Predictors of leader perfomance

MILITARY PSYCHOLOGY, 2002, 14(4), 321–338

Cognitive and Personality Predictors

of Leader Performance

in West Point Cadets

Paul T. Bartone and Scott A. Snook

Department of Behavioral Sciences and Leadership

United States Military Academy

Trueman R. Tremble, Jr.

U.S. Army Research Institute for the Behavioral and Social Sciences Alexandria, Virginia

The question of how to develop effective leaders is one of major importance to military organizations. This study, which examines a large cohort of U.S. Military Academy cadets over time, tests the influence of cognitive and personality variables on military leadership performance over a 4-year period. Hierarchical multiple regression procedures are used to identify factors at entry into the Academy that successfully predict military development grades as upperclassmen, 3 to 4 years later. A moderately stable cross-validated model reveals cognitive factors (college entrance scores, social judgment skills, and logical reasoning) and personality factors (agreeableness and conscientiousness) that contribute to later leader performance. A main effect for gender on leader performance was also identified, with women performing better than men. The amount of variance in leader performance scores accounted for by variables examined here, although modest, is notable considering the time interval involved. Nevertheless, future studies should explore additional factors, particularly personality ones, that may influence leader performance in developing leaders.

Military organizations place great emphasis on leadership and strive in various ways to train or develop effective leaders. To be successful, these training programs must be grounded in a good understanding of what factors are related to and

Requests for reprints should be sent to Paul T. Bartone, Department of Behavioral Sciences and Leadership, United States Military Academy, West Point, NY 10996. Email: paul-bartone@exmail. usma.edu

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may contribute to good leadership. Although a vast literature exists on leadership, much of it is theoretical or anecdotal in nature. Furthermore, as recently pointed out in a special report of the National Research Council, “the leadership literature is full of ambiguous theory and contradictory research findings” (Druckman, Singer, & Van Cott, 1997, p. 98). Many of the empirical studies on leadership are limited also by their cross-sectional designs, which assess possible influences on leadership as well as leader performance outcome indicators at the same point in time. The present research examines Army officer cadets over a 4-year period in order to determine the contribution of several cognitive and personality variables to leader performance over time.

Considerable research on leadership in recent years has focused on cognitive and problem-solving abilities (e.g., Jacobs & Jaques, 1987; Mumford, Zaccaro, Harding, Fleishman, & Reiter-Palmon, 1993; Phillips & Hunt, 1992) that might distinguish effective leaders from ineffective ones. In part, this emphasis on cognitive variables comes as a result of arguments that personality traits do not appear to predict leadership very well (Hollander & Julian, 1969; Stogdill, 1948), at least independently of other variables (House, 1988). However, interest has persisted in noncognitive variables that might distinguish good leaders from bad ones (Bass, 1998; Burns, 1978; House & Howell, 1992), perhaps because cognitive abilities, although important, leave much unexplained about effective leadership. In a succinct review of research and theory on military leadership, Lau (1998) suggested that some of the early lack of support for a trait or personality approach to leadership is due to limitations of measures used and that more recent studies using better measures lend support to the importance of traits (Bass, 1990). Lord, DeVader, and Alliger (1986), in a meta-analysis of 19 samples first presented by Mann (1959), also suggested that methodological factors influenced early results and conclusions. Lord et al. also point out that both Mann and Stogdill in their reviews did not examine personality traits in relation to leader performance, but rather in relation to leader emergence or “attained leadership status.” Lord et al. conclude that this early work on leadership and personality traits has been misinterpreted and that personality variables merit renewed attention.

The reemergence of personality variables is apparent in several domains related to leadership. For example, stratified systems theory, which puts heavy emphasis on cognitive abilities that become more important for leaders at the senior executive organizationallevels,hasrecentlyincorporatedvariablesthatarelessclearlycognitive into the definition of “cognitive complexity.” These variables include self-esteem (Sashkin, 1992) and something Lewis and Jacobs (1992) refer to as social perspec- tive-taking. The growing interest in the concept of “emotional intelligence” in both popular (Goleman, 1995) and professional (Salovey & Mayer, 1990) literature also suggests a tendency to incorporate personality and other noncognitive variables into an expanded definition of intelligence or mental abilities. Ryback (1998) identified potential applications of emotional intelligence to the leadership domain.

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The present study provides an exploratory examination of both cognitive abilities and personality factors as predictors of leader performance. Using data assembled on a cohort of U.S. Military Academy cadets over their 4-year college experience, we evaluate the contribution of several cognitive and personality variables collected at entry in predicting leader performance ratings 3 to 4 years later as upperclass cadets.

METHOD

Participants

A single class of U.S. Military Academy–West Point students (N = 1,143) was studied over time, from arrival in spring of 1994 until graduation 4 years later. Extensive measures were collected on this cohort, including personal background and biographical data, cognitive abilities and problem solving, personality, values, and leadership style (Evans, 1997; Tremble, 1997). Due to normal attrition, the original class cohort was reduced over 4 years by about 25%, resulting in a final study group of 855 for whom complete leader performance data were available as upperclassmen (juniors and seniors). This group was typical of recent West Point classes in terms of gender (12% women, n = 99; 88% men, n = 756), race (83% White, 17% minorities, including African American, Latino, and Asian), and age (M = 18.61 years, SD = 0.88 years).

Measures

Leader performance. As a leader performance criterion indicator, we used the West Point military development (MD) grades cumulative over the upperclass (junior and senior) years. The MD grade is a performance evaluation assigned at the end of each academic semester and summer training period and includes ratings by at least two supervisors, one a senior cadet in a direct supervisory role, and one an Army tactical officer (U.S. Corps of Cadets, 1995). In some cases (depending on the ratee’s duty position), up to two additional cadet supervisors also have input into the MD grade. In assigning MD grades, supervisors consider 12 basic leader dimensions related to a cadet’s duty performance as a leader. These are duty motivation, military bearing, teamwork, influencing others, consideration for others, professional ethics, planning and organizing, delegating, supervising, developing subordinates, decision making, and oral and written communication (U.S. Corps of Cadets, 1995). Previous work has verified the construct validity of these dimensions (Schwager & Evans, 1996). In their junior or “second class” year, cadets function as noncommissioned officers within the corps-of-cadets, typically serving in platoon sergeant or squad leader roles. They have considerable responsibility for planning and implementing a wide range of training activities for the

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cadet-soldiers in their units. In their senior or “first class” year, cadets have continued responsibility as leaders, serving in officer roles from platoon leader through battalion and brigade staff and commander positions.

This study used MD grades from two sources: the direct cadet supervisor, who is most familiar with the military and leader performance of the rated cadet; and the Army officer supervisor. Grades are assigned on a 4-point scale similar to the academic grading system, in which 1 = D, 2 = C, 3 = B, and 4 = A. Intermediate grades, such as B+ (numeric equivalent = 3.33) or A– (numeric equivalent = 3.66) are also possible. Cadet supervisor and Army officer grades for fall and spring semesters, junior and senior years, were summed to create a composite grade reflecting military performance at the upperclass level. Cronbach’s alpha coefficient for the eight scores (two raters×four semesters) was .76, sufficiently high to justify combining scores across the upperclass years.

Predictors of leader performance. All predictor measures were administered to students in the summer of 1994, just prior to freshman year. The following cognitive indicators were examined as potential predictors of leader performance:

1.Spatial judgment: A 20-item mental figure-rotation task was used to assess spatial judgment ability (Vandenberg & Kuse, 1978). This was one of several measuresdrawnfromabatteryusedinanextensiveresearchprogramonleadershipasorganizational problem solving (Management Research Institute, 1995; Mumford et al., 1993). Mumford et al. described spatial judgment as a basic cognitive ability that underlies or enables problem solving for leaders. Respondents must correctly identify geometric figures when rotated, as viewed on a printed page. The Kuder–Rich- ardson reliability coefficient for this measure is reported to be .88 (Wilson et al., 1975). High scores reflect good spatial abilities.

2.Logical reasoning: To measure this ability, this study used six verbal logical reasoning problems drawn from the Employee Aptitude Survey (F. L. Ruch & Ruch, 1980) and also used by Mumford et al. (1993). Like spatial judgment, Mumford et al. described verbal–logical reasoning as a basic cognitive ability that underlies a leader’s ability to solve problems effectively (Management Research Institute, 1995). Respondents read a series of mutually dependent statements and then answer “true” or “false” to a set of responses that might logically follow. Zaccaro, Mumford, Connelly, Marks, and Gilbert (2000) reported test–retest reliabilities for this measure that range in the .70s. W. W. Ruch, Stang, McKillip, and Dye (1994) reported an alternate forms reliability coefficient of .82. High scores reflect good logical reasoning skills.

3.Social judgment: This measure derives directly from the problem-solving model of leadership (Mumford & Connelly, 1991). Mumford et al. (1993) defined leadership as “discretionary problem solving in ill-defined social domains” (p. 25). Here, the ability to exercise sound judgment in regard to self, social, and organiza-

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tional relations is central to effective leadership. Based on this model, Mumford et al. developed a paper-and-pencil measure in which respondents are presented with two complex “organizational scenarios” and asked to answer three open-ended questions regarding each one. Answers are scored on a scale of 1 (not at all) to 6 (to a very large extent) for the following: (a) self-objectivity (knowing one’s strengths and weaknesses and able to work with or around them), (b) self-reflectivity (introspective, intuitive, good understanding of self based on past experience, learns from experience and past mistakes), (c) sensitivity to fit (knows what will work and what will not in a given situation, driven more by affect than knowledge), (d) systems perception (good understanding of others in social systems; sensitive to social needs, goals, demands at multiple levels in social systems), (e) good judgment under uncertain conditions (ability to make good decisions under ambiguous conditions and take appropriate action), (f) systems commitment (recognition of one’s and others’ roles in broader social systems, pursues socially constructive goals), and (g) overall wisdom (overall how wise the response is to the scenario). Scores on these seven dimensions are averaged to create a total social judgment score. Reported interrater reliability coefficients for this measure are .74 (Zaccaro et al., 2000; N = 840 Army officers, all ranks) and .75 (Tremble, Kane, & Stewart, 1997; N = 521 junior Army officers). Cronbach’s alpha coefficient for the seven dimensions is .88 in this sample (N = 984).

4.Problem solving: This study also used a measure of general organizational problem solving described by Tremble et al. (1997). Respondents answer three open-ended questions about two military scenarios. Answers are scored on a scale of 1 (low) to 5 (high) for the following eight dimensions: (a) shortversus long-term implications, (b) attention to restrictions, (c) nature of goals—self, (d) nature of goals—organization, (e) quality, (f) objectivity, (g) number of alternatives, and (h) originality. Scores on these eight dimensions were averaged to create a total problem solving score. Interrater reliability for this measure has been reported at .79 (Tremble et al., 1997) and .82 (Zaccaro et al., 2000).

5.College entrance equivalency rating (CEER): The CEER represents scores on standard college entrance examinations, the SAT or the ACT, converted to an equivalent scale and adjusted for academic rank of high school. Institutional research at the U.S. Military Academy led to the current CEER as the best predictor of academic performance for entering freshmen (Medsger, 1972). The mean CEER score in this sample (N = 855) is 608.71, with a standard deviation of 49.90.

Additional information on predictor measures is available in Milan, Bourne, Zazanis, and Bartone (2002).

In examining personality dimensions that might affect later leader performance, this study focused on the so-called Big Five factors of neuroticism, openness, extraversion, agreeableness, and conscientiousness (Costa & McCrae, 1985). Although direct measures were not available, NEO analog indicators created by Evans

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(1997) were available for this sample. These analog indicators are based on optimized and cross-validated regression equations developed on an earlier cohort of cadets who had completed the NEO–Personality Inventory (NEO–PI; Costa & McCrae, 1985), as well as a standard set of background questions given to all entering classes. Correlations between analog and actual NEO scales range from .52 (agreeableness) to .67 (neuroticism) in the development sample (N = 635; Evans, 1997). Evans reported good convergent and discriminant validity for these analog NEO scales. For example, analog NEO scales intercorrelate in expected ways and also show some power to discriminate dropouts from graduates (Evans, 1997, pp. 42–66). All items for the analog scales came either from the Astin Student Information Form (Astin, Korn, & Berz, 1990) or the West Point Class Characteristics Inventory (Institutional Research and Analysis Branch, 1990). Eleven items defined the analog neuroticism scale, including self-rated emotional distress, feeling depressed during the past year, and low expectation of graduating from West Point. Eleven items also comprised the analog extraversion scale, such as self-rated popularity, social self-confidence, and drive to achieve. Seventeen items made up the analog openness scale, including rated importance of writing original works, importance of developing one’s own philosophy of life, and self-rated originality. The analog agreeableness scale was composed of 14 items, such as self-rated cooperativeness, importance of helping others, and not arguing with teachers in the past year. Analog conscientiousness was made up of 11 items, including present career intentions (to follow a military career), always completing homework assignments on time, and not being late for class in the past year. (For additional technical detail on the structure and composition of these analog Five-Factor scales, see Evans, 1997.)

The data analysis strategy employed here was to evaluate first the possible influence of demographic variables (sex, race, and age) on upperclass leader performance. Next, the first-order correlations of all predictor variables with leader performance scores were examined. All variables that correlated significantly with leader performance were then entered into a hierarchical regression model, using a random half of the sample.1 After this, the same model was tested against the hold-out, cross-validation sample. Finally, these results were checked against a stepwise regression model entering in the same predictor set for the total, combined sample.

RESULTS

Table 1 displays the first-order correlations among all study variables (excluding race, a categorical variable). For race, analysis of variance showed no association

1It is possible, although unlikely, that a variable not showing a significant first-order correlation with leader performance might still emerge as a significant predictor in a regression model, when other variables are controlled for. This possibility was checked in a standard multiple regression in which all variables were entered. Results confirmed that only variables with a significant bivariate correlation with leader performance appeared as significant predictors in the regression model.

TABLE 1

Means, Standard Deviations, and First-Order Correlations Among the Study Variables

									Variable
	n	M	SD	1	2	3	4	5	6	7	8	9	10	11	12	13
1a	826	24.34	3.58	1.00
2	855	18.61	0.88	.01	1.00
3b	855	1.12	0.32	.15***	–.08**	1.00
4	849	19.44	8.40	–.03	–.03	–.25***	1.00
5	849	27.98	5.97	.07*	–.09**	–.04	.25***	1.00
6	848	2.86	0.30	.11**	–.04	.05	–.01	.07*	1.00
7	845	2.00	0.22	.04	–.01	.00	.02	.11***	.37***	1.00
8	855	608.7	49.90	.12***	–.22***	–.02	.18***	.32***	.12***	.15***	1.00
9	670	90.04	13.79	–.06	–.04	.05	–.01	–.04	–.07	–.08*	–.12*	1.00
10	648	119.6	10.46	.08*	.03	.02	–.15***	–.05	.07	.12**	–.08	–.37***	1.00
11	672	110.5	12.39	.01	.16***	.20***	–.04	.02	.10**	.13***	.00	.06	.17***	1.00
12	688	107.5	8.67	.13***	–.11**	.19***	–.08*	–.03	.13***	.04	.05	–.24***	.07	.08*	1.00
13	588	116.8	13.05	.13***	.03	.09*	–.04	.00	.06	.09*	.10*	–.66***	.47**	.00	.29***	1.00

Note. Sample sizes for correlations with personality scales range from 559 to 688. For cognitive measures, sample sizes range from 816 to 845. 1 = Composite leader performance grade; 2 = Age at entry; 3 = Sex; 4 = Mental rotation; 5 = Logical reasoning; 6 = Social judgment; 7 = Problem solving; 8 = College entrance equivalency rating (college entrance exam); 9 = Neuroticism; 10 = Extraversion; 11 = Openness; 12 = Agreeableness; 13 = Conscientiousness.

aCombined grades for four semesters covering junior and senior years, two supervisor rating sources per semester. Grades are on a 4-point scale, in which 1 = D, 2 = C, 3 = B, and 4 = A. bFor sex, 1 = male (n = 756), and 2 = female (n = 99).

*p < .05. **p < .01. ***p < .001.

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between race and military performance grades. Age also was not related to military performance in this sample. Gender was found to be associated with leader performance, with female cadets significantly higher than men on the MD composite indicator. Based on this finding, sex was entered in the first step for subsequent regression analyses.

Of the cognitive variables examined, problem solving and spatial judgment (mental figure rotation) did not correlate with leader performance and so were dropped from further consideration. Logical reasoning, social judgment, and CEER did correlate significantly with leader performance and so were kept. Of the personality variables, neuroticism and openness did not correlate with leader performance and thus were not analyzed further. Extraversion, agreeableness, and conscientiousness did correlate with leader performance and so were kept for subsequent regression analyses.

A standard hierarchical regression analysis was performed on a random half (n = 424) of the sample, with sex entered by itself in Step 1, followed by the cognitive variables in Step 2 (logical reasoning, social judgment, and CEER college entrance scores), and the personality variables in Step 3 (extraversion, agreeableness, and conscientiousness). The dependent variable was leader performance, as measured by the composite MD grade for junior and senior years. Probability for inclusion was .05 and for exclusion was .10. The overall model was highly significant, F(7, 417) = 3.8, p < .001, with a multiple R of .25. As can be seen in Table 2, each step resulted in a significant increase in the R2. The final model shows sex, CEER, social judgment, and agreeableness as significant predictors, with extraversion approaching significance (p < .08).

The same hierarchical regression analysis was performed on the hold-out, validation sample (n = 429), with quite similar results (Table 3). In this case, sex and college entrance scores again emerge as significant predictors of leader performance. However, social judgment is no longer a significant predictor, and conscientiousness (p < .06) replaces agreeableness in the equation. Logical reasoning approaches significance at .07. In addition, in the case of the second model, the personality set (extraversion, agreeableness, and conscientiousness) entered on Step 3 results in a small but not significant change in the R2.

It should be noted that there is some multicollinearity within the predictor set, as can be seen in Table 1. This may account for differences obtained across the two regression models and samples. For example, logical reasoning correlates with social judgment (r = .07, p < .05), and agreeableness is correlated with conscientiousness (r = .29, p < .001). In addition, agreeableness correlates with sex (r = .19, p <

.001), with women being higher in agreeableness. In the second (validation) model, the entry of sex at Step 1 accounts for substantially more of the variance in leader performance grades (R = .18, p < .001) than it does in the first model (R =

.12, p < .01). This suggests that multicollinearity between sex and agreeableness may partly explain the nonsignificant contribution of agreeableness in the

		PREDICTORS OF LEADER PERFORMANCE				329
		TABLE 2
Hierarchical Multiple Regression Predicting Leader Performance
	as Upperclassmen for the Test Sample
	β				Significance
Predictor		T	p	R2	∆R2	∆R2
Step 1: Demographics
Sex	.12	2.4	.01	.01	.01	.02
Step 2: Cognitive
Sex	.12	2.5	.01
Logical reasoning	–.02	–0.3	.76
College entrance exam	.09	1.8	.07
Social judgment	.12	2.5	.01	.04	.03	.01
Step 3: Personality
Sex	.10	2.1	.04
Logical reasoning	–.01	–0.2	.86
College entrance exam	.10	1.9	.06
Social judgment	.11	2.2	.03
Extraversion	.09	1.7	.08
Agreeableness	.12	2.4	.02
Conscientiousness	–.01	–0.2	.83	.06	.02	.02

Note. Hierarchical regression, variables entered in three blocks; mean substitution for missing data. Model: F(7, 417) = 3.85, p < .001; Multiple R = .25; R2 = .06.

TABLE 3

Hierarchical Multiple Regression Predicting Leader Performance as Upperclassmen for the Validation Sample

	β					Significance
Predictor		T	p	R2	∆R2	∆R2
Step 1: Demographics
Sex	.18	3.8	.001	.03	.03	.001
Step 2: Cognitive
Sex	.17	3.7	.001
Logical reasoning	.09	1.8	.07
College entrance exam	.11	2.1	.03
Social judgment	.05	1.0	.32	.06	.03	.01
Step 3: Personality
Sex	.17	3.5	.001
Logical reasoning	.09	1.8	.07
College entrance exam	.10	2.0	.05
Social judgment	.04	0.9	.39
Extraversion	–.01	–0.09	.93
Agreeableness	.01	0.2	.86
Conscientiousness	.10	1.9	.06	.07	.01	.18

Note. Hierarchical regression, variables entered in three blocks; mean substitution for missing data. Model: F(7, 422) = 4.71, p < .001; Multiple R = .27; R2 = .07.

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				TABLE 4
	Stepwise Multiple Regression Predicting Leader Performance
		as Upperclassmen for the Total Sample
		β					Significance
Predictor			T	p	R2	∆R2	∆R2
Sex		.14	4.2	.001	.02	.02	.001
College entrance exam		.10	3.1	.01	.03	.01	.001
Social judgment		.08	2.4	.02	.04	.01	.01
Conscientiousness		.08	2.4	.02	.05	.01	.02

Note. Stepwise multiple regression, total sample (N = 854); p to enter ≤ .05; p to remove ≥ .10; mean substitution for missing data. Model: F(4, 850) = 11.1, p < .001; Multiple R = .22; R2 = .05.

validation model. This interpretation is supported by a stepwise regression done with the total sample and same predictor set but excluding sex. Here, both agreeableness and conscientiousness emerge as significant (independent) predictors of leader performance, along with social judgment and college entrance scores. As a final check on these findings, a stepwise regression model was computed on the total sample using the same predictor set as in the hierarchical models, including sex. The resulting model, F(4, 850) = 11.1, p < .001, multiple R = .22, revealed sex, college entrance scores, social judgment, and conscientiousness as significant independent predictors of leader performance (Table 4), lending further support to the previous interpretation of overlapping variance between sex and agreeableness.

DISCUSSION

This study found that both cognitive and personality variables, assessed prior to freshman year, can predict leader performance 3 to 4 years later in West Point cadets. A modest but significant proportion of the variance in leader performance as rated by both officer and peer supervisors is explained by the predictor variables examined here. Although much of the variance in leader performance remains unexplained by the current predictor set, these findings nonetheless point the way for additional studies aimed at identifying both cognitive and personality factors that may influence leader performance.

First, cognitive abilities are found to be important to leader performance as upperclassmen. The college entrance exam scores, a measure of general intellectual ability assessed as part of the college application process, is a consistent predictor of later leader development scores for West Point cadets. Logical reasoning shows some predictive power but is not significant as an independent predictor. Problem solving and spatial abilities measures did not predict leader performance in this group. At least at the college level, then, although general intellectual abilities ap-