MSc in Business Administration- Leadership and Management track
Positioning career self-management behaviors as adapting
strategies: their relationship with career adaptability, job performance
and turnover intentions. The role of mentoring support.
Iliyana Hristova DAKOVA 11085029
Thesis supervisor:
Sofija Pajic
Statement of originality
This document is written by Student Iliyana Hristova Dakova who
declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document is
original and that no sources other than those mentioned in the text and
its references have been used in creating it.
The Faculty of Economics and Business is responsible solely for the
supervision of completion of the work, not for the contents.
Guided by the Career Construction Theory (Savickas & Porfeli, 2012), the present study tests the positioning career self-management behaviors (King, 2004) in their role of adapting responses. The research model posits that individuals employ their career adaptability resources in four adapting strategies, namely strategic choice of mobility opportunity, strategic investment in human capital, active network development and job content innovation. The paper investigates the relationships between career adaptability and both turnover intentions, and job performance. The conceptual model was tested using a cross-sectional survey of 298 employees and 41 employee-supervisor dyads. The translated Career Adapt-Abilities Scale (CAAS) Bulgaria form was also validated, and showed internal consistency of (ɑ = .91). The results show that with the exception of job content innovation, positioning career self-management behaviors explain the indirect relationship between career adaptability and turnover intention. Strategic investment in human capital and active network development help decrease the levels of turnover intentions. In addition, the perceived supervisory support weakens the positive indirect relationship between career adaptability and turnover intentions. It was also found that there is a positive indirect relationship between career adaptability and job performance, mediated by strategic investment in human capital. The overall findings of the research add to the theory on the underlying behavioral mechanism in career adaptation. The results of the study also help understand the role of the perceived supervisory support in combination with career self-management strategies.
Keywords: Career adaptability; Adaptive behaviors; Career self-management behaviors; Networking; Job content innovation; Supervisory support; Turnover intentions; Job performance.
Introduction ... 1 1. Literature review...5 1.1. Career adaptability...5 1.2. Adapting...6 1.3. Career self-management...7 1.4. Adaptation...10 1.4.1. Turnover intentions...10 1.4.2. Job performance...13
1.5. Supervisor mentoring support- career development and socioemotional support………...17
1.6. Conceptual model...21
2. Method and data...22
2.1. Sample...22 2.2. Measures...23 3. Results...27 3.1. Statistical procedure...27 3.2. Descriptive statistics...28 3.3. Hypotheses testing...30
3.3.1. Career adaptability and positioning career self-management behaviors………...30
3.3.2. Career adaptability and turnover intentions………...34
3.3.3. Career adaptability and job performance………...40
4. Discussion...43
4.1. Theoretical implications...48
4.2. Practical implications...49
4.3. Limitations and suggestions for future research...50
5. References...52
Appendix A: Questionnaire Employee Version...64
Appendix A: Questionnaire Supervisor Version...69
Appendix A: CAAS Bulgaria Translation...72
Appendix B: Table 15. Model testing the moderated indirect relationships between career adaptability and job performance...73
Table 1. Means, Standard deviations, Correlations, Reliability scores
Table 2. Hierarchical regression model testing the relationship between career adaptability resources and strategic investment in mobility opportunities
Table 3. Hierarchical regression model testing the relationship between career adaptability resources and strategic investment in human capital
Table 4. Hierarchical regression model testing the relationship between career adaptability resources and active network development
Table 5. Hierarchical regression model testing the relationship between career adaptability resources and job content innovation
Table 6. Testing mediating role of strategic choice of mobility opportunity in career adaptability- turnover intentions link
Table 7. Testing mediating role of strategic investment in human capital in career adaptability- turnover intentions link
Table 8. Testing mediating role of active network development in career adaptability- turnover intentions link
Table 9. Testing mediating role of job content innovation in career adaptability- turnover intentions link
Table 10. Model testing the moderated indirect relationships between career adaptability and turnover intentions
Table 11. Testing mediating role of strategic choice of mobility opportunity in career adaptability- job performance link
Table 12. Testing mediating role of strategic investment in human capital in career adaptability- job performance link
Table 13. Testing mediating role of active network development in career adaptability- job performance link
Table 14. Testing mediating role of job content innovation in career adaptability- job performance
Introduction
Today we live, work and play in conditions of rapid change in technologies, organizations and society. In these ambiguous and changing circumstances, people become more aware of and responsible for their own careers. In the era of the new careers, individuals need to be flexible and self-directed (Sullivan,1999). It is essential to respond quickly to changes, to be ready and able to adapt, to take action and to make choices that drive one’s career. The common goal that people have is to find a good fit and be successful and happy. And although most individuals share common goals, they all differ in the way they achieve these goals. People are not equally willing and able to change and adapt, nor are they engaging in the same strategies to achieve their goals.
When people look ahead and prepare for the future, they explore different scenarios, employ effort and build confidence to reach their goals. The abilities of concern, control, curiosity and confidence form the concept of one’s career adaptability (Savickas & Porfeli, 2012). These are the four resources that help individuals solve problems and deal with change in order to achieve their ultimate goal, to be successful and happy. The question how people
achieve their adaptation goals, or what adapting behaviors they choose to engage in,
however, is underexplored in the literature.
Adaptation is the consequence of the adapting behaviors that allow people to master their vocational development tasks, to cope with occupational transitions, and to adjust to work traumas and contingencies (Savickas & Porfeli, 2012). Although individuals might have the same adaptation goals, they differ in their career adaptability resources, as well as in the combination of behaviors they choose to employ these resource in, in order to achieve their goals. Adaptation is motivated and guided by the goal of individuals to bring inner needs and outer opportunities into harmony (Savickas & Porfeli, 2012). It can be expected that, in the work context, reaching adaptation harmony is expressed by the intentions of employees to leave or stay in the organization.
Research to date on the career adaptability- turnover intentions link reports contradictory results. Ito & Brotheridge, (2005) found career adaptability to be positively related to turnover intentions, while other studies find negative relationship between career adaptability and turnover intentions (Chan & Mai, 2015, Chan et al. 2016). The questions if
and how career adaptability is related to turnover intentions, as well as under what conditions this relationship occurs, have important implications for the practice. We can
expect that people who are more adaptable engage in a range of strategies to manage their careers proactively (Raabe, Frese and Beehr, 2007) and regulate fit with the company. They develop their skills and competencies, create more connections, find innovative ways to do their jobs, adapt better to changes, grasp more opportunities (Seibert et al.,2001, King, 2004). But are all of these strategies equally influential for triggering the intentions to leave or stay
in the company? This study aims to answer these questions by exploring further the
mechanisms of the relationship between career adaptability and turnover intentions.
Another question that arises from the contradictory research findings on the career adaptability- turnover intentions link is that of a possible factor(s) that might condition the relationship. Does the relationship between career adaptability –turnover intentions depend
on a third factor? Building on the Career Construction Theory (Savickas & Porfeli, 2012), I
suggest that different factors of the environment can set conditions under which the career adaptability – turnover intentions relationship is altered. The present research addresses the existing gap in the literature on this issue, by examining the effects of the perceived supervisor support in the career adaptability- turnover intentions relationship. Supportive supervisors contribute to job retention, both directly and through increased levels of affective commitment and perceived organizational support (Eisenberger et al., 2002, Maertz et al., 2007, Payne and Huffman, 2005). It is of interest to investigate further what is the role of supervisory support in the relationship between career adaptability and turnover intentions,
when individuals are more proactive and show more personal initiative (Seibert et al., 1999), expressed in career self-management behaviors (King, 2004).
A second, related adaptation goal that this study aims to investigate is job performance. In the existing research on career adaptability, the relationship between career adaptability and job performance is underexplored. Career adaptability has been found positively related to both salary and promotability (e.g. Chan, Mai, Kuok, Kong, 2016). One recent study found a positive relationship between career adaptability and job performance using a policy-capturing design (Ohme and Zacher, 2015). Job performance, however, is a complex construct with more dimensions, such as innovative and adaptive performance (Koopmans et al., 2011), and requires to be studied further in actual work settings. From the aforementioned evidence we can expect that employees who are more adaptable will perform better. But, some questions remain. Will all adaptive strategies influence job performance
equally? Are there other factors from the environment that might condition the relationship?
This study aims to explore the mechanisms of the relationship between career adaptability and job performance and answer the question how the perceived supervisor support
conditions this relationship.
This paper focuses on the outcomes in terms of turnover intentions and job performance for two reasons. Both turnover intentions and job performance have been found as directly related to turnover behavior (Tett and Meyer, 1993, Allen and Griffeth, 1999, Zimmerman and Darnold, 2009). This has important practical implications, since voluntary turnover causes the business to lose talent (Trevor, Gerhart and Boudreau, 1997). Therefore, investigating further the antecedents of turnover intentions and job performance can be beneficial for the business. Exploring the career adaptability-turnover intentions and career adaptability-job performance links, and how different adapting strategies mediate these relationships, can help companies make decisions regarding the selection, development and
retention of key employees. For example, if more adaptable employees have higher job performance than less adaptable employees, career adaptability can be included in the personnel selection process and career development programs. Also, if more adaptable employees are found to have higher turnover intentions, knowing the strategies that individuals higher on career adaptability engage in, can help the organization spot behaviors likely to lead to turnover intentions and turnover.
This research aims to answer the aforementioned questions and to contribute to the literature on the sequential network of career adaptation, investigating the relationships between career adaptability, adapting and distal outcomes. Firstly, as suggested by Hirschi and Valero, (2015), I will look deeper into adaptation process by investigating different adapting behaviors (e.g., networking behaviors and training participation). Secondly, I will investigate the conditioning role of supervisor mentoring support. Whereas supervisory support has been evidenced as an important determinant of employee performance (Edmondson & Boyer, 2003) and negatively related to turnover (Edmondson & Boyer, 2003). Tolentino, Garcia, and Lu, (2014) also recognized the need to test supervisor support as situational variable in empirical research on career adaptability. Thirdly, with this paper I also answer the call for future research to explore job performance as an adaptation outcome of career adaptability (Chan & Mai, 2015). Finally, due to previously mentioned conflicting findings about the relationship between career adaptability and turnover intentions, the mechanisms of the indirect effects of career adaptability on turnover intentions will be further illuminated. The need for shedding light on this relationship was also suggested by Guan, Zhou, Ye, Jiang, Zhou, (2015).
In the following sections I present the theoretical background that supports the proposed relationships, the hypotheses, and finally, my conceptual model (Fig. 1).
1. Literature review 1.1. Career adaptability
Career adaptability is embedded in the career construction theory (Savickas & Porfeli, 2012). In career construction theory, the sequential network goes from adaptivity, through career adaptability, to adapting and finally to the goal of adaptation. While adaptivity is being willing to respond to change, career adaptability is being able to do so, or having the resources to respond to changes in the work context. Career adaptability leads to adapting behaviors and subsequently to adaptation, a combination of success, satisfaction, and development (Savickas & Porfeli, 2012).
The career adaptability construct consists of self-regulatory, psychosocial resources that enable people to cope with career developmental tasks, transitions, and work traumas (Savickas, 1997). The resources of career adaptability are also multi-dimensional and hierarchical. The four dimensions that constitute the career adaptability construct are concern, control, curiosity, and confidence (Savickas and Porfeli, 2012). Concern is about planning one’s future, being aware, involved and preparing for the future. Control is about making decisions, being focused, decisive, organized and disciplined, and owning one’s own future. Curiosity is about exploring, being inquisitive, about inquiring and experimenting. And finally, confidence is about problem solving and knowing that one can shape his/her future, being efficacious, persistent and striving (Savickas and Porfeli, 2012). When individuals face complex and unfamiliar problems related to career development or adjustment, they employ the career adaptability resources in order to solve these problems (Savickas and Porfeli, 2012). Research on career adaptability relates this construct with a number of goals or adaptation outcomes, such as career satisfaction, salary, promotability, turnover intentions, and career performance (Ito & Brotheridge 2005, Chan, Mai, Kuok, Kong, 2016, Chan & Mai, 2015, Zacher, 2014, Omar & Noordin, 2013, Guan, Zhou, Ye, Jiang, Zhou, 2015).
1.2. Adapting
Savickas and Porfeli (2012) characterize the career adaptability resources as a form of human capital, or competencies accumulated over time, that lead to the self-regulation strategies of adapting. The career adaptability resources guide employees' adapting behaviors toward the achievement of career goals. There are five sets of adapting behaviors in which individuals employ their career adaptability resources. These activities are named after their adaptive functions: orientation, exploration, establishment, management, and disengagement, and form a cycle that is repeated periodically (Savickas & Porfeli, 2012).
In previous research, the adapting strategies have been operationalized using different constructs. In the following section I provide an overview of the different classifications of the self-regulation adapting behaviors, and their influence to adaptation outcomes. Hirschi, Herrmann, and Keller, 2015 conducted a study with a sample of university students and measured adapting in terms of career planning, career exploration, career decision-making difficulties, and occupational self-efficacy. In addition to behaviors, the authors included beliefs of self-efficacy and the barrier of career decision-making difficulties because they also represent reactions to challenges and changes in one’s career. This research was grounded on the theoretical assumption that each career adaptability resource is manifested in a separate adapting response: concern, in career planning; control, in career decidedness; curiosity, in career exploration; and confidence, in career self-efficacy. The results of this study established that the adaptability resources of concern, control, curiosity, and confidence are significantly related to, but empirically distinct from the examined four adapting responses. The researchers found that the career adaptability resource of concern was the one most strongly correlated to all of the investigated adapting measures. The findings of this research also suggest that the four resources of adaptability have a broad impact on different manifestations of adapting, and not only the ones corresponding conceptually to the same
resource (Hirschi, Herrmann, & Keller, 2015). The same four adapting behaviors were examined by Hirschi and Valero, (2015) in their study on different adaptability profiles of students, and found that profiles with higher adaptability showed more adapting attitudes and behaviors.
On a sample of working adults Sibunruang et al. (2016) related adapting behaviours to promotability at work. The authors examined particularly adapting in form of ingratiation, an impression management strategy or social influence tactic (Liden & Michell, 1988). Examples of ingratiation behaviors are opinion conformity and rendering favors (Gordon, 1996). In accordance to the notions of ingratiation as adapting response to barriers in their career progression (King, 2004), Sibunruang et al. (2016) found that ingratiation mediated the positive relationship between career adaptability and promotability. To my knowledge this is the only study conducted on working adults, with the objective to clarify the sequential process between career adaptability, adapting and adaptation. To address the gap, and to answer the call (Hirschi and Valero, 2015) on examination of the relationship between career adaptability and additional indicators of adapting, other than already investigated ones (career planning, career decidedness, career exploration, and career self-efficacy), the present research aims to examine the role of other career self-management behaviors, namely strategic choice of mobility opportunity, strategic investment in human capital, active network development and job content innovation (King, 2004).
1.3. Career self-management
I can suggest that the career adaptability resources, being self-regulation strengths or capacities (Savickas and Porfeli, 2012), result from the desire that one has to be in control of his/her own career. Ashford and Black (1996) also find that the desire for control is leading individuals to attain certainty in uncertain situations and is related to proactive socialization
tactics, such as networking, information seeking and job-change negotiation. One’s desire for control over the career is also an antecedent of the extent to which people engage in career self-management (King, 2004).
When individuals are high on concern and control, and make plans and decisions for the future, I can assume that they are oriented to deliberately invest in their own human capital. They will be disciplined and expected to be involved in initiatives such as training participation and obtaining educational qualifications that prepare them for what might come next. These resources of concern and control, together with curiosity and confidence will lead individuals also to behaviors related to proactively exploring and experimenting, to be involved in solving problems, be persistent and strive to establish themselves. It can be expected that examples of such behaviors will be active network building and initiating attempts to bring improvements to processes and procedures at work. Briefly, career adaptability resources should be related to behaviors that build one’s skills, contacts and experience.
King (2004) describes career self-management as a dynamic process composed by different and co-occurring behaviors divided in three groups: positioning, influence and boundary management behaviors. In his conceptual framework there are several types of positioning behaviors: strategic choice of mobility opportunity, strategic investment in human capital, active network development and job content innovation, all of which enhance one’s skills, contacts and experience:
• strategic choice of mobility opportunity relates to the initiation of job moves, or acceptance of proposed changes made by another party, such as one’s employer, or external agencies, examples are internal and external job moves, new assignments and projects, perceived by the individual as more or less instrumental than others;
training, and obtaining educational qualifications. This investment may be of generic value or of specific value for the organization, one’s career and industry;
• active network development, networks offer benefits such as information, guidance, and advocacy for employment or promotion. Having both internal and external networks increase one’s chances of having interactions with influential members of the employing or other organization;
• job content innovation, following on Graen, (1976), job content innovation is the development of substantive changes in methods or procedures used to perform job tasks and the enlargement of one’s effective task environment. Job content innovation serves to develop skills, experience, build human capital and gain access to influential members of the organization (King, 2004).
Based on the above I expect that:
H1 There is a positive relationship between career adaptability and the four positioning
career self-management behaviours, namely strategic choice of mobility opportunity, strategic investment in human capital, active network development and job content innovation.
Career construction theory and the existing empirical studies suggest that the skill, contact and experience enhancing positioning career-self management behaviors (King, 2004), will be an expected adapting response. Individuals will employ their career adaptability resources in order to achieve development and success (Savickas and Porfeli, 2012). Testing how King’s, (2004) conceptual model of positioning career-self management behaviors fits in the career construction network will add to our knowledge of the ways through which career adaptability leads to two outcomes of interest for both the theory and the practice, namely turnover intentions and job performance.
1.4. Adaptation
According to Savickas and Porfeli (2012), in the career construction network, adaptation is also referred to as “goodness of fit” (p.661). The notion that adaptation is indicated by development, success, and satisfaction (Savickas & Porfeli, 2012), guides this study to investigate turnover intentions and job performance in their roles of indicators of “goodness of fit”.
1.4.1. Turnover intentions
The turnover literature is based on satisfaction and number of perceived job alternatives as the two main factors predicting turnover (Hulin et al., 1985, Steers and Mowday, 1981, Hom and Kinicki, 2001). Although there is not always consistency between intentions to leave and voluntary turnover (Allen, Weeks, Moffitt, 2005), intentions to turnover can be considered the best predictor of turnover behavior (Armitage and Conner, 2001, Hom et al., 1992, Griffeth et al., 2000). Even when turnover intentions do not lead to actual turnover, they can negatively influence one’s motivation, loyalty, and commitment at work (Chow et al. 2012).
Ito & Brotheridge, (2005) found that career adaptability is positively related to turnover intentions both directly and through decreasing dependence. These results can be explained with career adaptability increasing the ease of movement, the perceived number of alternatives, and the willingness that a person has to take on new challenges. Career adaptability also decreased his/her dependence to the organization for employment. When employees perceive higher levels of mobility, and that their skills and education are transferable to another organization, they are more likely to have intentions to leave (Meyer et al., 2002, Ito & Brotheridge, 2005). We can assume that those who are more adaptable perceive more job alternatives, therefore I hypothesize that:
Career adaptability has been positively related to career planning and career exploration (Hirschi, Herrmann, & Keller, 2015), and career exploration, or exploring alternative positions, has been found to be positively related with lower loyalty to the organization and higher turnover intentions (Klehe et al., 2011). We can suggest that individuals who possess more career adaptability resources will plan and explore more strategically their surrounding, therefore, I expect to find that:
H3a Strategic choice of mobility opportunity mediates the positive relationship between
career adaptability and turnover intentions. Specifically, I expect that higher levels of career adaptability will positively relate to strategic choices about job moves, which might stimulate intentions to leave the organization.
According to human capital theory (Becker, 1965), the development of general skills, that are useful across firms, increases the possibility that the employee will use the acquired skill outside the employing organization (Becker, 1965, Lynch, 1991). Benson, (2006) found support for this human capital theory suggestion, reporting that employee participation in training that provides general or marketable skills is positively related to intentions to leave the organization. Other studies report similar results, when skills and abilities marketable outside the organization are acquired, employees increase their job alternatives and turnover (Lynch, 1991, Loewenstein and Spletzer, 1999). Therefore, I expect that:
H3b Strategic investment in human capital mediates the positive relationship between career
adaptability and turnover intentions. Specifically, I expect that higher levels of career adaptability will positively relate to engagement in training, and obtaining educational qualifications which might stimulate intentions to leave the organization.
Networking behaviors have been defined as “activities directed towards developing and sustaining multiple professional relationships” (Porter et al., 2015, p.4). Individuals who engage in more networking behaviors have access to more resources and advantages, and receive more opportunities and strategic information (Wolff & Moser, 2009), which can be positively related with intentions to leave and pursue new opportunities. Developing professional contacts outside the organization gives access to more diverse knowledge and insights, and is a source of information about job opportunities outside the organization (Cliffe 1998, Bian 1997). Since the perceived number of job alternatives is one of the main factors predicting turnover (Hulin et al., 1985, Steers and Mowday, 1981, Hom and Kinicki, 2001), and networking behaviors provide access to information about such alternatives, active network development would be associated with higher turnover intentions. Porter et al., 2015 find that external networking behaviors are positively related to receiving more job offers and to voluntary turnover, while internal networking is positively related to job embeddedness and negatively related to voluntary turnover. We can also suggest that those who engage in active network development do not keep only strong ties, but create bigger networks containing a higher number of weak ties. Weak ties have been noted to provide more alternatives than strong ties because they give the individual access to information that strong ties cannot offer, and in this way help individuals find employment (Granovetter, 1973). This idea finds support in the work of McPherson, Popielarz, and Drobnic (1992) who find evidence that individuals with larger networks of connections have shorter duration of group membership and join more new groups. Therefore, I expect that:
H3c Active network development mediates the positive relationship between career
adaptability and turnover intentions. Specifically, I expect that higher levels of career adaptability will positively relate to active development or networks of contacts, which might stimulate intentions to leave the organization.
Innovation at work as a process consists of several stages: idea generation, idea promotion, and idea realization, and innovative behaviors are related to all three stages (Janssen, 2004). Innovation at work not only requires effort, but involves creating something new and is change-oriented (Spreitzer, 1995; Woodman et al., 1993), and since career adaptability resources provide the individual with the ability to respond to change (Savickas & Porfeli, 2012), we can expect that individuals who possess more career adaptability resources will engage more in innovative work behavior and job content innovation. Janssen et al., (2004) propose a model where individual innovation offers the benefit of performance improvement, but also the cost of negative job attitudes, and although they do not specify what the negative job attitudes resulting from innovation are, there is empirical support for a proposition that innovative behaviors at work are positively related to turnover intentions (Posthuma et al., 2011, Shih and Susanto, 2011). Shih and Susanto, (2011) also find that innovative behaviors are positively related to conflicts with colleagues. We can also suggest that employees who engage in more job content innovation behaviors are those who look for new challenges. Therefore, I expect to find that:
H3d Job content innovation mediates the positive relationship between career adaptability
and turnover intentions. Specifically, I expect that higher levels of career adaptability will positively relate to innovations and improvements in one’s job which might stimulate intentions to leave the organization.
1.4.2. Job performance
Job performance is another relevant outcome measure of the occupational setting and can be defined as the behaviors, actions, and outcomes that are relevant or contribute to the organizational goals (Campbell, 1990, Viswesvaran and Ones, 2000). A distinction between
task performance and contextual performance is made by Borman & Motowidlo, (1993), who suggest that task performance refers to the set of duties central to a particular job, but different in different occupations. Contextual performance, on the other hand, refers to behaviors that are not formally part of the job, but that are inherent in all jobs and support the social structure of the organization. The construct of job performance has different dimensions, which have been additionally integrated by Koopmans et al., (2011) in a conceptual network as task performance, contextual performance, counterproductive work behavior, and adaptive performance.
Although job performance is an objective work outcome with practical implications, only one study on career adaptability to date has studied job performance. I believe the reason for lack of research on the link between career adaptability and job performance, is that job performance is a multidimensional construct (Koopmans et al., 2011), and different dimensions of job performance are relevant for measuring performance across organizations and industries. In a policy-capturing study, Ohme and Zacher, (2015), found that career adaptability is positively related with overall job performance. In this study, respondents rate the fictitious employees’ overall job performance in different given scenarios, and although their research design provides both external and internal validity, the authors recognize that examining the relative importance of career adaptability for job performance ratings in actual work settings is an important next step to further validate their findings (Ohme and Zacher, 2015). Another study by Sony and Mekoth, (2016) also found a positive relationship between employee adaptability and job performance.
Existing research on career adaptability relates the construct positively to different career success outcomes, such as career satisfaction, salary, promotability, self-rated career performance (Chan, Mai, Kuok, Kong, 2016, Chan & Mai, 2015, Zacher, 2014, Guan, Zhou, Ye, Jiang, Zhou, 2015). Also, previous research relates these positive career outcomes to job
performance (e.g. Noe, 1996). In line with the existing theoretical and empirical literature I propose that:
H4 There is a positive relationship between career adaptability and job performance.
Career performance does result from both high job performance, and effective career strategies (Gould and Penley, 1984). The positioning career self-management behaviors increase the perceived levels of control over one’s career, which should lead to increased performance and well-being (King, 2004).
Gould and Penley, (1984) found that creating opportunities and extended job involvement are positively related to salary progression, and strategies related to positioning inter- and intra- personally lead to better job performance ratings for managers. These activities include the development of contacts that can provide resources and information (networking) and proactively communicating the desire to take on higher responsibilities (self-nomination). We can assume that individuals who create more opportunities for themselves will have more opportunities and therefore will make more strategic choice, which will result in performance gains. Therefore, I expect that:
H5a Strategic choice of mobility opportunity mediates the positive relationship between
career adaptability and job performance. Specifically, I expect that higher levels of career adaptability will positively relate to strategic choices about job moves, which might stimulate higher job performance.
In line with career construction theory (Savickas & Porfeli, 2012) we can suggest that individuals who possess higher career adaptability resources will engage more actively and strategically in activities that will build their human capital and will prepare them to deal with
future need and challenges. Increase in skills and abilities should translate into job performance gains, therefore, I hypothesize that:
H5b Strategic investment in human capital mediates the positive relationship between career
adaptability and job performance. Specifically, I expect that higher levels of career adaptability will positively relate to engagement in training, and obtaining educational qualifications which might lead to higher job performance.
According to social capital theory, social capital is a value-enhancing asset, created when the relationships among individuals change (Coleman, 1990). Social resources embedded in networks, or ties between those within the social structure, will provide benefits to the individuals within this social structure (Coleman, 1990, Seibert et al., 2001). The benefits of the social resources embedded in networks include greater and more timely access to information, greater access to resources and greater visibility (Seibert et al., 2001). Through greater access to information and resources, the individual work performance increases (Hackman and Oldham 1980, Spreitzer 1996). Thompson, 2005 also finds that employees you actively build their networks, receive higher job performance ratings. Based on the theoretical and empirical support, we can suggest that active network development will create social capital, and the increased access to information and resources will offer benefits for the individuals who engage in networking, one of these benefits will be higher job performance, Therefore, I hypothesize that:
H5c Active network development mediates the positive relationship between career
adaptability and job performance. Specifically, I expect that higher levels of career adaptability will positively relate to active development or networks of contacts, which might lead to higher job performance.
Career adaptability resources allow individuals to cope with change, and coping effectively with change has been positively related to job performance (Judge et al., 1999). As we already suggested, more adaptive individuals will engage in more innovative behaviors, will cope effectively with change and should achieve higher performance. The existing body of research on the relationship between creativity and job performance also supports the expectation that innovation results in job performance gains. Creativity refers to the idea generation stage of the innovation process (Amabile 1996) and several studies provide empirical evidence for the positive relationship between creativity and job performance (e.g. Gilson 2008; Gong, Huang, and Farh 2009). Gong, Huang, and Farh, (2009) suggest that in the creative process new procedures are developed and refined, and more effective alternative procedures are found, which improves the performance of the individual. Innovative behaviors also imply that the individual will proactively take charge of the situation to bring on change, which should result in performance gains (Griffin et al. 2007).
H5d Job content innovation mediates the positive relationship between career adaptability
and job performance. Specifically, I expect that higher levels of career adaptability will positively relate to innovations and improvements in one’s job which might lead to higher job performance.
1.5. Supervisor mentoring support- career development and socioemotional support
In career construction theory, career adaptability resources are not the most basic part of the individual, but occupy the intersection of person- in-environment, which means that they depend on both the person and the environment, the culture and the context place boundary conditions around adaptability (Savickas and Porfeli, 2012). Environment characteristics such as feedback on performance, positive reinforcement of good performance, and opportunities
for achievement affect the career decisions and behaviors (London, 1983).
Mentoring at work is part of this environment and can be different types, but mainly consists of two functions, career development support and socioemotional support. Career development support includes direct forms of sponsorship for career enhancement, such as challenging assignments, coaching, protection and provision of exposure and visibility. Socioemotional support is about being a friend and counselor, and providing support to deal with difficult situations and positive regard and acceptance, and serving as a role model (Kram, 1985, Noe, 1988; Scandura, 1992).
Supportive supervisors affect individuals’ willingness to engage in development activities and are key for employee performance and success, mentoring support is positively related to career satisfaction and promotability, and when used together, mentoring support and self-management strategies have been found related to higher levels of job satisfaction and perceived career success (Kram, 1985, Noe, 1996, Ballout, 2007, Murphy and Ensher, 2001).
Supervisory support as perceived by the employees is the degree to which supervisors value subordinates' contributions and care about subordinates' well-being (Kottke and Sharafinski 1988). Based on social-exchange theory (Blau, 1964), in the dyadic relationship between subordinate and supervisor, when there is mutual trust, the gestures of support and goodwill will be exchanged. Mentoring support creates trust and indicates to employees that their supervisor cares about their future and well-being. It emerges from the evidence that employees will reciprocate the perceived support through their attitudes and behaviors (Blau, 1964). Therefore, we can suggest that when the individuals perceive higher levels of support, they will reciprocate this by having less intentions to leave the organization and better performance.
Another social exchange relationship that can explain the role of supervisor mentoring support in the career adaptability-turnover intentions and career adaptability-job performance relationships is the leader-member exchange (LMX) theory. The focus of LMX is the dyadic relationship between a leader and a subordinate, and the concept that leaders can treat their subordinates differently (Liden and Graen, 1980). LMX relationships can be categorized as low or high, low LMX relationships are mainly transactional, while high LMX relationships reflect trust, respect and influence between the leader and the subordinate (Bernerth et al., 2007). It has been suggested that LMX relationships impact organizational outcomes, such as turnover intentions and performance (Liden and Graen, 1980). The results of three meta-analytical studies on the outcomes of the social exchange quality (such as trust, perceived organizational support and the quality of the LMX relationship), show consistent results, and find significant positive relationship between LMX and job performance and turnover intentions (Gerstner and Day, 1997, Dulebohn et al. 2012, Colquitt et al. 2013). It has also been found that leaders tend to give more positive ratings to employees where the LMX relationship is stronger (Bowler et al., 2010).
In line with the theory and the empirical finding, I expect supervisor mentoring support to condition the relationships I hypothesize. While I expect to find a positive relationship between career adaptability and turnover intentions, the results of some recent studies showed negative relationship between career adaptability and turnover intentions, this relationship being mediated by career satisfaction and promotability (Chan & Mai, 2015, Chan et al. 2016). I believe that the inconsistent findings in the studies on the career adaptability-turnover intentions link are due to a possible contextual variable that conditions the relationship and expect that supervisor mentoring support is a possible such moderator. This leads to the following hypothesis:
H6: The indirect positive effect of career adaptability on turnover intentions through
positioning career self-management behaviors is moderated by supervisor mentoring support. Specifically, I expect the positive indirect relationship between career adaptability and turnover intentions through positioning self-management behaviors to be weaker for those employees who receive high mentoring support as opposed to those who receive low mentoring support. I expect this pattern of relationships for each of the investigated career self-management strategies: strategic choice of mobility opportunity(H6a), strategic investment in human capital(H6b), active network development(H6c), job content innovation(H6d)
While I expect to find a positive relationship between career adaptability and job performance mediated by positioning career self-management behaviors, there is also some empirical evidence that career strategies and job performance are not significantly related. In one such study, Noe, (1996) does not find a significant relationship between career strategies and job performance but shows that management support is significantly related to employee development activities. The findings of Noe, (1996) suggest that the mediated career adaptability- job performance relationship might be moderated by other variables, and I find strong theoretical and empirical support for a proposition that supervisor mentoring support is a variable that might condition this relationship. I find additional support for my proposition in the self-determination theory, according to which, supportive socio-contextual conditions promote individuals’ development and growth when their needs for autonomy, competence and relatedness conditions are met (Deci & Ryan, 1985). We can assume that mentoring support provides these three conditions, mentors promote autonomy by supporting the individual’s engagement in interesting activities facilitating challenging assignments; competence, or the need to produce and control the valued outcomes, is promoted by the
supervisor in the form of positive regard and exposure and visibility; and relatedness, or the need to feel closely connected with others who care about one, is promoted by a supervisor who is a friend and counselor, and provides protection and acceptance. Therefore, I expect to find that:
H7: The indirect positive effect of career adaptability on job performance through positioning
career self-management behaviors is moderated by supervisor mentoring support. Specifically, I expect the positive indirect relationship between career adaptability and turnover intentions through positioning self-management behaviors to be stronger for those employees who receive high mentoring support as opposed to those who receive low mentoring support. I expect this pattern of relationships for each of the investigated career self-management strategies: strategic choice of mobility opportunity(H7a), strategic investment in human capital(H7b), active network development(H7c), job content innovation(H7d)
1.6. Conceptual model Figure 1. Research model
In the following sections, the start of the empirical part of this study is presented. First, the sampling techniques, population, and characteristics of the collected sample will be outlined. Next, the variables and scales used, and their reliabilities will be discussed. Finally, a brief description of the statistical approach that was chosen to test for the proposed relationships between the variables, will be presented.
2. Method and data 2.1. Sample
The present research is a cross-sectional study using survey research strategy. The data collection technique that was used is questionnaire. Two versions of a questionnaire were distributed, in order to collect employee-supervisor dyads. Supervisors were sent one version of the questionnaire in which they were asked to rate the job performance of their employees and to include a unique code for each employee; the employees were provided with the same unique code when filling in the employee version of the questionnaire. The unique code was used to correctly match the employee- supervisor dyads. Copies of the two questionnaires can be found in the Appendix of the paper.
For this study, a total of six companies were approached to distribute questionnaires among their employees. Two of the organizations are small companies, one is in the logistics business and the other one is a small industrial furnaces manufacturer, the rest of the organizations are multinationals from the BPO and pharmaceutical industries. For this study, a non-probability convenience sampling was used, the questionnaires were distributed with the collaboration of HR managers and senior operations managers. The sample for this study consisted only of Bulgarian employees employed on a full-time basis.
Both electronic and pen and paper versions of the questionnaire were available, depending on the preferences of the participating organizations. Only the two small
companies chose the pen and paper version, due to the specifics of their work, where employees do not use computers on a daily basis. The number of pen and paper responses was 17 matched dyads. The total number of matched supervisor-employee dyads received was 41. From the 55 managers who started filling out the questionnaire, 54 fully completed it. From the 322 employees who started filling out the questionnaire, 211 fully completed it. The total number of employee responses that could be used for this study is 298, these were found to have no missing responses for any of the career adaptability questions.
Out of the 298 employees, 70 were male, 164 were female, and 64 did not specify their gender, this makes a valid percent of 29.9% male and 70.1% female respondents. With regards to the respondents age, the age group between 25-34 was the most largely represented with 41.1%, followed by the group 35-44 with 32.2%, and 45-54, with 15.7%. The age group 55-64 represented 5.9%, and finally the group 16-19, 0.8% of the total. These sample characteristics can be explained with the fact that the BPO and pharmaceutical industries in Bulgaria employ high number of young, highly educated female professionals. The range of educational backgrounds that the sample presents, also supports this proposition, with 51.7% of the respondents indicating that they hold a Master’s degree, 24.6% with Bachelor’s degree, 3% with a PhD, 19.1% with High School diploma and 1.7% who preferred not to specify their educational level.
2.2. Measures
The original scales used to measure the constructs in this study were all in English, therefore all questions were translated into Bulgarian, using the translation back-translation procedure. The author, translated the survey from English to Bulgarian. Consequently, additional person, a native Bulgarian speaker, who is also fluent in English, translated the survey back to English. There were no major inconsistencies between the original English version and the back translation, however small corrections were made in order to keep the exact meaning of
the questions. Example of such a correction was the item “Keeping upbeat” from the career adaptability scale, that does not have a meaning in Bulgarian, and was translated as “Keeping myself optimistic”.
Self-reported measures were collected from employees for all variables, except for one of the dependent variables, namely job performance, that was rated by the supervisors. The scales and their reliability are presented below.
Career adaptability
For this study the Career Adapt-Abilities Scale (CAAS) (Savickas & Porfeli 2012) was adopted. The scale contains four subscales with 6 items each to measure the adaptive resources of concern, control, curiosity and confidence. Overall scale reliability is α=0.91 for the 24 items. The four subscales showed the following reliability: concern α=0.83, control α=0.76, curiosity α=0.83 and confidence α=0.85. Respondents were asked to rate how strongly they have developed each of the career adapt-abilities using a 5-point, Likert-type scale ranging from 1 (“Not strong”) to 5 (“Strongest”). Sample item for the subscale of concern is “Preparing for the future”, a sample item for control is “Taking responsibility for my actions”, a sample item for curiosity is “Probing deeply into questions I have”, a sample item for confidence is “Taking care to do things well”.
Turnover intentions
The intentions to leave were measured with a 3 item scale adopted from Cammann et al., (1979), and validated by Park et al., (2015), α=0.92. In the current study the scale reliability is α=0.90. Respondents were asked to rate the extent to which they agree or disagree with statements using a 5-point, Likert-type scale ranging from 1 (“Strongly disagree”) to 5 (“Strongly agree”). Sample item is “I often think about quitting”.
Job performance
Job performance was measured with a 24 item scale, containing 6 subscales allowing to measure different dimensions of job performance. 20 of the items are from Welbourne, Johnson and Erez, (1998), 4 items are from Chen and Klimoski, (2003). The composed scale reliability of the 24 items is α=0.99, validated by Chen and Klimoski, (2003). In the current study the composed scale reliability is α=0.96. Supervisors were asked to rate the performance of the employee using a 5-point, Likert-type scale ranging from 1 (“Needs much improvement”) to 5 (“Excellent”) for the subscale that measures the job or doing things specifically related to one's job description. Sample item is “Quantity of work output”. A 5-point, Likert-type scale ranging from 1 (“Strongly disagree”) to 5 (“Strongly agree”) was used for the rest of the subscales, where supervisors were asked to rate the extent to which they agree or disagree with statements regarding the job performance of their subordinates. Sample item for the subscale related to career, or obtaining the necessary skills to progress through one's organization is “Developing skills needed for his/her future career”; sample item for the subscale measuring innovator, or creativity and innovation in one's job and the organization as a whole is “Working to implement new ideas”; sample item for the subscale measuring teamwork, or working with co-workers and team members, toward success of the firm is “Working as part of a team or work group”; sample item for the subscale measuring organization, or going above the call of duty in one's concern for the firm is “Working for the overall good of the company”; sample item for the subscale measuring employee’s customer service role is “Establishing excellent rapport with customers”.
Positioning career self-management behaviors
Positioning career self-management behaviors were measured with different scales for each behavior. Respondents are asked to rate the extent to which they agree or disagree with statements using a 5-point, Likert-type scale ranging from 1 (“Strongly disagree”) to 5 (“Strongly agree”).
Strategic choice of mobility opportunity was measured with 3 items adapted from the
6 item Employability activities scale by van Dam, (2004). Sample item “I make sure to be informed about internal job vacancies”. In the current study the 3 item scale showed reliability α=0.74
Strategic investment in human capital was measured with 6 items, adapted from 2
different scales. 2 items are from the job crafting scale developed by Tims, Bakker, and Derks, (2012). These two items are “I try to develop myself professionally”, and “I try to learn new things at work”. The rest of the items are adapted from the Enhancing Skill Crafting subscale developed by Bindl, (2014), sample item is “I actively try to develop wider capabilities in my job”. In the current study the 6 item scale showed reliability α=0.85
Active network development was measured with 6 items, adapted from 2 different
scales. 3 items are from the scale developed by Verbruggen and Sels, (2009). Sample item is “I can build and maintain contacts with people who can help me with my career”. The rest 3 items are from the Enhancing Relationship Crafting subscale developed by Bindl, (2014), sample item is “I actively seek to meet new people at work”. In the current study, the overall scale reliability is α=0.76 for the 6 items.
Job content innovation was measured using the 4 items Enhancing Task Crafting
subscale from Bindl, (2014). Sample item is “I add complexity in my tasks by changing their structure or sequence”. The overall scale reliability of the 4 items is α=0.80.
Supervisor mentoring support
Supervisor mentoring support was measured with a 14 item scale, adapted from Noe, (1988), overall scale reliability is α=0.92. This scale measures different aspects of mentoring support, including Coaching, Acceptance & Confirmation, Role Model, Counseling, and Sponsorship. Respondents were asked to rate the extent to which they agree or disagree that statements apply to them using a 5-point, Likert-type scale ranging from 1 (“Strongly disagree”) to 5 (“Strongly agree”). Sample item is “My direct supervisor has encouraged me to prepare for advancement”.
Control variables
I included age and gender as control variables to capture the demographic characteristics in this study. McEnrue, (1989) found that younger employees are more willing to engage in skill-development career management strategy. Older and more experienced workers were found to be less likely to quit, and women were more likely to quit (Brass 1985). More recent studies, however, found women to be less likely to quit and to move between organizations (Lyness & Schrader, 2006, Rosenblatt et al., 1999; Schnake et al., 2007). Gender has also been shown to have potential impact on career self-management behaviors in studies on networking behavior. One study found men to be more likely to engage in networking (Forret and Dougherty, 2001), while in another the opposite was found (Emmerick et al., 2006). Respondents were also asked about their educational level, job tenure and work experience.
3. Results
3.1. Statistical procedure
The data was collected in a one-month period, from April 13th, until May 13th, 2016, when the survey was closed. To perform the statistical analyses, the Statistical Analysis Software
Package SPSS v.23 was used. After dealing with the missing data, using the listwise deletion procedure, and inserting identifiers for missing responses (999.00), the dataset was checked for reverse-coded items. All items used were indicative, therefore no items were recoded. Next, scale reliabilities, and descriptive statistics were computed. Reliability analysis was run to confirm the quality of the measures. All scaled used showed high reliability with Cronbach’s Alpha a >.70. The 24 item career adaptability scale has high reliability, with Cronbach’s Alpha= .91; the 6 item active networking development scale Cronbach’s Alpha= .76; the 6 item strategic investment in human capital scale Cronbach’s Alpha= .85; the 4 item job content innovation scale Cronbach’s Alpha= .80; the 3 item strategic choice of mobility opportunity scale Cronbach’s Alpha= .74; the 3 item turnover intentions scale Cronbach’s Alpha= .90, and the 24 item job performance scale Cronbach’s Alpha= .96 . The corrected item-total correlations indicate that all items in all scales used have a good correlation with the total score of the scale (all above .30). Also, none of the items in any of the scales would substantially affect reliability if they were deleted, so no items were deleted.
3.2. Descriptive statistics
Correlation analysis was conducted to initially study the relationship between the variables. The correlation coefficients, means and standard deviations are reported in the correlation matrix below (Table 1). From the correlation carried on, career adaptability does not appear to relate significantly to turnover intentions, with a Pearson Correlation coefficient of r=-0.05,
Note: N (1-17) = 298; N (18) = 41 M SD 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 1 Age 3.75 1.00 _ 2 Gender 1.70 0.46 .12 _ 3 Education 3.44 0.89 .12 .13 _ 4 Job tenure 2.70 1.35 .41** .12 -.08 _ 5 Total work experience 4.09 1.71 .86** .15* .03 .43** _ 6 Manager liking 3.71 1.06 .01 .10 .05 -.035 .01 _ 7 CONCERN 3.08 0.78 -.21** -.08 .09 -.10 -.21** .07 (.83) 8 CONTROL 3.89 0.67 -.02 -.06 -.06 -.04 -.04 .00 .44** (.76) 9 CURIOSITY 3.55 0.75 -.17** -.07 -.10 -.07 -.15* -.01 .49** .54** (.83) 10 CONFIDENCE 3.85 0.68 -.02 .04 -.01 -.01 -.01 .08 .39** .60** .62** (.85) 11 Career Adaptability 3.59 0.58 -.14* -.05 -.02 -.07 -.14* .04 .75** .80** .83** .80** (.91) 12 Active Network Development 3.66 0.71 -.12 -.01 -.10 -.07 -.10 .23** .27** .28** .26** .19** .32** (.76) 13 Strategic Investment in Human Capital 4.36 0.53 .06 .07 .03 -.01 .11 .17** .33** .31** .33** .51** .46** .38** (.85) 14 Job Content Innovation 3.41 0.85 .09 .17** -.07 .14* .16* .05 .14* .14* .26** .39** .29** .26** .39** (.80) 15 Strategic Choice of Mobility Opportunity 3.39 1.02 -.15* -.06 -.10 -.24** -.15* .02 .24** .07 .19** .09 .19** .30** .31** .16** (.74) 16 Turnover intentions 2.68 1.26 -.21** .05 -.06 -.07 -.21** -.22** -.02 -.13* .03 -.07 -.05 -.07 -.06 .03 .45** (.90) 17 Supervisor mentoring support 3.28 0.82 -.10 .02 .06 -.08 -.11 .79** .19** .06 .07 .11 .13* .30** .15* .10 .08 -.21** (.92) 18 Job performance 3.76 0.74 .28 .23 .33* -.05 .22 .56** .10 -.20 -.30 -.14 -.16 -.03 .30 .31 .07 -.14 .48** (.96) ** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed). Variables
and job performance (r=-.16). On the other hand, career adaptability relates significantly to all investigated career self-management behaviors, examining relatively modest (r=0.19 and r=0.29 for strategic investment in mobility opportunities and job content innovation, respectively) to medium relations (r=0.46 and r=0.32 for strategic investment in human capital and active network development, respectively). Among the control variables only age had significant and negative relation with career adaptability (r=-0.14).
Next, PROCESS macro for SPSS, developed by Hayes (2012), was used to test the proposed simple mediation, and the indirect moderated mediation relationships. The models 4 and 14 were used. To additionally investigate the ability of the independent variable to explain variance in the dependent variable, hierarchical multiple regression analysis was performed.
3. 3. Hypotheses testing
3.3.1. Career adaptability and positioning career self-management behaviors
The first goal of this study, and the first hypothesis, referred to illuminating the relationship between career adaptability and positioning career self-management behaviors. My analysis showed that career adaptability is significantly and positively related to each of the positioning career self-management behaviors: strategic choice of mobility opportunity (effect=0.361, SE=0.111 p<0.05, CI: 0.142 to 0.579), strategic investment in human capital (effect=0.448, SE=0.052, p<0.001, CI: 0.345 to 0.551), active network development (effect= 0.422, SE= 0.074, p<0.001, CI: 0.276 to 0.566), job content innovation (effect=0.426, SE= 0.090, p<0.001, CI: 0.248 to 0.603). (Left columns in Table 6, Table 7, Table, 8 and Table 9 in section 3.3.2.)
To complement the findings regarding the relationship between career adaptability and positioning career self-management behaviors, I explored the relationships among different career adaptability dimensions and each of the positioning career self-management behaviors. The interest to report on each of the four career adaptability resources (e.g.,
concern, control, curiosity, and confidence) is guided by the multidimensional nature of the career adaptability construct (Savickas & Porfeli 2012). I also find support for the need to report on this information in the limited empirical research to date. Findings in studies on career adaptability show that concern and control are strongly and positively related with career planning, while curiosity has a negative effect on career planning (Taber and Blankemeyer, 2015, Hirschi et al, 2015). In the present study, hierarchical multiple regression was performed to investigate the individual contribution of each of the four career adaptability resources in explaining each of the positioning strategies. after controlling for age, gender and educational level. The results are presented in Table 2, Table 3, Table 4, Table 5 below.
In the first step of the hierarchical multiple regression the three control variables were entered, age, gender and educational level. This model was statistically non-significant for strategic choice of mobility opportunity (F(3,227)= 2.26; p ns= .082), strategic investment in human capital (F(3,229)=0.54; p ns=.65), and active network development (F(3,230)=1.92, p ns= .12), and statistically significant for job content innovation (F(3,228)= 3.45; p<.05 and explained 4.3% of variance). In accordance with previously evidenced correlation between career adaptability dimensions and positioning strategies, after entry of concern, control, curiosity and confidence at Step 2, all four models as a whole were statistically significant. Specifically, he introduction of the four career adaptability resources explained additional 5.7% variance in strategic choice of mobility opportunity (R2 Change= .057; F(4,223)=3.48, p<.05), 29.7% variance in strategic investment in human capital (R2 Change= .29; F(4,225); p<.001); 13% variance in active network development (R2 Change= .13; F (4,226)= 8.71; p<.001) and 14.3% variance in job content innovation (R2 Change= .14; F (4,224)=9.86, p<.001).
Table 2. Hierarchical regression model testing the relationship between career adaptability resources and strategic choice of mobility opportunity
R R 2 R 2 Change B SE β t Step 1 .17 .02 Age -.14 .06 -.13* -2.03 Gender -.06 .15 -.03 -.44 Education -.09 .07 -.07 -1.16 Step 2 .29 .08* .05* Age -.08 .07 -.08 -1.19 Gender -.05 .15 -.02 -.34 Education -.10 .07 -.09 -1.38 Concern .22 .10 .17* 2.12 Control -.18 .13 -.11 -1.37 Curiosity .17 .12 .11 1.38 Confidence .12 .14 .07 .80
Note. Statistical significance: *p<.05; **p<.001
Table 3. Hierarchical regression model testing the relationship between career adaptability resources and strategic investment in human capital
R R 2 R 2 Change B SE β t Step 1 .08 .01 Age .02 .03 .04 .68 Gender .07 .08 .06 .90 Education .01 .04 .01 .23 Step 2 .55 .30** .29** Age .04 .03 .08 1.49 Gender .06 .06 .05 .94 Education -.004 .03 -.007 -.12 Concern .13 .05 .19* 2.64 Control -.03 .06 -.03 -.52 Curiosity .00 .05 .00 -.00 Confidence .41 .06 .47** 6.08
Table 4. Hierarchical regression model testing the relationship between career adaptability resources and active network development
R R 2 R 2 Change B SE β t Step 1 .15 .02 Age -.08 .04 -.11 -1.77 Gender .02 .10 .01 .20 Education -.07 .05 -.09 -1.44 Step 2 .39 .15** .13** Age -.05 .04 -.07 -1.18 Gender .06 .09 .04 .63 Education -.07 .05 -.09 -1.47 Concern .10 .07 .11 1.43 Control .24 .09 .22* 2.73 Curiosity .11 .08 .11 1.34 Confidence -.01 .09 -.01 -.08
Note. Statistical significance: *p<.05; **p<.001
Table 5. Hierarchical regression model testing the relationship between career adaptability resources and job content innovation
R R 2 R 2 Change B SE β t Step 1 .20 .043* Age .07 .05 .09 1.37 Gender .30 .11 .17* 2.59 Education -.08 .06 -.08 -1.35 Step 2 .43 .187** .143** Age .09 .05 .11 1.78 Gender .26 .11 .14* 2.39 Education -.08 .05 -.09 -1.54 Concern .03 .08 .03 .41 Control -.26 .10 -.21* -.56 Curiosity .10 .09 .09 1.12 Confidence .52 .11 .40** 4.78
