Journal of Applied Psychology 2004, Vol. 89, No. 5, 835\u2013 853
Copyright 2004 by the American Psychological Association 0021-9010/04/$12.00 DOI: 10.1037/0021-9010.89.5.835
The Big Five Personality Traits and Individual Job Performance Growt Trajectories in Maintenance and Transitional Job Stages Carl J. Thoresen
Tulane University and Cornerstone Management Resource Systems, Inc.
Paul D. Bliese
U.S. Army Medical Research Unit\u2014Europe, Walter Reed Army Institute of Research
Jill C. Bradley
Tulane University
Joseph D. Thoresen
Cornerstone Management Resource Systems, Inc.
This study extends the literature on personality and job performance through the use of random coefficient modeling to test the validity of the Big Five personality traits in predicting overall sales performance and sales performance trajectories\u2014 or systematic patterns of performance growth\u2014in 2 samples of pharmaceutical sales representatives at maintenance and transitional job stages (K. R. Murphy, 1989). In the maintenance sample, conscientiousness and extraversion were positively associated with between-person differences in total sales, whereas only conscientiousness predicted performance growth. In the transitional sample, agreeableness and openness to experience predicted overall performance differences and performance trends. All effects remained significant with job tenure statistically controlled. Possible explanations for these findings are offered, and theoretical and practical implications of findings are discussed.
Organizational researchers have long been interested in relationIncorrect assumptions about the stability of performance might ships between personality traits and job performance. With the result in erroneous conclusions about personality\u2013performance resurgent interest in trait theories of personality and the \u201cdiscovrelationships. These assumptions could be quite costly to organiery\u201d of the Big Five model of trait structure (e.g., Goldberg, 1990; zations that rely on such research findings to make selection and Tupes & Christal, 1992), research in this area has flourished. training decisions. As noted by Hanges, Schneider, and Niles Authors of personality\u2013performance studies (e.g., Bing & (1990), \u201cEvery personnel decision in organizations is predicated Lounsbury, 2000; Crant, 1995; Judge, Erez, Bono, & Thoresen,on the belief that long-term performance can be pre2002; Stewart, 1999) frequently make the implicit assumptiondicted that . . . .Thus the degree to which performance is stable has performance is a stable construct and thus rely on cross-sectional, direct implications for the accuracy of any personnel decision\u201d (p one-time (as opposed to multiple-time) measures of performance 658). Indeed, if personnel selection decisions are based on a to capture something that by its very nature unfolds across time. In top\u2013down model using trait measures demonstrated to be valid large part, studies of the relationship between personality andpredictors static of performance at a particular point in time and the performance measures have been the norm despite longstanding rank-ordering of individuals on the criterion significantly changes evidence that performance is dynamic (Bass, 1962; Ghiselli, 1956; with time and experience, the utility of such a system likely would Ghiselli & Haire, 1960). be compromised (Deadrick & Madigan, 1990; Henry & Hulin, 1987, 1989; Hulin, Henry, & Noon, 1990). Given the centrality of these two areas of inquiry\u2014the nature of relationships between personality traits and job performance and Carl J. Thoresen, Department of Psychology, Tulane University, and the changing nature of performance across time\u2014it is somewhat Cornerstone Management Resource Systems, Inc., Carnegie, Pennsylvania; Jill C. Bradley, Department of Psychology, Tulane University; Paul D. surprising that more research has not attempted to integrate these two literatures. In fact, authors of recent reviews have pointed to Bliese, U.S. Army Medical Research Unit\u2014Europe, Walter Reed Army Institute of Research; Joseph D. Thoresen, Cornerstone Managementthe Re- need to examine motivational constructs such as personality source Systems, Inc. traits in the context of more sophisticated models of individual We acknowledge Dave Hofmann and several other members of Re- performance change (Steele-Johnson, Osburn, & Pieper, 2000). In search Methods Network (RMNET) for advice concerning data analysis for the current study we attempted to achieve such an integration by our study and are grateful for the assistance of Sally Porter and Mary capitalizing on recent innovations in the measurement of change. Westermann for their clerical and data management assistance. Our thanks In so doing, we drew upon Murphy\u2019s (1989) distinction between also go to Jose\u00b4 Cortina for his insightful contributions. Any errors are ours job performance at maintenance versus transitional job stages. alone. First, Correspondence concerning this article should be addressed to Carl J. we advanced hypotheses concerning different patterns of performance change or growth for employees working in these two Thoresen, Cornerstone Management Resource Systems, Inc., 212 Mary divergent job conditions. Second, we used the familiar Big Five Street, Carnegie, PA 15106. E-mail:
[email protected] 835
836
THORESEN, BRADLEY, BLIESE, AND THORESEN
framework to generate substantive hypotheses about individual mance during maintenance or steady-state stages. That is, once the differences in performance trajectories\u2014which we defined necessary as id- knowledge and skills have been obtained, personality iosyncratic patterns of systematic performance growth across traits a should become key forces in determining job-related behavspecified period of time or a series of performance observa- ior. In support of this reasoning, Keil and Cortina (2001) used tions\u2014at both maintenance and transitional job stages. meta-analysis to demonstrate a temporal deterioration of the validity of general cognitive ability for predicting performance of a Logistics of Performance Change Measurement variety of tasks, with the degree of validity deterioration being greatest for consistent (i.e., easily routinized or automated) tasks than Once performance is conceptualized as a dynamic construct, the for more complex ones. matter of how to measure performance change arises. Devising Although considerable research has been conducted examining correct methods for the study of change is a problem that longcognitive has ability and performance change, relatively little research plagued research in all areas of scientific psychology (Cronbach effort & has been directed at understanding the role of personality Furby, 1970), and the industrial\u2013 organizational field is no and excepdynamic criteria within the context of Murphy\u2019s (1989) maintion (Lance, Vandenberg, & Self, 2000). Fortunately, new statistenance and transitional job stage model. Stewart (1999) found that tical techniques provide sophisticated strategies for answering conscientiousness was positively associated with sales perforquestions about intraindividual performance change. In particular, mance for both maintenance and transitional stage employees. In use of random coefficient modeling (RCM; Bliese & Ployhart, subsequent analyses, Stewart found that the order component of 2002), also known as hierarchical linear modeling (Bryk & conscientiousness was more strongly related to performance for Raudenbush, 1992; Davison, Kwak, Seo, & Choi, 2002; Hofmann, transitional employees, whereas the achievement component was a 1997), has led to great advancements in this area. better predictor of performance for maintenance employees. On One of the primary advantages of RCM is its ability to simul-the basis of these results, Stewart concluded that \u201cwhen the critetaneously estimate within-person (Level 1; L1) and between- rion is dynamic, broad traits such as conscientiousness may be person (Level 2; L2) effects across time. L1 analyses concern appropriate [for selection] because they exhibit robust relationships performance stability and change\u2014specifically, the extent to with the various behaviors that affect success over time\u201d (p. 966). However, because of the cross-sectional nature of his study\u2019 which mean levels of performance for a group of individuals change across a specified period of time. For example, perfor-design, Stewart was unable to explicitly model individual performance may increase or decrease at a linear rate, accelerate ormance trajectories in these two samples as a function of decelerate (evidenced by significant higher order polynomial conscientiousness. terms), or display some combination of these trends (Mitchell & James, 2001; Ployhart & Hakel, 1998; Raudenbush, 2001; Willett Level 1 Predictions & Sayer, 1994). Conversely, L2 analyses address whether individual difference variables (e.g., abilities, personality traits) predict One possible reason that personality traits have rarely been both between-person differences in overall performance across a examined in longitudinal analyses of performance among job specified period of time (L2 intercept parameters; which we refer incumbents at different job stages is that the categorical distinction to from this point forward as mean performance differences) and between maintenance and transitional stages is difficult to operaindividual differences in shapes of performance trajectories\u2014or tionalize. Murphy (1989) argued that people experience transition rates of change\u2014across this specified period (L2 slopes; when Bliese\u201cmajor & duties or responsibilities of a job change\u201d (p. 1 Ployhart, 2002). the abstract, maintenance stages occur when employees have been performing a job long enough to have gained familiarity with task Performance Change and the Job Stage Context requirements, whereas transitional stages are associated with learning and adapting to new task requirements. The most obvious Perhaps nowhere are the issues of individual differences in illustration of a transitional stage involves a shifting of one\u2019s job, or organization. However, it certainly is possible to performance change more salient than in job stage research. occupation, In an experience a transitional stage without leaving one\u2019s job, occupa oft-cited theoretical piece, Murphy (1989) distinguished between maintenance and transitional job stages (see also Deadrick, Ben-tional group, or employer. In practice, there is no hard and fast nett, & Russell, 1997; Dodd, Wollowick, & McNamara, 1970). categorical distinction between the two stages, and judgments concerning maintenance versus transitional-stage status for a given Murphy defined the maintenance stage as a point at which \u201cthe set (or sets) of workers typically require inside knowledge of the worker has learned to perform all major job tasks and is no longer confronted with situations that present novel or unpredictablecontext surrounding data collection, because different job characteristicsamake it nearly impossible to define universal criteria for demands\u201d (p. 190). In contrast, the transitional period involves what constitutes a maintenance versus a transitional stage. stage when \u201cmethods of operation are undefined; the workers must learn new skills and tasks and make decisions about unfamiliar We believe that there are empirical criteria that can help support topics\u201d (p. 190). Thus, some form of change (usually an increase) a priori assumptions about whether a group of employees is in job performance is expected during the transitional job stage as experiencing a maintenance versus transitional job stage. For inworkers familiarize themselves with job-specific demands. stance, if one has reason to believe that a sample of employees is experiencing job transition (e.g., changes in required knowledge or Murphy (1989) originally proposed that cognitive ability would be most highly predictive of performance during transitional task demands), this can be confirmed by examining the perforstages, which require learning of new knowledge and skills. Inmance pattern for that group of employees to see if the pattern is contrast, volitional dispositional factors would predict perfor-consistent with a transitional stage. Conversely, if one has reason
PERSONALITY AND PERFORMANCE TRAJECTORIES
837
to believe that two samples of employees are at different job environments (Hesketh & Neal, 1999). In addition to contrasting stages, one can test this hypothesis by contrasting mean levels differences of in performance trends between employees in mainteperformance across a specified time period in these two groups. nance and transitional job stages, one of our central goals in the Gradual, uniform increases (or complete stability) of performance current study was to examine predictors of individual differences across time would provide indirect evidence of a maintenancein performance both in terms of (a) mean level performance across stage, whereas drastic performance increases would suggestaaspecified period of time and (b) interindividual differences in period of transition. performance growth trajectories during this period. Partly on the basis of Murphy\u2019s (1989) research, we proposed that different Results from several studies provide a useful starting point for identifying performance patterns associated with specific job personality traits may be salient at these two stages. We specifically investigated the usefulness of the Big Five personality traits stages. To illustrate, long-term studies of the relationship between as predictors of mean performance and performance trajectories in job tenure and performance have found an initially positive linear maintenance- and transitional-stage samples of employees. and then plateauing relationship (e.g., Avolio, Waldman, & McDaniel, 1990; Jacobs, Hofmann, & Kriska, 1990; Schmidt, Hunter, & Outerbridge, 1986; for exceptions see Hofmann, Jacobs, & Mean Performance Differences in Maintenance and Gerras, 1992; Russell, 2001). Thus, performance growth appears Transitional Job Stages to be more dramatic in early (transitional) job stages and then tapers off in later (maintenance) job stages. Further supporting Two traits should positively influence mean job performance these conclusions concerning temporal aspects of job performance, levels in both maintenance and transitional job stages. One such Hofmann, Jacobs, and Baratta (1993) found a mean group trend of is conscientiousness. Conscientious persons are dependable, trait linear then plateauing performance over a 3-year period for newly reliable, and achievement oriented, whereas low scorers are carehired insurance sales personnel. It is clear that the initial perforless, lackadaisical, and undependable (Digman, 1990). Metamance measures reflected a transitional phase for the new hires, analytic research has consistently supported conscientiousness as and one might infer that the employees were entering the mainteone of the few personality-based predictors with generalizable nance phase when their performance gains started to decelerate. In across occupations and job situations (Barrick & Mount, validity a similar vein, Ployhart and Hakel (1998) investigated sales per1991; Barrick, Mount, & Judge, 2001; Hurtz & Donovan, 2000; formance over eight consecutive business quarters. These re- Mount & Barrick, 1995; Salgado, 1997), and such research has searchers found support for a classic learning curve indicatedconfirmed by the positive association between conscientiousness and linear, quadratic, and cubic models in which performance in- sales performance as well (Vinchur, Schippmann, Switzer, & creased sharply in initial quarters (positive linear change) andRoth, then 1998). continued to increase, albeit at a decelerated rate (evidenced byA second trait associated with success in sales is extraversion. significant quadratic and cubic terms, respectively). Thus, results Extraverts are characterized by gregariousness, assertiveness, posclearly supported a pattern in which the greatest incremental itive gainsemotionality, activity, and sociability, whereas those low in in performance occurred in the initial stages of the study. In sum, this trait tend to be aloof, timid, and socially withdrawn (Digman, cumulative evidence from these studies suggests that performance 1990). Although the generalizability of extraversion in predicting increases over time; however, the nature of this increase is more performance across all jobs has not been supported in empirical dramatic in earlier observations. On the basis of these results,research we (Barrick & Mount, 1991; Barrick et al., 2001; Hurtz & predicted different patterns of performance for samples of employDonovan, 2000; Mount & Barrick, 1995; Salgado, 1997), this trait ees working in maintenance versus transitional stages. Specifidoes seem to have particular salience for sales effectiveness. In a cally, we hypothesized the following: meta-analysis restricted to the predictors of sales success, Vinchur et al. (1998) found extraversion to be a valid predictor of both Hypothesis 1: The overall performance trend for employees supervisory ratings of sales performance and actual sales volume. identified a priori as being in a maintenance stage will be Stewart, and Piotrowski (2002) found that extraverts were Barrick, positive and linear. motivated to obtain status and rewards at work and subsequently had increased sales. Hypothesis 2: The overall performance trend for employees Because of differences between the maintenance and transiidentified a priori as being in a transitional stage will be tional stages of employment, we also propose that openness to positive and linear but will also show evidence of deceleraexperience is related to performance in the transitional stage but tion via a significant negative quadratic trend. not necessarily in the maintenance stage. Highly open people display intellectual curiosity, creativity, flexible thinking, and culture (Digman, 1990). Most meta-analytic research has failed to Level 2 Predictions support a consistent and positive correlation between openness and job performance across broad occupational categories (Barrick et Regrettably, there is a paucity of research addressing exactly al., 2001), including sales success (Vinchur et al., 1998); however, how individual characteristics influence adaptive (i.e., transitional) Tett, Jackson, and Rothstein (1991) found that openness predicted job performance, or \u201cresponsiveness to changing job demands\u201d performance in a meta-analysis of 10 confirmatory studies that (Hesketh & Neal, 1999, p. 47; see also Pulakos, Arad, Donovan, & specifically hypothesized such a relationship. We propose that Plamondon, 2000). To the extent that novel (i.e., transitional) job openness to experience may be a critical factor for performance environments would seem to constitute weak situations (Mischel, 1977), relationships between personality traits and job perfor-under certain job circumstances. Specifically, we suggest that should be positively related to sales performance during mance may be most evident for employees embedded in novelopenness job
838
THORESEN, BRADLEY, BLIESE, AND THORESEN
transitional employment periods because in this stage, an em-ated with both initial growth and later plateauing, providing some ployee will benefit from adaptability and flexibility characterizing evidence for individual differences as predictors of performance openness (Goldberg, 1990). Results from a handful of experimengrowth patterns. Finally, Russell (2001) tested whether individual tal and field studies support this assertion. Using an undergraduate differences in managerial competencies could predict performance sample, LePine, Colquitt, and Erez (2000) found that openness growth curves of top-level executives. Results indicated that rehelped participants adapt to changing task demands in a computsource problem-solving-oriented competencies predicted initial pererized decision-making study. Highly open subjects were better formance and that people-oriented competencies predicted later able to adapt their decision-making and problem-solving heuristics performance growth. to changing situational cues. In a field setting of managerial We propose that certain traits are related to individual differsuccess, Judge, Thoresen, Pucik, and Welbourne (1999) foundences that in intraindividual performance patterns, although research in openness was positively related to managers’ ability to cope with this area admittedly is scant. Conscientiousness—the trait most various organizational changes, such as mergers, acquisitions, strongly and consistently related to performance—should predict downsizing, and the like. not only mean performance but also performance growth. BehavTaken together, these results suggest that openness to experiioral correlates of this trait include the use of self-regulatory tactics ence should foster effective performance at the transitional job such as autonomous goal setting (Barrick, Mount, & Strauss, 1993) stage. Because of their increased ability for flexible thinking, as and time management (Macan, 1994) as well as the ability to cope well as their preference for novel stimuli, open salespeople should with stress (Watson & Hubbard, 1996). Thus, we predict that the be more effective during times of job change. Thus, as with performance of conscientious persons will reflect continuous imconscientiousness and extraversion, openness to experience should provement, although this effect may take some time to manifest be positively associated with sales for transitional stage employitself. In support of this view, Helmreich, Sawin, and Carsrud ees. We made the following hypotheses: (1986) found that the trait work orientation (which is very similar conceptually to conscientiousness) demonstrated a stronger relaHypothesis 3: Conscientiousness will be positively related to tionship with performance after several months on the job (e.g., mean performance differences in the maintenance sample. when incumbents likely had moved from a transitional to a mainHypothesis 4: Extraversion will be positively related to mean tenance period) than with an initial “honeymoon period” measure performance differences in the maintenance sample. of performance taken shortly posthire, when motivation should be high among all new employees. Hypothesis 5: Conscientiousness will be positively related to With respect to the differential predictions for mean performance trajectories within maintenance versus transitional employmean performance differences in the transitional sample. ees, we expected a slightly different relationship between consciHypothesis 6: Extraversion will be positively related to mean entiousness and performance growth. Conscientiousness should be performance differences in the transitional sample. positively correlated with linear performance growth in the maintenance sample, reflecting the desire for continuous performance Hypothesis 7: Openness to experience will be positively improvement for conscientious persons in the steady-state sample. related to mean performance differences in the transitional In the transitional sample, we would expect this same tendency to sample. be manifested by a negative relationship between conscientiousness and negative quadratic growth. In other words, the perforPrediction of Performance Trajectories in Maintenance mance of conscientious persons should be less likely to peak with movement from the transitional or honeymoon period to a time and Transitional Job Stages when job-related duties have become somewhat routinized. Hence, The prediction of performance trajectories (slopes) is somewhat we offered the following hypotheses: more complex. A handful of investigators have studied such relationships in an exploratory manner (e.g., Ployhart & Hakel, 1998) Hypothesis 8: Conscientiousness will be positively related to or have used characteristics such as general cognitive ability and positive linear growth in performance within the maintenance job tenure to forecast performance change (e.g., Deadrick et al., sample. 1997). However, we are aware of no longitudinal research directly contrasting the validities of various personality traits within the Hypothesis 9: Conscientiousness will be negatively related to context of maintenance and transitional stages. Deadrick et al. negative quadratic growth in performance within the transi(1997) found that both job experience and psychomotor ability tional sample. were positively associated with initial individual job performance in a sample of sewing machine operators. Additionally, general In addition to conscientiousness, past personality–performance mental ability was positively correlated with performance in- research suggests that openness to experience should relate to performance trajectories for people in transitional job stages. Becreases, whereas previous job experience was negatively related to positive performance trends for individuals. In addition, Ployhart cause openness has been shown to relate positively to effectiveness and Hakel (1998) found that individual differences in trait empathy under changing conditions requiring adaptive performance (e.g., were positively and negatively associated with individual differJudge et al., 1999; LePine et al., 2000), people high in openness ences in initial performance increases (linear growth) and subseshould show steady performance gains initially (i.e., a positive quent performance plateauing (quadratic growth), respectively. linear trend). This prediction is consistent with results obtained by Furthermore, a trait measure of persuasion was positively associRussell (2001), who found that resource-oriented problem solv-
PERSONALITY AND PERFORMANCE TRAJECTORIES
839
relationship between previous individual job performance and reassigning—an employee competency conceptually similar to the flexible ment to the product launch project, as this decision was made at the group thinking and problem-solving ability characteristic of highly open level (i.e., salespeople working in primary care were shifted to the new individuals (Goldberg, 1990)—predicted initial performance of assignment regardless of their previous levels of effectiveness). This is a newly promoted executives. However, as the novelty of the trancritical point, as nonrandom assignment of individuals to the transitional sitional stage fades as people encounter relatively fewer novel job sample (e.g., highly conscientious persons or persons with a history of situations, we would expect openness to be less critical for peroutstanding performance) could complicate the interpretation of our study formance, although we certainly would not expect that openness results. would be a hindrance at this point. Thus, we hypothesized the Changes experienced by this group constituted entry into a transitional following: phase for at least two reasons. First, transitional sample employees were required to focus exclusively on the marketing of one particular product
Hypothesis 10: Openness will be positively related to positive and hence were shifting to a specialty area. This change required mastering
linear performance growth in performance within the atransigreat deal of technical information regarding issues such as the physiological mechanisms by which the product had been found to effectively tional sample.
treat the condition for which it is prescribed, indications for the product, potential interactions with other drugs, and so forth. Because the product Method was new, this was novel information for transitional participants. The company provided participants with extensive technical training in these Participants and Procedure areas, and each individual salesperson was required to pass a job knowlMaintenance sample. The population of interest to the maintenanceedge examination covering these areas. Individuals who failed to pass this stage study consisted of 137 sales representatives employed by a large examination on the first try were subsequently retested until a previously pharmaceutical firm headquartered in the United States. Primary jobspecified relevel of declarative knowledge was reached. sponsibilities for this position include duties such as gaining access to Second, employees assigned to the product launch were required to potential client physicians, detailing or educating physicians as to thesolicit business from an entirely new client base. Specifically, individual indications for particular products, and strategic targeting of high-potential salespeople had to shift their focus from calling on general practitioners to client physicians in one’s sales territory. Survey materials were sent to the specialists in obstetrics and gynecology (ob/gyn). An organizational rephomes of all potential respondents as part of a large, company-wide study resentative confirmed that there was little if any overlap for the transitional of relationships between personality traits, job attitudes, and sales perforsample in terms of their previous versus new client bases. Thus, to achieve mance. These surveys were accompanied by a letter from the primarysuccess, sales representatives had to strategically target potentially highinvestigator explaining the purpose of the study, along with a similar letter prescribing ob/gyn specialists (in part on the basis of information concernon company letterhead from an organizational representative indicating ing prescription history of similar competitor products, as provided by the that although purely voluntary, participation in the study could provide the research group within the organization), and “get a foot in the door” in organization with useful information regarding factors that influencegaining sales access to these individuals. The potential frustrations due to shortsuccess. term setbacks inherent in the sales occupation (Corr & Gray, 1995) are A total of 99 complete responses were received in the maintenanceparticularly salient here, as initial efforts to influence ob/gyn specialists to sample, for a response rate of 72.2%. The mean age of respondents was change their prescribing habits (i.e., switch from familiar products to the 41.76 years (SD 9.51), and respondents reported a mean job tenurenew of medication) were likely to meet with failure. Furthermore, given the 11.11 years (SD 9.45). A majority (61.6%) of respondents were men, importance of return business, it was necessary for participants in the and 38.4% were women. A company representative confirmed that these transitional sample to establish interpersonal credibility and long-term, figures were roughly characteristic of the demographic makeup of this professional business relationships with this new set of potential clients. particular population. Although the two issues discussed here may not constitute an exhaustive Transitional sample. The population of interest for the transitional list of the changes experienced by the transitional group, we believe that sample was 78 sales representatives employed by the same organization they provide a sufficient basis for inferring that these persons were entering involved in a product launch of a new medication. There was no overlap of a transitional job stage at the time of reassignment to the product launch. participants between the maintenance and transitional samples. The procedure used in the transitional sample was identical to that used in the Measures maintenance sample. We received a total of 48 responses from the transiThe Big Five traits. The Big Five traits were assessed using the tional group (response rate 61.5%). Mean age for respondents was 36.77 years (SD 7.79), and mean job tenure was 7.92 years (SD 7.51 years). 12-item scales from the NEO-FFI (Costa & McCrae, 1992) in both the A slight majority (52.1%) of respondents from the transitional samplemaintenance were and transitional samples. This measure has been shown to women, and 47.9% were men. Again, these figures appeared to matchpredict the job performance in numerous organizational field studies (Costa, profile of the population from which the transitional sample was drawn, as All responses were scored on a 9-point scale with response options 1996). confirmed by a company representative. ranging from 0 (strongly disagree) to 8 (strongly agree).1 Internal consistency (coefficient alpha) reliabilities for the Big Five traits obtained in the The validity of our study hinges on the difference in job responsibilities between the maintenance and transitional samples—that in fact, the current study were as follows: emotional stability ( .80 in the maintenance sample, .87 in the transitional sample), extraversion ( .79 changes experienced by the latter truly were transitional in nature. This maintenance, .83 transitional), openness to experience ( .69 issue deserves some further comment. All members of our transitional maintenance, .62 transitional), agreeableness ( .72 maintenance, sample had previously been working in the primary care area, focusing on marketing a variety of products (similar to those carried out by participants in the maintenance sample) to general practitioner physicians. On the basis 1 This format represents a change to the original NEO-FFI format, which of a corporate-wide decision, members of the primary care sales force were reassigned to a new product launch involving the marketing of a hormone uses a 5-point scale. As the NEO-FFI was administered with a number of replacement therapy product. Thus, participation in the product launch waspersonality and attitude measures (not related to the current study) in other not voluntary for this sample of employees. Employee compensation was our surveys, we felt it necessary to adopt a common format for all of these directly correlated with sales of the new product. There was no systematic measures to avoid confusing respondents (Mattell & Jacoby, 1971).
840
THORESEN, BRADLEY, BLIESE, AND THORESEN
.71 transitional), and conscientiousness ( .88 maintenance,Analyses .78 transitional). The reliability values obtained for openness to experience Power analyses. Because of the different number of participants in the were somewhat lower than those reported in the NEO-FFI manual (Costa maintenance and transitional samples, as well as the modest sample size in & McCrae, 1992), although the reason for this difference was unclear. the latter, we sought to estimate the relative power for analyses in the two Control variables. Although we offered hypotheses concerning only groups. Power analyses in random coefficient models are complex. Althree of the Big Five traits (conscientiousness, extraversion, and openness though exact methods have been developed for power analyses of discrete to experience), we included the remaining two traits in all estimated models predictors, Raudenbush and Xiao-Feng (2001) noted that approximations for two reasons. First, it is well established that the Big Five traits are not are possible in cases in which explanatory variables are continuous (e.g., entirely orthogonal (Digman, 1997). Thus, for us to determine the traits, job tenure). For these analyses, we used the PINT computer program independent contribution of conscientiousness, extraversion, and open(Snijders & Bosker, 1999) to estimate the relative power between a sample ness to experience as predictors of growth parameters (L2 intercept and with 99 respondents and four time periods and a sample with 48 responslope terms), we felt it necessary to include the remaining traits (emo-dents and four time periods. tional stability and agreeableness) in all of the relevant models. Second,In the comparative power analysis, we assumed that personality would as so few studies have incorporated a temporal perspective to the have a direct and cross-level effect size (in a correlation metric) of .30. We prediction of performance from personality traits, we felt that the chose this value because a validity coefficient of .30 corresponds to a inclusion of these dimensions could provide valuable exploratory practically significant effect for a given trait in a selection context and is information. consistent with meta-analytic research estimating the size of associations Job tenure was used as a control variable in all subsequent RCM between traits such as conscientiousness and extraversion and sales performance (e.g., Mount & Barrick, 1995; Vinchur et al., 1998). Given a analyses. Although we offered no formal hypotheses concerning the relasample size of 99 in the maintenance sample and a conservative two-tailed tionships between job tenure and performance growth parameters, we test of statistical significance, power was estimated at .99 for both the included this variable for three reasons. First, past meta-analytic research direct and cross-level effects. Using the same parameters in the transitional has revealed moderate positive relationships between measures of job sample with a sample size of 48 resulted in a power estimate of .89. tenure and work experience and job performance (Hunter & Hunter, 1984; RCM analyses. We tested random coefficient models examining the McDaniel, Schmidt, & Hunter, 1988a, 1988b; Quin˜ ones, Ford, & nature of relationships between the Big Five traits, job tenure, mean sales Teachout, 1995), with the magnitude of the relationship decreasing with increasing levels of job tenure (McDaniel et al., 1988b). Second, the performance levels, and performance trajectories by using Bliese and Ployhart’s (2002) six-step model estimation procedure. To test hypotheses potentially complex nature of relations between work experience and job of interest to the current study, we estimated random coefficient models performance trajectories is worthy of further investigation in its own right. separately for the maintenance and transitional samples. All analyses were In a rare study of this type, Deadrick et al. (1997) found that previous work conducted using the Nonlinear and Linear Mixed Effects program (Pinexperience was positively related to mean levels (i.e., intercepts) of job heiro & Bates, 2000) in the statistical package R (Bliese & Ployhart, 2002). performance— but negatively related to subsequent performance increases Step 1 of the procedure involves estimating the intraclass correlation (slopes)—in a sample of sewing machine operators. Likewise, Tesluk and coefficient (ICC1) for the criterion measure. In our context, ICC1 indicates Jacobs (1998) have posited that the benefits of job tenure may be negated how much variability in quarterly sales (i.e., among 396 and 192 individual by transitional job environments in which the stimuli one encounters bear observations in the maintenance and transitional samples, respectively) can little similarity to past work experiences. Third, failing to control for tenure be attributed to between-person differences across the 4 quarters studied could result in upwardly biased estimates of personality–performance(Bryk & Raudenbush, 1992). Step 2 involves estimating the nature and relationships if levels of the Big Five traits were substantially correlated shape of the time–performance relationship through the use of orthogonal with job tenure in our samples and if tenure were related to performance. polynomial terms (e.g., linear, quadratic, cubic). Each polynomial term This possibility is indirectly supported by research demonstrating robust reflects a change in the direction of performance change for the sample as relationships between traits (in particular, conscientiousness) and voluntary a whole (Hypotheses 1–2). Step 3 involves testing for significant variability turnover (Barrick & Mount, 1996; Barrick, Mount, & Strauss, 1994; across persons in intercepts (mean level differences in performance, as suggested by Hypotheses 3–7). This step also tests for individual differSalgado, 2002). Job performance. We used results-oriented (i.e., hard sales) criteria toences in the slopes of time–performance relationships (Hypotheses 8 –10). As Bliese and Ployhart (2002) noted, tests for intercept and slope differoperationalize job performance for both the maintenance and transitional ences are based on a log-likelihood ratio test contrasting models with and samples. In the maintenance sample, the outcome measure was a simple without random effects (see also Pinheiro & Bates, 2000). In Step 3, count of territory sales aggregated on a quarterly basis (November 1998 – separate tests are performed for all relevant higher order polynomial terms January 1999, February 1999–April 1999, May 1999–July 1999, and (e.g., linear, quadratic, cubic) to specifically determine potential sources of August 1999 –October 1999) such that performance was assessed at four between-person slope variability. points in time (99 persons 4 396 observations). In the transitional Step 4 involves estimating the structure of errors (autocorrelation, hetsample, performance was operationalized as quarterly product market share eroskedasticity) in the criterion measure. Accounting for correlated errors (raw sales divided by all sales in the given product class for each individual and nonconstant variance is critical in random coefficient models for salesperson’s territory) because of large differences in market size for deriving accurate standard errors for estimated parameters in estimating the products carried by this sample. Although the scaling of the criterion L1 solution (DeShon, Ployhart, & Sacco, 1998). Results from tests of error measure was not strictly equivalent across samples, we do not see anystructures at Step 4 provide parameter estimates for the final L1 solution. reason to believe that raw versus market-adjusted sales figures differ On from the basis of the final L1 model, one can also estimate a pseudo- R2 a construct perspective, and such market size adjustments are frequent in statistic to determine the extent to which a model specifying higher order studies of sales success (see Cravens & Woodruff, 1973; Lucas, Weinberg, growth terms explains variance in the criterion variable for the entire & Clowes, 1975; McManus & Brown, 1995; and Ryans & Weinberg, 1979, sample by comparing residual variances for the relevant parameter estifor in-depth discussions of this issue). Market share data were available for in the final model with the same estimates from a model specifying mates the same 4 consecutive business quarters in the transitional sample asonly for random variation in the criterion measure (Bryk & Raudenbush, 1992; the maintenance group, coinciding with the month of the product launch in Hofmann, 1997; Snijders & Bosker, 1994). Step 5 involves accounting for the former sample (48 persons 4 192 observations). between-person differences in intercepts—or mean sales performance
841
PERSONALITY AND PERFORMANCE TRAJECTORIES
across the 4 quarters studied— using scores from predictor variables Maintenance (e.g., Sample Big Five traits, job tenure, as indicated by Hypotheses 3–7). Finally, Step 6 adds tests for cross-level interactions by estimating the extent to which For the maintenance group (the upper diagonal of Table 1), individual-level predictors account for between-person differences inrank-order slope performance appeared to be highly stable across the 4 parameters (i.e., growth trajectories) for time–performance relationships quarters (Quarter 1–Quarter 4). Correlations ranged from .84 ( p (Hypotheses 8 –10). Thus, Step 6 contains estimates for the final L2 model. .01) between Quarter 1 and Quarter 4 to .96 ( p .01) between Again, a pseudo-R2 can be computed to determine the extent to which Quarter 1 and Quarter 2. Thus, although these correlations do not predictor variables account for between-person variance in L2 intercept show the degree of rank-order instability found in some previous and slope terms (Bryk & Raudenbush, 1992; Hofmann, 1997; Snijders & longitudinal performance studies (e.g., Ployhart & Hakel, 1998), Bosker, 1994).
there is at least some evidence of a simplex pattern of correlations. In addition, there is evidence of changes in performance across Results time in the sample as a whole, with pronounced increases in mean sales between Quarter 1 and Quarter 2, t(98) 10.86 p .001, Comparability of Maintenance and Transitional Samples and Quarter 3 and Quarter 4, t(98) 9.00, p .001. An examination of bivariate associations displayed in Table 1 reveals a As discussed previously, we felt it critical to establish the rough consistent correlation between job tenure and sales, ranging from equivalence of the maintenance and transitional samples in terms of the predictor variables of interest to our study (the Big Five .23 ( p .05) for Quarter 4 to .33 ( p .01) at Quarter 1. As conscientiousness predicted performance, with correlatraits, job tenure). Descriptive statistics and intercorrelationsexpected, for all variables in both samples are shown in Table 1. As indicated bytions ranging from .21 ( p .05) for Quarter 3 to .28 ( p .01) at Quarter 1. Extraversion was positively associated with perforTable 1, the two groups appeared virtually identical with respect to mance at Quarter 1 (r .24, p .05) and Quarter 2 (r .23, p the Big Five traits, and two-tailed t tests for differences between .05), means for the maintenance versus transitional samples revealed nobut the relationships between extraversion and performance marginal at Quarter 3 (r .18, p .10) and Quarter 4 (r differences at the .05 level of significance. Results did indicatewere a mean difference in job tenure between the two samples of 3.18.19, p .10). No other traits were significantly correlated with years, t(145) 2.04, p .05. However, the direction of this sales performance at any time period in the maintenance group. difference was such that tenure was higher in the maintenance than RCM results for the maintenance sample are presented in Table the transitional group. If anything, these results confirm the ten2. Results for Step 1 provide strong confirmation of reliable person dency of the maintenance sample to be employed in a steady-state effects on sales performance (ICC1 .83). At Step 2, L1 results job situation, although the average job tenure for the transitional reveal a positive, linear trend in performance across the four time sample (nearly 8 years) was still quite substantial. periods and thus support Hypothesis 1. However, a visual inspec-
Table 1
Means, Standard Deviations, and Intercorrelations for Variables From Maintenance and Transitional Stage Samples Variable 1. Job tenure (years)
M
11.11 7.92 2. Emotional stability 68.71 66.85 3. Extraversion 70.63 71.42 4. Openness to experience 53.44 51.86 5. Agreeableness 67.67 67.00 6. Conscientiousness 76.73 76.81 7. Sales (Quarter 1) 1101.66 2.10 8. Sales (Quarter 2) 1324.71 4.91 9. Sales (Quarter 3) 1280.36 7.26 10. Sales (Quarter 4) 1499.08 9.39 Note.
SD
1
2
9.45 7.51 13.16 15.43 10.83 11.74 11.42 10.53 10.73 10.15 12.21 9.93 520.97 1.20 631.22 2.27 539.73 2.89 681.38 3.50
— —
.08
.11
.80 .87
.00
3
4
5
6
7
8
9
10
.06
.03
.07
.13
.33
.30
.28
.23
.49
.03
.27
.40
.13
.12
.10
.11
.45
.79 .83
.09
.47
.36
.24
.23
.18
.19
.16
.05
.13
.69 .62
.04
.31
.49
.03
.30
.57
.34
.13
.02
.23
.02
.02
.03
.01
.00
.05
.02
.32
.04
.02
.23
.88 .78
.27
.28
.21
.25
.25
.38
.14
— —
.96
.90
.84
.93
.90 .95
.10
.72 .71
.14
.15
.01
.17
.30
.34
.12
.94
— —
.12
.07
.20
.26
.34
.08
.91
.96
— —
.12
.12
.19
.17
.33
.06
.89
.93
.97
— —
Correlations for the maintenance sample are shown in upper portion of the diagonal. Correlations for the transitional sample are shown in lower portion of the diagonal. For means, standard deviations, and internal consistency (coefficients alpha) reliability estimates, the top number refers to th maintenance sample, and the bottom number refers to the transitional sample. Means and standard deviations for NEO–FFI scales are based on sum scores from a 9-point scale. Sales data for the maintenance sample represent raw sales volume. Sales data for the transitional sample represent perc market share. For maintenance sample, p .01 at r .26; p .05 at r .21; p .10 at r .18 for two-tailed tests. For the transitional sample p .01 at r .38; p .05 at r .31; p .10 at r .25 for two-tailed tests.
842
THORESEN, BRADLEY, BLIESE, AND THORESEN
Table 2
Random Coefficient Models Predicting Quarterly Sales in Maintenance Stage Sample Model and parameter Final Level 1 model Intercept
Parameter estimate
SE
95% CI lower bound
95% CI upper bound
t
1189.134 2020.775 248.449 872.120
1413.770 3087.188 205.332 1488.253
22.71*** 9.39*** 0.18 7.51***
1301.452 2553.981 21.558 1180.187
57.305 272.044 115.761 157.177
16.129 2.719 12.418 0.709 9.245 10.472
5.787 4.924 6.339 4.850 5.806 5.142
4.787 12.370 0.007 10.215 20.625 0.394
27.471 6.932 24.842 8.797 2.135 20.550
2.79** 0.55 1.96† 0.15 1.59 2.04*
Job Tenure Linear (slope) Emotional Stability Linear (slope) Extraversion Linear (slope) Openness to Experience Linear (slope) Agreeableness Linear (slope)
19.385 2.048 9.427 11.465 10.238 10.342
30.004 25.532 32.869 25.147 30.105 26.660
78.193 47.994 73.849 37.823 69.242 41.912
39.424 52.091 54.996 60.753 48.767 62.596
0.64 0.08 0.28 0.46 0.34 0.39
Job tenure Quadratic (slope) Emotional Stability Quadratic (slope) Extraversion Quadratic (slope) Openness to Experience Quadratic (slope) Agreeableness Quadratic (slope) Conscientiousness Quadratic (slope)
7.803 5.410 10.820 5.277 24.354 3.313
12.455 10.598 13.644 10.438 12.496 11.067
32.214 15.362 37.562 15.182 0.139 18.377
16.608 26.183 15.922 25.737 48.847 25.004
0.62 0.51 0.79 0.51 1.95† 0.30
Job tenure Cubic (slope) Emotional Stability Cubic (slope) Extraversion Cubic (slope) Openness to Experience Cubic (slope) Agreeableness Cubic (slope) Conscientiousness Cubic (slope)
19.639 12.657 21.956 4.252 4.660 35.602
16.216 13.799 17.764 13.591 16.270 14.409
12.145 39.703 12.862 30.891 27.230 7.361
51.422 14.389 56.774 22.386 36.550 63.844
1.21 0.92 1.24 0.31 0.29 2.47*
Linear trend
Quadratic trend Cubic trend Final Level 2 model Job tenure (intercept) Emotional stability (intercept) Extraversion (intercept)
Openness to experience (intercept) Agreeableness (intercept)
Conscientiousness (intercept)
Conscientiousness
Linear (slope)
Note.
For all Level 1 parameter estimates, df 294: for parameters predicting intercept variation in Level 2 analyses, df 92: for cross-level interaction parameters in Level 2 analyses, df 276. For the sake of clarity, hypothesized effects are italicized. CI confidence interval. † p .10. * p .05. ** p .01. *** p .001.
tion of our data (as well as a critical examination of descriptivestudied) and slope parameters (growth trajectories). Not surprisstatistics from Table 1) reveals a large increase in performance ingly, allowing intercepts to vary significantly improved the fit of between Quarter 1 and Quarter 2, relative stability of performance our model, 2 diff(1) 402.73, p .001. The fit of the model was between Quarter 2 and Quarter 3, and another large increase further improved by allowing between-person variation in the 2 between Quarter 3 and Quarter 4. In an attempt to model these linear slope parameter, (2) 75.15, p .001, was unaffected diff marked group-level changes, we reestimated L1 models to include by allowing between-person variation in the quadratic slope palinear, quadratic, and cubic growth terms in an exploratory fashion. rameter, 2 diff(5) 5.42, ns, and was significantly improved by The inclusion of both quadratic and cubic growth terms is consisallowing between-person variation in the cubic slope parameter, 2 tent with previous studies modeling sales performance growthdiff (9) 61.61, p .001. Taken together, these results suggest (e.g., Ployhart & Hakel, 1998). Results fail to support a statistically considerable individual variability in overall performance levels significant quadratic effect but do support positive cubic growth. and growth trajectories. Although we did not hypothesize such a trend, we included this Next (in Step 4), we sought to determine if the fit of our positive cubic increase in sample mean quarterly performancemaintenance in sample model could be improved through modeling subsequent models to determine if personality traits (in particular, within-person error structures. The results fail to support the pres2 extraversion and conscientiousness) might be associated withence in- of autocorrelation, (1) 0.02, ns, or heteroskedasticity, diff 2 dividual differences in this later performance increase. Although 0.00, ns, in the maintenance sample data; hence, sub diff (1) the quadratic growth term was nonsignificant, we retained it in sequent models excluded these error term specifications. Final subsequent analyses to preserve the scaling of the criterion estimates for the final L1 model are shown in Table 2. Included are variable. parameter estimates, estimated standard errors, 95% confidence intervals for estimated parameters, and corresponding t statistics. Step 3 analyses involved testing for significant between-person The upper diagonal of Table 3 displays correlations between differences in intercepts (mean performance across the 4 quarters
PERSONALITY AND PERFORMANCE TRAJECTORIES
843
linear performance increases, as well as the lack of significant quadratic trend effects at L1, the model failed to account for Correlations Between Growth Terms in Maintenance and significant variance in linear or quadratic growth.2 Transitional Samples Given the unexpected finding concerning the relationship beVariable 1 2 3 4 tween conscientiousness and positive cubic growth, we sought to determine the exact form of this interaction. The complexity of the 1. Intercept (mean Conscientiousness Time interaction is revealed in Figure 1, performance) — .34*** .03 .76*** 2. Linear growth .94*** — .55*** .09 which uses the final L2 model parameters to estimate predicted 3. Quadratic growth .54*** — .01 .30* performance in each of the 4 quarters for persons high (one 4. Cubic growth standard deviation above the sample mean) and low (one standard Note. For maintenance sample (upper diagonal), n 99; for transitional deviation below the sample mean) on conscientiousness, consample (lower diagonal), n 48. As no cubic term is included in the trasted with predicted performance at each quarter for persons transitional sample model, no correlations are shown for the cubic growth scoring at the sample mean on conscientiousness (Bliese & Ployterm. hart, 2002). Values for job tenure and the remaining traits were * p .05. *** p .001. held constant at their respective sample means in these contrasts. The effect of conscientiousness in predicting mean performance across time was reflected in the average performance difference higher order growth terms. Of particular interest are positive between high- and low-conscientiousness persons across the 4 relationships between mean sales and both linear (r .34, p quarters, which is relatively constant once sample mean differ.001) and cubic (r .76, p .001) sales growth. These results ences in predicted performance are taken into account. A closer examination of Figure 1 shows a slightly steeper slope for high indicate that effective performers (in terms of mean sales across conscientiousness persons between Quarter 1 and Quarter 2 than the 4-quarter period) were also likely to increase their performance between Quarter 1 and Quarter 2 and between Quarter 3 and for their low conscientiousness counterparts, and the same pattern is observed between Quarter 3 and Quarter 4, capturing the sigQuarter 4. As shown in Table 4, the final L1 model accounted for nificant association between conscientiousness and positive cubic 41% of the reliable within-person variance in sales performance growth. across the 4-quarter period for this group. Table 2 also shows the L2 solution for the maintenance sample. The first set of terms listed represents predictors of individual Transitional Sample intercept terms, or in this case, predictors of mean level sales performance differences (Step 5; Hypotheses 3– 4). Recall that all Descriptive statistics and intercorrelations for all transitional trait effects are conditional on job tenure. Clear support was found sample variables are shown in the upper diagonal of Table 1. for Hypothesis 3 (conscientiousness and mean level performance), Again, we observed strong evidence for rank-order stability across and marginal support ( p .10) was obtained for Hypothesis 4 the 4 quarters studied (Quarter 1–Quarter 4) in this sample, with (extraversion and mean level performance). Job tenure also was correlations ranging from .89 ( p .001; Quarter 1–Quarter 4) to positively associated with individual performance intercepts. .97 Tests ( p .001; Quarter 3–Quarter 4), and there was evidence of a for individual differences in growth parameters as a function of the simplex pattern to these associations. As shown in Table 1, slight traits and job tenure are captured in the cross-level interaction there was strong evidence of mean performance increases between terms shown in Table 2. The full L2 model shows cross-level Quarter 1 and Quarter 2, t(47) 16.13, p .001; Quarter 2 and interaction terms for the linear, quadratic, and cubic trends inQuarter the 3, t(47) 17.63, p .001; and Quarter 3 and Quarter 4, data. Hypothesis 8 stated that conscientiousness should be posit(47) 15.26, p .001. This dramatic pattern of performance tively related to continuous performance change in the maintegrowth reaffirmed our expectation that this sample truly was in a nance sample, which is evidenced by a positive association be-transitional period in contrast with the maintenance group. In a tween this trait and the linear growth term. Although this relative sense, sales performance increased by 134% in the tranhypothesis was not strictly supported with respect to the linear sitional sample between Quarter 1 and Quarter 2 (compared with term, conscientiousness was positively associated with the cubic a 20% increase between the same two quarters for the maintenance term, providing some support for the general tendency of conscigroup), increased by another 49% between Quarter 2 and Quarter entiousness to predict positive job performance trends in the main3 (in contrast to a slight performance decline of 3% in the maintenance sample. The results also reveal a nonsignificant ( p .10), positive association between agreeableness and negative quadratic 2 In computing pseudo-R2 statistics, we actually encountered negative growth. However, given the nonsignificance of the quadratic term estimates for the linear and quadratic terms at L2, evidenced by the (which was retained to preserve scaling) at L1, this result likely increase in variance for the linear term when the predictor variables were was a statistical artifact. added (see Table 4). As suggested by Snijders and Bosker (1994, p. 343), Table 4 shows the percentage of variance in between-person this is a common occurrence in growth-based random coefficient models in differences in both intercepts accounted for by the differences in which L1 predictors (linear and cubic growth functions in this case) are not levels of predictor variables. Predictor variables in the final L2 expected to vary at L2. This suggestion is consistent with our result that no model accounted for 13% of the between-person variance in perpredictor variables were significantly (at p .05) associated with individformance intercepts (mean performance differences) along with ual differences in linear or quadratic growth in the maintenance sample. 10% of the between-person variance in cubic slopes, across the 4 that pseudo-R2 values represent mere approximations in random Given quarters studied. Because of the lack of significant predictorscoefficient of models, we assumed an R2 value of .00 in these cases. Table 3
844
THORESEN, BRADLEY, BLIESE, AND THORESEN
Table 4
Variance Accounted for in Final Level 1 and Level 2 Models for Maintenance Sample Model description
Observed variance
Level 1 Unconditional on time trends Conditional on linear and cubic trends Level 2 intercept differences Unconditional on Big Five traits and job tenure Conditional on Big Five traits and job tenure Level 2 linear slope differences Unconditional on Big Five traits and job tenure Conditional on Big Five traits and job tenure Level 2 quadratic slope differences Unconditional on Big Five traits and job tenure Conditional on Big Five traits and job tenure Level 2 cubic slope differences Unconditional on Big Five traits and job tenure Conditional on Big Five traits and job tenure
63,604.29 37,327.71 319,030.57 278,104.28 6,430,197.19 6,869,322.77 436,504.62 483,695.22 1,562,525.60 1,407,917.53
Percent variance accounted for in model (pseudo R2) .41 .13 .00 .00 .10
tenance sample), and finally, jumped by another 29% betweenlevel of significance for any of the 4 quarters studied in the Quarter 3 and Quarter 4 (the positive change over the same period transitional group. Openness to experience predicted performance for the maintenance employees was 17%). at Quarter 2 (r .30, p .05). Correlations between openness and performance were positive but nonsignificant at Quarter 1 (r Given the difference in the scaling of performance in the main.25) and Quarter 3 (r .26; both ps .10). Openness did not tenance (raw sales counts) and transitional (percent market share) performance at Quarter 4 (r .17, ns). Surprisingly, samples in the four periods of interest to our study, we soughtpredict to confirm a positive association between raw and adjusted salesconscientiousness (Hypothesis 5) failed to predict performance in any of the 4 quarters studied. Although not hypothesized, agreefigures in the latter group. Strong, positive correlations between ableness predicted performance in each of the 4 quarters, with raw and market share adjusted sales figures at each quarter would correlations ranging from .33 ( p .05) at Quarter 4 to .38 ( p support our use of the latter as criteria in the transitional sample. .01) at Quarter 1. The remaining Big Five traits, as well as job We obtained the necessary data from company records and found tenure, failed to predict performance at any measurement period in strong correlations between raw and adjusted sales of .85 at Quarthis sample. ter 1, .78 at Quarter 2, .72 at Quarter 3, and .72 at Quarter 4 (all ps .001). The mean correlation between raw and market share RCM results for the transitional sample are presented in Table 5. At Step 1, we found ICC1 .22. Consistent with adjusted sales across these four periods was .77. 2, the L1 results show a positive linear trend in Regarding bivariate predictor– criterion relationships (seeHypothesis Table performance followed by a significant negative quadratic trend, 1), extraversion failed to predict performance at the traditional .05
Predicted sales in the maintenance sample at each quarter as a function of conscientiousness (C). Total sales volume sales in terms of the number of prescriptions written by physicians in the salesperson’s territory.
Figure 1.
845
PERSONALITY AND PERFORMANCE TRAJECTORIES
Table 5
Random Coefficient Models Predicting Monthly Sales in Transitional Stage Sample
SE
95% CI lower bound
95% CI upper bound
5.916 37.497 2.350
0.349 1.839 0.593
5.233 33.893 3.512
6.599 41.102 1.188
Conscientiousness (intercept)
0.059 0.052 0.016 0.064 0.091 0.034
0.046 0.027 0.034 0.032 0.037 0.042
0.030 0.105 0.051 0.003 0.019 0.048
0.148 0.001 0.083 0.126 0.163 0.117
1.29 1.92† 0.47 2.04* 2.47* 0.82
Job Tenure Linear (slope) Emotional Stability Linear (slope) Extraversion Linear (slope) Openness to Experience Linear (slope) Agreeableness Linear (slope) Conscientiousness Linear (slope)
0.242 0.359 0.167 0.173 0.396 0.146
0.249 0.148 0.187 0.172 0.201 0.229
0.245 0.649 0.199 0.165 0.002 0.302
0.730 0.069 0.534 0.510 0.789 0.595
0.97 2.43* 0.89 1.00 1.97* 0.64
Job tenure Quadratic (slope) Emotional stability Quadratic (slope) Extraversion Quadratic (slope)
0.082 0.020 0.069 0.202 0.065 0.039
0.077 0.046 0.058 0.053 0.062 0.071
0.232 0.109 0.044 0.305 0.186 0.177
0.068 0.070 0.181 0.098 0.056 0.099
1.07 0.44 1.19 3.80** 1.05 0.55
Parameter estimate
Linear trend Quadratic trend
Extraversion (intercept) Openness to experience (intercept)
Model and parameter Final Level 1 model Intercept Final Level 2 model Job tenure (intercept) Emotional stability (intercept) Agreeableness (intercept)
Openness to Experience
Agreeableness
Quadratic (slope)
Quadratic (slope)
Conscientiousness
Quadratic (slope)
t
16.97*** 20.39*** 3.96***
For all Level 1 parameter estimates, df 142; for parameters predicting intercept variation in Level 2 analyses, df 41; for cross-level interaction parameters in level 2 analyses, df 130. For the sake of clarity, hypothesized effects are italicized. CI confidence interval. † p .10. * p .05. ** p .01. *** p .001.
Note.
indicating a plateauing or deceleration of group-level perfor(r –.30, p .05). These results suggest a pattern in which mance (which still increases, but not at the same rate) between effective performers in the transitional sample (in terms of Quarter 2 and Quarter 3 (Step 2). These results may suggestmean a sales) were more likely to experience performance inmovement from a transitional to a maintenance stage at thiscreases early in the study and also less likely to experience period. As in the maintenance sample, we tested an L1 model plateaued performance throughout the course of the study. As involving a cubic term in an exploratory fashion (Ployhart &shown in Table 5, the final L1 model accounted for 88% of the Hakel, 1998). The results fail to support cubic growth in thereliable within-person variance in sales performance across the transitional sample— hence, the cubic term was dropped from 4-quarter period for the transitional sample. all subsequent analyses. The results of our Step 3 analyses show Also shown in Table 5 are parameter estimates for the L2 2 that allowing intercepts to vary increased model fit, model in the transitional sample. Again, all effects for the traits (2) diff are conditional on job tenure. Hypotheses 5–7 concerned the 10.98, p .001. There was significant interindividual variation 2 prediction of performance intercept differences (mean perforin both the linear, (2) 198.94, p .001, and quadratic, diff 2 mance) from conscientiousness, extraversion, and openness to 33.86, p .001, slope parameters. Again, these diff (5) experience, respectively, with job tenure held constant. Only results support the possibility of individual difference-based Hypothesis 7 (openness to experience) received support—indipredictors of the L2 terms. The results of our analyses of error 2 structures fail to support autocorrelation, (1) diff 1.60, ns, or viduals high in openness tended to have higher mean performance than did those low in openness. Although not hypotheheteroskedasticity,2 (1) 0.96, ns, so these specifications diff sized, agreeableness also was positively associated with mean were dropped from subsequent analyses. A correlational analysis of trend terms (see lower diagonal of Table 3) shows a level performance. nearly perfect correlation between mean performance and linear Hypothesis 9 concerned the effects of conscientiousness on growth (r .94, p .001), perhaps a tautological result in thenegative quadratic performance growth (e.g., the plateauing sense that all salespeople in the transitional sample began the effect—such that the performance of conscientious persons study with sales of zero. More interesting is the finding thatshould be less likely to peak at some point during the study). As mean performance was negatively related to negative quadratic shown in Table 5, this hypothesis failed to receive support, as growth (r –.54, p .001). Positive linear and negative conscientiousness failed to predict any of the L2 parameters. quadratic growth also were moderately and inversely related Two traits clearly were associated with the linear term. Our
846
THORESEN, BRADLEY, BLIESE, AND THORESEN
Table 6
Variance Accounted for in Final Level 1 and Level 2 Models for Transitional Sample Model description
Observed variance
Level 1 Unconditional on time trends 11.07 Conditional on linear and quadratic trends 1.28 Level 2 intercept differences Unconditional on Big Five traits and job tenure 5.51 Conditional on Big Five traits and job tenure 4.53 Level 2 linear slope differences Unconditional on Big Five traits and job tenure 155.56 Conditional on Big Five traits and job tenure 137.72 Level 2 quadratic slope differences Unconditional on Big Five traits and job tenure 10.09 Conditional on Big Five traits and job tenure 6.94
Percent variance accounted for in model (Pseudo R2) .88 .18 .11 .31
results indicate that agreeable salespeople were more likely Figure and 2 supports a persistent effect on mean level performance emotionally stable individuals were less likely to increase their across the 4 quarters for agreeableness, corresponding to the sigsales in a positive linear fashion across the period of the study. nificant association between agreeableness and the L2 intercept Finally, openness to experience was negatively associated with term in this sample. In addition, a close examination of Figure 2 negative quadratic growth, indicating that open salespeople shows a slightly steeper slope for persons high in agreeableness were less likely to experience plateaued performance across across the the study period, reflecting the positive association between 4-quarter period of the study. Job tenure failed to predict both this trait and linear growth at L2. Identical effects are shown in mean level performance and performance growth. As indicated Figure 3 for emotional stability, although this effect is in the by Table 6, predictor variables in the final L2 model accounted opposite direction as one might expect, with low emotional stabilfor 18% of the between-person variance in performance interity (i.e., neuroticism) positively associated with mean performance cepts and 11% and 31% of the between-person variance in differences and positive performance growth. Finally, Figure 4 linear and quadratic slopes, respectively, across the 4 quarters reveals the complexity of the interaction between openness to studied for the transitional group. experience and time. Again, positive mean-level performance differences as a function of openness across the 4 quarters are Effects on performance at each quarter for agreeableness, emotional stability, and openness to experience in the transitional immediately apparent. The increasing divergence between highsample are shown in Figures 2, 3, and 4, respectively. For eachand low-openness salespeople across the 4 quarters represents the negative association between openness and negative quadratic trait, predicted performance of persons one standard deviation growth. Although there is a slight decrease in the sample as a above and one standard deviation below the sample mean on the whole given trait are contrasted along with predicted performance at eachin the rate of performance growth between Quarter 1 and quarter for persons scoring at the sample mean for each trait. Quarter 4 (see the line corresponding to predicted sales at sample mean levels of openness), this effect is less pronounced for those Again, values for job tenure and the relevant other four traits are high in openness to experience. held constant at their respective sample means in these contrasts.
Figure 2.
Predicted sales in the transitional sample at each quarter as a function of agreeableness (A).
PERSONALITY AND PERFORMANCE TRAJECTORIES
Figure 3.
847
Predicted sales in the transitional sample at each quarter as a function of emotional stability (ES).
change (for conscientiousness) in the maintenance sample but not in the transitional sample. The reason for this discrepancy is unclear. Our study adds to a growing body of literature concerning the However, it has been argued that during the maintenance stage, temporal nature of job performance. In addition, ours is the first employees do not necessarily face new challenges or novel stimuli on study of which we are aware to advance explicit hypotheses a regular basis (Murphy, 1989). Perhaps employees low on these traits concerning associations between personality factors and change in may become complacent during this stage. In contrast, extraverts and individual performance trajectories while accounting for job stage conscientious persons are more likely to excel under these circumin a field setting. To date, the majority of research on personality– stances, as such persons have high energy levels, strive for achieveperformance relations has correlated personality traits with performent, and in the case of conscientiousness, are more likely to be mance measured at only one point in time. Some of our hypotheses duty-bound (Hogan & Ones, 1997). Thus, extraversion and consciconcerning personality–performance relations in the context of entiousness should continue to predict job performance even when performance change were supported, whereas others were not. job-related tasks have become fairly routinized, as in the maintenance Conversely, we obtained serendipitous findings with respect to the stage (Stewart, 1999). In fact, our results do point to conscientiousness validity of agreeableness in predicting performance growth paramas a positive force in performance change in the maintenance sample, eters in the transitional sample. as evidenced by the significant cubic trend. These traits may be less Most important, the same personality factors associated with sucsalient during transitional stages, in which individual differences in cess did not necessarily generalize across the maintenance and trancreativity, intellectual flexibility, problem solving, and adaptability sitional job contexts. For example, conscientiousness and extraversion are brought to the forefront. were positively associated with mean performance and performance
Discussion
Figure 4.
ence (OE).
Predicted sales in the transitional sample at each quarter as a function of openness to experi-
848
THORESEN, BRADLEY, BLIESE, AND THORESEN
Consistent with this view, openness was positively associated action (e.g., increase effort) to eliminate the unpleasant emotions with both mean performance and performance trends in the tranassociated with stress. As people low in emotional stability are sitional sample but unrelated to sales in the maintenance sample. more likely to appraise their job environments as threatening Thus, openness may be a critical factor for performance when(Spector, Zapf, Chen, & Frese, 2000) and a transitional job period employees are required to adapt to change (as hypothesized) but is full of novel challenges, some degree of neuroticism may less important for steady state performance. One might expectactually that be beneficial for performance under these conditions. the validity of openness to experience would wane with time inHowever, our researchers rarely advance such arguments, and this transitional sample, signaling the movement to more of a maintefinding clearly needs replication before such an interpretation nance stage for this group of employees. Bivariate analyses from would seem credible. our study suggest slightly weaker correlations between openness Finally, because job tenure was not a central focus of this study, and later performance (e.g., Quarter 4). However, our RCM results we did not hypothesize any directional associations between tenure tell a different story, as highly open salespeople had increasedand either mean level performance or performance trends in the sales aggregated across the 4-quarter period as a whole and were maintenance and transitional samples. However, our results reveal less likely to experience plateaued performance at later periods. a positive relationship between tenure and mean performance in An unexpected finding was the strong positive relationship the maintenance sample, indicating that employees who had worked in their jobs longer had higher sales. There was no assobetween agreeableness and both mean performance and perforciation between tenure and sales in the transitional sample. These mance growth in the transitional sample. Agreeableness, although findings deserve comment. On one hand, to the extent that tenure sometimes argued to interact with other personality traits such as would facilitate performance, one might expect that this effect conscientiousness in predicting performance (Witt, Burke, Barrick, would be stronger for incumbents in the transitional sample, as & Mount, 2002), is rarely hypothesized to have a main effect on performance. However, in the transitional sample, we believe these persons may have similar (although not identical) experiences salesperson agreeableness may have resulted in a positive “foot in in their past work with the company to those encountered in their new positions. This effect would be reflected in a higher the door” effect. That is, agreeable salespeople may have achieved greater success in the transitional group as a function of their positive linear trend (i.e., higher initial performance) for highly salespeople. On the other hand, consistent with Deadrick increased ability to gain access to potential customers as well tenured as et al.’s (1997) findings, such an effect would be expected to their ability to maintain positive relationships with these persons across time. What would lead to such an effect? One possible dissipate with time. Neither assertion is supported by our data. The mediating mechanism is trust. A fundamental characteristic ofpositive relationship between tenure and mean sales in the maintenance sample may simply reflect the within-sample variation in agreeable persons is their trustworthiness, whereas disagreeable job knowledge as a result of experience in this group (Murphy, people are manipulative, cynical, and self-serving (Costa & McCrae, 1995). In addition, agreeableness has been shown to be 1989). a key Although not the central focus of the current study, a critical research question in this context might involve estimation component of employee integrity (Sackett & DeVore, 2001). As of the diminishing returns on performance across time (e.g., plagatekeepers of information, it is critical that pharmaceutical sales teaued growth) of previous job tenure and experience as a function representatives have trusting relationships with potential customof job characteristics such as complexity or changing task enviers. In fact, a recent meta-analysis of the sales literature uncovered ronments (Schmidt, Hunter, Outerbridge, & Goff, 1988; Tesluk & a significant positive association between customer trust percepJacobs, 1998). tions and sales performance (Swan, Bowers, & Richardson, 1998). Thus, the quality of employee–customer interactions may have Several potential weaknesses of the current study deserve menrepresented the driving force behind the validity of agreeableness tion. First, it should be noted that in both the maintenance and in predicting transitional group performance and performance transitional data, rank-order consistency in performance across trends in our study. Consistent with such an interpretation, metatime was somewhat higher than that frequently reported in other analytic research has shown that agreeableness possesses validity studies of this type (e.g., Deadrick et al., 1997; Hofmann et al., comparable with that of conscientiousness for jobs focused on1992, 1993; Ployhart & Hakel, 1998). Although the reason for this interpersonal interactions in which “getting along” is critical for tendency in our own data is unclear, it is possible that individual performance (Hogan & Holland, 2003; Mount, Barrick, & Stewart, performance in both samples was largely determined by tempo1998). rally stable factors outside the person’s control (e.g., market demographics, territory size), resulting in upwardly biased consisMore difficult to explain is the negative association between tency estimates. The measurement of performance— even objecemotional stability and linear performance growth in the transitive performance—is always potentially subject to confounds of tional sample. To the extent that emotional stability predicts perthis sort (Austin & Villanova, 1992; Muckler, 1992), and we do formance, meta-analytic reviews have concluded that the associanot necessarily see our samples as differing from typical sales tion is positive (e.g., Judge & Bono, 2001; Salgado, 1997). This samples in this regard. Such influences might place limits on the makes sense, in light of the fact that people with low emotional effects of individual difference factors as predictors of individual stability are described as depressed, insecure, and anxious (Costa & McCrae, 1995), traits that would hardly seem to facilitate mean performance differences and performance trajectories across a specified time period. However, the magnitude of bivariate effective job performance under any circumstances. One possible personality–performance relationships we observed in our study explanation for this counterintuitive finding comes from control was comparable to those frequently reported in the literature (e.g., and cybernetic theories of the stress process as applied to work Barrick & Mount, 1991; Hurtz & Donovan, 2000), although our (Carver & Scheier, 1990, 1998; Edwards, 1992). These theories conclusions about which traits possess validity under maintenance posit that when confronted with stressful episodes, people take
PERSONALITY AND PERFORMANCE TRAJECTORIES
849
information, and had to seek out a new client base, they ultimately versus transitional job conditions differed somewhat from findings typically generated by studies correlating personality traits with remained working for the same employer in the same industry. It static job performance measures, as well as several major metais difficult to definitively say whether our designation of this group analyses of personality trait validity (e.g., Barrick & Mount, 1991; of employees as a transitional sample diminished the internal Barrick et al., 2001; Hurtz & Donovan, 2000). Future validity validity of our study (Cook & Campbell, 1979), and we acknowlgeneralization research may want to consider job stage as a modedge this possibility. However, if the transitional stage in the erator of personality–performance relationships by comparing the current study were truly not transitional in nature, we probably validity of traits in high- versus low-tenured employees. The often would not have observed the strong positive linear and negative disappointing meta-analytic results obtained for the validity ofquadratic trends in group mean performance (signaling a potential traits such as agreeableness and openness to experience may transitional to maintenance stage shift) as well as the tendency of simply be the result of the tendency of previous meta-analytic different personality factors (e.g., openness to experience, agreeauthors to collapse across job stage variables in estimating the ableness) to be associated with success in this situation vis-a` -vis validity of these traits. the maintenance context. If anything, we believe that our results A second potential shortcoming of our study concerns our use of be on the conservative side, given the nature of our transimay broadband measures of the Big Five traits—particularly in light of sample. That is, maintenance versus transitional differences tional the null effects for conscientiousness in predicting performance in performance trends—and predictors of these trends—might and performance growth parameters in the transitional sample. In been more pronounced had we used a start-up sample as our have recent years, attention has returned to the longstanding bandwidth– transitional group. Future studies could avert this problem through fidelity debate within industrial–organizational psychology asthe it use of transitional samples comprising persons with no prior relates to the relative validity of broad versus narrow traits in the experience in a given industry or occupation or at least the use of prediction of job performance. Several researchers have argued subjective perceptual measures of job stage status on which mainthat narrow traits offer the most promise (e.g., Ashton, 1998), tenance and (ostensibly) transitional samples could be contrasted others have suggested that broad traits are preferable (Ones & to verify the status of the latter. Viswesvaran, 1996), and still others have pointed out that the Finally, we did not measure general mental ability (g) in the choice of broad versus narrow measures should be determined by current study to test its relationship to individual performance the nature of the criteria that one is trying to predict (Hogan &growth. Thus, it was not possible to test the relative importance of Holland, 2003; Hogan & Roberts, 1996; R. J. Schneider, Hough, g& versus personality dispositions and job tenure in the prediction of Dunnette, 1996). In the context of our study, it is possible that performance across time. However, we do not feel that this omissome facets of conscientiousness (e.g., order, duty, achievement, sion invalidates our results. Meta-analytic research has shown that, competence) may be relevant for transitional job performance, because g is relatively orthogonal to the Big Five dimensions, g whereas others are less relevant (or perhaps negatively related). andIfpersonality uniquely add to the prediction of job performance so, the use of a measure of conscientiousness combining itemsin most occupations (Schmidt & Hunter, 1998). In addition—and from these various facets—yet not allowing for comprehensivein contradiction to previous research in this area—Vinchur et al. assessment of any of the facets individually—would cause these (1998) found that g was uncorrelated with objective sales data in competing influences to cancel out, producing an overall null their meta-analysis of the predictors of sales success. Thus, it is effect for conscientiousness. In fact, several recent studies have unlikely that the omission of g from our study substantively suggested differences in the nature and direction of facet-level affected parameter estimates for the Big Five traits in the predicassociations within Big Five constructs for the prediction of crition of performance. However, future research might incorporate teria such as escalation of commitment in decision-making situaboth g and personality traits in the prediction of temporal changes tions (Moon, 2001; Moon, Hollenbeck, Humphrey, & Maue, in job performance for employees at maintenance and transitional 2003), absenteeism (Judge, Martocchio, & Thoresen, 1997), and job stages. In spite of these potential shortcomings, we feel that our most critical to our study, job performance (Stewart, 1999). Likeuse of real field data, as well as our use of the Big Five taxonomy wise, we found fairly modest effects for the broad traits in pre-to generate and test theoretically salient personality–performance dicting some of the higher order growth trend terms (e.g., linear and performance trajectory relationships, somewhat ameliorates growth in maintenance and transitional samples) relative to our these concerns. ability to predict mean performance levels. It is possible that the The practical implications of our results for organizations dehigher order growth trend terms contain specific factor variance serve some comment. Numerous management theorists have obuniquely associated with the facet level (but not the broad-based) served that the nature of jobs is changing, such that in the future, components of the Big Five traits.3 Future research might attempt workers will need to continuously increase their skill base to to replicate our results using measures allowing for more fine experience workplace success (Howard, 1995; Patterson, 2001). grained assessments of Big Five traits at the facet level to tease out Likewise, our economy is becoming increasingly service oriented these potentially complex influences in predicting job performance (V. Schneider, Chung, & Yusko, 1993), and the focus on service in a temporal context while still allowing for broad-based assessis particularly salient for people in sales jobs. Given these changment by summing facet-level scores for each Big Five trait. ing aspects of the workplace environment, organizations may want A third issue revolves around salespeople in the transitionalto consider traits that relate to adaptability (openness) and service sample. One may question whether the changes experienced by these individuals were qualitatively comparable to those described by Murphy (1989). For example, although these persons experi-3 We thank an anonymous reviewer for bringing to our attention this enced a shift in priorities, were required to learn new technical possibility.
850
THORESEN, BRADLEY, BLIESE, AND THORESEN
(most likely, agreeableness) in addition to factors such as conscitraits. Rather than suggesting that the validity for traits deteriorates entiousness and general mental ability when making hiring deciwith time, our results point to the conclusion that changes in sions. Furthermore, organizations may want to take these characperformance at relatively distal time periods (i.e., performance teristics into account when nominating employees for transitional growth trajectories) can actually be predicted with some degree of job situations. Other researchers have advanced similar arguments accuracy from personality traits such as conscientiousness, openwith respect to identifying employees most capable of coping ness with to experience, and agreeableness, depending on the nature of the demands of changes such as organizational restructuring the andsample of job incumbents in question. That is, traits may downsizing (Judge et al., 1999), expatriate work assignments constitute substantively important determinants of changes in job (Ones & Viswesvaran, 1997, 1999), and the implementation ofperformance patterns with increased job experience. Thus, one new technologies (Hesketh & Neal, 1999). Although the changes conclusion one might draw from our study is that the initial gains experienced by our transitional sample may not have approached to organizations for selection based on personality traits are not the scope of those listed here, it is interesting to note that the same epiphenomenal but that they persist (and may even increase) with traits hypothesized to affect performance for these types of increased time on the job. In addition, even small gains in indichanges (in particular, openness) predicted sales effectiveness vidual in performance across time as a function of these individual our transitional sample. differences would be expected to translate into large economic Another practical consideration stemming from our results gains con- in the aggregate within an entire sales force or organization. cerns the practice of banding in a personnel selection context.Of course, a 1-year time frame simply may not have been long enough for us to observe a decline in validity for traits similar to Simply stated, banding is a procedure that treats predictor test scores within a range of potential scores (i.e., a score band) asthose often observed for cognitive ability (Keil & Cortina, 2001). equivalent, given a previously specified level of measurement Clearly, a number of questions about the relationships between precision in the predictor (Cascio, Outtz, Zedeck, & Goldstein,personality traits and job performance trajectories remain to be 1991). Some researchers have advocated this method as a means of addressed by future researchers in other occupational settings and reducing adverse impact against minority groups in a selection contexts. Although the field has witnessed important theoretical context (e.g., Cascio et al., 1991), whereas others (e.g., Schmidt, and empirical advances concerning relationships between ability 1991) have questioned the logic underlying this method. Sophisconstructs and performance in a temporal context (e.g., Ackerman, ticated models have been developed that take into account the1988, 1992; Hulin et al., 1990; Keil & Cortina, 2001; Murphy, effects of unreliability in predictor tests in the process of deter1989; Schmidt et al., 1988), similar theories focusing on volitional mining score bands (e.g., Murphy, 1994; Murphy, Osten, & My-variables such as personality traits have been lacking. In addition ors, 1995). However, researchers have largely overlooked theto issue replicating the current study in other field contexts with more of change in criterion scores (i.e., dynamic criteria) in the context sophisticated research designs, experimental laboratory research of the practice of banding (for an exception, see Aguinis, Cortina, could test more complex temporal aspects of personality–perfor& Goldberg, 1998). Incorporating performance change into bandmance relationships using a task-based skill-acquisition frameing models may prove problematic. Schmidt and colleagues (in work. In fact, the evolution and evaluation of testable theories Campion et al., 2001, pp. 163–164) presented a scenario in which involving personality–performance relationships in the context of accounting for unreliability in job performance measures resulted temporal and career stage variables may represent the next imporin score bands including 97% of all predicted performance tant step for personality research in applied settings. We hope that scores— hence negating the utility of banding in such a scenario. our study provides a useful starting point for additional research in Clearly, more research is needed that incorporates a criterion-this tradition. based perspective and acknowledges both group- and individuallevel changes in job performance. One possible solution involves References treating temporal change in criterion scores as systematic (rather Ackerman, P. L. (1988). Determinants of individual differences during than random measurement error) and setting bands around preskill acquisition: Cognitive abilities and information processing. Journal dicted performance scores that incorporate expected performance of Experimental Psychology: General, 117, 288 –318. growth. Of course, it should be noted that there is no clear-cut Ackerman, P. L. (1992). Predicting individual differences in complex skill evidence of sizable group differences on measures of broad (e.g., acquisition: Dynamics of ability determinants. Journal of Applied Psythe Big Five) personality traits (Hough, Oswald, & Ployhart, chology, 77, 598 – 614. 2001), which would suggest that adverse impact may not be a Aguinis, H., Cortina, J. M., & Goldberg, E. (1998). A new procedure for significant problem for selection based on measures of these computing equivalence bands in personnel selection. Human Perforconstructs. mance, 11, 351–365. Finally, our design provides some basis for confidence in theAshton, M. C. (1998). Personality and job performance: The importance of long-term validity—and consequently, the utility—of selection narrow traits. Journal of Organizational Behavior, 19, 289 –303. Austin, J. T., & Villanova, P. (1992). The criterion problem: 1917–1992. systems based on personality traits, a point that has been debated Journal of Applied Psychology, 77, 836 – 874. in the literature (Henry & Hulin, 1987, 1989; Schmidt et al., 1988). Avolio, B. J., Waldman, D. A., & McDaniel, M. A. (1990). Age and work The validity of personality traits for predicting sales performance performance in nonmanagerial jobs: The effects of experience and did not systematically decrease across the 1-year time interval for occupational type. Academy of Management Journal, 33, 407– 422. our study in either of the two samples. Although research has Barrick, M. R., & Mount, M. K. (1991). The Big Five personality dimensupported the deterioration of the validity of cognitive ability sions and job performance: A meta-analysis. Personnel Psychology, 44, across time (Keil & Cortina, 2001), our results indicate cause for1–26. cautious optimism with respect to this question for personalityBarrick, M. R., & Mount, M. K. (1996). Effects of impression management
PERSONALITY AND PERFORMANCE TRAJECTORIES
851
and self-deception on the predictive validity of personality constructs. linear modeling to examine dynamic performance criteria over time. Journal of Management, 23, 745–757. Barrick, M. R., Mount, M. K., & Judge, T. A. (2001). Personality and Deadrick, D. L., & Madigan, R. M. (1990). Dynamic criteria revisited: A performance at the beginning of the new millennium: What do we know longitudinal study of performance stability and predictive validity. Personnel Psychology, 43, 717–744. and where do we go next? International Journal of Selection and Assessment, 9, 9 –30. Deshon, R. P., Ployhart, R. E., & Sacco, J. M. (1998). The estimation of Barrick, M. R., Mount, M. K., & Strauss, J. P. (1993). Conscientiousnessreliability in longitudinal models. International Journal of Behavior and Development, 22, 493–515. and performance of sales representatives: Test of the mediating effects of goal setting. Journal of Applied Psychology, 78, 715–722. Digman, J. M. (1990). Personality structure: Emergence of the five-factor Barrick, M. R., Mount, M. K., & Strauss, J. P. (1994). Antecedentsmodel. of Annual Review of Psychology, 41, 417– 440. voluntary turnover due to a reduction in force. Personnel Psychology, Digman, J. M. (1997). Higher-order factors of the Big Five. Journal of 47, 515–535. Personality and Social Psychology, 73, 1246 –1256. Barrick, M. R., Stewart, G. L., & Piotrowski, M. (2002). Personality and Dodd, W. E., Wollowick, H. B., & McNamara, W. J. (1970). Task job performance: Test of the mediating effects of motivation among difficulty as a moderator of long-range prediction. Journal of Applied Psychology, 54, 265–270. sales representatives. Journal of Applied Psychology, 87, 43–51. Bass, B. M. (1962). Further evidence of the dynamic nature of criteria. Edwards, J. R. (1992). A cybernetic theory of stress, coping, and wellPersonnel Psychology, 15, 93–97. being in organizations. Academy of Management Review, 17, 238 –274. Bing, M. N., & Lounsbury, J. W. (2000). Openness and job performance Ghiselli, in E. E. (1956). Dimensional problems of criteria. Journal of Applied U. S.-based Japanese manufacturing companies. Journal of Business and Psychology, 40, 1– 4. Psychology, 14, 515–522. Ghiselli, E. E., & Haire, M. (1960). The validation of selection tests in the light of the dynamic nature of criteria. Personnel Psychology, 13, 225– Bliese, P. D., & Ployhart, R. E. (2002). Growth modeling using random 231. coefficient models: Model building, testing, and illustrations. Organizational Research Methods, 5, 362–387. Goldberg, L. R. (1990). An alternative “description of personality”: The Bryk, A. S., & Raudenbush, S. W. (1992). Hierarchical linear models: Big-Five factor structure. Journal of Personality and Social Psychology, Applications and data analysis methods. Newbury Park, CA: Sage. 59, 1216 –1229. Campion, M. A., Outtz, J. L., Zedeck, S., Schmidt, F. L., Kehoe, J. F., Hanges, P. J., Schneider, B., & Niles, K. (1990). Stability of performance: Murphy, K. R., & Guion, R. M. (2001). The controversy over score An interactionist perspective. Journal of Applied Psychology, 75, 658 – banding in personnel selection: Answers to 10 key questions. Personnel 667. Psychology, 54, 149 –185. Helmreich, R. L., Sawin, L. L., & Carsrud, A. L. (1986). The honeymoon Carver, C. S., & Scheier, M. F. (1990). Origins and functions of positive effect in job performance: Temporal increases in the predictive power of and negative affect: A control-process view. Psychological Review, 97, achievement motivation. Journal of Applied Psychology, 71, 185–188. 19 –35. Henry, R. A., & Hulin, C. L. (1987). Stability of skilled performance across time: Some generalizations and limitations on utilities. Journal of ApCarver, C. S., & Scheier, M. F. (1998). On the self-regulation of behavior. plied Psychology, 72, 457– 462. Cambridge, England: Cambridge University Press. Henry, R. A., & Hulin, C. L. (1989). Changing validities: Ability–perforCascio, W. F., Outtz, J., Zedeck, S., & Goldstein, I. L. (1991). Statistical mance relations and utilities. Journal of Applied Psychology, 74, 365– implications of six methods of test score use in personnel selection. Human Performance, 4, 233–264. 367. Cook, T. D., & Campbell, D. T. (1979). Quasi-experimentation: Design Hesketh, B., & Neal, A. (1999). Technology and performance. In D. R. and analysis issues for field settings. Boston: Houghton Mifflin. Ilgen & E. D. Pulakos (Eds.), The changing nature of performance: Implications for staffing, motivation, and development (pp. 21–55). San Corr, P. J., & Gray, J. A. (1995). Attributional style, socialization and cognitive ability as predictors of sales success: A predictive validity Francisco: Jossey-Bass. study. Personality and Individual Differences, 18, 241–252. Hofmann, D. A. (1997). An overview of the logic and rationale of hierarCosta, P. T., Jr. (1996). Work and personality: Use of the NEO-PI-R chical in linear models. Journal of Management, 23, 723–744. industrial/organizational psychology. Applied Psychology: An Interna- Hofmann, D. A., Jacobs, R., & Baratta, J. E. (1993). Dynamic criteria and tional Review, 45, 225–241. the measurement of change. Journal of Applied Psychology, 78, 194 – 204. Costa, P. T., Jr., & McCrae, R. R. (1992). Revised NEO Personality Inventory (NEO-PI-R) and NEO Five-Factor Inventory (NEO-FFI) pro-Hofmann, D. A., Jacobs, R., & Gerras, S. J. (1992). Mapping individual fessional manual. Odessa, FL: Psychological Assessment Resources. performance over time. Journal of Applied Psychology, 77, 185–195. Costa, P. T., Jr., & McCrae, R. R. (1995). Domains and facets: Hierarchical Hogan, J., & Holland, B. (2003). Using theory to evaluate personality and job-performance relations: A socioanalytic perspective. Journal of Appersonality assessment using the Revised NEO Personality Inventory. Journal of Personality Assessment, 64, 21–50. plied Psychology, 88, 100 –112. Crant, J. M. (1995). The Proactive Personality Scale and objective Hogan, job J., & Ones, D. S. (1997). Conscientiousness and integrity at work. performance among real estate agents. Journal of Applied Psychology, In R. Hogan, J. Johnson, & S. Briggs (Eds.), Handbook of personality 80, 532–537. psychology (pp. 849 – 870). San Diego, CA: Academic Press. Cravens, D. W., & Woodruff, R. B. (1973). An approach for determining Hogan, J., & Roberts, B. W. (1996). Issues and non-issues in the fidelity– criteria of sales performance. Journal of Applied Psychology, 57, 242– bandwidth trade-off. Journal of Organizational Behavior, 17, 627– 637. 247. Hough, L. M., Oswald, F. L., & Ployhart, R. E. (2001). Determinants, detection and amelioration of adverse impact in personnel selection Cronbach, L. J., & Furby, L. (1970). How we should measure “change”: Or procedures: Issues, evidence and lessons learned. International Journal should we? Psychological Bulletin, 74, 68–80. Davison, M. L., Kwak, N., Seo, Y. S., & Choi, J. (2002). Using hierarchicalof Selection and Assessment, 9, 152–194. linear models to examine moderator effects: Person-by-organization Howard, A. (1995). The changing nature of work. San Francisco: Josseyinteractions. Organizational Research Methods, 5, 231–254. Bass. Deadrick, D. L., Bennett, N., & Russell, C. J. (1997). Using hierarchical Hulin, C. L., Henry, R. A., & Noon, S. L. (1990). Adding a dimension: Journal of Applied Psychology, 81, 261–272.
852
THORESEN, BRADLEY, BLIESE, AND THORESEN
Time as a factor in the generalizability and predictive relationships. agement. Research in Personnel and Human Resources Management, 13, 153–200. Mount, M. K., Barrick, M. R., & Stewart, G. L. (1998). Five-factor model Hunter, J. E., & Hunter, R. F. (1984). Validity and utility of alternative of personality and performance in jobs involving interpersonal interacpredictors of job performance. Psychological Bulletin, 96, 72–98. tions. Human Performance, 11, 145–165. Hurtz, G. M., & Donovan, J. J. (2000). Personality and job performance: The Big Five revisited. Journal of Applied Psychology, 85, 869 – 879. Muckler, F. A. (1992). Selecting performance measures: “Objective” versus “subjective” measurement. Human Factors, 34, 441– 445. Jacobs, R., Hofmann, D. A., & Kriska, S. D. (1990). Performance and Murphy, K. R. (1989). Is the relationship between cognitive ability and job seniority. Human Performance, 3, 107–121. performance stable over time? Human Performance, 2, 183–200. Judge, T. A., & Bono, J. E. (2001). Relationship of core self-evaluation Murphy, K. R. (1994). Potential effects of banding as a function of test traits—self-esteem, generalized self-efficacy, locus of control, and emotional stability—with job satisfaction and job performance: A meta- reliability. Personnel Psychology, 47, 477– 495. Murphy, K. R., Osten, K., & Myors, B. (1995). Modeling the effects of analysis. Journal of Applied Psychology, 86, 80 –92. Judge, T. A., Erez, A., Bono, J. E., & Thoresen, C. J. (2002). Are measures banding in personnel selection. Personnel Psychology, 48, 61– 83. of self-esteem, neuroticism, locus of control, and generalized self- Ones, D. S., & Viswesvaran, C. (1996). Bandwidth-fidelity dilemma in efficacy indicators of a common core construct? Journal of Personality personality measurement for personnel selection. Journal of Organizational Behavior, 17, 609 – 626. and Social Psychology, 83, 693–710. Ones, Judge, T. A., Martocchio, J. J., & Thoresen, C. J. (1997). Five-factor model D. S., & Viswesvaran, C. (1997). Personality determinants in the of personality and employee absence. Journal of Applied Psychology, prediction of aspects of expatriate job success. In A. Zeynep (Ed.), New approaches to employee management: Vol. 4. Expatriate management: 82, 745–755. Theory and research (pp. 63–92). Stamford, CT : JAI Press. Judge, T. A., Thoresen, C. J., Pucik, V., & Welbourne, T. M. (1999). Ones, Managerial coping with organizational change: A dispositional perspec- D. S., & Viswesvaran, C. (1999). Relative importance of personality dimensions for expatriate selection: A policy capturing study. Human tive. Journal of Applied Psychology, 84, 107–122. Performance, 12, 275–294. Keil, C. T., & Cortina, J. M. (2001). Degradation of validity over time: A Patterson, F. (2001). Developments in work psychology: Emerging issues test and extension of Ackerman’s model. Psychological Bulletin, 127, and future trends. Journal of Occupational and Organizational Psychol673– 697. ogy, 74, 381–390. Lance, C. E., Vandenberg, R. J., & Self, R. M. (2000). Latent growth Pinheiro, J. C., & Bates, D. M. (2000). Mixed-effects models in S and models of individual change: The case of newcomer adjustment. OrgaS-PLUS. New York: Springer-Verlag. nizational Behavior and Human Decision Processes, 83, 107–140. Ployhart, R. E., & Hakel, M. D. (1998). The substantive nature of perforLePine, J. A., Colquitt, J. A., & Erez, A. (2000). Adaptability to changing mance variability: Predicting interindividual differences in intrainditask contexts: Effects of general cognitive ability, conscientiousness, and vidual performance. Personnel Psychology, 51, 859 –901. openness to experience. Personnel Psychology, 53, 563–593. Pulakos, E. D., Arad, S., Donovan, M. A., & Plamondon, K. E. (2000). Lucas, H. C., Jr., Weinberg, C. B., & Clowes, K. W. (1975). Sales response Adaptability in the workplace: Development of a taxonomy of adaptive as a function of territorial potential and sales representative workload. performance. Journal of Applied Psychology, 85, 612– 624. Journal of Marketing Research, 12, 298 –305. Quinones, ˜ M. A., Ford, J. K., & Teachout, M. S. (1995). The relationship Macan, T. H. (1994). Time management: Test of a process model. Journal between work experience and job performance. Personnel Psychology, of Applied Psychology, 79, 381–391. 48, 887–910. Mattell, M. S., & Jacoby, J. (1971). Is there an optimal number of Raudenbush, S. W. (2001). Comparing personal trajectories and drawing alternatives for Likert scale items? Educational and Psychological Meacausal inferences from longitudinal data. Annual Review of Psychology, surement, 31, 657– 674. 52, 501–525. McDaniel, M. A., Schmidt, F. L., & Hunter, J. E. (1988a). Job experience Raudenbush, S. W., & Xiao-Feng, L. (2001). Effects of study duration, correlates of job performance. Journal of Applied Psychology, 73, 327– frequency of observations, and sample size on power in studies of group 330. differences in polynomial change. Psychological Methods, 6, 387– 401. McDaniel, M. A., Schmidt, F. L., & Hunter, J. E. (1988b). A meta-analysis Russell, C. J. (2001). A longitudinal study of top-level executive perforof the validity of methods for rating training and experience in personnel mance. Journal of Applied Psychology, 86, 560 –573. selection. Personnel Psychology, 41, 283–314. Ryans, A. B., & Weinberg, C. B. (1979). Territory sales response. Journal McManus, M. A., & Brown, S. H. (1995). Adjusting sales results measures of Marketing Research, 16, 453– 465. for use as criteria. Personnel Psychology, 48, 391– 400. Sackett, P. R., & DeVore, C. J. (2001). Counterproductive behaviors at Mischel, W. (1977). The interaction of person and situation. In D. Magwork. In N. Anderson, D. S. Ones, H. K. Sinangil, & C. Viswesvaran nusson & N. S. Endler (Eds.), Personality and the crossroads: Current (Eds.), Handbook of industrial, work, & organizational psychology issues of interactional psychology (pp. 333–352). Hillsdale, NJ: (Vol. 1, pp. 145–164). London: Sage. Erlbaum. Salgado, J. F. (1997). The five factor model of personality and job perforMitchell, T. R., & James, L. R. (2001). Building better theory: Time and mance in the European Community. Journal of Applied Psychology, 82, the specification of when things happen. Academy of Management 30 – 43. Review, 26, 530 –547. Salgado, J. F. (2002). The Big Five personality dimensions and counterMoon, H. (2001). The two faces of conscientiousness: Duty and achieveproductive behaviors. International Journal of Selection and Assessment striving in escalation of commitment dilemmas. Journal of Applied ment, 10, 117–125. Psychology, 86, 535–540. Schmidt, F. L. (1991). Why all banding procedures are logically flawed. Moon, H., Hollenbeck, J. R., Humphrey, S. E., & Maue, B. (2003). The Human Performance, 4, 265–277. tripartite model of neuroticism and the suppression of depression Schmidt, and F. L., & Hunter, J. E. (1998). The validity and utility of selection anxiety within an escalation of commitment dilemma. Journal of Per- methods in personnel psychology: Practical and theoretical implications sonality, 71, 347–368. from 85 years of research findings. Psychological Bulletin, 124, 262– Mount, M. K., & Barrick, M. R. (1995). The Big Five personality dimen274. sions: Implications for research and practice in human resources Schmidt, man- F. L., Hunter, J. E., & Outerbridge, A. N. (1986). Impact of job Psychological Bulletin, 107, 328 –340.
PERSONALITY AND PERFORMANCE TRAJECTORIES
853
Swan, experience and ability on job knowledge, work sample performance, andJ. E., Bowers, M. R., & Richardson, L. D. (1998). Customer trust in supervisory ratings of job performance. Journal of Applied Psychology, the salesperson: An integrative review and meta-analysis of the empir71, 432– 439. ical literature. Journal of Business Research, 44, 93–107. Schmidt, F. L., Hunter, J. E., Outerbridge, A. N., & Goff, S. (1988). JointTesluk, P. E., & Jacobs, R. R. (1998). Toward an integrated model of work relation of experience and ability with job performance: Test of three experience. Personnel Psychology, 51, 321–355. Tett, R. P., Jackson, D. N., & Rothstein, M. (1991). Personality measures hypotheses. Journal of Applied Psychology, 73, 46 –57. Schneider, R. J., Hough, L. M., & Dunnette, M. D. (1996). Broadsidedasbypredictors of job performance: A meta-analytic review. Personnel 44, 703–742. broad traits: How to sink science in five dimensions or less. JournalPsychology, of Tupes, E. C., & Christal, R. E. (1992). Recurrent personality factors based Organizational Behavior, 17, 639 – 655. on trait ratings. Journal of Personality, 60, 225–251. Schneider, V., Chung, B., & Yusko, K. P. (1993). Service climate for service quality. Current Directions in Psychological Science, 2, 197– Vinchur, A. J., Schippmann, J. S., Switzer, F. S., III, & Roth, P. L. (1998). A meta-analytic review of predictors of job performance for salespeople. 200. Journal of Applied Psychology, 83, 586 –597. Snijders, T. A. B., & Bosker, R. J. (1994). Modeled variance in two-level Watson, D., & Hubbard, B. (1996). Adaptational style and dispositional models. Sociological Methods and Research, 22, 342–363. structure: Coping in the context of the five-factor model. Journal of Snijders, T. A. B., & Bosker, R. J. (1999). Multilevel analysis: An introPersonality, 64, 737–774. duction to basic and advanced multilevel modeling. London: Sage. Spector, P. E., Zapf, D., Chen, P. Y., & Frese, M. (2000). Why negative Willett, J. B., & Sayer, A. G. (1994). Using covariance structure analysis to detect correlates and predictors of individual change over time. affectivity should not be controlled in job stress research: Don’t throw Psychological Bulletin, 116, 363–381. out the baby with the bath water. Journal of Organizational Behavior, Witt, L. A., Burke, L. A., Barrick, M. R., & Mount, M. K. (2002). The 21, 79 –95. interactive effects of conscientiousness and agreeableness on job perSteele-Johnson, D., Osburn, H. G., & Pieper, K. F. (2000). A review and formance. Journal of Applied Psychology, 87, 164 –169. extension of current models of dynamic criteria. International Model of Selection and Assessment, 8, 110 –136. Received August 9, 2002 Stewart, G. L. (1999). Trait bandwidth and stages of job performance: Revision received November 10, 2003 Assessing differential effects for conscientiousness and its subtraits. Journal of Applied Psychology, 84, 959 –968. Accepted November 19, 2003
