Development and Initial Validation of a Perceived Future Employability Scale for Young Adults

Abstract

This study reports on development and initial validation of a scale to measure young adults’ perceptions of their future employability. Perceived future employability concerns young people’s perceptions of their future skills, experience, networks, personal traits, labor market knowledge, and institutional reputation at the time of completing their formal education, when they are on the verge of entering the labor market. In Phase 1, an initial item pool was developed from focus group discussions and expert feedback. In Phase 2, exploratory factor analyses reduced the number of items using data from a university student sample (N = 324). In Phase 3, confirmatory factor analyses tested the initial structure using data from a second sample of university students (N = 250). In Phase 4, construct validity was examined by correlating scale scores with measures of career ambition, university commitment, and career distress. The scale potentially (a) augments research on perceived future employability, (b) illuminates factors promoting employability and well-being in young adults, and (c) provides information to young adults who are concerned about their future career.

Keywords

perceived future employability career ambition university commitment future self career distress scale development

Perceived employability, or an individual’s perception of the chances of obtaining and/or maintaining employment (Akkermans & Kubasch, 2017; Vanhercke, De Cuyper, Peeters, & De Witte, 2014), is important for career goal setting and goal management and for how individuals behave, think, and feel about their occupation or career (Fugate, Kinicki, & Ashforth, 2004; Van der Heijde & Van der Heijden, 2005). Perceived future employability refers to the representation of one’s career self in the future (Ellen, Wiener, & Fitzgerald, 2012). For young adults, perceived future employability refers to how employable they perceive themselves to be in the future after training, education, and personal development (i.e., after completing their education and/or training and are ready to enter the labor market). As no measures are currently available to assess perceived future employability, this article reports on a study that developed and provided initial validation of a scale to measure this important construct.

The Employability Construct

First used at the beginning of the 20th century, the concept of employability differentiated between “employable” individuals (capable and willing and/or needing to work) and those who were “unemployable” (unable to work and needing help; Gazier, 1998). By the 1950s and 1960s, the concept had shifted to refer more to an attitude about work and the self, and in the 1970s, it was used to refer to the knowledge and abilities required for work. In the 1980s, it related to the transferable skills required for labor market flexibility, and since the 1990s, employability has referred to how individuals might maintain their job readiness, especially if they were at risk of having to change jobs (Guilbert, Bernaud, Gouvernet, & Rossier, 2016). The notion of “interactive employability,” which focused on individual adaptation, was introduced toward the end of the 20th century (Gazier, 1998). The construct has attracted much attention from governments, researchers, and professionals and has been studied in various disciplines including economics, education, and psychology (Rothwell, Jewell, & Hardie, 2009; Vanhercke et al., 2014).

Rothwell, Jewell, and Hardie (2009) identified three perspectives on employability: at the national workforce level (e.g., related to government policy), the human resource management level (e.g., considered as a component of human resource strategy), and the individual level (e.g., emphasizing individual beliefs about their employment options). The current study focused on the individual or psychological level, which is important to understanding individual perceptions of employability, and allows insight into processes that young people might use to take control of, and manage, their own career progress. Managing their own career progress has the potential to maximize benefits and satisfaction, as emergent workforce members strive for, and meet, their own needs and goals (DiRenzo, Greenhaus, & Weer, 2011; Weng & McElroy, 2012; Weng, McElroy, Morrow, & Liu, 2010).

Perceived Employability

The individual perspective focuses on the person’s own “perceived employability” (Berntson & Marklund, 2007), which “…potentially provides the individual with a feeling of security and a feeling of independence towards environmental circumstances” (Berntson, 2008, p. 19). Perceived employability has been examined in various groups and situations including undergraduate students entering the labor market (Knight & Yorke, 2004; Pool & Qualter, 2013; Pool, Qualter, & Sewell, 2014), older workers (Van der Heijde & Van der Heijden, 2005), temporarily employed workers (De Cuyper & DeWitte, 2010), unemployed (McArdle, Waters, Briscoe, & Hall, 2007) and long-term unemployed people (Koen, Klehe, & Van Vianen, 2013), people who have been released from prison (Graffam, Shinkfield, & Hardcastle, 2008), and those with disabilities (Bricout & Bentley, 2000).

Perceived employability has been defined as the individual’s perception of their own possibilities for maintaining existing, or finding new, employment (Berntson & Marklund, 2007; Vanhercke et al., 2014). It also has been referred to as self-perceived employability (Rothwell, Herbert, & Rothwell, 2008), graduate employability (Pool et al., 2014), or simply employability (Harvey, 2001; Hillage & Pollard, 1998; Knight & Yorke, 2004; van der Heijde, 2014; van der Heijde & van der Heijden, 2005). While these references indicate that the concept is widespread (Berntson, Naswall, & Sverke, 2010; Rothwell & Arnold, 2007), it remains “…in the relatively early stages of conceptual development” (Akkermans & Kubasch, 2017, p. 592). However, these perspectives have not been built on robust scientific theories, and definitions have tended to reflect researchers’ own perspectives. Thus, there is a need for more theoretical development and conceptual clarity for the construct (Akkermans & Kubbasch, 2017).

Dimensions of Perceived Employability

Several facets of perceived employability have been identified, including perceived skills, experience, network, personal characteristics, and labor market knowledge (Berntson & Marklund, 2007). Perceived skills encompass generic and job skills and related knowledge (Rothwell & Arnold, 2007; van der Heijde & van der Heijden, 2005), academic achievement (Pool et al., 2014; Rothwell et al., 2008), skilful practice (Knight & Yorke, 2004), job seeking skills, and employability assets (Harvey, 2001; Hillage & Pollard, 1998); all competencies related to obtaining and maintaining employment. Perceived experience includes job, work, and life experiences (Pool et al., 2014; Rothwell & Arnold, 2007), while networking refers to the extent and usefulness of the individual’s work and social connections (Rothwell & Arnold, 2007; van der Heijde & van der Heijden, 2005), especially those providing information on available jobs.

Personal characteristics refer to capacities related to learning and enhancing oneself and one’s skills (Rothwell & Arnold, 2007) and include agentic qualities that drive flexibility and adaptability, such as anticipation, self-efficacy, metacognitive competencies (Knight & Yorke, 2004; van der Heijde & van der Heijden, 2005), emotional intelligence, problem-solving, and self-management (Pool et al., 2014). Labor market knowledge covers awareness of opportunities in the labor market (Rothwell & Arnold, 2007; Rothwell et al., 2008), organizational and job sense (Harvey, 2001; Knight & Yorke, 2004; van der Heijde & van der Heijden, 2005), understanding career development and self-management (Pool et al., 2014), and adopting a strategic approach to occupational success (Hillage & Pollard, 1998). Based on these dimensions, perceived employability in the current study is considered to be an individual’s appraisal of their own skills, experience, networks, personal traits, and labor market knowledge.

Existing Measures of Perceived Employability

Currently available self-perceived employability measures are either unsuitable for use with young adults, as they were constructed to measure perceived employability in individuals who were already in work (e.g., Berntson & Marklund, 2007; Rothwell & Arnold, 2007), or were designed to measure current employability in young adults rather than perceptions of future employability after completing education/training (e.g., Pool et al., 2014; Rothwell et al., 2008). For example, Rothwell, Herbert, and Rothwell (2008) designed a self-perceived employability scale for undergraduate students, which was modified from the Self-Perceived Employability Scale for adults (Rothwell & Arnold, 2007), and Pool, Qualter, and Sewell (2014) developed the Employability Development Profile, which was designed for use with students from higher education institutions.

Perceived Future Employability

For young adults, perceived future employability is the representation of their occupational self after they have completed their study and/or training. Future selves (including future occupational selves) refer to an individual’s specific, individualized representations of what they might become (cf. future selves theory: Cross & Markus, 1991; Ellen et al., 2012; Markus & Nurius, 1986). Possible selves stimulate goal setting, planning, and goal striving behaviors; that is, they “…provide the means–ends patterns for new behaviors” (Markus & Nurius, 1986, p. 955). Thus, future selves can be considered to result from: “…the construction of prospective self-representations in terms of hopes and fears [that are] seen to provide a basis for anticipating future events, setting goals, planning, exploring options, making commitments, and subsequently guiding a developmental course” (Creed & Klisch, 2005, p. 252).

From this perspective, the perceived future employability of young adults drives their current occupational thoughts, affect, and behaviors. The relationship between future images and current behaviors has been demonstrated in a number of domains (Comello, 2015). For example, Oyserman, Bybee, Terry, and Hart-Johnson (2004) showed that future selves were related to achievement goals and, in turn, to academic performance in children. Krishnamurthy and Sujan (1999) found that adults with better self-referencing imagery about the future developed more, and more detailed, contextually relevant thoughts, which resulted in more positive attitudes and intentions than adult with poorer future self-referencing imagery. Pham and Taylor (1999) also found that better imagining of the future (e.g., studying behavior and getting good grades) increased students’ likelihood of engaging in the processes that led to the desired behavior.

Thus, positive images by an individual of their own future employability should be associated with the person engaging in detailed relevant thoughts about their current status (e.g., comparing where they are now to where they want to be; Lord, Diefendorff, Schmidt, & Hall, 2010) and lead them to implement strategies and behaviors (i.e., self-regulate) that will maintain their progress and improve their chances of fulfilling their future image (i.e., meet their employment goals). In sum, positive future self-views will be associated with engaging in behaviors that facilitate achieving positive outcomes. By contrast, negative future self-views entail pessimistic expectations or later threatening scenarios and tend to be associated with low engagement in goal-focused behaviors (Kornadt, Voss, & Rotrhermund, 2015).

Future selves most likely to influence behavior have been termed self-regulatory future selves (Oyserman, Bybee, Terry, & Hart-Johnson, 2004). These typically include self-defining goals and incorporate specific behavioral strategies for pursuing those goals. In the current study, it was expected that perceived future employability would correlate positively with career ambition and university commitment and correlate negatively with career distress. Career ambition, which is the perception of one’s future career success (Greenhaus, Parasuraman, & Wormley, 1990; Nabi, 2001), has been shown to be associated positively with individual employability (Rothwell et al., 2009), as has university commitment (Rothwell et al., 2008). As career distress reflects negative feelings toward the career decision-making process, it was expected to be associated negatively with perceived future employability (Larson, Toulouse, Ngumba, Fitzpatrick, & Heppner, 1994).

Current Study

An individual’s view of how employable they will be after completing their formal education is expected to be related to an appraisal of their current skills, experience, networks, personal traits, and their current perceived employability. When there is a discrepancy between their perceived future employability status and their current progress toward that imagined goal (e.g., appraisal that the goal might not be met), then the individual is likely to engage in behaviors that will reduce the discrepancy, or they will cognitively adjust their perceptions (e.g., lower their expectations about the future), or both (i.e., change behaviors and expectations). How close the individual comes to achieving their perceived future employability relies on the efficacy of the behaviors and the strategies applied (i.e., how well they self-regulate; Lord et al., 2010).

Assessing the relationship between perceived future employability and current behaviors (e.g., acquired skills, self-regulatory processes) is difficult, as no scale is currently adequate for making this comparison. Therefore, creating a scale to assess perceived future employability could stimulate research that can potentially enhance understanding of how young people plan for, and progress, their occupational goals. As a part of scale development, incremental validity of the newly devised scale will be assessed against an existing Individual Employability Scale (i.e., one that measures current employability; Rothwell et al., 2009) when predicting study effort, which is an indicator of how well young people are striving to achieve career-related goals (Butler, 2007). Construct validity will be assessed by examining associations between perceived future employability, career-related effort, university commitment, and career distress.

Method

Phase 1: Item Development

Phase 1 consisted of generating a set of well-articulated items to form the basis for the new scale and to support content validity (Hinkin, 1998). This is important in developing a valid scale and has been identified as best practice for scale development (Wright, Quick, Hannah, & Hargrove, 2017). Items were generated based on findings from a review of the perceived employability literature (e.g., Berntson & Marklund, 2007; Pool et al., 2014; Rothwell et al., 2008; van der Heijde & van der Heijden, 2005), conducting focus groups with young adults (Vogt, King, and King, 2004), and obtaining feedback from expert reviewers (Hinkin, 1998).

Focus groups were conducted with university and technical college students whose main role was study and preparing themselves for future employment. Twenty-two students (∼50% male, aged 18–30 years) reflected on key aspects of the perceived future employability construct. The aims were to (a) develop an understanding of young adults’ perceptions of perceived future employability (What do they think it is?), (b) validate the dimensions of perceived future employability (What domains do they perceive; do these overlap with those identified in the literature?), and (c) generate items that might be used to measure perceived future employability (e.g., What questions might they ask?). These steps were designed to support content validity for the scale (Hinkin, 1998; Vogt et al., 2004). The focus group discussions were audiotaped, transcribed, and used as a reference for item development.

A content analysis of the perceived future employability construct derived from the literature and the focus groups identified six potential dimensions of the construct as follows: (a) skills, (b) accumulated experiences, (c) personal characteristics, (d) networks, (e) labor market knowledge, and (f) reputation of educational institution attended (see Table 1). Based on this analysis, and consistent with Hinkin’s (1998) recommendation to generate approximately twice the number of items required for the final scale, 42 items were generated to cover the six dimensions. The aim was to develop a final scale of about 20 items that would represent the construct and minimize possible response biases due to boredom or fatigue (Schmitt & Stutts, 1985; Schriesheim & Eisenbach, 1995).

Table 1.
Dimensions of Perceived Future Employability.

Published Source Dimension 1 Dimension 2 Dimension 3 Dimension 4 Dimension 5 Other

Berntson and Marklund (2007) Perceived skills Experience Personal characteristics Networking Knowledge of labor market —

Rothwell and Arnold (2007) Transferable skills and knowledge, job skills Work experience Learning capacity, confidence, and organizational focus Networking Awareness of opportunities inside/outside organization —

Rothwell, Herbert, and Rothwell (2008) Education achievement — Vocational knowledge and skills, job search, and learning potential — Awareness of opportunities/demand in labor market Reputation/image of university, field of study

van der Heijde and van der Heijden (2005) Occupational expertise — Anticipation and personal flexibility (adaptability) Social capital (networking) Corporate sense Balance

Knight and Yorke (2004) Academic, life skills, and employment — Self-efficacy and metacognitions — Discipline knowledge and business knowledge —

Harvey (2001) Core work skills — Interest and capacity to learn, desired attributes on recruitment — Job goal Timely job success

Pool et al. (2014) Academic skills and performance Work and life experience Emotional intelligence, problem-solving, and self-management — Career development learning —

Hillage and Pollard (1998) Employment, skills, knowledge, and attitude — — — Career management, job search skills, and strategic approach Personal situation and labor market

Ten independent experts, including career development practitioners, researchers, and psychometric experts, who were independent from the researchers conducting the study, reviewed the 42 items. The experts rated each item as to how well it represented its nominated dimension, commented on the phrasing, and made suggestions for improvement or rewording to replace any items that they considered problematic. For all items, at least six experts rated them as adequate or better; thus, after some minor adjustments, all 42 were retained. The items were also tested for readability using the Flesch Reading Ease Scale (readability score = 58.7/100) and the Flesch–Kincaid Grade Level measure (readability grade level 8.9), indicating that the items were suitable for respondents with Grade 9–level schooling or better (Calderon, Morales, Liu, & Hays, 2006). After piloting the items with a small group of the target population (N = 7), the 42 items, together with demographic questions and two scales used to assess incremental validity, were compiled into a questionnaire and administered to a sample of university students.

Phase 2: Item Analysis and Exploratory Factor Analysis

The aim of this phase was to identify items to be retained in the new scale, which was labeled the Perceived Future Employability Scale (PFES), using item analysis and exploratory factor analysis.

Participants

These were 324 young adults (62.3% female, mean age = 20.77 years, SD = 5.70, range = 17–30). Mean self-reported academic level in the final year of high school was 1.90 (SD = 0.67; 5-point scale from 1 = very high achievement to 5 = very limited achievement). As a proxy for socioeconomic status (cf. European Social Survey, 2010), participants indicated, compared to their peers, how they would describe their current economic position: 18 (5.6%) indicated they were much better off than others, 83 (25.6%) a little better off, 146 (45%) about the same, 68 (21%) a little worse off, and 9 (2.8%) much worse off than others (mean = 2.90, SD = 0.89). Participants were mainly domestic students, with a small number of international students, recruited from one university in a large regional city on the east coast of Australia. As is typical of Australian universities, the participating university population comprised approximately 89% domestic Australian (mainly Caucasian) students.

Materials

PFES

These were the 42 items generated in Phase 1, which were developed to reflect the six potential domains of perceived future employability (future skills, accumulated experiences, personal characteristics, networks, labor market knowledge, and reputation of educational institution attended). Participants responded to each item with a Likert-type format, with options ranging from 1 = strongly disagree to 6 = strongly agree.

Individual Employability Scale

This was assessed using the 6-item Individual Employability Scale (Rothwell et al., 2009), which assessed students’ current perceived employability. A sample item is, “The skills and abilities that I possess are what employers are looking for” (response option from 1 = strongly disagree to 6 = strongly agree). The scale developers reported an internal reliability coefficient of .72 and supported validity by finding that the scale related positively to student ambition and university commitment (Rothwell et al., 2009). The value of α for the current sample was .85.

Study effort

The 9-item University Effort Scale (Butler, 2007) measures effort expended on various tasks related to university achievement. A sample item is, “I put in a high level of effort at my studies” (response format from 1 = strongly disagree to 6 = strongly agree). Butler (2007) reported an α internal reliability of .88 and found the scale to be related positively to attendance, grade point average, and university satisfaction, as expected. Cronbach’s α for the current sample was .90.

Procedure

The authors’ University Human Research Ethics Committee approved the study. The online survey was advertised via a university-wide e-mail sent to all students. Participants could enter a prize draw for a AUD50 shopping voucher.

Results

Item Analysis

Item distributions were assessed (heavily skewed and kurtotic items were marked for deletion), interitem correlations were calculated (correlations > .80 were marked for deletion), and corrected item–total correlations were examined (correlations < 30 were marked for deletion; Gorsuch, 1997; Klein, 2000). No items were removed based on these analyses.

Exploratory Factor Analysis

The Kaiser–Meyer–Olkin measure of sampling adequacy (.94) and Bartlett’s test of sphericity (p < .001) indicated that the 42 items were suitable for factor analysis. Factor analyses were conducted using principal axis factoring extraction and direct oblimin rotations, as the underlying domains were expected to be correlated (Hair, Black, Babin, & Anderson, 2010). Recommendations by Hayton, Allen, and Scarpello (2004), Hinkin (1998), Kahn (2006), O’Connor (2000), and Patil, Singh, Mishra, and Donovan (2008) were followed. A combination of decision rules was used to determine the number of factors to be retained, including the scree plot, Velicer’s minimum average partial test, parallel analysis (O’Connor, 2000), a minimum of 3 items per factor (Costello & Osborne, 2005), and factor interpretability (Hinkin, 1998).

The scree plot, Velicer’s minimum average partial test, and a parallel analysis all indicated a six-factor solution. Being consistent with our expected six domains, this solution was accepted for the PFES. Items with factor loadings <.40 or cross-loading items (≥ .30; Costello & Osborne, 2005) were deleted one at a time, and the analysis was rerun after each item deletion. This left 24 items (4 per factor) accounting for 79.03% of the variance, exceeding the recommended minimum 60% target (Hinkin, 1998). All items showed acceptable corrected item–total correlations (range .53–.95; Costello & Osborne, 2005). See Table 2 for final item selection and factor loadings.

Table 2.
Factor Loadings for Perceived Future Employability Scale Items.

Factor Factor Loading

Item stem: “When I complete my studies…” F1 F2 F3 F4 F5 F6

Perceived future network

…I will be able to draw on the network I have developed to succeed at my work .95 −.02 .03 .01 .01 .03

…I will have built up a social network that will help me do well in my job .92 −.02 .035 .05 .03 .02

…I will have developed a network of contacts who can help identify potential work opportunities .80 .11 −.00 .02 −.06 −.04

…I will know how to network with people who can help me find work in my chosen career .72 .03 .02 −.02 −.13 .03

Perceived expected experiences

…I will have had relevant work experience applying the knowledge acquired in my studies −.07 .91 −.03 −.07 .00 .06

…future employers will be impressed with the relevant work experience I have accumulated −.10 .87 .01 .10 .03 −.03

…future employers will be satisfied with the work experiences I have gained .04 .66 .14 .10 −.11 .01

…I will be able to show future employers that I have the required practical skills and academic experience they require .02 .53 −.01 .01 −.11 .33

Perceived future personal characteristics

…my experiences will show that I have developed resilience and do not give up easily .10 .06 .87 −.03 −.06 −.03

…prospective employers will be able to see from what I have achieved that I am well motivated −.08 −.02 .84 .00 .01 −.01

…prospective employers will be able to see that I have clear goals for myself −.03 .02 .75 −.04 −.07 .01

…my record will show that I have a strong work ethic −.06 −.04 .70 .08 .08 .08

Anticipated reputation of educational institution

…I will have an advantage as future employers will be more likely to recruit graduates from my institution than from other Institutions −.07 .07 .01 .87 .12 −.07

…the reputation of my educational institution will be a significant asset to me in job seeking −.01 −.02 .01 .81 .01 .05

…I will have a lot of work opportunities open to me because my teaching institution has strong partnerships with many potential employers .01 .02 .02 .80 −.10 .02

…I will be in demand because graduates from my institution are well prepared for work roles that are in high demand −.01 −.01 −.03 .65 −.21 .11

Perceived future labor market knowledge

…I will have developed a good understanding of the variety of work opportunities available to me −.01 −.05 .04 .04 −.85 .06

…I will know the steps I need to take to do well in my chosen career −.03 .11 .08 .05 −.77 −.07

…I will have developed the ability to find out about job opportunities in my chosen field −.16 −.02 .06 −.06 −.70 .09

…I will be up-to-date with occupational trends in my chosen field −.07 .14 −.03 .09 −.62 .03

Perceived future skills

…I will have gained the knowledge required to get the job I want −.01 .08 −.02 .01 .05 .82

…I will have the relevant skills for the occupation I choose −.01 −.00 −.01 −.09 −.07 .78

…future employers will see that I will have learned the right discipline specific/technical skills and knowledge that they want .11 .07 .09 .10 −.08 .70

…I will have developed the reasoning and problem-solving skills that future employers often require −.05 −.02 .09 .12 .01 .65

Note. N = 324.

Incremental Validity Check

As an initial test of the incremental validity, and thus, usefulness of the PFES (cf. Haynes & Lench, 2003), a hierarchical linear multiple regression analysis was undertaken to establish whether the PFES explained additional variance in a relevant variable (i.e., study effort) over and above that explained by an existing measure of employability (i.e., the Individual Employability Scale; Rothwell et al., 2009). At Step 1 in the regression analysis, the Individual Employability Scale accounted for 8.5% of the variance in study effort, F(1, 322) = 30.82; p < .001. At Step 2, the PFES total score accounted for an additional 7.3% of the variance (15.8% total variance explained), F _Change(1, 321) = 27.98; p < .001, suggesting that the PFES was a better predictor of student striving than an existing measure of current perceived employability, as would be expected from future selves theory (Markus & Nurius, 1986).

Phase 3: Confirmatory Factor Analyses

The aim of this phase was to confirm the factor structure of the PFES on a second sample of students.

Participants

Participants were a new sample of 250 students (83.2% female, mean age = 21.18 years, SD = 4.34, range = 17–30), recruited from the same institutions as for Phases 1 and 2, and answered the same biographic questions. The sample was primarily domestic and Caucasian (61%) and had a mean self-reported academic level from final year of high school of 2.02 (SD = 0.67) and a mean of socioeconomic status (SES) of 2.96 (SD = 0.94).

Materials

Perceived future employability

The 24-item PFES developed in Phases 1 and 2 was used in these analyses (6-point response format from 1 = strongly disagree to 6 = strongly agree; see Table 2 for full stem and items). Internal reliability coefficients with this sample were .95 (full scale), .88 (future skills), .92 (accumulated experiences), .88 (personal characteristics), .95 (networks), .91 (labor market knowledge), and .89 (reputation of educational institution attended).

Career ambition

A 6-item Career Ambition Scale, which was derived from the Individual Employability Scale (Rothwell et al., 2009), was used to represent perceptions of future career success. A sample item was, “I am satisfied with the progress I have made meeting my goals for career development” (response format from 1 = strongly disagree to 6 = strongly agree). This scale has been used previously with young adults, where validity was supported by showing that the scale related positively to perceived employability and university commitment (Rothwell et al., 2009). The internal reliability coefficient for the current sample was .77.

University commitment

The 7-item University Commitment Scale measured participants’ commitment to their tertiary institution (Rothwell et al., 2008). A sample item was, “I am extremely glad I chose this university over others I was considering at the time I joined” (response format from 1 = strongly disagree to 6 = strongly agree). The scale has demonstrated good psychometric properties with young adult samples, including an internal reliability coefficient of .87, and correlations with other scales, such as perceived employability, in the expected direction. The value of α for the current sample was .92.

Career distress

This was measured with the 9-item Career Distress Scale (Creed, Hood, Praskova, & Makransky, 2016). A sample item was, “I often feel down or depressed about selecting a career” (response format from 1 = strongly disagree to 6 = strongly agree). The scale has good psychometric properties with young adults, including an internal reliability of .90 and, in support of validity, negative associations with positive affect and positive associations with negative affect (Creed et al., 2016). The value of α for the current sample was .93.

Results

Confirmatory factor analysis (AMOS v24), which can assess how well obtained data fit a proposed factor structure (van Prooijen & van der Kloot, 2001), was used to test the factor structure of the 24-item PFES identified in Phase 2. Four models were assessed. First, a six-factor model representing the six factors identified in Phase 2 was tested. In this model, each cluster of 4 items identified in Phase 2 was assigned to its respective latent variable, and correlations among the six latent variables were freely estimated. Second, a single-factor model with all items loaded onto a single latent variable was tested. This model assessed whether all items could be represented by a unidimensional scale. Third, a second-order, hierarchical model with a single, second-order latent variable representing the six factors from Phase 2 was tested. This model assessed whether the six factors could be represented by a single, higher level factor. Fourth, a bifactor model was tested, in which each item was allowed to load on a general factor as well as to load onto each factor individually. This model assessed the proportion of common item variance accounted for by the general factor, while controlling for the group factors, and vice versa.

Model fit was assessed using χ², normed χ² (χ²/df), comparative fit index (CFI), and root mean square error of approximation (RMSEA), as suggested by Hair, Black, Babin, and Anderson (2010). With 250 participants and 24 observed variables, a significant χ² value is expected, and χ²/df < 3.0, CFI > .92, and RMSEA < .05 indicate an acceptable fit. Differences between the nonembedded models were assessed using the Akaike information criterion (AIC), with the lower values indicating better fit (Hair et al., 2010).

Fit statistics for the four models are in Table 3. Summary data and bivariate correlations among scales are in Table 4. All models produced a satisfactory fit except for the one-factor model, thereby ruling this model out as a potential fit for the data. Of the remaining three models (six-factor, second-order, and bifactor), the bifactor model had the best fit statistics and the lowest AIC. Thus, the bifactor model was accepted as the best representation of the data. A bifactor model is a latent structure with individual items loading onto a general factor, which reflects what is common among the items, and also loading onto the individual factors, which represent individual differences among the target dimensions. A bifactor structure specifies two or more orthogonal “group” factors. These group factors (in this case, future skills, accumulated experiences, personal characteristics, networks, labor market knowledge, and reputation of educational institution attended) represent common factors explaining item response variance not accounted for by the general factor.

Table 3.
Goodness-of-Fit Statistics for CFA Models.

Model χ² df χ²/df CFI RMSEA AIC

Six factor 529.6* 237 2.2 .94 .07 655.63

One factor 2,432.9* 252 9.6 .55 .19 2,528.95

Second-order factor 563.8* 246 2.3 .94 .07 671.78

Bifactor 471.6* 228 2.1 .95 .06 615.59

Note. N = 250. AIC = Akaike information criterion; CFA = confirmatory factor analysis; CFI = Comparative Fit Index; df = degrees of freedom; RMSEA = root mean square error of approximation.

p < .001.

Table 4.
Means, Standard Deviations, and Correlations Among Scales.

Variable 1 2 3 4 5 6 7 8 9 10 11 12

1. PFES total —

2. PFES F1: Skills .76 —

3. PFES F2: Experience .82* .65* —

4. PFES F3: Person characteristics .71* .50* .43* —

5. PFES F4: Networks .81* .46* .58* .49* —

6. PFES F5: Market knowledge .83* .56* .61* .54* .65* —

7. PFES F6: Institution reputation .74* .48* .51* .43* .50* .53* —

8. Career ambition .65* .51* .48* .52* .54* .62* .39* —

9. University commitment .59* .39* .41* .44* .43* .51* .56* .43* —

10. Career distress −.39* −.35* −.29* −.34* −.29* −.41* −.16* −.45* −.36* —

11. Age −.04 .03 .04 .09 −.09 −.02 −.19 .09 −.12 −.21 —

12. Gender .07 .06 .03 .08 .10 .05 −.01 .06 −.11 −.01 −.05 —

Mean 139.88 24.49 22.60 24.82 21.72 23.72 22.53 29.61 33.01 27.61 21.18 —

SD 18.39 3.32 4.43 3.39 4.62 3.75 4.01 3.84 5.86 10.45 4.34 —

Note. PFES = Perceived Future Employability Scale.

p < .01. *p < .001.

The six-factor, second-order, and bifactor models all supported multidimensionality of the PFES. However, despite this demonstrated multidimensionality, it still needs to be determined whether the PFES is better reflected as a general factor (i.e., used at the total score level) or whether it is more reliably interpreted at the specific factor level (i.e., at the subscale level). Based on recommendations by Rodriguez, Reise, and Haviland (2016), and using the Bifactor Indices Calculator (Dueber, 2017), four bifactor coefficients (ω, ωH, relative ω, and the explained common variance) were calculated to aid with this determination.

The bifactor coefficient ω, which is the model-based reliability estimate reflecting the proportion of variance accounted for when considering all items, was .97 for the general factor and .88, .92, .88, .95, .91, and .90 for the specific factors, indicating good reliability for the general factor and sound to good reliability for the specific factors. ωH, the proportion of unique variance accounted for by the general factor, was .86; the ωH coefficients for the specific factors were .38 (future skills), .34 (accumulated experiences), .53 (personal characteristics), .46 (networks), .19 (labor market knowledge), and .53 (reputation of educational institution). When ωH > .80, a multidimensional construct is better considered at the total item level rather than the subscale level (Rodriguez, Reise, & Haviland, 2016). Relative ω is the proportion of reliable variance due to a factor. For the general factor, this was .88; for the specific factors, the statistics were .43, .37, .60, .48, .21, and .59, respectively; again, supporting interpretation at the general factor level. Last, the explained common variance, or the proportion of common variance explained by a factor, was .55 for the general factor and .07, .07, .09, .09, .04, and .09, respectively, for the specific factors. These results suggested that using the global score would provide the most meaningful measure of perceived future employability, with much less variance accounted for when interpreted at the subscale level; that is, the scale is best applied at a global level.

Phase 4: Construct Validity

The aim of this phase was to provide initial support for construct validity of the scale by correlating the total PFES score with scores from measures of career ambition, university commitment, and career distress. As expected, positive correlations were found between PFES total and career ambition (r = .65) and university commitment (r =.59), and the PFES was correlated negatively with career distress (r = −.39), indicating that the PFES was related appropriately to variables identified in its nomological net. We also noted that the PFES total score was uncorrelated with age and gender, suggesting no inherent bias in the scale in relation to these variables.

Discussion

This study reported on the development and validation of a measure of young adults’ perceived future employability, which concerns their perceptions of their future skills, experience, networks, personal traits, labor market knowledge, and institutional reputation at the time of completing their formal education when they are on the verge of entering the labor market. This employability concept is important as an emerging quality that can enable workers to adapt and thrive in the contemporary workforce. No scales had previously been developed specifically to assess perceived future employability in young adults who have as one of their main developmental foci their future career.

The study advances theoretical understanding of how perceived future employability is manifested in young adults who are preparing themselves for the workforce. It also contributes to the existing, but limited, perceived employability literature, which has focused primarily on working adults, and within organizational contexts that involved employees and job seekers who were moving, or who had been forced to move, between employers. Based on the perceived employability literature (e.g., Berntson & Marklund, 2007; Rothwell & Arnold, 2007), perceived future employability was operationalized as a multidimensional construct (i.e., perceptions of future skills, experience, networks, personal traits, labor market knowledge, and institutional reputation).

A psychometrically sound, 24-item measure was devised to assess perceived future employability (i.e., the PFES). Subsequent analyses supported that the PFES was multifactorial but that it should be interpreted using the global-level score rather than at the subscale level. The global measure was found to have good internal reliability, and initial evidence for the validity of the measure was also obtained. First, the study demonstrated that the PFES accounted for additional variance in study effort, an important variable representing student goal striving, over and above that explained by an existing employability scale. Second, the PFES was shown to be related to other important career variables (i.e., career ambition, university commitment, and career distress) in expected ways.

The scale can be used to examine perceived future employability in young adult, college/university students. This will allow scholars to test the correlates of perceived future employability (e.g., motivation, performance, and well-being) and to test how these relationships change over time as perceived future employability changes. For university students (current perceptions of), employability has been related to constructs such as self-efficacy, self-esteem, and self-confidence (Pool & Sewell, 2007). For adults, employability has been associated negatively with job insecurity (Berntson et al., 2010; De Cuyper, Mäkikangas, Kinnunen, & Mauno, 2012), burnout (Aybas, Elmas, & Dündar, 2015), and other job-related maladjustments (Berntson et al., 2010). It has also been associated positively with job search behaviors (Chen & Lim, 2012), adaptation to change (Berntson, Sverke, & Marklund, 2006; Fugate et al., 2004), job satisfaction (Giorgi, Shoss, & Leon-Perez, 2015), and well-being (Berntson & Marklund, 2007; Silla, De Cuyper, Gracia, Peiró, & De Witte, 2009). However, previous research has primarily used workplace samples and examined current employability. It remains to be determined how perceived future employability relates to important variables for young adults who are not currently employed.

Caricati, Chiesa, Guglielmi, and Mariani (2016) suggested that perceived employability could be linked credibly to employment success. Demonstrating a connection between perceived future employability and labor market outcomes will support the predictive validity of the PFES, inform interventions that could boost students’ realistic employability perceptions, and provide them with the most efficacious strategies. If predictive validity is demonstrated, this will also enable an evaluation of how well universities and other training/educational bodies are accomplishing the task of building bridges between the educational system and the labor market. Tomlinson (2012) noted that “…some students on the point of transiting to employment are significantly more orientated towards the labour market than others” (p. 422). Further research is needed to explain this variability; for example, do students who invest in longer and more demanding academic curricula develop stronger identities and forms of identification with a specific future pathway or are other variables operating? Studies have found that higher levels of education are associated with stronger perception of employability (Berntson et al., 2006; Wittekind, Raeder, & Grote, 2010).

This new scale could also be useful as a screening device for use by academic advisors, counselors, student services’ personnel, human resource professionals, and others who work with students who are preparing themselves for future employment. An examination of item and subscale responses could alert practitioners to the multiple dimensions of perceived future employability. This might assist them to help students develop those aspects of their future view that are most problematic and allow them to provide targeted, effective strategies to enhance student employability.

Limitations

The study was conducted at one university in one country, and the applicability of the scale needs to be tested in other samples. The current study sample also contained disproportionately more female than male students, and a majority of participants were enrolled in social science and health courses. No significant association was found between PFES and gender (or age), and there is no reason to expect that men and women studying at university level would report different levels (cf. Caricati, Chiesa, Guglielmi, & Mariani, 2016). However, validation of the scale in more diverse samples, where there is a more equal gender balance, needs to be undertaken. This would allow, for example, testing for gender (and age and other) invariance. Last, it was not possible to test the predictive validity of the new measure. This would mean, for example, assessing whether higher scale scores at one point in time was associated with stronger academic engagement and better well-being later, for which longitudinal studies will be required. Assessing test–retest reliability is another task for future studies.

Conclusion

The findings indicated that this newly developed PFES measure shows promise as a reliable and valid measure of perceived future employability in young adults. Further research with the scale is needed to augment validity, but having a scale to assess perceived future employability in young adults will allow researchers to develop a better understanding of young people’s perceptions of their occupational futures and how these relate to current behavior, cognitions, and affect.

Published Source	Dimension 1	Dimension 2	Dimension 3	Dimension 4	Dimension 5	Other
Berntson and Marklund (2007)	Perceived skills	Experience	Personal characteristics	Networking	Knowledge of labor market	—
Rothwell and Arnold (2007)	Transferable skills and knowledge, job skills	Work experience	Learning capacity, confidence, and organizational focus	Networking	Awareness of opportunities inside/outside organization	—
Rothwell, Herbert, and Rothwell (2008)	Education achievement	—	Vocational knowledge and skills, job search, and learning potential	—	Awareness of opportunities/demand in labor market	Reputation/image of university, field of study
van der Heijde and van der Heijden (2005)	Occupational expertise	—	Anticipation and personal flexibility (adaptability)	Social capital (networking)	Corporate sense	Balance
Knight and Yorke (2004)	Academic, life skills, and employment	—	Self-efficacy and metacognitions	—	Discipline knowledge and business knowledge	—
Harvey (2001)	Core work skills	—	Interest and capacity to learn, desired attributes on recruitment	—	Job goal	Timely job success
Pool et al. (2014)	Academic skills and performance	Work and life experience	Emotional intelligence, problem-solving, and self-management	—	Career development learning	—
Hillage and Pollard (1998)	Employment, skills, knowledge, and attitude	—	—	—	Career management, job search skills, and strategic approach	Personal situation and labor market

Factor	Factor Loading
Perceived future network
…I will be able to draw on the network I have developed to succeed at my work	.95	−.02	.03	.01	.01	.03
…I will have built up a social network that will help me do well in my job	.92	−.02	.035	.05	.03	.02
…I will have developed a network of contacts who can help identify potential work opportunities	.80	.11	−.00	.02	−.06	−.04
…I will know how to network with people who can help me find work in my chosen career	.72	.03	.02	−.02	−.13	.03
Perceived expected experiences
…I will have had relevant work experience applying the knowledge acquired in my studies	−.07	.91	−.03	−.07	.00	.06
…future employers will be impressed with the relevant work experience I have accumulated	−.10	.87	.01	.10	.03	−.03
…future employers will be satisfied with the work experiences I have gained	.04	.66	.14	.10	−.11	.01
…I will be able to show future employers that I have the required practical skills and academic experience they require	.02	.53	−.01	.01	−.11	.33
Perceived future personal characteristics
…my experiences will show that I have developed resilience and do not give up easily	.10	.06	.87	−.03	−.06	−.03
…prospective employers will be able to see from what I have achieved that I am well motivated	−.08	−.02	.84	.00	.01	−.01
…prospective employers will be able to see that I have clear goals for myself	−.03	.02	.75	−.04	−.07	.01
…my record will show that I have a strong work ethic	−.06	−.04	.70	.08	.08	.08
Anticipated reputation of educational institution
…I will have an advantage as future employers will be more likely to recruit graduates from my institution than from other Institutions	−.07	.07	.01	.87	.12	−.07
…the reputation of my educational institution will be a significant asset to me in job seeking	−.01	−.02	.01	.81	.01	.05
…I will have a lot of work opportunities open to me because my teaching institution has strong partnerships with many potential employers	.01	.02	.02	.80	−.10	.02
…I will be in demand because graduates from my institution are well prepared for work roles that are in high demand	−.01	−.01	−.03	.65	−.21	.11
Perceived future labor market knowledge
…I will have developed a good understanding of the variety of work opportunities available to me	−.01	−.05	.04	.04	−.85	.06
…I will know the steps I need to take to do well in my chosen career	−.03	.11	.08	.05	−.77	−.07
…I will have developed the ability to find out about job opportunities in my chosen field	−.16	−.02	.06	−.06	−.70	.09
…I will be up-to-date with occupational trends in my chosen field	−.07	.14	−.03	.09	−.62	.03
Perceived future skills
…I will have gained the knowledge required to get the job I want	−.01	.08	−.02	.01	.05	.82
…I will have the relevant skills for the occupation I choose	−.01	−.00	−.01	−.09	−.07	.78
…future employers will see that I will have learned the right discipline specific/technical skills and knowledge that they want	.11	.07	.09	.10	−.08	.70
…I will have developed the reasoning and problem-solving skills that future employers often require	−.05	−.02	.09	.12	.01	.65

Model	χ²	df	χ²/df	CFI	RMSEA	AIC
Six factor	529.6***	237	2.2	.94	.07	655.63
One factor	2,432.9***	252	9.6	.55	.19	2,528.95
Second-order factor	563.8***	246	2.3	.94	.07	671.78
Bifactor	471.6***	228	2.1	.95	.06	615.59

Variable	1	2	3	4	5	6	7	8	9	10	11	12
1. PFES total	—
2. PFES F1: Skills	.76***	—
3. PFES F2: Experience	.82***	.65***	—
4. PFES F3: Person characteristics	.71***	.50***	.43***	—
5. PFES F4: Networks	.81***	.46***	.58***	.49***	—
6. PFES F5: Market knowledge	.83***	.56***	.61***	.54***	.65***	—
7. PFES F6: Institution reputation	.74***	.48***	.51***	.43***	.50***	.53***	—
8. Career ambition	.65***	.51***	.48***	.52***	.54***	.62***	.39***	—
9. University commitment	.59***	.39***	.41***	.44***	.43***	.51***	.56***	.43***	—
10. Career distress	−.39***	−.35***	−.29***	−.34***	−.29***	−.41***	−.16***	−.45***	−.36***	—
11. Age	−.04	.03	.04	.09	−.09	−.02	−.19**	.09	−.12	−.21**	—
12. Gender	.07	.06	.03	.08	.10	.05	−.01	.06	−.11	−.01	−.05	—
Mean	139.88	24.49	22.60	24.82	21.72	23.72	22.53	29.61	33.01	27.61	21.18	—
SD	18.39	3.32	4.43	3.39	4.62	3.75	4.01	3.84	5.86	10.45	4.34	—

Footnotes

Authors’ Note

This research project is being conducted as part of the requirements of the doctor of philosophy degree, undertaken by William Gunawan, and supervised by Prof Peter Creed and A/Prof Ian Glendon. The research is investigating (1) the perceptions that young adults have of their future, particularly their career future and (2) how these perception influences their current behavior and well-being.

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.

References

Akkermans

Kubasch

(2017). Trending topics in careers: A review and future research agenda. Career Development International, 22, 586–627. doi:10.1108/CDI-08-2017-0143

Aybas

Elmas

Dündar

G. I.

(2015). Job insecurity and burnout: The moderating role of employability. European Journal of Business and Management, 7, 195–202. Retrieved from www.iiste.org/Journals/index.php/EJBM/article/viewFile/21200/21544

Berntson

(2008). Employability perceptions: Nature, determinants, and implications for health and well-being (PhD thesis). Stockholm University, Stockholm, Sweden.

Berntson

Marklund

(2007). The relationship between perceived employability and subsequent health. Work and Stress, 21, 279–292. doi:10.1080/02678370701659215

Berntson

Näswall

Sverke

(2010). Investigating the relationship between employability and self-efficacy: A cross-lagged analysis. European Journal of Work and Organizational Psychology, 17, 413–425. doi:10.1080/13594320801969699

Berntson

Sverke

Marklund

(2006). Predicting perceived employability: Human capital or labour market opportunities? Economic and Industrial Democracy, 27, 223–244. doi:10.1177/0143831X06063098

Bricout

J. C.

Bentley

K. J.

(2000). Disability status and perceptions of employability by employers. Social Work Research, 24, 87–95. doi:10.1093/swr/24.2.87

Butler

A. B.

(2007). Job characteristics and college performance and attitudes: A model of work-school conflict and facilitation. Journal of Applied Psychology, 92, 500–510. doi:10.1037/0021-9010.92.2.500

Calderon

J. L.

Morales

L. S.

Liu

Hays

R. D.

(2006). Variation in the readability of items within surveys. American Journal of Medical Quality, 21, 49–56. doi:10.1177/1062860605283572

10.

Caricati

Chiesa

Guglielmi

Mariani

M. G.

(2016). Real and perceived employability: A comparison among Italian graduates. Journal of Higher Education Policy and Management, 38, 490–502. Retrieved from http://www-tandfonline-com.libraryproxy.griffith.edu.au/loi/cjhe20

11.

Chen

D. Q.

Lim

V. G.

(2012). Strength in adversity: The influence of psychological capital on job search. Journal of Organizational Behavior, 33, 811–839. doi:10.1002/job.1814

12.

Comello

M. L.

(2015). How does a risk-oriented “future-self” influence behavior? A structural-equation-modeling approach with marijuana-related outcomes. Journal of Health Psychology, 20, 37–47. doi:10.1177/1359105313498107

13.

Costello

A. B.

Osborne

J. W.

(2005). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Practical Assessment, Research & Evaluation, 10, 1–9. Retrieved from https://pareonline.net/pdf/v10n7.pdf

14.

Creed

P. A.

Hood

Praskova

Makransky

(2016). The career distress scale: Using Rasch measurement theory to evaluate a brief measure of career distress. Journal of Career Assessment, 24, 732–746. doi:10.1177/1069072715616126

15.

Creed

P. A.

Klisch

(2005). Future outlook and financial strain: Testing the personal agency and latent deprivation models of unemployment and well-being. Journal of Occupational Health Psychology, 10, 251–260. doi:10.1037/1076-8998.10.3.251

16.

Cross

Markus

(1991). Possible selves across the life-span. Human Development, 34, 225–230. doi:10.1159/000277058

17.

De Cuyper

De Witte

(2010). Temporary employment and perceived employability: Mediation by impression management. Journal of Career Development, 37, 635–652. doi:10.1177/0894845309357051

18.

De Cuyper

Mäkikangas

Kinnunen

Mauno

(2012). Cross-lagged associations between perceived external employability, job insecurity, and exhaustion: Testing gain and loss spirals according to the conservation of resources theory. Journal of Organizational Behavior, 33, 770–788. doi:10.1002/job.1800

19.

DiRenzo

M. S.

Greenhaus

J. H.

Weer

C. H.

(2011). Job level, demands, and resources as antecedents of work–family conflict. Journal of Vocational Behavior, 78, 305–314. doi:10.1016/j.jvb.2010.10.002

20.

Dueber

D. M.

(2017). Bifactor indices calculator: A Microsoft excel-based tool to calculate various indices relevant to bifactor CFA models. doi:10.13023/edp.tool.01. Retrieved from http://sites.education.uky.edu/apslab/resources/

21.

Ellen

P. S.

Wiener

J. L.

Fitzgerald

M. P.

(2012). Encouraging people to save for their future: Augmenting current efforts with positive visions of the future. Journal of Public Policy & Marketing, 31, 58–72. doi:10.1509/jppm.09.089

22.

European Social Survey. (2010). ESS round 5 source questionnaire. London, England: Centre for Comparative Social Surveys Retrieved from http://www.europeansocialsurvey.org/methodology/questionnaire/

23.

Fugate

Kinicki

A. J.

Ashforth

B. E.

(2004). Employability: A psycho-social construct, its dimensions, and applications. Journal of Vocational Behavior, 65, 14–38. doi:10.1016/j. jvb.2003.10.005

24.

Gazier

(1998). Employability: Definitions and trends. In Gazier

(Ed.), Employability: Concepts and policies (pp. 37–71). Berlin, Germany: European Employment Observatory.

25.

Giorgi

Shoss

M. K.

Leon-Perez

J. M.

(2015). Going beyond workplace stressors: Economic crisis and perceived employability in relation to psychological distress and job dissatisfaction. International Journal of Stress Management, 22, 137–158. doi:10.1037/a0038900

26.

Gorsuch

R. L.

(1997). Exploratory factor analysis: Its role in item analysis. Journal of Personality Assessment, 68, 532–560. doi:10.1207/s15327752jpa6803_5

27.

Graffam

Shinkfield

A. J.

Hardcastle

(2008). The perceived employability of ex-prisoners and offenders. International Journal of Offender Therapy and Comparative Criminology, 52, 673–685. doi:10.1177/0306624X07307783

28.

Greenhaus

J. H.

Parasuraman

Wormley

W. M.

(1990). Effects of race on organizational experiences, job performance evaluations, and career outcomes. Academy of Management Journal, 33, 64–86. doi:10.2307/256352

29.

Guilbert

Bernaud

Gouvernet

Rossier

(2016). Employability: Review and research prospects. International Journal for Educational and Vocational Guidance, 16, 69–89. doi:10.1007/s10775-015-9288-4

30.

Hair

J. F.

Black

W. C.

Babin

B. J.

Anderson

R. E.

(2010). Multivariate data analysis. A global perspective (7th ed.). Upper Saddle River, NJ: Prentice Hall.

31.

Harvey

(2001). Defining and measuring employability. Quality in Higher Education, 7, 97–110. doi:10.1080/13538320120059990

32.

Haynes

S. N.

Lench

H. C.

(2003). Incremental validity of new clinical assessment measures. Psychological Assessment, 15, 456–466. doi:10.1037/1040-3590.15.4.456

33.

Hayton

J. C.

Allen

D. G.

Scarpello

(2004). Factor retention decisions in exploratory factor analysis: A tutorial on parallel analysis. Organizational Research Methods, 7, 191–205. doi:10.1177/1094428104263675

34.

Hillage

Pollard

(1998). Employability: Developing a framework for policy analysis. (Research report RR85). Brighton, England: Institute for Employment Studies. Retrieved from https://goo.gl/z68mlS

35.

Hinkin

T. R.

(1998). A brief tutorial on the development of measures for the use in survey questionnaires. Organizational Research Methods, 1, 104–121. doi:10.1177/109442819800100106

36.

Kahn

J. H.

(2006). Factor analysis in counseling psychology research, training, and practice. The Counseling Psychologist, 34, 684–718. doi:10.1177/0011000006286347

37.

Klein

(2000). The handbook of psychological testing (2nd ed.). London, England: Routledge.

38.

Knight

Yorke

(2004). Learning, curriculum and employability in higher education. London, England: Routledge Falmer.

39.

Koen

Klehe

Van Vianen

A. E. M.

(2013). Employability among the long-term unemployed: A futile quest or worth the effort? Journal of Vocational Behavior, 82, 37–48 doi:10.1016/j.jvb.2012.11.001

40.

Kornadt

A. E.

Voss

Rothermund

(2015). Hope for the best, prepare for the worst? Future self-views and preparation for age-related changes. Psychology and Aging, 30, 967–976. doi:10.1037/pag0000048

41.

Krishnamurthy

Sujan

(1999). Retrospection versus anticipation: The role of the ad under retrospective and anticipatory self-referencing. Journal of Consumer Research, 26, 55–69. doi:10.1086/209550

42.

Larson

L. M.

Toulouse

A. L.

Ngumba

W. E.

Fitzpatrick

L. A.

Heppner

P. P.

(1994). The development and validation of coping with career indecision. Journal of Career Assessment, 2, 91–110. doi:10.1177/106907279400200201

43.

Lord

R. G.

Diefendorff

J. M.

Schmidt

A. M.

Hall

R. J.

(2010). Self-regulation at work. Annual Review of Psychology, 61, 543–568. doi:10.1146/annurevpsych.093308. 100314

44.

Markus

Nurius

(1986). Possible selves. American Psychologist, 41, 954–969. doi:10.1037/0003-066X.41.9.954

45.

McArdle

Waters

Briscoe

J. P.

Hall

(2007). Employability during unemployment: Adaptability, career identity and human and social capital. Journal of Vocational Behavior, 71, 247–264. doi:10.1016/j.jvb.2007.06.003

46.

Nabi

G. R.

(2001). The relationship between HRM, social support and subjective career success among men and women. International Journal of Manpower, 22, 457–474. doi:10.1108/EUM0000000005850

47.

O’Connor

(2000). SPSS and SAS programs for determining the number of components using parallel analysis and Velicer’s MAP test. Behavior Research Methods, 32, 396–402. doi:10.3758/bf03200807

48.

Oyserman

Bybee

Terry

Hart-Johnson

(2004). Possible selves as roadmaps. Journal of Research in Personality, 38, 130–149. doi:10.1016/S0092-6566(03)00057-6

49.

Patil

V. H.

Singh

S. N.

Mishra

Donovan

D. T.

(2008). Efficient theory development and factor retention criteria: Abandon the “eigenvalue greater than one” criterion. Journal of Business Research, 61, 162–170. doi:10.1016/j.jbusres.2007.05.008

50.

Pham

L. B.

Taylor

S. E.

(1999). From thought to action: Effects of process- versus outcome-based mental simulation on performance. Personality and Social Psychology Bulletin, 25, 250–260. doi:10.1177/0146167299025002010

51.

Pool

L. D.

Qualter

(2013). Emotional self-efficacy, graduate employability, and career satisfaction: Testing the associations. Australian Journal of Psychology, 65, 214–223. doi:10.1111/ajpy.12023

52.

Pool

L. D.

Qualter

Sewell

P. J.

(2014). Exploring the factor structure of the CareerEDGE employability development profile. Education and Training, 56, 303–313. doi:10.1108/ET-01-2013-0009

53.

Pool

L. D.

Sewell

P. J.

(2007). The key to employability: Developing a practical model of graduate employability. Education &Training, 49, 277–289. doi:10.1108/00400910710754435

54.

Rodriguez

Reise

S. P.

Haviland

M. G.

(2016). Evaluating bifactor models: Calculating and interpreting statistical indices. Psychological Methods, 21, 137–150. doi:10.1037/met0000045

55.

Rothwell

Arnold

(2007). Self-perceived employability: Development and validation of a scale. Personnel Review, 36, 23–41. doi:10.1108/00483480710716704

56.

Rothwell

Herbert

Rothwell

(2008). Self-perceived employability: Construction and initial validation of a scale for university students. Journal of Vocational Behavior, 73, 1–12. doi:10.1016/j.jvb.2007.12.001

57.

Rothwell

Jewell

Hardie

(2009). Self-perceived employability: Investigating the responses of post-graduate students. Journal of Vocational Behavior, 75, 152–161. doi:10.1016/j.jvb.2009.05.002

58.

Schmitt

Stutts

D. M.

(1985). Factors defined by negatively keyed items: The result of careless respondents? Applied Psychological Measurement, 9, 367–373. doi:10.1177/014662168500900405

59.

Schriesheim

C. A.

Eisenbach

R. J.

(1995). An exploratory and confirmatory factor-analytic investigation of item wording effects on the obtained factor structures of survey questionnaire measures. Journal of Management, 21, 1177–1193. doi:10.1177/014920639502100609

60.

Silla

De Cuyper

Gracia

F. J.

Peiró

J. M.

De Witte

(2009). Job insecurity and well-being: Moderation by employability. Journal of Happiness Studies, 10, 739–751. doi:10.1007/ s10902-008-9119-0

61.

Tomlinson

(2012). Graduate employability: A review of conceptual and empirical themes. Higher Education Policy, 25, 407–431. doi:10.1057/hep.2011.26

62.

Vanhercke

De Cuyper

Peeters

De Witte

(2014). Defining perceived employability: A psychological approach. Personnel Review, 43, 592–605. doi:10.1016/j.ics.2005.02.061

63.

Van der Heijde

C. M.

(2014). Employability and self-regulation in contemporary careers. In Coetzee

(Ed.), Psycho-social career meta-capacities: Dynamics of contemporary career development (pp. 7–17). Dordrecht, the Netherlands: Springer.

64.

Van der Heijde

C. M.

van der Heijden

B. I.

(2005). The development and psychometric evaluation of a multi-dimensional measurement instrument of employability—and the impact of aging. International Congress Series, 1280, 142–147. doi:10.1016/j.ics.2005.02.061

65.

van Prooijen

J. W.

van der Kloot

W. A.

(2001). Confirmatory analysis of exploratively obtained factor structures. Education and Psychological Measurement, 61, 777–792. doi:10.1177/00131640121971518

66.

Vogt

D. S.

King

D. W.

King

L. A.

(2004). Focus groups in psychological assessment: Enhancing content validity by consulting members of the target population. Psychological Assessment, 16, 231–243. doi:10.1037/1040-3590.16.3.231

67.

Weng

McElroy

J. C.

(2012). Organizational career growth, affective occupational commitment and turnover intentions. Journal of Vocational Behavior, 80, 256–265. doi:10.1016/j.jvb.2012.01.014

68.

Weng

McElroy

J. C.

Morrow

P. C.

Liu

(2010). The relationship between career growth and organizational commitment. Journal of Vocational Behavior, 77, 391–400. doi:10.1016/j.jvb.2010.05.003

69.

Wittekind

Raeder

Grote

(2010). A longitudinal study of determinants of perceived employability. Journal of Organizational Behavior, 31, 566–586. doi:10.1002/job.646

70.

Wright

T. A.

Quick

J. C.

Hannah

S. T.

Hargrove

S. T.

(2017). Best practice recommendations for scale construction in organizational research: The development and initial validation of the Character Strength Inventory (CSI). Journal of Organizational Behavior, 38, 615–628. doi:10.1002/job.2180

Factor	Factor Loading
Item stem: “When I complete my studies…”	F1	F2	F3	F4	F5	F6
Perceived future network
…I will be able to draw on the network I have developed to succeed at my work	.95	−.02	.03	.01	.01	.03
…I will have built up a social network that will help me do well in my job	.92	−.02	.035	.05	.03	.02
…I will have developed a network of contacts who can help identify potential work opportunities	.80	.11	−.00	.02	−.06	−.04
…I will know how to network with people who can help me find work in my chosen career	.72	.03	.02	−.02	−.13	.03
Perceived expected experiences
…I will have had relevant work experience applying the knowledge acquired in my studies	−.07	.91	−.03	−.07	.00	.06
…future employers will be impressed with the relevant work experience I have accumulated	−.10	.87	.01	.10	.03	−.03
…future employers will be satisfied with the work experiences I have gained	.04	.66	.14	.10	−.11	.01
…I will be able to show future employers that I have the required practical skills and academic experience they require	.02	.53	−.01	.01	−.11	.33
Perceived future personal characteristics
…my experiences will show that I have developed resilience and do not give up easily	.10	.06	.87	−.03	−.06	−.03
…prospective employers will be able to see from what I have achieved that I am well motivated	−.08	−.02	.84	.00	.01	−.01
…prospective employers will be able to see that I have clear goals for myself	−.03	.02	.75	−.04	−.07	.01
…my record will show that I have a strong work ethic	−.06	−.04	.70	.08	.08	.08
Anticipated reputation of educational institution
…I will have an advantage as future employers will be more likely to recruit graduates from my institution than from other Institutions	−.07	.07	.01	.87	.12	−.07
…the reputation of my educational institution will be a significant asset to me in job seeking	−.01	−.02	.01	.81	.01	.05
…I will have a lot of work opportunities open to me because my teaching institution has strong partnerships with many potential employers	.01	.02	.02	.80	−.10	.02
…I will be in demand because graduates from my institution are well prepared for work roles that are in high demand	−.01	−.01	−.03	.65	−.21	.11
Perceived future labor market knowledge
…I will have developed a good understanding of the variety of work opportunities available to me	−.01	−.05	.04	.04	−.85	.06
…I will know the steps I need to take to do well in my chosen career	−.03	.11	.08	.05	−.77	−.07
…I will have developed the ability to find out about job opportunities in my chosen field	−.16	−.02	.06	−.06	−.70	.09
…I will be up-to-date with occupational trends in my chosen field	−.07	.14	−.03	.09	−.62	.03
Perceived future skills
…I will have gained the knowledge required to get the job I want	−.01	.08	−.02	.01	.05	.82
…I will have the relevant skills for the occupation I choose	−.01	−.00	−.01	−.09	−.07	.78
…future employers will see that I will have learned the right discipline specific/technical skills and knowledge that they want	.11	.07	.09	.10	−.08	.70
…I will have developed the reasoning and problem-solving skills that future employers often require	−.05	−.02	.09	.12	.01	.65