AGE AND INNOVATION-RELATED BEHAVIOR
STUDENT NAME & SURNAME (STUDENT ID)
STUDENT NAME & SURNAME (STUDENT ID)
STUDENT NAME & SURNAME (STUDENT ID)
INTRODUCTION
As the mean age of the workforce is rising in most industrial countries, the amount of
attention given to the relationship between age and job performance has grown as well
(Sturman, 2003). One dimension of job performance typically perceived as being outside the
bounds of core task performance is innovation-related behavior (IRB). IRB is the extent to
which employees generate new ideas, disseminate their and others’ new ideas, and implement
those ideas themselves or help others to do so (Ng, Feldman, & Lam, 2010). There is little
research on the effects of employees’ age on their IRB.
Therefore the aim of the study is to examine the effect of age on innovation-related
behavior (IRB).
The examination of age–IRB relationship is important for at least two reasons. First, the
generation of ideas that do not gain widespread attention, which are poorly implemented or
are never implemented at all, has little effect on improving the organization’s rate of
innovation (Choi & Chang, 2009). Thus, in addition to generating novel ideas, employees
need to be able to articulate, disseminate, and implement ideas generated by themselves, their
colleagues, or their supervisors. Second, innovation is increasingly critical for firm-level
performance (Anderson, De Dreu, & Nijstad, 2004).
THEORETICAL FRAMEWORK
The relationship between age and IRB has received far less attention than the age–
creativity relationship (e.g., Simonton, 1988). Across the 23 empirical studies on IRB, 11
have excluded age from the study and the remaining 12 utilized age only as a control variable.
No previous study has considered the substantive role of age in predicting IRBs. Thus, both
the theoretical nature and empirical nature of the relationship between age and IRB have been
rather elusive so far.
1
AGE AND INNOVATION-RELATED BEHAVIOR
Figure 1: Theoretical Framework
Age
Independent Variable
Innovation-Related
Behaviors
Dependent Variable
We hypothesize that age is positively related to IRB because older workers are both
more motivated and better able to engage in IRB. Our theoretical argument for expecting this
relationship is explained below.
On the basis of Ng and Feldman’s (2008) findings that older workers are generally good
citizens who are willing to go the extra mile in helping their organizations improve, we argue
that older workers will have greater motivation to engage in IRB as well. Indeed, contrary to
negative age stereotypes, older adults are actually highly interested in engaging in creative
activity because such endeavors enhance their sense of purpose, personal growth, and selfacceptance (Fisher & Specht, 1999). In addition, older workers tend to receive more
gratification from having high-quality employment relationships than younger workers do
(Ng & Feldman, 2010a). As a result, older workers are more motivated to engage in behaviors
(such as IRB) geared to helping colleagues and employers survive and thrive.
We also propose that older workers are more capable than younger workers in the
generation, dissemination, and implementation of new ideas in the workplace. In terms of idea
generation, because of their longer career spans, older workers may have more numerous and
diverse network links to individuals outside the firm (Constant, Sproull, and Kiesler, 1996).
Older workers may also contribute to idea dissemination and implementation more
effectively than younger workers. For instance, older workers may be better able to separate
high-value ideas from low-value propositions because they have greater work experience and
judgment. These higher levels of experience and judgment also help them get their ideas
across in more socially skillful ways and to discern the best ways of implementing
innovations in practice (Van Veldhoven & Dorenbosch, 2008). Taken together, these
arguments lead us to predict:
Hypothesis 1: Age is positively related to IRB.
AGE AND INNOVATION-RELATED BEHAVIOR
RESEARCH METHODOLOGY
Research design
The purpose of the research design is hypothesis testing. In order to test our hypothesis
we chose survey research where the extent of researcher interference is minimal and the data
collection takes place in non-contrived setting. The unit of analysis is individuals. The time
horizon of the design is cross-sectional.
Participants and Procedures
We recruited respondents by means of an online survey company (Zoomerang.com),
which asked potential respondents to participate in a survey. In return, we promised
respondents small monetary incentives (e.g., coupons) for their participation.
Within the research company’s database, we chose randomly from a diverse set of
industries subjects with some managerial responsibilities. We chose employees with some
managerial responsibilities as a sample because their jobs typically provide them with greater
opportunities for engaging in IRB than entry-level employees have (Chusmir & Koberg,
1986). Thus, the relative homogeneity here in terms of job requirements for innovation is
partially counterbalanced by a diverse set of industries.
Sample Characteristics
Thirty-eight percent (38 percent) of respondents were women. Average organizational
tenure was 8.7 years; average job tenure was 6.9 years. Sixty-six percent (66 percent) of the
sample had at least some college education. The average age of the participants in the study
was 40 years (SD = 11). Forty percent (40 percent) were between 22 and 39 years old, 47
percent between 40 and 54 years old, and the remaining 13 percent were between 55 and 66
years old. Therefore, 60 percent of our sample could be classified as older workers by using
the Age Discrimination in Employment Act definition.
Measures
Age: We measure chronological age as a continuous variable (ratio scale).
IRB: We measured IRB with the 5-item scale from Scott & Bruce, (1994). At this scale
supervisor indicated how characteristic each of the following behaviors was of a particular
employee: (1=Not at all Characteristic, 5=Very Characteristics).
1. Searches out new technologies, processes, techniques, and/or product ideas.
AGE AND INNOVATION-RELATED BEHAVIOR
2. Generates creative ideas.
3. Promotes and champions ideas to others.
4. Investigates and secures funds needed to implement new ideas.
5. Develops adequate plans and schedules for the implementation of new ideas.
Data Analysis
The study incorporates regression analysis. Regression analysis is a statistical process
for estimating the relationships of independent variables with a dependent variable.
Findings
We provide means, standard deviations, and correlations in Table 1. Table 2 shows the
regression results for testing our hypotheses, including standardized betas (b) and explained
variance (R2). Hypothesis 1 predicted that age would be positively related to IRB. The results
support that hypothesis. In Step 1 in Table 2, age was significantly related to IRB (b = .20,
p<.05).
Table 1: Means, standard deviations, and correlations among study variables (N= 196)
Gender
Age
Organizational Tenure
IRB
Mean
Standard Deviation
*p<.05; **p<.01.
Gender
1
-.11*
-.07
-.09
1.38
0.46
Age
Org. Tenure
IRB
1
.44*
.16**
39.59
11.13
1
-.03
8.73
6.78
1
5.13
2.50
Table 2: Age effect on innovation-related behavior (N=196)
Regression Analysis
Control variables
 Gender
 Organizational Tenure
Main Effect
 Age
Coefficients
R2
F-value
p value
-.09
-.07
0.855
0.613
.20*
.013
.16**
4.43
.000
CONCLUSION
This study addresses several gaps in the organizational sciences. The present research
highlights that the construct of age warrants much more attention both as independent and
AGE AND INNOVATION-RELATED BEHAVIOR
moderator variables in organizational research. Surprisingly, all the studies that have
examined IRB have treated age as a control variable or excluded it from investigation
altogether. This study, along with the growing literature on older workers (Ng & Feldman,
2008; Posthuma & Campion, 2009), suggests that age deserves much greater attention as a
factor in employees’ behavior. For instance, here, we found that in terms of predicting IRB,
age had comparable predictive power with proactive personality and greater predictive power
than supervisor undermining. Further, contrary to the negative stereotype that older workers
are less creative (Rosen & Jerdee, 1976), the evidence here suggests that older workers are not
only more active in idea generation but also more active in idea dissemination and
implementation as well. Taken together, these results suggest that simply excluding age or
treating it as a control variable in organizational research does not do justice to its effects on
workplace behavior.
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