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Personal reflection on the article consisting of your personal opinions, thoughts, and/or experiences related to the topic

Personal reflection on the article consisting of your personal opinions, thoughts, and/or experiences related to the topic

 

A good article review will include the following:

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  • A ½ page (minimum) personal reflection on the article consisting of your personal opinions, thoughts, and/or experiences related to the topic

Your complete assignment will be 1 page per article, 2 pages total. Each article is worth 1.5 points.

European Journal of Personality, Eur. J. Pers. 25: 31–42 (2011) Published online 4 April 2010 (wileyonlinelibrary.com) DOI: 10.1002/per.769

Personality and the Prediction of Team Performance

THOMAS A. O’NEILL* and NATALIE J. ALLEN

Department of Psychology, The University of Western Ontario, London, Ontario, Canada

Abstract: Although much is known about personality and individuals’ job performance, only a few studies have considered the effects of team-level personality on team performance. Existing research examining the effects of personality on team performance has found that, of the Big Five factors of personality, Conscientiousness is often the most important predictor. Accordingly, we investigated the criterion validity of lower-level Conscientiousness traits to determine whether any one trait is particularly predictive of team performance. In addition to Conscientiousness, we examined the criterion validity of the other Big Five personality factors. We found that Conscientiousness and its facets predicted team performance. Agreeableness, Extraversion and Neuroticism were not predictive of team performance, whereas Openness had a modest negative relation with team performance. Copyright # 2010 John Wiley & Sons, Ltd.

Key words: team performance; team composition; personality; Big Five; narrow traits; personality facets

INTRODUCTION

The composition of a work team is defined by the individual characteristics of its members. One implicit rationale underlying the research on team composition is that individual characteristics of team members (i.e. their personalities, demographic characteristics, attitudes and so on) serve as inputs that indirectly influence team perform-

ance through group processes (e.g. collaboration) and emergent states (e.g. team cohesion). In other words, the characteristics of team members affect the way in which a team operates and its subsequent performance.

Personality, as a class of team composition variables, is the focus of the present study. Over the past several years, research on personality has received considerable attention in the teams literature (e.g. Bell, 2007; Humphrey, Hollenbeck, Meyer, & Ilgen, 2007; Peeters, van Tuijl, Rutte, & Reymen, 2006). Interest in this topic continues for at least two reasons. First, there is an intuitive appeal to the argument that personality will influence team-related variables. Conceptually, personality should be related to (a) team knowledge, skills and abilities, (b) processes and emergent states and (c) general dimensions of teamwork (e.g. collaboration, supportive behaviour, team trust). Most of these variables appear to be natural outgrowths of personality and, therefore, one would expect personality to be a valid predictor in many cases (see Halfhill, Sundstrom, Lahner, Calderone, & Nielsen, 2005; Kichuk & Wiesner, 1998).

A second reason that personality continues to be investigated in team settings is that it is a consistent and important predictor of individuals’ job performance (e.g. Barrick & Mount, 1991; Tett, Jackson, Rothstein, & Reddon,

*Correspondence to: Thomas A. O’Neill, Department of Psychology, Social Science Centre, The University of Western Ontario, London, Ontario N6A 5C2, Canada. E-mail: [email protected]

Copyright # 2010 John Wiley & Sons, Ltd.

1999). Extending these findings to the team level is needed as organizations are increasingly turning to teamwork in an effort to stay competitive in the global marketplace (Allen & West, 2005; Kozlowski & Ilgen, 2006). Thus, research on personality and team performance is an ongoing priority.

In this study, we collected personality data from members of project design teams, operationalized those data at the group level (e.g. using the group mean on each trait), and correlated the resulting team-level personality scores with team performance. Our purpose in this research was threefold. First, we examined the extent to which any content-relevant personality facets of Conscientiousness could demonstrate superior prediction of team performance relative to a broad Conscientiousness composite. An investigation of this type is needed given that Conscien- tiousness has been shown to be one of the most consistent Big Five predictors of job performance and team performance, but the criterion validity of its facets have rarely been examined at the team level (but see LePine, 2003). Second, we investigated whether any personality factors besides Conscientiousness could be valid predictors of team performance in the present context. Specifically, we assessed the criterion validity of the other Big Five factors: Agreeableneness, Extraversion, Neuroticism and Openness. Third, when considered as a team-level construct, personality has historically been operationalized in several ways. In this study we provide new evidence regarding the criterion validity of the four most common team-level personality operationalizations.

TEAM-LEVEL PERSONALITY

Typically, the operationalization of personality variables at the team level is accomplished by aggregating individual- level personality scores using one of four group-level

Received 29 July 2009 Revised 16 February 2010, Accepted 16 February 2010

32 T. A. O’Neill and N. J. Allen

indices: Mean, variance, minimum and maximum scores (see Barrick, Stewart, Neubert, & Mount, 1998; Halfhill et al., 2005; Williams & Allen, 2008). The particular operationalization is usually chosen through a consideration of the personality variable, the nature of the task, and how the two are expected to interact (e.g. Allen & West, 2005; Hecht & Allen, 1999; LePine, Hollenbeck, Ilgen, & Hedlund, 1997).

The mean approach involves computing the arithmetic average of each team member’s score on the personality variable. This approach is appropriate when the trait is theorized to work additively—that is, when it is suspected that the more (or less) team members possess the trait, the better the team will perform. The variance approach indexes the dispersion, or heterogeneity, of the trait across team members. This operationalization is used when the researcher believes a greater (or lesser) amount of variation in the trait will be related to the criterion. Finally, sometimes it is appropriate to consider only the team member with the highest, or lowest, score on a trait (referred to as the maximum or minimum approach, respectively), and refer to that value as the team-level score. As an analogy, on an assembly line, the number of units produced will often depend on the slowest working team member, and, accordingly, the minimum score on a trait such as Achievement could be most predictive of team performance. Conversely, on a creativity task, the team member with the highest score on a trait such as Innovation could be most responsible for the level of team performance achieved (because a novel idea has only to come from one team member). Theorizing about the most appropriate operationalization for team personality is critical as these may substantially affect the magnitude of person- ality’s criterion validity (Moynihan & Peterson, 2004; Williams & Allen, 2008).

In the most recent and comprehensive meta-analysis examining relations between team-level personality and performance, Bell (2007) found that, overall, team-level personality does predict team performance. The findings for lab studies were generally weak, likely because team performance measurement in those studies tended to be too coarse to detect small variations in behaviour related to expressions of personality. Field studies in Bell’s meta-

analysis, however, demonstrated the strongest and most consistent findings for Conscientiousness. Teams with high means, high team member maximum and minimum scores and low variance had the greatest performance levels (Emotional Stability was coded in the socially desirable direction). Other Big Five factors were predictive of team performance, but not with the same magnitude and consistency across operationalizations.

Given that Conscientiousness was the most consist- ently predictive trait of team performance in Bell’s (2007) meta-analysis, it is reasonable to consider that facets of Conscientiousness might even be more predictive (see Dudley, Orvis, Lebiecki, & Cortina, 2006). For example, the factor of Conscientiousness encompasses several more specific facets of personality, such as Industrious- ness, Order, Self-Control, Responsibility, Traditionalism and Virtue (see Roberts, Chernyshenko, Stark, & Gold-

berg, 2005). Arguably, some of these lower-level personality variables belonging to the same higher-level personality factor may correlate differently, in magnitude or direction, from the others in the prediction of a criterion (see Ashton, 1998; Ashton, Jackson, Paunonen, Helmes, & Rothstein, 1995; Hough, 1992; LePine, 2003; Paunonen, 1998, 2003). Reflecting on Bell’s meta-

analytic findings, as well as the literature demonstrating the validity of narrow traits, we suggest that, in order to maximize the predictive power of Conscientiousness as it relates to team performance, criterion-relevant facets ought to be considered.

The fact that personality variables other than Conscien- tiousness (e.g. Agreeableness) were predictive of team performance in Bell’s meta-analysis suggests that they, too, may be relevant in the present study. As we will argue later, our criterion, project team performance, could be associated with certain team-level operationalizations of Agreeable- ness, Extraversion, Neuroticism and Openness. Finally, the method of operationalizing team personality (e.g. mean, minimum) that will be most predictive of team performance must also be considered in maximizing criterion validity. In the section that follows we develop our predictions regarding the operationalization that is, in the context of our study, most theoretically appropriate for each personality factor and facet included in this study.

THE PRESENT STUDY

Our sample consisted of concept design teams, composed of engineering students, who worked interdependently for 6.5 months. The teams were engaged in an intensive, complex engineering design task. The team members had shared outcomes of significant value, and coordinated most work dynamically and reciprocally (rather than through pooled or sequential processes). These were classic ‘project teams’ as they were created for a specific purpose and time frame, after which they would disband (see Chiocchio & Essiembre, 2009). Knowledge of these contextual details was important in generating predictions, outlined below.

The Big Five

In the present research we assessed the Big Five factors of personality. In order to optimize their prediction of team performance, we judged it most appropriate to operationalize the Big Five factors, at the team-level, as follows: Conscientiousness (mean), Agreeableness (mean), Neuroti- cism (mean), Extraversion (variance) and Openness (maxi-

mum). Important theoretical rationales underlie the choice of team personality operationalizations. Beginning with Con- scientiousness, we contend that this factor captures a class of attributes that manifest themselves as valuable resources, such as achievement-striving, organization, planning and task focus. The team may draw upon resources of this type to accomplish its work (see LePine et al., 1997; Stewart, 2003). An additive team-level conceptualization, using the mean approach, is most appropriate in the present research because

Copyright # 2010 John Wiley & Sons, Ltd. Eur. J. Pers. 25: 31–42 (2011) DOI: 10.1002/per

Personality and team performance 33

the more team members are conscientious, the better the team should perform (see also Barrick et al., 1998). Similarly, Agreeableness represents a factor of personality that can be expected to foster effective team interactions because members are trusting, altruistic and cooperative. Such teams could perform well because of their smooth conflict resolution, and inclination towards open communi-

cation and information seeking (Peeters et al., 2006). We also see Agreeableness as accumulating additively, as the more members are characterized as agreeable, the more they should have positive interactions, and in turn, create a higher performing team. Regarding the personality factor Neuroti- cism, most previous studies have found important relations with team performance for the mean only (see Bell, 2007). As Neuman, Wagner and Christiansen (1999) pointed out, teams that are higher on Neuroticism will have difficulty coordinating one another’s tasks and may experience disruption from tempermental and/or impulsive team members (see also Driskell, Hogan, & Salas, 1987). Thus, we predicted that the mean operationalization of Neuroti- cism would be most predictive of team performance relative to other operationalizations.

Turning to Extraversion, we expected that the variance operationalization would be the strongest predictor of team performance for that trait. A team comprising all extraverts could be expected to have high conflict as its members will all be assertive and leadership oriented, and therefore, power struggles are likely to emerge (see Barry & Stewart, 1997). Conversely, a team composed of all introverts would likely not perform well because members may not converse enough to generate a compelling design idea and stay coordinated during project work. A mix of introverts and extraverts (i.e. heterogeneity) may characterize effective teams because there will likely be fewer leadership battles, but enough communication to keep the team coordinated and on track towards effective task completion (see Mohammad & Angell, 2003). Thus, we operationalized Extraversion using the variance approach.

Finally, Openness was operationalized as the maximum score. Given that the engineering projects in the present study required that teams generate novel solutions to design problems of their choosing, generating a creative solution or approach to the project was critical. However, only one team member is likely needed to generate an idea that other group members can subsequently develop (see Valente, 1995). Original and innovative ideas might be expected to come

from the member highest on Openness, which calls for the maximum operationalization.

Conscientiousness facets

Recall that one purpose of this research was to investigate whether any lower level personality facets, within the Conscientiousness domain, would be especially predictive of team performance. Regarding the selection of these narrow, facet-level traits, we chose a subset that we expected, on an a priori basis, to predict team performance on the project teams’ tasks. To select the traits, we considered three sources of content-relevant information that have been shown to lead to effective a priori selection of criterion-relevant person- ality traits (for a review, see O’Neill, Goffin, & Tett, 2009). We began with a large pool comprising 35 narrow personality traits found in two highly regarded and established personality instruments: the Personality Research Form (PRF; Jackson, 1989) and the Jackson Personality Inventory-Revised (JPI-R; Jackson, 1994). A sample of subject matter experts, comprising eight indus- trial-organizational psychology faculty and graduate stu- dents, rated the extent to which each trait would be most likely to predict team performance (i.e. trait relevance for predicting team performance; see also Goffin et al., 2009; Paunonen & Ashton, 2001). These traits were a mix of Conscientiousness-related and unrelated traits, but only those with content overlapping with Conscientiousness were considered in this research for reasons explained earlier. Second, we examined the literature, including literature reviews, theoretical articles, and empirical studies (e.g. English, Griffith, & Steelman, 2004). Third, the character- istics of the project teams’ tasks, and surrounding context, were taken into account, and traits were aligned to this context by theorizing about how they might relate to team performance. Overall, this approach was consistent with commonly used methods of identifying potentially job- related personality traits (see Goffin et al., 2009; Raymark, Schmit, & Guion, 1997; Tett & Guterman, 2000).

The result of the process outlined above was the selection of four facets of Conscientiousness, to each of which we assigned a specific trait operationalization for comparison with the Big Five at the team level: Organization (maximum), Cognitive Structure (maximum), Achievement (mean) and Endurance (mean; see Table 1 for trait definitions). These traits were identified by Ashton, Jackson,

Table 1. Narrow trait definitions

Personality variable Description

Organization Concerned with keeping personal effects and surroundings neat and organized; dislikes clutter, confusion, lack of organization; interested in developing methods for keeping materials methodically organized.

Cognitive structure Does not like ambiguity or uncertainty in information; wants all questions answered completely; desires to make decisions based upon definite knowledge, rather than upon guesses or probabilities.

Achievement Aspires to accomplish difficult tasks; maintains high standards and is willing to work towards distant goals; responds positively to competition; willing to put forth effort to attain excellence.

Endurance Willing to work long hours; doesn’t give up quickly on a problem; persevering, even in face of great difficulty; patient and unrelenting in work habits.

Note: Definitions modified from Jackson (1989, 1994).

Copyright # 2010 John Wiley & Sons, Ltd. Eur. J. Pers. 25: 31–42 (2011) DOI: 10.1002/per

34 T. A. O’Neill and N. J. Allen

Helmes, and Paunonen (1998) as scales that chiefly define the Conscientiousness factor. Important theoretical ration- ales for each trait and team-level operationalization accompanied these decisions, which are described next.

Organization was expected to be important for team performance as individuals high on this trait should use their time wisely and avoid procrastination. However, we predicted that only one team member needed to be high on Organization in order to manage the team and keep the work structured and on schedule; thus, we operationalized Organization using the maximum score within the team. We also predicted that Cognitive Structure would be important because individuals high on this trait want to carefully plan out and research all aspects of a task before getting started. Again, we expected that only one team member needed to engage in this systematic planning and forethought to ensure that the team effectively structured its work and adapted it as needed over time. Accordingly, we selected the maximum operationalization for Cognitive Structure.

Those who are high on Achievement tend to set difficult goals by choosing challenging tasks that they find engaging (Gellatly, 1996). We surmised that these attributes are valuable qualities for any team members to possess, and that the more team members are Achievement-oriented, the more likely the team is to perform at a superior level. This additive rationale supports the mean operationalization. We also predicted that Endurance would be a valuable trait for all team members to have. The more Endurance team members have, the higher their team’s performance because members will be more likely to devote long hours at various milestones of the project lifecycle (e.g. prototype design, prototype construction). Thus, the mean approach was used for operationalizing Endurance.

METHOD

Participants, procedure, and description of teamwork context

Team personality and performance data were collected from 129 student engineering design teams comprised of three, four or five team members each. The mean age of the 564 respondents was 18.6 (SD ¼ 2.2), and 81% were male. Data were collected at two points: First, on the day that the project teams were assembled, personality and demographic data were collected; second, approximately 6.5 months later, when the teams completed their work, team performance data were collected.

Teams participating in this study carried out a complex design project. Specifically, the project required teams to develop a functional prototype that either (a) demonstrated and explained a physical law in an innovative way that would have pedagogical value in a secondary school setting, or (b) represented an innovative concept that could help protect the environment. In addition to building a physical prototype demonstrating their design concepts, the project required teams to produce a detailed report of their work and to deliver a public ‘science fair’ presentation of the prototype.

Outcome interdependence was high given that instructor ratings of team performance constituted 20% of students’ final course grades.

It should be noted that team members spent a great deal of time interacting with one another over the course of the 6.5 months. In addition to completing the large design project, teams worked on small course-related projects and tasks almost every week for the duration of the 6.5 months. They met for at least 2 hours per week in mandatory laboratory sessions where they completed required tasks and assign- ments together. Most of these teams also met extensively outside of class time, especially during the 3 months prior to completing the large design project that was our focal interest in the present research.

Measures

Personality: Narrow traits The following narrow trait scales from the PRF (Jackson, 1989) and JPI-R (Jackson, 1994) were administered: Achievement (PRF), Endurance (PRF), Organization (JPI- R) and Cognitive structure (PRF). Original scales included 20 items (JPI-R) or 16 items (PRF), but, because of time constraints, we could administer scales that were only eight items long. To select items, we retained an equal number of positively- and negatively-keyed items. We also retained items that were context-relevant, such as those that refer to work styles and behaviour at work. Ratings were provided on a typical five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree).

Personality: Broad traits Participants completed a version of Goldberg’s (1999) International Personality Item Pool (IPIP) measure of the Big Five personality factors, as described in Johnson (2001; see also Hastings and O’Neill, 2009). The measure includes 24 items for each of the Big Five and uses the usual five-point Likert scale ranging from 1 (very inaccurate) to 5 (very accurate). The content measured is intended to reflect the same content as is found in the NEO-PI-R (Costa & McCrae, 1992), and, supportively, high convergent correlations have been reported (see Goldberg, 1999; Johnson, 2001).

Team performance Team performance consisted of a composite of ratings on several key dimensions associated with the design project. These included Problem Definition, Design Methodology, Engineering Validation (i.e. appropriate application of engineering design principles), Design Documentation, and Technical Writing. Team performance ratings were provided by experienced course administrators. Because administrators did not rate the same teams, interrater reliability could not be assessed. Thus, we adopted procedures typically used in similar situations (e.g. Wage-

man & Gordon, 2005). Specifically, to control for the possibility that raters used different performance distri- butions (i.e. mean and variance of distributions), we standardized the composite performance scores within rater.

Copyright # 2010 John Wiley & Sons, Ltd. Eur. J. Pers. 25: 31–42 (2011) DOI: 10.1002/per

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Personality and team performance 35

RESULTS

Cronbach’s as were calculated on the full sample of individual participants. Reliabilities for the narrow traits ranged from .65 to .74, whereas for the Big Five they fell between .81 and .88. Intercorrelations of team-level personality operationalizations are displayed in Table 2. That table shows that, whereas within-trait operationaliza- tions tend to be correlated and are somewhat interdependent, these correlations are not sufficiently large to suggest completely overlapping constructs (see also Barrick et al., 1998). Table 3 presents the mean and variance for each team-

level personality operationalization, as well as the zero-order correlations among team-level personality and team per- formance. Table 3 also identifies the trait operationalizations

Table 2. Team-level personality correlation matrix

that were expected to show the strongest team personality- performance relations for each trait (see underlined values) and the strongest observed correlations (see boldfaced values).

Criterion validity of conscientiousness and selected conscientiousness facets

The criterion validity of the Conscientiousness scale was generally supported across operationalizations (see Table 3). The mean was the strongest predictor of team performance, r ¼ .27, followed by the maximum, r ¼ .21, and the minimum, r ¼ .19. In contrast to findings in Bell’s (2007) meta-analysis, the variance was not predictive of team performance in this study.

1 2 3 4 5 6 7 8 9 10 11 12 13

Organization 1. Mean 2. Variance .06 3. Minimum .76 .57 4. Maximum .71 .56 .30 Cognitive Structure 5. Mean .44 .03 .27 .27 6. Variance .11 .19 .20 .04 .08 7. Minimum .34 .14 .32 .14 .67 .73 8. Maximum .25 .11 .07 .26 .68 .56 .11 Achievement 9. Mean .44 .12 .35 .24 .30 .05 .14 .24 10. Variance .14 .26 .28 .06 .03 .12 .05 .18 .13 11. Minimum .43 .21 .44 .18 .24 .02 .16 .12 .80 .61 12. Maximum .27 .10 .08 .28 .26 .12 .07 .33 .72 .51 .34 Endurance 13. Mean .33 .10 .06 .27 .32 .11 .12 .31 .42 .11 .27 .40 14. Variance .15 .24 .27 .04 .01 .08 .07 .08 .01 .47 .25 .29 .08 15. Minimum .36 .07 .32 .20 .27 .03 .17 .19 .37 .27 .46 .14 .69 16. Maximum .13 .25 .08 .24 .21 .11 .05 .27 .31 .39 .04 .51 .75 IPIP Conscientiousness 17. Mean .66 .00 .47 .49 .50 .03 .31 .34 .49 .10 .47 .37 .43 18. Variance .00 .25 .13 .17 .06 .20 .13 .13 .04 .21 .15 .08 .01 19. Minimum .48 .14 .44 .28 .35 .16 .31 .12 .40 .26 .50 .22 .29 20. Maximum .50 .18 .26 .53 .32 .06 .16 .33 .36 .04 .30 .39 .36 IPIP Extraversion 21. Mean .05 .08 .07 .03 .22 .06 .21 .12 .14 .07 .18 .07 .23 22. Variance .00 .13 .12 .06 .06 .05 .07 .01 .01 .08 .02 .12 .04 23. Minimum .04 .04 .04 .04 .18 .08 .19 .10 .12 .03 .11 .16 .15 24. Maximum .11 .15 .20 .02 .14 .03 .15 .08 .15 .14 .18 .02 .11 IPIP Agreeableness 25. Mean .16 .05 .15 .09 .11 .09 .12 .05 .25 .17 .27 .09 .18 26. Variance .06 .00 .05 .05 .01 .01 .03 .04 .01 .19 .09 .12 .03 27. Minimum .08 .05 .09 .02 .06 .09 .09 .03 .17 .24 .23 .04 .08 28. Maximum .14 .07 .13 .07 .08 .11 .12 .06 .19 .03 .12 .17 .14 IPIP Neuroticism 29. Mean .05 .07 .02 .14 .07 .09 .15 .03 .05 .07 .06 .06 .22 30. Variance .10 .05 .16 .08 .07 .07 .14 .08 .02 .15 .11 .05 .07 31. Minimum .06 .12 .15 .07 .11 .07 .19 .03 .04 .20 .15 .14 .14 32. Maximum .08 .01 .13 .11 .01 .02 .02 .05 .01 .07 .07 .00 .16 IPIP Openness 33. Mean .11 .07 .04 .14 .09 .03 .04 .08 .02 .02 .03 .06 .14 34. Variance .09 .21 .20 .06 .01 .10 .06 .13 .03 .17 .08 .13 .07 35. Minimum .01 .21 .14 .16 .05 .07 .00 .16 .03 .11 .09 .05 .05 36. Maximum .14 .08 .17 .06 .08 .02 .08 .00 .02 .13 .06 .13 .10

Copyright # 2010 John Wiley & Sons, Ltd. Eur. J. Pers. 25: 31–42 (2011) DOI: 10.1002/per

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