Hiring for Retention and (1)

8/6/2019 Hiring for Retention and (1)

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184 H UMAN R ESOURCE M ANAGEMENT , M ARCH A PRIL 2009

Human Resource Management DOI: 10.1002/hrm

related to employee turnover ( R=.33) withinsix months after hire. What is virtually un-mentioned in the literature is whether pre-hire predictors of turnover would also beeffective predictors of work performance.

By examining the validity of pre-hire pre-

dictors of voluntary turnover, this study buildson prior research, particularly Barrick andZimmerman (2005). It differs, however, inthat it also examines whether predictors thatare theoretically relevant to turnover alsowould relate to job performance as measuredby supervisory ratings. Since job performanceand voluntary turnover are two of the most

important criteria affected by em-ployee behavior, they warrant si-multaneous study in determiningjoint causes of both outcomes.This study also investigates abroader set of predictors, includingrelevant personality traits and anadditional biodata construct to testwhether individuals who have ahistory of job hopping will bemore likely to leave their currentorganization (Ghiselli, 1974). Italso examines whether these rela-tionships exist long after the ap-plicant is hired (up to two years),

not just shortly after hire (up to sixmonths). Thus, the purpose of thisstudy is to systematically explorethe ability of each pre-hire variableto predict both voluntary turnoverand performance over an extendedperiod of time.

Theoretical Foundationfor Pre-hire Predictors of VoluntaryTurnover and Job Performance

An overarching theme common to most turn-over theories is that some employees havegreater feelings of attachment to their organi-zations than others do. Perhaps the first timethis idea was codified in the management lit-erature was with March and Simons (1958)discussion of factors influencing employeesdesire to leave their organizations. Laterresearchers (Lee, Mitchell, Sablynski, Burton,& Holtom, 2004; Mitchell, Holtom, Lee,

Sablynski, & Erez, 2001) have examined howemployee embeddedness can influence theirdesire to leave, whether through the employ-ees perceptions of how well they fit withtheir jobs and organizations or the number of links the employees have with other individu-

als within their work environments. Otherresearchers (Maertz & Campion, 2004; Maertz& Griffeth, 2004) have focused on examiningmotivational forces that influence employeesdesire to remain in their jobs. These forcesinclude organization-related factors, such asemployees enjoying the jobs they hold, likingthe organizations for which they work, orwanting to continue working with coworkerswith whom they have close relationships.These forces also include individual-relatedfactors, such as feelings of obligation to anemployer who provides them with a job, aninnate sense of responsibility not to quit theirjob, or even an escalation of commitment totheir decision to work for the organizationsthat employ them. Although some factorsthat influence the desire to leave (or stay) canonly be determined once individuals starttheir job and experience their work environ-ment, other factors may be ascertained evenbefore they are hired. Finally, some of thesesame researchers have suggested that the at-

tributes that influence employees attachmentto their organizations may also influencetheir motivation to perform well in their jobs(Lee et al., 2004; March & Simon, 1958).Therefore, the predictors used in this studywere selected based on their theoretical rela-tionship to factors that would influence em-ployees desire to stay, as well as affect theirlevel of job performance.

Effects of Biodata on Employees

Turnover Decisions and JobPerformance

Recent research using biodata has attemptedto create a theoretical basis for the items used(Dean, Russell, & Muchinsky, 1999). Barrickand Zimmerman (2005) examined three the-oretically relevant biodata items (number of friends and family working at the firm,referral by an employee, and tenure in priorjob) and found that the items predicted

The vast majority of

selection research

has focused on

prehire predictors

of job performance.

In contrast, very

little research. . . .

has investigated

whether employers

can prevent turnover

before employees

start their jobs.


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Hiring for Retention and Performance 185


voluntary, avoidable turnover ( R=.31). Thetheoretical basis of these hypothesized effectsis tied to the job embeddedness literature(Mitchell et al., 2001), realistic job previewliterature (Breaugh & Dossett, 1989; Premack& Wanous, 1985; Rynes, 1991), and the find-

ing that past behavior is the best predictor of future behavior (Owens & Schoenfeldt, 1979;Wernimont & Campbell, 1968). Supplement-ing the three items that Barrick and Zimmer-man used, we add a fourth biodata item: theinfluence of frequent job changes. In thisstudy, two measures composed of two bio-data items each are used to reflect pre-hireembeddedness in the organization (employeereferral; number of friends and family) andhabitual commitment (tenure in prior job;number of jobs in last five years).

Biodata items assessing the impact of whether current employees referred the appli-cants and whether they have friends or rela-tives working at the organization have theirtheoretical basis tied to the job embeddednessliterature (Mitchell et al., 2001), which suggeststhat the greater the number of links to the or-ganization, the less likely employees are toquit. In addition, if applicants have contactswithin the organization, they are more likelyto understand the advantages and disadvan-

tages of the position for which they are apply-ing. Hence, they are better able to engage inself-selection (Rynes, 1991; Wanous, 1980),because their perceptions of fit with the joband the organization (Hom & Griffeth, 1995;Premack & Wanous, 1985) are better informed.The ability to better assess fit, in addition tomore embedded social links, will likely increasethe probability that employees will remainwith the organization. Thus, these two biodataitems are combined into one measure to reflect

pre-hire embeddedness.The other two biodata items, tenure inlast job (Barrick & Zimmerman, 2005) andnumber of jobs over the past five years (Price& Mueller, 1986), reflect commitment toprior employers. These two items were com-bined into one biodata measure to reflecthabitual commitment. Since past behavior isthe best predictor of future behavior (Owens& Schoenfeldt, 1979; Wernimont & Camp-bell, 1968), individuals who have a habit of

seeking new jobs, as represented by how longthey stayed in the previous job and the num-ber of jobs held over the previous five years,could be expected to do so again. Accordingto the unfolding model of turnover (Holtom,Mitchell, Lee, & Inderrieden, 2005; Lee &

Mitchell, 1994), some individuals are likelyto be impulsive quitters who terminate theiremployment spontaneously. Similarly, Ghis-elli (1974) noted that some individuals aremore likely to develop a habit of quitting jobafter job, which he termed hobo syndrome.Empirical research by Judge and Watanabe(1995) has supported this contention.

The four biodata items used inthis study also are likely to corre-late with job performance. In arecent study on job embedded-ness, Lee et al. (2004) theorizedthat employees with a greaternumber of links to other cowork-ers would be more likely to bemotivated to perform than em-ployees with fewer links. Further-more, they suggested that themore individuals are socially en-meshed in an organization, themore likely they are to engage incontextual performance. Embed-

ded employees are likely to havelarger social networks from whichto obtain assistance in performingtheir jobs effectively (Settoon, Ben-nett, & Liden, 1996). Lee et al.found that on-the-job embedded-ness was a significant predictor of both in-role and extra-role job per-formance. Positive performancenot only helps avoid termination,but also helps preserve the reputa-

tion of the coworkers closest to the employee,specifically friends and family employed atthe organization. Therefore, the more friendsand family members an employee has work-ing at an organization, the more likely it isthat the employee will perform well. In addi-tion, there is evidence that current employeesare likely to refer more capable applicants(Breaugh & Starke, 2000; Rynes, 1991).

An applicants tenure in prior jobs andthe number of jobs recently held may be

Since past behavior

is the best predictor

of future behavior,

individuals who

have a habit of

seeking new jobs, as

represented by how

long they stayed

in the previous job

and the number of

jobs held over the

previous five years,

could be expected

to do so again.


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influenced by several factors, including pre-vious performance. An applicant who leftprevious jobs because of poor performancewill likely exhibit a similar level of perfor-mance in the new position. Because poorperformers tend to be terminated before

good performers, poor performers will haveless tenure in their previous job. If poor per-formers are not fired, they are more likely todecide to leave their organizations (Griffeth,Hom, & Gaertner, 2000) because of decreasedjob satisfaction (Judge, Thoresen, Bono, &Patton, 2001). In addition, a meta-analysisby Meyer, Stanley, Herscovitch, and Topol-nytsky (2002) showed a positive relationshipbetween affective organizational commit-ment and supervisor-rated job performance

( =.17), as well as between affec-tive organizational commitmentand contextual performance( =.32). Since past job-hoppingbehaviors also indicate a histori-cal lack of commitment to em-ployers, employees who have atrack record of job hopping arealso more likely to have lower jobperformance if they are uncom-mitted to their current employer.There are two hypotheses for

these two biodata measures in reference toboth turnover and performance:

H1: Employees who have greater pre-hire em-beddedness in the organization will be (a) morelikely to remain with their current employers and (b) better performers than those with lower em-beddedness.

H2: Employees who had greater habitual com-mitment to their former employers will be (a)more likely to stay with their current employersand (b) better performers than those with lesscommitment.

Effects of Pre-hire Attitudes onEmployees Turnover Decisionsand Job Performance

Employee pre-hire attitudes were found todifferentially predict turnover in the Barrickand Zimmerman (2005) study. Specifically,

they found that personal confidence scales(called disguised-purpose scales) added incre-mental validity to the prediction of voluntaryturnover beyond the biodata predictors, whileemployment motivation scales (termed clear-purpose scales) did not. This study will exam-

ine whether this distinction also matters inthis setting for turnover and extends to pre-dictions of job performance.

Personal Condence Scales

Barrick and Zimmerman (2005) found thattwo measures of confidence, confidence withself and confidence with decisions, predictedvoluntary, avoidable turnover ( r =.17 and.22, respectively), because employees withhigher confidence will be more persistent instriving to adapt to novel job demands or thework setting and will be less likely to with-draw from work because of anxiety over lowperformance or ineffective adjustment (Lee,Ashford, Walsh, & Mowday, 1992). Higherconfidence also should be related to higherjob performance, as employees with greaterconfidence are likely to be more involved intheir jobs, exert greater effort, and persist at atask longer. Kanfer and Ackerman (2005)theorized that self-confidence affects job per-

formance through self-regulatory behaviorsbecause individuals with higher self-confi-dence are more likely to persist in perfor-mance-related goals, even in the face of obstacles. Furthermore, self-confidence canaffect employees motivation in such a waythat employees low in self-confidence per-ceive the effort-performance relationship tobe flat even if objective information indicatesthe contrary (Kanfer & Ackerman, 2005). Inaddition, previous empirical research has de-

termined that job performance is positivelyaffected by both self-confidence (Linnehan,1998) and confidence with decisions (or deci-siveness) (Kipnis & Glickman, 1962; Pynes &Bernardin, 1992). Finally, both self-efficacyand generalized self-efficacy have been shownto moderately correlate with job performance(r =.38 for self-efficacy, Stajkovic & Luthans,1998; =.23 for generalized self-efficacy, Judge& Bono, 2001). Although confidence is abroader, more distal construct than

An applicants

tenure in prior jobs

and the number of

jobs recently held

may be influenced

by several factors.


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self-efficacy, both reflect the impact of onesperceived competence in a setting.

H3: Employees with higher condence will be(a) more likely to stay with the organizationand (b) better performers than those with lower

condence.

Employment Motivation Scales

Barrick and Zimmerman (2005) showed thatapplicants differ in their attraction to the jobor organization even before they are hired,and these differences were predictive of vol-untary, avoidable turnover. Specifically, theyfound that two measures of the applicantsmotivation to obtain the job, the applicantsdesire for the job and pre-hire intent to quit,were related to turnover ( R=.20). These resultsreveal that one of the best predictors of vol-untary turnover for current employees, thatis, intent to quit (Griffeth et al., 2000), mayalso predict turnover when assessed beforethe employee is hired.

Employment motivation is also expectedto relate to job performance. Breaugh andMann (1984) posited that active job seekerstended to be better performers than passivejob seekers because they were more moti-

vated to obtain a job with that particularemployer. Also, new employees who have astrong desire to work for an organizationlikely require less time to be socialized intoits culture (Van Maanen & Schein, 1979).Employees who are more effectively social-ized into an organization should achievehigher performance (Wanous & Colella,1989). In addition, according to the theoriesof social exchange (Van Dyne & Ang, 1998),norms of reciprocity (Gouldner, 1960), and

perceived organizational support (Rhoades &Eisenberger, 2002), applicants who are moreattracted to the job are more likely to repaythe organization through greater effort (Leeet al., 2004).

Applicants who intend to quit or wholack desire for their job will have lower com-mitment to the job or organization, whichmay lead to lower job performance (Meyeret al., 2002). A meta-analysis by Zimmermanand Darnold (2009) indicated a negative

relationship between intent to quit and jobperformance ( = .14). For these reasons, theemployment motivation scales (desire forthe job and intent to stay) are likely to berelated to turnover, even when assessed be-fore hire, as well as to overall job perfor-

mance.

H4: Employees who are more motivated to ob-tain the job will be (a) more likely to stay and (b) better performers than those who are not asmotivated.

Effects of Personality Traits onEmployees Turnover Decisionsand Job Performance

Theoretically, both conscientiousness andemotional stability should be negatively re-lated to voluntary turnover (Bar-rick & Mount, 1996). Maertz andcolleagues (Maertz & Campion,2004; Maertz & Griffeth, 2004)suggested that conscientiousness,partially defined as being depend-able and reliable (Barrick &Mount, 1991), is a factor in thecontractual and moral/ethicalmotivational forces that affect

employees turnover decisions.Specifically, Maertz and Griffethstated that individuals who con-sider leaving their employers mayreflect, Do I owe any obligationto the organization that I wouldbreak by leaving? Therefore, in acontractual situation, such as ac-cepting a job offer, conscientiousemployees are more likely to perceive thatobligations exist to their employers and are

more likely to adhere to these obligations bystaying at the organization. These perceivedobligations have been termed normative com-mitment (Meyer & Allen, 1991) and havebeen found to negatively relate to intent toquit (Shore, Tetrick, Shore, & Barksdale,2000). For moral/ethical motivational forcesdiscussed by Maertz and Griffeth (2004),conscientious individuals are more likely tobelieve they have a moral obligation to staywith an organization. Maertz and Griffeth

Previous empirical

research has

determined that

job performance

is positively

affected by both self-confidence

and confidence

with decisions (or

decisiveness).


6/25



posited that individuals with religious ormoral beliefs, such as the Protestant workethic, believe that perseverance is good re-gardless of the circumstances (Blau & Ryan,1997; Niles, 1999), and that switching jobsindiscriminately is a sign of poor character.

Conscientiousness also has well-establishedrelationships with job satisfaction ( =.26, Judge, Heller, & Mount, 2002; Judge, Locke,Durham, & Kluger, 1998; Organ & Lingl,1995), an important predictor of employeesturnover decisions.

There are also reasons to believe thatemotional stability would be negativelylinked to turnover. Individuals low in thetrait (or high in neuroticism) tend to havenegative perceptions of themselves and theirenvironment (Burke, Brief, & George, 1993;Watson, Clark, & Tellegen, 1988). This leads

to an increased likelihood of expe-riencing negative states of mindor mood, which are associatedwith encoding and recalling nega-tive information (Watson & Clark,1984; Weiss & Cropanzano, 1996),and higher levels of conflict withcoworkers (Organ, 1994). Becauseneurotic individuals tend to be innegative moods more often than

emotionally stable individuals areand tend to have more conflictswith coworkers (Organ, 1994),

they are less likely to become effectively so-cialized into their organizations. Cote (2005)theorized that individuals exhibiting nega-tive emotions, such as sadness and anger, areless likely to receive social support from co-workers and more likely to experience inter-personal conflict, thereby increasing theirstress levels and intentions to quit (Spector &

Jex, 1998).In discussing the affective motivationalforces influencing voluntary turnover, Maertzand Griffeth (2004) noted that employeeswho have negative views of their work envi-ronments are more likely to leave (Meyer& Allen, 1991). Judge et al. (2002) found thatof all the five factor model (FFM) traits,emotional stability had the largest true scorecorrelation with job satisfaction, at .29,while Barrick and Mount (1996) noted that

conscientiousness and emotional stabilitywere predictive of turnover of semi-truckdrivers ( = .26 for conscientiousness; = .22for emotional stability). This evidence indi-cates that both personality traits should benegatively related to voluntary turnover.

H5: Employees who are more conscientious willbe (a) more likely to stay with the organizationand (b) better performers than those who are lessconscientious.

H6: Employees who are more emotionally stablewill be (a) more likely to remain with the or-

ganization and (b) better performers than thosewho are less stable.

The full value of using FFM personalitytraits during selection emerges when onesimultaneously considers the predictive va-lidity with both turnover and performance.Research (e.g., Barrick, Mount, & Judge, 2001)has shown that the two FFM traits examinedhere are valid predictors of performance inall, or nearly all, jobs. Hence, these two traitsshould be correlated with job performance,as well as with voluntary, avoidable turn-over.

The Temporally Dynamic Nature ofTurnover

How do the effects of the variables examinedin this study endure over time? Theoreticallythe biodata measures and pre-hire attitudescales are expected to primarily affect turn-over early in the job. When applicants beginnew jobs, socialization has been shown tohave a disproportionately large effect onturnover (Berlew & Hall, 1966). Socialization

promotes sense making, situational identifi-cation, acculturation (Louis, 1980), and cre-ation of relationships and social integration(Louis, Posner, & Powell, 1983). Basing hiswork on field theory (Lewin, 1951), Allen(2006) noted that employees who fail toadapt to a new job environment may takethe extreme response of leaving the organi-zation, particularly during the early stages of socialization. Learning how to do the job,meeting the right people from whom to

Theoretically, both

conscientiousness

and emotional

stability should be

negatively related to

voluntary turnover.


7/25



learn about the organization, and figuringout the power structure of the firm and theorganizations goals and values are impor-tant to employee success and lead to lowerturnover (Chao, OLeary-Kelly, Wolf, Klein,& Gardner, 1994; OReilly, Caldwell, & Bar-

nett, 1989).Employees who were referred by otheremployees and who have more friends andfamily in the organization are more likelyto have been provided with a realistic jobpreview and therefore are more familiarwith the job requirements. These employ-ees also have a pre-established social net-work within the organization, whichprovides a means of social support early intheir tenure. Similarly, the employmentmotivation and personal confidence scalesrelate to the internal resources employeeshave to deal with these issues. Specifically,greater confidence, desire for the job, andintention to stay contribute to overcomingthe new and uncertain situations inherentin the early stages of organizational entry.Hence, employees who rate higher on theseconstructs are better able to cope with thedemands of a new job early in their tenure,while employees who rate lower on theseconstructs are more susceptible to the psy-

chological upheaval that can occur duringthe early stages of employees socializationinto an organization (Bauer, Morrison, &Callister, 1998).

According to attitude theory (Fishbein &Ajzen, 1975), however, pre-hire attitudesabout a job are likely to change over time,based on on-the-job experiences. These ex-periences may affect how employees feelabout their positions, including their desireto stay, their confidence in having made the

right job choice, and their efficacy in com-pleting their job duties. Furthermore, laterin their job tenure, employees without pre-existing social networks will establish theirown social circles with the organization.Taken together, these predictors are ex-pected to have stronger relationships withturnover early in the job but weaker effectsover time, as the social and coping benefitsderived from these variables become lessimportant. Conversely, personality and

habitual commitment are expected to havea continuous effect on turnover and perfor-mance. In keeping with this reasoning, wepropose:

H7: The impact of more pre-hire embeddedness,

attraction, and condence on turnover and performance will be greater earlier in employees job tenure than later in their tenure.

Research Methodology andMeasures Used in the Study

The sample consisted of job applicants ata large financial company in the RockyMountain region. The total sample was 354applicants, of whom 119 were hired ascredit union tellers. The typicalparticipant was white (93%), fe-male (about 75%), in her earlytwenties (median age was 20 or21), with at least a high schooleducation. The respondents hada stake in the outcome of the as-sessments and consequentlywere motivated test takers whothought their responses wouldinfluence the hiring decision.However, the results from these

questionnaires were not used forhiring purposes. Applicants whowere not hired ( N = 235) weretold so at that time and were ex-cluded from consideration for the purposesof this study. Thus, all analyses were basedon responses from hired applicants(N = 119).

As part of a formal job selection process,all applicants completed a pre-hire assess-ment based on the scales used in this study.

All predictor measures, except the biodatameasures, used a 5-point Likert rating for-mat (1=strongly disagree to 5=stronglyagree).

Biodata Measures

The first biodata measure, number of friendsand family , asked the applicant the number of friends working at the organization and howmany family members work at the organiza-

Socialization

promotes sense

making, situational

identification,

acculturation,

and creation of

relationships and social integration.


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tion (Breaugh & Dossett, 1989). The sum of both answers was used to reflect the number of friends and family variable. Employee refer-rals , the second biodata measure (Breaugh &Mann, 1984), asked whether the applicanthad been referred by an employee of the

company. Those who were referred werecoded as a 1, and those who were not werecoded as a 0. Each biodata item was con-verted to a z-score, and these scores wereadded together to reflect the biodata/pre-hireembeddedness measure.

The number of months the applicanthad worked in his or her most recent jobrepresented the third theoretically relevantbiodata item, time in prior job . The fourththeoretically relevant item was number of

jobs held in the past five years.Again, these two items were con-verted into z-scores and thencombined to form the biodata/habitual commitment measure.Standardized scores for the num-ber of jobs in the last five years variable were calculated to clas-sify applicants into four groups:those less than 18 years old,those 18 to 19 years old, those20 to 21 years old, and those

over age 21. These scores werecompared only to those of otherapplicants in the same categoryto control for differences in the

opportunity to switch jobs, depending ontime in the workforce. The number of jobs inthe last five years variable was reverse-codedbefore being combined with the time in

prior job variable, so high scores on bothwere equated with greater commitment toprior employers.

Employment Motivation Scales

The measure of applicant attraction to theemployment opportunity focused on the ap-plicants pre-hire desire for the job at the firmand pre-hire intent to stay . Desire for a job wasassessed with eight items from the Lee et al.(1992) job desirability scale ( =.76). Exampleswere I have a strong desire to be an em-ployee of this company and I feel very

committed to this company. Intent to staywas assessed with five items ( =.80) fromChatman (1991). These were based on itemswritten for traditional intent-to-quit scales.Examples were I intend to remain with thiscompany for a long time, and If I have my

own way, I will be working for this companysix months from now. Confirmatory factoranalyses indicated that a one-factor model fitthe data better than a two-factor model. Fitstatistics for the one-factor model were: 2:151.78, 65 df ; PNFI: .77; SRMR: .049; PGFI:.67. Fit statistics for the two-factor modelwere: 2: 143.20, 64 df; PNFI: .76; SRMR: .047;PGFI: .66. The coefficient alpha for the com-bined scale was .70.

Personal Condence Scales The measure reflecting applicant confi-dence was the sum of two scales: confidencewith self and confidence with decisions.Confidence with self was assessed witheight items from Lee et al. (1992) ( =.76).Examples of confidence-with-self items in-clude I have always been able to do well inanything I have tried, and I expect to dowell at this company. Confidence with de-cisions was measured with a five-item scale

adapted from Lee et al. (1992) ( =.76). Ex-amples were I never make major decisionsquickly, and I always carefully weighcosts and benefits when making decisionsthat affect my life. Confirmatory factoranalyses indicated that a one-factor modelfit the data either the same as or slightlybetter than a two-factor model. Fit statisticsfor the one-factor model were: 2: 281.12,65 df ; PNFI: .69; SRMR: .074; PGFI: .64. Fitstatistics for the two-factor model were: 2:

239.97, 64 df ; PNFI: .69; SRMR: .074; PGFI:.64. The coefficient alpha for the combinedscale was .73.

Personality Traits

The personality assessment consisted of 60items designed to comprehensively measureconscientiousness and emotional stability,with 30 items measuring each personalitytrait. Coefficient alpha reliabilities were .87

As part of a

formal job

selection process,

all applicants

completed a pre-

hire assessment

based on the scales used in this study.


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and .86, respectively. Examples of items forconscientiousness were, I put a great deal of effort into my work, and, Others have de-scribed me as a very disciplined person. Ex-amples of emotional stability items were, Ibecome irritated when others criticize me,

and I tend to get over embarrassing situationsvery quickly.

Turnover

Turnover data were collected over a two-yearperiod after the applicants were hired andwere categorized as having occurred withinsix months or after this period, up to twoyears. Within the first six months, there were95 stayers (coded as 0) and 24 leavers (codedas 1). Of the employees who left during thisperiod, 18 left for voluntary, avoidable rea-sons, and 6 left for voluntary, unavoidablereasons. Of those leaving between six monthsand two years after hire, there were 70 stayersand 25 leavers. Of the employees who leftduring this period, one left because of involuntary reasons (was fired); 18 left forvoluntary, avoidable reasons; and 6 left forvoluntary, unavoidable reasons. Reasons forturnover decisions were coded according tothe classification scheme developed by Abel-

son (1987). The voluntary, avoidable turn-over category refers to turnover that reflectedthe individuals decision to leave and that theorganization may have been able to avoid(e.g., through raises or by providing betterwork conditions). Voluntary, unavoidableturnover occurs when the employee choosesto leave but the organization had no controlover it (e.g., quitting to trail a relocatingspouse or to resume education). Abelson(1987) found that those who leave the orga-

nization for unavoidable reasons resemblestayers more than they resemble the leaverswhose departure is avoidable. In fact, Homand Griffeth (1995) stated that voluntary,avoidable turnover is a superior criterion fortesting prevailing turnover models. For thesereasons, this study examines the predictivevalidity of the various selection variables (e.g., biodata and personality) by focusing onvoluntary, avoidable turnover. Correlationswith voluntary turnover also are reported,

but only for comparative purposes with pre-vious findings.

Job Performance Ratings

The employees supervisors rated their job

performance after 30 days, 6 months, and 1year. Employees were evaluated on nine di-mensions: quality of work, quantity of work,job knowledge, interpersonal skills, rule-fol-lowing behavior, communication skills, ini-tiative, punctuality, and customer service.Performance was evaluated on a five-pointLikert scale ranging from unsatisfactory tofar exceeds expectations ( =.75.84). Over-all performance was the mean of the ratingsacross all dimensions. Correlations betweenother variables and job perfor-mance for time 1 (up to sixmonths) used the 30-day perfor-mance ratings, while correlationswith job performance for time 2(up to two years after hire) usedthe most recent performance rat-ing (either performance rated atsix months or at one year) for em-ployees who remained after sixmonths.

Study Results: Pre-hirePredictors Are Related toBoth Turnover and JobPerformance

Table I reports the means, stan-dard deviations, and zero-order correlationsamong the variables. For variables 1 to 9, cor-relations greater than .15 are significant at the.05 level using a one-tailed test; for variables10 to 12, correlations greater than .17 are

significant. All the predictors were negativelyrelated to voluntary, avoidable turnover ( r ranges from .18 to .27) during the six-month period, as hypothesized. These resultsprovide initial support for the hypothesesthat pre-hire embeddedness ( r =.22, hypoth-esis 1a), habitual commitment ( r =.21, hy-pothesis 2a), personal confidence ( r =.20,hypothesis 3a), motivation for employment(r =.18, hypothesis 4a), conscientiousness(r =.19, hypothesis 5a), and emotional stabil-

The personality

assessment

consisted of 60

items designed to

comprehensively

measure

conscientiousness

and emotional

stability.


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T A B L E

I

C o r r e

l a t i o n s

A m o n g

V a r i a

b l e s

V a r i a

b l e s

M

S D

1

1 a

1 b

2

2 a

2 b

3

4

5

6

9

1 2

1 . B i o d a

t a P r e

h i r e

E m

b e d d e

d n e s s

C o m p o s i

t e

. 0 0

. 7 4

1 a .

E m p

l o y e e

R e

f e r r a

l

. 4 1

. 4 9

. 6 5

1 b

. N u m

b e r o

f F r i e n

d s a n

d

F a m

i l y

1 . 2 1

1 . 4

. 5 7

. 1 0

2 .

B i o d a

t a H a

b i t u a

l C o m m

i t m e n

t

C o m p o s i

t e

. 0 1

. 7 1

. 3 1

. 2 8

. 1 4

2 a . T

i m e o n

P r i o r

J o b ( i n

m o n

t h s )

2 2

. 6

2 6

. 3

. 2 8

. 2 5

. 1 7

. 8 7

2 b

. N u m

b e r o

f J o b s

i n L a s t

F i v e

Y e a r s

2 . 7

0

1 . 4

. 0

7

. 0

9

. 0

1

. 7

3

. 5

4

3 .

P e r s o n a

l C o n

d e n c e

3 . 6

8

. 4 3

. 0 9

. 0 0

. 1 1

. 1 2

. 0 9

. 0

8

4 .

E m p

l o y m e n

t M o

t i v a

t i o n

4 . 1

5

. 4 6

. 0 9

. 0

4

. 1 6

. 0 6

. 0 9

. 0 4

. 2 4

5 .

C o n s c

i e n

t i o u s n e s s

4 . 3

0

. 3 4

. 1 7

. 0 9

. 1 6

. 0 9

. 0 6

. 0

7

. 4 0

. 4 3

6 .

E m o

t i o n a

l S t a b i l i t y

3 . 9

0

. 3 6

. 2 8

. 1 7

. 2 4

. 0 7

. 0 4

. 0

6

. 4 5

. 3 1

. 7 3

U p

t o s i x m o n

t h s a

f t e r

h i r e

7 . V o

l u n

t a r y , A

v o i d a

b l e T u r n o v e r

( N =

1 1 3 )

0 . 1

6

. 3 7

. 2

2

. 1

7

. 1

5

. 2

1

. 0

5

. 1 9

. 2

0

. 1

8

. 1

9

. 2 7

. 2

5

8 . V

o l u n

t a r y

T u r n o v e r

( N = 1

1 9 )

0 . 2

0

. 4 0

. 2

0

. 1

7

. 1

4

. 2

2

. 0

8

. 1 9

. 1

6

. 1

3

. 1

8

. 2 7

. 2

9

9 .

J o b P e r f o r m a n c e

( N =

1 1 9 )

3 . 3

3

. 6 1

. 2 9

. 2 6

. 1 7

. 2 2

. 1 9

. 0

6

. 0 3

. 0

5

. 1 8

. 1 9

. 3 7

U p

t o t w o y e a r s a

f t e r h

i r e

1 0 . V

o l u n

t a r y , A

v o i d a

b l e T u r n o v e r

( N =

8 8 )

0 . 2

0

. 4 1

. 0 0

. 1 7

. 1

5

. 0

6

. 0

3

. 0 5

. 0

5

. 0 4

. 2

2

. 2 1

. 1

4

. 2

7

1 1 . V

o l u n

t a r y

T u r n o v e r

( N = 9

5 )

0 . 2

6

. 4 4

. 0 2

. 1 6

. 1

2

. 0

1

. 1 0

. 1 2

. 0

5

. 0 4

. 2

1

. 2 0

. 1

0

. 2

9

1 2 .

J o b P e r f o r m a n c e

( N =

9 5 )

3 . 5

0

. 3 7

. 1 1

. 1 7

. 0

1

. 0 7

. 1 2

. 0 6

. 1 4

. 0

8

. 1 8

. 1 8

. 3 7

N o

t e :

F o r v a r

i a b l e s

1 9 , N =

1 1 3 1

1 9 , p . 1

5 ; f o r v a r i a

b l e s

1 0 1

2 , N =

8 8 9 5

, p < . 0

5 f o r c o r r e l a

t i o n s > . 1

7 .


11/25



ity ( r =.27, hypothesis 6a) predict who islikely to remain working for a company sixmonths after hire. Table I also reports thecorrelations between these predictors and abroader turnover category, one that reflects allvoluntary turnover. This outcome reflects all

turnover decisions when the employee volun-tarily chooses to leave, regardless of whetherthe company could reasonably do anythingabout it (avoidable) or not (unavoidable). Asexpected, these correlations are comparableto those reported for voluntary, avoidableturnover ( r ranges from .13 to .27).

After the six-month period and up totwo years later, conscientiousness and emo-tional stability were still related to volun-tary, avoidable turnover, as expected ( r =.22and .21, respectively). All other predictors(pre-hire embeddedness, habitual commit-ment, employment motivation, and per-sonal confidence scales) had correlationswith voluntary, avoidable turnover thatwere nearly equal to zero ( r ranges from.06 to .04). Overall, there was initial par-tial support for hypothesis 7. Specifically,the validity of pre-hire embeddedness, em-ployment motivation, and personal confi-dence scales decreased over time for thesepredictors when predicting voluntary,

avoidable turnover. However, the validityof the habitual commitment measure,which was expected to be a valid predictorduring the later time period, also decreasedover time. As expected, personality wasfound to be a useful predictor of voluntary,avoidable turnover up to two years afterhire.

Table I also provides information as towhether the turnover that occurs is func-tional (poor performers leave) or dysfunc-

tional (good performers leave). In accor-dance with the Griffeth et al. (2000)meta-analysis, voluntary, avoidable turn-over is negatively correlated with perfor-mance ( r =.25 at up to six months andr =.27 up to two years). This supports thecontention that those who stay tend to bebetter performers. The results in Table I alsodemonstrate that a number of the variablesthat predict turnover also predicted job per-formance at up to six months. Specifically,

pre-hire embeddedness and habitual com-mitment are both related to supervisoryratings of job performance at six monthswith correlations of .29 and .22, respec-tively. These results provide initial supportfor hypotheses 1b and 2b. In addition, hy-

potheses 5b and 6b were initially supported,given that conscientiousness and emotionalstability predicted job performance at sixmonths ( r =.18 and .19, respectively). How-ever, personal confidence and motivationfor employment were not related to jobperformance at six months, which fails tosupport hypotheses 3b and 4b. After thesix-month period, only the two personalitytraits ( r =.18 for both) were significantly re-lated to performance. The other predictors,including the two biodata mea-sures and pre-hire attitude scales,were not significant predictors ( r ranges from .08 to .14). There-fore, hypothesis 7 was again onlypartially supported.

Although the primary analy-ses involving the biodata itemswere for the broader construct-level composites, the results forthe individual items comprisingthe composites were also included

in the correlation matrix for infor-mational purposes. As can be seenin Table I, both items making upthe pre-hire embeddedness com-posite had fairly similar relation-ships with turnover and perfor-mance up to six months afterhire. However, for the habitual commitmentcomposite, the number of jobs held over theprevious five years was a better predictor of early turnover, while tenure on the most re-

cent job was more predictive of early jobperformance.These findings suggest that although all

the predictors studied here are able to fore-cast who leaves within six months, only thebiodata measures and personality traits pre-dicted employees job performance early intheir jobs. Furthermore, only the personalitytraits were correlated with performance aftersix months. Finally, the pre-hire attitudescales did not predict who is likely to be

This study

examines the

predictive validity

of the various

selection variables

(e.g., biodata

and personality)

by focusing on

voluntary, avoidable

turnover.


12/25



successful in the job either early or up to twoyears later.

Although the post-six-month analysesconsidered only the employees who were stillemployed at the credit union at the time, thedecrease in the magnitude of the correlations

was not due to restriction in the variability of the predictor variables. The degree of rangerestriction between the time 1 and time 2samples was extremely small, with range re-striction values ( SD for time 2/ SD for time 1)of .96 to 1.01 across all the predictors,although the means were higher at time 2.Although the organization did not use theresults of the assessments to make hiring de-cisions, it was still important to evaluate pos-sible range restriction in the hired sampleversus the applicant sample. Similar to the

results between the time 1 andtime 2 samples, the degree of range restriction was very small(range restriction values of .90 to1.06) for most of the variables.However, employment motiva-tion and emotional stability hadhigher levels of range restriction:values of .76 and .82, respectively.This finding indicates that rangerestriction may be responsible for

the somewhat lower correlationsthat employment motivation haswith turnover and performancecompared to the other predictors.Similarly, the effects of personal-

ity, especially the trait of emotional stability,on turnover and job performance are evengreater when accounting for range restric-tion.

Another important purpose of this studywas to establish the incremental validity of

these theoretically relevant predictors of vol-untary, avoidable turnover and performance.Hierarchical regression analyses tested theability of each set of predictors (biodata, pre-hire attitudes, and personality traits) to explainseparate portions of the variance in eitherturnover or performance. Each set of variableswas standardized before being entered intothe regressions. Tables II and III summarizethe results for predictions of voluntary,avoidable turnover and Tables IV and V

for performance. For each set of predictors(e.g., biodata), regressions were run threeways by entering the set of predictors in eachstep. In this way, it was possible to assess theincremental gain provided by each set of pre-dictors, after accounting for the effects of

other sets of predictors. For step 2, the resultsfor both possible orders of entry are presentedas steps 2a and 2b, with the subhead indicat-ing which construct was entered first. Specifi-cally, biodata were entered after eitherpersonality (2a) or pre-hire attitudes (2b),personality after biodata (2a) or pre-hire atti-tudes (2b), and pre-hire attitudes after per-sonality (2a) or biodata (2b).

For each regression, we assessed the over-all variance accounted for ( R2) and the rela-tive change in prediction ( R2) obtained byadding the set of variables in each step of thatregression. Thus, the relative change ( R2)demonstrates the incremental gain of thatpredictor set, once other sets (steps) of vari-ables are included in the regression. For thelogistic regression results presented in TablesII and III, the R2 values are Cox and Snellanalogs to ordinary-least-squares R2 estimates.In addition, the odds ratios are also pre-sented. The odds ratio indicates the ratio of relative importance of the independent vari-

ables in terms of their effect on the depen-dent variables odds of occurring.

The overall regression equations for turn-over and performance, assessed at six months,were of comparable magnitude ( R2=.134 to.143), indicating that these three sets of vari-ables (biodata, pre-hire attitudes, and per-sonality traits) are useful predictors of bothoutcomes at up to six months after hire. Asshown in the logistic regression results pre-sented in Table II, each set of predictors sig-

nificantly predicted voluntary, avoidableturnover during the six-month period whenentered alone (step 1). The only significantgains in incremental validity occur whenpersonality is entered either second after bio-data in the regression equation ( R2=.050 forstep 2a) or when biodata are added ( R2=.059for step 2a or 3, R2=.066 for step 2b). Theodds ratios confirm these results. Specifically,including biodata in the logistic regressionsat steps 1, 2a, 2b, or 3 indicates that employ-

The magnitude of

the predictions

obtained from the

biodata and pre-hire

attitudinal predictors

of voluntary,

avoidable turnover

attenuate over time.


13/25



T A B L E

I I

H i e r a r c

h i c a l

L o g

i s t i c

R e g r e s s

i o n

R e s u

l t s

B e t w e e n

V o

l u n t a r y

, A v o

i d a

b l e T u r n o v e r a t U p t o

S i x M o n t h s

A f t e r

H i r e a n

d V a r

i o u s

S e t s o

f P r e

d i c t o r s

U p

t o S i x M o n

t h s

A f t e r

H i r e

S t e p

1

S t e p

2 a

S t e p

2 b

S t e p

3

V a r i a

b l e s e

t s

R 2

R 2

R 2

R 2

R 2

R 2

R 2

R 2

E n

t e r e

d A f t e r

P e r s o n a

l i t y

E n

t e r e

d A f t e r

A t t i t u

d e s

B i o d a

t a

. 0 7 3 *

. 1 2 3 *

. 0 5 9 *

. 1 2 0 *

. 0 6 6 *

. 1 3 4 *

. 0 5 9 *

F u l l m o

d e

l 2

, d f

8 . 5

5 6

, 1

1 4 . 8

1 5 ,

2

1 4 . 4

5 1

, 2

1 6 . 2

9 6

, 3

S t e p

2

, d f

7 . 3 9 2

, 1

8 . 1

2 7 , 1

7 . 5 3 4

, 1

O d d s r a

t i o

. 2 4 2 *

. 2 4 5 *

. 2 3 1 *

. 2 3 6 *

E n

t e r e

d A f t e r

B i o d a

t a

E n

t e r e

d A f t e r

A t t i t u

d e s

P e r s o n a

l i t y

. 0 6 4 *

. 1 2 3 *

. 0 5 0 *

. 0 7 5 *

. 0 2 1

. 1 3 4 *

. 0 1 4

F u l l m o

d e

l 2

, d f

7 . 4 2 3

, 1

1 4 . 8

1 5 ,

2

8 . 7

6 2

, 2

1 6 . 2

9 6

, 3

S t e p

2

, d f

6 . 2

5 9

, 1

2 . 4

3 8

, 1

1 . 8

4 5

, 1

O d d s r a

t i o

. 4 4 3 *

. 4 4 6 *

. 5 6 6

. 5 8 9

E n

t e r e

d A f t e r

P e r s o n a

l i t y

E n

t e r e

d A f t e r

B i o d a

t a

P r e - h

i r e

A t t i t u

d e s

. 0 5 4 *

. 0 7 5 *

. 0 1 1

. 1 2 0 *

. 0 4 7 *

. 1 3 4 *

. 0 1 1

F u l l m o

d e

l 2

, d f

6 . 3

2 4

, 1

8 . 7

6 2

, 2

1 4 . 4

5 1

, 2

1 6 . 2

9 6

, 3

S t e p

2

, d f

1 . 3 3 9

, 1

5 . 8

9 5

, 1

1 . 4

8 1

, 1

O d d s r a

t i o

. 3 6 6 *

. 5 7 2

. 3 5 6 *

. 5 3 1

N o

t e :

R 2

v a

l u e s a r e

C o x a n

d S n e l

l R 2 .

* p < . 0

5


14/25


15/25


16/25



T A B L E

V

H i e r a r c

h i c a l

R e g r e s s

i o n

R e s u

l t s

B e t w e e n

P e r f o r m a n c e a t

U p t o

T w o

Y e a r s

A f t e r

H i r e a n d

V a r i o u s

S e t s o

f P r e

d i c t o r s

U p

t o T w o

Y e a r s

A f t e r

H i r e

S t e p

1

S t e p

2 a

S t e p

2 b

S t e p

3

V a r i a

b l e s e

t s

R 2

R 2

R 2

R 2

R 2

R 2

R 2

R 2

E n

t e r e

d A f t e r

P e r s o n a

l i t y

E n

t e r e d A f t e r

A t t i t u d e s

B i o d a

t a

. 0 1 1

. 0 4 5

. 0 0 7

. 0 1 2

. 0 1 1

. 0 5 1

. 0 0 5

M o

d e

l F - v a

l u e ,

d f

. 9 4 9 ;

1 ,

8 6

1 . 9 1 7 ;

2 ,

8 5

. 4 9 9 ;

2 ,

8 5

1 . 4 4 8

; 3

, 8 4

S t e p

F - v a

l u e ,

d f

. 5 3 2

, 1

. 9 3 3 1

, 1

. 4 6 0

, 1

E n

t e r e

d A f t e r

B i o d a

t a

E n

t e r e d A f t e r

A t t i t u d e s

P e r s o n a

l i t y

. 0 3 8 *

. 0 4 5

. 0 3 3 *

. 0 4 6

. 0 4 5 *

. 0 5 1

. 0 3 9 *

M o

d e

l F - v a

l u e ,

d f

3 . 3

1 6 ;

1 ,

8 6

1 . 9 1 7 ;

2 ,

8 5

1 . 9 5 5 ;

2 ,

8 5

1 . 4 4 8

; 3

, 8 4

S t e p

F - v a

l u e ,

d f

2 . 8 6 4

, 1

3 . 8

4 1 ,

1

3 . 3

1 8 ,

1

E n

t e r e

d A f t e r

P e r s o n a

l i t y

E n

t e r e d A f t e r

B i o d a t a

P r e - h

i r e

A t t i t u

d e s

. 0 0 1

. 0 4 6

. 0 0 8

. 0 1 2

. 0 0 1

. 0 5 1

. 0 0 6

M o

d e

l F - v a

l u e ,

d f

. 0 6 7 ;

1 ,

8 6

1 . 9 5 5 ;

2 ,

8 5

. 4 9 9 ;

2 ,

8 5

1 . 4 4 8

; 3

, 8 4

S t e p

F - v a

l u e ,

d f

. 6 1 0

, 1

. 0 6 0

, 1

. 5 3 2

, 1

N o

t e :

* p < . 0

5


17/25



ees who were one standard deviation abovethe mean had less than one-quarter the oddsof turnover as employees at the mean. In-cluding personality in the logistic regressionsat step 1 or 2a indicates that employees onestandard deviation higher on personality

had less than half the odds of turnover asemployees at the mean. As these findings il-lustrate, once personality and biodata areincluded in the regression of voluntary,avoidable turnover, most of the availablevariance is accounted for ( R2=.123).

Furthermore, the magnitude of the pre-dictions obtained from the biodata and pre-hire attitudinal predictors of voluntary,avoidable turnover attenuates over time. Infact, as shown in Table III, only personalitysignificantly added incremental validity tothe prediction of voluntary, avoidable turn-over up to two years after hire, regardless of when personality was entered in the regres-sion equation ( R2=.053, .052, .070, or .070for steps 1, 2a, 2b, or 3, respectively). Forsteps 1 and 2a, employees one standard de-viation above the mean on personality haveless than half the odds of turnover as em-ployees at the mean. For steps 2b and 3, theodds of turnover are about 38% of those foremployees at the mean.

In Table IV, two sets of predictors, bio-data and personality traits, were shown tohave added significant incremental gains invalidity when predicting early job perfor-mance. The results reveal that biodatasignificantly improved the prediction, re-gardless of when they were added ( R2 =.079,.103, or .082 in steps 2a, 2b, and 3, respec-tively). The two personality traits also addedsignificant incremental predictive validityafter pre-hire attitudes were entered ( R2=.062

in step 2b) or after all other predictors (pre-hire attitudes and biodata) were accountedfor ( R2=.040 in step 3). Consequently, oncepersonality and biodata were included in theregression of early job performance, most of the available variance was accounted for( R2=.118)

In order to ensure that the regression re-sults were not affected due to a common an-tecedent, such as differences in ability level,supplemental analyses were performed using

level of education as a proxy for ability. Thepattern of results for the regressions betweenjob performance at time 1 and the three setsof predictors still held even when controllingfor the employees level of education. Thevariance in performance attributable to the

biodata scales decreased slightly (step 1 R2 =.084; step 2a R2=.061; step 2b R2=.087;step 3 R2 =.064), but the results at each stepwere still significant. For personality and pre-hire attitudes, the variance explained actuallyincreased by extremely small amounts (maxi-mum increase in the R2 or change in R2 of .008). Education was not significantly corre-lated with performance at either time 1 ortime 2 ( r =.15 and .11, respectively).

As shown in Table V, only per-sonality significantly added incre-mental validity to the predictionof job performance up to twoyears after hire, and this finding istrue regardless of when personal-ity was entered into the regression( R2=.038, .033, .045, and .039 forSteps 1, 2a, 2b, or 3, respectively).Thus, by accounting for biodataand personality, one is able to ac-count for nearly all the incremen-tal gain when predicting either

voluntary, avoidable turnover orperformance after six months. Incontrast, only personality addedsignificant incremental validityfor either turnover or performancetwo years after hire.

Discussion of Implications of Find-ings, Study Limitations, and FutureResearch Opportunities

The purpose of this study was to examine theextent to which employers can reduce turn-over and simultaneously increase perfor-mance during the selection process by usingpredictors related to applicants propensityto become attached to their organizations.Turnover researchers have historically ne-glected this question with actual job appli-cants (Griffeth et al., 2000). To fully evaluatethe utility of assessing pre-hire retention-related individual differences, however, it is

The finding that

pre-hire attraction

and confidence

scales offer little

incremental

validity over the

broader traits of

conscientiousness

and emotional

stability is important.


18/25



important to examine whether these predic-tors of turnover are also simultaneously re-lated to job performance. This study bringstogether biodata, pre-hire attitudes, and per-sonality traits for the first time to determinetheir ability to jointly predict turnover and

performance.Consistent with earlier research (Barrick &Zimmerman, 2005), the results indicate thatbiodata measures that assess pre-hire embed-dedness in the organization and habitualcommitment and pre-hire attitude scales thatmeasure employment motivation, personal

confidence, and the traits of con-scientiousness and emotionalstability predicted voluntary,avoidable turnover during a six-month period after hire. However,these results also show that thebiodata and pre-hire attitudescales validities attenuate rapidly,as only the personality traits wererelevant predictors of turnover upto two years later. The results alsoindicate that biodata and person-ality predicted job performance,although personality was the onlyvalid predictor of performanceafter six months. Furthermore, the

study showed that the pre-hire at-titude scales (employment moti-vation and personal confidence)were not related to job perfor-mance. Thus, this study goes be-yond earlier findings to show thatthe pre-hire attitudinal predictorsdid not add significant incremen-tal validity in predicting eitherturnover or performance afteraccounting for biodata and per-

sonality. These findings have im-plications for companies experiencing highturnover, as well as for models of the turnoverprocess. Taken together, these results illustratethat during selection, general personalitytraits and life history experiences are betterpredictors of voluntary, avoidable turnoverand job performance than pre-hire attitudes.

The finding that pre-hire attraction andconfidence scales offer little incremental va-lidity over the broader traits of conscientious-

ness and emotional stability is important. Forcurrent employees, job-specific attitudes, par-ticularly intent to quit, are among the bestpredictors of voluntary turnover. These re-sults reveal that these measures are not aspredictive when applicants provide the re-

sponses. Furthermore, these pre-hire mea-sures are not related to later job performance.These findings indicate that general appli-cant personality traits are more useful predic-tors of turnover and performance thanjob- or organization-specific predictors of turnover. This may suggest that regardless of applicants pre-hire perceptions of how wellthe specific job meets their needs, it is moreimportant to select applicants with a positivepropensity toward working in general. Thefindings also indicate another potential ben-efit of using personality-based integrity tests:reduction of turnover. Possibly because of theindirect measure of the personality constructsof conscientiousness and emotional stability(Ones, 1993), integrity tests predict not onlythievery and other deviant behaviors, butalso job performance (Ones, Viswesvaran, &Schmidt, 1993) and, as implied by the resultsof this study, turnover.

Despite the presence of individual dif-ferences in most models of turnover, they

are the least understood. The use of thesedistinct sets of individual differences be-gins to fill in the empirical gaps in theo-retical models of turnover, particularly inrelation to pre-hire antecedents of turn-over. One of the most frequently examinedpre-hire antecedents of turnover has beenrealistic job previews. However, as Phillips(1998) illustrates, these effects are modestat best (mean r =.09 in field settings,

R2 =.03). The magnitude of the effects re-

ported here ( R2

=.14 at up to six months)far exceeds those obtained using realisticjob previews. Consequently, the under-standing that differences in employeeslikelihood of becoming attached to the or-ganization influence their turnover deci-sions provides future researchers with afoundation to examine how individual dif-ferences work through job satisfaction andorganizational commitment to predictturnover. In fact, researchers (Hom & Grif-

Besides losing

a potentially

productive

employee,

turnover during the

transition phase

is likely to be

costly because the

organization has

yet to recoup the

direct and indirect

costs associated

with hiring and

training the

employee.


19/25



feth, 1995) have been critical of structuralequation model tests and accompanyingparameter estimates that do not include allthe necessary variables. Our findings sug-gest that omitting individual differences,such as those examined in this study (par-

ticularly the personality and biodata vari-ables), from the model may affect theaccuracy of the parameter estimates of other variables studied.

Another contribution of this study is theevidence that the validities of several pre-dictors of turnover decline over time. Thisfinding is consistent with the Griffeth et al.(2000) meta-analysis, which found that therelationships of both performance and com-mitment with turnover were weaker whenturnover was measured more than 12months after the measurement of the pre-dictor. Researchers who develop turnovermodels need to be explicit regarding whethertheir model explains turnover decisionsshortly after hire or after an extended pe-riod, as the antecedents of turnover duringthese two time frames may differ (Mitchell& James, 2001). Although there have beenrepeated calls for the investigation of theeffects of time in organizational research(Wright, 1997, 2002), such studies are still

few and far between.In this study, the decline in predictive

validity may have resulted from changes inemployees ability to deal with job require-ments early in their tenure as opposed toafter having been on the job for an ex-tended period. This change in predictivevalidity may be related to Murphys (1989)conceptualized division of job tenure intoa transition phase, when job demandsare uncertain and stressful, and a mainte-

nance phase, when the demands are nolonger novel after the employee learns howto effectively perform the job. While turn-over in either phase may be detrimental toorganizational performance, turnover earlyin an employees tenure may be particu-larly harmful. Besides losing a potentiallyproductive employee, turnover during thetransition phase is likely to be costly be-cause the organization has yet to recoupthe direct and indirect costs associated

with hiring and training the employee. Or-ganizations would benefit from implement-ing programs (e.g., formal socialization,mentoring, or training) that minimizeturnover by reducing an employees uncer-tainty and ambiguity during the transition

phase.Surprisingly, whether the individual wasreferred by an employee (one of the itemsin the pre-hire embeddedness scale) changedfrom being negatively related to turnover attime 1 to being positively related to turn-over at time 2. The reason is unclear, but itmay be that people who are referred by em-ployees (particularly friends or family mem-bers) often feel obligated to accept the job,even if they are not sure that it is the bestposition for them. Although they may ini-tially stay because of such feelings of obli-gation, they may later realize that theymade a wrong decision and leave for a jobwith another organization. This explana-tion is pure conjecture, however. Futureresearch should focus specifically on repli-cating this finding and examining the un-derlying causes.

One limitation of the study is thepossibility that candidates engaged in im-pression management. This would possibly

attenuate the correlation between the mea-sured constructs and turnover (Barrick &Mount, 1996; Bernardin, 1987). In particu-lar, employment motivation items, such asIf I have my own way, I will be workingfor this company six months from now,could be influenced by applicant faking.Nevertheless, even these predictors werefound to be significantly related to turn-over in an actual applicant setting. Futureresearch should examine the effects of im-

pression management on these measures.In addition, as a precondition for collect-ing enough data to provide reliable effectsize estimates, researchers typically studyjobs that have sufficient quit rates to affordthe large sample sizes needed to examineturnover. Although a strength of this studywas its departure from the use of health careprofessionals and military personnel as sub-jects, the reliance on a lower-level job (creditunion teller) may mean that the findings do


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not necessarily apply to all types of posi-tions. Similar to the finding that level of jobcomplexity moderates the relationship be-tween general cognitive ability and perfor-mance (Schmidt & Hunter, 1998), job levelmay also moderate the relationships between

the predictors in this study and turnover.Future research should replicate these find-ings in upper-level jobs, where the costs as-sociated with turnover are typically muchhigher (Hom & Griffeth, 1995).

Another limitation of the study is thefairly homogeneous sample used, particu-larly in terms of minorities and individualsover age 40 (which is also likely a functionof the type of job in the sample), both of whom made up 7% or less of the sample.Because of this, meaningful adverse impactanalyses would be impossible. However, werefer readers to findings by Barrick andZimmerman (2005) in reference to theminimal adverse impact caused by the pre-dictors included in both that study and thisone, as well as Hough (1998) and Hough,Oswald, and Ployhart (2001) regarding thelow d -scores of personality traits.

Further research also should investigatethe incremental validity of other pre-hiremethods of predicting turnover and perfor-

mance, such as person-environment fit(Kristof-Brown, Zimmerman, & Johnson,2005) and extraorganizational loyalties (e.g.,moonlighting), to gain a more comprehen-sive picture of the value of each predictor.

Although considerable research has beenconducted on the incremental validity of predictors of performance (Schmidt &Hunter, 1998), we know of no such researchfor voluntary, avoidable turnover.

This study has identified a number of

individual differences related to organiza-tional attachment that can be used to pre-dict both turnover and performance beforethe applicant is hired, with biodata and per-sonality being among the most effective.However, pre-hire attitudes (employmentmotivation and personal confidence) didnot predict turnover and performance be-yond biodata (pre-hire embeddedness in theorganization and habitual commitment)and the personality traits (conscientious-ness and emotional stability). Therefore,organizations would benefit most from in-cluding the biodata and personality traitpredictors in their hiring process. This studyalso illustrates that except for personality,the importance of these predictors attenu-ates over time. The finding that the con-structs that best predicted early job turnoverare related to employees having social andpsychological support provides indirect en-dorsement of developmental programs de-signed to reduce employees uncertainty

and ambiguity shortly after they begin theirjobs. Future research should replicate thesefindings in higher-level jobs and includeother predictors related to job performanceand voluntary turnover.

MURRAY R. BARRICK is the department head and Robertson Chair in Business at theMays Business School, Texas A&M University. He earned his PhD in industrial/organiza-tional psychology from the University of Akron. His research interests include assessingthe impact individual differences in behavior and personality have on job and team per-formance and on methods of measuring and predicting such differences. His work hasbeen cited more than 5,300 times (Google Scholar, Nov. 2008). Along with Mick Mount,Barrick is the 2009 recipient of the Distinguished Scientic Contributions Award from theSociety for Industrial and Organizational Psychology.

RYAN D. ZIMMERMAN is an assistant professor of human resource management in theManagement Department at Texas A&M University. He earned his PhD in HRM from theUniversity of Iowa. His research interests include personnel selection, employee turn over,


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