does a corresponding set of variables for explaining voluntary organizational turnover transfer to...

Journal of Vocational Behavior 70 (2007) 135–148

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Does a corresponding set of variables for explaining voluntary organizational turnover transfer to explaining voluntary occupational turnover? �

Gary Blau ¤

Temple University, Human Resource Management Department, 1810 N. 13th St., 384 Speakman Hall, Philadelphia, PA 19122, USA

Received 18 July 2006Available online 8 September 2006

Abstract

This study proposed and tested corresponding sets of variables for explaining voluntary organiza-tional versus occupational turnover for a sample of medical technologists. This study is believed to bethe Wrst test of the Rhodes and Doering (1983) occupational change model using occupational turn-over data. Results showed that corresponding job (occupational) satisfaction and intent to leaveorganization (occupation) variables were each signiWcant for explaining subsequent organization(occupation) turnover. Job insecurity was found to be a signiWcant correlate for organizational turn-over while work exhaustion was found to be a signiWcant correlate for occupational turnover. Studylimitations and directions for future research are discussed.© 2006 Elsevier Inc. All rights reserved.

Keywords: Occupational turnover; Comparing organizational versus occupational turnover

� The author was a member of the Research and Development Committee for the Board of Registry, AmericanSociety of Clinical Pathologists. I thank the Board of Registry for permission to use this data. Portions of thispaper were written while the author received Summer Research support from Temple University.

* Fax: +1 215 204 8362.E-mail address: [email protected].

0001-8791/$ - see front matter © 2006 Elsevier Inc. All rights reserved. doi:10.1016/j.jvb.2006.07.007

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136 G. Blau / Journal of Vocational Behavior 70 (2007) 135–148

1. Introduction

Voluntarily changing organizations (jobs) and occupations are each viewed as sepa-rate types of interrole transitions, where a transition is deWned (Louis, 1980, p.330), as“a period during which an individual is changing roles (taking on a diVerent objectiverole).” Louis (1980) distinguishes Wve types of interrole transitions: entry/reentry; intra-company (transfer), intercompany, interprofession and exit (retirement). This paperwill focus on comparing voluntary intercompany (organization) and interprofession(occupation) work transitions. In a voluntary organizational work transition employ-ees leave their organization, while for voluntary occupational turnover an individualchanges their occupation.

Practitioner literature in the United States suggests that changing organizations hap-pens much more frequently than changing occupations. For example, Bolles (2006) hassuggested that the average worker under 35 years of age will go job-hunting in a diVerentorganization every one to three years, while over 35 year olds will go look for an interorga-nization change every Wve to eight years. Bolles (2006) also suggests that many individualswill change occupations at least three times before exiting the work force.

Academic research on leaving one’s occupation suggests that it is typically a muchmore diYcult type of work transition, versus leaving one’s organization, due to thegreater “costs,” such as additional needed training and human capital investment, dis-rupted work relationships, and lost time and income, typically associated with occupa-tional change (Blau, 2000; Blau, Tatum, & Ward-Cook, 2003a; Carson, Carson, &Bedeian, 1995; Cunningham & Sagas, 2004; Neapolitan, 1980). Research designs reXectthe diYculty of this transition and collecting actual occupational change data is veryrare. Prior survey-based research has focused on intent to change occupations as the out-come variable (e.g., Blau, 2000; Blau & Lunz, 1998; Blau et al., 2003a; Carson et al., 1995;Cunningham & Sagas, 2004; Lee, Carswell, & Allen, 2000; Meyer, Allen, & Smith, 1993;Rhodes & Doering, 1993; Snape & Redman, 2003).

The goals of this paper are to: Wrst, test the relationships of individual controls, workattitude antecedents, work attitudes, turnover perceptions, and turnover intent variablesfor explaining subsequent organizational turnover behavior. Second, the applicability ofthe same individual controls and corresponding work attitude antecedents, work attitudes,turnover perceptions, and turnover intent variables for explaining subsequent occupationalturnover behavior will be tested.

1.1. One set of variables leading to a voluntary organizational turnover decision

As part of decision paths #3 and #4b in Lee and Mitchell’s (1994, p.62) unfoldingemployee job (organizational) turnover model, job dissatisfaction due to negative evalua-tion leads to job search-related behavior which then leads to evaluating job alternativesand subsequent employee quit decisions to leave their organizations. Lee, Mitchell, Holton,McDaniel, and Hill (1999) found some support for these paths within their model. Deci-sion path #4 is acknowledged by Lee and Mitchell (1994, p.62) to be the most similar pathto general psychological models of voluntary organizational turnover (e.g., Mobley, 1977;Mobley, GriVeth, Hand, & Meglino, 1979; Steers & Mowday, 1981). In their integration ofturnover theories and corresponding results, Hom and GriVeth (1995) suggested that vari-ous job factors, including stresses such as job insecurity, collectively lead to corresponding

G. Blau / Journal of Vocational Behavior 70 (2007) 135–148 137

work-related attitudes, i.e., decreased organizational commitment and job satisfaction,which lead to job withdrawal cognitions. These cognitions, along with job search and avail-ability/evaluation of job alternatives, then lead to voluntary job turnover. Meta-analyses oforganizational turnover research (Cotton & Tuttle, 1986; GriVeth, Hom, & Gaertner, 2000)provide general support for this set of proposed variables being associated with voluntaryorganizational turnover.

One recent prominent stress is job insecurity. In a 1995 USA Today poll (Anony-mous, 1995), the top source of employee stress cited was job security or the fear of losingone’s job. Job insecurity has been deWned by Greenhalgh and Rosenblatt (1984, p.438),as “perceived powerlessness to maintain desired continuity in a threatened job situa-tion.” Job insecurity is a negative antecedent of job satisfaction (Sverke, Hellgren, &Naswall, 2002).

In their meta-analysis, GriVeth et al. (2000) found that the demographic variable, num-ber of dependent children, was negatively related to voluntary job turnover. Increasing orat least maintaining one’s income, especially if one is the primary income source for ahousehold, can be an issue when deciding to leave a job (Price, 1977). Therefore, number ofdependent children and primary income source will be measured as common control vari-ables. The overall variable set of common controls, and “corresponding” antecedents ofwork attitudes, work attitudes, turnover perceptions, and turnover intentions to leavingthe organization is shown in Fig. 1.

By “corresponding” is meant common or shared work referent. For example, organi-zational commitment has been more strongly linked to organizational withdrawal whileoccupational commitment has been more strongly linked to occupational withdrawal(Blau et al., 2003a; Meyer et al., 1993). Cumulatively, this suggests the following generalhypothesis:

Hypothesis 1. beyond the control variables, corresponding antecedents of work attitudes,work attitudes turnover perceptions, and turnover intentions will relate to leaving theorganization.

Fig. 1. Presentation of corresponding sets of variables for explaining voluntary organizational versus occupa-tional turnover.


1.2. A corresponding set of variables leading to a voluntary occupational turnover decision

The only general psychological model of voluntary career change found in the literaturewas presented by Rhodes and Doering (1983) in which changing one’s career, “refers tomovement to a new occupation that is not part of a typical career progression” (p.631).Rhodes and Doering (1983) based their model on prior voluntary job turnover models,particularly Mobley et al. (1979), and to a lesser extent Price (1977) and Steers and Mow-day (1981). Rhodes and Doering (1983, p. 633) theorized that reduced job satisfaction andcareer satisfaction lead to career withdrawal cognitions (including intent to changecareers), which combined with search and availability of alternatives, then leads to actualcareer change.

In identifying job satisfaction as a key initial “driver” of the career change process,Rhodes and Doering (1983) discuss the prominent role of person–work environment corre-spondence for aVecting job satisfaction. Work exhaustion could be characterized as oneproxy measure of person–work environment correspondence. Work exhaustion has beendeWned as “the depletion of emotional and mental energy needed to meet job demands”(Moore, 2000, p.336). Moore (2000) argued that work exhaustion has a wider applicationto jobs with lower interpersonal contact, and thus encompasses emotional exhaustion, i.e.,a lack of energy and a feeling that one’s emotional resources, particularly for dealing withpeople, are used up.

Emotional exhaustion is widely viewed as the initial key component of the burnout pro-cess (Cordes & Dougherty, 1993; Lee & Ashforth, 1996). Jackson, Schwab, and Schuler(1986) found a signiWcant relationship between emotional exhaustion and teachers’ consid-ering leaving their education Weld. Doering and Rhodes (1989) also found that burnoutwas a reason given by teachers for considering an occupational change. If employees per-ceive that changing jobs but remaining in the same occupation will continue their basic jobduties they may view simply changing jobs as going “from the frying pan to the Wre.” One“change cure” for work exhaustion may be to change occupations (Doering & Rhodes,1989; Neapolitan, 1980).

A partial empirical test of the Rhodes and Doering (1983) model, using intent to changecareers as the outcome, was supported (Rhodes & Doering, 1993). In applying the Rhodesand Doering (1983) model here several variables will be modiWed. A parallel measure tojob satisfaction continuing the focus on an “occupational” referent, would be occupationalsatisfaction or “career” satisfaction, with the understanding that career means one’s occu-pation (Blau, Paul, & St. John, 1993). Occupational satisfaction should correlate with, butbe distinct from, occupational commitment, just as job satisfaction overlaps with, but isdistinct from, organizational commitment (Mathieu & Zajac, 1990). Career commitmenthas been deWned as one’s attitude towards one’s profession or vocation (Blau, 1985), and ithas been found to be negatively related to intent to change occupation (Blau, 1985; Leeet al., 2000). Consistent with the focus on desire to work in an occupation and the corre-sponding terminology used in more recent literature, career commitment is better labeledaVective occupational commitment (Lee et al., 2000), and intent to leave career and chang-ing career (Rhodes & Doering, 1983) really means intent to leave occupation and occupa-tional turnover (Blau et al., 1993; Lee et al., 2000).

A corresponding set of variable linkages for leaving an occupation is also shown inFig. 1. Again, primary income source and number of dependent children will serve as com-mon control variables. Neapolitan (1980) noted the greater Wnancial obstacle to changing


occupations generally for someone who was the primary income source for their house-hold. Doering and Rhodes (1989) noted that not having a family to support, as well as hav-ing older, self-suYcient children, facilitated occupational change. The variable set of:antecedents of work attitudes, work attitudes, turnover perceptions, and intent to leaveoccupation, for aVecting voluntary occupation turnover is also shown in Fig. 1. Cumula-tively, this research leads to the following hypothesis:

Hypothesis 2. beyond the control variables, corresponding antecedents of work attitudes,work attitudes turnover perceptions, and turnover intentions will relate to leaving theoccupation.

2. Method

2.1. Sample and procedure

Medical technologists (MTs) constituted the study sample, and the data comes from alongitudinal study of the career paths of medical technologists (MTs) by the Board of Reg-istry of the American Society for Clinical Pathology (BOR-ASCP). The study was begun in1993 when the ASCP mailed surveys to a stratiWed sample of 2002 recently graduated MTs.These MTs had registered with the BOR-ASCP to take some type of certiWcation exam. Ofthe 2002 surveys mailed out, 1156 (58%) were voluntarily returned. Every year since 1993,ending in 2002, surveys were mailed to this initial respondent base of 1156 respondents.The study here draws from variables collected in 2001 and 2002 (the end of the data collec-tion period).

MTs work in a laboratory in a variety of health-related organizations (e.g., hospitals,independent laboratories). They are responsible for the accurate performance of tests (e.g.,analyzing blood, urine and tissue samples; and growing cultures) that help determine thepresence or absence of disease. Cordes and Dougherty (1993, p.643) characterized labora-tory personnel as a lower frequency/lower intensity interpersonal contact occupation. Assuch it is more appropriate to measure work exhaustion, rather then emotional exhaustion(Moore, 2000). A 1995 decision by the National Labor Relations Board (1995) aYrmedthat medical technology is a profession. Consistent with discussion by Lee et al.(2000,p.800) the terms “profession” and “occupation” are used interchangeably in the measuressection.

In 2001, 501 of 1156 (43%) MTs returned their survey containing demographic, job inse-curity, work exhaustion, job satisfaction, occupational satisfaction, organizational com-mitment, and occupational commitment data. In 2002, 451 out of 1156 (39%) of the MTsreturned their surveys containing demographic, job search, occupation search, alternativejob opportunity, alternative occupation opportunity, intent to leave job, and intent to leaveoccupation data. Due to the national nature of the sample, surveys were mailed to respon-dents’ home addresses in January following the survey year, e.g., in January 2002 for the2001 survey. Surveys answers were matched over time using respondent social securitynumbers.

Across both surveys, based on the variables used in this study, complete data was avail-able for only 233 MTs. Such a reduction in sample size is not uncommon (WineWeld &Tiggerman, 1990). This sample reduction was primarily due to missing data. In addition,respondents who indicated that they had “changed jobs” (e.g., intra-organization transfer)


within the two year period were eliminated. Each year respondents were also asked to writein the name of their organization where they currently worked. If a respondent wrote in adiVerent name for the 2001 versus 2002 survey, he or she was eliminated from the study.Such steps should control for intra-organization and inter-organization work transitions(Louis, 1980) during data collection.

Within this complete data set a 2001 demographic comparison on gender, age, maritalstatus, and education level of the 233 complete-data MT sample to the 268 (501¡ 233)remaining MT sample indicated no signiWcant demographic diVerences. A 2001 demo-graphic breakdown of the sample of 233 MTs showed that: their median age was 33, with arange of 29–63 years old; 82% were women; 95% had a baccalaureate degree, and 5% hadan advanced degree; 66% were married; the mean number of years worked in their particu-lar organization was four, and the mean number of years worked in the laboratory was ten.General population demographics collected by the BOR-ASCP in 2000 on 73, 471 MTsshowed that 82% were female and the median age was 43. Thus this sample studied isrepresentative for gender but is younger.

Using the complete survey respondent sample of 233 MTs, permission was given to con-tact these individuals by the BOR-ASCP, to ask about voluntary organizational and occu-pational turnover in 2003, using their home address information. A very short survey, withreply paid envelop, was mailed to each respondent in January, 2004. Follow-up phone callswere made if needed. Ultimately, complete responses were given by 221 of the 233 MTs.

2.2. Measures (year collected)

Control variables (2001). Primary income source was measured based on a one-item mea-sure, i.e., “are you the primary source of income for your household?”, answered either1Dno, 2D yes. Number of dependent children was measured by asking respondents to indi-cate how many dependent children they had. Organizational (occupational) tenure wasmeasured by asking respondents the number of years each had worked in the organization(laboratory).

Job insecurity (2001) was measured using seven items focusing on the perceived threat ofinvoluntary job loss over projected time ranges, consistent with Sverke et al. (2002). Surveyconstraints prevented using the more comprehensive 57-item Ashford, Lee, and Bobko(1989) measure. Sample items are: “I am concerned that I may lose my job next year,” and“I am concerned that my job will be negatively aVected by my institution’s downsizing inthe next three years.” Unless otherwise noted, all items were responded to using a four-point scale, where 1D strongly disagree, 2Ddisagree, 3Dagree, 4D strongly agree.Research has shown that the proportion of the scale used in a four-point response formatis no diVerent than more common Wve-, six-, and seven-point formats (Matell & Jacoby,1972). For all multi-item scales items were averaged to form scale scores.

Work exhaustion (2001) was measured using a shortened adapted seven-item scalebased on the Gillespie–Numerof Burnout Inventory (Seltzer & Numerof, 1988). Sampleitems included are: “my job has me at the end of my rope,” and “I am unable to get outfrom under my work.” This seven-item scale showed good internal consistency in an ear-lier study (Blau, Tatum, & Ward-Cook, 2003b). A four-point frequency-based responsescale was used, where 1D hardly ever (once every few months or less); 2D rarely (aboutonce a month); 3D sometimes (at least once a week); and 4D frequently (at least once aday).


Job satisfaction (2001) was measured using the Job Diagnostic Survey (Hackman &Oldham, 1975). The fourteen items asked respondents to indicate: “how satisWed they werewith diVerent aspects of their job,” including co-workers, personal growth options, supervi-sion, and salary. Items were responded to using a four-point scale, 1D very dissatisWed,4Dvery satisWed.

Occupational satisfaction (2001) was measured using Wve items adapted from the Wve-item career satisfaction scale by Greenhaus, Parasuraman, and Wormley (1990). Inspectionof the items used by Greenhaus et al. (1990, p.86) suggested that “career” means withinone’s organization, e.g., satisfaction with salary, advancement. Accordingly, all Wve of theitems within Greenhaus et al. (1990) were modiWed to have an occupational referent. Asample item is: “I am satisWed with the success I have achieved in my occupation.”

Organizational commitment (2001) was measured using an adapted version of Meyeret al.’s (1993) six-item measure of aVective organizational commitment (OC). The onlychange made to relevant items was to word them all positively. Some researchers (e.g.,Jackson, Wall, Martin, & Davids, 1993) have argued that using reverse-scored items, tobalance the polarity of items within a scale, can introduce systematic error to a scale. Asample items is: “I feel emotionally attached to this organization.”

Occupational commitment (2001) was also measured using an adapted version of Meyeret al.’s (1993) original six-item aVective occupational commitment scale. In addition to pos-itively wording all items (Jackson et al., 1993), the occupation referent was changed fromnursing (Meyer et al., 1993) to “medical technology.” A sample item is: “I am happy tohave entered the medical technology profession.”

Job search (2002) was measured using two items. A sample item is: “to what extent didyou job search in 2002 in order to leave your current employer.” Similar to Boswell, Boud-reau, and Dunford (2004), a four point response scale was used, where 1Dno extent, 2Dalittle extent, 3D some extent, and 4Dgreat extent.

Occupational search (2002) was also measured using a similar two-item measure.A sample item is: “to what extent did you job search in 2002 in order to leave the medicaltechnology profession.” The same 4-point response scale as with job search was used.

Alternate job opportunities (2002) were measured using a two-item measure adaptedfrom Price and Mueller (1986). A sample item is: “there are alternative jobs available forme if I decide to leave my current job.”

Alternate occupational opportunities (2002) were measured using a two-item measureadapted from Carson et al. (1995) career entrenchment measure. A sample item is: “thereare alternative occupations available for me if I decide to leave my current profession.”

Intent to leave organization (2002) was measured using three items adapted from Blau(2000). A sample item is “I intend to leave this organization as soon as possible.”

Intent to leave occupation (2002) was measured using three items also taken from Blau(2000), e.g., “I intend to leave the medical technology profession as soon as possible.”

Voluntary organizational turnover (2003) was measured using one-item, “did you volun-tarily change organizations, but still remain in medical technology,” and a NoD 1, YesD2response scale was used. Of the 221 respondents, 47 (21%) said they had voluntarilychanged organizations in 2003. To try and ensure that respondents who said “yes” in factdid change organizations, they were asked to write in the name of the new organizationwhere they worked during 2003. This 2003 organization name was compared to the organi-zation name written in 2002, and this data indicated that all 47 did change organizationsbetween 2002 and 2003.


Voluntary occupational turnover was measured for 2003 using one-item, “did you volun-tarily change and leave the medical technology profession during 2003,” and a NoD1,YesD2 response scale was used. Of the 221 respondents, 25 (11%) indicated that they hadchanged professions in 2003. To try and ensure that respondents who said “yes” in fact didchange professions, (either a new occupation or commitment to a degree in a new Weld,Rhodes & Doering, 1983), they were asked to write in what their new job title was. All 25“changers” did, and the new titles included: sales manager, dental student, science teacher,data manager, claims processor, epidemiologist, clinical systems specialist, medical student,and residential manager.

3. Results

3.1. Background

Given the large amount of missing data, an analysis was done to determine if subjectattrition was biasing the study results. Goodman and Blum (1996) have recommendedusing logistic regression because it models the probability of being included in one of tworesponse categories, remaining in or leaving the sample. Results indicated that none of thestudy variables was signiWcantly related to staying in versus leaving the sample.

Means, standard deviations, reliabilities and correlations among study variables arereported in Table 1. Variable means are based on the response scale used for that scale. Allmulti-item scales had internal consistencies (Cronbach alpha) of at least .70 (Nunnally,1978). Correlation results indicate suYcient discriminant validity between correspondingreferents and type of turnover behavior. There are two “measurement issues” inXating thecorrelation of .57 between organizational—occupational turnover, i.e., for the majority ofMTs sampled, there was no movement in either changing organizations or occupations,plus if an employee leaves their occupation they typically leave their present organization.However by deWnition (Louis, 1980), there is a diVerence in these types of turnover.

3.2. Test of hypotheses

Since the two dependent variables, voluntary job and occupational turnover, are eachdichotomous, it is more appropriate to test each hypothesis using logistic regression(Norusis, 1994). Variables will be entered in chronological order, i.e., Wrst 2001, then 2002,for explaining each type of turnover. Closer time proximity of an antecedent to the actualturnover behavior can increase its relationship to the behavior (Mitchell & James, 2001).The logistic regression results for testing H1 are presented in Table 2. Of the 2001 corre-sponding variables entered in Step 1, only job insecurity and job satisfaction were signiW-cantly related to subsequent organizational turnover. Primary income source, number ofdependent children, organizational tenure, and organizational commitment were non-sig-niWcant. For Step 2, 2002 job search and intent to leave organization were signiWcant, butalternate job opportunities were not. These results partially support H1, and 23% of thevariance in organizational turnover was accounted for.

The results are more modest for H2, and are shown in Table 3. For Step 1, of the four 2001corresponding variables entered, only two were signiWcant, work exhaustion and occupa-tional satisfaction. Primary income source, number of dependent children, occupational ten-ure, and occupational commitment each had a non-signiWcant relationship to voluntary

G. B

lau / Journal of Vocational B

ehavior 70 (2007) 135–148143

Table 1

A, not applicable.

12 13 14 15 16 17 18

5)2 (.71)

0 .05 (.72)4 .13 .18 (.71)

1 .17 .05 .04 (.81)

5 .06 .21 .23 .38 (.83)

7 .15 .10 .11 .32 .15 (NA)

1 .06 .18 .15 .10 .24 .57 (NA)

Means, standard deviations, reliabilities and correlations among study variables

Note. N D 228, r > .13, p < .05; r > .17, p < .01. 01 D 2001; 02 D 2002; 03 D 2003, internal consistencies in diagonal; Na Dichotomous variable, 1D No, 2 D Yes, N D 221.

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

1. Primary income source, 01a 1.46 .50 (NA)2. Number of dependent

children, 011.25 1.07 ¡.09 (NA)

3. Organizational tenure, 01 4.02 3.71 .12 .15 (NA)4. Occupational tenure, 01 10.41 6.86 .11 .07 .25 (NA)5. Job insecurity, 01 1.99 .66 .08 .10 ¡.17 ¡.06 (.90)6. Work exhaustion, 01 2.08 .67 .13 .03 .08 .14. .20 (82)7. Job satisfaction, 01 2.84 .53 ¡.07 ¡.08 .13 .09 ¡.28 ¡.20 (.93)8. Organizational

commitment, 012.79 .55 .05 .03 .15 .04 ¡.25 ¡.19 .39 (.88)

9. Occupational satisfaction, 01

2.61 .48 .10 .06 .08 .16 ¡.17 ¡.22 .41 .36 (.81)

10. Occupational commitment, 01

2.73 .51 .11 ¡.02 .06 .18 ¡.14 ¡.20 .31 .38 .45 (.87)

11. Job search, 02 1.66 .74 ¡.05 ¡.04 ¡.15 ¡.05 .27 .19 ¡.35 ¡.26 ¡.11 ¡.12 (.12. Alternate job

opportunities, 021.59 .73 ¡.07 ¡.05 ¡.17 ¡.06 .18 .12 ¡.13 ¡.10 ¡.07 ¡.08 .

13. Occupational search, 02 1.43 .70 ¡.12 ¡.09 ¡.10 ¡.13 .12 .17 ¡.08 ¡.06 ¡.24 ¡.21 .14. Alternate occupation

opportunities, 021.38 .67 .04 ¡.07 ¡.06 ¡.11 .10 .14 ¡.03 ¡.02 ¡.11 ¡.13 .

15. Intent to leave organization, 02

1.88 .62 ¡.08 ¡.10 ¡.15 ¡.08 .22 .16 ¡.30 ¡.27 ¡.07 ¡.06 .

16. Intent to leave occupation, 02

1.53 .59 ¡.11 ¡.12 ¡.06 ¡.13 .15 .21 ¡.20 ¡.15 ¡.31 ¡.29 .

17. Voluntary organizational turnover, 03a

1.21 .38 ¡.02 ¡.03 ¡.10 ¡.04 .22 .18 ¡.29 ¡.25 ¡.14 ¡.12 .

18. Voluntary occupational turnover, 03a

1.11 .40 ¡.04 ¡.08 ¡.05 ¡.12 .14 .21 ¡.12 ¡.11 ¡.22 ¡.19 .

72

20

2

0

1

1


occupational turnover. For Step 2, only 2002 intent to leave occupation was signiWcant, whileoccupational search and alternative occupation opportunities were not. Overall, the resultspartially support H2 and 15% of the variance in occupational turnover was accounted for.

Table 2Hierarchical logistic regression using voluntary organizational turnover as the dependent variablea

Note. N D 221.a Standardized coeYcients for all continuous variables.b 01D 2001, 02 D 2002.¤ < p .05 (two-tailed).

¤¤ p < .01.

Variable Beta Standard error

Step 1Primary income source, 01 ¡.24 .49Number of dependent children, 01 ¡.08 .35Organizational tenure, 01 ¡.10 .28Job insecurity, 01 .20¤ .09Job satisfaction, 01 ¡.30¤ .13Organizational commitment, 01 ¡.22 .15

Step 2Job search, 02 .23¤ .10Alternative job opportunities, 02 .39 .21Intent to leave organization, 02 .45¤¤ .18

¡2 Log likelihood 114.33�2 (9 degrees of freedom) 43.81¤¤

R2 (Cox & Snell) .23Percentage of cases correctly classiWed 88%

Table 3Hierarchical logistic regression using voluntary occupational turnover as the dependent variablea

Note. N D 221.a Standardized coeYcients for all continuous variables.b 01 D 2001; 02D 2002.¤ p < .05 (two-tailed).

¤¤ p < .01.

Variable Beta Standard error

Step 1Primary income source, 01 ¡.18 .39Number of dependent children, 01 ¡.09 .28Occupational tenure, 01 ¡.12 .17Work exhaustion, 01 .23¤ .11Occupational satisfaction, 01 ¡.25¤ .12Occupational commitment, 01 ¡.20 .13

Step 2Occupational search, 02 .21 .15Alternative occupation opportunities, 02 .31 .20Intent to leave occupation, 02 .28¤ .12

¡2 Log likelihood 172.26�2 (9 degrees of freedom) 95.26¤¤

R2 .15Percentage of cases correctly classiWed 82%


4. Discussion

Overall the results of this study support voluntary organizational turnover versusoccupational turnover as separate types of interrole transitions (Louis, 1980). A litera-ture search suggests that this is the Wrst study testing these types of turnover using acorresponding variable set framework for each type of turnover. The results of thestudy are partially supportive of previous voluntary job (organizational) turnover Wnd-ings (Cotton & Tuttle, 1986; GriVeth et al., 2000) in Wnding job insecurity, job satisfac-tion, job search and intent to leave the organization as signiWcant correspondingcorrelates. Study results are consistent with other research Wnding job satisfaction to bea key “driver” of voluntary employee turnover (Hom & Kinicki, 2001). It was disap-pointing not to Wnd organizational commitment to be a signiWcant antecedent. Onestudy limitation was only measuring the aVective dimension of organizational commit-ment, and not also the normative and continuance commitment dimensions (Meyeret al., 1993).

This study is believed to be the Wrst test of the Rhodes and Doering (1983) model usingoccupational turnover data. Prior research has used intent to change/leave career (occupa-tion) as the outcome variable (e.g., Blau et al., 2003a; Carson et al., 1995; Rhodes &Doering, 1993). Additional research design strengths include having a prospective studydesign over a several year period, controlling for intra-organizational transfers, andrespondent organizational stability, as well as behavioral “checks” on the self-reportedturnover data.

Occupational satisfaction also emerged as a signiWcant correlate, suggesting that satis-faction may be an important “driver” variable for both organizational and occupationalturnover. In addition, work exhaustion was found to be signiWcant, consistent with previ-ous qualitative work on career changers (Doering & Rhodes, 1989). Intent to leave occupa-tion was also a signiWcant antecedent of occupational turnover. Across both types ofturnover, signiWcance consistency of the satisfaction and intent variables’ supports a “cor-responding variable set framework” for explaining each type of turnover. Unfortunately,similar to organizational commitment, occupational commitment did not emerge as a sig-niWcant correlate of occupational turnover. Again, only measuring aVective and not thenormative or continuance dimensions for occupational commitment (Meyer et al., 1993)must be noted.

A limited amount of variance was explained for each type of turnover. It can be arguedthat measure “crudeness” (e.g., primary income source) and restricted measure range (e.g.,number of dependent children) contributed to this. Although logistic regression was anappropriate data analytic technique (Norusis, 1994), the improvement in classiWcationaccuracy for organizational turnover was marginal and even less for occupational turn-over. Given the 21% rate of organizational turnover, and the predictive accuracy of 88%with nine variables, this suggests a very modest gain of 9% (21%¡ 12%) using the nine cor-relates studied. The improvement for occupational turnover is worse. An alternateapproach to consider is survival analysis (Mossholder, Settoon, & Henagan, 2005). How-ever, survival analysis would require organizational and occupational turnover data accessover the time period needed.

In addition, the model used was underspeciWed since some relevant variables were notincluded. Unfortunately labor market inXuences such as unemployment rate, along withjob embeddedness, withdrawal expected utility and comparing alternatives were not


measured, and prior research suggests that each variable can be part of the job turnoverprocess (Hom & GriVeth, 1995; Hom & Kinicki, 2001; Mitchell, Holton, Lee, Sablynski,& Erez, 2001). More recent employee organizational turnover research (Mossholderet al., 2005) found that two relational variables, i.e., network centrality or coworker ties,and interpersonal citizenship behavior, were each important impediments to voluntaryemployee turnover. Including at least several of these variables would have probablyincreased the amount of voluntary job turnover variance accounted for. One reason fornot including these variables, aside from survey length constraints, was trying to create“corresponding variable sets” for comparing voluntary job versus occupational turn-over. Comparable scales for occupational: embeddedness, withdrawal expected utilityand comparing alternatives, as well as occupational relational variable scales, awaitdevelopment.

Looking at future research directions, testing the “robustness” of the job insecurity-organizational turnover and work exhaustion-occupational turnover relationshipsfound here using other measures of job insecurity (e.g., Sverke et al., 2002) and workexhaustion (e.g., Schaufeli, Leiter, & Kalimo, 1995) is important. It is important to alsoacknowledge that both types of turnover, job and occupational, were self-report and hadlimited base rates (Adkins, Werbel, & Farh, 2001). Another limitation to acknowledge isthe sample, including its relative homogeneity, i.e., primarily female medical technolo-gists with a bachelor’s degree. In addition, during the time period studied, there was acurrently a shortage of qualiWed laboratory professionals, including MTs, in the UnitedStates (Ward-Cook & Tamar, 2000). As such, this may explain the somewhat lower over-all level of job insecurity indicated by the sample. Such a shortage could be expected toencourage increased voluntary job turnover of MTs. High demand employees are argu-ably in a stronger position to capitalize on their human capital and obtain external jobopportunities (Hom & GriVeth, 1995). In addition, such a labor shortage may also con-tribute to greater work exhaustion in one’s present job situation (Cordes & Dougherty,1993). Therefore, testing the generalizability of the study’s Wndings is important. Theresearch design only allowed for year-long measures to be collected. Individuals maywell use shorter job and occupation search cycles (Steel, 2002), and such cycles may bemore sensitive to explaining a greater amount of voluntary organizational andoccupational turnover. DiVerentiating between passive versus active job (occupational)search may also help to tease out stronger relationships with each type of turnover (Blau,1993).

From a practical perspective, what is important about these results? The higher intent toleave and actual organizational turnover means, versus comparable intent and actual occu-pational turnover variable means, support practitioner Wndings about greater frequency oforganizational turnover (Bolles, 2006). One concern is how an organization can “realisti-cally defuse” job loss insecurity perceptions. Adkins et al. (2001) discuss the importance oforganizations providing timely, accurate and suYcient information about any restructur-ing. The aftermath of any restructuring is important to monitor, including task overloadfor survivors (Cascio, 1993), which may help lead to their work exhaustion. Such exhaus-tion may contribute to not just organizational but occupational turnover. To conclude, it ishoped that the presented Wndings will stimulate additional study comparing the voluntaryorganizational versus occupational turnover processes. Continued study may helpresearchers to understand how people decide whether to engage in one type of turnoverversus the other.


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