An Innovative Work Behavior-Enhancing Employability Model Moderated by Age
Jol Stoffers & Beatrice Van der Heijden
Jol M.M. Stoffers
[email protected]
Faculty of Management & Law, Zuyd University of Applied Sciences, Heerlen-SittardMaastricht, the Netherlands
Beatrice I.J.M. Van der Heijden
[email protected]
Institute for Management Research, Radboud University Nijmegen, Nijmegen, the Netherlands
Open Universiteit in the Netherlands, Heerlen, the Netherlands
University of Twente, Enschede, the Netherlands
An Innovative Work Behavior-Enhancing Employability Model Moderated by Age.
Abstract
Purpose - This study empirically validates an innovative work behavior-enhancing model of
employability in Small and Medium-sized Enterprises (SMEs), and examines possible
moderating effects of age.
Design/methodology/approach - Data were collected from 487 pairs of employees and their
immediate supervisors who worked in 151 SMEs. Structural Equation Modeling (SEM) was
used to investigate the predictive validity of employability on innovative work behavior using a
multi-source approach. The moderating effect of employee age on the relationship between, on
the one hand, self- and supervisor ratings of employability, and on the other hand, innovative
work behavior was tested using multi-group SEM.
Findings - Results suggested that self-rated employability correlates positively with supervisorrated innovative work behavior, and that supervisor-rated employability correlates positively
with self-rated innovative work behavior. Age appeared to have a weak influence on the
relationship between employability and innovative work behavior, more specifically, in case of a
higher age the relationship was stronger.
Research limitations/implications - The cross-sectional design is a limitation of this study.
Another limitation relates to the generalizability of the study findings outside the context in
which the research was undertaken. The relational meaning of employee age might be different
in other cultures.
Practical Implications - Supervisors appear to play an essential role in providing an agefriendly working life for employees. Moreover, as SMEs often do not employ professionals to
manage human resources, supervisors themselves have to carry the responsibility to encourage
aging employees to develop themselves enhancing innovative work behavior.
Originality/value - This study is the first to investigate the predictive validity of employability
on innovative work behavior, and the effects of age on this relationship.
Social implications - Enhancing employee innovative work behavior in SMEs will increase the
chances for economic development, herewith contributing to a more stable society.
Keywords - Employability, Innovative Work Behavior, Age, Small and Medium-sized
Enterprises
Paper type - Research paper
Introduction
Successful innovation is crucial in economic development (Porter, 1998), and it is generally
acknowledged as a key factor in the competitiveness of nations and firms (Galia and Legros,
2004), and, through this, contributes to a stable society (Kuznets, 1955). According to West and
Farr (1989), innovative work behavior is “the intentional creation, introduction and application
of new ideas within a work role, group or organization, in order to promote role performance, the
group, or the organization” (Janssen, 2000, p. 288). More concrete, innovative work behavior is
associated with the three stages involved in the innovation process: the generation, promotion,
and realization of ideas (Janssen, 2000). Innovation depends on the knowledge, skills, and
expertise of individual employees (Youndt et al., 1996; Verworn and Hipp, 2009), and ideas
generated from previous work experience enhance innovation (Rank et al., 2004). Innovation is
not only important in the light of employees’ current work processes, but also in regard to the
future when employees should acquire occupational expertise from adjacent or new work areas
(Van der Heijden, 2002) in order to stay employable in the long run. Employability can be
defined as “the continuously fulfilling, acquiring or creating of work through the optimal use of
competences” (Van der Heijde and Van der Heijden, 2006, p. 453).
Concrete, investing in employability (conceptualized as an individual, competency-based
approach) (Van der Heijde and Van der Heijden, 2006; Van der Heijden et al., 2009) enhances
innovative work behavior (Stoffers et al., under review). Otherwise stated, highly employable
workers are able to adapt to changes in internal and external labour markets (Fugate et al., 2004).
It is only since the late 1990s that employability and its consequences have been studied
empirically, mainly due to a lack of psychometrically sound operationalizations of the concept
(see Van der Heijde and Van der Heijden, 2006 for an elaborate review). Although several
studies already reported relationships between employability and positive work outcomes (De
Cuyper et al., 2011; De Vos et al., 2011), moderation tests of age - a significant sociodemographic characteristic in contemporary business and society - on these relationships are rare
(see Van der Heijden et al., 2009, for an exception in this regard). Therefore, we thoroughly
investigated age effects in an innovative work behavior-enhancing employability model, with the
purpose of elucidating the complexity of the relationship between employability and innovative
work behavior.
Employee Age and Employability
Van der Heijde and Van der Heijden’s (2006) conceptualization of employability has been
operationalized into five dimensions combining domain-specific occupational expertise expertise
(a) (knowledge and skills, including meta-cognitive ones, and social recognition by important
key figures (Van der Heijden, 2000) with four more generic competences: (b) anticipation and
optimization; (c) personal flexibility; (d) corporate sense; and (e) balance.
Through maturation, older employees experience, to a greater or lesser extent, reductions
in their capabilities (European Agency for Safety and Health at Work, 2007). However, the
impact of these alterations for workers’ employability depends on their specific occupation
(Billett, 2011). According to Žnidaršič (2012), it is not the age of older employees that
determines their employability, but the age of the specific knowledge they possess. That is to
say, complex mental capacities and expertise in a certain field increase with aging (Baltes and
Smith, 1990; Ericsson, 1999). This knowledge base occasionally compensates for softening of
capabilities, and strategic qualities of experienced employees’ knowledge are often effective
(Billett, 2011). Hence, employee age and employability relate contradictory, herewith stressing
the need for further investigation.
Employee Age and Innovative Work Behavior
Aging and innovation also relate contradictory (Nonaka et al., 2006). The aging and maturation
of knowledge and experience, resulting in wisdom or intelligence, enhances innovative behavior
(Glynn, 1996; Nonaka et al., 2006). Leonard (1998) defined this as core capabilities, or
competitive advantages that are constructed and that cannot be replicated without considerable
effort, and that are related to organizational innovation (Leonard and Sensiper, 1998). However,
aging and out-dated knowledge can also reduce innovation, and Leonard (1998) referred to these
as core rigidities, conservative thinking, and old mental models.
Waldman and Avolio (1986) suggested that work performance increases with age since
complex mental capacities develop across the life-span (Baltes and Smith, 1990; Schaie, 1994),
making older employees more innovative and productive because they are more independent and
experienced (Opinion Leader Research, 2004). According to Ericsson (1999), greater experience
and expertise (wisdom) grow naturally, implying that the generation of new ideas increases
during employees’ aging and throughout their work lives. In a similar vein, Martin et al. (2007)
found that age relates positively to individual innovation.
Verworn and Hipp (2009) reported that German companies with a high proportion of
older employees are as innovative as similar firms. Similarly, Janssen (2000) found that neither
self- nor supervisor-assessed innovative work behavior were age-dependent. Contradictory
results found in the literature urge us to further investigate the influence of age on innovation
(Verworn and Hipp, 2009). The focus of this study is to investigate these relationships in SMEs
since there is a considerable lack of empirical research regarding Human Resource Management
(HRM) practices in these organizations (Hornsby and Kuratko, 2003).
Multi-Source Ratings
Assessing performance is complicated due to multiple relational and social components between
assessors and assessees (Ferris et al., 2008). Using a multi-rater (i.e., multi-source) approach to
assess occupational competencies improves the reliability of these assessments, which in turn
reduces error associated with single-source assessments, and adds incremental validity to the
appraisal of individual performance (Blickle et al., 2011; Brett and Atwater, 2001). Van der
Heijden and Bakker (2011) argued that due to frequent disagreements between supervisors and
employees regarding workers’ employability, self-assessments and supervisor assessments
should be compared and discrepancies should be carefully discussed.
Previous research concerning occupational expertise and employability demonstrated that
workers rate themselves higher than supervisors do (Van der Heijden, 2000; Van der Heijde &
Van der Heijden, 2006), which is in line with research on leniency effects in performance
appraisal (Fox et al., 1994). People are inclined to present a better image of themselves in
comparison to others (Atwater and Yammarino, 1997). According to Korsgaard et al. (2004),
self-enhancement is one of the most common reasons for self-other rating disagreements.
Based on earlier found support for the convergent and discriminant validity of the
employability construct across the two rater sources, i.e. employee and supervisor (see Van der
Heijden, 2000; Van der Heijde and Van der Heijden, 2006), and across age groups (see Van der
Heijden et al., 2009), we could assume that significant differences are not caused by
psychometric problems regarding the measurement instrument. Rather, self-ratings may reflect a
reliable, but somewhat more differentiated self-image, whereas supervisor ratings, within and
across sub-scales, may be relatively more similar because of the halo effect, implying that the
scores for items are more accommodated to each other. That is to say, the ratings made by
supervisors are more colored by the ratings for other items and also by the ratings for other
dimensions of the attribute that are to be rated.
The halo effect has been documented extensively in person perception research (Palmer
and Loveland, 2008). Moreover, since the work of middle and higher-level employees is largely
autonomous, the effect caused by under-sampling selective information for the supervisor (i.e.,
rater) may contribute to a bias, such as age-related stereotyping (Loretto and White, 2006).
Hypotheses
To conclude, innovative work behavior (Janssen, 2000) depends on the knowledge, skills, and
expertise of employees (Adams et al., 2006; Globe et al., 1973), the latter all being so-called
competence-based antecedents. That is, by investing in workers’ employability, innovative work
behavior is assumed to be nurtured. Specifically, previous research already indicated that two of
the five dimensions of employability (see the operationalization above) predict each stage of
innovative work behavior (Stoffers et al., under review). A multi-rater approach (self-ratings
versus supervisor ratings) was used to better understand the influence of rater source in the
association between employability and innovative work behavior. Self-rated employability was
expected to correlate positively with supervisor-rated innovative work behavior (Hypothesis 1a),
and supervisor-rated employability was expected to correlate positively with self-rated
innovative work behavior (Hypothesis 1b).
The aging workforce and its consequences for employees’ skills, knowledge, and expertise
(Dychtwald et al., 2006) are supposed to strongly influence knowledge-based economies and
comprises key themes in contemporary socio-economic debates among politicians, scholars, and
managers. Based on the literature review above, we may conclude that aging appears to affect
employability and innovative work behavior, and so becomes a critical socio-demographic
characteristic in business and society. This study contributes to the current debate by examining
the influence of employees’ age on the relationship between employability and innovative work
behavior. Given previous contradictory results (see the theoretical framework above), we are not
able to hypothesize about a direction of the moderation effect. Therefore, we hypothesized that
employee age is expected to moderate the relationship between self-rated employability and
supervisor-rated innovative work behavior (Hypothesis 2a), and the relationship between
supervisor-rated employability and self-rated innovative work behavior (Hypothesis 2b).
Methods
Participants and Procedure
The sample included employees and supervisors working in SMEs in Limburg, a province in the
south of the Netherlands. Participants held a variety of job types at both middle and higher
occupational levels, allowing for more variation in individual innovation opportunities (Scott and
Bruce, 1994). Using the European Union definition, SMEs are defined as commercial
organizations employing fewer than 250 people. Companies were identified using existing
personal contacts. When considering a certain enterprise, the researchers took into account the
geographical representation of SMEs in the province and their branches.
Employees and supervisors were informed about the fact that paired samples were used
for assessing the individual workers’ employability and innovative behavior since the validity of
self-ratings is found to be higher when employees are cognizant of the fact that supervisors are
also providing ratings (Mabe and West, 1982), resulting in a suppression of the leniency effect
(Arnold and MacKenzie Daveys, 1992; Hoffman et al., 1991). The final data set comprised 487
pairs of employees and their immediate supervisors, working in 151 SMEs. Sixty percent of the
employees were men, 52% were younger than 40 with a mean age of 38 (SD = 11.05). The
average length of service to their organization we 7.43 years (SD = 5.51). Eighty-two percent of
the supervisors were men and the average age was 43 (SD = 9.23). To ensure respondent
anonymity and to mitigate social desirability, we used an independent agency to administer two
versions (i.e., employee and supervisor) of a web questionnaire. The individual employee rated
their employability and innovative work behavior while the supervisors completed a
questionnaire containing amended items, phrased to assess the employability and innovative
work behavior of their corresponding subordinates. The item sets for the employees and the
supervisors were nominally identical, except for the fact that the items in the self-ratings
questionnaire referred to the employee him or herself, and the ones in the questionnaire for the
supervisors refer to a particular employee. To avoid invalid information due to training or fatigue
experienced by overburdened supervisors, and to protect data independence, one supervisor
filled out employability and innovative work behavior ratings for a maximum of three employees
(see also Van der Heijden, 2000), striving for an adequate distribution of respondents across
departments. In order to increase the response rate, each employee received an anonymous
response report containing his or her individual scores, interpretation guidelines, and a clear
framework demonstrating ways to improve employability.
Measures
Employability was measured using the extensively validated, five-dimension instrument from
Van der Heijde and Van der Heijden (2006) (see also Van der Heijden et al., 2009). The five
dimensions of employability are: (a) occupational expertise (15 items), (b) anticipation and
optimization (8 items), (c) personal flexibility (8 items), (d) corporate sense (7 items), and (e)
balance (9 items). Sample items from the self-rated version included: (a) I consider myself
competent to indicate when my knowledge is insufficient to perform a task or solve a problem,
(b) I approach the development of my weaknesses in a systematic manner, (c) I have a very
negative-very positive attitude to changes in my function, (d) In my work, I take the initiative in
sharing responsibilities with colleagues, and (e) The time I spend on my work and career
development on the one hand, and my personal development and relaxation on the other, are
evenly balanced. All 47 items were scored using a six-point Likert scale with responses ranging
from: 1 (not at all) to 6 (to a considerable degree), and 1 (never) to 6 (very often), depending on
an item’s wording. The reliability estimates for the subscales for employability ranged from
Cronbach’s alpha is .78 to .91 for the self-ratings, and from .83 to .95 for the supervisor ratings
(see Table 1 for all specific outcomes).
Innovative work behavior was measured using a nine-item scale developed by Janssen
(2000, 2001). Items corresponded to: (a) idea generation (3 items), (b) idea promotion (3 items),
and (c) idea realization (3 items). Examples of supervisor items included: (a) This worker
generates original solutions for problems, (b) This worker acquires approval for innovative ideas,
and (c) This worker introduces innovative ideas into the work environment in a systematic way.
All nine items were scored using a seven-point Likert scale with responses ranging from: 1
(never) to 7 (always). Innovative work behavior ranged from Cronbach’s alpha is .82 to .85 for
the self-ratings, and from .90 to .92 for the supervisor ratings.
Control Factors: Given the outcomes of previous studies (Adams et al., 2006; Calantone and Di
Benedetto, 1988; De Clippeleer et al., 2009; Globe et al., 1973; Stoffers et al., under review),
some control variables were included in preliminary analyses: (1) gender (1 = male; 2 = female),
(2) education (1 = high school or equivalent; 2 = college/(some) university; 3 = bachelor’s
degree or recognized equivalent; 4 = master’s degree or recognized equivalent; 5 =
doctorate/PhD), (3) number of years spent in other areas of expertise, (4) length of service, (5) 1
= management experience; 2 = no management experience, and (6) number of organizations for
which the employee had worked. The incorporation of these factors improves the generalizability
of our findings by mitigating alternative hypotheses and confounding effects (Blickle et al.,
2011).
(Table 1 about here)
Results
Descriptive Statistics and Preliminary Analyses
The means, standard deviations and correlations between all study variables are presented in
Table 1. All correlations between the supervisor-rated employability dimensions were relatively
high (r ≥ .55), whereas they were somewhat lower for the correlations between self-rated
dimensions (r ≥ .27). Correlations between supervisor-rated innovative work behavior stages
were high (r ≥ .77), yet slightly lower for self-rated stages (r ≥ .65). The correlations between
self- and supervisor ratings for the same employability dimension ranged from .25 to .32. For
innovative work behavior stages, the correlations between self- and supervisor ratings ranged
from .28 to .33. Nearly all supervisor ratings of employability appeared to relate to self- and
supervisor ratings of innovative work behavior stages (26 of 30 correlations), herewith
supporting our assumption regarding a positive association between the two. Concerning selfreported ratings of employability, 23 out of 30 correlations with innovative work behavior were
significant.
We incorporated the control variables in the preliminary analyses. By using this
approach, we were able to investigate possible confounding effects. The outcomes of these
analyses indicated that there was no reason to incorporate the control variables in the subsequent
SEM analyses.
Relationship between Employability and Innovative Work Behavior
Hypotheses 1a and 1b were tested by means of structural equation modeling (SEM) using AMOS
software (Arbuckle, 2006), investigating whether self-ratings of employability correlated
positively with supervisor ratings of innovative work behavior, on the one hand, and whether
supervisor ratings of employability correlated positively with self-ratings of innovative work
behavior, on the other hand. Scale scores, calculated as the means of the raw scores for self- and
supervisor-rated occupational expertise, anticipation and optimization, personal flexibility,
corporate sense, and balance (with employability being the latent construct) and self- and
supervisor-rated idea generation, idea promotion, and idea realization (with innovative work
behavior being the latent construct), were used as indicators for the two employability and for the
two innovative work behavior factors (see Figure 1).
(Figure 1 about here)
The results of the SEM analysis showed a Chi-square of 1063.123, a GFI of .802, and a
RMSEA of .140. With these outcomes, overall, the model fit appeared to be mediocre. Upon
closer inspection, the beta coefficient for the relationship between self-rated employability and
supervisor-rated innovative work behavior was .285 (p < .001), herewith supporting Hypothesis
1a. The beta coefficient for the relationship between supervisor-rated employability and selfrated innovative work behavior was .268 (p < .001), thus supporting Hypothesis 1b as well. The
results of these analyses are summarized below in Tables 2 and 3 and in Figure 2.
(Table 2 about here)
(Table 3 about here)
(Figure 2 about here)
Test of the Innovative Work Behavior-Enhancing Employability Model Moderated by Age
Hypotheses 2a and 2b posited that age moderates the relationship between employability and
innovative work behavior (see Figure 1). In order to test these hypotheses, our sample was split
into two sub-samples. Although there is little agreement in the literature about which age marks
the beginning of being “older” (Nishii et al., in progress), a considerable amount of scholars has
used the age of 40 as the cut-off because of its consistency with how the Age Discrimination in
Employment Act (ADEA) of 1967 defines the “older” worker (Finkelstein and Farrell, 2007;
Scidurlo, 2006). The age of 40 also comprises a threshold as supervisors are less inclined to
provide opportunities for training and development at the workplace, given their negative
evaluations regarding the future employability of their older subordinates (see also Boerlijst et
al., 1993). Therefore, our first sub-sample consisted of employees under the age of 40, and the
second sub-sample included employees who were 40 years of age or older. This dichotomising
of age has also been argued for and used in other employability research to examine moderation
effects (see also Van der Heijden et al., 2009).
In order to test the moderating effects of age, we conducted Multi-Group SEM. In our
analyses, the number of employees in the age category under 40 as opposed to the category of
their older counterparts was 255 and 232, respectively. In the first step, all structural paths were
allowed to be different for the two age groups. In the second step, we compared the fit of this
free model with the fit of a model in which all structural relationships were constrained to be
equal. The model that posed no restrictions in the estimation of the parameters appeared to have
a satisfactory fit with the data.
Results for the younger sub-sample showed a similar fit to the one for the full sample; the
Chi-square was 566.249, the GFI .792, and the RMSEA .135 (see Table 2 for more specific
outcomes). Therefore, it can be concluded that being younger was not a factor that moderated the
relationships between employability and innovative work behavior. For the older employees’
sub-sample, the Chi-square was 584.770, the GFI was .781, and the RMSEA was .144.
Therefore, being 40 and older was not a factor that moderated the relationship between
employability and innovative work behavior either. To conclude, the results in Table 2 clearly
show that none of the two sub-samples fitted the data significantly better in comparison with the
full sample. According to these results, we have not found overall support for Hypotheses 2a and
2b that referred to moderation effects of age in the relationship between employability and
innovative work behavior.
However, one important difference observed in the sub-samples of workers depending on
their age category (see Table 3) comprised the beta weights for the younger workers’ age group.
The betas were significant, although to a lesser extent when compared to the full sample, in
regard to the relationship between self-rated employability and supervisor-rated innovative work
behavior (Hypothesis 2a) (.285 for the full sample and .242 for the employees under 40 subsample). A similar result was observed for the relationship between supervisor-rated
employability and self-rated innovative work behavior (Hypothesis 2b) (.268 for the full sample
and .261 for the employees under 40 sub-sample). For the 40 and older employee sub-sample, a
similar but opposite effect could be observed. The beta weights were higher for this sub-sample
in comparison to the full sample, regarding the relationships between self-rated employability
and supervisor-rated innovative work behavior (Hypothesis 2a) (.285 for the full sample and .320
for the 40 and older employees sub-sample), and between supervisor-rated employability and
self-rated innovative work behavior (Hypothesis 2b) (.268 for the full sample and .279 for the 40
and older employees sub-sample). Consequently, there is enough partial support for Hypotheses
2a and 2b to suggest that age is a moderator in the relationship between employability and
innovative work behavior.
Discussion
In this study, we investigated the predictive validity of employability on innovative work
behavior by using a multi-source approach. The results demonstrated that self-rated
employability correlated positively with supervisor-rated innovative work behavior, and that
supervisor-rated employability correlated positively with self-rated innovative work behavior as
well.
Although the model fit appeared to be mediocre, we believe that the practical
implications of discussing outcomes based on testing the multi-source model and confirming its
hypothesized relationships, instead of working towards perfect model fit, comprise a more
important contribution to the literature. Moreover, strictly adhering to the distinguished cut-off
values may lead to instances of Type I error (the incorrect rejection of an acceptable model)
(Marsh et al., 2004). In addition, by allowing the model fit to drive the process, instead of
adhering to the underlying theoretical framework, research moves away from the original,
theory-testing purpose of structural equation modeling (Hooper et al., 2008).
We also investigated whether employee age moderates the relationship between self- and
supervisor ratings of employability and innovative work behavior. Our beta weights suggested
that the older employee sub-sample showed stronger relationships between the two variables of
interest compared with their younger counterparts. This suggests that age, although the effects
were weak, moderated the relationship between employability and innovative work behavior.
Specifically, for younger workers, the association between the model variables appeared to be
weaker in comparison with the total group of workers, while this relationship appeared to be
stronger in case the older workers were compared with the total group. From this study, we may
conclude that for the older workers in particular, attention for employability enhancement is
important given its higher predictive validity for innovative work behavior in comparison with
the added value for their younger counterparts. However, given the contradictory outcomes in
previous research on the effect of age in models incorporating employability and innovative
work behavior, we call for more empirical research in this field.
Ericsson (1999) and Youndt et al. (1996) already argued that innovation depends greatly
on the specific combination of employee knowledge and expertise. For example, complex mental
capacities such as attaining wisdom appear to increase with age (Baltes and Smith, 1990; Schaie,
1994) while cognitive work performance such as innovative work behavior is unaffected by age
throughout an employee’s career because it comprises a process of several diminishing
capabilities, coupled with increasing mental capabilities. Occupational experience compensates
for diminishing capacity (Ilmarinen, 2006), and it is therefore highly important to invest in the
further development of employees’ knowledge and skills (that is their employability or career
potential). Our findings contribute on the scholarly literature in this field by stressing the need
for employability enhancement for older workers in particular.
Previous research already indicated that stereotyping of older employees is a broad
phenomenon in that a supervisor’s negative mindset toward older employees makes aging an
important topic that needs to be addressed (Boerlijst et al., 1993; Finkelstein and Burke, 1998;
Van der Heijden et al., 2009). And even worse, as supervisors have a rather negative view of the
possibilities for older workers to make any further progression in a professional sense, it is
conceivable that the negative evaluations made by supervisors may produce some kind of
negative spin-off. Following a predominantly instrumental style of leadership, wherein the
expected return on investment is key, instead of people management, supervisors are less
inclined to invest in training and development of their older subordinates (Boerlijst et al., 1993).
This while exactly the latter category of workers appears to benefit most from a growth in
employability in the light of their innovative work behavior.
Practical Implications
Aging of the working population provokes a need to extend employees’ working lives beyond
the current retirement age. SMEs are more vulnerable to the demographic shift toward old age,
and HRM practices are consequently highly important to them (Wognum and Horstink, 2010). In
knowledge-based economies, such as the Netherlands, where SMEs comprise a large portion of
the economy, highly-skilled employees are essential (Dundon and Wilkinson, 2009) in order to
stay in the race. Small firms do not often employ professionals to manage human resources
(Bacon et al., 1996). Therefore, SME supervisors commonly implement their own models of
HRM, and base practices on multiple negative stereotypes concerning older workers. These
beliefs stem less from current performance levels and more from supervisors’ fears regarding
employees’ future prospects (Van der Heijden et al., 2009). Persistent stereotypes include beliefs
that older workers have great difficulty learning new technology, and that investment in their
training provides a poor return (Gray and McGregor, 2003). Awareness campaigns (Evans and
Pye, 2005) are useful to educate supervisors and young professionals about older workers and
reduce harmful stereotyping and biases (Malatest et al., 2003).
Age management (Ilmarinen, 2011) involves understanding age structures and strategies
in an organization, and possessing appropriate attitudes toward age. The role of supervisors is
essential to improving an age-friendly work life (Ilmarinen, 2011). Since HRM in SMEs is
informal (De Kok et al., 2006), age management strategies in SMEs are likewise at the discretion
of respective supervisors. An age-conscious workforce plan, which includes mentoring, training,
and flexible work options for retaining staff and corporate knowledge, formalizes age
management strategies (Pillay et al., 2010). For example, employers can encourage succession
planning and create positions in which accumulated expertise is channeled into less demanding
roles (Evans and Pye, 2005). These practices should not only include stimulating leadership
roles, but also encompass all essential professional knowledge and roles. This is especially
appropriate in SMEs where professionals often hold a single position (Leibold and Voelpel,
2006). Social factors such as stereotypes, experience with mature workers, and awareness of
aging issues hinder implementation of formal age management (Loretto and White, 2006; Pillay
et al., 2010).
According to Billett (2011), workers’ employability is conditional upon the possibility to
work, respond to new challenges, and demonstrate and develop competences further. However,
limited size and resources in SMEs suggest insufficient HRM to support employees’
opportunities to develop themselves and enhance innovative work behavior. Individual firms
should combine their capabilities with other SMEs since inter-firm collaboration allows more
opportunities for employee learning and innovation (Lundvall, 1993; OECD, 2000). Inter-firm
workplaces and education institutions are assumed to support employee development, but it is
important that employees themselves engage meaningfully and intentionally in career
development. Employability is the joint responsibility of individual employees, workplaces, and
education institutions (Billett, 2011).
Limitations and Recommendations for Further Research
Data were collected at one point in time (i.e., cross-sectional) only. A longitudinal design is
desirable and may solve causality problems (Taris et al., 2003), offering insights into reciprocal
relationships (Wright et al., 2005).
Analyses were based on data obtained from SMEs in various branches. Legal conditions
and cultural factors of a branch - especially regarding aging - might affect transferability of
results. The meanings of demographic characteristics and social implications of a category, such
as age, link to many factors, including national, cultural, and temporal contexts (Williams and
O’Reilly, 1998). According to Peterson (1997), a great lack of cross-national and cross-cultural
comparative social science research exists that would be advantageous to HRM practices. In this
study, age effects on employability and innovative work behavior were tested by using only one
sample from the Netherlands. The relational meaning of demographic characteristics might be
different for employees in other cultures. Further research is needed to elucidate the role of
national cultures from this perspective.
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