals may have more difficulties with complex tasks that require a high level of executive functioning. Indeed, there is also cumulative empirical evidence to indicate that older individuals do not do as well as younger individuals when performing multiple complex tasks simultaneously (Verhaeghen, Steitz,
Sliwinski, & Cerella, 2003). Another area in which age appears to have negative association with performance is memory capacity. Previous meta-analyses have demonstrated a significant negative relationship between age and memory. For instance, older adults were found to have poorer recognition and recall memory than younger adults (La Voie & Light, 1994; Spencer & Raz, 1995; Verhaeghen, Marcoen, & Goosens, 1993). Moreover, as a result of these memory differences, employees are less likely to trust the memories of older coworkers.
In an experimental study of attribution theory, for example, Erber and Danker (1995) found that participants expected memory-related performance problems of older workers to continue longer than those of younger workers and were less likely to recommend training when “problem” employees were older. Above and beyond these differences in aptitudes and short-term memory, researchers have also found that older individuals may have less intense work motivation than their younger colleagues (S. R. Rhodes, 1983). For instance, Ebner et al. 2006) found that younger individuals are more likely to frame their goal orientations in terms of striving for gains (e. g. , I want to improve my fitness), whereas older individuals are more likely to frame their goal orientation around maintaining the status quo or preventing loss (e. g. , I do not want my fitness to deteriorate). These changes in motivation may also be linked to lower productivity on the job. Evidence Supporting Positive or Neutral Relationships of Age With Performance The above literature paints a rather pessimistic view of the relationship of age with job performance.
Nonetheless, a strong case can also be made that older workers may exhibit at least the same, if not greater, job performance as their younger colleagues (Greller & Simpson, 1999). The rationale most frequently cited to support this case is that older workers substitute lengthy job experience and greater general expertise for speed of information acquisition and information recall. This wisdom and expertise, accumulated over the course of a career, may be sufficient to compensate for productivity losses due to any changes in cognitive and physical abilities (Baltes, Staudinger, Maercker, & Smith, 1995).
Kanfer and Ackerman (2004) have emphasized that older age is often accompanied by increases in “crystallized” intelligence (experiential knowledge). Indeed, experimental evidence provides robust support for Kanfer and Ackerman’s assertion. For instance, Allen, Lien, Murphy, Sanders, and McCann (2002) found that older participants could multitask as effectively as younger participants, albeit at a slower pace. Artistico, Cervone, and Pezzuti (2003) found that older adults’ performance in solving problems exceeded that of younger adults when the problems were familiar
Evidence Supporting Negative Relationships of Age With Performance Numerous studies have found support for the proposition that age negatively relates to cognitive functioning. For instance, in a large sample of 20,000 American workers across multiple occupational groups, Avolio and Waldman (1994) found that age was negatively related to several types of aptitudes, including general intelligence, verbal aptitude, numerical aptitude, spatial aptitude, form perception, clerical perception, motor coordination, finger dexterity, and manual dexterity.
Thus, for jobs in which general cognitive abilities, visual-perceptual abilities, and psychomotor abilities are important components for superior job performance, Avolio and Waldman have suggested that age is negatively related to job performance. Furthermore, M. G. Rhodes (2004) found that there was a strong and significant difference between older and younger adults in performance on a test battery measuring individuals’ executive AGE AND JOB PERFORMANCE 395 and representative of tasks frequently encountered.
ColoniaWillner (1998) found that the best performing older employees had higher levels of tacit knowledge than their younger employees. Studies using different research designs have also found that professional expertise, developed over years of practice and experience, can attenuate potential negative relationships between age and performance dimensions (Hess & Auman, 2001; Lindenberger, Kliegl, & Baltes, 1992; Morrow, Leirer, Altieri, & Fitzsimmons, 1994; Thornton & Dumke, 2005; Wilson, Li, Bienias, & Bennett, 2006).
Taken together, the research described above suggests that, after a slower pace of initial learning, older workers can reach the same performance levels as those of their younger colleagues and can multitask effectively. Moreover, when older workers are asked to solve familiar problems, higher self-efficacy beliefs are activated, and these beliefs can accelerate performance. Thus, although fluid intelligence, short-term working memory, and cognitive speed may decrease with age, deductive reasoning and professional expertise are likely to increase (Masunaga & Horn, 2001).
Moreover, increased wisdom and judgment gained over years of service may increase older workers’ effectiveness in contextual performance activities as well. Creativity Creativity is the extent to which employees generate new and useful ideas for improving organizational productivity (Anderson, De Dreu, & Nijstad, 2004). For many jobs, creativity might be considered as a separate element of job performance, particularly when creativity relates to organizational adaptability and flexibility.
For instance, some researchers have emphasized the importance of employees’ creativity as a critical component of an organization’s ability to adapt to rapidly changing business environments (A. De Jonge & De Ruyter, 2004; Johnson, 2001). Consistent with this view of creativity as a key element of job effectiveness, a major study of performance evaluation systems found that some organizations evaluated employees on their innovativeness as well as on their core task performance (Welbourne, Johnson, & Erez, 1998). Performance in Training Programs
Older workers are often stereotyped as being somewhat resistant to change and slow in learning new material. For this reason, researchers have examined older workers’ performance in training programs as an element of job effectiveness (Martocchio, 1994). As Tracey, Tannenbaum, and Michael (1995) have suggested, organizations typically provide training to employees on the basis of the assumption that the short-run costs of the design and execution of training can be recouped through employees’ increased productivity in the long run.
However, if employees do not perform well in training programs, it is highly unlikely that they will transfer that new knowledge to real work settings. Furthermore, when employees fail to learn in training programs, the expenses associated with training are wasted as well (Winfred, Bennett, Edens, & Bell, 2003). Expanding the Domain of the Performance Construct Previous reviews of the age–performance relationship have primarily focused on the performance of core tasks.
According to Borman and Motowidlo (1997), core task performance is concerned with “the effectiveness with which job incumbents perform activities that contribute to the organization’s technical core” (p. 99). In addition to core task performance, however, we also examine nine other performance dimensions that comprise the two broad categories of job behaviors identified by Hunt (1996) as independent of the core job role, namely, citizenship behaviors and minimum performance behaviors.
Citizenship behaviors are those extra behaviors engaged in by employees, over and above their core task requirements, that actively promote and strengthen the organization’s effectiveness (Organ, 1988). In this study, the first category is represented by such dimensions as employee creativity, performance in training programs, citizenship behaviors geared to different beneficiaries, and safety performance. In contrast, minimum performance behaviors are those that employees have to engage in (like attending work) or refrain from engaging in (like theft) to keep their jobs (Hunt, 1996).
This second category is represented by such dimensions as general counterproductive work behaviors, workplace aggression, on-the-job substance use, tardiness, and absenteeism. Conceptually, there are certainly other behavioral dimensions that could be included under these two categories. For example, working long hours and demonstrating effective leadership are examples of additional citizenship behaviors that might be considered, whereas refraining from sexual harassment and manipulating stock prices are additional examples of minimum performance variables that could be considered.
Empirically, however, a metaanalysis is constrained by the number of previous studies conducted on a specific relationship, and here we have included the nine dimensions identified above as the ones on which the most empirical studies are available. We discuss each of these additional nine dimensions of job performance in more detail below. OCBs Researchers have documented the importance of OCB for organizational functioning over the last 2 decades (LePine, Erez, & Johnson, 2002; Organ, 1988).
OCBs (sometimes called prosocial behaviors or extrarole behaviors) are not job-specific but rather support the broader organizational environment in which core performance takes place (Motowidlo & Van Scotter, 1994; Organ, 1988). Examples of OCB are compliance with organizational norms, not complaining about trivial matters, and helping coworkers. Employees’ aggregated OCBs frequently benefit group, unit, and organizational productivity (Podsakoff, MacKenzie, Paine, & Bachrach, 2000). Safety Performance
Safety performance is the extent to which employees comply with safety rules and demonstrate safe behaviors in the workplace (Parker, Axtell, & Turner, 2001). This performance dimension is particularly important in industries that require employee contact with hazardous materials, operation of heavy machinery, and extensive highway driving (Clarke & Robertson, 2005). Poor safety performance can have two distinct negative consequences for firms’ effectiveness. At the individual level, inattention to safety behaviors contributes to employee injuries; these injuries result in lower worker productivity and time lost from work.
At the orga- 396 NG AND FELDMAN nizational level, poor safety practices contribute to potentially costly litigation. These claims create substantial financial burdens for firms in the event of serious employee accidents, dismemberments, and death (Hofmann & Morgeson, 1999). Both directly and indirectly, then, employee safety behaviors are an important component of job performance. General Counterproductive Work Behaviors Whereas research investigating OCB concentrates on what workers can do to romote smooth organizational functioning, research on workplace deviance examines how the lack of counterproductive work behaviors is essential to maintaining smooth organizational functioning (Neuman & Baron, 1998). Counterproductive work behaviors are intentional employee acts that harm organizations’ legitimate business interests (Bennett & Robinson, 2000). Examples of counterproductive work behaviors include working on personal matters instead of assigned tasks, neglecting supervisors’ instructions, stealing property, starting or repeating rumors and gossip, and using unprofessional language.
It is easy to see the multiple ways in which these counterproductive work behaviors can reduce both individual and group performance. Moreover, Dalal (2005) found that employees who frequently engaged in counterproductive work behaviors were also less likely to demonstrate OCBs. son, 2000; Martocchio, 1989). Researchers have documented numerous negative effects of employee absence on organizational productivity (Harrison & Martocchio, 1998). When employees are absent from work, the completion of their own work is slowed down.
Coworkers are often called upon to cover for absent employees, thereby distracting them from completing their own assignments. In cases in which task interdependence among a group of workers is high, the whole team’s progress may be affected when an employee is chronically absent or absent for extended periods of time. As with tardiness, frequent absences can also adversely affect organizational productivity by creating an “absence culture” in which more and more employees consider being absent acceptable (rather than counterproductive) behavior (Johns & Xie, 1998).
Summary. Before we can draw strong conclusions about the relationship of age to job performance, then, it is important to consider citizenship behaviors and minimum performance behaviors in addition to core task performance. In light of the above literature review, we include 10 dimensions of job performance in the current meta-analysis: core task performance, creativity, performance in training programs, OCB, safety performance, general counterproductive work behaviors, workplace aggression, on-thejob substance use, tardiness, and absenteeism.
From this point on, we use the phrase “job performance” to represent these 10 dimensions collectively. Specific Counterproductive Work Behaviors In addition to general counterproductive work behaviors, four specific forms of counterproductive work behavior have been discussed separately and extensively in the literature. We also examine these four specific counterproductive work behaviors— workplace aggression, on-the-job substance use, tardiness, and absenteeism—in the present meta-analysis. Workplace aggression.
Workplace aggression consists of employees’ efforts to harm others with whom they work, harm the reputation of their current employers, or harm former colleagues and previous employers (Lapierre, Spector, & Leck, 2005). Acts of workplace aggression can cause bodily harm to employees, pose physical danger for customers, create public relations crises, and harm the business reputation of the firm as a whole. On-the-job substance use. On-the-job substance use involves drinking alcohol or taking illegal drugs at work or during work time (Frone, 2003).
Researchers have found that on-the-job substance use hampers individuals’ decision-making abilities; increases the frequency of dysfunctional job behaviors; and puts coworkers, supervisors, and customers at increased risk of injury (Lehman & Simpson, 1992). Tardiness. Tardiness is lateness for work (Blau, 1994; Koslowsky, Sagie, Krausz, & Singer, 1997). Employee tardiness is likely to create both direct financial costs to organizations (e. g. , decreased time on productive activities) and indirect financial costs (e. g. , time lost by coworkers waiting for late colleagues. . Left unchecked, numerous cases of tardiness can lead to a “culture of tardiness” (Koslowsky et al. , 1997) in which employees come to see being late as an acceptable behavior rather than as a deviant one. Absenteeism. Skipping work has also been conceptualized as a form of employee counterproductive behavior (Bennett & Robin- Moderator Relationships Another way in which the present study contributes to the literature is by investigating how different sample and design characteristics moderate the relationship between age and job performance.
Many of these characteristics have been discussed in the literature as variables that can affect age–performance relationships (Lawrence, 1996; S. R. Rhodes, 1983; Shore et al. , 2003; Sturman, 2003) and as potential explanations for inconsistent research findings in the area. Sample Characteristics In this study, we examine the potential moderating effects of the average age, age dispersion, job tenure, and organizational tenure of research samples.
Testing for average sample age as a moderator essentially examines whether the form of the relationship between age and performance is linear or curvilinear (see Sturman, 2003). Testing the moderating role of age dispersion associated with the sample (operationalized as the standard deviation of age in the sample) assesses whether the age–performance relationship varies across samples with different degrees of age homogeneity. Testing for average job tenure and average organizational tenure examines whether the age–performance relationship varies across samples with different (average) tenures.
In general, these four sample characteristics might influence authors’ definitions

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