Age as moderator of the relationship of proactive personality with training motivation, perceived career development from training, and training behavioral intentions

Journal of Organizational Behavior

J. Organiz. Behav. 32, 248–263 (2011)

Published online 4 January 2011 in Wiley Online Library

(wileyonlinelibrary.com) DOI: 10.1002/job.670

* Correspondence to:Cognitive et Sociale,

Copyright # 2011

Age as moderator of the relationship ofproactive personality with trainingmotivation, perceived career developmentfrom training, and training behavioralintentions

MARILENA BERTOLINO1*, DONALD M. TRUXILLO2

AND FRANCO FRACCAROLI1

1Department of Cognitive Science and Education, University of Trento, Trento, Italy2Department of Psychology, Portland State University, Portland, Oregon, U.S.A.

Summary Based on changes in motivation thought to occur across the lifespan, we investigated whetherage would moderate the relationship between proactive personality and three training-relatedvariables: training motivation, perceived career development from training, and trainingbehavioral intentions. A survey was completed by 252 municipal government employees.As hypothesized, participants’ age moderated the relationship between proactive personalityand these outcomes. Specifically, there was generally a more positive relationship betweenproactive personality and the outcomes for younger participants than for older participants.Our discussion focuses on implications for training in organizations and recommendations forpractice. Copyright # 2011 John Wiley & Sons, Ltd.

Introduction

Research into older workers has accelerated due to the aging population. For example, the number

of U.S. workers over age 55 is expected to grow at nearly four times the rate of the overall labor force by

2012 (Alley & Crimmins, 2007). Thus, it is useful to examine the factors that may influence older

workers to continue to contribute in the workplace and to understand how older workers’ skills,

interests, and motivations may differ from those of younger colleagues. As a result, research has begun

to examine how age may affect outcomes such as work attitudes (e.g., Gaillard & Desmette, 2008), goal

orientation (e.g., Ebner, Freund, & Baltes, 2006), work motivation (e.g., Kanfer & Ackerman, 2004),

personal initiative at work (e.g., Warr & Fay, 2001), and training and development activities

(e.g., Greller & Simpson, 1999; Maurer, Weiss, & Barbeite, 2003).

Marilena Bertolino, who is now at University of Nice Sophia-Antipolis, Laboratoire de Psychologie24 avenue des Diables Bleus, 06357 Nice, France. E-mail: [email protected]

John Wiley & Sons, Ltd.

Received 1 December 2008Revised 21 September 2009

Accepted 29 September 2009

AGE AND PROACTIVE PERSONALITY 249

Today many training programs are being offered to employees in addition to the many types of

training offered outside of the employment setting. Given this range of choices, employees now have

greater opportunities for learning and development, but also have increased responsibility for getting

the training that will enhance their careers. Indeed, today’s workers can be ‘‘free agents’’ in their own

careers (Major, Turner, & Fletcher, 2006), implying that they must actively pursue training and

development opportunities to be successful. Further, several studies have pointed out the importance of

training and development activities for the organization and individuals (e.g., Maurer & Tarulli, 1994;

Maurer et al., 2003).

Research has also shown that individual differences may be important predictors of engagement in

training and development activities, especially when the activities are voluntary (e.g., Major et al.,

2006; Maurer & Tarulli, 1994; Warr & Birdi, 1998). People participate in these training and

development activities in order to learn new job skills, extend existing skills, or grow their careers.

Major et al. (2006) demonstrated the importance of proactive personality (e.g., Seibert, Crant, &

Kraimer, 1999) in training and development. Specifically, Major et al. found that proactive personality

predicted motivation to learn and that it was indirectly linked to development activity.

Maurer et al. (2003) presented a comprehensive model to explain the main effects of age in work-

related development activities, examining the effect of age on development-related variables such as

training motivation and training behavioral intentions. However, no research to date has explicitly

examined how age differences may moderate the relationship between personality variables and

training and development activity, that is, how age may moderate the effects of personality on training-

related variables. Because motivation appears to mediate the effects of personality on work-related

outcomes (e.g., Barrick, Stewart, & Piotrowski, 2002), and because there may be differences in types of

work motivation due to age (Kanfer & Ackerman, 2004), it is important to see if personality variables

such as proactive personality are differentially related to training-related variables for older and

younger workers. Examining the moderating effects of age on the relationship between proactivity and

training-related outcomes is also important in light of meta-analytic evidence that age differentially

affects work outcomes (Ng & Feldman, 2008).

The present study fills this gap by investigating whether age moderates the relationships between

proactive personality and three development variables: training motivation, perceived career

development opportunity, and behavioral intentions (cf., Maurer et al., 2003). Specifically, we

examined whether proactive personality has a differential relationship with these development-related

variables for younger workers and older workers, perhaps due to differences in what motivates younger

and older workers (e.g., Kanfer & Ackerman, 2004). Our specific point is not that older and younger

workers differ in terms of proactive personality, but that proactive personality will result in different

motivational mechanisms and thus different outcomes for older and younger workers. As such, this

study integrates models of work motivation and aging (e.g., Kanfer & Ackerman, 2004) with research

on the role of proactive personality in training motivation and outcomes (e.g., Major et al., 2006) and

research on the role of age in development activity (e.g., Maurer et al., 2003).

Proactive personality, motivation, and age

Bateman and Crant (1993) developed the concept of proactive personality, which is defined as a

relatively stable tendency to effect environmental changes. Individuals with a prototypical proactive

personality take action to influence their environments, or ‘‘identify opportunities and act on them,

show initiative, take action, and persevere until meaningful change occurs’’ (Crant, 2000, p. 439).

Proactive individuals show a willingness and determination to pursue a course of action, characteristics

that are central to models of self-development (Antonacopoulou, 2000). Proactive personality has been

Copyright # 2011 John Wiley & Sons, Ltd. J. Organiz. Behav. 32, 248–263 (2011)

DOI: 10.1002/job

250 M. BERTOLINO ET AL.

linked to objective (salary and promotions) and subjective (career satisfaction) indicators of career

success (e.g., Erdogan & Bauer, 2005; Rauch & Frese, 2007; Seibert et al., 1999). Moreover, proactive

personality has been shown to explain additional variance in both objective and subjective career

success even after accounting for other predictors such as demographics, motivation, type of

organization, and type of industry (Seibert et al., 1999).

Importantly, Major et al. (2006) found that proactive personality was related to training outcomes

such as motivation and behavioral intentions, although they did not examine moderator variables such

as age which may affect the relationship between proactive personality and training-related outcomes.

However, there is reason to believe that age may moderate the relationship between proactive

personality and training-related outcomes, as research suggests that people focus on different types of

motivation across the adult lifespan. Kanfer and Ackerman (2004) argue that the motivational

structures of older and younger employees may differ due to changes across the life span in terms of

certain individual differences (e.g., fluid intelligence), organizational rewards, and career situations.

Thus, older workers may focus less on training at work than their younger counterparts. Accordingly,

Ebner et al. (2006) found that while younger individuals were more focused on growth in their goal

orientations, older individuals were more focused on maintenance. Similarly, Freund (2006) found that

younger adults were more likely to persist in optimizing performance, while older adults persisted in

minimizing losses. Given these effects of age on motivation, and given evidence that motivation

variables such as goals mediate the effects of personality on job behaviors (e.g., Barrick et al., 2002), it

seems likely that age may moderate the relationship between proactive personality and training

motivation and training behavioral intentions. Specifically, we expected that proactivity would be more

strongly associated with training-related outcomes for younger workers than for older workers.

Taken together, this research on differences in the motivation of younger and older adults (e.g., Ebner

et al., 2006) and motivational differences between older and younger workers (e.g., Kanfer &

Ackerman, 2004) suggests that older and younger workers may manifest proactivity differently in

organizational settings, and that the meaning of being ‘‘proactive’’ may be different for older and

younger workers. In other words, older and younger workers do not necessarily differ in their levels of

proactivity; in fact, research has generally found non-significant correlations between age and

proactivity (e.g., Erdogan & Bauer, 2005; Harvey, Blouin, & Stout, 2006; Seibert et al., 1999). Rather,

we argue that older and younger workers may manifest proactivity on the job in different ways.

Whereas younger workers may focus on career development activity, older workers may hold more

generative motives (e.g., Kanfer & Ackerman, 2004), and thus focus on activities such as mentoring,

group processes, and organizational citizenship behavior. For these reasons, proactive personality

should have a differential relationship with training motivation, perceived career development

opportunity, and intentions to participate in training and development activities for younger and older

workers. Specifically, proactive personality should be positively related to these training-related

outcomes for younger workers, for whom training is instrumental to their careers. But this relationship

should be less positive for older workers, for whom the benefits of training such as career development

are less interesting and relevant.

We are not aware of other studies that have investigated the moderating effects of age on the

relationship between proactive personality and training-related outcomes, but we consider this to be an

important topic for organizations and researchers alike. As noted, proactive personality is a critical,

motivation-focused individual difference variable focused on seeking opportunities in one’s

organizational setting. In general, the more proactive employees are, the more likely they are to

show initiative and motivation regarding training and to see training as important, assuming that

training affords them opportunities in the organization. For younger workers, proactivity is likely to be

focused on job-related training and development activity because they see it as a vehicle for career

development. Proactive older workers, on the other hand, will be less focused on training and


DOI: 10.1002/job


development activity, perhaps focusing instead on mentoring and maintenance activities (cf., Ebner

et al., 2006; Kanfer & Ackerman, 2004). This difference in the manifestation of proactive personality

for older and younger workers could lead to a differential impact on development variables such as

training motivation, perceived career development from training, and training behavioral intentions. In

short, proactive personality may differentially predict these training and development outcomes for

older and younger workers.

In summary, the outcomes in our model are based on the motivational and behavioral categories

included in Maurer et al.’s (2003) model of the role of age in development activity. However, rather than

focusing on the main effects of age, we now examine age as a possible moderator. Although researchers

have separately examined the effects of age (Maurer et al., 2003) and proactive personality (Major

et al., 2006) in development activity, the combined role of age and proactive personality has not been

examined. Thus, in the present study we looked at the interactive effects of age and proactive

personality on training and development-related variables.

Hypotheses

Training motivation

Training motivation refers to the tendency to engage in training and development activities, to learn

training content, and to embrace the training experience (cf. Carlson, Bozeman, Kacmar, Wright, &

McMahan, 2000; Noe, 1986). Major et al. (2006) found that proactive personality predicted motivation

to learn in a training context. However, according to Kanfer and Ackerman’s (2004) review, the

strength of such achievement motives may decline as workers age. In contrast, younger individuals are

more focused on career success (Kanfer & Ackerman, 2004). Thus, research suggests that the value of

training may be lower among older workers, especially since training is less useful to older workers in

the organizational context. In this sense, the instrumentality of the training to achieving work-related

goals may be lower for older workers. Thus, while proactive younger workers will recognize the

instrumentality of training to learn new job skills, a proactive older worker will be less likely to do so.

For these reasons, we expected that the relationship between proactive personality and training

instrumentality motivation would be moderated by age.

Hypothesis 1: Workers’ age will moderate the relationship between proactive personality and

training instrumentality motivation. Specifically, there will be a more positive relationship between

proactive personality and training motivation for younger workers than for older workers.

Perceived career development from training

The reality of today’s work context suggests that organizations can no longer promise steady upward

mobility or lifelong employment (Farr, Tesluk, & Klein, 1998). Instead, work conditions may require

employees to continually learn new skills and acquire new knowledge (Hedge, Borman, & Lammlein,

2006). Thus, career development now involves more periodic cycles of skill learning, mastery, and

‘‘reskilling’’ in order to reach new positions, jobs, and assignments throughout a person’s career.

Further, factors that may affect employees’ perceptions of opportunities for career development are

important to examine.


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Taking part in training activities is influenced by individual characteristics such as proactivity (e.g.,

Major et al., 2006), in the sense that more proactive people would be more likely to take part in

voluntary developmental activities. Moreover, highly proactive people are more likely to actively seek

out and identify new opportunities (Seibert et al., 1999). However, opportunities for career

development (such as training) are more relevant for younger workers than older workers because they

may have a greater impact on a younger worker’s career growth. As such, highly proactive older

workers may not perceive training as a particularly relevant opportunity. The opportunity-seeking

aspect of proactive personality is therefore unlikely to be manifested in terms of training opportunities

for older workers. We thus believed that the relationship between proactive personality and perceived

opportunity for career development offered by training would be moderated by age.


perceived career development from training. Specifically, there will be a more positive relationship

between proactive personality and perceived career development from training for younger workers

than for older workers.

Training behavioral intentions

More proactive people are thought to be more likely to take part in training programs and development

opportunities in order to maintain internal and external marketability (e.g., Arthur & Rousseau, 1996;

DeMeuse, Bergmann, & Lester, 2001; King, 2004). Empirically, Major et al. (2006) found proactive

personality was linked to development activity through the mediating role of motivation to learn.

However, learning new skills may be more relevant for younger adults, who are focused on getting

ahead, than for older adults, who are less focused on career advancement (e.g., Kanfer & Ackerman,

2004). In addition, research shows that younger adults are more persistent than older adults in realizing

a task that offers the possibility for optimizing performance (Freund, 2006). Thus, while proactive

younger persons may be more concerned with acquiring new knowledge and skills that will enable

them to reach their career goals, proactive older adults may focus on different goals, particularly for

training designed to provide skills needed for career advancement. Thus, we expected that proactive

personality would be manifested differently at different life stages, and that its relationship with

training behavioral intentions would be lower for older workers, for whom the training would be

perceived as less instrumental to career advancement.


training behavioral intentions. Specifically, there will be a more positive relationship between

proactive personality and training behavioral intentions for younger workers than for older workers.

Method

Participants and procedure

Participants were 272 employees of a municipal government in Northeast Italy. The sample was

composed of employees working in the administration, technical bureau, and accounting office, all

having a permanent working contract. Employees who work at the technical bureau perform tasks such

as town planning and design, and planning, managing, and controlling public works. Moreover, they do


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drafting and survey work as part of building code enforcement. Employees who work in the accounting

office and administration perform tasks such as processing payments, counting pension contributions,

and performing welfare duties. They also deal with fiscal/tax reports, calculate internal balances, and

arrange monthly and annual fiscal reports for the government.

With regard to the work arrangements (contracts) employees have in this organization, level A is the

lowest level contract, and D is the highest level contract, which includes a range of jobs except at the

director level. (Contracts are a typical way of classifying work assignments in public organizations in

Italy.) In our sample, no participants belonged to the level A group, 16 participants belonged to level B,

18 belonged to level D, and the majority of the sample had a level C contract.

From the initial sample (N¼ 272), because 14 participants did not totally complete the questionnaire

and six participants did not indicate their age, we excluded them from all data analyses, so the final

sample was based on 252 employees. This resulted in a final response rate of 94.85 percent among those

contacted. Their mean age was 40.60 (SD¼ 8.30, Mode¼ 40, Median¼ 40.00) with a range from

21 to 60. Thirty-four percent of the samples were men, 64 percent were women, and 2 percent (five

participants) did not indicate gender. With regard to education, 4.3 percent had less than high school,

72.5 percent had a high school diploma, 18.2 percent had a university degree, and 2.3 percent had a post

university degree; 2.7 percent (seven participants) did not indicate their education. With regard to

organizational tenure, 14.7 percent had less than five years of experience with the organization, 15.9

percent had between 5 and 10 years, and 67.8 percent had more than 10 years of experience. The

training offered by the organization covered a range of issues such as new rules of the registry office and

vital statistics; training in management accounting; and training regarding privacy rules and the

treatment of personal data. Participation at these training programs was voluntary.

Participants were asked to fill out a survey on their perceptions regarding their proactivity, training

motivation, perceived career development from training, and training behavioral intentions. One

hundred and thirty one participants (Mage ¼ 40.35; SD¼ 8.70) completed the survey during their

participation in one of the training programs, and the other group of participants (N¼ 121;

Mage¼ 40.84; SD¼ 7.87) completed the survey during their break on the job. Note that these two data

collection groups did not differ in terms of mean (t(250)¼�0.47, ns) or variance (F¼ 1.88, ns) for age.

Participants were assured of the confidentiality and anonymity of their responses, and they returned

the survey directly to the researchers.

Measures

To the extent possible, we chose established measures from the literature. An English version of the

items used in this study is in the Appendix. We used the following procedure to translate the proactive

personality and training motivation items into Italian from the original English. First, the items were

translated into Italian by two native Italian speakers. Second, the items were translated back into

English by a bilingual translator. Third, the items were checked by two of the authors to be sure their

meaning was correct.

Proactive personality

We measured proactive personality based on five positively worded items of the proactive personality

scale (Seibert et al., 1999). Although the original scale was composed of 10 items, in this survey we

retained only those items that could be meaningfully translated into Italian and back translated into

English. Respondents were asked to assess the extent to which they believed the items described

themselves. Responses were on a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly

agree). A sample item is ‘‘I am constantly on the lookout for new ways to improve my life’’ (a¼ 0.67).


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Training motivation

Participants’ training motivation was assessed by two items adapted from the instrumentality subscale of

Truxillo and Weathers’ (2005) training motivation scale which is based in expectancy theory (Vroom,

1964). Responses were given on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly

agree). An example item is ‘‘My completion of this training will make me a better worker’’ (a¼ 0.82).


Perceived career development from training in the organization was assessed by a 7-item scale from the

original 15 of Battistelli and Odoardi (2004). These items focused on the perceived likelihood of

various results workers would obtain as a result of training provided in their organization in the coming

years. Items were on a 5-point Likert scale ranging from 1 (not likely at all) to 5 (absolutely likely).

Sample items are ‘‘Contribute to improve the work in my organization’’ and ‘‘Improve my current level

of discretion and responsibility’’ (a¼ 0.88).

Training behavioral intentions

One item assessed participants’ behavioral intentions to participate in training programs in the near

future, rated on a ‘‘yes’’ ‘‘no’’ scale (‘‘Do you plan to take part in training programs in the next six

months?’’). We chose this period of time because the following six months was when participants were

most likely to take part in the several training programs offered by their organization. Moreover, the

different types of training were usually offered repeatedly over a period of months so that all employees

would have the chance to receive training and so that offices would not need to close (i.e., if all

employees attended training at the same time).

Demographic informationThe demographic section of the questionnaire asked questions about the participants’ age, gender,

education level, and organizational tenure. Participants’ age was measured by an open-ended question.

Participants’ gender, educational level, and organizational tenure were evaluated using a multiple-

choice response format.

Results

Means, standard deviations, intercorrelations, and a reliabilities are presented in Table 1. A review of

the correlation matrix indicates a non-significant correlation between age and proactive personality

(r¼�0.11, ns), which is consistent with past research (e.g., Erdogan & Bauer, 2005; Harvey et al.,

2006; Seibert et al., 1999). Although proactive personality was related to training motivation, r¼ 0.24,

p< 0.01, it was not correlated with training behavioral intentions, r¼ 0.03, ns, nor with perceived

career development from training, r¼ 0.04, ns.

We used hierarchical regression to test Hypotheses H1 and H2. Hypothesis 3 was tested via logistic

regression. The three dependent variables in these equations were training motivation (H1), perceived

career development from training (H2), and training behavioral intentions (H3). Because gender was

correlated with at least one of the dependent variables and could be related to available opportunities

for development, we used it as a control variable. We centered (e.g., Aiken & West, 1991) the main

effects (i.e., set the mean equal to 0) in order to reduce multicollinearity between the main effects and

interaction term. The use of standardized scores to center variables also facilitates interpretation of the

difference in regression slopes at �1 and þ1 standard deviations from the mean. The control


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Table 1. Means, standard deviations, intercorrelations, and a reliabilities among all the variables

Variables M SD 1 2 3 4 5 6 7 8

1. Age 40.60 8.302. Gender 0.65 0.48 �0.34�� —3. Educational level 1.20 0.54 �0.11 �0.02 —4. Org. tenure 1.53 0.76 0.61�� 0.19�� 0.08 —5. Proactive personality 5.70 0.76 �0.11 0.07 0.06 �0.12 (0.67)6. Training motivation 3.80 0.73 �0.02 0.06 0.08 �0.03 0.24�� (0.82)7. Training behavioral intentions 0.67 0.47 �0.06 0.08 0.09 0.00 0.03 0.13�

8. Perceived career developmentfrom training

3.29 0.64 �0.29�� 0.20�� 0.01 �0.15� 0.04 0.20�� 0.34�� (0.86)

Note: Gender was coded: 0¼men, 1¼women; educational level was coded: 0¼ less than high school, 1¼ high school diploma,2¼ university degree; 3¼ post university degree; organizational tenure was coded: 0¼ less than five years, 1¼ between 5 and 10years, 2¼more than 10 years.�p< 0.05; ��p< 0.01.


variable (gender), participants’ age (centered), and proactive personality (centered) were entered on

Step 1. The interaction term, which was the product of age and proactive personality, was entered on

Step 2. Hypotheses 1 and 2 were tested using OLS regression. Hypothesis 3 was tested using logistic

regression because training behavioral intentions is a binary variable. These results are presented in

Table 2.

Hypothesis 1 stated that workers’ age and proactive personality would interact to affect training

motivation (i.e., instrumentality), such that there would be a more positive relationship between

proactive personality and training motivation for younger workers than for older workers. Results

supported Hypothesis 1, as indicated by the significant increase in R2 with the addition of the

interaction term on Step 2, DR2¼ 0.01, F(1, 245)¼ 4.00, p< 0.05. As shown in Figure 1, for younger

workers there was a stronger relationship between proactive personality and training motivation, but

this relationship was weaker for older workers.

Hypothesis 2 predicted that age and proactive personality would interact to affect perceived career

development from training, such that there would be a more positive relationship between proactive

Table 2. Hierarchical OLS regressions and logistic regression for age, proactive personality, and their interactionon training motivation and perceived career development from training, and training behavioral intentions

Variable

Training motivation

Perceived careerdevelopment from

trainingTraining behavioral

intentions

R2 DR2 b R2 DR2 b R2 DR2 Odds ratio

Step 1 0.05�� 0.07� 0.02�

Control variable: gender 0.06 0.20 0.48�

Age 0.03 �0.12 1.01Proactive personality 0.26�� 0.05 1.14Step 2 0.07�� 0.01� 0.09� 0.03� 0.05� 0.02�

Age� proactive personality �0.13� �0.17� 0.72�

Note: N¼ 252. Hierarchical OLS regression was used for training motivation and perceived career development from training,and logistic regression was used for training behavioral intentions. For training behavioral intentions, R2 values are for Cox andSnell R2. R2 and DR2 may not add up due to rounding. Gender was coded: 0¼men, 1¼women. Betas and odds ratios are for thefinal equation.�p< 0.05; ��p< 0.01; ��p< 0.001.


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Figure 1. Interaction of age and proactive personality on training motivation (instrumentality). Note: Younger agemeans 32.3 (– 1 SD below the mean) and older age means 48.9 (þ 1 SD below the mean)


personality and perceived career development from training for younger workers than for older

workers. Results supported Hypothesis 2, DR2¼ 0.03, F(1, 245)¼ 7.05, p< 0.05. This interaction is

shown graphically in Figure 2. Specifically, there was a more positive relationship between proactive

personality and perceived career development from training for younger workers than for older

workers.

Hypothesis 3 stated that age and proactive personality would interact to affect training behavioral

intentions. Results supported Hypothesis 3 as indicated by the significant increase in Cox and Snell’s R2

with the addition of the interaction term on Step 2, DR2¼ 0.02, x2(1)¼ 5.10, p< 0.05. We then

transformed the predicted values of the dependent variable (log odds of training behavioral intentions)

into the probability of behavioral intentions regarding training using the formula described by Cohen,

Cohen, West, and Aiken (2003). This interaction, shown graphically in Figure 3, suggests a more

positive relationship between proactive personality and training behavioral intentions for younger

workers than for older workers.

Discussion

The purpose of this study was to fill a gap in the literature by examining the interaction between

proactive personality and age, specifically, to understand the moderating effect of age on the

relationship between proactivity and training motivation, perceived career development from training,

and training behavioral intentions. We sought to integrate research on the role of proactive personality

Figure 2. Interaction of age and proactive personality on perceived career development from training. Note:Younger age means 32.3 (– 1 SD below the mean) and older age means 48.9 (þ 1 SD below the mean)


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Figure 3. Interaction of age and proactive personality on training behavioral intentions. Note: Younger age means32.3 (– 1 SD below the mean) and older age means 48.9 (þ 1 SD below the mean)


in training and development (e.g., Major et al., 2006), models of age and development activity (Maurer

et al., 2003), and research regarding the motivation of older and younger workers (e.g., Kanfer &

Ackerman, 2004). As hypothesized, we found that proactive personality was differentially related to

these training-related variables for older and younger workers.

Our results illustrate that age moderated the relationships of proactive personality with training

motivation, perceived career development from training, and behavioral intentions. Although previous

empirical research has found that age is associated with differences in motivation (e.g., Freund, 2006)

and development outcomes (e.g., Maurer et al., 2003), and that personality may differ with age (e.g.,

Roberts, Walton, & Viechtbauer, 2006), we are not aware of other published studies that explored the

interaction between proactive personality and an individual’s age. The results of this study were

consistent across the outcomes we examined: More positive relationships were found between

proactive personality and training motivation (H1), perceived career development from training (H2),

and training behavioral intentions (H3) for younger workers than for their older counterparts. Indeed,

for the overall sample we found no correlation between proactive personality and two of the dependent

variables (perceived career development from training and training behavioral intentions). This may be

due to the effects of a moderator variable such as age, as the differential relationships between proactive

personality and these dependent variables for older and younger workers may have reduced the

correlations within the larger sample. These findings support the idea that the relationship between

proactive personality and its motivational outcomes may differ across the life span. It is noteworthy that

for training motivation and training behavioral intentions, the greatest differences between older and

younger workers were for those with low levels of proactivity. Specifically, younger workers with low

levels of proactivity were relatively less motivated to receive training than their older counterparts.

Similarly, they were less likely to indicate that they intend to get training. In addition, it appears that for

older workers there is a negative relationship between proactivity and the development outcomes of

perceived career development from training and training behavioral intentions, perhaps because

proactive older workers are focused on other outcomes at the expense of these (cf. Kanfer & Ackerman,

2004). Future research should investigate this issue.

From an applied perspective, organizations should take into consideration that proactive personality

may not have the same meaning or lead to the same outcomes for younger and older workers. A

possible explanation for these findings is that proactive personality may lead to different behavioral

manifestations depending on individuals’ career stage. Indeed, reviews of worker age and

organizationally relevant outcomes suggest that chronological age is an indicator of many variables

that may affect work outcomes (e.g., Kanfer & Ackerman, 2004). Moreover, as Kanfer and Ackerman’s

review points out, employees’ motivation can be focused on different factors depending on their

life stage. For instance, older employees may be less threatened by a failure to get promoted,


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because occupational achievement plays a smaller role in their lives. Indeed, older people may be

more oriented toward factors such as task maintenance rather than optimization (Freund, 2006) or

growth (Ebner et al., 2006). However, this does not mean that older workers are not proactive; indeed,

as in past research (e.g., Erdogan & Bauer, 2005; Harvey et al., 2006; Seibert et al., 1999), in the present

study we did not find a significant relationship between age and proactive personality. Rather, older

workers may focus their proactivity on substantially different goals than younger workers (cf., Ebner

et al., 2006) such as generativity motivation (e.g., Kanfer & Ackerman, 2004). Future research should

investigate whether there are outcomes that are better predicted by proactive personality for older

workers than for younger workers, for example, coaching or mentoring coworkers (e.g., Kanfer &

Ackerman, 2004), or perhaps a greater focus on non-work-related activities (e.g., spending more time

with family).

The theory of socio-emotional selectivity (Carstensen, Isaacowitz, & Charles, 1999) could

provide an additional interpretation. This theory posits that the perceptions people have about time

play a critical role in goal setting. Specifically, when time is perceived as unlimited people are more

inclined to choose career-focused objectives. Translated into an organizational setting, younger

workers who perceive that they have more time remaining in their careers would be more

interested in training and development activities, while older workers would have greater

motivation for activities more oriented toward building and maintaining relationships with

colleagues (Beier, 2008). Alternatively, older workers may be less motivated to participate in

training because there are fewer career development opportunities for them. In this sense, it may be

that even proactive older workers see little value in training. It may in fact be that our results

were also due to cohort differences. In any case, it is interesting to point out that in this sample,

older workers did not show lower intention to participate in training, and they did not see training

as less instrumental. However, age was associated with lower perceived career development from

training.

Potential limitations and future research

Although this study makes several contributions, it is also important to note some potential limitations.

First, because the sample was made up of municipal government employees, the results of this study

may not generalize to other contexts. However, our sample did include a wide range of jobs. We

encourage further research on this topic using additional samples from a variety of organizations.

Second, our study used a cross-sectional data collection methodology to examine these hypotheses.

Although this could be problematic in terms of drawing inferences regarding changes in proactive

personality across the lifespan, the aim of this study was to better understand the role of age in the

relationship between proactive personality and training-related variables, not to study the aging process

across the lifespan. Moreover, while such cross-sectional data may lead to inflated relationships among

variables, this is less of a problem when examining moderator effects as in the present study, where

differences in age produced different slopes (i.e., the relationship between proactive personality and the

outcomes was different for older and younger workers.) Third, some of the effect sizes for our

interaction terms were fairly low. On the other hand, given the difficulty of detecting interaction effects

especially in field samples (Judd, McClelland, & Culhane, 1995; McClelland & Judd, 1993; Whisman

& McClelland, 2005), we were pleased that we were able to detect the hypothesized interactions.

Fourth, although the a for the proactive personality scale was a bit low, we were able to obtain support

for our hypotheses. A small weakness of the study design is that all the data were self-reported. When

possible, the use of company training records would be useful in future studies of these issues. Another

limitation is that our study only examined outcomes that would be of interest to younger workers, that


DOI: 10.1002/job


is, training-related outcomes. As our study was focused on worker reactions to training, we did not

measure other, non-training related outcomes which might be of interest to proactive older workers.

Future research should examine these additional outcomes.

Another limitation of this study regards the motivation training scale based on Vroom’s (1964)

expectancy theory. In the present study, we used only the instrumentality dimension because it is the

most likely to be affected by age, specifically, because older workers would likely find training to be

less instrumental to them than younger workers. Another potential limitation regards changes that were

made to the proactive personality scale. Although the original scale is composed of 10 items (cf. Seibert

et al., 1999), in our survey we kept the most representative and meaningful ones (five items) that

resulted after the translation into Italian and back translation into English. If possible, future studies

should use other measures of proactive personality.

A final potential limitation of this study regards the perceived career development from

training scale. As an anonymous reviewer pointed out, the items of this scale refer to the perceived

opportunity employees have regarding their development in that organization. Proactive personality

should be related to the perceived availability of opportunities for action and not only to perceived

opportunity for career development. Future studies should focus on the actual actions employees would

take.

Future studies should also clarify the role played by proactive personality in predicting a range of

different outcomes for different age groups. For example, some studies have investigated the role of

contextualizing motivational effects of goal focus during the life span (e.g., Baltes & Baltes, 1990;

Ebner et al., 2006; Freund, 2006), such that goals and motivation had different foci for younger and

older adults. The findings of the present study are consistent with the selection, optimization, and

compensation theory (SOC; Baltes & Baltes, 1990; Freund & Baltes, 2000), which underlines the

importance of contextualizing motivational processes into a life span approach. Accordingly, one line

of research could examine how proactivity is manifested on the job among older individuals. For

example, organizational citizenship behaviors (OCBs) are an important component of job performance

(e.g., Motowidlo & van Scotter, 1994). Because older workers may be more oriented toward generative

motives (e.g., Kanfer & Ackerman, 2004), proactivity among older workers may be manifested in

increased OCBs. Thus, future research should examine how proactive personality is related to different

job behaviors at work for older and younger people, similar to the differential relationships that have

been found between age and various work behaviors (e.g., Ng & Feldman, 2008). This might be

especially true because certain work behaviors are more instrumental for certain age groups. Relatedly,

research should investigate whether other personality variables (e.g., conscientiousness) may

differentially relate to work attitudes and outcomes for older and younger workers, as has been noted in

recent reviews (e.g., Kanfer, 2009). Given the recent interest in personality in the work and

organizational psychology literature (e.g., Morgeson, Campion, Dipboye, Hollenbeck, Murphy, &

Schmitt, 2007), an examination of variables such as age which may moderate the relationship between

personality and attitudinal and behavioral outcomes is in order.

In this study, we examined the interaction between chronological age and proactive personality in

relationship with several training-related outcomes. Future studies should consider individual

psychological or subjective age measures that indicate how old or young the individual perceives him-

or herself to be (Barak, 1987; Riordan, 2000), and perhaps captures a person’s capacity to adapt

behavior to the demands of the environment (Sterns & Miklos, 1995). Also it seems useful to

investigate social age, or the social norms and roles applied to a person who lives in a cultural context

(Birren & Birren, 1990). Although it is beyond the scope of this study, future research should take into

consideration the interaction between age and gender (as suggested by an anonymous reviewer).

Indeed, these two variables could have a different influence on several outcomes. For example, older

women and older men could orient their motivation toward different outcomes.


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Another important issue for future research is to examine what is meant by ‘‘older’’ and ‘‘younger’’

workers, and relatedly, how workers’ motivation and behavior might change at different life stages.

There has been little agreement in the literature on how to operationalize worker age groups, or what is

meant by ‘‘older’’ and ‘‘younger’’ workers (e.g, Finkelstein & Farrell, 2007). Future research should

examine at what specific ages or stages important, work-related differences occur in workers to better

understand the motivations and work behaviors of different age groups. It may also be that these ages

are different for different types of workers; for example, age may have different effects on work

motivation and behavior for managers than for non-managers.

In conclusion, the results of this study suggest that age may be an important consideration in

understanding the meaning of proactivity to work outcomes. Specifically, it suggests that proactive

personality may lead to different work outcomes for employees of different ages. As the first study to

examine the moderating effect of age on the relationship between proactive personality and training

and development-related outcomes, this study contributes to and extends the literatures on personality,

training and development, older workers, and work motivation.

Acknowledgements

The authors thank Talya Bauer, David Cadiz and Kyle Mack for their helpful comments on this paper.

We also acknowledge Cristina Rizzi for work on the data collection. This research was funded by

Ministero dell’Istruzione, dell’Universita e della Ricerca (MIUR), Programmi di Ricerca Scientifica di

Rilevante Interesse Nazionale (PRIN), 2006, prot. 2006119348_003.

Marilena Bertolino’s term at University of Trento was supported by the postdoctoral fellowship from

Municipality of Rovereto (2006–2008).

Author biographies

Marilena Bertolino is an assistant professor of I/O Psychology at the University of Nice Sophia-

Antipolis, where she received her PhD in 2004. Her primary research interests are in the area of

discrimination in the workplace, including age stereotyping and other issues regarding older and

younger workers. She also conducts research on applicant reactions among minority and majority

groups in France, based on organizational justice theory. Moreover, she is interested in the antecedents

of workplace safety including the role of individual variables in relation to safety behavior.

Donald M. Truxillo is a professor in the Department of Psychology at Portland State University in

Portland, Oregon. His research interests include applicant and test taker reactions, older worker issues

including older worker stereotypes and motivation, and workplace safety. He is a fellow of the Society

for Industrial and Organizational Psychology and the American Psychological Association.

Franco Fraccaroli received his PhD from the University of Trento where he is currently a professor of

Work and Organizational Psychology. He is Director of the Department of Cognitive Science and

Education and past President of the European Association of Work and Organizational Psychology. His

research interests include organizational socialization, older workers and late career, and psychosocial

risks in organizations.


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References

Aiken, L., & West, S. (1991). Multiple regression: Testing and interpreting interactions. Newbury Park, CA: Sage.Alley, D., & Crimmins, E. (2007). The demography of aging and work. In K. S. Schultz, & G. A. Adams (Eds.),Aging and work in the 21st century (pp. 7–23). Mahway, NJ: Lawrence Erlbaum Associates.

Antonacopoulou, E. (2000). Employee development through self development in three retail banks. PersonnelReview, 29, 491–508.

Arthur, M., & Rousseau, D. (1996). The boundaryless career as a new employment principle. In M. Arthur, & D.Rousseau (Eds.), The boundaryless career: A new employment principle for a new organizational era (pp. 3–22).New York: Oxford University Press.

Baltes, P. B., & Baltes, M. M. (1990). Psychological perspectives on successful aging: The model of selectiveoptimization with compensation. In P. B. Baltes, & M. M. Baltes (Eds.), Successful aging: Perspectives from thebehavioral sciences (pp. 1–34). New York: Cambridge University Press.

Barak, B. (1987). Cognitive age: A new multidimensional approach to measuring age identity. InternationalJournal of Aging and Human Development, 25, 109–128.

Barrick, M. R., Stewart, G. L., & Piotrowski, M. (2002). Personality and job performance: Test of the mediatingeffects of motivation among sales representatives. Journal of Applied Psychology, 87, 43–51.

Bateman, T., & Crant, J. (1993). The proactive component of organizational behavior: A measure and correlates.Journal of Organizational Behavior, 14, 103–118.

Battistelli, A., & Odoardi, C. (2004). Les composantes individuelles et organisationnelles de la motivation a laformation des adultes salaries. In A. Lancry, & C. Lemoine (Eds.), Competences, Carrieres, Evolutions autravail (pp. 185–196). Paris: L’Harmattan.

Beier, M. E. (2008). Age and learning in organizations. In G. P. Hodgkinson, & J. K. Ford (Eds.), Internationalreview of industrial and organizational psychology (Vol. 23, pp. 83–105). Chicester, England: John Wiley &Sons Ltd.

Birren, J. E., & Birren, B. A. (1990). The concepts, models and history of the psychology of aging. In J. E.Birren, & K. W. Schaie (Eds.), Handbook of the psychology of aging (pp. 3–18). San Diego: AcademicPress.

Carlson, D., Bozeman, D., Kacmar, M., Wright, P., & McMahan, G. (2000). Training motivation in organizations:An analysis of individual level antecedents. Journal of Managerial Issues, 12, 271–287.

Carstensen, L. L., Isaacowitz, D., & Charles, S. T. (1999). Taking time seriously: A theory of socioemotionalselectivity. American Psychologist, 54, 165–181.

Cohen, J., Cohen, P., West, S., & Aiken, L. (2003). Applied multiple regression/correlation analysis for thebehavioral sciences (3rd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates.

Crant, J. M. (2000). Proactive behavior in organizations. Journal of Management, 26, 435–462.DeMeuse, K., Bergmann, T., & Lester, S. (2001). An investigation of the relational component of the

psychological contract across time, generation, and employment status. Journal of Managerial Issues, 13,102–118.

Ebner, N. C., Freund, A. M., & Baltes, P. B. (2006). Developmental changes in personal goal orientation fromyoung to late adulthood: From striving for gains to maintenance and prevention of losses. Psychology and Aging,21, 664–678.

Erdogan, B., & Bauer, T. N. (2005). When do proactive individuals feel successful in their careers? The role ofperson-job and person-organization fit. Personnel Psychology, 58, 859–891.

Farr, J. L., Tesluk, P. E., & Klein, S. R. (1998). Organizational structure of the workplace and the older worker. InK. Schaie, & C. Schooler (Eds.), Impact of work on older adults (pp. 143–185). New York: Springer PublishingCompany.

Finkelstein, L. M., & Farrell, S. K. (2007). An expanded view of age bias in the workplace. In K. S. Schultz, &G. A. Adams (Eds.), Aging and work in the 21st century (pp. 73–108). Mahway, NJ: Lawrence ErlbaumAssociates.

Freund, A. M. (2006). Age-differential motivational consequences of optimization versus compensation focus inyounger and older adults. Psychology and Aging, 21, 240–252.

Freund, A. M., & Baltes, P. B. (2000). The orchestration of selection, optimization, and compensation: An action-theoretical conceptualization of a theory of developmental regulation. In W. J. Perrig, & A. Grob (Eds.), Controlof human behavior, mental processes and consciousness (pp. 35–58). Mahwah, NJ: Erlbaum.


DOI: 10.1002/job


Gaillard, M., & Desmette, D. (2008). Intergroup predictors of older workers’ attitudes towards work and early exit.European Journal of Work and Organizational Psychology, 17, 450–481.

Greller, M. M., & Simpson, P. (1999). In search of late career: A review of contemporary social science researchapplicable to the understanding of late career. Human Resource Management Review, 9, 309–347.

Harvey, S., Blouin, C., & Stout, D. (2006). Proactive personality as a moderator of outcomes for younger workersexperiencing conflict at work. Personality and Individual Differences, 40, 1063–1074.

Hedge, J. W., Borman, W. C., & Lammlein, S. E. (2006). The aging workforce: Realities, myths and implicationsfor organizations. Washington, DC: American Psychological Association.

Judd, C. M., McClelland, G. H., & Culhane, S. E. (1995). Data analysis: Continuing issues in the everyday analysisof psychological data. Annual Review of Psychology, 46, 433–465.

Kanfer, R. (2009). Work motivation: Advancing theory and impact. Industrial and Organizational Psychology:Perspectives on Science and Practice, 2, 118–127.

Kanfer, R., & Ackerman, P. L. (2004). Aging, adult development, and work motivation. Academy of ManagementReview, 29, 440–458.

King, Z. (2004). Career self-management: Its nature, causes and consequences. Journal of Vocational Behavior,65, 112–133.

Major, D. A., Turner, J. E., & Fletcher, T. D. (2006). Linking proactive personality and the big five to motivation tolearn and development activity. Journal of Applied Psychology, 4, 927–935.

Maurer, T. J., & Tarulli, B. (1994). Perceived environment, perceived outcome, and person variables in relationshipto voluntary development activity by employees. Journal of Applied Psychology, 79, 3–14.

Maurer, T. J., Weiss, E. M., & Barbeite, F. G. (2003). A model of involvement in work-related learning anddevelopment activity: The effects of individual, situational, motivation, and age variables. Journal of AppliedPsychology, 88, 707–724.

McClelland, G. H., & Judd, C. M. (1993). Statistical difficulties in testing interactions and moderator effects.Psychological Bulletin, 114, 376–390.

Morgeson, F. P., Campion, M. A., Dipboye, R. L., Hollenbeck, J. R., Murphy, K., & Schmitt, N. (2007).Reconsidering the use of personality tests in personnel selection contexts. Personnel Psychology, 60, 683–729.

Motowidlo, S. J., & Van Scotter, J. R. (1994). Evidence that task performance should be distinguished fromcontextual performance. Journal of Applied Psychology, 79, 475–480.

Ng, T. W. H., & Feldman, D. C. (2008). The relationship of age to ten dimensions of job performance. Journal ofApplied Psychology, 93, 392–423.

Noe, R. (1986). Trainee attributes and attitudes: Neglected influences on training effectiveness. Academy ofManagement Review, 11, 736–749.

Rauch, A., & Frese, M. (2007). Let’s put the person back into entrepreneurship research: A meta-analysis on therelationship between business owners’ personality traits, business creation, and success. European Journal ofWork and Organizational Psychology, 16, 353–385.

Riordan, C. M. (2000). Relational demography within groups: Past developments, contradictions, new directionsIn G. R. Ferris (Ed.), Research in personnel and human resources management (Vol. 19, pp. 131–173).Greenwich, CT: JAI Press.

Roberts, B. W., Walton, K. E., & Viechtbauer, W. (2006). Patterns of mean-level change in personality traits acrossthe life course: A metaanalysis of longitudinal studies. Psychological Bulletin, 132, 3–27.

Seibert, S., Crant, J., & Kraimer, M. (1999). Proactive personality and career success. Journal of AppliedPsychology, 84, 416–427.

Sterns, H. L., & Miklos, S. M. (1995). The aging worker in a changing environment: Organizational issues. Journalof Vocational Behavior 47, 248–268.

Truxillo, D. M., & Weathers, V. M. (2005). Evaluation of a substance abuse training program for supervisors: Somepreliminary findings. Technical Report, Oregon Nurses Foundation, Portland, Oregon, USA.

Vroom, V. (1964). Work and motivation. New York: Wiley.Warr, P., & Birdi, K. (1998). Employee age and voluntary development activity. International Journal of Trainingand Development, 2, 190–204.

Warr, P., & Fay, D. (2001). Short Report: Age and personal initiative at work. European Journal of Work andOrganizational Psychology, 10, 343–353.

Whisman, M. A., & McClelland, G. H. (2005). Designing, testing, and interpreting interactions and moderatoreffects in family research. Journal of Family Psychology, 19, 111–120.


DOI: 10.1002/job


Appendix: Items for Proactive Personality, Training Motivation,and Perceived Career Development from Training

Proactive personality

(1) I

Cop

am constantly on the lookout for new ways to improve my life.

(2) I
f I see something I don’t like, I fix it.
(3) I
love being a champion for my ideas, even against others’ opposition.
(4) I
excel at identifying opportunities.
(5) I
am always looking for better ways to do things.
Training motivation

(1) I
will be able to apply on my job what I learn in the training activities.
(2) G
aining the skills provided by training activities will positively affect my performance.

(1) I
mprove my skills at work.
(2) U
se in my everyday job what I learned through training and experience.
(3) C
ontribute to improve the work in my organization.
(4) B
ecome more competent, having the possibility to take part at several specialized development
activities.

(5) A
pply on my job knowledge learned outside.
(6) B
e more able to solve problems at work.
(7) I
mprove my current level of discretion and responsibility.
yright # 2011 John Wiley & Sons, Ltd. J. Organiz. Behav. 32, 248–263 (2011)

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Documents

Age as moderator of the relationship of proactive personality with training motivation, perceived career development from training, and training behavioral intentions