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Human Resource DevelopmentInternationalPublication details, including instructions for authors andsubscription information:http://www.tandfonline.com/loi/rhrd20
Proactivity and work experienceas predictors of career-enhancingstrategiesDimitrios M. Mihail aa University of Macedonia , GreecePublished online: 07 Nov 2008.
To cite this article: Dimitrios M. Mihail (2008) Proactivity and work experience as predictors ofcareer-enhancing strategies, Human Resource Development International, 11:5, 523-537, DOI:10.1080/13678860802417668
To link to this article: http://dx.doi.org/10.1080/13678860802417668
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Proactivity and work experience as predictors of career-enhancing
strategies
Dimitrios M. Mihail*
University of Macedonia, Greece
The present study aims to enhance researchers’ understanding of career self-manage-ment behaviour by introducing proactivity along with human capital variables into theanalysis. By modelling employees’ career strategies, this empirical investigation assessesthe relative importance of human capital predictors as well as that of proactivepersonality. A survey was conducted using a structured questionnaire. There were 328participants in the survey, consisting of individuals working for firms across all sectorsof the Greek economy. Factor analysis was used to form implemented career strategiesreported in the survey. Regression analysis was applied for assessing the impact of eachpredictor on career self-management behaviour. The main findings indicate that theprimary sources behind shaping employees’ career strategies are their own proactivepersonality and their work experience in full-time jobs. The importance of combininghuman capital variables with employees’ proactivity in modelling career development isstressed by the present study.
Keywords: career development; proactivity
Introduction
In today’s volatile business environment of corporate mergers and takeovers, a company’slong-term commitment to employees’ job security and career development are disappear-ing. Each individual is responsible for his or her own career (Arthur 1994: Schein 1996;Adamson, Doherty, and Viney 1998; Cohen and Mallon 1999). Indeed, career-drivenindividuals perform diversified job tasks, developing new skills, acquiring knowledge,using different skill sets and accumulating human capital (Judge et al. 1995; Garavan,O’Brien, and O’Hanlon 2006; Nafukho, Hairston, and Brooks 2004; Zula and Chermack2007). This willingness to multi-task communicates a willingness to be employable andflexible in the workplace, thereby increasing one’s ability to remain marketable andmanage one’s own career. Furthermore, within the context of a protean, multi-employercareer orientation, individuals tend to enhance their career prospects by changingemployers across businesses and industries, facing new challenges and accumulatingvaluable work experience (Hall 1996, 2004; Arthur 1994; Arthur and Rousseau 1996;Arthur, Khapova, and Wilderom 2005; Baruch 2004; King 2003).
Working people need to not only update job specific skills but also prepare themselvesfor future jobs and new challenges in the workplace. In a constantly changing labour
*Email: [email protected]
Human Resource Development International
Vol. 11, No. 5, November 2008, 523–537
ISSN 1367-8868 print/ISSN 1469-8374 online
� 2008 Taylor & Francis
DOI: 10.1080/13678860802417668
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market (Capelli 1997, 1999; Gual and Ricart 2001), being in a continuous state ofpreparedness and developing an adaptive orientation to the job market seem to be keydeterminants of a career self-management strategy. In other words, environment-ledchanges such as waves of mergers and acquisitions and rapid technological advances leadcareer-driven individuals to become proactive (Crant 2000). Rather than reacting to theirworkplace changes, proactive individuals who are both aware and prepared for the futurechallenges can manage their own careers.
The present study aims to enhance researchers’ understanding of the determinants ofcareer self-management behaviour and hence to contribute to the human resourcedevelopment literature. Having mentioned both the importance of human capitaland proactive behaviour, this research seeks to complement human capital and careermobility predictors with proactive personality, as indicator of proactivity, in analysingcareer-enhancing behaviour (Seibert et al. 1999; Eby, Butts, and Lockwood 2003). Thus,modelling employees’ career strategies, this empirical investigation simultaneously assessesthe relative importance of human capital variables and the proactive personality indicator.This adds to existing research given that analysis of the impact of proactivity on careerself-management behaviour has been very limited so far. This article tries to shed light onthis issue introducing proactive personality as a predictor of an individual’s careerstrategies along with work experience, training, and career mobility for the Greek jobmarket.
The study is organized into five parts. The first part serves as an introduction, while thesecond presents the theoretical framework of the research and stipulates the researchhypotheses. The third discusses the research design providing information on the methodand data collection of the survey. The fourth presents the main findings of the empiricalresearch. Finally, the most important conclusions of the empirical investigation aresummarized.
Theoretical framework and research hypotheses
Competencies and proactivity shaping career self-management behaviour
During recent decades, corporate restructuring, delayering and massive waves ofdownsizing have resulted in workplace turbulence marked by job insecurity, flatterorganizational structures, fewer promotion opportunities and limited career prospects(Cappelli 1997; Appelbaum and Santiago 1997). Actually, even in fast growing firms,employers have been increasingly diverted from formal career management practices andlifelong career planning (Kossek et al. 1998).
In light of widespread corporate restructuring and economic uncertainty, scholars havepointed out that the core assumptions of the stable employment path and the employee’sorganizational commitment that have underpinned traditional notions of career are nolonger valid (Kanter 1989; Handy 1994; Arthur 1994; DeFillippi and Arthur 1994; Halland Mirvis 1995; Schein 1996; Peiperl and Baruch 1997). Systemic changes and workplacetransformation forcing a decoupling of individual careers from employing organizationslead individuals to form their own boundaryless, multidirectional careers (Baruch 2004),creating an even greater need for enhancing employability and accumulating social capital,namely networking, consultation and mentoring (Eby, Butts, and Lockwood 2003;Lambert et al. 2006; Mihail 2008).
In understanding boundaryless career behaviour, the present study relies on thecompetency-based perspective proposed by Defillippi and Arthur (1994). The know-howcompetencies according to the authors consist of knowledge and skills employees may
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possess not to accommodate specific performance requirements of an organization butrather to enhance their employability and potential in the workplace. The know-whomcompetencies relate to the individual’s efforts in forming a career-centred ‘social capital’rather than developing firm-centred networking and information. Such social capitalincludes networking, mentoring and consultation that extend beyond the employerenvironment to social contacts with family, acquaintances and, even more importantly,friends (Lin and Dumin 1986; Eby, Butts, and Lockwood 2003). The know-why careercompetencies are linked to employees’ concerted efforts to integrate their work experiencesinto a coherent individual career plan decoupling their own career paths from currentemployer’s job settings (Eby, Butts, and Lockwood 2003).
Even though concepts such as Hall’s protean career (Hall 1996, 2004; Hall and Moss1998) and Arthur’s boundaryless career (Arthur 1994; Arthur and Rousseau 1996; Arthur,Khapova, and Wilderom 2005) could frame an employee-centred career theory based onindividual’s accumulation of human and social capital (Defillippi and Arthur 1994), aparadox in the modern workplace must be taken into account. Along the lines of theboundaryless career perspective, more and more employees tend to assume greaterresponsibility for their careers, while corporate restructuring and fluid job marketsincrease the uncertainties of the future, thus deterring working people from committingresources to additional education and training.
Under these circumstances, proactive behaviour seems to be instrumental in allowingemployees to keep their own career on track (Bateman and Crant 1993, 1999). In fact, evenif someone is satisfied with his/her current job, it is imperative to keep an eye on the futureand exhibit proactive behaviour, i.e. have a proactive personality. Proactive behaviourstems from proactive personalities who can ‘intentionally and directly change their currentcircumstances’ in the labour market by scanning ‘for opportunities, show initiative, takeaction, and persevere until they reach closure by bringing about change’ (Bateman andCrant, 1993, 104–5).
A growing literature has used the concept of the proactive personality in theorizingcareer outcomes (Crant 2000). In approaching the traits of a proactive personalityempirically, Bateman and Crant (1993) devised the proactive personality scale that hasbeen incorporated into a series of pertinent studies. Thus, empirical research hasestablished relationships between proactive personality and job performance (Crant 1995),entrepreneurial intentions (Crant 1996), career success (Seibert, Crant, and Kraimer 1999;Seibert, Kraimer, and Crant 2001), proactive behaviour at work (Parker, Turner, andWilliams 2006) and job search (Brown et al. 2006).
Hypothesis setting
The present study, drawing both on the competency-based perspective and onproactive personality research, tests a model of career self-management behaviourand tries to expand our understanding of human resource development in corporateGreece. Based upon the above discussion, several research hypotheses may now bepostulated.
People have the opportunity to perform job tasks, learn new skills and use differentskill sets through work experience. This communicates a willingness to learn and faceversatile tasks, thereby increasing one’s ability to remain employable in the workplace.Along this line of reasoning, lack of such a work experience due to spells of unemploymentwould undermine an individual’s employability. In addition to work experience, training isessential to continue learning and adding skill sets. Continuously acquiring knowledge and
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new skills is a positive approach to career self-management that prevents the atrophy ofskills in a rapidly changing workplace. That is:
Hypothesis 1: Work experience, training and education are related positively to career-enhancing strategies, such as employability, networking, mentoring and career planning.Spells of unemployment are expected to undermine individuals’ career-enhancing strategies.
Another dimension of work experience is approached through career mobility.Promotions within organizations and relatively frequent employer changes might point toindividuals that besides developing updated skills are capable of cultivating upwardrelationships in the employing firm and know the ‘right people’ both in and outside theorganization. Career mobility behaviour leading to promotions and employer changes areindicative of career-driven individuals that are likely to commit themselves to career-enhancing strategies. That is:
Hypothesis 2: Promotions and employer changes are positively related to career-enhancingstrategies, such as employability, networking, mentoring and career planning.
Third, it is hypothesized that proactive personality is expected to enhance employee’sstrategies of career development. That is:
Hypothesis 3: Proactive personality will be related positively to an individual’s employability,networking, mentoring and career planning.
Methodology
Research design
The research design that was used to examine the research hypotheses mentioned above isbased on the replies of the participants that were surveyed. A set of questionnairestatements was aimed at exploring respondents’ concerted actions towards career buildingsuch as ‘enhancing employability’, ‘networking’, ‘mentoring’ and ‘career planning’ (Claesand Ruiz-Quintannila 1998). Another set of questionnaire statements was designed toconstruct the proactive personality scale using Bateman and Crant’s (1993) 17-itemmeasure.
Exploratory factor analysis with a principal components extraction was used to reducethe career behaviour items to a smaller number of uncorrelated variables or factors. Thus,factor analysis was performed and it was instrumental in identifying and thereforemeasuring certain career-centred behaviour. Furthermore, the study tried to model career-enhancing behaviour by regressing the identified factors of career strategies on theproactive personality scale, that of career mobility and work experience, along withpersonal and organizational characteristics. Regression analysis, therefore, led to someconclusions on the relative impact of certain predictors on pursuing distinct careerstrategies, such as employability, networking, mentoring and career planning.
Sample and survey instrument
Survey participants for this research were randomly selected working people who attendedseminars enhancing business-centred skills and knowledge such as accounting, finance andmarketing techniques and practices. These seminars, lasting two months, are financed by
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the participants and offered on a regular basis by the University of Macedonia, located inthe city of Thessaloniki. This sample design ensures that the sample included workingpeople who are career-driven individuals and at the same time have diversified educationaland professional backgrounds. The former sample characteristic is considered as necessaryto model career strategy behaviour and the latter as important in broadening thegenerality of the research findings.
In order to survey working people’s attitudes toward career-enhancing behaviour, astructured questionnaire was distributed to 328 employees attending seminars during a six-month period in 2006 and 2007. Participants in this survey were given an introductoryletter explaining the aim of the research, and were provided instructions on how tocomplete the questionnaire. These questionnaires also ensured absolute confidentiality.Questionnaires were administered during class and were filled out anonymously just afterthe completion of the class in the respondents’ free time. The researcher’s assistantscollected the questionnaires from the respondents immediately upon completion. A totalof 266 questionnaires were returned to the investigator, of which 252 were completedcorrectly in their entirety. The high response rate of 81% is because the participants in thesurvey were attending seminars organized and offered by the researcher’s faculty. Thesample was comprised of 163 women and 89 men. The respondents’ average age was 25years and more than 86% of the participants were under 30 years old. More than 68% ofthe surveyed people held a degree of higher education, 88% worked in the private sector,and 70% were under full-employment contract.
The structured questionnaire consisted of three sections. The first section was used forgathering personal and organizational information of the respondents. The second sectionincluded participants’ responses on 11 statements concerning career-enhancing actionswhich were empirically assessed using a Likert-scale format from 1 (not at all) to 5 (a greatdeal). The third section consisted of 17 statements pertinent to the proactive personalityscale. Respondents’ replies on proactivity were also assessed by a seven-point Likert scaleranging from 1 (I strongly disagree) to 7 (I strongly agree).
Measures
The dependent variables were measured using multi-item scales. The career-enhancingstrategy items were adapted from a previous empirical study on career development (Claesand Ruiz-Ouintanilla 1998) that in turn was based on Bachman, O’Maley, and Johnston(1978), and Penley and Gould (1981). An exploratory factor analysis of 11 items indicatedfour indices of career strategies (dependent variables). The response items, the extractedfactors, and coefficient alpha reliability estimates are presented in the findings section(Table 1).
The first set of predictors represents human capital variables. As Becker (1993)maintains, besides formal education, individuals invest in additional types of human capitalsuch as on-the-job training, formal training and any other knowledge that could potentialincrease their command of their career prospects. Within this framework, the present studyintroduces all the main types of work experience – full-time employment, temporary, part-time work and internships – to empirically approximate the dimension of on-the-jobtraining, along with formal training and education. Thus, the employment variables includethe length (in months) of work experience on full-time, temporary, part-time employmentcontracts, internships, formal training programmes and unemployment. While theeducation level variable (0 ¼ basic education and high school diploma, 1 ¼ highereducation degree) accounts for the formal education dimension of human capital.
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Table
1.
Exploratory
factoranalysisforcareer-enhancingbehaviours.
Questionnairestatements
andfactors:Career-enhancing
behaviour
Enhancing
employability
Mentoring
Networking
Career
planning
Factormeans
(SD)
FactorI.Enhancingem
ployability(Cronbach’salpha¼
0.76)
3.49(.80)
‘Ihavedeveloped
skills
thatmay
beneeded
infuture
job
positions’
.776
‘Ihavegained
experience
inavarietyofwork
assignments
toincrease
myknowledgeandskills’
.848
‘Ihavedeveloped
more
knowledgeandskillin
taskscriticalto
mywork
unit’soperation’
.764
FactorIII.Mentoring(Cronbach’salpha¼
0.69)
2.82(1.04)
‘Ihaverecentlysoughtadvicefrom
myco-w
orkers,familyor
other
people
aboutadditionaltrainingorexperience
Ineed
toim
provemyfuture
work
prospects’
.777
‘Since
Ihave
worked
here
Ihaveinitiated
talkswith
my
supervisorabouttraining
orwork
assignments
Ineed
todevelopskillsthatwillhelpmyfuture
work
chances’
.763
‘Ihavemademysupervisoraware
ofmywork
aspirationsand
goals’
.658
FactorII.Networking(Cronbach’salpha¼
0.71)
3.33(1.08)
‘Ihavebuiltanetwork
ofcontactsorfriendshipswithother
employeesto
obtain
inform
ationabouthow
todomywork
orto
determinewhatisexpectedofme’
.873
‘Ihavebuiltanetwork
ofcontactsorfriendshipswith
co-w
orkersorother
people
toprovidemewith
help
or
advicethatwillfurther
mywork
chances’
.800
FactorIV
.Career
planning(Cronbach’salpha¼
0.65)
3.78(.96)
‘Ihavebegunto
thinkmore
aboutthekindofwork
forwhichI
am
bestsuited
since
Ibeganworkingin
mypresentjob’
.828
‘Ihaverecentlybegunto
thinkmore
aboutwhatIwould
like
toaccomplice
inmywork
duringthenextyearortw
o’
.827
Explained
variance
0.19
0.18
0.15
0.16
Eigenvalues
2.08
1.97
1.67
1.70
Note:N¼
238;Varimaxrotationwasusedandloadingswasusedandloadingsgreaterthan0.50are
reported;Thefiverotatedfactors
accountedfor53%
ofthetotal
variance;Factormeansare
inbold
andstatements
wereratedonafive-pointLikert-typescale
(1,‘notatall’,5,‘a
greatdeal’).
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Another set of predictors represent career mobility variables such as organizationalpromotions and employer changes. Following Crant (1995) and Seibert, Crant, andKraimer (1999), proactive personality was added as a predictor in theorizing about careerbehaviour. Proactive personality was measured with 17 questionnaire items adapted fromBateman and Crant (1993). Sample items from this scale are: ‘I enjoy facing andovercoming obstacles to my ideas’, ‘I excel at identifying opportunities’ and ‘When I havea problem, I tackle it head-on’ (Appendix, Table 1A). Responses ranged from (1) ‘stronglydisagree’ to (7) ‘strongly agree’. The Cronbach’s alpha of the scale was 0.86 (X ¼ 4.69,SD ¼ 0.79).
Besides the predictors in modelling career strategies, control variables were used in theregression analysis to account for the influence of personal and organizationalcharacteristics. Main demographic characteristics, such as gender (0 ¼ female, 1 ¼ male)and age were used as control variables. Considering organizational-industry controls, itwas hypothesized that in contrast to private employees, civil servants and managers instagnant career paths, with seniority as the main criterion for career advancement, will nothave strong motives toward career self-management behaviour (Kufidu, Petridou, andMihail 1997). Further, one needs to control for the effects of working for a small companywith strong atypical employment relations. These can be found within the stagnantmanufacturing industry and have a diverse effect on an individual’s career behaviour(Mihail 2003, 2004, 2008). Thus, organizational-industry controls were company size(1 ¼ 200 þ employees, 0 ¼ less than 200), economic sector (1 ¼ private, 0 ¼ public) andthe manufacturing industry (1 ¼ manufacturing, 0 ¼ services).
Findings
A factor analysis was conducted to determine the dimensionality of respondents’ career-enhancing behaviour. Table 1 presents the factors obtained, the variables and the meanscore of each factor, and the factor loadings. Factor analysis was used with varimaxrotation on the 11 career statements. Tests for appropriateness, including the Bartlett Testof Sphericity and the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy werethen performed. These tests indicated that the factor analysis was an appropriatetechnique for career variables (KMO ¼ 0.77).
Four factors were extracted, accounting for 68% of the variance in working people’scareer-centred statements. All factors were internally consistent and well defined by thevariables with Cronbach alpha scores ranging from 0.65 to 0.76, with a 0.6 cut-off(Eisenhardt 1988, 510).
Scores represent significant factor loadings (i.e. above 0.5) of individual scale items oneach of the four factors (Finkelstein 1992, 519–20). Thus, the statement ‘I have a welldeveloped plan for the next few years of my work future’ concerning career planning wasdropped by using item loadings higher than 0.50. Apart from factor loadings for eachsingle statement, the mean for each single factor (as the average score of the means of itsconstituent items) is illustrated in Table 1.
The first factor of the career strategy items is labelled ‘enhancing employability’(Cronbach’s a ¼ 0.76) and respondents’ mean score 3.49 indicates a relatively highpreference for pursuing career actions aimed at building up high levels of job skills, workexperience and job-related knowledge.
The second factor is labelled ‘mentoring’ (Cronbach’s a ¼ 0.64) and includesstatements that refer to social behaviour systematically seeking advice and assistancefrom key persons at work such as supervisors and colleagues. Respondents are certainly
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quite active in seeking ‘mentoring’ (mean score 2.82), even though it seems not to be theirfirst priority.
The third factor is labelled ‘networking’ (Cronbach’s a ¼ 0.71) and consists ofconcerted actions directly related to career networking. Respondents’ mean score 3.33shows that enacting social contacts is considered vital in building up career prospects.Hence, mentoring and, even more importantly, networking tend to accumulate socialcapital, which in combination with human capital enhancement are perceived as the basisfor career-enhancing behaviour by working people.
Apart from accumulating human and social capital, participants rate the self-management of their own careers very high (mean score 3.78). Thus, the fourth factorlabelled ‘career planning’ (Cronbach’s a ¼ 0.65), consists of career self-managementbehaviour, which tends to shape career prospects. It becomes evident from the relativelyhigh mean score of 3.78 that respondents commit ample effort and time in designing theirown career, a trend that is consistent with the emergence of a ‘new career’ orientationamong high-skilled employees in Greece (Mihail 2008).
Table 2 shows the means, standard deviations, and inter-correlations among thevariables in the study. As one can see, no high correlations between the independentvariables exist, thus multicollinearity seems not to be a problem. To assess therelationships between predictors included in the analysis more rigorously, a moresophisticated collinearity statistic was estimated: the Variance Inflation Factor (VIF). Thevalue of the statistic for each single independent variable was much lower than the criticalvalue of two (Miles and Shelvin 2001), indicating that the predictors of the study can beincluded in multiple regression analysis.
Hierarchical regression analysis was instrumental in examining the hypothesizedrelationships between alternative sets of predictors and career-enhancing behaviour. Morespecifically, hierarchical regression procedure was used in order to determine theincremental effect of the employment, career mobility variables and the proactivepersonality scale on career strategies, after controlling for personal and organizationalvariables. There is a separate regression equation for each of the four dependent variables:employability, networking, mentoring, and career planning. Following the recommenda-tions of Cohen and Cohen (1983), the control variables were entered first. In the third stepof each equation, ‘employment variables’ were entered. In the fourth step, the careerstrategies were regressed on career mobility variables such as job position changes, careerpromotions, and employer changes. The proactive personality scale was entered in thefinal step in the hierarchical regression.
To estimate the direct effects of each single control and independent variable on thedependent variables, the standardized regression coefficients were used in the statisticalanalysis, often called b weights. These standardized coefficients allow for directcomparison of the relative strengths of relationships between predictors and dependentvariables. Table 3 summarizes the results, providing beta values and significance levels forthe single variables. The total explained variance, R2, is illustrated for each of the fourequations at the bottom of Table 3.
The regression analysis suggests that personal characteristics do not play an importantrole in career-enhancing behaviour. The only one exception is age exerting some influenceon employability. Age is positively associated with skill accumulation and employabilityand its effect is in the expected direction (b ¼ 0.22; p 5 0.01).
Only two organizational variables, firm size and economic sector, had an impact onsome of the career-enhancing behaviour. The development of informal, intimate employeerelations in small and medium-sized companies (Mihail 2004), in contrast to large
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Table
2.
Means,standard
deviationsandintercorrelationsamongstudyvariables.
MSD
12
34
56
78
910
11
12
13
14
15
16
17
18
1.G
ender
.353
.478
–2.Age
25.41
5.148
7.012
–3.Industry
.103
.3049
7.032
.052
–4.Sector
.884
.320
.165
.028
.042
–5.Firm
size
.131
.338
7.238
7.047
7.093
7.302
–6.Full-tim
eem
ployment
15.93
30.49
7.142
.523
.014
7.138
.124
–7.Tem
porary
employment
2.89
6.023
7.006
7.081
7.055
7.090
7.020
7.144
–8.Part-tim
eem
ployment
3.63
9.931
7.006
7.104
7.047
.014
7.053
7.108
.064
–9.Work-studyexperience
10.23
12.928
.131
.065
7.014
.088
7.001
.147
.093
.344
–10.Unem
ployment
2.72
6.032
7.102
.151
7.027
.021
.004
.028
.052
7.017
.020
–11.Training
1.74
3.418
7.124
.276
.153
.021
7.067
.076
.021
.061
.046
.142
–12.Education
.676
.468
.009
.370
.096
7.004
7.144
.160
7.021
7.069
.021
.240
.113
–13.Promotions
.17
.482
.025
.255
.067
.080
7.068
.128
7.037
7.056
.100
7.012
.371
.128
–14.Changes
ofem
ployers
.92
1.119
7.022
7.140
.188
.175
.007
7.109
.140
7.008
.007
.040
7.029
7.022
.033
–15.Proactivitypersonality
4.685
.790
.140
.161
7.086
7.056
7.051
.051
7.077
.036
.095
7.067
.048
.031
.131
–.027
–16.Employability
3.495
.801
7.056
.229
.100
7.013
7.024
.255
7.042
.045
.143
7.117
.160
.122
.209
–.006
.230
–17.Networking
3.325
1.080
.058
7.049
7.048
7.058
7.014
.039
.023
.068
.029
7.103
7.020
7.094
.158
.010
.189
.308
–18.Mentoring
2.816
1.048
.045
.004
7.065
.001
7.142
.072
7.066
7.001
.100
7.016
.090
.120
.090
.001
.102
.312
.398
–19.Career
planning
3.779
.963
.022
.100
.057
.190
7.027
.147
7.080
.053
.116
.053
7.008
.049
.036
.067
.148
.278
.217
.299
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organizations, seem to encourage employees to get involved in mentoring (b ¼ 0.15;p 5 0.05). Private employing organizations, in contrast to public ones (Kufidu, Petridu,and Mihail 1997), tend to condition working people’s career planning favourably(b ¼ 0.18; p 5 0.01).
Human capital variables encompassing work experience, training, and education wereentered as a separate block of predictors in the third step. Together, the human capitalvariables produced a significant increase in the amount of variance explained inemployability and mentoring strategies. This set of predictors explained an additional9% of the variance in employability (p 5 0.01) and 6% of the variance in mentoring(p 5 0.05). In fact, human capital was the strongest among the alternative sets ofpredictors for enhancing employability and mentoring. Still, the results show that thehuman capital did not have a significant effect on the other two career strategies. Studyingthe beta weights, the analysis shows that full-time work experience was a significantpredictor for employability (b ¼ 0.21; p 5 0.01), career planning (b ¼ 0.17; p 5 0.05),and marginally significant for mentoring (b ¼ 0.14; p 5 0.10). In contrast to full-timework experience, working on atypical employment contracts seem not to affect anydimension of career-enhancing behaviour. The length of unemployment, as expected, hada negative impact on behaviour concerning skill development (b ¼ 70.17; p 5 0.01),while the attendance of training programmes is marginally significant for employabilityenhancement (b ¼ 0.13; p 5 0.10) and mentoring (b ¼ 0.13; p 5 0.10).
The fourth set of predictors labelled ‘career mobility’ variables exerted a significanteffect only on networking. In fact, it is the strongest effect on networking accounting for anadditional 4% (p 5 0.05) of the variance in building up personal contacts. Morespecifically, promotions are significantly related to networking (b ¼ 0.21; p 5 0.01),whereas changes in employers do not have any significant impact on networking or on anyother career-enhancing behaviour.
The proactive personality scale, entered at the final step in the hierarchical regressions,was significantly related to all the career strategies except mentoring. A proactivepersonality was found to produce a significant increase in the amount of varianceexplained by the employability equation (DR2 ¼ 0.03; p 5 0.01; b ¼ 0.19; p 5 0.01).Actions aimed at networking (DR2 ¼ 0.024; p 5 0.05; b ¼ 0.16; p 5 0.05), and careerplanning (DR2 ¼ 0.027; p 5 0.01; b ¼ 0.17; p 5 0.01) were also found to be influencedsignificantly by the proactive personality variable.
Discussion
This exploratory study, surveying 252 working individuals, attempted to measure and tomodel main dimensions of their career-enhancing behaviour. Factor analysis led to fourtypes of career strategies: enhancing employability, engaging in career planning, andbuilding up social capital through active networking and mentoring. The main findingsindicated that respondents were particularly involved in career strategies that aimed atenhancing their employability and career planning and to a lesser extent at building uptheir social capital.
A series of hierarchical regression analyses was conducted to assess the relative impactof various sets of determinants on career strategies. Of the human capital variables, onlythe full-time work experience seems to have a significant impact on two dimensions ofcareer-enhancing behaviour: employability and career planning. By contrast, atypicalforms of work, such as part-time employment, contingent jobs and internships do not haveany impact on career self-management behaviour. This can be easily understood in the
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Table
3.
Regressing
career-enhancing
behaviouron
personaland
organizationalcharacteristics,human
capital,
career
mobility
and
proactive
personality
scale.
Employability
Networking
Mentoring
Career
planning
St.Beta
Sig.
St.Beta
Sig.
St.Beta
Sig.
St.Beta
Sig.
I.PersonalvariablesDR2
.052
.002
.005
.514
.003
.714
.011
.263
Gender
(0¼
female,1¼
male)
7.052
.405
.055
.390
.051
.423
.019
.765
Age
.220
.000
7.048
.454
.012
.851
.103
.107
II.OrganizationalvariablesDR2
.009
.508
.007
.617
.025
.110
.034
.039
Industry
(1¼
manufacturing,0¼
services)
.091
.149
7.043
.502
7.080
.215
.045
.479
Sector(1¼
private,0¼
public)
7.008
.905
7.077
.253
7.034
.606
.184
.006
Firm
size
(1¼
200þ
employees,0¼
2–199em
ployees)
7.023
.731
7.030
.663
7.153
.026
.027
.694
III.HumancapitalvariablesDR2
.088
.002
.027
.486
.058
.043
.038
.222
Full-tim
ework
experience
.214
.005
.117
.145
.140
.076
.170
.031
Tem
porary
work
experience
7.040
.515
.017
.793
7.069
.286
7.041
.522
Part-tim
ework
experience
.046
.488
.069
.329
7.045
.509
.062
.367
Educationwork
experience
.074
.277
7.021
.773
.100
.158
.050
.481
Unem
ploymentexperience
7.174
.006
7.088
.186
7.032
.620
.046
.477
Training
.127
.055
.017
.807
.134
.051
7.043
.527
Education(0¼
basic,
1¼
higher)
.051
.441
7.076
.278
.127
.065
.023
.737
IV.Career
mobilityvariablesDR2
.010
.261
.037
.011
.003
.712
.002
.826
Promotions
.108
.112
.211
.003
.032
.652
7.018
.797
Employer
changes
.019
.769
.026
.695
.044
.510
.039
.565
V.Proactivepersonality
scale
DR2
.033
.002
.024
.014
.007
.185
.027
.009
PPS
.193
.002
.164
.014
.089
.185
.173
.009
Adjusted
R2
N¼
252
.139
.042
.036
.052
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Greek labour market context, where atypical forms of employment are firmly linked tolow-paid jobs with practically limited career prospects (Giannikis and Mihail 2007). Aswas expected, unemployment was found to have a significant negative effect onemployability, since it reduces opportunities for skill utilization and development (Warr1987). Even though marginally significant, training tends to enhance both skilldevelopment and consultation with senior personnel in organizations. Therefore,Hypothesis 1 was supported partially by the empirical analysis.
Upward mobility within an organization and ‘outward’ mobility through employerchanges are found not to be important in explaining variation in career self-managementbehaviour. The only exception is the significant effect of promotions on developing socialnetworks with peers and senior personnel. Quite expectedly, ascending the corporateladder allows working people to expand networking and thus enhance career prospects.Therefore, the study’s results indicate limited support for Hypothesis 2.
Along with widely used predictors, such as stable employment, training and priorcareer achievement, proactivity seems to be instrumental in analysing career-shapingbehaviour. Specifically, the proactive personality scale is related positively to employ-ability, networking and career planning, but not to mentoring. These findings providesubstantial support for hypothesis 3 that states that proactive personality is a significantpredictor of career-enhancing behaviour, and therefore it seems very useful in careermodelling (Crant 1995, 1996; Seibert, Crant, and Kraimer 1999).
In the current study, the demographic and organizational variable sets add anaemicexplanatory power in predicting career-enhancing behaviour. Still, controlling fororganizational variables, such as economic sector and firm size, seem to be imperative inmodelling career strategies in the Greek labour market context. Even though firm size is aninsignificant variable for the most of the career strategies, it is related negatively tomentoring. Apparently, working people seek consultation and support for building theircareers from proprietors of small firms but not from senior managers in largeorganizations. This is an expected result for the Greek case, since patron-clientrelationships among small proprietors and their employees are typical and pivotal inmanaging human resources in small and medium-sized companies (Mihail 2004). Withinthe same context, the finding that being employed in the Greek private sector enhancescareer planning is not surprising at all. By contrast, career planning as a career self-management strategy seems to be obsolete in the public sector where career advancement isstrictly determined by employee’s seniority (Kufidu, Petridu, and Mihail 1997).
Overall, the complete regression model accounted for significant variance only in twocareer strategies: employability enhancement (adjusted R2 ¼ 0.14; p 5 0.01) and careerplanning (adjusted R2 ¼ 0.05; p 5 0.05). For enhancing employability, age, full-timework experience, the length of training and proactive personality, as was hypothesized,had a significant positive effect. Quite expectedly, the length of unemployment exerted anegative effect on skill development and employability. For initiatives leading to careerplanning, as was expected for the Greek case, being someone employed in a private insteadof a public company had a significant positive effect. Among the predictors, only full-timework experience along with possessing a proactive personality seems to condition careerplanning favourably.
By contrast, the model did not explain significant variance in the two measures ofsocial capital, namely networking and mentoring. The analysis indicated that onlypromotions within the employing organizations and proactive personality are positivelyassociated with networking. As concerns mentoring behaviour, respondents who work forrelatively small-sized companies with close employee–employer relationships were foundto seek career-related advice and guidance systematically. Besides this control variable,
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full-time work experience, training schemes and higher education were singled out asmarginally significant predictors for mentoring strategy.
Conclusion
Implications of the study
To my knowledge, this empirical study is the first attempt to measure and to model themain dimensions of career-enhancing behaviour in corporate Greece. Factor analysis ledto four types of career strategies: enhancing employability, engaging in career planning,and building up social capital through active networking and mentoring. The mainfindings indicated that respondents were particularly involved in career strategies thataimed at enhancing their employability and career planning and to a lesser extent atbuilding up their social capital.
Hierarchical regression analysis allowed us to assess the relative impact of various sets ofpredictors on career strategies. Thus, in modelling career-enhancing behaviour, aftercontrolling for personal and organizational effects, proactivity emerged as the main predictorhaving a positive impact on almost every dimension of career-related behaviour. Thus,despite its relatively recent introduction into the organizational literature, the present studyindicated that proactive personality could have considerable utility in analysing humanresource development issues. Among human capital variables, full-time employment andtraining, to a lesser extent, emerged as significant determinants of career-building behaviour.By contrast, contingent work did not have any impact on self-management career behaviour.In addition, the block of predictors concerning career mobility did not have any significantimpact on the dependent variables, with the exception of organizational promotions thatseem to facilitate active networking. Overall, the study contributes to human resourcedevelopment literature by demonstrating the influence of proactivity, along with traditionalhuman capital variables, in modelling career self-management behaviour.
Limitations of the study
The findings of this study are not without limitations. In this exploratory investigation, thesize and the geographical coverage of the sample on which the results were based arerelatively small, so conclusions must be drawn with caution. Further extensive researchsurveying more working people across the whole country would lead to findings that aremore reliable. Furthermore, the findings of this paper may not be applied easily to other,more specific samples of working youth, such as working graduates, young professionalsand managers. Examining and comparing attitudes among employers, senior managersand working people would certainly allow for a more articulated discussion of the mainsources of influence on career-enhancing behaviour in corporate Greece.
Future research along the lines suggested above can enhance our understanding ofyoung employees’ career development in Greece. Such knowledge is vital, because it iseconomically imperative for the country to allow an ever-increasing number of well-educated people to pursue career advancement in the business world.
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Appendix
Table 1A. The proactive personality scale.*
1. I am constantly on the lookout for new ways to improve my life2. I feel driven to make a difference in my community, and maybe the world3. I tend to let others take the initiative to start new projects4. Wherever I have been, I have been a powerful force for constructive change5. I enjoy facing and overcoming obstacles to my ideas6. Nothing is more exciting than seeing my ideas turn into reality7. If I see something I don’t like, I fix it8. No matter what the odds, if I believe in something I will make it happen9. I love being a champion for my ideas, even against others’ opposition10. I excel at identifying opportunities11. I am always looking for better ways to do things12. If I believe in an idea, no obstacle will prevent me from making it happen13. I love to challenge the status quo14. When I have a problem, I tackle it head-on15. I am great at turning problems into opportunities16. I can spot a good opportunity long before others can17. If I see someone in trouble, I help out in any way I can
*Bateman and Crant (1993).
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