Social Support and Career Psychological States

Abstract

This study examined the mediating role of person–environment (P-E) fit in the relationships of perceived social support (PSS) with perceived employability and career decision self-efficacy (CDSE). The moderating role of gender was also tested in the PSS and P-E fit relationship and in the P-E fit mediated relationships of PSS with perceived employability and CDSE. Seven hundred and ninety-nine Chinese university students returned usable questionnaires. Data were analyzed using structural equation modeling (SEM). Results demonstrated that P-E fit fully mediated the relationship between PSS and perceived employability and partially mediated the PSS–CDSE relationship. Multi-group SEM revealed that the relationship between PSS and P-E fit was stronger among males than among females. This gender difference also contributed to the gender difference in the indirect relationships of PSS with perceived employability and CDSE via P-E fit, such that these indirect relationships were stronger for males than for females.

Keywords

social support person–environment fit career decision self-efficacy perceived employability gender China

Over the past two decades, two psychological states, perceived employability and career decision self-efficacy (CDSE), have attracted increasing academic interest in the career development literature (Berntson, Näswall, & Sverke, 2008; Forstenlechner, Selim, Baruch, & Madi, 2014; Jiang, 2014). Perceived employability refers to one’s perceived ability to move self-sufficiently within the labor market to acquire employment (Hillage, Pollard, & Britain, 1998; Rothwell & Arnold, 2007), while CDSE reflects individual’s general confidence of completing career exploration and decision-making tasks (Berntson et al., 2008; Betz, Klein, & Taylor, 1996). As two closely correlated but clearly distinguished career variables, both perceived employability and CDSE are important in vocational development because they can facilitate individuals’ career exploration, preparation, evaluation, and decision-making processes (Brown, George-Curran, & Smith, 2003; Forstenlechner et al., 2014).

The importance of these variables is particularly prominent for university students, as they are likely to experience career-related bewilderment during the identity transition from student to worker (Jiang, 2014). Although some researchers argue that CDSE tends to be salient at the start of college while perceived employability is likely to be primed during the late college years, accumulative evidence has shown that both constructs are relevant to university students at different points in career development (Jiang, 2014; Rothwell, Herbert, & Rothwell, 2008). This phenomenon has become increasingly apparent in fast-growing economies (e.g., China) where students face tremendous career opportunities and challenges (Jiang, 2015). Therefore, scholars suggest that researchers and counselors should explore various approaches to increase both CDSE and perceived employability among university students in such economies/societies, so as to lead them to a smooth transition and a favorable starting point for the career development journey (e.g., Jiang, 2014; Nauta, Vianen, Heijden, Dam, & Willemsen, 2009; Rothwell et al., 2008).

Treated as a type of social resource or capital perceived by individuals, social support has been found to be an approach to fostering CDSE (Patel, Salahuddin, & O’Brien, 2008), perceived employability (Wittekind, Raeder, & Grote, 2010), and other positive attitudes and perceptions related to career activities like planning and exploration (Creed, Fallon, & Hood, 2009; Rogers, Creed, & Ian Glendon, 2008). The conceptual reasoning underlying this role of social support underscores the idea that the dependence of individuals on the social environment means that the ability to address career-specific issues relies on both individual (internal) and environmental (external) variables (Lent, Brown, & Hackett, 1994; Wiesenberg & Aghakhani, 2007). In line with this theoretical basis, both self-exploration and environmental exploration have been found to help transmit the effects of social support on career-related evaluation, perception, and growth (Zikic & Klehe, 2006). Although this cluster of research has significantly contributed to our understanding of the environment-based psychological process that leads to career attitudes and perceptions, empirical studies have ignored some key factors that align the self and the environment in examining the role of social support in career-related processes.

For instance, acknowledging that both individual and environmental characteristics can assist in constructing career development models (Osipow, 1990), the literature suggests that person–environment (P-E) fit operates a more essential interlocking mechanism that influences career construction, given that people naturally prefer an adequate state of P-E congruence (e.g., Lent et al., 1994). This indication is in line with Parsons’ (1909) early viewpoint that humans collect information about the self (e.g., values) and environment (e.g., social environment) in developmental vocational processes, and finally integrate the information to pursue an area of match (Xu & Tracey, 2014). Despite these theoretical bases suggesting that P-E nexuses, particularly P-E fit, may boost the functioning of social resources or capital (e.g., social support from the affiliated career environment) in career exploration and decision making, lack of empirical evidence may limit further inferences and theory development in relation to the integration of individuals, environments, and career-related psychological states.

The present study, therefore, seeks to advance the knowledge of the effects of social support on career psychological states, from an empirical perspective rooted in the fit between the person and the environment. Specifically, this study uses a Chinese student sample to examine the mediating role of P-E fit in the relationships of perceived social support (PSS) with perceived employability and CDSE. Based on social capital theory (Coleman, 1988) and Holland’s (1985) theory of careers, this study argues that social support influences perceived employability and CDSE because it helps individuals fit into career environments, thereby facilitating the formation of positive psychological states in career exploration and decisions. Relying on social role theory (Eagly, 1987), this study also proposes that the effect of PSS on P-E fit differs among gender, being stronger for males than for females. As an extension, the present study also tests whether this gender difference extends to the indirect effects of PSS on perceived employability and CDSE via P-E fit.

Perceived Employability and CDSE

Employability is a type of active work-specific adaptability that enables the identification and realization of employment opportunities in career exploration. Although it does not guarantee actual employment, it facilitates the job search process and increases the likelihood of positive career-relevant outcomes (Fugate, Kinicki, & Ashforth, 2004). Individuals’ perception of employability reflects their beliefs about the possibility of gaining or changing employment (Berntson et al., 2008) based on the evaluation of their own competencies in obtaining, performing, and maintaining jobs (Forstenlechner et al., 2014; Ghoshal, Bartlett, & Moran, 1999). Generally, high employability embodies one’s abilities to handle problems and difficult situations in career development (Berntson et al., 2008). These abilities, according to Fugate, Kinicki, and Ashforth (2004) and McArdle, Waters, Briscoe, and Hall (2007), fall into multiple categories such as humans’ adaptability, career identity, and human and social capital. Specifically, individuals’ perceived employability is established on the ability to change personal behaviors, dispositions, and thoughts in varying environments; to define and conceptualize self in career contexts; and to leverage formal and informal career-related social networks as a source of social support (McArdle, Waters, Briscoe, & Hall, 2007).

Self-efficacy reflects one’s beliefs and confidence in successfully carrying out given tasks or behaviors, including elements like choice, initiation, performance, and persistence in the process of task or behavioral implementation (Creed, Patton, & Prideaux, 2006). CDSE, as an extension of the self-efficacy theory to career exploration and selection (Betz & Luzzo, 1996), reflects one’s degree of confidence in his or her capacity to successfully perform vocational exploration and decision-making tasks (Creed et al., 2006; Jiang, 2014). These tasks have been categorized into five groups, namely, self-appraisal, career information collection, goal selection, problem solving, and planning for the future, each of which corresponds to a conceptual dimension of CDSE (Betz & Luzzo, 1996). However, due to the inconsistent empirical findings regarding the factorial structure of CDSE, an increasing number of researchers are focusing on the overall-level rather than multidimensional CDSE (e.g., Brown et al., 2003; Jiang, 2014).

PSS, Perceived Employability, and CDSE

In the career context, PSS is the perceived helpfulness of immediate and extended family, friends, and significant others when in need of help with situations such as career planning and decision making (Patel et al., 2008; Zimet, Dahlem, Zimet, & Farley, 1988). According to Creed, Fallon, and Hood (2009), social support is a potential resource for obtaining career-specific advice and information and dealing with the demands of changes. It can alleviate career concerns and strengthen capacities such as self-regulation in career development. In career preparation, social support has been suggested to contribute to readiness and implementation actions of career planning, exploration, and decision making (Di Fabio & Kenny, 2012; Rogers et al., 2008). It is helpful in navigating the ups and downs in career transitions (e.g., from student to worker) and subsequently fulfilling individuals’ career aspirations, considering that perception of support drives people to form positive attitudes toward life futures including the career journey (Wiesenberg & Aghakhani, 2007). In various career contexts, PSS may increase the likelihood of accepting changes and thus encourage people to take more proactive approaches in career activities (Clarke, 2008). In essence, such functions of PSS are centered on the key point that PSS can foster individuals’ optimistic attitudes in the process of personal career development and management (Zikic & Klehe, 2006).

Both psychological constructs, perceived employability and CDSE, largely reflect individuals’ optimism regarding career thinking (Fugate et al., 2004). Due to the potential of PSS to lead to optimism, this conceptual reflection legitimately foresees the role of PSS in increasing perceived employability and CDSE, which indeed has been confirmed by strong empirical cases. For example, research indicates that general social support (McArdle et al., 2007) as well as career-specific support (Wittekind et al., 2010) are able to significantly explain increases in perceived employability. Under various contexts, PSS has also been consistently found to be a key predictor and correlate of CDSE (Di Fabio & Kenny, 2012; Patel et al., 2008). The commonality of this research stream is that it regards social support as contextual affordances that can smooth career choice and development processes (Lent et al., 1994) through strengthening career outlooks and confidence. Consistent with this research, recent empirical studies have also demonstrated that social support from different sources plays a significant role in shaping Chinese youths’ career development and constructing their career planning (Ma & Yeh, 2010).

The Mediating Role of P-E Fit

The literature has highlighted the importance of P-E fit in career psychology (Holland, 1985; Lent et al., 1994). Prior research suggests that most individuals are to a certain degree tied to, and have a natural tendency to blend into, their affiliated environments or contexts (Jiang & Jiang, 2015). Their interactions with the environment help integrate and utilize social resources (e.g., social support) in vocational development processes mentally. These interactions involve one’s self-evaluation and environmental reflection simultaneously, which form the basis for perceptions of P-E fit or misfit (Jiang & Jiang, 2015). In career-relevant settings, PSS has been suggested to promote individuals to match self to the environment, and subsequently reduce negative, and increase positive, psychological outcomes in career processes (Lent et al., 1994; Xu & Tracey, 2014). That means, individuals integrate social resources (e.g., social support) into self-concepts to pursue P-E congruence, which benefits cognitive, evaluative, explorative, constructive, adaptive, and reflective processes of vocational development (Rogers & Creed, 2011). Following this rationale, this study argues that PSS, as a type of socio-psychological resource, can influence variables related to career development such as CDSE and perceived employability because it can increase P-E fit in career exploration and decision-making processes. As elaborated below, social capital theory (Coleman, 1988) can help explain the potential influence of PSS on P-E fit, and Holland’s (1985) theory of careers offers a basis for the relationship between P-E fit and career-relevant constructs (e.g., CDSE and perceived employability).

An underpinning insight of social capital theory (Coleman, 1988; Seibert, Kraimer, & Liden, 2001) indicates that social networks (e.g., family, friends, and significant others) provide individuals with general and domain-specific social support, which functions as a type of resource or capital to cope with unstructured situations in the P-E interaction where stress may occur (Carlson & Perrewé, 1999), such as career environment exploration processes (Jiang, 2014). This effect of social support can facilitate people’s explorations of the self and the environment (Zikic & Klehe, 2006), and may affect their internal regulation in the P-E interaction. The literature suggests that people perceiving social support may find it easier to fit into their associated environments because they tend to feel valued, own positive core self-evaluations, and are better able to confront obstacles in interacting with and getting along with external environments (Jiang & Jiang, 2015; McArdle et al., 2007). Indeed, empirical evidence has demonstrated the roles of social support in forming the fit between individuals and environments. For example, peer support helps individuals fit work settings (Lovelace & Rosen, 1996). Similarly, it is reported that social support from family is positively related to P-E fit variables such as the congruence between the person and career communities (Edwards & Rothbard, 1999).

According to Holland’s theory of careers (Holland, 1985), P-E fit serves as a cornerstone in career psychology and is a catalyzer in occupational exploration and choice (Wilkins & Tracey, 2014). The core emphasis is that the fit between persons and characteristics of environments leads people to be optimistic, develop self-confidence, and perform better, in different life domains (Jiang & Jiang, 2015). In the context of vocational development, scholars argue that the compatibility between individuals’ attributes (e.g., values, beliefs, and interests) and the characteristics of occupational environments tend to influence people’s career cognition and attitudes (Holland, 1997; Lent, Brown, & Hackett, 2002; Savickas, 2013) because this compatibility is likely to alleviate their psychological barriers in completing career development tasks. In support of this argument, research shows that P-E congruence is positively related to self-efficacy beliefs in career decisions (Gore & Leuwerke, 2000) and can explain individual employability and career success (Ballout, 2007).

The above discussion has suggested a potentially positive relationship between PSS and P-E fit as well as potentially positive relationships between P-E fit and favorable career beliefs and perceptions (i.e., CDSE and perceived employability). As noted earlier, past research has long established overall positive relationships between PSS and individuals’ self-efficacy and employability perceptions (Patel et al., 2008; Wittekind et al., 2010). Taken together, these relationships imply indirect effects of PSS on CDSE and perceived employability via P-E fit. It should be appropriate to extend this logic to the Chinese context, given that existing evidence and hints show that PSS facilitates Chinese university students’ career development process and their engagement in P-E interactions in this process (Ma & Yeh, 2010; Xu, Hou, & Tracey, 2014). Specifically, this study proposes:
Hypothesis 1: P-E fit mediates the relationships of PSS with perceived employability (Hypothesis 1a) and CDSE (Hypothesis 1b).

The Moderating Role of Gender

Another purpose of this article is to explore whether and how gender roles can influence the effect of PSS on P-E fit. As discussed previously, P-E fit theory suggests that humans, both males and females, generally prefer their congruence with the environment, which can potentially generate positive outcomes in significant life events like career activities (Holland, 1997; Jiang & Jiang, 2015). However, the reliance on social resources (e.g., social support) to achieve a P-E fit status in the career development context may differ between men and women. Social role theory (Eagly, 1987) contends that men and women learn different gender roles through socialization. These distinctive roles stereotypically guide their behaviors via psychological and social processes. Males are generally seen to have agentic qualities, being instrumentally competent, competitive, assertive, and masterful, while females are regarded to have more communal qualities, being emotionally expressive, passive, and friendly (Eagly, 1987; Franke, Crown, & Spake, 1997). These differentiations have been shown to be robust in the Chinese society (Tang & Tang, 2001). In general, such differentiations direct men and women to place differential importance on the career environment. For example, consistent with gender role expectations (e.g., men being more assertive than women), men are more accommodative to an employment role and eager to fulfill their psychological needs for career success (Eagly, 1987). Due to this tendency, men may rely on external social resources (e.g., support) to a larger extent than women to reach a certain level of P-E fit, so as to achieve desired career outcomes. In addition, with female gender roles, women have been found to naturally have a wider range of network sources for social support than men (Antonucci & Akiyama, 1987). In other words, men may not be able to obtain social support as easily as women due to their exposure to relatively limited network sources. The effort justification perspective holds that people have the tendency to attach greater value to outcomes, which are to be acquired via greater efforts (Lydall, Gilmour, & Dwyer, 2010). Such social facts, demonstrated in previous research, lead men to value social support more than women in interacting with external environments. Overall, these perspectives suggest that PSS may exert a greater influence on men’s than on women’s P-E fit. I argue that these theoretical perspectives can also apply to Chinese university students.
Hypothesis 2: Gender moderates the relationship between PSS and P-E fit, such that this relationship is stronger for males than for females.

On the basis of Hayes (2013), the examination of Hypothesis 2 suggests the potential existence of first-stage moderated mediation. That is, gender may also affect the strength of the indirect relationships of PSS with the two career-related psychological states, perceived employability and CDSE. Although males and females, to a similar extent, value P-E fit because of its benefits, and P-E fit may have similar impacts on career outcomes (Feldman, Smart, & Ethington, 1999), the role of gender in the first-stage (i.e., the linkage between PSS and P-E fit) of the mediation may still result in different strengths of the indirect relationships from PSS to perceived employability and CDSE (Preacher, Rucker, & Hayes, 2007). That means the moderating role of gender in the effect of PSS on P-E fit may be extended to produce gender differences in the mediating role of P-E fit in the relationships between PSS and career-relevant psychological outcomes. Therefore, as an extension of Hypothesis 2, it is further hypothesized:
Hypothesis 3: Gender moderates the relationships of PSS with perceived employability (Hypothesis 3a) and CDSE (Hypothesis 3b) that are mediated by P-E fit, such that these relationships are stronger for males than for females.

Method

Participants and Procedure

Data were collected from full-time undergraduate students in a public university in northeastern China. Faculty members invited students to participate in the survey during class time. Participants were informed that the survey was voluntary, anonymous, and confidential, and assured that their responses could be accessed only by the research team. To alleviate the possibility of coercion caused by returning surveys to faculty, students were also assured that non-participation would not affect their course outcomes and any other study issues. The participants handed the completed questionnaires directly to the faculty members in the classroom. A total number of 799 students returned usable questionnaires (valid response rate = 94.0%), with 483 females (60.5%) and 316 males (39.5%). Their age ranged from 17 to 25 years (mean age = 20.43, SD = 1.40). Of these students, 454 (56.8%) were freshmen, 201 (25.2%) sophomores, 99 (12.4%) juniors, 44 (5.5%) seniors, and 1 (0.1%) unreported. As for their majors, 246 (30.8%) were enrolled in science and engineering, 254 (31.8%) in social sciences, 208 (26.0%) in economics and management, 15 (1.9%) in sports and the arts, 69 (8.6%) in other areas, and 7 (0.9%) unreported.

Measures

All measurement items were initially developed in English and were translated into Chinese using a back-translation procedure (Brislin, 1980). Specifically, one bilingual scholar with expertise in career psychology translated these items from English to Chinese, and another bilingual scholar in the same field translated this Chinese version back to English. The two scholars compared the two English versions (the original and the translated) and resolved discrepancies through joint discussion. All measures used in this study have been demonstrated to have sound psychometric properties in the Chinese context (e.g., Chou, 2000; Jiang & Jiang, 2015; Jin, Watkins, & Yuen, 2009; Lu, Sun, & Du, 2015).

PSS

The 12-item scale of Zimet, Dahlem, Zimet, and Farley (1988) was used to measure respondents’ overall PSS regarding career development. This scale was developed from a sample of undergraduates, reflecting important sources of social support for university students such as support from family, friends, and significant others (Zimet et al., 1988). In this study, students were asked to reflect on their own experiences in career development (e.g., career preparation and decision) when responding to the PSS items such as “My family is willing to help me make decisions”. These items were rated on a Likert-type scale ranging from 1 (strongly disagree) to 5 (strongly agree). Prior research operationalizing these items to assess the overall PSS demonstrated a Cronbach’s α of greater than .80 (e.g., Bozo, Tathan, & Yılmaz, 2014; Xia et al., 2012). The Cronbach’s α was .88 in this study.

P-E fit

P-E fit was assessed using 11 items adapted from Lauver and Kristof-Brown (2001). These items measured how individuals fit into such career contexts as major (profession), university (environment for career preparation), and a broader society where careers develop. All these career contexts have been suggested to be primarily valued by university students in career development (Eun, Sohn, & Lee, 2013; Gilbreath, Kim, & Nichols, 2011; Yang, Noels, & Saumure, 2006). Similar methods for adaptation were used in past research (Jiang & Jiang, 2015). One example item was “There is a good match between the requirements of this major [profession] and my skills”. Students responded to these items on a Likert-type scale ranging from 1 (strongly disagree) to 5 (strongly agree). In this study, the Cronbach’s α for this 11-item scale was .88.

Perceived employability

The 4-item scale used by De Cuyper, Mauno, Kinnunen, and Mäkikangas (2011) was adapted to measure perceived employability. Example items included: “Given my qualifications and experience, getting a job would not be very hard at all” and “My qualifications and experience are in demand on the labor market”. The response format was a Likert-type scale ranging from 1 (strongly disagree) to 5 (strongly agree). Consistent with prior studies (e.g., De Cuyper, Mauno, Kinnunen, & Mäkikangas, 2011), the Cronbach’s α (.85) for perceived employability was greater than .80 in this study.

CDSE

The CDSE-Short Form (CDSE-SF), a 25-item instrument developed by Betz, Klein, and Taylor (1996), was adopted to measure individuals’ overall self-efficacy expectations for accomplishing tasks in relation to career decision making. Example tasks in this scale included “Find out the employment trends for an occupation over the next 10 years” and “Determine what your ideal job would be”. Students rated their confidence in successfully completing these career decision tasks on a Likert-type scale ranging from 1 (no confidence at all) to 5 (complete confidence). In line with previous research (e.g., Brown et al., 2003), the current study had a Cronbach’s α (.91) of over .90 for the CDSE.

Data Analysis

A two-step procedure involving confirmatory factor analyses (CFAs) and structural equation modeling (SEM) recommended by predecessors (e.g., Anderson & Gerbing, 1988) was used to analyze the data. First, CFA was performed to test the distinctiveness of the 4 study variables. In this step, the 4-factor model was compared with six 3-factor models, three 2-factor models, and one 1-factor model. Second, a model comparison approach was used to assess structural models and thus identify the best fitting one, based on which hypotheses were examined.

An item parceling strategy recommended by previous researchers was employed to reduce the number of indicators (Nasser-Abu Alhija & Wisenbaker, 2006). This strategy was adopted because inflated measurement errors tend to bias results when too many indicators (e.g., CDSE has 25 measurement items) are loaded on a single latent construct (Nasser-Abu Alhija & Wisenbaker, 2006). Three parcel indicators were created for each of the four constructs using the item-to-construct balance procedure elaborated in Little, Cunningham, Shahar, and Widaman (2002). Specifically, using factor loadings as a guide, items with the highest and lowest loadings were bundled together successively until all items were allocated to a parcel. The score for such a parcel indicator was calculated as the mean score of all items assigned to the same indicator.

The model fit was assessed using the ratio of chi-square to degrees of freedom (χ²/df), the standardized root mean residual (SRMR), the root mean square error approximation (RMSEA), and the comparative fit index (CFI). For models to be acceptable, χ²/df should be less than 5.0 and preferably less than 3.0 (Kline, 2010; Marsh & Hocevar, 1985); SRMR and RMSEA should be less than .08; and CFI should be greater than .90. A further criterion, the Akaike information criterion (AIC, Akaike, 1987), was used in model comparison, with smaller values indicating a better fitting model (Blunch, 2008).

Results

Table 1 presents the results of CFA. The fit indexes showed that the 4-factor model fits the data best, supporting that the four study variables were distinctive constructs.

Table 1.
Results of CFA.

Models χ²/df df SRMR RMSEA CFI AIC

1-Factor Model 49.62 54 .15 .25 .577 2,727.20

2-Factor Model A 36.99 53 .14 .21 .693 2,010.19

2-Factor Model B 41.43 53 .20 .23 .655 2,245.51

2-Factor Model C 34.79 53 .13 .21 .711 1,894.05

3-Factor Model A 24.34 51 .11 .17 .808 1,295.47

3-Factor Model B 25.58 51 .18 .18 .798 1,358.81

3-Factor Model C 23.75 51 .11 .17 .813 1,265.05

3-Factor Model D 15.10 51 .08 .13 .884 824.14

3-Factor Model E 20.37 51 .08 .16 .841 1,093.06

3-Factor Model F 16.86 51 .09 .08 .870 913.81

4-Factor Model 2.47 48 .03 .04 .989 178.34

Note. The 1-factor model: all four constructs, that is, perceived social support (PSS), person–environment fit (P-E fit), perceived employability, and career decision self-efficacy (CDSE), were loaded on a single factor; The 2-factor Model A: PSS and P-E fit were loaded on one factor, while perceived employability and CDSE were loaded on the other factor; The 2-factor Model B: PSS and perceived employability were loaded on one factor, while P-E fit and CDSE were loaded on the other factor; The 2-factor Model C: PSS and CDSE were loaded on one factor, while P-E fit and perceived employability were loaded on the other factor; The 3-factor Model A: PSS and P-E fit were loaded on one factor; The 3-factor Model B: PSS and perceived employability were loaded on one factor; The 3-factor Model C: PSS and CDSE were loaded on one factor; The 3-factor Model D: P-E fit and perceived employability were loaded on one factor; The 3-factor Model E: P-E fit and CDSE were loaded on one factor; The 3-factor Model F: perceived employability and CDSE were loaded on one factor; The 4-factor model: the four constructs were loaded on four independent factors. CFA = confirmatory factor analysis.

As with all self-report data, common method variance has the potential to bias the results. To test the extent to which the method variance could influence the current data, the 1-factor test recommended by Podsakoff, MacKenzie, Lee, and Podsakoff (2003) and used by previous researchers (e.g., Rutherford, Marshall, & Park, 2014; Sánchez, Vélez, & Ramón-Jerónimo, 2012) was conducted via CFA. If the method variance is largely influential, the CFA results should indicate a good fit for the 1-factor model (Mossholder, Bennett, Kemery, & Wesolowski, 1998; Podsakoff, MacKenzie, Lee, & Podsakoff, 2003). As shown in Table 1, the 1-factor model did not fit the data well. Chi-square difference test showed that its model fit was much poorer than that of the 4-factor model, Δχ ² (6) = 47.15, p < .001, reducing the concern about common method variance. Furthermore, the 4-factor model was compared to one with a common method factor. If the common method bias exists, the 4-factor model with a method factor should fit the data significantly better than the one without the method factor (Andrews, Kacmar, Blakely, & Bucklew, 2008; Podsakoff et al., 2003). Model comparison demonstrated that the addition of a method factor to the 4-factor model slightly improved model fit, χ ² (36) = 1.69, SRMR = .02, RMSEA = .03, CFI = .996, AIC = 144.81; however, the improvement was not statistically significant, Δχ ² (12) = .78, p > .10, further confirming that common method variance is less likely to be an issue in the current study.

Table 2 presents the means, standard deviations, reliabilities, and correlational coefficients of study variables. PSS and P-E fit were positively related to perceived employability and CDSE.

Table 2.
Means, Standard Deviations (SDs), Reliabilities, and Correlations.

Variables Mean SD 1 2 3

1. Perceived social support (PSS) 3.66 .57

2. Person–environment fit (P-E fit) 3.53 .63 .42*

3. Perceived employability 3.26 .76 .21* .57*

4. Career decision self-efficacy (CDSE) 3.39 .48 .45* .62* .54*

***p < .001.

With reference to prior researchers (e.g., Jiang & Jiang, 2015), the four conditions of mediation (Baron & Kenny, 1986) were assessed to test the mediating role of P-E fit. As shown in Table 2, correlational coefficients revealed that PSS was positively related to both perceived employability and CDSE, satisfying the first condition. PSS was significantly related to P-E fit, supporting the second condition. P-E fit was significantly related to both perceived employability and CDSE, meeting the third condition.

The fourth condition was tested based on the comparison of alternative models with the baseline (full mediation) model. As displayed in Table 3, fit indexes suggested that all three partial mediation models (Models 2–4) fit the data better than the full mediation model (Model 1). Among these three models, Models 3 and 4 had better fit relative to Model 2. Since the values of χ ²/df and AIC were smaller for Model 3 than for Model 4 and the direct path from PSS to perceived employability was not statistically significant in Model 4, Model 3 (partial mediation B) was identified as the best fitting model.

Table 3.
Results of SEM Model Comparisons.

Models χ²/df df SRMR RMSEA CFI AIC

Model 1 (full mediation model) 3.35 50 .05 .05 .98 223.55

Model 2 (partial mediation model A) 3.24 49 .05 .05 .98 216.61

Model 3 (partial mediation model B) 2.44 49 .03 .04 .99 177.49

Model 4 (partial mediation model C) 2.47 48 .03 .04 .99 178.34

Note. Model 2 adds to Model 1 the path from perceived social support (PSS) to perceived employability; Model 3 adds to Model 1 the path from PSS to career decision self-efficacy (CDSE); and Model 4 adds to Model 1 the paths from PSS to both perceived employability and CDSE. SEM = structural equation modeling.

Figure 1 presents the standardized estimates generated from AMOS 20 for the besting fitting model. Bootstrapping analysis (5,000 samples) revealed that both indirect effects of PSS on perceived employability (β = .24, SE = .03, 95% biased-corrected CI [.20, .28]) and CDSE (β = .22, SE = .03, 95% biased-corrected CI [.18, .26]) via P-E fit were significant. These results indicated that P-E fit fully mediated the relationship between PSS and perceived employability, and partially mediated the relationship between PSS and CDSE. Therefore, Hypotheses 1a and 1b were supported.

Figure 1.
The best fitting structural model. Note. Standardized coefficients are reported. Coefficients above the parentheses are for the full sample. In the parentheses, coefficients in front of the slash are for the female group and the others are for the male group. The fit indexes for the overall model are shown in Table 3 (Model 3). The fit indexes for multigroup SEM (unconstrained) are as follows: χ ²/df = 1.97, df = 98, SRMR = .03, RMSEA = .04, CFI = .99. p < .001. AIC = akaike information criterion; CFA = confirmatory factor analysis; SRMR = standardized root mean residual; RMSEA = root mean square error approximation; CFI = comparative fit index; SEM = structural equation modeling.

Multi-group SEM was performed to test the moderating role of gender, namely, gender differences. Firstly, multi-group CFA was use to examine whether the measurement model was equivalent among male and female groups. As recommended by predecessors (e.g., Vandenberg & Lance, 2000), configural and metric invariance was tested. It was found that the configural invariance model well fit the data (χ²/df = 1.98, df = 96, SRMR = .03, RMSEA = .04, CFI = .99), indicating that the number of factors applied to each gender group and the indicators loaded on the same factor were invariant between the two groups. The metric invariance model also demonstrated excellent fit (χ²/df = 1.98, df = 96, SRMR = .03, RMSEA = .04, CFI = .99), suggesting that the factor loadings were invariant between genders. These results indicated that further comparisons of the strength of relationships among variables can be legitimately undertaken between gender groups.

Then, Kafetsios and Sideridis’ (2006) procedure was used to conduct multi-group SEM path analyses to test whether the proposed relationships were different between groups (i.e., the moderating role of gender). The structural path(s) corresponding to the specific relationship(s) was(were) constrained to be equal at a time between groups, and the significance of Chi-square change was tested to confirm gender differences. Specifically for testing Hypotheses 2, 3a, and 3b, three constrained multi-group models (see Table 4) were compared with the unconstrained one (Model 1): (a) males versus females for the relationship between PSS and P-E fit (Model 2); (b) males versus females for the indirect relationship between PSS and perceived employability via P-E fit (Model 5); and (c) males versus females for the indirect relationship between PSS and CDSE via P-E fit (Model 6). Although this study did not hypothesize the second-stage moderation, two additional multi-group models were run to explore whether the second stage of the indirect relationships of PSS with outcome variables could contribute to the variation of the overall indirect relationships. These two models constrained the relationships of P-E fit with perceived employability (Model 3) and CDSE (Model 4), respectively.

Table 4.
Multigroup SEM Results for Gender Effects.

Models χ² χ²/df df Δχ² SRMR RMSEA CFI AIC

1. Unconstrained model 192.67 1.97 98 – .03 .04 .99 308.67

2. PSS → P-E fit equal 202.51 2.05 99 9.84 (1)^a .04 .04 .98 316.51

3. P-E fit → PE equal 192.74 1.95 99 .07 (1)^a .03 .03 .99 306.74

4. P-E fit → CDSE equal 193.69 1.96 99 1.02 (1)^a .03 .04 .99 307.69

5. PSS → P-E fit → PE equal 202.89 2.03 100 10.22 (2)^a .05 .04 .98 314.90

6. PSS → P-E fit → CDSE equal 202.90 2.03 100 10.23 (2)^a .04 .04 .98 314.90

Note.* The multigroup analyses were based on the partial mediation model B presented in Table 3. PSS = perceived social support; P-E fit = person–environment fit; CDSE = career decision self-efficacy; PE = perceived employability; SEM = structural equation modeling; AIC = akaike information criterion; SRMR = standardized root mean residual; RMSEA = root mean square error approximation; CFI = comparative fit index.

^aCompared to the unconstrained model.

**p < .01.

Results for multi-group SEM are presented in Table 4, and the standardized path estimates for each group are displayed in Figure 1. Gender differences were identified via Chi-square difference tests showing that the unconstrained structural model fits the data significantly better than Models 2, 5 and 6 (see Table 4). Unstandardized bootstrapping (5,000 samples) path estimates and coefficient difference tests (Paternoster, Brame, Mazerolle, & Piquero, 1998) provided further confirmation. Males, compared to females, had a stronger relationship between PSS and P-E fit (B = .65, SE = .08, 95% bias-corrected CI [.51, .79] versus B = .36, SE = .05, 95% bias-corrected CI [.29, .44]; ΔB = .29, p < .001), and stronger indirect relationships of PSS with perceived employability (B = .46, SE = .08, 95% bias-corrected CI [.34, .61] versus B = .25, SE = .04, 95% bias-corrected CI [.19, .32]; ΔB = 0.21, p < .01) and CDSE (B = .15, SE = .05, 95% bias-corrected CI [.15, .32] versus B = .22, SE = .02, 95% bias-corrected CI [.11, .19]; ΔB = .07, p < 0.05) via P-E fit. Thus, Hypotheses 2, 3a, and 3b were supported. No gender differences were detected for the second stage of mediation, that is the relationships of P-E fit with perceived employability and CDSE, as suggested by the results of Chi-square difference tests (Model 1 versus Models 3 and 4, Table 4). Figure 2 depicts gender effects on the PSS and P-E fit relationship.

Figure 2.
The moderating role of gender in the relationship between perceived social support and person–environment fit.

Discussion

Results from a Chinese student sample showed that PSS was positively related to individuals’ P-E fit, which in turn positively influenced perceived employability and CDSE. Additionally, the moderating effect of gender was exhibited in the influence of PSS on P-E fit, such that this influence was stronger for males than for females. The extended moderated mediation model was also supported in predicting perceived employability and CDSE. These findings contribute to a number of aspects of the literature and career management practice.

Theoretical Implications

First, the present study reconfirms the significant role of social support in career choice processes by demonstrating that Chinese university students perceiving higher levels of social support tend to fit better into the career environment, feel more employable, and have higher CDSE. In general, these results are in line with prior studies reporting that social support increases the quality of planning, exploration, and decision making in career management (Creed et al., 2009; Rogers et al., 2008; Zikic & Klehe, 2006), and to promote the development of optimistic attitudes (e.g., self-efficacy) that help reduce psychological difficulties in resolving career issues (Di Fabio & Kenny, 2012; Patel et al., 2008). These present findings, to a certain degree, have verified the perspective grounded in social capital theory that social support is a form of social capital or resource that can contribute to the management of life events, including managing one’s career (Carlson & Perrewé, 1999; Coleman, 1988).

Second, this study is among the first to apply P-E fit to explore the mediation mechanism that underlies the function of social support in career development issues. As discussed earlier, previous research in vocational psychology has paid attention to explorations of both self and environment (e.g., Xu et al., 2014; Xu & Tracey, 2014; Zikic & Klehe, 2006), but has not offered sufficient empirical evidence regarding the effects of the congruence between the person and the environment. In the present study, P-E fit proves an essential bridge that connects social support to Chinese students’ perceived employability and CDSE. Considering that P-E fit is a conceptualization inclusive of individuals’ cognitions of the self and the environment and seeking balance between the two (Edwards, 1996), this finding reflects the importance of matching self-appraisal to environmental-appraisal in transmitting the function of social support to career management. Building on this focus, the mediating role of P-E fit, detected in the relationships of PSS with perceived employability and CDSE, provides empirical evidence to integrate social capital theory (Coleman, 1988) and P-E fit theory of careers (Holland, 1985) in explaining the psychological processing of career choice. For example, as suggested in the present findings, social capital (e.g., support from one’s social environments) can be a source that facilitates one’s adaptation to the career environment, leading to positive career-relevant psychological states.

Third, gender differences, identified in this study for the main effect of social support on P-E fit and its indirect effect on perceived employability and CDSE, have extended the application of social role theory (Eagly, 1987) to P-E interaction in career choice processes. The results support that the prescribed social gender roles for Chinese men, along with the availability of social networks, make them more likely to rely on social support to fit into the environment, and as a result, to perceive higher levels of employability and CDSE via the path of P-E fit. This gender effect is opposite to the findings of some other studies, which found the effect of social support to be stronger among females than among males when it is considered as the predictor of well-being, depression, stress, and other psychological distresses (Antonucci & Akiyama, 1987; Umberson, Chen, House, Hopkins, & Slaten, 1996). However, researchers also argue that due to the sophisticated socialization associated with psychological mechanisms in men and women, gender effects on social support from interpersonal relationships and its influences are always complex; they can be non-existent or appear in different directions (Umberson et al., 1996). Studies conducted in other cultures reported that social support from interpersonal networks is more likely to lead to school-related outcomes (e.g., the United States, Rueger, Malecki, & Demaray, 2010) and subjective career success (e.g., the United Kingdom, Nabi, 2001) for males than for females. The present findings from China, to some extent, enrich the literature and further affirm the complexity of gender effects in the function of social support. Importantly, these findings, generated from career-focused contexts, suggest the possibility that the role of effort justification intervenes in the interaction of gender and social support, which may have resulted in the direction of gender effects that differs from that found in other life contexts (Antonucci & Akiyama, 1987).

A fourth contribution is that this study provides empirical evidence suggesting that perceived employability is distinctive from CDSE. Since employability is conceptually related to self-efficacy, there is debate regarding whether perceived employability and CDSE are two distinct constructs (Berntson et al., 2008). Some researchers (e.g., Daniels, D’Andrea, & Gaughen, 1998) assume them to be identical and even use the scale for perceived employability to measure CDSE. However, analyses from the current study support the distinctiveness of these two variables among Chinese university students. For instance, CFA results show that the model fits the data better when perceived employability and CDSE are considered as two different constructs. Also, after correlation of these two variables in SEM, CDSE is still directly and significantly influenced by PSS when the mediator, P-E fit, is added into the model, but the direct path from PSS to perceived employability is no longer significant at this point. Furthermore, post hoc analysis was performed to compare the unconstrained best fitting model (see Model 3 of Table 3) and one in which the perceived employability-CDSE correlation was constrained to one. Results demonstrated that the unconstrained model, which treats perceived employability and CDSE as distinct constructs, fit the data much better than the constrained model, Δχ ² (1) = 633.43, p < .001. This study presents initial evidence to support their distinctiveness.

Practical Implications

The present findings offer useful guidance for career management and counseling. First, as with previous studies (e.g., Creed et al., 2009; Di Fabio & Kenny, 2012), this study highlights the role of social support in individuals’ positive perceptions of their career situations. Career counselors in China should be aware that social support can be a direct source that increases people’s self-confidence in career decision making. With this informed evidence, counseling practitioners may consider designing interventions that lead to perceptions of more social support, so as to help clients become more confident about their involvement in activities related to career decisions. These interventions have been suggested to be effective when they expand and strengthen supportive social networks (Clarke, 2008).

In addition, the significant mediating effect of P-E fit provides new knowledge through which counselors can appreciate the psychological path linking social support to career decision processes. Career counselors in Chinese societies may need to consider not only the influences of contextual factors (e.g., support from social environments) but the congruence between an individual and his or her associated contexts or environments, in order to foster clients’ positive psychological states (e.g., CDSE and perceived employability) in the career development journey (Lent et al., 1994, 2002). It might be helpful for counselors to evaluate the level of the client’s P-E fit and seek targeted contextual sources of support to achieve positive psychological outcomes in the career environment.

Finally, the gender effects on the influence of social support on the career development process suggest that counseling practitioners should take into account male–female differences in developing relevant intervention strategies. In light of the present findings, when dealing with males, vocational counselors in China may incorporate more elements (e.g., network sources) associated with social contexts to facilitate matching individuals to environments, given that the effects of social support on P-E fit, and in turn those on career-relevant psychological states (e.g., CDSE and perceived employability), are greater for males than for females. The potential effectiveness of this practice is also implied in the fact that men, relative to women, to some extent lack social support and thus tend to be more sensitive to interventions making more support available (Antonucci & Akiyama, 1987; Lydall et al., 2010).

Limitations and Future Research Directions

Several limitations should be noted and may provide future avenues for research. First, the data were collected from a single source using self-report instruments. This approach has the potential to introduce common method bias (Podsakoff et al., 2003). Although CFA results indicated the results of the present study were less likely to be biased by the common method factor, it would be ideal for future research to use data from multiple sources. Second, despite the strong theoretical guidance in the literature (e.g., Creed et al., 2009; Di Fabio & Kenny, 2012), the cross-sectional design makes it difficult to infer causal relationships based on the empirical data used in the current study. The identified significant relationships among PSS, P-E fit, CDSE, and perceived employability need to be re-confirmed in future research that employs a longitudinal or experimental design. Third, as with many other studies (Creed et al., 2009), although this study used a general statement to ask students to reflect on their career development experiences when answering items for PSS and P-E fit, it is possible that this reflection in their mind diminished as they responded to more items. In this way, there might be some chance that the scores for career-specific PSS were slightly contaminated by elements of general PSS. Though previous research proves that both general and career-specific social support can have impacts on individuals’ career-related processes (Perry, Liu, & Pabian, 2010), general support appears to have a broader connotation, which may have confounded some results that are more specific for vocational development settings. Therefore, to increase the clarity of the results, future research can continue to verify the present research framework by employing a more thoroughly adapted PSS scale (e.g., adapt each item to fit the career context). Fourth, like many prior studies of careers (Creed et al., 2009), over half of the participants in this study were freshmen. This unbalanced sample composition would make the author somewhat reluctant to overly generalize the findings to students across the undergraduate span. However, in the present study, the sample and findings to a certain degree reflect the reality that today’s university students involve in career exploration and decision making at an early time point (Morgan & Ness, 2003). Future studies may test the conceptual model using samples that are evenly proportioned by year of study or have more juniors and seniors, who are more approaching to the stage of actual career decision.

Models	χ²/df	df	SRMR	RMSEA	CFI	AIC
1-Factor Model	49.62	54	.15	.25	.577	2,727.20
2-Factor Model A	36.99	53	.14	.21	.693	2,010.19
2-Factor Model B	41.43	53	.20	.23	.655	2,245.51
2-Factor Model C	34.79	53	.13	.21	.711	1,894.05
3-Factor Model A	24.34	51	.11	.17	.808	1,295.47
3-Factor Model B	25.58	51	.18	.18	.798	1,358.81
3-Factor Model C	23.75	51	.11	.17	.813	1,265.05
3-Factor Model D	15.10	51	.08	.13	.884	824.14
3-Factor Model E	20.37	51	.08	.16	.841	1,093.06
3-Factor Model F	16.86	51	.09	.08	.870	913.81
4-Factor Model	2.47	48	.03	.04	.989	178.34

Variables	Mean	SD	1	2	3
1. Perceived social support (PSS)	3.66	.57
2. Person–environment fit (P-E fit)	3.53	.63	.42***
3. Perceived employability	3.26	.76	.21***	.57***
4. Career decision self-efficacy (CDSE)	3.39	.48	.45***	.62***	.54***

Models	χ²/df	df	SRMR	RMSEA	CFI	AIC
Model 1 (full mediation model)	3.35	50	.05	.05	.98	223.55
Model 2 (partial mediation model A)	3.24	49	.05	.05	.98	216.61
Model 3 (partial mediation model B)	2.44	49	.03	.04	.99	177.49
Model 4 (partial mediation model C)	2.47	48	.03	.04	.99	178.34

Models	χ²	χ²/df	df	Δχ²	SRMR	RMSEA	CFI	AIC
1. Unconstrained model	192.67	1.97	98	–	.03	.04	.99	308.67
2. PSS → P-E fit equal	202.51	2.05	99	9.84 (1)**^a	.04	.04	.98	316.51
3. P-E fit → PE equal	192.74	1.95	99	.07 (1)^a	.03	.03	.99	306.74
4. P-E fit → CDSE equal	193.69	1.96	99	1.02 (1)^a	.03	.04	.99	307.69
5. PSS → P-E fit → PE equal	202.89	2.03	100	10.22 (2)**^a	.05	.04	.98	314.90
6. PSS → P-E fit → CDSE equal	202.90	2.03	100	10.23 (2)**^a	.04	.04	.98	314.90

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

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