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A Personality-Based Measure of Employability Michael J. Boudreaux, Brandon T. Ferrell, Nathan A. Hundley, and Ryne A. Sherman

Hogan Assessment Systems, Tulsa, OK, USA

Abstract. Hogan et al. (2013) proposed a personality-basedmodel of employability that describes individual differences in (1) being rewarding to deal with, (2) being able to learn the job, and (3) being willing to work hard. In this study, we evaluated the model by selecting subscales from the Hogan Personality Inventory (HPI; Hogan & Hogan, 2007) that best predicted supervisor ratings of competencies related to these three constructs. The psychometric properties of those scales were examined in independent samples. Results indicated that the scales converged with similar scales from other instruments, covaried in meaningful ways with observer descriptions, and predicted supervisor ratings of job performance. The measure – which is 64% shorter than the full HPI – includes personality characteristics applicable to most jobs across multiple job families that can be used to identify successful candidates.

Keywords: employability, five-factor model, Hogan Personality Inventory, individual differences, workplace assessment

The success of any organization depends on the people who work in the organization. Businesses that make better hiring decisions are more productive, have less turnover, have more satisfied and engaged employees, and are more financially successful (Babakus et al., 2011; Kristof-Brown et al., 2005). Businesses that make poor hiring decisions suffer low pro- ductivity, high turnover, alienated employees, and, ultimately, failure (Jones, 2011). It is therefore crucial for businesses to hire the right people. But who are the right people and how do they contribute to an organization’s success? One way of answering this question is to consider what

employers say they want in new employees. In the first large-scale, US-based study on this topic, the Secretary’s Commission on Achieving Necessary Skills (SCANS) surveyed business owners, public employers, unions, workers, and supervisors about the performance demands of modern employment (U.S. Department of Labor, 1991). The SCANS survey identified five broad categories of critical competencies: resources – being able to identify and allocate resources; interpersonal skills – being able to work with others; information – being able to acquire and use information; systems – being able to understand complex interrelationships; and technology – being able to work with a variety of technologies. In a related survey, employers’ complaints about their employees concerned three basic problems – poor interpersonal, problem-solving, and personal management skills (Bureau of National Affairs, 1988). These complaints reflect the absence of key competencies critical for work success – interpersonal, cognitive, and intrapersonal (National Research Council [NRC], 2012).

The description of employability has also received considerable attention in several other countries, including Australia, Canada, the European Union, and the United Kingdom. For example, a survey of Australian organizations identified eight important skills for the Australian workforce (e.g., communication, learning, problem-solving, and self- management; Department of Education, Science, and Training [DEST], 2002). Working in the Netherlands, Van der Heijde and Van der Heijden (2006) developed a five-dimensional model and assessment of employability that includes occupational expertise, self-development, personal flexibility, collaboration, and balance. Although the number of dimensions across models differs, several themes common to each are consistent with the interper- sonal (e.g., communication and collaboration), cognitive (e.g., critical thinking and information literacy), and intra- personal (e.g., flexibility and initiative) domains of the NRC’s key competencies. While the research cited above has taken a skill-based

view of employability, recent attention has focused on individual difference characteristics of highly employable workers (e.g., Fugate et al., 2004; Hogan et al., 2013). Hogan et al. (2013) proposed a three-dimensional model that encompasses interpersonal, cognitive, and intraper- sonal aspects of personality. They argued that employ- ability consists of the knowledge, skills, and abilities needed to perform a job but is a more general and varie- gated concept that also includes dispositional tendencies. Specifically, they defined employability as a broadband, multifaceted construct that describes individual differences in the capacity to gain and maintain employment or find

Journal of Personnel Psychology (2022), 21(1), 11–22 https://doi.org/10.1027/1866-5888/a000283

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new employment if necessary. Their model comprises the following dimensions: Rewarding – being pleasant and easy to work with; Able – being capable and motivated to learn the job; and Willing – being hardworking and dependable. Hogan et al. (2013) noted that employability is an “attri- bution employers make about the probability that job candidates will make positive contributions to their orga- nization” (p. 11). These attributions are judgments based on job candidates’ reputations (Hogan, 1982, 1996). This is the basis of the Rewarding/Able/Willing (RAW) model of employability.

RAW Model of Employability

The RAW model of employability argues that supervisor evaluations of performance are based on the degree to which an employee is seen as Rewarding, Able, and Willing. While these dimensions are conceptualized as independently evaluated, the model makes no specifica- tions regarding the statistical associations between these dimensions. Moreover, the model is conceptually a for- mative (as opposed to reflective) model in that employees who behave in ways that are more Rewarding, Able, and Willing cause higher attributions of employability. Nothing about the RAW model presupposes that employees have latent “employability” that causes them to behave in ways that are more Rewarding, Able, andWilling. In this regard, the RAW model is akin to the conceptualization of so- cioeconomic status (SES), wherein SES is the sum of several quantifiable dimensions (e.g., income and edu- cational attainment). Our statistical treatment of this model is consistent with this conceptualization. We de- scribe each component dimension of the RAW model in turn.

Rewarding

The Rewarding component concerns the ability to get along and work well with others. Most jobs require individuals to work with others or as part of a team (Levy & Cannon, 2016). As a result, interpersonal or teamwork skills are an important part of most employability models. Research demonstrates the importance of assessing in- terpersonal skills. A content analysis of employment ads found that a large percentage refer to the need for good interpersonal skills (Hogan & Brinkmeyer, 1994). These skills were deemed essential for most jobs involving any kind of client, coworker, subordinate, or management interaction. Research also indicates that employers de- scribe self-presentation skills as the foundation of

employability (Brown &Hesketh, 2004), and recruiters, in a survey from the United Kingdom, report that employers often focus on candidates’ interpersonal skills more than their academic credentials (Taylor, 2006).

Hogan and Holland (2003) used the scales of the Hogan Personality Inventory (HPI; Hogan & Hogan, 2007) in a meta-analysis to examine the relationship between per- sonality dimensions and aligned job performance criteria. The HPI is a seven-factor measure of normal personality that can be mapped onto the five-factor model (FFM; e.g., Goldberg, 1992): Adjustment (FFM Emotional Stability), Ambition and Sociability (both FFM Extraversion), Inter- personal Sensitivity (FFM Agreeableness), Prudence (FFM Conscientiousness), and Inquisitive and Learning Ap- proach (both FFM Openness). Adjustment (ρ = .34), Prudence (ρ = .31), and Interpersonal Sensitivity (ρ = .23) were the best predictors of interpersonal skills. These results suggest that employees with good interpersonal skills will seem friendly, pleasant, and helpful. Those with poor interpersonal skills are likely to be seen as blunt, tactless, and distant or aloof.

Able

The Able component concerns the propensity to learn the essential functions of a job and develop new skills as that job changes over time. Formal education cannot foresee the skills needed in many contemporary jobs, let alone the jobs of the future (Grob-Zakhary & Hjarrand, 2017). As a result, many employees are expected to learn their job while on the job. Moreover, as organizations restructure, employees often change roles within a company. In these cases, the capacity to learn new skills quickly is critical. Self-driven knowledge and skill acquisition are also components in many models of employability. In Van der Heijde and Van der Heijden’s model (2006), it is “an- ticipation and optimization.” In Australia’s DEST model (2002), it is “learning.” In the NRC’s skills list (2012), it is the adaptability and self-development components of the “intrapersonal” competencies. In the SCANS survey, Able relates to “information” and “technology.” We concep- tualize the Able component as encompassing a basic re- ceptivity to intellectual experience rather than as a cognitive ability, per se.

Research finds that learning orientation is positively associated with performance across multiple levels of an organization. For example, learning orientation among insurance agents (Gong et al., 2009) and work groups in the banking and financial industry (Ning et al., 2017) positively predict employee job performance. Barrick and Mount (1991; see also Barrick et al., 2001) found in their meta-analysis on the FFM and job performance that

12 M. J. Boudreaux et al., A Personality-Based Measure of Employability

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training performance is associated with Extraversion, Openness, and Consciousness. Hogan and Holland (2003) found meta-analytic correlations of .27 (Ambition), .25 (Learning Approach), and .20 (Adjustment) with job per- formance criteria related to training and job knowledge acquisition. These results suggest that employees with good learning skills are likely to be seen by others as bright, curious, and motivated to learn. Those without good training skills are likely to be seen as simple, rigid, and tedious.

Willing

The Willing component concerns the tendency to take in- struction, work hard, and produce high-quality results in a timely fashion. Work ethic has historically been a critical competency for every job, and that has not changed in to- day’s workforce. Work ethic and its underlying dimensions are related to measures of task and contextual performance (Borman &Motowidlo, 1993). Miller et al. (2002) found that work ethic positively predicted job performance in a fi- nancial management organization. In laboratory studies, participants with high work ethic scores performed better, weremore likely to respond to negative feedback byworking harder, and were less likely to value unearned rewards than people with low work ethic scores (Greenberg, 1977). Outside of task performance, work ethic is positively

related to organizational citizenship behaviors and nega- tively related to counterproductive work behaviors (Meriac & Gorman, 2017). Work ethic also positively predicts job satisfaction (Miller et al., 2002), job involvement (Meriac et al., 2013), and organizational commitment (Miller et al., 2002; Saks et al., 1996). It negatively predicts turnover (Saks et al., 1996) and turnover intentions (Meriac et al., 2013). Miller et al. (2002) found moderately strong cor- relations between Conscientiousness and their seven di- mensions of work ethic. Hogan and Holland (2003) found meta-analytic correlations of .26 (Ambition), .22 (Adjust- ment), .20 (Prudence), and .15 (Learning Approach) with job performance criteria related to working with energy and exhibiting effort. These results suggest that employees with a good work ethic are likely to be seen by others as hardworking, productive, and dependable. Those without a good work ethic are likely to be seen as unreliable, lacking urgency, and underperforming.

The Present Study

The goal of this study was to test the model of employ- ability put forth by Hogan et al. (2013). They argued that to

be employable, a person should be Rewarding, Able, and Willing. The more a person possesses these qualities, the more likely it is that they will receive favorable perfor- mance evaluations. To evaluate this theory, we created composite variables that reflect these components by selecting subscales from the HPI that best predicted su- pervisor ratings of competencies relevant to these three domains. We then constructed a “super-composite” by combining scores on the Rewarding, Able, and Willing scales. In doing so, we created a shorter measure of the HPI that can be used to quantify a person’s employability. Similar past research using HPI subscales have created custom-purpose measures to predict qualities such as in- tegrity (Hogan & Hogan, 1989) and customer service orientation (Hogan et al., 1984). In the present study, we evaluated the psychometric properties of the RAW model scales in several independent samples of adult workers. Specifically, we examined descriptive information of the three scales and overall score, the degree to which the scales converge with similar scales from other instru- ments, how the scales relate to observer ratings of per- sonality, and the ability of the scales to predict supervisor ratings of job performance.

Method

Participants

Descriptive Sample To examine the descriptive statistics for the three RAW model scales, we obtained data from a global sample of 42,961 workers (Hogan Assessment Systems, 2019a). The sample includes representation of people from 179 countries or territories who took the HPI between January 2013 and August 2017. Table 1 presents demographic information for this sample broken down by age, gender, and job category. Everyone took the HPI for applicant screening purposes.

Validation Sample We obtained data from three samples to gather construct validation evidence for the RAW model: the Eugene- Springfield Community Sample (Goldberg, 2008) and samples with matched HPI and cognitive ability data using the Watson-Glaser II Critical Thinking Test (Watson & Glaser, 2010;N = 200) and Raven’s Advanced Progressive Matrices (APM-III; NCS Pearson, 2015a, 2015b; N = 332). The Eugene-Springfield Community Sample consisted of

196 participants, including 87 men and 109 women. Ages ranged from 21 to 72 years with amean of 45.5 (SD = 8.7). Up to four observers (e.g., significant others, spouses, friends, acquaintances, and coworkers) responded to questions

M. J. Boudreaux et al., A Personality-Based Measure of Employability 13

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about the personality styles and dispositions of the target individual. This sample of 538 respondents included 208 men and 330 women with a mean age of 41.5 (SD = 16.2). Most observers indicated knowing the target well or very well (N = 522), and most indicated they liked or very much liked the target (N = 520).

Development of Scales for the RAW Model We followed a four-step process to develop personality- based scales to predict employability. First, six researchers identified competencies from the Hogan Competency Library (Hogan Assessment Systems, 2009) whose defi- nitions aligned with the definitions of each component of the RAW model. At least five of the six researchers identified the following competencies: Leveraging People Skills (getting along well with others), Relationship Building (developing collaborative relationships), and Caring about People (being sensitive to others’ attitudes and feelings), which aligned with Rewarding; Self- Development (acquiring new knowledge and skills), Flexibility (changing direction as appropriate), and Pro- cessing Information (gathering, organizing, and analyzing information), which aligned with Able; and Working Hard (striving to complete tasks and assignments), Depend- ability (performing work in a reliable, consistent, and timely manner), and Quality Focus (striving to meet quality standards), which aligned with Willing. These nine competencies do not preclude other competencies that

may apply to specific jobs. Our goal was to identify competencies that were broadly applicable and concep- tually aligned with the RAW model dimensions.

Second, we verified that these competencies were important to jobs across multiple job families (specifi- cally, administrative and clerical, customer support, operations and trades, sales, service and support, and technical and specialist jobs) using job analysis (Hogan Assessment Systems, 2016). Across 100 job analytic studies, we identified 1,420 subject matter experts (SMEs) who were knowledgeable about the given job’s requirements. These SMEs included high-performing job incumbents or job supervisors. The number of job studies in which each competency was rated as impor- tant was as follows: Leveraging People Skills (77), Re- lationship Building (59), Caring About People (26), Self- Development (82), Flexibility (81), Processing Infor- mation (34), Working Hard (95), Dependability (94), and Quality Focus (60).

Third, we examined both (a) empirical relationships between the HPI’s subscales and supervisor ratings of these competencies using the Hogan archive and (b) theoretical relationships between the subscales and the RAWmodel. Finally, we built scales for each component of the RAW model using those subscales that showed strong empirical and theoretical relationships.

The Rewarding scale includes HICs from Adjustment (Even-Tempered – “I believe people should have a second chance”; Trusting – “Most people are basically honest”; Good Attachment – “In school, teachers liked me”) and Interpersonal Sensitivity (Easy to Live With – “I can get along with just about anybody”; Caring – “I like helping people who need a break”). The Able scale includes HICs from Inquisitive (Curiosity – “I ask other people a lot of questions”; Intellectual Games – “I enjoy solving riddles”; Generates Ideas – “I enjoy brainstorming”) and Learning Approach (Education – “Doing well in school was im- portant to me”; Good Memory – “I have a good memory”; Reading – “I am always reading”). The Willing scale in- cluded HICs from Ambition (Competitive – “I always play to win”; Accomplishment – “When I fail at something, I try even harder the next time”; Leadership – “I think I would enjoy positions of authority”) and Prudence (Mastery – “I strive for perfection in everything I do”; Impulse Control – “I would never buy the first car that I test drive”; Avoids Trouble – “I avoid trouble at all costs”).

Measures We analyzed relationships between scores on the three RAW model scales (described below) and scores on the following questionnaires: 16 Personality Factor (16PF) Questionnaire (Conn & Reike, 1994), NEO Personality Inventory – Revised (NEO PI-R; Costa & McCrae, 1992),

Table 1. Demographic information for the RAW model descriptive sample

Variable Sample N Sample %

Age

Under 30 15,558 36.2

30–39 12,879 30.0

40–49 6,237 14.5

50 and older 2,457 5.7

Not reported 5,830 13.6

Gender

Female 17,248 40.1

Male 22,164 51.6

Not reported 3,549 8.3

Job category

Administrative and clerical 7,554 17.6

Customer support 1,687 3.9

Operations and trades 6,298 14.7

Sales 10,278 23.9

Service and support 5,614 13.1

Technicians and specialists 11,521 26.8

Note. N = 42,961. Sample N = number of people in the descriptive sample; sample % = percentage of people in the descriptive sample.

14 M. J. Boudreaux et al., A Personality-Based Measure of Employability

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HEXACO Personality Inventory (HEXACO-PI; Lee & Ashton, 2004), Hogan Business Reasoning Inventory (HBRI; Hogan Assessment Systems, 2019b), Raven’s Advanced Progressive Matrices (APM-III; NCS Pearson, 2015a, 2015b), and Watson-Glaser II Critical Thinking Test (Watson & Glaser, 2010). Observers completed the Big-Five Mini-Markers (Saucier, 1994) and Big Five In- ventory (John & Srivastava, 1999) about the target individual.

Results

Descriptive Statistics Mean scores for the Rewarding, Able, and Willing com- ponents were calculated by averaging the relevant HIC scores within each component. They were then scaled from 0 to 100. The Overall score was calculated by av- eraging the three scaled scores. Mean scores were 80.90 (SD = 12.43), 72.55 (SD = 16.17), and 76.32 (SD = 10.58) for Rewarding, Able, and Willing, respectively; the mean Overall score was 76.59 (SD = 9.48). Scores ranged from 3 (Able) to 100 (for all three scales, including the Overall score). Cronbach’s α values were .63 (Rewarding), .73 (Able), and .58 (Willing). No skewness or kurtosis statistics fell below �1 or above +1 for any component score or the Overall score, indicating that the score distributions were adequately symmetric and neither abnormally peaked nor abnormally flat. Correlations between the three components were .19

(Rewarding and Able), .41 (Rewarding andWilling), and .29 (Able and Willing). The magnitude of these correlations suggests that each component describes different aspects of the employability construct and are consistent with ex- pectations about formativemeasures (e.g., Diamantopoulos & Siguaw, 2006). We assessed the stability of scores over time using in-

traclass correlation coefficients ([2,1]; Shrout & Fleiss, 1979) assuming absolute agreement. For these analyses, we used data from 6,435 individuals who completed the HPI twice within a 1-year period (M = 128.96 days, SD = 114.44 days). Test–retest coefficients were as follows: .61 (Rewarding), .70 (Able), .63 (Willing), and .65 (Overall score).

Construct Validity Tables 2, 3, 4, and 5 present correlations of the model’s components and Overall score with the NEO PI-R, HEXACO, 16PF, and measures of cognitive ability. The results highlight the considerate (NEO PI-R and

HEXACO-PI Agreeableness) and even-tempered (NEO PI- R Neuroticism and 16PF Emotional Stability) nature of the Rewarding component. People will likely view those with

high Rewarding scores as warm and considerate (NEO PI-R and 16PF Warmth; HEXACO-PI Gentleness), trusting of and concerned for others (NEO PI-R Trust and Altruism; HEXACO-PI Forgiveness), socially outgoing (HEXACO-PI Sociability), and calm and composed (NEO PI-R Angry Hostility, HEXACO-PI Patience, 16PF Tension). The Able component correlatedmost strongly with NEO

PI-R and HEXACO-PI Openness to Experience and 16PF Openness to Change, highlighting this component’s re- lationship to the desire and ability to learn. People will likely view those with high Able scores as bright (16PF Reasoning) and curious and eager to explore new ideas and ways of doing things (NEO PI-R Ideas and HEXACO- PI Inquisitiveness and Creativity). The Able component also has a consistent positive relationship with measures of cognitive ability (HBRI, APM-III, and Watson-Glaser II overall scores). The conforming and dependable nature of the Willing

component is highlighted by its correlations with NEO PI- R and HEXACO-PI Conscientiousness. People will likely view those with high Willing scores as hardworking (NEO PI-R Achievement Striving and HEXACO-PI Diligence) and self-disciplined (NEO PI-R Self-Discipline and 16PF Perfectionism). People with high Willing scores will also seem organized (HEXACO-PI Organization), rule-abiding (16PF Rule Consciousness), and confident (NEO PI-R Competence).

Correlations With Observer Descriptions of Personality Table 6 presents selected correlations for each component of the RAW model and averaged observer ratings of personality (see Tables E1 and E2 in the Electronic Sup- plementary Material [ESM 1] for the full correlation ma- trices). These ratings derive from Goldberg’s (2008) longitudinal community research. The results reflect the kind and composed nature of the Rewarding component, the bright and clever nature of the Able component, and the hardworking and orderly nature of the Willing com- ponent. For example, people with high Rewarding scores were described as calm, cooperative, friendly, and relaxed whereas those with low scores were described as con- frontational, rude, and temperamental. People with high Able scores were described as ingenious and intellectual whereas those with low scores were seen as uncreative and unintellectual. Finally, people with high Willing scores were described as organized, reliable, and persistent, and those with low scores were described as disorganized, careless, and lazy.

Criterion-Related Validity We used procedures outlined by Hunter and Schmidt (2004) to evaluate meta-analytic correlations between

M. J. Boudreaux et al., A Personality-Based Measure of Employability 15

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Table 2. Correlations of the RAW model with the revised NEO personality inventory

NEO PI-R

RAW model

Rewarding Able Willing Overall score

Domain scales

Neuroticism �.51** �.19* �.48** �.59**

Extraversion .28** .15 .36** .40**

Openness to Experience �.08 .47** �.14 .18*

Agreeableness .55** �.07 .03 .27**

Conscientiousness .21* .14 .66** .47**

Facet scales

Neuroticism

Anxiety �.45** �.13 �.29** �.43**

Angry Hostility �.61** �.17* �.24** �.51**

Depression �.38** �.13 �.41** �.45**

Self-consciousness �.27** �.23** �.39** �.45**

Impulsivity �.27** �.08 �.41** �.37**

Vulnerability �.36** �.19* �.52** �.52**

Extraversion

Warmth .43** .01 .11 .30**

Gregariousness .20* .01 .20* .21*

Assertiveness .04 .27** .44** .37**

Activity .04 .19* .29** .26**

Excitement-seeking �.04 �.03 .06 .00

Positive emotions .37** .13 .21* .36**

Openness to Experience

Fantasy �.10 .22** �.22** �.02

Esthetics �.04 .34** �.13 .12

Feelings �.02 .20* �.01 .13

Actions .05 .32** .00 .22*

Ideas �.11 .59** .04 .30**

Values �.07 .29** �.21** .04

Agreeableness

Trust .61** .07 .23** .47**

Straightforwardness .32** �.22** .04 .05

Altruism .53** .01 .18* .36**

Compliance .51** .01 �.01 .27**

Modesty �.04 �.18* �.15 �.19*

Tender-mindedness .21* .04 �.16 .09

Conscientiousness

Competence .27** .30** .54** .54**

Order .08 �.07 .41** .17*

Dutifulness .13 �.02 .45** .25**

Achievement Striving .10 .22** .57** .43**

Self-discipline .19* .08 .63** .42**

Deliberation .20* .15 .39** .36**

Note. N ranges from 137 to 149.**p < .01, *p < .05; two-tailed.

16 M. J. Boudreaux et al., A Personality-Based Measure of Employability

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the Overall score of the RAWmodel and supervisor ratings of performance. We used zero-order product-moment correlations (r) as effect sizes for all studies. Moreover, as recommended byHunter and Schmidt (2004), we used a

randomeffectsmodel, allowing the population parameter to vary from study to study. This also allows for confidence and credibility intervals to be estimated. If the lower end of a 95% CI does not include zero, there is a less than 5%

Table 3. Correlations of the RAW model with the HEXACO personality inventory – revised

HEXACO PI-R

RAW model

Rewarding Able Willing Overall score

Domain scales

Honesty-humility .19* �.11 �.01 .04

Emotional Stability �.15 �.16* �.16* �.21*

Extraversion .20* .26** .27** .35**

Agreeableness .52** .09 �.01 .35**

Conscientiousness .08 .02 .53** .29**

Openness to Experience �.11 .59** �.06 .27**

Facet scales

Honesty-humility

Sincerity .06 �.07 .00 �.02

Fairness .26** .00 .25** .25**

Greed avoidance .08 .03 �.14 .01

Modesty .19* �.28** �.10 �.09

Emotional Stability

Fearfulness �.06 �.25** �.21** �.23**

Anxiety �.37** �.18* �.12 �.36**

Dependence �.08 .00 �.10 �.09

Sentimentality .08 �.01 �.01 .08

Extraversion

Social self-esteem �.12 .05 �.04 �.09

Social boldness .05 .38** .38** .41**

Sociability .26** .03 .14 .22**

Liveliness .36** .26** .26** .42**

Agreeableness

Forgiveness .38** .07 .02 .27**

Gentleness .44** .04 �.08 .27**

Flexibility .36** .00 �.05 .16

Patience .47** .15 .06 .38**

Conscientiousness

Organization .08 �.18* .39** .11

Diligence .07 .20* .54** .39**

Perfectionism �.15 .00 .19* .01

Prudence .24** .13 .42** .40**

Openness to Experience

Aesthetic appreciation .00 .39** �.13 .18*

Inquisitiveness �.01 .57** .07 .36**

Creativity �.08 .51** .11 .30**

Unconventionality �.29** .41** �.25** �.01

Note. N ranges from 137 to 167.**p < .01, *p < .05; two-tailed.

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chance that the results are simply due to chance. If the lower end of an 80% credibility interval does not include zero, more than 90% of the results across studies will be in the expected direction. We corrected effect sizes for unreli- ability using the .52 reliability coefficient proposed by Viswesvaran et al. (1996).

The upper portion of Table 7 presents meta-analytic correlations between the overall score and supervisory ratings of job performance, separately for six job families. The uncorrected sample-weighted correlations ranged from .10 (Sales) to .19 (Customer Support). The lower bounds of the 80% credibility intervals, which do not contain zero, suggest that these results remain consistent across the jobs within each of the job families (except Sales). The 95% CIs for all job families (except Sales) do not contain zero, indicating that those results are statis- tically significant. It should be noted that the Sales job family had the least amount of data in terms of number of studies and people. When the effect sizes (i.e., Pearson correlation coefficients) were corrected for unreliability, the correlations between the scales and job performance ratings ranged from .13 (Sales) to .27 (Customer Support). We examined moderating effects for both age and gender on overall RAW scores. The effects were small and did not reach statistical significance. Table E3 in ESM 1 provides meta-analytic correlations for each component of the RAW model.

For comparison purposes, we present meta-analytic correlations based on an overall HPI score in the lower portion of Table 7. The uncorrected sample-weighted correlations ranged from .04 (Technicians and Special- ists) to .18 (Customer Support). Whereas the results for the RAW model were significant for all job families (except Sales), the 95%CI indicates that four of the six job families are statistically significant for the overall HPI score. When the Pearson correlation coefficients were corrected for unreliability, the correlations between the overall HPI score and job performance ratings ranged from .04 (Technicians and Specialists) to .25 (Customer Support). Thus, across every job family, the meta-analytic correla- tions based on the RAW model were stronger than those for the overall HPI score. (We note, however, that the HPI was not designed to generate an overall mean score andwe do not encourage this practice; here, we used an overall score simply as a means to compare results for the RAW model.)

Discussion

The RAW model of employability (Hogan et al., 2013) describes three characteristics of employable people: be- ing tactful and calm under pressure (Rewarding), being able to quickly learn new skills (Able), and being de- pendable (Willing). People who have these characteristics interact well with customers and coworkers, get up to speed on the job quickly, and work hard, producing high quality products. We empirically operationalized each characteristic using scales from a common workplace

Table 4. Correlations of the RAW model with the 16 Personality Factor Questionnaire

16PF

RAW model

Rewarding Able Willing Overall score

Warmth .20* �.08 .08 .11

Reasoning �.20* .39** .02 .19*

Emotional Stability .41** .11 .36** .45**

Dominance �.18* .08 .30** .10

Liveliness .08 .05 �.07 .02

Rule-consciousness .28** �.24** .32** .14

Social-boldness .16 .15 .28** .24**

Sensitivity �.11 .01 �.28** �.16

Vigilance �.35** �.21** �.21** �.42**

Abstractedness �.24** .33** �.29** �.06

Privateness �.06 .07 .07 .02

Apprehension �.26** �.18* �.29** �.36**

Openness to change �.14 .43** �.07 .18*

Self-reliance �.23** �.08 �.25** �.26**

Perfectionism .05 �.16 .32** .09

Tension �.50** �.07 �.16 �.39**

Note. N ranges from 132 to 156.**p < .01, *p < .05; two-tailed.

Table 5. Correlations of the RAW model with measures of cognitive ability

Measure

RAW model

Rewarding Able Willing Overall score

HBRIa

Tactical .12** .06** .06** .11**

Strategic .13** .09** .08** .14**

Overall score .15** .09** .09** .15**

Raven’sb

Raw overall �.06 .13* �.08 .03

Watson-Glaser IIc

Draw conclusions .10 .17* �.06 .11

Recognize assumptions �.02 .08 �.14 �.02

Evaluate arguments .11 .15* .06 .15*

Overall score .13** .24** .02 .20**

Note. HBRI = Hogan Business Reasoning Inventory; Raven’s = Raven’s Advanced Progressive Matrices (AMP-III); Watson-Glaser II = Watson-Glaser II Critical Thinking Test. aN = 2,926. bN = 332. cN = 200. **p < .01, *p < .05; two-tailed.

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personality assessment, the HPI. These RAW scales (a) showed relationships with theoretically related constructs and with observer ratings and (b) predicted job perfor- mance across multiple job families and industries. Overall, these results support the theoretical propositions of the RAW model – specifically, supervisor attributions of per- formance are grounded in the degree to which the

employee is rewarding to work with, able to do the job, and willing to work hard. Our measurement model deserves some comment. We

conceptualize employability as a multidimensional con- struct that is caused by or given meaning because of its component dimensions. In this respect, our measure of employability can be considered an aggregate measure

Table 7. Criterion validity results for the RAW model and HPI overall score by job family

Job family K N robs SDr ρ SDρ %VE 80% CV 95% CI

RAW model

Administrative and clerical 16 1,526 .17 0.10 .24 0.14 96 .15 .12

Customer support 9 716 .19 0.16 .27 0.22 48 .07 .09

Operations and trades 38 2,425 .12 0.12 .17 0.17 100 .12 .08

Sales 7 272 .10 0.21 .13 0.29 55 �.06 �.06

Service and support 20 1,709 .13 0.13 .18 0.19 62 .03 .07

Technicians and specialists 10 1,125 .11 0.08 .15 0.11 100 .11 .05

HPI overall score

Administrative and clerical 16 1,526 .14 0.12 .19 0.17 67 .05 .07

Customer support 9 716 .18 0.10 .25 0.13 100 .18 .12

Operations and trades 38 2,425 .09 0.13 .12 0.18 85 .03 .04

Sales 7 272 .08 0.21 .08 0.21 59 �.06 �.08

Service and support 20 1,709 .08 0.14 .08 0.14 56 �.03 .02

Technicians and specialists 10 1,125 .04 0.10 .04 0.10 90 .00 �.02

Note. Results corrected for criterion unreliability. The seven sales jobs do not include sales managers or higher-level sales positions. The sales meta-analysis resulted in a negative expected variance, so the adjusted 80% credibility interval lower-bound is presented (see Steel & Kammeyer-Mueller, 2008). HPI = Hogan Personality Inventory. k = number of correlations;N = sample size; robs = sample-weighted observedmean correlation; SDr = sample weighted SD; ρ = sample weighted correlation corrected for unreliability in the criteria; SDρ = SD of the corrected population correlation; %VE = percent of variance accounted for by sampling error and artifact corrections; 80% CV = lower 10% boundary of 80% credibility interval; 95% CI = lower 2.5 boundary of 95% CI.

Table 6. Example correlations of the RAW model with observer descriptions of personality

RAW Observer ratings

Rewarding Relaxed (.33**); remains calm in tense situations (.33**); emotionally stable, not easily upset (.31**); considerate and kind to almost everyone (.26**); cooperative (.25**); relaxed, handles stress well (.23**); helpful and unselfish with others (.22*); has a forgiving nature (.21*); kind (.20*); sympathetic (.20*)

Finds fault with others (�.32**); temperamental (�.31**); depressed, blue (�.31**); unsympathetic (�.30**); can be tense (�.30**); can be moody (�.29**); starts quarrels with others (�.25**); gets nervous easily (�.24**); rude (�.23**); worries a lot (�.23**)

Able Intellectual (.42**); likes to reflect, play with ideas (.40**); ingenious, a deep thinker (.35**); Original, comes up with new ideas (.34**); has an active imagination (.30**); Philosophical (.29**); Imaginative (.28**); Inventive (.26); Sophisticated in art, music, literature (.25**); creative (.24**); curious about many things (.23**)

Unintellectual (�.34**); Prefers routine work (�.30**); Uncreative (�.25**); bashful (�.19*); Can be tense (�.17*); temperamental (�.16*)

Willing Does things efficiently (.33**); makes plans and follows through (.32**); perseveres until the task is finished (.32**); efficient (.28**); systematic (.26**); does a thorough job (.25**); organized (.25**); a reliable worker (.24**); energetic (.24**); practical (.19*)

Easily distracted (�.37**); inefficient (�.33**); tends to be disorganized (�.29**); sloppy (�.27**); disorganized (�.26**); tends to be lazy (�.25**); withdrawn (�.23**); depressed, blue (�.22**); gets nervous easily (�.21**); can be somewhat careless (�.21**)

Overall score Relaxed (.36**); remains calm in tense situations (.35**); emotionally stable, not easily upset (.29**); makes plans and follows through (.24**); perseveres until the task is finished (.24**); relaxed, handles stress well (.22*); inventive (.20*); considerate and kind to almost everyone (.20*); energetic (.19*); original, comes up with new ideas (.19*)

Temperamental (�.33); can be tense (�.31) depressed, blue (�.30); gets nervous easily (�.30); moody (�.28); easily distracted (�.25); withdrawn (�.20); tends to be lazy (�.19); fretful (�.19); uncreative (�.19)

Note. N ranges from 126 to 157. **p < .01, *p < .05; two-tailed.

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consisting of three dimensions. Although each dimension has independent value, together they give rise to em- ployability. Thus, the direction of relations is formative rather than reflective (Bollen & Lennox, 1991). In other words, one’s ability to gain and maintain employment is derived from their ability to be seen as Rewarding, Able, and Willing. Although some writers are critical of for- mative measurement (e.g., Edwards, 2011), it is gaining wide appeal in business research, as evidenced by special issues on the topic (e.g., Diamantopoulos, 2008). More- over, our view is consistent with other dispositional models of employability. For example, Fugate et al. (2004) assert that “it is the synergistic combination of [person-centered variables] that give rise and value to employability” (p. 8). Their model consists of three variables: career identity, personal adaptability, and social and human capital. Conceptually, they point out, for example, that it makes more sense to say that social and human capital (e.g., inter- personal skills) cause employability than the converse – that interpersonal skills are caused by employability.

One of the motivations for the RAW model was for “research to include what it is that employers actually want in new hires” (Hogan et al., 2013, p. 13). The use of job analytic data from diverse jobs and the broad predictive ability of the model suggest two things. First, certain characteristics are widely applicable across jobs and in- dustries, consistent with the personality and organizational literature (Barrick & Mount, 1991; Hogan & Holland, 2003). Second, it is possible to combine these charac- teristics into a reliable and valid assessment instrument that can be used by employers, recruiters, or human re- source administrators to identify successful candidates.

While this research began as a theoretical investigation, it has also yielded a measure of employability that can be used in a variety of hiring contexts, particularly in lower- level selection involving large numbers of job candidates or positions where employees may need to shift roles or take onmultiple roles.While employability will likely relate to job performance among professionals or managers – everyone must manage relationships, keep up-to-date with relevant skills, andwork diligently – those jobsmay require additional training (e.g., graduate medical training) or duties (e.g., strategic thinking and decision making) that likely fall outside the RAW model. As such, different selection tools may be more appropriate for those cases.

Scales for the RAW model consist of 75 items – a 64% reduction from the full HPI – measuring three critical competencies for workplace success. Scores for each component are percentiles, ranging from 0% to 100%, and reflect the candidate’s standing relative to a normative sample. It is important to note, however, that higher scores on any component do not indicate that the individual will demonstrate the behaviors associated with that component

all the time. Rather, higher scores indicate that the can- didate has a greater likelihood of displaying those behaviors in any given situation and should display these behaviors more often on average across many situations and over time. Although higher scores increase a person’s chances of gaining employment, employability does not guarantee actual employment.

Although the use of the RAWmodel scales as a selection tool should depend on the results of a job analysis, there is criterion validity evidence for five job families (adminis- trative and clerical jobs, customer support jobs, operations and trades jobs, service and support jobs, and technical and specialist jobs). The meta-analytic correlation was not statistically significant for the sales jobs, but this may be due to the small sample size and a small number of jobs in the sales group. These results provide evidence that some characteristics are helpful for performance in widely dif- ferent jobs. Furthermore, the RAWmodel scales may have other value in the workplace outside of selection decisions, including identifying employees better able to take on different roles or more likely to benefit from reskilling. Each RAW model scale relates to important workplace outcomes, and scores on these scales could be used to help target development opportunities.

Electronic Supplementary Material

The electronic supplementary material is available with the online version of the article at https://doi.org/ 10.1027/1866-5888/a000283. ESM 1. Correlations of the RAW model with other mea- sures and criterion validity results for the RAW model components.

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History Received July 21, 2020 Revision received April 23, 2021 Accepted April 28, 2021 Published online September 14, 2021

ORCID Michael J. Boudreaux  https://orcid.org/0000-0002-8179-8047

Michael J. Boudreaux Hogan Assessment Systems 11 S. Greenwood Ave. Tulsa, OK 74120 USA [email protected]

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