HUMAN PERFORMANCE, 20(4), 317–343
Copyright © 2007, Lawrence Erlbaum Associates, Inc.
Beyond the Big Five: Leader
Goal Orientation as a Predictor
of Leadership Effectiveness
Joseph W. Hendricks and Stephanie C. Payne
Texas A&M University
This study examined proximal traits as mediators of the relationships between distal
traits and leadership effectiveness. Specifically, we examined goal orientation, leadership self–efficacy, and motivation to lead (MTL) as antecedents of leadership effectiveness, after controlling for the Big Five personality traits. We tested our hypotheses with a sample of 100 leaders of four-person teams performing a manufacturing
task in a laboratory setting. Consistent with expectation, leadership self-efficacy
partially mediated the relationships between learning goal orientation and Affective-Identity MTL as well as Social-Normative MTL, after controlling for the Big
Five. Noncalculative MTL related significantly to averaged team member ratings of
leadership effectiveness, after controlling for both the leader’s and the team member’s personality. These results help aid in our understanding of why leader traits relate to leadership effectiveness.
The study of leadership in organizations has been prevalent since the beginning of
the 19th century. Thousands of research studies have focused on leadership phenomenon (Yukl, 1989) in part to enhance our ability to predict leadership effectiveness. A recent meta-analysis revealed that cumulatively the Big Five personality
variables have a multiple correlation of .39 with leadership effectiveness (Judge,
Bono, Ilies, & Werner, 2002). Although their work aided in demonstrating an empirical relationship between the Big Five and leadership criteria, their examination
did not reveal why these relationships exist. As a result, the question of why individual differences predict leadership effectiveness remains unanswered.
Whereas the Big Five classification captures a broad array of dispositional
traits, it is not a comprehensive taxonomy of all individual difference characterisCorrespondence should be sent to Joseph W. Hendricks, Mail Stop 4235, Texas A&M University,
College Station, TX, 77843–4235. E-mail: jwh@neo.tamu.edu
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tics that have been or could be related to leadership effectiveness. For example, one
motivational construct that has not been extensively explored as an antecedent of
leadership effectiveness is goal orientation (Dweck, 1986). Goal orientation describes an individual’s predisposition to set certain types of goals in achievement
situations. We propose that goal orientation is indirectly related to leadership effectiveness through more proximal individual difference characteristics. Thus, the
purpose of the study presented here is to examine the extent to which goal orientation predicts leadership effectiveness above and beyond the Big Five.
We also respond to calls for research to explain why leader traits predict leadership effectiveness (e.g., Judge et al., 2002). To do this, we build on Chan and
Drasgow’s (2001) theoretical framework for explaining the role of individual differences in leadership development. Specifically, we propose that goal orientation
dimensions indirectly relate to leadership effectiveness, through the mediating
variables leadership self-efficacy (LSE) and motivation to lead (MTL) as depicted
in Figure 1. We include the Big Five personality variables as the most distal traits
inferring that their influence is further mediated by goal orientation. After briefly
reviewing trait theory, we describe goal orientation and these mediating variables
that help to explain why we expect goal orientation to relate to leadership
effectiveness.
TRAIT THEORY OF LEADERSHIP
Trait approaches for explaining leadership behavior and effectiveness have had the
longest and arguably least successful history compared to other leadership theories. Efforts to identify a list of essential leader traits were not very fruitful. There
were a number of limitations to early trait leadership research that contributed to
the lack of empirical support for trait theory.
First, researchers focused on individual, bivariate correlations between individual traits and leadership (Lord & Hall, 1992). Also, until relatively recently, we
lacked a well-accepted model of personality to aid in the development of trait models of leadership (House & Aditya, 1997). Thus we take a more holistic approach
simultaneously examining multiple individual differences as predictors of leadership effectiveness including the broad Big Five personality traits. Further, we examine both leader and team member traits in an effort to determine if leader traits
predict leadership effectiveness beyond group member traits (Piccolo & Judge,
2006).
Second, previous trait studies lacked a theoretical explanation for why certain
traits predict leadership. Yukl (1998) advocated seeking processes that mediate the
relationship between traits and leadership effectiveness. “Traits offer the potential
to explain why people seek leadership positions and why they act the way they do
when they occupy these positions” (Yukl & Van Fleet, 1992, p. 153). We build on
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FIGURE 1
Model of hypothesized relationships among leader proximal and distal traits and leadership effectiveness.
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Chan and Drasgow’s (2001) framework, which proposed LSE and MTL as important mediators of the relationships between more stable/distal individual differences and leader effectiveness.
Third, trait researchers did not differentiate between three leadership criteria:
leadership perceptions, leader emergence, and leadership effectiveness (Lord,
DeVader, & Alliger, 1986). In the study presented here, we focus on leadership effectiveness, which can be defined as (a) how well the leader facilitates “the movement of a group of people toward a common goal or objective” (House &
Podsakoff, 1994, p. 46), as well as (b) the consequences of the leader’s actions (i.e.,
team outcomes; Yukl, 1998). The former indicator is typically an aggregation of
subjective ratings provided by each of the individual followers that have been
shown to empirically converge. The latter indicator is usually a more objective and
distal measure than the former.
In summary, our study builds on Chan and Drasgow’s (2001) integrative theoretical framework for understanding the relationship between individual differences and leadership effectiveness. It also addresses limitations of previous
trait-based leadership studies by including multiple individual differences for the
leader and the team members, examining theoretically driven mediator variables,
and focusing on leadership effectiveness. We now turn to the individual difference
characteristics we propose as distal antecedents of leadership effectiveness.
GOAL ORIENTATION
Goal orientation describes an individual’s disposition to set certain types of goals
in achievement-related settings affecting what type of feedback is sought and how
feedback is interpreted. This disposition influences behavior on task performance
by affecting the way in which a person reacts to task difficulty (Brett &
VandeWalle, 1999; Dweck, 1986; Dweck & Leggett, 1988; Elliott & Dweck,
1988; Farr, Hofmann, & Ringenbach, 1993). Taking a social–cognitive approach
to motivation (e.g., Markus, 1977), Dweck and Leggett described two different
types of goals. Performance goals are goals to successfully complete a task and are
norm-referenced. Individuals with a strong performance goal orientation (PGO)
are concerned with judgments of peers as well as superiors and want to be able to
succeed at whatever tasks they perform. They will often engage in tasks they know
they can complete or set goals they know are obtainable. In addition, these individuals are characterized as having a fear of failure and experiencing escapist
thoughts or thoughts of quitting the task at hand (Button, Mathieu, & Zajac, 1996).
Learning goals are goals to further develop knowledge or skills with the intention
to ultimately “master” the given task and are self-referenced. Individuals with a
strong learning goal orientation (LGO) have the desire to learn about new material
GOAL ORIENTATION AND LEADERSHIP
321
and master task performance. They are not concerned with their relative performance to others but their absolute performance and furthering their understanding
of some content or task (Dweck & Leggett, 1988).
Initially these goals and corresponding goal orientations were conceptualized
as two different ends of the same continuum. Now, however, they are believed to be
separate dimensions (Button et al., 1996; Payne, Youngcourt, & Beaubien, in
press). In fact, the dimensionality of the PGO dimension has been further examined (Elliot & Harackewitz, 1996; VandeWalle, 1997). For example, VandeWalle
divided PGO into two separate dimensions, performance-prove (PPGO) and performance-avoid goal orientations (PAGO). He suggested the division is a better
representation of the divergent response patterns typically associated with a strong
PGO. The PPGO dimension describes efforts of individuals to try to appear better
than their reference group. The PAGO dimension describes efforts of individuals
to avoid negative evaluations and criticisms of others.
Previous Goal Orientation and Leadership Studies
Little research has been conducted linking goal orientation to leadership, and no
studies have examined leader goal orientation as an antecedent of leadership effectiveness. Instead, most research linking these two constructs has focused on the extent to which leadership variables predict followers’ goal orientation (e.g.,
Dragoni, 2005; Gorenflo-Gilbert, 1999; Schwager, 1997). We found only one
study that examined leader’s goal orientation as an independent variable. Although
not specifically hypothesized, McCormick (1999) found leader LGO was significantly related to both pre- and posttraining LSE. The study presented here extends
this research by also examining the leader’s PGO, MTL, and leadership
effectiveness.
MEDIATORS OF THE INDIVIDUAL
DIFFERENCE-LEADERSHIP EFFECTIVENESS
RELATIONSHIP
Recently, Chan and Drasgow (2001) proposed a theoretical framework for understanding the role of traits in leadership behavior by integrating the process of
leader development with leader performance. Their framework proposed that
noncognitive individual differences such as personality relate to leader effectiveness through the leader’s LSE and MTL, which in turn relate to participation in
leadership roles and activities, facilitating leadership development. We describe
these theoretically driven mediator variables in the next section.
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Leadership Self-Efficacy
Building on Langston and Sykes (1997) findings that the Big Five variables are
correlated with individual beliefs, Chan and Drasgow (2001) proposed that personality and values lead to LSE. This construct is the result of the application of
Bandura’s (1997) self-efficacy theory to the leadership literature. Kane (1999) defined LSE as “one’s perceived self-capability to perform cognitive and behavioral
functions required to effectively perform a specific leadership task” (p. 5). Kane
contended that LSE is similar to task-specific self-efficacy except that team members also influence it. The leader must realize his or her capability is affected by
team members or followers and must regulate his or her thoughts and actions as
well as team activities. In other words, team composition, processes, and the environment for a specific task and/or situation influence task-specific LSE. Kane,
Zaccaro, Tremble, and Masuda (2002) found that LSE related significantly to
leader goal level, leader strategies, and functional leadership behaviors. Chan and
Drasgow (2001) proposed that LSE is a proximal antecedent of MTL and found
LSE to be empirically related to two MTL factors. They also found that all of the
Big Five were positively related to LSE. Consistent with the positive influence of
specific self-efficacy on performance (Stajkovic & Luthans, 1998), high levels of
LSE are expected to result in higher levels of engagement in leadership opportunities and higher levels of leadership effectiveness.
Motivation to Lead
MTL has been defined as an individual difference variable that determines whether
individuals seek out leadership positions, and if they do, how much effort they exert to perform their leadership duties at a high level (Chan & Drasgow, 2001). Chan
and Drasgow conceptualized MTL as a three-dimensional construct and demonstrated empirical support for this structure. The first factor is termed Affective-Identity MTL. An individual with a high score on this dimension is someone
who generally likes to lead. The second factor, Social-Normative MTL, is MTL
out of a sense of duty or responsibility. The third factor, Noncalculative MTL, is of
particular interest in this study. One with a high level of Noncalculative MTL does
not try to weigh the costs versus the benefits of assuming a leadership role. Because leadership roles usually have a number of potential costs (i.e., time, large
amount of responsibility), an individual who is calculative of the costs–benefits ratio will presumably not want to assume the leadership role.
Chan and Drasgow (2001) proposed that MTL is a direct outcome of LSE, and
it is also directly influenced by personality and values. They found that LSE was
significantly related to both the Affective-Identity and Social-Normative MTL factors, indicating that those that have confidence in their leadership ability are more
GOAL ORIENTATION AND LEADERSHIP
323
likely to want to lead and feel the need to lead out of a sense of duty. They also
found empirical evidence for a direct effect of the Big Five on the MTL factors.
INTEGRATION OF LITERATURE AND HYPOTHESES
Building on Chan and Drasgow’s (2001) theoretical framework, we propose the relationships between goal orientation and leadership effectiveness can also be explained by the motivational mechanisms LSE and MTL. For individuals who are
assigned leadership roles, as they were in our study, MTL captures the intensity of
his or her effort of leading and persistence as a leader (Chan & Drasgow, 2001).
Conceptually the three goal-orientation dimensions can be linked both directly and
indirectly to MTL and to LSE. McCormick (1999) suggested that those with a
strong LGO would sustain or improve their efficacy expectations due to their
nonnegative view of mistakes. Conversely, individuals with a strong PGO view
mistakes as a limitation to their capabilities and therefore are less likely to enhance
efficacy judgments. Empirically, LGO has shown consistently positive relationships with specific self-efficacy (e.g., Bell & Kozlowski, 2002; Kozlowski et al.,
2001; Phillips & Gully, 1997). We test this relationship with specific self-efficacy
for leadership roles (LSE).
Given the relationships Chan and Drasgow (2001) revealed between the Big
Five and LSE as well as the Big Five and MTL and Judge et al.’s (2002) meta-analytic findings that all of the Big Five are related to leadership effectiveness, we examine the extent to which goal orientation predicts LSE and MTL above and beyond the Big Five.
H1: LGO will positively relate to LSE above and beyond the Big Five.
LSE might also facilitate a relationship between LGO and both Affective-Identity and Social-Normative MTL. In other words, individuals with high levels of
LGO are likely to have high levels of Affective-Identity MTL and Social-Normative MTL, because they are likely to be efficacious about their leadership abilities.
H2a: LSE will partially mediate the positive relationship between LGO and Affective-identity MTL.
H2b: LSE will partially mediate the positive relationship between LGO and Social-normative MTL.
Both PGO dimensions are expected to indirectly relate to leadership effectiveness as well. The basis for these relationships is through the Noncalculative MTL
factor. Those who are motivated to lead for Noncalculative reasons do not readily
calculate the possible consequences of leadership behaviors. In other words, they
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are less concerned about or “not calculative about, the costs of leading relative to
the benefits (i.e., noncalculative MTL)” (Chan & Drasgow, 2001, p. 482). Those
with a high level of PPGO are motivated to demonstrate their abilities to others.
Accordingly, these individuals are likely to calculate the benefits of leading (e.g.,
the extent to which they can demonstrate their abilities to others). According to
Chan and Drasgow, calculative individuals will be less motivated to lead due to the
high costs of leading. Therefore, we propose that PPGO will be negatively related
to Noncalculative MTL.
H3a: PPGO will negatively relate to Noncalculative MTL above and beyond the
Big Five.
Similarly, individuals with high levels of PAGO are motivated to avoid negative
feedback and criticism. They will be motivated to calculate the costs and consequences of assuming a leadership role (e.g., responsibility, accountability) to avoid
negative feedback. In addition, PAGO is positively related to negative affect
(Payne et al., in press), which in turn is related to more careful information processing (Clore, Schwarz, & Conway, 1994; Forgas, 1995; Isen, 1987) and
calculative decision making. Thus, the inclination to calculate will make individuals with high levels of PAGO less motivated to lead. Therefore, we expect PAGO to
also be negatively related to Noncalculative MTL.
H3b: PAGO will negatively relate to Noncalculative MTL above and beyond the
Big Five.
To establish that goal orientation is a distal antecedent of leadership effectiveness, each of the MTL factors must be related to leadership effectiveness. Chan
and Drasgow (2001) did not predict that MTL would be directly related to leadership effectiveness; however, they did not discount the possibility. In addition, their
data did not permit an examination of this relationship, as they did not measure
leadership effectiveness. They did, however, demonstrate that MTL was a significant predictor of leadership potential ratings. We expect each of the three MTL
factors to positively relate to leadership effectiveness. Those who generally enjoy
leading (Affective-Identity MTL) will be better leaders than those individuals that
do not enjoy or like leading. In addition, individuals who are less likely to calculate
the costs–benefits ratio (Noncalculative MTL) are more likely to be effective leaders. Finally, those who feel a sense of duty to lead (Social-Normative MTL) are
more likely to be effective leaders than those who do not feel a sense of duty to
lead. We test these relationships after controlling for the leader’s and the team
members’ Big Five personality characteristics in an effort to address the lack of research examining the influence of leader traits over and above follower traits (Piccolo & Judge, 2006).
GOAL ORIENTATION AND LEADERSHIP
325
H4a: Affective-Identity MTL will positively relate to leadership effectiveness
above and beyond the leader’s and team members’ Big Five.
H4b: Noncalculative MTL will positively relate to leadership effectiveness
above and beyond the leader’s and team members’ Big Five.
H4c: Social-Normative MTL will positively relate to leadership effectiveness
above and beyond the leader’s and team members’ Big Five.
In summary, the goal of our study is to examine the relationship between goal
orientation and leadership effectiveness via two motivational mechanisms. We
conduct a conservative test of these relationships by controlling for distal traits.
METHOD
Participants
Four hundred undergraduate students enrolled in introductory psychology participated in this laboratory study voluntarily as one option for fulfilling a course research requirement. The participants were recruited through the participant pool of
the psychology department at a large, southwestern university. The ages of participants ranged from 17 to 24 (M = 19.02, SD = 1.11) and the number of men and
women was essentially equal (53% male). The majority of the participants were
White (80.8%).
The participants completed the study in four-person teams consisting of one
leader and three team members. A power analysis with a power of .80 revealed that
a minimum of 96 leaders were necessary to obtain correlations of .30 (a medium
effect size; Cohen, 1988) or higher. Accordingly, data were collected for 100
teams. The roles of leader and team member were determined before the study began based on how the participants signed-up for the session. This ensured no one
knew beforehand that they were going to be placed in a leadership position. The
demographics of the sample of leaders were very similar to the demographics of
the rest of the participants. Approximately one half of the leaders were male
(53%). On average, the leaders were 19.08 years of age, and the majority was
White (76%).
Measures
Big Five personality dimensions. Saucier’s (1994) Mini-Markers was
used to measure the Big Five personality factors. This scale consists of 40 adjectives and is an abbreviated list of Goldberg’s (1990) 100 adjectives. The participants rated how well the adjectives described themselves using a 5-point accuracy
scale.
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HENDRICKS AND PAYNE
Goal orientation. Individuals’ dispositional goal orientation was assessed
using a modified version of VandeWalle’s (1997) 13-item, three-dimensional work
domain measure. References to work were removed from the items. Five items
measured LGO, 4 items measured PPGO, and 4 items measured PAGO. A 5-point
Likert agreement scale was used as the response format for each of the items.
Motivation to lead. Chan and Drasgow’s (2001) 27-item MTL measure was
used to assess MTL. The measure contained three nine-item scales: Affective-Identity MTL, Noncalculative MTL, and Social-Normative MTL. A 5-point
Likert agreement scale was used for each item.
Leadership self-efficacy. The measure for LSE was also developed by
Chan and Drasgow (2001) based on a measure constructed by Feasel (1995). This
instrument contained six items that were responded to on a 5-point Likert agreement response scale.
Leadership effectiveness. We obtained two measures of leadership effectiveness: team member ratings of the leader’s performance in the team task (averaged within each team) and team performance on the experimental task (profit
level). Using a 5-point agreement scale, each team member rated his or her team’s
leader on a 17-item instrument developed by Kane (1999) for the experimental
task used in this study. A sample item read, “Overall, I thought the leader did a
good job.” A confirmatory factor analysis (CFA) revealed two items had weak
loadings on the latent construct, so we dropped them from further analyses.1 A
CFA of the remaining 15 items supported a unidimensional structure, χ2 (90, N =
300) = 339.07, p < .01; Tucker–Lewis Index (TLI) = .98, comparative fit index
(CFI) = .98, incremental fit index (IFI) = .98, root mean square error of approximation (RMSEA) = 0.08.
We then tested to see if we had sufficient agreement within each team to aggregate the team members’ ratings of leadership effectiveness to the team level. Both
within-team agreement and interrater reliabilities were estimated (cf. Bliese, 2000,
and James, Demaree, & Wolf, 1984). Within-team interrater agreement (rwg(j) =
.93) was substantially high, indicating on average team members were uniform in
their assessment of the leader’s performance. In addition, intraclass correlations
(ICC[1] = .46 and ICC[2] = .72) indicated rater consistency across items. Thus, the
mean of the team members’ ratings within each team were used to represent leader
effectiveness.
1The following two items were dropped from the groups’ ratings of leadership effectiveness inventory: “This leader assigned group members particular roles for performing the task” and “The leader
did things his/her own way.”
GOAL ORIENTATION AND LEADERSHIP
327
Experimental Task
Participants completed an experimental task titled “The Manufacturing Game”
(Kane et al., 2002; Zaccaro, Foti, & Kenny, 1991) in four-person teams. Each team
was given the task of building products and selling them for profit. The overall goal
of the task was to maximize team profit by buying at lower prices and selling at higher
prices, as the market prices changed during the task. The products were built from
raw materials (LEGO® blocks), and the design of three products was given to all participants in two- and three-dimensional formats. Correspondingly, the task could be
described as an “executing performance task” (McGrath, 1984) that is somewhat additive in that performance represents the sum of each member’s individual contribution (Steiner, 1972), although leader contributions were not exactly the same as the
team members’ contributions. Some interdependence between the leader and the
team members was uniformly imposed across all teams by only permitting the team
members to build the products. The leader could place orders and sell products, but
she or he could not build any products. Using existing team typologies, the teams in
our study would be classified as hierarchical production teams (Devine, 2002; Hackman, 1990; LePine, Hollenbeck, Ilgen, & Hedlund, 1997).
Procedure
Ten hypothesis-blind research assistants were trained to follow a tightly scripted
protocol and collected all of the data for the study. The leaders were required to arrive 45 min prior to the other participants for pretraining on the task. Upon arrival,
the leader completed a series of individual difference measures. Next, the leader
was given a set of instructions indicating she or he was going to participate in the
Manufacturing Game, how to complete the game, and the objective of the game.
She or he was also provided with an ordering form, market prices, and models of
the products. The leader was allotted 5 min to prepare for the task and 15 min of
production time. The experimenter distributed supplies and bought finished products at the specified market price, which changed every 5 min. If the products were
not built to exact specifications, they were rejected and returned for “repairs.” The
leader’s performance (profit) on the task was recorded to be used as a covariate
when predicting team performance.
Concurrent with the leader completing the experimental task, the additional participants (team members) arrived for the session. The team members completed the
same battery of individual difference measures that the leader previously completed
while the leader took a short break. Upon completion of the self-report inventories,
the team was informed that they were going to perform the Manufacturing Game as a
team and introduced to their designated leader. At this time, the experimenter reminded the team members, as indicated in their informed consent, the three most
profitable teams were eligible for a $100 prize ($25 each). The leader was then given
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HENDRICKS AND PAYNE
a second set of instructions for the Manufacturing Game and told she or he was responsible for communicating the instructions to her or his team members. The leader
was instructed that this time she or he could not physically contribute to the building
of the products. Each leader was given 10 min to explain the task and plan for production, followed by 20 min of production time. Again, the market buying prices and
selling prices changed every 5 min throughout the 20-min performance phase. The
leader was given the changes in market information at the beginning of the task. The
leader and team members were permitted to ask the experimenter for time checks
throughout the exercise, but they were not permitted to wear a watch in order to maintain standardization of resources across participants. As before, raw materials were
purchased using an order form and inaccurate products were sent back for “repairs.”
Once the time allotted had passed, the team members independently rated the
effectiveness of the leader. Team profit was calculated by subtracting the money
spent on raw materials from total revenue. The experimenter used a log sheet to record all transactions.
Level of Analysis
All participants completed the individual difference measures; thus, both leader
and follower proximal and distal traits were assessed. The leadership role in this
study was determined relatively randomly, so there was no reason to expect leaders
to be different from the team members on the variables examined. We conducted a
series of independent t tests to confirm this assumption and found that the leaders
did not vary significantly from the team members on any of the focal variables examined in this study. All hypotheses were tested with a sample size of 100. Team
member characteristics (e.g., Big Five) were averaged within each team.
RESULTS
Descriptive statistics, reliability estimates, and intercorrelations among the variables are presented in Tables 1 and 2 for the leader and team members, respectively. Despite Chan and Drasgow’s (2001) conceptual distinction between the
MTL factors and LSE, the correlations between LSE and the MTL factors were
relatively high (ranging .39–.68) calling into question the discriminability of these
constructs. However, a CFA demonstrated that a four-factor model, χ2(489, N =
400) = 1,069.31, p < .01 (χ2/df = 2.19; TLI = .85, CFI = .86, IFI = .86, RMSEA =
.06), fit the data better than a single-factor solution, χ2(495, N = 400) = 1,992.21, p
< .01 (χ2/df = 4.025; TLI = .62, CFI = .65, IFI = .65, RMSEA = .09).2 Also, the dif2We used the full sample (N = 400) for the CFA to maximize the sample size for each parameter that
was estimated.
329
M
1
2
0.52
(.78)
0.61
.38 (.79)
0.67
.32
.43
0.73
.35
.09
0.51
.32
.13
0.56
.12
.26
0.65
.05
.03
0.71
–.09 –.10
0.53
.21
.35
0.56
.05
.25
0.43
.23
.31
0.45
.24
.28
5,166.00 .00
.02
0.65
.09
.08
17,856.12 –.12
.02
SD
4
5
6
(.78)
.23 (.86)
.08
.18 (.73)
.19
.35
.27 (.78)
–.25
.09
.19
.31
–.25 –.19 –.05 –.20
.26
.39
.27
.40
.13
.40
.19
.40
.29
.30
.28
.29
.28
.33
.24
.40
–.13 –.12
.08
.20
.03
.30
.06
.16
–.02
.04 –.04
.09
3
(.71)
.36
.16
.31
.04
.29
.22
.00
.17
7
(.78)
–.19
–.09
–.17
–.11
.02
–.08
–.11
8
(.81)
.68
.39
.57
.03
.29
.12
9
(.83)
.22
.50
.14
.24
.19
10
12
13
14
(.79)
.38 (.72)
.01 –.08
.23 –.01 .17 (.93)a
.09 –.02 .33 .38
11
15
Note. N = 100. Reliability estimates (Cronbach’s alpha) are in parentheses along the diagonal. Correlations greater than or equal to |.20|, p ≤ .05, correlations greater than or equal to |.27|, p ≤ .01. Ldr = leader; Conscientious = Conscientiousness; Em. Stability = Emotional Stability; Openness = Openness to Experience; Learning GO = Learning Goal Orientation; Prove GO = Performance-Prove Goal Orientation; Avoid GO = Performance-Avoid Goal Orientation; LSE =
Leadership Self-Efficacy; AIMTL = Affective-Identity Motivation to Lead; Noncalculative Motivation to Lead; SNMTL = Social Normative Motivation to
Lead.
aWithin-group interrater agreement index (r
wg(j)).
1. Ldr Agreeableness
4.04
2. Ldr Conscientious
3.58
3. Ldr Em. Stability
3.27
4. Ldr Extraversion
3.43
5. Ldr Openness
3.77
6. Ldr Learning GO
3.80
7. Ldr Prove GO
3.44
8. Ldr Avoid GO
2.85
9. Ldr LSE
4.13
10. Ldr AIMTL
3.56
11. Ldr NCMTL
4.01
12. Ldr SNMTL
3.49
13. Ldr Performance
2,465.13
14. Team Ratings
3.62
15. Team Profit
35,136.86
Variable
TABLE 1
Descriptive Statistics and Intercorrelations Among Study Variables for Leaders Only
330
4.11
3.81
3.31
3.54
3.84
3.90
3.49
2.76
4.16
3.54
3.96
3.56
3.62
35,136.86
M
0.29
0.37
0.36
0.42
0.32
0.31
0.43
0.46
0.31
0.41
0.29
0.29
0.65
17,856.12
SD
.15
.21
–.03
.10
.02
–.20
–.17
.06
–.27
.36
.08
.21
.17
1
.08
.11
.04
.25
.01
–.32
.32
.22
.17
.21
.02
–.01
2
.23
–.05
.06
–.28
–.20
–.11
–.20
.18
–.19
.04
.18
3
.11
.36
–.06
–.30
.35
.48
.09
.25
–.10
.00
4
.28
.13
–.06
.30
.29
.07
.17
–.05
–.01
5
.19
–.30
.40
.48
.42
.49
–.10
.08
6
.38
.19
.40
–.08
.35
–.22
–.02
7
–.25
–.16
–.21
.01
.07
.07
8
.64
.22
.36
.16
.01
9
.16
.44
.19
.05
10
.32
.06
.11
11
–.07
.04
12
13
.38
14
15
Note. N = 100 teams. Correlations greater than or equal to |.20|, p ≤ .05, correlations greater than or equal to |.27|, p ≤ .01. Em. Stability = Emotional Stability; Openness = Openness to Experience; Learning GO = LGO; Prove GO = Performance-Prove Goal Orientation; Avoid GO = Performance-Avoid Goal Orientation; LSE = Leadership Self-Efficacy; AIMTL = Affective-Identity Motivation to Lead; Noncalculative Motivation to Lead; SNMTL = Social Normative Motivation to Lead; Ldr = Leader.
1. Team Agreeableness
2. Team Conscientiousness
3. Team Em. Stability
4. Team Extraversion
5. Team Openness
6. Team Learning GO
7. Team Prove GO
8. Team Avoid GO
9. Team LSE
10. Team AIMTL
11. Team NCMTL
12. Team SNMTL
14. Team Ratings
15. Team Profit
Variable
TABLE 2
Descriptive Statistics and Intercorrelations Among Study Variables for Team Members (Aggregated)
GOAL ORIENTATION AND LEADERSHIP
331
ference of the fit for the two models was statistically significant: ∆χ2(6, N = 400) =
922.90, p < .01. These results indicate that these constructs are also empirically
distinct.
The zero order correlations in Tables 1 and 2 reveal direct relationships between
the individual differences examined and leadership effectiveness. Consistent with
our hypotheses, none of the goal orientation dimensions have significant relationships with leadership effectiveness. Only leader extraversion, LSE, Affective-Identity MTL, and Noncalculative MTL had significant relationships with
team member ratings of leadership effectiveness and the ratings were significantly
related to team performance (team profit).
Hypothesis 1 stated LGO would positively relate to LSE above and beyond the
Big Five. We tested this hypothesis using hierarchical regression in which the five
personality variables were entered in the first step and LGO was entered in the second step. Consistent with expectation, LGO was positively related to LSE; however, it did not account for a significant amount of variance above and beyond the
personality variables (β = .19, p = .058; see Table 3). Consistent with Figure 1,
LGO appears to partially mediate relationships between the Big Five and LSE, as
the beta weights for the Big Five drop in the second step of the regression analyses.
The second hypotheses posited the positive relationships between LGO and
both Affective-Identity MTL and Social-Normative MTL are partially mediated
by LSE. We conducted a very conservative test of this hypothesis by controlling
for all of the Big Five variables before entering the independent variable for a given
step, and we used Baron and Kenny’s (1986) approach and Sobel’s (1982) test to
test for mediation.
As shown in Table 4, the first regression for testing both Hypotheses 2a and 2b
involved regressing LSE on LGO (after controlling for the Big Five), which is the
same analysis we performed to test Hypothesis 1. In the second regression for Hypothesis 2a, Affective-Identity MTL was regressed onto LSE. This was significant
(β = .60, p < .01) even after controlling for the Big Five. In the third regression, Affective-Identity MTL was regressed onto LGO. Again, incremental validity was
shown above the Big Five (β = .21, p < .05). Finally, Affective-Identity MTL was
simultaneously regressed onto LGO and LSE following the entry of the Big Five.
Here the beta for LGO became nonsignificant (β = .10) providing preliminary evidence for partial mediation, supporting Hypothesis 2a. We further determined this
change was significant using Goodman’s (1960) I version of Sobel’s (1982) test (z
= 3.77, p < .01).
We conducted the same analyses with Social-Normative MTL to test Hypothesis 2b. Both LSE (β = .47, p < .01) and LGO (β = .25, p < .05) were significantly related to Social-Normative MTL above and beyond the Big Five. As depicted in Table 4, when both variables were entered into the equation simultaneously, the beta
weight for LGO became nonsignificant (β = .17), indicating partial mediation and
support for Hypothesis 2b. Again, Sobel’s (1982) test indicated this change was
332
–.12
.27**
.05
.26**
.21*
–.08
.23*
.04
.21**
.16
.18+
.11
.09
.08
.07
.10
.11
.09
.08
.07
.10
.09
SE B
–.12
.31
.07
.35
.20
–.08
.26
.06
.29
.06
.19
.29
.32
.03+
R2
.29**
R2
.09
.07
.07
.06
.08
.09
.08
.07
.06
.08
.07
.09
.07
.07
.06
.08
.06
.01
–.04
.16*
.08
.13*
.19*
–.05
SE B
–.04
.16*
.09
.13*
.19*
–.04
.15*
.09
.13*
.18*
B
.01
–.05
.22
.12
.22
.22
–.07
–.05
.22
.14
.23
.22
–.05
.22
.14
.23
.22
Noncalculative MTL
.01
.00
.23**
R2
.23
.23
.23
R2
Note. The B weights in the columns are from the step of entry into the model. Ldr = leader; Prove Goal Orientation = Performance-Prove Goal Orientation;
Avoid Goal Orientation = Performance-Avoid Goal Orientation; MTL = Motivation to Lead.
+p ≤ .10. *p ≤ .05. **p ≤ .01.
1. Ldr Agreeableness
Ldr Conscientiousness
Ldr Emotional Stability
Ldr Extraversion
Ldr Openness
2. Ldr Agreeableness
Ldr Conscientiousness
Ldr Emotional Stability
Ldr Extraversion
Ldr Openness
Ldr Learning Goal Orientation
Ldr Prove Goal Orientation
2. Ldr Agreeableness
Ldr Conscientiousness
Ldr Emotional Stability
Ldr Extraversion
Ldr Openness
Ldr Avoid Goal Orientation
B
Leadership Self-Efficacy
TABLE 3
Incremental Validity of Goal Orientation on Leadership Self-Efficacy (Hypothesis 1) and Noncalculative MTL (Hypothesis 3)
333
–.27*
.27**
–.02
.34**
.17*
–.20*
.10
–.06
.18**
.04
.63**
–.23*
.23*
–.03
.28**
.11
.21*
–.18
.09
–.06
.16*
.02
.10
.61**
.11
.10
.08
.07
.10
.09
.08
.07
.07
.09
.10
.11
.10
.08
.08
.11
.10
.09
.08
.07
.07
.09
.08
.10
SE B
–.26
.30
–.03
.44
.15
–.19
.11
–.07
.23
.03
.60
–.22
.25
–.04
.37
.10
.21
–.17
.10
–.07
.20
.01
.10
.58
.26**
.51**
.29**
.52**
.25**
.03*
.26**
R2
.26**
R2
–.01
.14+
.09
.16**
.15+
.04
.03
.06
.06
.06
.40**
.03
.09
.08
.11+
.09
.20*
.06
.01
.06
.03
.03
.14+
.37**
B
.09
.08
.07
.06
.09
.09
.07
.06
.06
.08
.08
.09
.08
.07
.06
.09
.08
.09
.07
.06
.06
.08
.08
.08
SE B
–.01
.19
.13
.26
.16
.04
.04
.10
.10
.07
.47
.03
.13
.12
.18
.10
.25
.07
.01
.09
.05
.04
.17
.43
R2
.18**
.05*
.16**
.21**
Social-Normative MTL
Note. N = 100. The B weights in the columns are from the step of entry into the model. Ldr = leader; MTL = Motivation to Lead.
+p < .10. *p < .05. **p < .01.
1. Ldr Agreeableness
Ldr Conscientiousness
Ldr Emotional Stability
Ldr Extraversion
Ldr Openness
2. Ldr Agreeableness
Ldr Conscientiousness
Ldr Emotional Stability
Ldr Extraversion
Ldr Openness
Ldr Leadership Self-efficacy
2. Ldr Agreeableness
Ldr Conscientiousness
Ldr Emotional Stability
Ldr Extraversion
Ldr Openness
Ldr Learning Goal Orientation
2. Ldr Agreeableness
Ldr Conscientiousness
Ldr Emotional Stability
Ldr Extraversion
Ldr Openness
Ldr Learning Goal Orientation
Ldr Leadership Self-efficacy
B
Affective-Identity MTL
TABLE 4
Mediating Role of Leadership Self-Efficacy on the Learning Goal Orientation-Motivation to Lead Relationships (Hypothesis 2)
.39**
.26**
.37**
.21**
R2
334
HENDRICKS AND PAYNE
significant (z = 3.44, p < .01), demonstrating further support for partial mediation.
Consistent with Figure 1, the beta weights for the Big Five drop when LGO is
added to the equation, suggesting LGO mediates relationships between the Big
Five and Affective-Identity and Social-Normative MTL factors.
Hypothesis 3 proposed that both PPGO and PAGO would negatively relate to
Noncalculative MTL above and beyond the Big Five. Because the two PGO dimensions were significantly related to one another (r = .36), we calculated two
separate regression equations. As depicted in Table 3, after controlling for the Big
Five, neither PPGO nor PAGO accounted for a significant amount of variance in
Noncalculative MTL (β = .01, ns and β = –.07, ns), indicating no support for Hypothesis 3a or 3b. Contrary to Figure 1, PPGO and PAGO do not appear to mediate
relationships between the Big Five and Noncalculative MTL.
The fourth hypothesis predicted significant positive relationships between the
MTL factors and leadership effectiveness after controlling for both the leaders’ and
team members’ Big Five personality characteristics, as well as the leader’s previous task performance. We tested this hypothesis with both indicators of leadership
effectiveness: team ratings and team profit, separately. First, the leader’s performance on the task by him- or herself and the group members’ Big Five, followed by
the leader’s Big Five, and then the leader’s three MTL factors were entered into a
regression equation to predict each measure of leadership effectiveness (see Table
5). Consistent with expectation, Noncalculative MTL was significantly and positively related to team ratings (β = .23, p < .05); however, contrary to expectation,
Social-Normative MTL related negatively (β = –.24, p < .10), not positively to the
ratings. The relationships between Affective-Identity MTL and team ratings (β =
.16, p < .10) as well as team profit (β = .11, p < .10) approached significance. Neither Noncalculative nor Social-Normative MTL related to the team profit criterion.
These results provide some support for Hypotheses 4b.
DISCUSSION
The purpose of this study was to test an indirect relationship between goal orientation and leadership effectiveness through the more proximal individual difference
characteristics LSE and MTL. We also test the incremental validity of these predictors over and above the Big Five personality characteristics. Consistent with our
expectations and research by McCormick (1999), LGO was positively related to
LSE, which in turn positively related to Affective-Identity MTL and Social-Normative MTL suggesting that individuals with a high level of LGO are more likely
to want to lead because they like to lead and feel a sense of duty to lead.
Contrary to expectation, PPGO and PAGO were not significantly related to
Noncalculative MTL above and beyond the Big Five. This may have been a function of limited power to detect these relationships, because PAGO and
335
.00
.48*
–.02
–.01
–.17
–.10
–.05
.09
–.03
.29**
–.07
.18+
–.34+
.34*
.00
.24
.18
.19
.16
.21
.15
.12
.11
.10
.14
.15
.18
.17
SE B
.17
.21
–.01
.00
–.11
–.05
–.04
.08
–.04
.32
–.05
.16
–.24
.23
.09
.18+
.24
.09+
.06*
R2
.09
R2
1.13**
9301.50
–2650.55
6639.82
–3069.77
559.47
–5675.35
1705.02
815.79
3226.62
–2906.10
3436.60
5914.68
–3785.43
B
.34
6282.98
4678.04
5084.08
4289.25
5422.63
3961.26
3253.94
2952.32
2606.94
3782.79
4103.11
4796.80
4987.17
SE B
.33
.15
–.06
.13
–.07
.01
–.17
.06
.03
.13
–.08
.11+
.14
–.10
Team Profit
.02
.04
.16*
R2
.21+
.20*
.16*
R2
Note. N = 100. The B weights in the columns are from the step of entry into the model. Stab = Stability; Exp = Experience; Ldr = leader; MTL = Motivation
to Lead.
+p < .10. *p < .05. **p < .01.
1. Leader Performance
Team Agreeableness
Team Conscientiousness
Team Emotional Stab
Team Extraversion
Team Openness to Exp
2. Ldr Agreeableness
Ldr Conscientiousness
Ldr Emotional Stability
Ldr Extraversion
Ldr Openness to Exp
3. Ldr Affective-Identity MTL
Ldr Social-Normative MTL
Ldr Noncalculative MTL
B
Team Ratings
TABLE 5
Incremental Validity of the Motivation to Lead Factors on Leadership Effectiveness (Hypothesis 4)
336
HENDRICKS AND PAYNE
Noncalculative MTL were negatively correlated with one another. Thus, individuals with strong PAGO may be more likely to calculate the pros and cons of leading
and therefore be less motivated to assume a leadership role.
Although we did not propose specific hypotheses, our data provide some empirical support for LGO as a mediator of the Big Five/LSE, Big Five/Affective-Identity MTL, and Big Five/Social-Normative MTL relationships. Consistent with Figure 1, the Big Five personality characteristics appear to be more distal leadership
traits influencing motivational mechanisms through achievement goal tendencies.
Future research theorizing about and replicating these patterns of relationships
seems warranted.
We also examined the predictive validity of the MTL factors for leadership effectiveness. Consistent with Chan and Drasgow’s (2001) theoretical framework,
Noncalculative MTL was positively related to team ratings of leadership effectiveness after controlling for the leader’s previous task performance and the leader and
the team members’ Big Five characteristics, indicating that those who are motivated to lead because they do not calculate the costs of leading are more effective
leaders in the eyes of their followers. Affective-Identity MTL also came very close
to relating significantly to team ratings of leadership effectiveness and team profit.
Larger sample sizes with more power to detect significant relationships may have
yielded stronger support for these relationships. Contrary to theory, Social-Normative MTL was negatively related to team ratings of leadership effectiveness, indicating that those who are motivated to lead out of a sense of duty are actually perceived to be less effective. Similarly, Chan and Drasgow found that
Social-Normative MTL did not account for unique variance in leadership potential
ratings. Additional research is needed to confirm if Social-Normative MTL is not a
sufficient type of motivation to facilitate leadership effectiveness or if it actually
hinders leadership effectiveness. Examining profiles of the three MTL factors may
illuminate these findings.
Finally, we assessed team member traits, aggregated them to the team level, and
examined how they influenced leadership effectiveness. It is interesting that only
team member PPGO and Agreeableness related significantly to the leader effectiveness ratings. We did not examine whether leader and team member traits have
interactive effects on leadership and team outcomes. The number of possible interactions is so extensive that further theorizing seems warranted before examining
these relationships.
Our research contributes to the individual difference and leadership literatures
in four ways:
1. We supplement Chan and Drasgow’s (2001) theoretical framework with
three additional individual difference variables and two measures of leadership effectiveness.
GOAL ORIENTATION AND LEADERSHIP
337
2. We respond to Judge et al.’s (2002) call to examine why personality relates
to leadership effectiveness by providing conceptual and empirical linkages
between proximal and distal individual differences and leadership
effectiveness.
3. We provide additional empirical evidence of the nomological network and
validity for MTL.
4. We demonstrate the incremental validity of narrow leader traits over and
above broad leader and team member traits.
Theoretical Implications
Our research has implications for theory in a number of domains to include individual differences, goal orientation, and leadership. First, by examining the incremental validity of goal orientation over and above the Big Five, we demonstrated
the goal orientation dimensions are empirically distinct from broad personality
constructs. We also demonstrate that other individual differences constructs besides the Big Five are important predictors of more proximal antecedents of leadership effectiveness.
Although previous research had examined the influence of leadership variables
on followers’ goal orientation (e.g., Dragoni, 2005; Gorenflo-Gilbert, 1999;
Schwager, 1997), this is the first study to examine the leader’s goal orientation on
leadership effectiveness. We added the mediating variables LSE and MTL to the
list of goal orientation outcomes. More specifically, we provide additional support
for the LGO-specific self-efficacy relationship. In this study, we examine LSE,
which demonstrated a positive relationship with LGO, indicating that individuals
with a high level of LGO tend to be more efficacious about their leadership abilities. We also demonstrated some support for the idea that individuals with high levels of PAGO are more calculative of the costs relative to the benefits of leading. In
contrast, individuals with high levels of LGO were motivated to lead for affective-identity and social normative reasons. These findings provide further insight
about these motivational orientations suggesting that they have implications for
calculative thinking and beliefs. It would be interesting to see if these cognitions
extend to nonleadership contexts as well.
We utilized a three-dimensional measure of goal orientation and examined each
dimension separately. Recent research by Elliot and colleagues (Conroy, Elliott, &
Hofer, 2003; Elliot & McGregor, 2001) suggests that LGO may also have prove
and avoid components and that profiles of goal orientation (e.g., Carr & DeShon,
2002) may be a more meaningful way to examine this construct, as the dimensions
are not mutually exclusive. It might also prove fruitful to examine the relationship
between the leader’s dispositional goal orientation and the team members’ state
goal orientation to further our understanding of the role of the leader’s goal orientation in leadership contexts. For example, do leaders with a strong LGO foster a
338
HENDRICKS AND PAYNE
high level of state LGO in their followers, which may in turn facilitate higher levels
of collective efficacy?
We contributed to the nomological network of MTL. First, we replicated
Chan and Drasgow’s (2001) findings that the MTL factors are significantly related to but distinct from LSE. We also replicated relationships between the Big
Five and the three MTL factors, as well as LSE. Consistent findings suggest robust relationships and warrant further theoretical attention. Second, we extend
Chan and Drasgow’s research by examining the relationships between the MTL
factors and leadership effectiveness, noting additional research on the relationship between Social-Normative MTL and leadership effectiveness seems
warranted.
The trait theory of leadership focuses on the leader’s traits as opposed to the
team members’ traits. Yet leadership effectiveness is often operationalized as a
team outcome that is also determined by variables beyond the leader’s control
(e.g., the team member’s traits and skills). Although Chan and Drasgow’s (2001)
framework illuminates why leader traits are likely to influence leader behavior, it
does not extensively incorporate team inputs (e.g., team member’s traits) and processes (e.g., cohesion and communication) that are also known to contribute to
team outcomes. We demonstrated proximal and distal leader traits predicted leadership effectiveness above and beyond team member traits.
Another avenue for future research is to integrate Chan and Drasgow’s (2001)
framework with models of team effectiveness (e.g., Gladstein, 1984), perhaps by
including aspects of functional leadership theory (Hackman & Walton, 1986). Because Chan and Drasgow’s framework focuses on leader behavior, how leader
traits and MTL influence team performance is not fully explicated. According to
their framework, MTL leads to participation in leadership roles and training,
which leads to social knowledge and skills for leading and leadership style, which
in turn leads to leadership performance. We believe leadership knowledge and
skills contribute to appropriate leadership behaviors, which in turn facilitate effective team processes (e.g., communication). According to functional leadership theory, leaders demonstrate two basic categories of behaviors: (a) developing and
shaping team processes and (b) monitoring and managing team performance
(Hackman & Walton, 1986). One way they do this is establish and maintain a favorable team climate (Kozlowski & Doherty, 1989). Leaders with a strong LGO
may encourage team members to develop new skills, set learning goals for the
team, and provide feedback that promotes collective efficacy (Kozlowski, Gully,
McHugh, Salas, & Cannon-Bowers, 1996).
Practical Implications
The study presented here offers some information that is likely to be useful when
predicting successful leadership with simple assessments of individual differ-
GOAL ORIENTATION AND LEADERSHIP
339
ences. Ideally, any organization should seek to identify those who may be more
adaptable to assuming and carrying out leadership roles effectively for selection,
placement, and promotion decisions. If organizations are going to expend resources to develop these individuals, then being able to predict who is more likely
to be a successful leader with relatively inexpensive materials (e.g., self-report
measures) would be highly util.
This research also has practical implications for training leaders. For example,
the development of leaders may be more efficient if the Big Five, goal orientation,
LSE, and MTL are taken into account when selecting who receives leadership
training or a developmental intervention. Individuals with high levels of Extraversion, Conscientiousness, Openness to Experience, LGO, MTL, LSE, and low
levels of PPGO and PAGO may benefit the most from leadership training. This research suggests using a Big Five measure in conjunction with a goal orientation
measure is more useful than using a Big Five measure alone. Finally, leadership
trainers should strive to enhance leaders’ LSE and MTL during training as LSE and
MTL are arguably more malleable than goal orientation and personality.
Limitations and Directions for Future Research
We acknowledge the limitations of our study. These are primarily weaknesses
commonly associated with the characteristics of the sample and the use of a lab
task. The sample was relatively homogeneous, consisting mostly of White 18- to
20-year-olds. We also assigned leaders instead of examining those who were nominated or emerged. Whereas the laboratory study allowed us to examine a large
number of leaders in a standardized environment, the short time frame may not
have been long enough for leaders to demonstrate all manifested behaviors and for
all leadership and group processes to occur. At the same time, simulations are not
considered entirely weak methods for studying leadership (e.g., Bass, 1990;
Thornton & Cleveland, 1990), and the relationships we found are supported by
theory. Additional tests of these relationships in the field are encouraged.
Whereas our research provides some empirical support for LSE and MTL as
mediators of the leader trait-leader effectiveness relationships, we did not examine
the implied mediator leader behavior, and clearly there are more processes that are
likely to occur between traits and outcomes that explain these relationships. For
example, Lee, Sheldon, and Turban (2003) recently showed that goal level mediates relationships between goal orientation and performance. In team context,
there are also group processes like communication and cohesion that are likely to
mediate relationships between leader behaviors and leadership effectiveness.
Ideally a test of Chan and Drasgow’s model would include all constructs depicted in their model. For example, we did not include values or interests or some
potential moderators like situational factors in this study. An even more robust test
of the model would include collecting longitudinal data to test the predictions
340
HENDRICKS AND PAYNE
made for leaders’ development including their leadership experience and their acquisition of the knowledge and skills needed to be an effective leader. Future research should attempt to provide a comprehensive test of their model.
Despite the limitations, we feel the goals of our study were met. The research
reported herein developed a conceptual link between dispositional goal orientation
and specific motivational consequences within the leadership domain. Subsequently, these hypothesized relationships were tested and some were supported,
adding empirical support to the conceptual arguments. Finally, we shed some light
on why leader traits influence leadership effectiveness, by proposing LSE and
MTL as motivational mechanisms.
ACKNOWLEDGMENTS
This paper is based on the first author’s Master’s thesis under the direction of
Stephanie C. Payne. The authors wish to acknowledge the other thesis committee
members, Charlie Samuelson and Christine Townsend. We also express our appreciation to Tome Kane for his assistance with task materials and measures and to
Jennifer Camp, Melissa Frommert, Tracy Huffman, Thomas Lopez, Lee
McGilvray, Taikia Smith, Catherine Vo, and Meredith Vrba for their assistance
with data collection.
An earlier version of this paper was presented at the 17th annual Society for Industrial and Organizational Psychology Conference, Toronto, Canada, April 2002.
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