Journal of Organizational Behavior
J. Organiz. Behav. 32, 264–290 (2011)
Published online 14 December 2010 in Wiley Online Library
(wileyonlinelibrary.com) DOI: 10.1002/job.698
Age diversity, age discrimination climate
and performance consequences—a cross
organizational study
FLORIAN KUNZE*, STEPHAN A. BOEHM AND HEIKE BRUCH
Institute for Leadership and Human Resource Management, University of St. Gallen, St. Gallen,
Switzerland
Summary
This paper deals with the emergence of perceived age discrimination climate on the company
level and its performance consequences. In this new approach to the field of diversity research,
we investigated (a) the effect of organizational-level age diversity on collective perceptions of
age discrimination climate that (b) in turn should influence the collective affective commitment of employees, which is (c) an important trigger for overall company performance. In a
large-scale study that included 128 companies, a total of 8,651 employees provided data on
their perceptions of age discrimination and affective commitment on the company level.
Information on firm-level performance was collected from key informants. We tested the
proposed model using structural equation modeling (SEM) procedures and, overall, found
support for all hypothesized relationships. The findings demonstrated that age diversity seems
to be related to the emergence of an age discrimination climate in companies, which negatively
impacts overall firm performance through the mediation of affective commitment. These
results make valuable contributions to the diversity and discrimination literature by establishing perceived age discrimination on the company level as a decisive mediator in the age
diversity/performance link. The results also suggest important practical implications for the
effective management of an increasingly age diverse workforce. Copyright # 2010 John
Wiley & Sons, Ltd.
Introduction
Vivid terms like the ‘‘demographic time bomb’’ (Tempest, Barnatt, & Coupland, 2002, p. 487) or the
impending ‘‘age quake’’ (Tempest et al., p. 489) describe one of the key challenges for most developed
countries today: Simultaneously shrinking and aging populations resulting from low birth rates and
increased longevity. These factors also impact a country’s workforce as a lack of skilled junior
employees, combined with the potential rise of the legal retirement age, forces companies to retain
older, more experienced personnel, (e.g., Dychtwald, Erickson, & Morison, 2004; Tempest et al.).
Already today, just over half of the United States’ 147 million-member workforce is 40 years old or
older and, until 2016, the number of workers age 25–54 will rise only slightly (2.4 per cent), while the
* Correspondence to: Florian Kunze, Institute for Leadership and Human Resource Management, University of St. Gallen,
Dufourstrasse 40a, CH-9000 St. Gallen, Switzerland. E-mail: florian.kunze@unisg.ch
Copyright # 2010 John Wiley & Sons, Ltd.
Received 30 November 2008
Revised 20 January 2010
Accepted 26 February 2010
AGE DIVERSITY, AGE DISCRIMINATION CLIMATE
265
workers age 55–64 are expected to climb by 36.5 per cent (U.S. Bureau of Labor Statistics, 2008). The
same is true for Germany where, from 2020 on, the employees aged 55–64 will become the largest age
demographic in the workforce (Destatis, 2006).
As a consequence of these demographics, a growing age diversity has become part of many
organizations. As we know from research on other demographic diversity categories, such as gender or
ethnicity, diversity rarely has an unambiguous effect but is a ‘‘double-edged sword’’ (Horwitz &
Horwitz, 2007, p. 988; for an overview, see Jackson, Joshi, Erhardt, 2003; Van Knippenberg &
Schippers, 2007). In this regard, age diversity is not different: Some studies have reported positive
effects on performance (e.g., Kilduff, Angelmar, & Mehra, 2000), while others have found either no
significant effects (e.g., Bunderson & Sutcliffe, 2002; Simons, Pelled, & Smith, 1999) or negative
effects (e.g., Ely, 2004; Leonard, Levine, & Joshi, 2004; Timmerman, 2000; West, Patterson, Dawson,
& Nickel, 1999; Zenger & Lawrence, 1989).
The reason for these mixed results may be traced back to researchers’ neglect of possible mediators
and moderators in the relationship between age diversity and outcomes in the studies on organizational
demography (e.g., Lawrence, 1997).
The construct of perceived age discrimination climate
The construct of perceived age discrimination climate may play a decisive role in this regard. Butler
(1969) was among the first to define ageism as ‘‘a process of systematic stereotyping and discrimination
against people because they are old’’ (p. 22). Today, the concept of ageism (or age bias) tends to be
conceptualized more broadly, referring to potential prejudices and subsequent discrimination against
any age group, including bias and unfairness toward employees on the grounds of being too young, as
well as too old (Palmore, 1999; Duncan, Loretto, & White, 2000; Snape & Redman, 2003).
Perceived and actual age discrimination are major issues in the corporate world: In fiscal year 2009,
the U.S. Equal Employment Opportunity Commission (2010) received over 22,700 charges of age
discrimination, and many major lawsuits related to age discrimination have been filed and won with
verdicts up to US$11 million (James & Wooten, 2006). Germany, where our sample originates, has had
legislation prohibiting discrimination in the workplace since 2006. This new law costs companies in
Germany Euro 1.75 billion through more costly recruiting procedures, changed structures and
processes, and lawsuits in the first year after it came into effect (Hoffjan & Bramann, 2007).
In order to analyze and structure the different forms of age bias, we employed the meta-framework of
Fiske (2004). Finkelstein and Farrell (2007) built upon Fiske’s ‘‘tripartite view of bias,’’ adapting it for
the special case of age bias. They differentiated among three dimensions of age bias by classifying
‘‘stereotyping’’ as the cognitive component, ‘‘prejudice’’ as the affective component, and
‘‘discrimination’’ as the behavioral component. With our focus on discrimination, we target the
behavioral component of age bias. However, our conceptualization of age discrimination differs from
that in prior work (e.g., Finkelstein and Farrell; Finkelstein, Burke, & Raju, 1995) with regard to two
aspects of the issue: First, we understand age discrimination as unfair, age-related treatment against any
age group, not only against older members of the group. Second, we conceptualize age discrimination
as an organizational-level variable that refers to the aggregate member perceptions about the
organization’ age related treatment of different age groups.
In a first step, such employee perceptions may develop on basis of certain interpersonal processes
and events between employees and their colleagues or supervisors. For example, an employee might
feel treated unfairly by his or her supervisor on the basis of his or her age. Likewise it seems possible
that employees feel certain forms of discrimination with regard to organization wide systems or
processes, e.g., with regard to the firm’s human resource (HR) system. Employees who experience such
Copyright # 2010 John Wiley & Sons, Ltd.
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F. KUNZE ET AL.
age-related forms of discrimination by their colleagues, their supervisors, or by organizational systems
might form perceptions that age discriminatory behavior is present in their firm. In a second step, such
individual perceptions of age-discriminatory behavior may be amplified through interaction and
exchange with others to form an organizational level phenomenon. As such, age discrimination climate
is an emergent construct that reflects group members’ shared perceptions (Kozlowski & Klein, 2000) of
the fairness or unfairness of organizational actions, procedures, and behavior towards different age
groups (e.g., regarding job assignments, promotions, performance evaluations, or leadership behavior).
We are particularly interested in members’ perceptions of the age discrimination climate because
perceived discriminatory practices are as much a problem for organizations as actual discrimination
since ‘‘employees’ beliefs, whether or not they are consistent with reality, affect their behaviors’’
(Ensher, Grant-Vallone, & Donaldson, 2001, p. 53; see also Mor Barak, Cherin, & Berkman, 1998), as
well as their decisions to file equal-opportunity lawsuits and related litigation (Sanchez & Brock,
1996).
The role of perceived age discrimination climate in the diversity/performance link
Antecedents and outcomes of perceived discrimination climate in companies have received only little
attention in the extant literature so far. One exception is the discussion of the relational and
organizational demography framework (e.g., Riordan, Schaffer, & Stewart, 2005; Tsui & Gutek, 1999),
which predicts that higher demographic similarity in the workplace leads to greater perceptions of
support and fairness, while heightened levels of dissimilarity or diversity may lead to perceptions of
discriminatory treatment (e.g., Avery, McKay, & Wilson, 2008), building on theoretical reasoning from
social identity theory (Tajfel & Turner, 1986), self-categorization theory (Turner, 1987), and the
similarity-attraction-paradigm (Byrne, 1971). Going beyond those theories, we integrate other
literature streams from the diversity and ageism literature, such as career timetables violations
(Lawrence, 1984) and prototype matching (Perry, 1994), to explain how organizational-level age-group
composition might impact perceived age discrimination climate. To our knowledge, our study is among
the first to explore such a compositional age-diversity model at the organizational level of analysis.
We also focus on potential outcomes of a climate of perceived age discrimination. While there is
strong evidence suggesting that gender- and sexuality-based discrimination negatively affects
individuals, groups, and whole organizations (Corning & Krengal, 2002; Gutek, Cohen, & Tsui, 1996;
Mays & Cochran, 2001), the research on the effects of age discrimination is less well developed
(Redman & Snape, 2006). We strive to contribute to this direction of research by building upon work
from scholars (e.g., Hassell & Perrewe, 1993; Redman & Snape, 2006; Snape & Redman, 2003) who
have described the impact of age discrimination on employees’ affective states, including self-esteem,
job satisfaction, job involvement, and organizational citizenship behavior. We analyze how an
increasing age discrimination climate leads to decreased levels of collective affective commitment
which, in turn, negatively affects company performance.
In sum, the present study is an attempt to test an integrative model of the age diversity/performance
link, with a focus on the mediating role of age discrimination climate. In doing so, we make valuable
contributions to two streams of literature. First, our research brings diversity research to a new level by
investigating age diversity as an organizational-level antecedent. In addition, we also introduce
perceived age discrimination climate as a new mediator in the age diversity/performance relationship to
shed more light on the ‘‘black box of organizational demography’’ (Lawrence, 1997). Second, with
regard to the field of ageism, we want to establish perceived age discrimination as an organizationallevel construct and demonstrate the counterintuitive positive link between age diversity and perceived
age discrimination climate.
Copyright # 2010 John Wiley & Sons, Ltd.
J. Organiz. Behav. 32, 264–290 (2011)
DOI: 10.1002/job
AGE DIVERSITY, AGE DISCRIMINATION CLIMATE
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Theory and Hypotheses Development
Age diversity and perceived age discrimination climate
While an increase in age diversity has become an organizational reality in most corporations, its
potential effects on age discrimination, commitment, and performance are not yet fully understood.
Several scholars have proposed that an increase in age diversity at the workplace may lead to lower
levels of discrimination, arguing with a familiarization to older workers in an increasingly aging
workforce (Chiu, Chan, Snape, & Redman, 2001; Finkelstein et al., 1995; Hassell & Perrewe, 1995).
Furthermore, for other diversity categories (e.g., gender, ethnicity) some scholars have tended to reason
that increasing diversity should lead to a more positive diversity climate as employees notice a growing
workplace heterogeneity and infer that the organization values diversity (e.g., Kossek & Zonia, 1993;
Kossek, Markel, & McHugh, 2003).
While these arguments may be accurate, we propose a different (i.e., positive) relationship between
increasing levels of age diversity and increasing levels of perceived age discrimination climate. First,
increasing age diversity in companies tends to differ from increasing gender diversity because, in most
cases, age diversity is not actively fostered or managed by the firms (e.g., through affirmative action
programs) but is a direct result of the demographic change in western economies (e.g., Dychtwald et al.,
2004; Tempest et al., 2002), and thus less accompanied by active diversity-management programs.
Second, different theoretical arguments imply a positive relationship between increasing age diversity
and increasing levels of perceived age discrimination climate in the workplace. All of these arguments
assume a negative effect of growing age diversity on members’ social integration, i.e., a weakened
psychological linkage toward striving for common goals (Harrison, Price, & Bell, 1998). In the
following section, we analyze those rationales in more detail, drawing on arguments from four
theoretical perspectives: The similarity-attraction paradigm, the social identity and self-categorization
theory, research on career timetables, and prototype matching.
As a first theoretical argument the similarity-attraction paradigm (Byrne, 1971; Riordan & Shore,
1997) proposes that individuals prefer to affiliate with persons whom they perceive to be similar to
themselves based on demographic characteristics, including age. (Avery et al., 2008; McPherson,
Smith-Lovin, & Cook, 2001; Tsui, Egan, & O’Reilly, 1992). Several authors have argued that such
personal ties and attraction foster cooperation in teams and workgroups (e.g., Chattopadhyay, 1999,
Hobman, Bordia, & Gallois, 2004, Pelled, Xin, & Weiss, 2001). Lawrence (1988, p. 313) referred to
such effects when she explained that employees of similar age ‘‘share comparable experiences and
therefore develop like attitudes and beliefs’’ that, in turn, foster communication and cooperation. These
comparable experiences stem from both historically generated similarities (e.g., graduating and
starting a job during the boom of the ‘‘New Economy’’) and from similar stages in private and
family lives that same-aged colleagues tend to reach simultaneously (e.g., being newly married,
having young children, being near to retirement, etc.) (Lawrence, 1980). We believe that such
processes of homophily are not limited to teams and workgroups but can also take place at the
organizational level. For example, similar aged peers in different teams or departments might prefer to
go to lunch together or pursue common social activities inside and outside the workplace, rather
than with younger or older colleagues from their own units. In sum, the dissociation between younger
and older employees might be stronger than that between employees of different units or departments.
Employees that are either younger or older than such a cohesive age group might infer that the
reason for such behavior (i.e., less intensive contact with colleagues of different ages, not being invited
to joint activities, etc.) is their age, and generate perceptions of age discriminatory behavior at the
workplace.
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As a second theoretical argument, the idea of the development of age-based subgroups within an
organization is also supported by social identity (Tajfel & Turner, 1986) and self-categorization theory
(Turner, 1987) which suggest that individuals tend to classify themselves and others into certain groups
on the basis of dimensions that are personally relevant for them, such as the demographic categories of
gender, race, or age. As a consequence, individuals tend to favor members of their own group (ingroup) at the expense of other groups (out-groups) (Turner, 1987; Tajfel & Turner, 1986), against which
they tend to discriminate. In the organizational context, a large number of such group memberships
may exist simultaneously.
While age has the potential to become a relevant category for classification and formation of
subgroups (e.g., young employees, middle-aged employees, and older employees) (Avery et al., 2008;
Ensher et al., 2001; Finkelstein et al., 1995, Kearney & Gebert, 2009), whether the subgroups actually
develop seems to depend on the organizational context. Growing heterogeneity could play a key role in
this process since an increase in age diversity can heighten the salience (or importance) of age as a
category for classification and identification. As in a group of men, gender is unlikely to be a salient
category, age can only become a relevant criterion for distinction when there is some age diversity in
the organization. In other words, when an organization that had been largely homogenous in terms of
age distribution (e.g., consisting mainly mid-aged and older employees) gradually becomes more ageheterogeneous (e.g., by hiring more younger graduates for management positions), the importance
attached to membership in one age group of employees or another should increase.
The third theoretical argument related to an increase in age discrimination climate in companies due
to raising levels of age diversity is derived from the concept of career timetables (Lawrence, 1984,
1988) which assumes that clear age norms develop within an organization concerning which
hierarchical level an employee should reach by a given age. While those employees who are ‘‘on
schedule’’ (who are promoted as quickly as their same-aged peers) and those ahead of schedule (who
are promoted more quickly than their peers) face few problems in the way of discrimination, employees
behind schedule often struggle with lower work satisfaction (Lawrence, 1984) and tend to receive lower
performance ratings and development opportunities (Cleveland & Shore, 1992; Lawrence, 1988; Tsui,
Porter, & Egan, 2002).
Demographic changes and growing age diversity within organizations is likely to produce situations
in which such age norms are violated more often and more employees fall behind schedule. For
example, a rising number of older employees who stay in the organization until the legal retirement age
will have to deal with significantly younger supervisors and might perceive that as a violation of the
classic career timetable as more experienced employees have to report to organizational newcomers
(Shore & Goldberg, 2005). Older employees might also feel behind schedule compared to their young
supervisors and perceive certain forms of age discrimination such as lower performance and
promotability ratings (Shore, Cleveland, & Goldberg, 2003; Tsui et al., 2002).
Also for younger employees, age norms might be violated more often, if for instance a lack of
middle-aged managers within an organization suddenly improves promotion expectations for young
managers (Lawrence, 1988). After the best of these young managers are promoted to fill the gaps,
promotion chances for younger managers drop again to normal levels. Until employee perceptions readjust, younger workers who were not promoted might feel a certain disillusion and a violation of age
norms because they cannot develop their careers as quickly as their peers, and a negative attitude
toward middle-aged and older managers who are ‘‘in the way’’ might develop.
Finally, a similar, yet distinct, line of argumentation can be derived from the concept of prototype
matching (Perry, 1994; Perry & Finkelstein, 1999), which suggests that an employee’s age is often
compared to the age of a ‘‘prototypical’’ job holder, where certain kinds of jobs are considered jobs for
younger workers (with traits and skills like being energetic and being able to adapt to change quickly),
while other jobs are more suitable for older employees or are age-neutral because of their reliance on
Copyright # 2010 John Wiley & Sons, Ltd.
J. Organiz. Behav. 32, 264–290 (2011)
DOI: 10.1002/job
AGE DIVERSITY, AGE DISCRIMINATION CLIMATE
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steadiness and corporate knowledge (Cleveland & Landy, 1987; Perry, 1994; Perry & Bourhis, 1998). As in
the case of career timetables, we suggest that an organization-wide increase in age diversity will lead to an
increase in perceived misfits between job holders and job-age prototypes, where older employees work in
‘‘young-type jobs’’ with apparently high demands regarding pro-activity and stress-handling such as
distribution and customer service, where they might be exposed to different forms of perceived age
discrimination from both younger colleagues and supervisors (‘‘Is he/she really able to keep up with us in
this kind of job?’’). On the other hand, younger employees might have to work in more ‘‘old-type jobs’’ that
call for a lot of experience, such as higher management functions. Just like older employees in young-type
jobs, younger employees in old-type jobs might also face certain forms of perceived age discrimination
from peers, supervisors, and their employees (‘‘Isn’t he/she a bit young for this kind of job?’’).
In sum, we presented theoretical and empirical evidence stemming from different streams of
literature such as the similarity-attraction paradigm, social identity, and self-categorization theory, as
well as theories on career timetables and prototype matching. Taken together, we assert that it is
theoretically plausible to build a model in which higher levels of age diversity on an organizational
level trigger perceptions of organization-wide age discrimination climate.
Thus, we propose:
H1: Higher levels of age diversity will be positively related to respondents’ perceptions of age
discrimination climate within companies.
Perceived age discrimination climate and collective affective commitment
One key attitudinal state of employees is their affective commitment toward the organization, which
was defined by Meyer and Allen (1991) as the ‘‘the employee’s emotional attachment to, identification
with, and involvement in the organization’’ (p. 67). Affective commitment has been shown to be of high
importance for organizations because it increases employees’ acceptance of organizational goals, their
willingness to exert effort on behalf of the organization, and their desire to remain with the organization
(Meyer & Allen, 1997; Mowday, Porter, & Steers, 1982).
Several authors have shown that, in addition to individual commitment, collective forms of
commitment may evolve within an organization (Kirkman & Rosen, 1999; van der Vegt & Bunderson,
2005). Following prior research by González-Romá, Peiró, and Tordera (2002), we also argue with
collective perceptions of affective commitment and aggregate employees’ commitment scores at the
organizational level of analysis.
While a potentially negative impact of perceived age discrimination climate on members’ collective
commitment makes intuitive sense, various theoretical approaches also support such a relationship. First,
social exchange theory suggests that members’ perceptions of a supportive and fair exchange relationship
between the organization and themselves is a necessary precondition for the development and preservation
of high levels of affective commitment (Meyer & Allen, 1997; Shore & Wayne, 1993). Consequently,
‘‘commitment develops as the result of the experiences that satisfy employees’ needs’’ (Meyer & Allen,
1991, p. 70). A perception of age discrimination climate is a clear violation of such an equitable give-andtake relationship, which is why it should negatively affect employees’ emotional attachment to the
organization, as well as their willingness to contribute. Hassell and Perrewe (1993) showed such a decline
in attachment to the organization for members who perceived age discrimination in the workplace.
Second, employees’ attitudes toward their employers are dependent on their perceptions of whether
their own opportunities and treatment by the organization are equal to those of other groups of
employees (Gutek et al., 1996). Snape and Redman (2003) argued in this regard that individuals who
feel that they have suffered from unfair, age-related treatment are likely to develop a ‘‘sense of being
under-valued by the organization and its members’’ (p. 80). In turn, such members can be expected to
Copyright # 2010 John Wiley & Sons, Ltd.
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show decreasing levels of motivation to act on behalf of the organization. Tougas and Veilleux (1989)
referred to such processes as feelings of ‘‘collective relative deprivation’’ where ‘‘individuals feel upset
about the position of their group’’ within the larger organization (p. 122). This may lead to an emotional
withdraw from an organization when employees feel that members of their own group are treated in an
unfair and discriminative manner, as shown for gender subgroups (Gutek et al.). It is likely that such
feelings of collective deprivation are also transferable to the context of perceived age discrimination,
where the group of younger or older employees perceive age discrimination against their own age
group and, consequently, exhibit a collective drop in their level of affective commitment. On the basis
of this evidence, we suggest:
H2a: Higher levels of perceived age discrimination climate will be negatively related to
respondents’ collective affective commitment towards companies.
H2b: The relationship between age diversity and respondents’ collective affective commitment is
mediated through perceived age discrimination climate.
Collective affective commitment and company performance
Decreasing levels of collective commitment might become a serious problem for companies since
research has proposed a direct link between organizational commitment and organizational
performance (Meyer, Paunonen, Gellatly, Goffin, & Jackson, 1989; Meyer, Becker, & Vandenberghe,
2004; Meyer, Becker, & Van Dick, 2006). The theoretical rationale behind this relationship is the
understanding of commitment as being ‘‘a force that binds an individual to a course of action that is of
relevance to a particular target‘‘ (Meyer & Herscovitch, 2001, p. 301). Especially for employees
showing high levels of affective commitment, a distinct willingness to contribute to organizational
goals and, hence, to organizational performance has been assumed (Meyer, Paunonen et al.; Meyer,
Becker, & Vandenberghe; Meyer, Becker, & Van Dick). Compared to individuals showing continuance
or normative commitment (Meyer & Allen, 1991), such employees stay within an organization because
they want to (Meyer, Becker & Van Dick). Giving their services wholeheartedly to the organization and
performing well above the minimum required for retention, employees with high levels of affective
commitment should become a driver of organizational productivity and performance (Ostroff, 1992).
The relationship between affective commitment and performance has also been investigated
empirically. However, most research has focused on the effect of affective commitment on job
performance, rather than on its effect on organizational performance (e.g., Meyer, Stanley,
Herscovitch, & Topolnytsky, 2002).
On the organizational level of analysis, research on the affective commitment/performance link is
scarce. An exception is the study of Ostroff (1992), which found a significant positive correlation
between collective attitudinal commitment and organizational performance in 298 schools in terms of
performance criteria such as academic achievement, student behavior, and administrative performance.
We believe that such an effect is transferable to our research question. Thus, we propose:
H3a: Higher levels of collective affective commitment will be positively related to organizational
performance.
H3b: The relationship between perceived age discrimination and organizational performance is
mediated through collective affective commitment.
Figure 1 gives an overview of all hypothesized relationships.
Copyright # 2010 John Wiley & Sons, Ltd.
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Figure 1. Conceptual model
Method Section
Sample
Data for the present investigation were collected between March and June 2008 as part of a larger study
in cooperation with an agency in Germany that specializes in benchmarking small to medium-sized
enterprises. Initially, the agency solicited participation from 164 organizations based on the criteria that
the organizations (a) were located in Germany and (b) did not exceed 5000 employees. Each
organization was promised a detailed technical benchmarking report in return for their participation. Of
the 164 organizations initially contacted, 36 did not participate or failed to provide sufficient data,
resulting in an organizational level response rate of 81 per cent (n ¼ 128). Participating organizations
represented companies from a variety of industries, including services (53 per cent), manufacturing
(28 per cent), trade (13 per cent), and finance and insurance (6 per cent), and ranged in size from 10 to
3333 employees (median ¼ 156). Eliminating organizations with 1000 or more employees (n ¼ 9) and
those with 20 or fewer employees (n ¼ 2) did not change the pattern of results, so all sample
organizations were used in hypotheses testing.
In order to improve equivalence of data collection, standardized procedures were employed across
all organizations. Data were collected in three steps. First, general information on the participating
organizations (organization size, industry affiliation, and so on) was gauged through a key informant
survey completed by the organizations’ HR executives or other members of their top management
teams. Answers to this key informant survey were required in order to confirm organizations’
participation in the study.
Second, employee survey data were collected to obtain information on the focal study variables.
Participating organizations sent a standardized email invitation to all employees through their HR
departments (if applicable) or through a top management team member’s email address. The email
described the study’s purpose and provided a link to a web-based survey hosted by an independent third
Copyright # 2010 John Wiley & Sons, Ltd.
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F. KUNZE ET AL.
party. A paper version of the questionnaire was provided to employees who had no web access. Based
on an algorithm programmed in the survey website, respondents were randomly directed to one of four
versions of the survey, thereby implementing a split-sample design (Rousseau, 1985; for similar
approaches, see Dickson, Resick, & Hanges, 2006; Erdogan, Liden, & Kraimer, 2006). To alleviate
concerns about common-source bias (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003), age
discrimination and affective commitment were measured in two different versions of the employee
surveys. All survey versions were translated to German by professional translators following a doubleblind back-translation procedure to ensure semantic equivalence with the original English items
(Schaffer & Riordan, 2003). Respondents were assured full anonymity.
In total, 18 269 employees chose to participate in the survey. The average within-organization
response rate was 65 per cent (standard deviation ¼ 23 per cent). Our study used only the responses
from those employees who completed the first and second version of the survey (n ¼ 8651), because
these parts included our study variables. The other two versions included items that were used for
other research projects. The algorithm effectively distributed participating employees among the
four versions of the survey, yielding 4,574 respondents for the survey including affective commitment
and 4,077 responses for the survey including age discrimination. Individual respondents were
more heavily represented by males (54 per cent) than females (39 per cent), although 8 per cent
chose not to indicate their gender. Respondents belonged to different age groups with a majority
in the middle age group of 31–51 (60 per cent), followed by 27 per cent in the 16–30 age group and
13 per cent in the over-50 group. Average tenure rate at the companies was eight years. Participants
came from all major divisions and hierarchical levels of their organizations, with 2 per cent in top
management, 11 per cent in middle management, 10 per cent first-line supervisors, and 70 per cent
employees without leadership responsibility. Seven per cent provided no answer about their
employment level.
To account for a potential non-response bias we compared the age and gender demographics of
our sample with data from the working population we sampled, as provided by the HR representatives.
We discovered no substantial difference in the composition. Nevertheless, we additionally reran our
analysis excluding all companies with response rates 0.95 (e.g., Hu & Bentler, 1998). Additionally we also report the
Root Mean Square Error of Approximation (RMSEA) as common practice in many SEM papers.
However, this index should be interpreted with caution, since it tends to over reject models with sample
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F. KUNZE ET AL.
Table 1. Means and standard deviation for the perceived age discrimination climate and affective commitment
measures
Item
Perceived Age Discrimination Climate
1
Age-discriminatory behavior regarding job
assignments exists in our company
2
Age-discriminatory behavior regarding
opportunities for individual promotion
exists in our company
3
Age-discriminatory behavior regarding
performance evaluation exists in our company
4
Age-discriminatory behavior regarding
opportunities for personal and professional
development of employees exists in our company
5
Age-discriminatory behavior in the daily
leadership of the seniors exists in our company
Cronbachs a
Affective Commitment
1
Working at this company has a great deal of
personal meaning to me
2
I feel a strong sense of belonging to this company
3
I would be happy to work at this company until I retire
4
I think that I could easily become as attached to
another organization as I am to this one (R)
Cronbachs a
Item M
Item SD
2.09
0.62
2.24
0.76
2.17
0.72
2.24
0.72
2.02
0.63
5.66
0.45
5.41
4.88
4.01
0.57
0.59
0.59
0.98
0.94
Note: N ¼ 128.
size below 200 (Chen, Curra, Bollen, Kirby, & Paxton, 2008; Sharma et al., 2005; Hu & Bentler, 1999)
and also depends on the number of variables in the model (Kenny & McCoach, 2003). Thus, we
decided to set the cutoff value for a still acceptable model at 0.5.
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Table 5. Mediation analysis via bootstrapping
Age Diversity ! Age Discrimination
Climate ! Affective Commitment
Age Discrimination Climate ! Affective
Commitment ! Performance
Indirect
effect
Standard
error
95% Confidence
intervals
Significance
0.25
0.07
0.36 – 0.15
0.002
0.14
0.09
0.32 – 0.03
0.048
Note: Standardized estimates are shown. 1000 bootstraps samples were used. Two-tailed significance.
t ¼ 1.65, p < 0.08). The overall model fit remained virtually unchanged (see Table 4). The two paths of
hypothesis 1 between age diversity and age discrimination climate (b ¼ 0.35, t ¼ 4.18, p < 0.001), as well
as the path of hypothesis 2 between age discrimination climate and affective commitment (b ¼ 0.73,
t ¼ 8.27, p < 0.001), remained significant. These results indicate a mediation of perceived age
discrimination climate in the relationship between age diversity and collective affective commitment.
In a further step, we applied bootstrapping procedures, as proposed by Cheung and Lau (2008). In
this analysis, the product terms of the direct path from the independent variable to the mediator and the
direct path from the mediator to the dependent variable are examined with bootstrapping methods to
achieve intervals for the mediation effects. As Cheung and Lau recommended, we used 1000 bootstrap
samples to generate the results. Table 5 illustrates the results that further confirmed the proposed
mediation. The indirect effect has the expected negative sign and is significant on a 1 per cent level.
Thus, the effect of age diversity on collective commitment was mediated by perceived age
discrimination climate in the companies.
Hypothesis 3, which stated that collective commitment would be positively related to overall
company performance, was supported (b ¼ 0.21, t ¼ 2.35, p < 0.02). Applying the same proceeding as
described above, we also tested for a mediating effect on overall performance of age discrimination
climate through collective commitment. Adding to the model a direct path between age discrimination
climate and performance did not improve the overall model fit, as illustrated by the ‘‘Mediation model
3’’ in Table 4. The x2 dropped only slightly and all the fit measures remained virtually unchanged (see
Table 4). The direct path between perceived age discrimination climate and performance suggests no 5
per cent significant effect between the two variables (b ¼ 0.13, t ¼ 1.49, p < 0.14), while the two main
effects remained significant. A bootstrapping analysis strengthened these outcomes. As Table 5 shows,
the indirect effect was negative and significant (ß ¼ 0.14, p < 0.05). These results predict that
collective commitment mediates the relationship between perceived age discrimination climate and
company performance.
We further investigated two alternatives models. The first (model 4) assumed a direct linkage
between age diversity and company performance with all mediation paths set to zero. The second
(model 5) assumes a direct relation between perceived age discrimination climate and performance
excluding the mediation by affective commitment. As the results in Table 4 show both models had a
significantly worse fit to our data compared to the baseline model 1. That further strengthened
indication that we may have discovered a good fitting model to the data.
Discussion
The purpose of this study was to explore the link between age diversity and company performance by
shedding light on several potential mediators of this relationship. In a first step, age diversity on the
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company level was examined for its influence on perceived age discrimination climate and for whether
it indirectly relates to collective affective commitment via this mediator. Second, perceived age
discrimination climate was assumed to have a negative effect on collective affective commitment
within companies, which in turn should be positively linked to company performance. Therefore, we
hypothesized a negative indirect effect of perceived age discrimination climate via collective
commitment on the overall company performance.
In general we found support for all our hypotheses. In line with our hypotheses, age diversity was
related to higher levels of perceived age discrimination climate in companies and indirectly also
negatively influenced collective affective commitment of employees. Furthermore, perceived age
discrimination climate showed the hypothesized negative link to collective affective commitment. Last,
our analysis confirmed the mediated negative relationship of perceived age discrimination climate on
overall company performance.
We believe that these results contribute to the literature by corroborating and extending prior findings
in several ways. Concerning the age diversity literature, we were able to make a contribution regarding
mechanisms influencing the age diversity/performance link by establishing perceived age
discrimination climate on the company level as a mediator for the relationship between increasing
diversity in terms of age and collective commitment of employees, which is positively related to overall
company achievements. By doing so, we added to the stream of research on possible mediators and
moderators that has emerged since Lawrence (1997) originated the definition of the ‘‘black box of
organizational demography.’’ As one of the first studies in the diversity literature to do so, our study also
investigated processes that may occur as a result of increased age diversity on the company level. Since
our results show clear indications for a meaningful effect of age diversity on the company level, rather
than only on the team level, this new level of analysis for diversity research, proposed by Van
Knippenberg and Schippers (2007), appears to be a valuable road to follow for future investigation in
the area. Future studies may also incorporate age diversity in teams and departments through a
multilevel analysis and thereby showing that age diversity on the company level has an impact on the
company performance over and above the lower level influences.
Our findings also contribute to the developing literature on ageism and age discrimination. First, with
perceived age discrimination climate we describe an organizational level variable which we conceptualize
as the aggregate member perceptions about the organizations’ age related treatment of different age
groups. Second, our results are a first attempt to establish a positive link between age diversity on the
company level and perceived age discrimination climate. We relied on processes of similarity-attraction
(Byrne, 1971), social identity (Tajfel & Turner, 1986) and self-categorization (Turner, 1987), as well as on
violation of career timetables (Lawrence, 1984), and prototype matching (Perry, 1994) to theoretically
explain this rather counterintuitive relationship. Overall, increasing age diversity seems to undermine
social integration (Harrison et al., 1998) within companies and thus triggers higher levels of perceived age
discrimination climate. Future studies may expand our results by integrating these mechanisms directly in
empirical models, and thereby test our theoretical reasoning for the first hypothesis. Promising routes to
follow might be to integrate variables like cohesion (Seashore, 1954) or age group identification (Garstka,
Schmitt, Branscombe, & Hummert, 2004) on the organizational level as mediators in future models.
Likewise, the extent of perceived age timetable violations or misfits between job holders and job-age
prototypes should be tried to operationalize in further studies to empirically inspect our complex
theoretical arguments. Integrating those variables might also help to fully understand the emergence of
perceived age discrimination climate and thereby investigate whether this organizational level construct
originates more from individual and leadership interactions or organizational rules and procedures set by
the company’s HR-department or top management.
Moreover, we built on social exchange theory (Shore & Wayne, 1993) and applied earlier findings on
the relationship between certain work experiences and members’ commitment (Meyer & Allen, 1991)
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to the context of age discrimination as one relevant violation of social exchange processes. Finally, we
partly replicated Ostroff’s (1992) study and substantiated her findings on the effect of collective-level
affective commitment on organizational performance.
Our control variables allow us to argue against several alternative explications for the relationships
we observed. Since integrating company size in our analysis did not change the pattern of the results,
our findings indicate that the appearance of perceived age discrimination climate on the company level
is not affected by company size and, thus, that perceived discriminatory behavior triggered by the
different processes mentioned above may occur, no matter how big the company is. Second, including
the median age of the employees did not influence the observed relationships substantially, which
indicates that the suggestion by Finkelstein et al. (1995) concerning the lower salience of age in
environments with older personnel is not true for our dataset. Age diversity on the company level seems
to play a decisive role in the appearance of an age discrimination climate, independent of the median
age of the employees.
Practical implications
There are two important implications of our research for company managers. First, they must be aware
that, with an increase in the age diversity of their workforce, higher levels of perceived age discrimination
climate in their companies may occur. This relationship might surprise both line managers and HR
professionals as it partly contradicts popular belief. Second, and perhaps even more important, our results
indicate that perceived age discrimination climate is potentially related to performance. In line with
previous research (Goldman, Gutek, Stein, & Lewis, 2006), we found clear indications that organizations
may experience poor performance when employees perceive discriminatory treatment. Thus, age
discrimination is not only an issue that should be avoided from a normative and ethical point of view, but it
might also have business consequences if it is not adequately addressed.
To address these issues, companies should regularly assess the age composition of their employees in
order to be more aware of the potential occurrence of perceived age discrimination climate. In this respect,
an audit that includes an aging profile analysis and projection should be applied (Jonker & Ziekemeier,
2005). Second, if considerable age diversity is present, assessment tools such as employee opinion surveys,
focus groups, exit interviews, and analysis of patterns of employees’ grievances should be deployed in
order to increase awareness of perceptions of age discrimination (Ensher et al., 2001).
If these analyses indicate serious levels of perceived age discrimination climate on the company level,
several potential measures can be established to lower the perception of age discriminatory behavior in the
company. For example, sensitizing the whole organization to the issues of the aging workforce seems to
be a key requirement for keeping age discrimination on the company level low. As several authors have
proposed (Armstrong-Stassen and Templer, 2005; Elliott, 1995; Rynes & Rosen, 1995) age awareness
trainings for executives should be held to promote a positive view about the potential of different age
groups in the company and to emphasize the relationship of an age-discriminatory corporate culture to
lowered performance levels. Diversity trainings should also educate participants about procedural (e.g.,
process fairness) and interactional justice rules (e.g., fairness in offering information about the decisionmaking process and fairness toward affected persons) (Greenberg & Colquitt, 2005) in order to achieve a
lower level of perceived discrimination for all employees (Avery et al.). Ensher et al. (2001) proposed
organization-wide change efforts with a business-driven imperative that should be justifiable in light of our
results, to avoid perceived discrimination. Companies should also show senior leadership’s commitment to
anti-age-discriminatory behavior and make their age-related HR practices transparent to all employees
(Avery et al.). In sum, companies with high levels of age diversity should aim at pro-diverse work climates
(McKay & Avery, 2005).
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Limitations and future research directions
In spite of several methodological strengths (e.g., independent data sources for all focal study
variables), the current study has several limitations that restrict the interpretation and generalization of
our findings. First, the data for this study were collected at only one point in time, and participants
included in the sample participated voluntarily, rather than being randomly assigned to the research.
Therefore, no final conclusion about causality can be drawn. Future studies might overcome these
weaknesses by applying longitudinal and quasi-experimental research designs for the study of
antecedents and outcomes of age discrimination climate in companies (Shadish, Cook, & Campbell,
2002). That is especially the case for the relation between collective commitment and organizational
performance that could also be in the reverse direction. Longitudinal analysis may also enable a test of
the competing hypothesis that individuating information through inter-age contact and the presence of
stereotype-inconsistent information may diminish age discriminatory behavior over time (Cuddy &
Fiske, 2002; Erber, Etheart, & Szuchman, 1992, Hummert, 1999).
Second, although the study used a relatively large sample of German companies, the generalizability
of its findings is limited because the data came from only one cultural environment, Germany. As the
research by Chiu et al. (2001) indicated, there is some evidence for different discriminatory attitudes in
different cultural backgrounds. Hofstede (2001) argued that the German national culture is
characterized by relatively high levels of individualism and masculinity, by relatively low levels of
power distance, and by medium levels of uncertainty avoidance and long-term orientation, any which
characterizations may influence the level and form of age discrimination in companies. Therefore,
future studies could possibly aim at a replication of our results using different cultural backgrounds. In
a similar vein, we caution readers that our sample consisted of small and medium-size organizations
with no more than 5000 employees. Future researchers could obtain study samples that include larger
organizations in order to further generalize the present findings.
Third, the low response rate within organizations may be source of potential bias for our results.
However, our average within-organization response rate of 65 per cent compares favorably to those
reported in prior research (e.g., Griffith, 2006; Lincoln & Kalleberg, 1996). We conducted several post
hoc analyses to investigate the potential influence of such a sampling bias, and those analyses revealed
that the pattern of our results remained unchanged when (a) the response rate per organization was
integrated as a control variable in the model and (b) companies with response rate below 30 per cent
(n ¼ 9) were excluded. The results from this additional analysis indicate a low probability of a biasing
effect.
Finally, the firm-level performance outcomes were obtained from a single source, a key
organizational informant, suggesting concerns related to reliability and accuracy, as well as causal
reciprocity. In the literature, the reliability of key informant ratings is much discussed (e.g., Wright
et al., 2001) and should be treated with caution. Future research may thus benefit from replicating the
present study with objective performance outcomes.
Beyond these limitations, our study suggests several directions for future research. Scholars could, for
instance, look in more detail at the antecedent side of the evolution of an age discrimination climate in
companies. Another stream of future research may be to consider organizational factors, such as
structures, cultures, values, and technology (Perry & Finkelstein, 1999), as potential sources of age
discrimination on the organizational level, which might contribute to a more comprehensive
understanding of the evolution of an age discrimination climate in companies. Research that links
perceived age discrimination climate on the organizational level directly to leadership behaviors and HRpractices in companies may also be worthwhile. On the group level, for example, there is recent evidence
that transformational leadership (TFL) is a potential moderator for the relationship between diversity and
group performance (Kearney & Gebert, 2009). Replicating this effect on the company level with TFL
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company climate as a boundary condition for decreased age discrimination might be interesting.
Furthermore, although mostly on a descriptive level, current research has emerged about age specific HRpractices (e.g., age-specific training, incentives, career paths, health management, and recruiting) that
may be a source of competitive advantage in an era of demographic change (e.g., Armstrong-Stassen and
Templer, 2005; Loretto & White, 2006, Streb, Voelpel, & Leibold, 2008). It may be particularly valuable
to investigate whether HR-practices that are adjusted to the specific needs of different age groups reduce
the level of perceived age discrimination climate on the company level. Finally, a diversity climate (e.g.,
Mor Barak et al., 1998, Pugh, Dietz, Brief, & Wiley, 2008) may be a boundary condition that favors or
impedes social integration among different age groups in companies and may thus be incorporated in
future studies.
We hope that this study contributes to a better understanding of the emergence of perceived age
discrimination climate and the performance consequences thereof on the organizational level, and that
it provides a solid foundation for future research on these issues and for practical efforts to address
demographic change in companies.
Author biographies
Florian Kunze is a research associate at the University of St. Gallen, Switzerland. His current research
interests include consequences of the demographic change for companies, within-group processes, and
dynamics in work teams and organizations, discrimination and stereotyping due to demographic
characteristics, and leadership research.
Stephan A. Boehm is a senior lecturer and director of the Center for Disability and Integration at the
University of St. Gallen, Switzerland. His research interests include diversity management with a focus
on the integration of disabled employees, the management of the demographic change, as well as group
and organizational level processes of categorization, stereotyping, and discrimination.
Heike Bruch is a professor of leadership and director of the Institute for Leadership and Human
Resource Management at the University of St. Gallen, Switzerland. Her research interests include
organizational energy, leaders’action, emotions in organizations, as well as team and organization
processes triggered by diversity.
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