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lNTERPERSONAL COMPETITIVENESS AS A MOTIVATIONAL CONSTRUCT:
AN APPLICATION TO GOAL SETTING

By

Ronald Stephen Landis

A DISSERTATION

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Department of Psychology

1995

ABSTRACT

lNTERPERSONAL COMPETITIVENESS AS A MOTIVATIONAL CONSTRUCT:
AN APPLICATION TO GOAL SETTING

By

Ronald Stephen Landis

Attempting to understand work motivation has historically occupied a central role in the
field of industrial and organizational (1/0) psychology. The current study sought to
extend the work motivation literature by examining the impact of individual differences
with respect to the construct of competitiveness. Relevant literature from a variety of
psychological areas was reviewed. Hypotheses were proposed based on previous
research and current theory. Results indicated that an individual's competitive
orientation had some significant effects on subsequent task performance accuracy on a
complex decision task. Additional evidence suggested that, despite the claims of Locke
and Latham (1990) regarding the similarity of goal difficulty and situational
competitiveness, these two situational factors were differentially related to both
individual perceptions and task performance. Support was also found for several other
hypotheses, however the proposed model did not receive complete empirical support.

Conclusions, limitations, and future research implications are presented and discussed.

For Alexander

ACKNOWLEDGEMENTS

I would like to take this opportunity to thank several people who have been
instrumental in helping me not only complete this dissertation, but also to complete my
graduate education at Michigan State. First, and foremost, I would like to extend my
thanks to my wife, Sandy. In order to completely express my gratitude to her, I would
need more pages than are actually in this manuscript. Her love, support, and
encouragement allowed me to keep my goals focused and this project in perspective.
Also, my mother and brother deserve special recognition for their support, both
emotional and financial, throughout my graduate career. I would also like to say
thanks to my father, who passed away before he could see the completion of my
education. His desire to see me succeed kept me going during times when I felt like
settling for less.

I am indebted to several friends as well. lose, when I met you five years ago, it
seemed as though I had known you forever. Your friendship and support throughout
our time at MSU was more helpful than you can ever know. Mickey, thanks for
showing me that life is always fun, you just have to look at it the right way. Jeff, all I
have to say is thanks for the ”Bachelor's Club" and always having time to talk. Keith,
thanks for making me think more deeply about issues than I often wanted. Also,

thanks to Stan, Jean, Sherry, & Kim for the Thursday night dinners. These dinners

were proof that you can never have too many good friends, too much good food, or too
much good wine. I would also like to say thanks to Dennis & Julie, Matt & Kathy,
Rob, Tim, Whit, Dale, Jen, and Dan W. for good times and great memories.

I would also like to express my appreciation to the faculty at MSU. Thanks to
Dan Ilgen and John Hollenbeck for helping me through the early stages of my graduate
career and for the use of the lab. For helping me get a job, providing a sounding board
for my crazy ideas, and allowing me to use his lab, thanks to Rick DeShon. A special
thanks to my committee members, Kevin Ford, Steve Kozlowski, and Neal Schmitt.
Although you had many suggestions and comments that I didn't always want to hear,
you helped make this manuscript immeasurably better. Finally, I would like to say
thanks to Mike Lindell, my dissertation Chair. Your insightful comments on earlier
versions of this paper provided me with ideas and perspectives that I would have not
had otherwise. Also, "thanks” for our numerous discussions about 1/0 psychology,
current events, and other associated topics. I consider you not only my advisor, but
also my friend. I only hope that I can bring to this field and my students, the same

qualities and experiences that you have given me.

TABLE OF CONTENTS

Page

LIST OF TABLES .......................................... ix
LIST OF FIGURES ......................................... xi
INTRODUCTION .......................................... 1
Competition .......................................... 4
Competitiveness as a Situation or Person Variable ............. 6

Within- versus Between-Person Referents in Competitive Behavior . . 9
Dimensionality of Research on Competition ................ 10

Summary ...................................... 13

Review of Competitiveness Literature ........................ 15
Individual Differences in Competitive Behavior ............. 15
Competitiveness and Related Constructs .................. 23

Achievement Motivation ....................... 23

Learning versus Outcome Orientation ............... 26

Self-Efficacy ............................... 29

Influence of Competitive Situational Characteristics on Behavior . . . 36

Competition and Goal Setting Research ................... 43
An Integration and Development of a Conceptual Model ............ 46
Hypotheses .................................... 53

METHOD .............................................. 6O

Participants ......................................... 60
Design ............................................ 60
Task ............................................. 60
Goal and Competitive Manipulations ......................... 63
Measures .......................................... 64
Competitive Orientation ............................ 64
Pre-Task Knowledge .............................. 65
Pre-Performance Self-Efficacy ........................ 65

Task Performance Inventory ......................... 65
Performance Quantity ............ . .................. 66
Performance Accuracy ............................. 66
Perceptions of Situation Competitiveness .................. 66
Post-Performance Self-Efficacy ........................ 67
Post-Performance Attitudes .......................... 67
Procedure .......................................... 67
Data Analysis Strategy .................................. 69
RESULTS .............................................. 7O
Descriptive Data ...................................... 70
Analyses of Primary Hypotheses ............................ 77
DISCUSSION ........................................... 1 12
Review of Results and Integration with Current Literature .......... 112

Limitations to the Generalizability of Results ................... 123

Future Research ..................................... 127
APPENDIX A: Training Handbook ............................ 130
APPENDIX B: Competitive Orientation Measure ................... 137
APPENDIX C: Task Knowledge Test ........................... 138
APPENDIX D: Self-Efficacy Scale ............................ 146
APPENDIX E: Task Performance Inventory ...................... 147
APPENDIX F: Perceptions of Situation Competitiveness .............. 150
APPENDIX G: Post-Performance Attitudes ....................... 151
APPENDIX H: Participant Consent Form ........................ 152
APPENDIX 1: Protocols for Experimental Conditions ................ 153
LIST OF REFERENCES .................................... 156

TABLE 1:

TABLE 2:

TABLE 3:

TABLE 4:

TABLE 5:

TABLE 6:

TABLE 7:

TABLE 8:

TABLE 9:

TABLE 10:

LIST OF TABLES

Page
Summary of Study Hypotheses ......................... 59
Means, Standard Deviations, and Reliabilities of Study Variables . . . 71
Intercorrelations Among Study Variables ................... 72

Results of Hierarchical Regression Analyses with Performance Accuracy
Regressed on Competitive Orientation and Ability ............. 78
Results of Hierarchical Regression Analyses with Performance Quantity
Regressed on Competitive Orientation and Ability ............. 79
Results of Hierarchical Regression Analyses with Performance Accuracy
Regressed on Situation Competitiveness and Ability ............ 82
Results of Hierarchical Regression Analyses with Performance Quantity
Regressed on Situation Competitiveness and Ability ............ 83
Results of Hierarchical Regression Analyses with Performance Accuracy
Regressed on Goal Situation and Ability ................... 85
Results of Hierarchical Regression Analyses with Performance Quantity
Regressed on Goal Situation and Ability ................... 86
Results of Hierarchical Regression Analyses with Performance Accuracy

Regressed on Situation Competitiveness and Competitive Orientation . 88

TABLE 11:

TABLE 12:

TABLE 13:

TABLE 14:

TABLE 15:

TABLE 16:

TABLE 17:

TABLE 18:

Results of Hierarchical Regression Analyses with Performance Quantity
Regressed on Situation Competitiveness and Competitive Orientation . 90
Results of Hierarchical Regression Analyses with Performance Accuracy
Regressed on Goal Situation and Competitive Orientation ........ 93
Results of Hierarchical Regression Analyses with Performance Quantity
Regressed on Goal Situation and Competitive Orientation ........ 95
Results of Logistic Regression Analyses with Assigned Goal Acceptance
Regressed on Situation Competitiveness and Competitive Orientation . 98
Results of Hierarchical Regression Analyses with Goal Commitment
Regressed on Goal Situation, Situation Competitiveness, Competitive
Orientation, and Respective Interaction Terms .............. 100
Results of Hierarchical Regression Analyses with Performance Accuracy
Regressed on Goal Situation, Situation Competitiveness, Competitive
Orientation, Goal Commitment, and Respective Interaction Terms . . 107
Results of Hierarchical Regression Analyses with Post-Task Self-Efficacy
Regressed on Pre-Task Self-Efficacy and Performance Accuracy . . . 109
Results of Hierarchical Regression Analyses with Post-Task Self-Efficacy

Regressed on Pre-Task Self-Efficacy and Performance Quantity . . . 110

FIGURE 1:

FIGURE 2:

FIGURE 3:

FIGURE 4:

FIGURE 5:

LIST OF FIGURES

A Conceptual Matrix of Competition Research ..............

Conceptual Model of Relationships Among Key Study Variables . . . .

Performance Accuracy Scores at Three Time Periods ..........
Performance Quantity at Three Time Periods ...............
Interaction of Goa] Situation and Competitive Situation on Goal

Commitment ....................................

Page

.11

48

.74

.76

104

INTRODUCTION

Industrial and organizational (l/O) psychologists have traditionally considered
motivation to be one of the key determinants of individual performance within
conventional work settings (Pinder, 1984). As a result, a plethora of research related
to work motivation has been conducted in the past 50 or 60 years (Kanfer, 1990). Both
theoretical and empirical approaches have been used to examine topics such as goal
setting (Locke & Latham, 1990), incentives and reward systems (Guzzo, 1979),
intrinsic rewards (Deci & Ryan, 1980), expectancies (Vroom, 1964), and traits, needs,
and drives (Kanfer, 1990). These diverse topics have been studied from both
individual and group levels of analysis and in a variety of settings including laboratory
investigations, field experiments, and naturalistic observations (Kanfer, 1990).
However, irrespective of the specific topic or approach of a particular study, the
ultimate question of interest has been, ”What are the forces, both internal and external,
that result in an individual initiating work-related behavior, as well as determine the
form, direction, intensity, and duration of the behavior (Pinder, 1984)?"

The broad scope of the previous question and the relatively narrow views of
most individual motivation theories illustrates the fractionist approach that has
characterized the study of work motivation. Stated another way, despite the collective

breadth and depth of research on work motivation, individual theories have typically

2

taken a rather limited view of the problem. In spite of this narrow focus and the well
documented limitations of various theories of motivation, researchers have continued to
promote their efforts as the theory of work motivation (Kanfer, 1990). This myopic
perspective of work motivation is further suggested by the limited integration among
key theories and/or constructs despite the vast amount of conceptualization and
empirical research within the many subareas of motivation over the past 50 or more
years (Kanfer, 1990).

An integration of concepts within the area of work motivation is needed to
produce a meaningful and useful ”meta-theory" of motivation (Kanfer, 1990). In fact,
several authors have begun to develop such models (Kanfer, 1990; Landy & Becker,
1987). The general feature shared by these approaches has been a combination of
constructs from many different subareas in the work motivation literature (6. g. , goals,
self-efficacy, expectancies). This integration has led to the development of an
expansive, hierarchically-organized architecture for considering the broader construct
of work motivation. The primary goal of such integrative models has been to provide a
framework for understanding work motivation at the level implied by Pinder's (1984)
question.

While models such as those proposed by Kanfer (1990) and Landy & Becker
(1987) have provided an integration of key constructs within the area of work
motivation, another useful method for constructing more integrative theories of work
motivation may be to combine key constructs across research areas of psychology

(Kanfer, 1990). The utility of this type of integration has been demonstrated in a

3

variety of areas within [/0 psychology. For example, many of the constructs (e. g.,
search patterns, framing effects, and decisions in uncertain environments) and methods
(e. g., multiple-cue probability learning and process tracing) commonly associated with
individual decision making research in applied settings (Stevenson, Busemeyer, &
Naylor, 1990) had their origins in research related to cognitive psychology (Abelson &
Levi, 1985; Stevenson, Busemeyer, & Naylor, 1990). Had I/O researchers not
incorporated ideas and results from this other literature, the base of knowledge
regarding decision making within organizational contexts would not be at it's current
state (Stevenson, Busemeyer, & Naylor, 1990). In summary, integration of variables
and constructs that are common not only within the work motivation literature, but also
considered by other areas of psychology as critical in understanding motivation may
provide a richer view of work motivation.

The current paper describes an attempt toward building such an integrative
framework. Specifically, research related to the cross-disciplinary motivational topic
of competition is reviewed and integrated within the well developed theoretical
framework of goal setting. The importance of integrating a variety of perspectives of
competition is demonstrated through a discussion of key research results from sport
psychology (Gill & Deeter, 1988), educational psychology (Ames, 1984),
developmental psychology (Monsaas & Engelhard, 1990), and 1/0 psychology (Locke
& Latham, 1990).

The integration of competition within a goal setting framework is based on the

fact that 1/0 psychologists have considered goal setting to be a key component of any

4

integrative framework for explaining work motivation because of the broad empirical
support for goal effects (Locke, Shaw, Saari, & Latham, 1981). However, a number
of observed boundary conditions and constraints have suggested the limitations of the
effectiveness of goal setting in particular situations (Locke & Latham, 1990).
Additionally, current research (Locke & Latham, 1990) in the area of goal setting has
investigated the potential moderating effects of a variety of phenomena (e.g. ,
incentives, task complexity, and goal commitment). One moderator that has received
insufficient attention to date has been competition (Locke & Latham, 1990). The
demonstrated importance of competition in other domains clearly indicates that this
neglected variable must be addressed if goal setting theory is to serve as the framework

for a multi-disciplinary approach to work motivation (Locke & Latham, 1990).

Competition

The construct of competition has been examined from a number of perspectives.
It has been treated as an organizational-level variable (Carlton & Perloff, 1990; Steers,
1991), a group-level variable (Schermerhorn, 1986), a situational variable (Locke &
Latham, 1990), and an individual difference variable (Monsaas & Engelhard, 1990).
Because competition has been studied from such different perspectives, the extensive
literature on this topic reaches beyond the scope of the current paper. However, a brief
review of some of the principal definitions of competition provides a theoretical
framework for the current study.

Some of the research that has examined competition has considered the

5

construct from a macrosocial perspective. For example, researchers in the area of
organizational science (Carlton & Perloff, 1990) have often defined competition from
an economic/market—oriented perspective. In such conceptualizations, competition
exists at the organizational level of analysis and is manifested in such topics as
competitive strategies, supply—demand curves, and short-run/long-run equilibrium
(Carlton & Perloff, 1990). In addition to the organizational level of analysis,
competition has also been examined at the group level. The focus of this research has
been on examining the inter-group competition within larger organizations.
Specifically, since groups within an organization often rely on common resources, each
group's desire to succeed creates competition over these scarce supplies (Schermerhorn,
1986). Although both the organizational and group views of competition may provide
important perspectives for understanding competition, these macrosocial perspectives
cannot fully explain the behaviors of individuals.

At the individual level of analysis, competition research has been divided along
two major viewpoints. The first, illustrated by Johnson, Johnson, & Skon (1979),
suggests that competition arises primarily from situational characteristics (i.e., some
situations are more or less competitive than others). In contrast, an alternate view
exemplified by Monsaas & Engelhard (1990) is that competitiveness is primarily the
result of individual differences (i.e., some people are more or less competitive than
others). One of the important distinctions within this literature is between competition,
a behavior, and competitiyeness, a situation or person characteristic. Research related

to these perspectives is discussed in the following sections.

6
C .. S. . E Il'll

A study by Johnson, Maruyama, Johnson, Nelson, and Skon (1981) illustrates
the view of competitiveness as a situational variable. Johnson et al. (1981) defined a
competitive situation as "one in which the goals of separate participants are so linked
that there is a negative correlation among their goal attainments. " Two critical features
of this definition are: (1) competition is caused by an environmental characteristic and
(2) a competitive situation necessarily places a "win-lose" emphasis on individuals
within the situation. The latter aspect of the Johnson et al. (1981) definition places an
important restriction on this perspective of competitiveness. That is, only situations
which result in a perfect negative relationship between the goal attainments of
individual participants should be considered competitive.

The relatively narrow focus of the previous definition has been modified to take
into account the variety of other competitive situations that may exist. An example of a
more inclusive definition of competitiveness was presented by Tjosvold (1993). This
view suggested that a competitive situation was ”one in which the attainment of one
individual's goals makes another individual's goal attainment less likely." While
Tjosvold ( 1993) agreed that competition is the result of situational characteristics, he
recognized that competition can arise not only in ”win-lose" situations, but also in
situations where there is a probabilistic negative relationship among individual
outcomes.

Other researchers (cf. Ames, 1984 and King & Sorrentino, 1983) that have

studied competition and its effects at the individual level have adopted similar

7

definitions to those of Johnson et al. (1981) and Tjosvold (1993). Irrespective of the
definition employed by researchers within this perspective, all have made the same
critical, common assumption: competition results entirely from characteristics of the
situation (Johnson, Johnson, & Skon, 1979). While this perspective has generated
interesting and important results related to the impact of competitive environments on
individual behavior, it has failed to consider the competitive orientation that individuals
may bring to the situation.

A similar body of research has examined the effect of individual differences in
competitive behavior. Monsaas and Engelhard (1990) offered a definition of individual
competitiveness that illustrates this particular viewpoint. Specifically, these authors
suggested that individual competitiveness may bedefined as the desire to win at be
better than others engaged in the same, or similar, activityf;

Two critical features of this conceptualization have had implications for
considering competitiveness as an individual difference variable. First, that individuals
differ with respect to their competitive orientation, or competitiveness, has led
researchers in this area to search for main effects for individuals, irrespective of
situational contexts. Second, Monsaas and Engelhard's definition reflects the same idea
as Tjosvold's (1993) suggestion that competition need not be solely a ”win-lose"
orientation. While this ”win-lose" focus has been used to describe some types of
competitiveness, it has also been suggested that individuals may strive to simply ”be
better" than a referent other (Monsaas & Engelhard, 1990).

A related perspective of competition comes from the research on negotiation and

8

conflict. In a review of this literature, Thomas (1992) defined conflict as "the process
that begins when one party perceives that the other has negatively affected, or is about
to negatively affect, something that he/she cares about (p. 653). " A key factor of this
definition that serves to delineate conflict from competition is the emphasis on the
direct interdependence of outcomes. While Thomas (1976; 1992) acknowledged that
outcomes other than "win-lose" (e. g., win-win) are possible, he suggested the critical
characteristic of a conflict situation is that individuals have ditccmffccts on the
outcomes of others. By contrast, competitive situations have generally been defined by
the lack of direct intervention by participants on others’ outcomes (e. g., Weinberg,
Gould, & Jackson, 1979). As an illustration of this difference, consider the following
example. Football games are more appropriately termed conflict situations because
teams directly attempt to impede the goal attainment of each other. Alternatively, golf
is considered competitiite because of the lack of direct competitor intervention.

A more detailed description of the research that has examined competitiveness
as both a situational and an individual difference variable in competition is presented
later. At this point it is important to address another key consideration in the definition
of competitiveness: the comparison referent used by individuals in competitive
situations. A brief description of the distinction between frames of reference will

provide an additional means for considering competition research.

9
IMP- B -E BE 'C .. El .

Irrespective of whether competition is attributed to situational or personal
characteristics, a fundamental idea has been that individuals compete against some
referent (cf. Deci & Ryan, 1980). ThMmpumn referent has been defined as an
internal standard of performance by which individuals compare their current
performance levels (Csikszentmihalyi, 1975, 1978). Some critics of this view have
suggested that when within-person referents are the primary standards by which
individuals compare their performance level, competition is isomorphic to intrinsic
motivation (e. g., Deci & Ryan, 1980). In fact, some authors (Deci & Ryan, 1980)
have further suggested that such a view should more precisely be termed a ”mastery"
situation, rather than a competitive one. However, no matter what the specific
terminology that has been used, past research (e. g., Csikszentmihalyi, 1975 , 1978) has
demonstrated that individuals engage in such comparisons and that these comparisons
can impact task performance as well as other key individual outcome variables (e. g.,
self-efficacy and task satisfaction).

Alternatively, thew view has suggested that individuals compare
their performance to that of others engaged in the same, or similar, activities. As Deci
and Ryan (1980) observed, it is this type of situation that has most often been defined
as competitive within much of the motivation literature. More specifically, since
typical competitive situations involve two or more parties (i.e. , participants) attempting
to outperform one another, the most common performance standard (i.e. , referent) has

been another participant's performance level. Similar to the within-person perspective,

10

the general conclusion from the literature on between-person comparisons has been that
such situations affect not only individual performance, but also a variety of other
individual outcome variables (e. g., aggression, frustration, and satisfaction) (Deci &

Ryan, 1930).

11' . l' [C .. B l

The previous discussion has illustrated that competition research has been
broadly categorized along two independent dimensions. The first dimension has
attributed competition to either a situational or personal characteristic, while the second
dimension has been defined in terms of the referent used (i.e., either within- or
between-person comparisons). These dimensions can be thought of in terms of a 2 x 2
matrix (see Figure 1) that can be used to broadly classify research related to
competition and provide a framework for considering the perspective of competition
adopted in the current study.

Cells 1 and 2 of the matrix represent instances of competition research when the
referent, or comparator, has been a within-person standard. As previously described,
research that has been conducted with respect to this dimension has typically been
concerned with issues related to intrinsic motivation (see Csikszentmihalyi, 1975, 1978
and Deci & Ryan, 1980). An everyday example of the type of behavior included in
these cells can be seen in the performance of golfers. Many golfers have standards of
performance that are internally generated. They evaluate their performance for a

particular round of golf relative to how well they have played in the recent past, not

11

Situation Person

 

 

Within

Person 2 1
Between

Person 3 4

 

 

 

 

Figure 1. A Conceptual Matrix of Competition Research

12

necessarily with respect to the scores of other golfers. The distinction between whether
this comparison process arises from situational cues (i.e., cell 2) or characteristics of
the individual (i.e., cell 1) is an important consideration for researchers operating
within this portion of the matrix. However, because the current research is concerned
primarily with between-person comparisons, the distinction and issues illustrated above
are considered outside the scope of this study.

Previous research on competition in both [/0 (e. g., Locke & Latham, 1990) and
educational psychology (e.g., Ames, 1984, Johnson et al., 1981, King & Sorrentino,
1983) has often occurred within cell 3 of the matrix. Specifically, this cell represents
research that has taken the perspective that competition arises primarily from the
situation and involves a comparison between self-performance and the performance of
some relevant other(s). Further, this view has implicitly suggested a main effect for
the situation. Alternatively, this view has neglected to consider the potential influence
of competitiveness as an individual difference factor. Consequently, these perspectives
often have examined how various learning or work environments foster either
cooperative or competitive behaviors. As a result, an extensive literature has developed
that addresses the effects of various environmental cues on b6th individual perceptions
of competitive situations and the subsequent effects of these perceptions on individual
performance. The results of these studies have provided important information in
determining what effect situational competitiveness exerts on individuals. Nonetheless,
these studies have suffered from a rather myopic perspective by suggesting only

situational factors to be an important determinant of competition.

13

The final cell in the proposed matrix (cell 4) represents research that has
suggested a between-person comparison process and that competition arises from an
individual difference characteristic (e. g., Martens & Gill, 1976). This perspective
asserts the importance of an individual difference variable often called competitiveness
(e. g., Martens & Gill, 1976) or competitive orientation (e. g., Vealey, 1986). Research
adopting this perspective has often been conducted in the area of sport psychology. In
contrast to cell (3), research from this perspective has typically been framed in terms of
how different types of individuals (i.e. , competitive or noncompetitive) respond and
perform in a variety of situations. Again, quite an extensive literature has accumulated
with respect to how competitiveness impacts individual performance. However, this
view of competition also has suffered from the same limitation as research proposing
only a situation main effect: a myopic perspective that has neglected to consider the

potential interaction between the person and situation.

Summary

From this broad review of the competition literature, at least two conclusions
can be drawn. First, competitiveness plays an important role in many performance
contexts. Researchers such as Johnson et al. (1981) and Monsaas & Engelhard (1990)
have provided evidence for the importance of considering the impact of competitiveness
arising from both situations and individuals, respectively. Second, although research
has demonstrated the independent role of competitiveness as a function of situations or

individuals, there has been little research that has focused on their possible joint effects.

14

Because the behavior of individuals can be considered to be a function of both personal
traits and situational characteristics (Hogan, 1991), research that neglects this potential
interaction provides potentially incomplete information.

This point is especially important in light of the assertion that competition is
more realistically represented by an interactionist framework that includes
characteristics of the situation and the individual in defining the level of
competitiveness in a particular context (e. g., Krane, Williams, & Feltz, 1992).
Researchers adopting this ”interactionist” perspective have suggested the most
important issue to be, ”What is the nature of this interaction?" There have been two
primary responses to this question. One has suggested that the relationship is one of
reciprocal causation. Specifically, the situation exerts influence over individuals'
perceptions of competitive cues, while at the same time individuals' competitiveness
colors the cues (Krane, Williams, & Feltz, 1992). A second view has been that
situations have cues that define them as more or less competitive and that the
competition inherent in a situation has an effect on individuals' performance.
Moreover, the relationship between situation and performance is moderated by
individual differences (e.g. , competitive orientation). Because little evidence has been
gathered in support of either position, recent investigators have noted the need for
future research to test them (Krane, Williams, & Feltz, 1992).

Thus, given previous research on competitiveness, the current study seeks to
examine the hypothesis that competitiveness is a characteristic of both situations and

persons and that performance in specific situations will be affected by both factors.

15

This view extends current conceptualizations of competition within the I/O literature by
suggesting that competitiveness involves important individual differences as well as
situational cues. In addition, by adopting an interactionist perspective, the current
approach examines the nature of the combination of person and situation

characteristics.

Review of Competitiveness Literature
With the previous synopsis of competition research and current definition of
competition in mind, a review of the literature that has focused on competition both in
terms of individual differences and situational variables is presented. Theoretical
issues, methodologies, and key results from this literature are reviewed and integrated ‘

to provide a framework for the research questions asked in the current study.

Il"llE'Efi 'C .. 131'

As an individual difference variable, competitiveness has been examined by
researchers from at least two perspectives. One perspective has been interested in
construct development and refinement (Butt, 1979; Corcoran, 1989; Gill & Deeter,
1988; Gill, Kelley, Martin, & Caruso, 1991; Martens & Gill, 1976), while the other
focus has examined how various conceptualizations and operationalizations of
competitiveness are related to important individual outcome variables (Matheson &
Mathes, 1991; Weinberg, 1985). Results of research related to each of these emphases

are presented.

16

There have been a number of conceptualizations and operationalizations of
competitiveness as an individual difference variable (Butt, 1974). Indeed, some of the
initial research in this area focused not on competitiveness per se, but on a closely
related individual difference variable: competitive anxiety. This research is important
in illustrating the fundamental idea that individuals have certain predispositions to
respond differently. For example, Martens and Gill (1976) reported an investigation
involving the Sport Competition Anxiety Test (SCAT). This study examined the
influence of ”competitive A-trait" on a number of individual outcome variables within
competitive sport situations. Martens and Gill (1976) defined competitive A-trait as a
relatively stable personality disposition that reflects a person's tendency to perceive
competitive situations as threatening or nonthreatening. Martens (1977) described the
development of the SCAT as an alternative to more global measures of general trait
anxiety (i.e., A-trait). Because situation-specific measures of trait anxiety have
demonstrated greater predictive power in the situations for which they were developed
(e. g., Martens, 1977), the SCAT was developed as a tool to be used as a predictor in
competitive sport situation.

The Martens and Gill (1976) study was designed to provide support for the
SCAT measure as well as to examine the impact of success or failure on measures of
competitive A-trait. Results of this study provided some construct validity evidence for
the SCAT. In addition, results suggested that the relationship between levels of
competitive A-trait and failure was negative. Specifically, the more games an

individual won, the lower the level of A-trait anxiety (Martens & Gill, 1976).

17

Additional support for the validity of the SCAT has been offered by Martens (1977)
and Corcoran (1989). These studies presented results that demonstrated both
convergent and discriminant validity evidence for the SCAT as a measure of
competitive anxiety.

In contrast to this measure of competitive anxiety, Butt (1979) conceptualized a
construct called ”competitiveness”, which was operationalized in a set of scales
designed to measure a variety of sport-related motivations. Among the measures that
were described in this research was a scale proposed to assess the degree to which an
individual desires to defeat others in a contest. Butt (1979) hypothesized that
competitors perceive a contest as an opportunity for self-assertion and dominance over
others. Highly competitive individuals would be more concerned with status and
position when completing a task than would those lower in competitiveness. Further,
highly competitive individuals would be expected to be resentful and frustrated if task
performance was thwarted (Butt, 1979). Results from this study indicated that
competitive behavior appeared to be "the social expression of the psychological states
of aggression and conflict (Butt, 1979). " Additionally, individuals who scored high on
the competitive scale also described themselves as more insecure and lacking in self-
confidence than those who scored lower on the scale (Butt, 1979).

Another attempt at measuring individual competitiveness was the Sport
Orientation Questionnaire (SOQ) developed by Gill and Deeter (1988). Specifically,
the SOQ was designed to measure competitive orientation in sport situations. SOQ

development reflected the idea that competitive orientation was a multidimensional

18

construct. Three separate, but related, factors were defined as critical in determining a
person's degree of competitiveness (Gill & Deeter, 1988). Although the items
originally were written with the Spence & Helmreich (1983) notion of achievement
orientation in mind, the final version of the scale was based upon empirical item
analyses and factor analyses. The first dimension, competitixeness, was related to the
desire to strive for success in competitive situations. Winotientation was the second
dimension and was defined as the degree to which an individual had a focus on winning
and avoiding losing. The final dimension was defined in terms of an individual's focus
on personal goals and was termed goaLotientation. Reported studies that have used this
measure have reported evidence for both convergent and discriminant validity (see Gill
& Deeter, 1988; Gill, Dzewaltowski, & Deeter, 1988).

Another widely used measure of competitive orientation reported in the sport
psychology literature has been the Competitive Orientation Inventory (COI) developed
by Vealey (1986). Although designed to measure the same construct as the SOQ (i.e. ,
individual competitiveness in sport situations), the COI has been a substantially
different instrument with respect to both construct conceptualization and
operationalization. Unlike the SOQ, the items on the COI were developed and retained
based solely on rational content analyses. In addition to the differences in scale
construction, the COI was based primarily on the task-ego orientation distinction
proposed by Nicholls (1984). N icholls (1984) defined an W as one in
which an individual seeks to demonstrate ability by improving task mastery rather than

demonstrating ability relative to others. On the other hand, a taskotientation is one in

19

which the individual seeks to demonstrate ability by performing well relative to others.
In addition, Nicholls (1984) suggested that different situations may elicit different
orientations within the same individual: an interactionist perspective which will be
addressed later. An additional difference between the CO] and SOQ was that only two
dimensions of competitive orientation were proposed in the C01: (1) the orientation
toward performing well, and (2) the orientation toward winning (Gill et al., 1991).

Another distinguishing feature of the C01 is the manner in which individuals are
scored. Responses to the C0] are framed as choices that indicate the relative
importance of the two dimensions (Gill et al., 1991). Specifically, the COI measure
consists of a 4 x 4 matrix with four levels of outcome and four levels of performance.
Respondents indicate for each of the cells how satisfying the particular combination is
on a scale from 0 (very unsatisfying) to 10 (very satisfying). Individuals are scored on
the COI by calculating the proportion of variance due to performance and the
proportion due to outcome (Gill et al., 1991). Refinement of the COI scale along with
further construct validity evidence has been reported by Vealey (1986, 1988).

Gill et al. (1991) conducted a methodological study that compared the extent to
which the SOQ and C01 measures tapped the same construct. Given the differences in
conceptualization and operationalization of the two constructs, Gill et al. (1991)
predicted that these two scales would not measure the same dimensions of competitive
orientation. Results indicated some support for this hypothesis. Gill et al. (1991)
found that the sport-specific achievement orientation, as measured by the SOQ, and

performance versus outcome orientations, as measured by the COI, were relatively

20

independent dimensions.

Additional research examining individual competitiveness has examined the
construct's possible causal antecedents. Much of this research has examined the role of
genetic and environmental influences on an individual's competitiveness. As Monsaas
and Engelhard (1990) noted, Mead (1937) demonstrated the critical role environmental
settings play in developing an individual's social behavior. Mead (1937) contended
that social groups such as families vary significantly in terms of the relative emphasis
placed on cooperative, competitive, and individualistic behaviors and attitudes.

In a recent examination of the relationship between childhood home
environments and competitiveness as adults, Monsaas and Engelhard (1990) highlighted
several critical issues. They proposed that ”because competitiveness is a social
behavior, it may be learned in much the same way as other social behaviors. " Drawing
on a variety of sources (e. g., Bandura, 1977a; Deutsch, 1949; Johnson & Johnson,
1987; and Mead, 1937), Monsaas and Engelhard (1990) proposed that individuals who
came from home environments where competitiveness was modeled, reinforced, and
valued would display a greater degree of individual competitiveness than those from
non-competitive home environments.

Monsaas and Engelhard (1990) gathered data to test this proposition by means
of extensive individual interviews covering a variety of topics. Because the interviews
were conducted for a larger purpose than this study alone, questions related to
individual and home competitiveness were embedded as part of a longer questionnaire

battery. A five-item scale of individual competitiveness included items addressing the

21

importance of winning or being the best, the motivation for wanting to win or be the
best (e. g., to impress others), and competitive behaviors (e. g. , did they compete with
others regularly). An independent sample of judges then rated these items on a three-
point scale from 1 (not competitive) to 3 (very competitive). Home environment
competitiveness was assessed in a similar manner using a four-item scale. Interviews
with parents and relevant others (e. g., peers and coaches) were also conducted
following similar procedures in order to ”corroborate ratings of competitiveness"
provided by individuals. Simple correlational analyses indicated that, as hypothesized,
individual competitiveness was significantly correlated with home environment
competitiveness (r = .68). That is, approximately 46% of the variance in individual
competitiveness could be accounted for by home environment competitiveness.

Notwithstanding the potential problem of method bias in the data reported by
Monsaas and Engelhard (1990), several aspects of this study should be mentioned.
First, the magnitude of the observed relationship suggests that the degree of
competitiveness in developmentally early environments should be considered when
attempting to understand the construct of individual competitiveness. Second, unlike
other studies of competition (cf. Johnson & Johnson, 1987; Slavin, 1987), Monsaas
and Engelhard (1990) evaluated competitiveness in a non-laboratory setting. Finally, a
very unusual sample (i.e., individuals from specialized talent areas) was used in this
study and therefore generalizability to other samples is unknown.

Additional research on the antecedents of competitiveness has examined the role

of gender differences. Specifically, this research has considered the role of an

22

individual's expectancy for success in various situations. The primary view has been
that these expectancies are related to gender and subsequently to performance. Early
work in this area (e.g., Feather & Simon, 1973; Maccoby & Jacklin, 1974) reported
that females generally exhibited less self-confidence than males in certain types of
situations, particularly competitive ones. However, other research has suggested no
gender differences in these situations (e.g., Corbin & Nix, 1979; House & Perney,
1974). In an attempt to resolve these conflicting results, Hall (1990) examined the
effects of gender, skill level, and opponent gender on self-confidence on a competitive
task. Results indicated that gender differences were erased when differences in initial
performance level were controlled. Hall (1990) suggested that a potential reason for
gender differences in early research may have been due to a failure to control for these
initial performance differences. In short, Hall's (1990) conclusion was that skill level
is a better predictor of expectancies than gender.

Taken together, the results of these studies demonstrate that while the construct
of competitiveness has received attention, there continue to be disagreements regarding
the appropriate conceptualization and operationalization of the construct. On one hand,
these disagreements are troubling because they indicate that an extensive amount
remains to be learned about competition and competitiveness. On the other hand, they
do illustrate the potentially important role that individual competitiveness may play
with respect to performance in a variety of situations. It is also important to consider
that since most of this research has been conducted in the area of sport psychology, the

results of these efforts may be limited in their generalizability to other contexts. That

23

is, certain aspects of sport situations such as well defined roles, strong emphasis on
motor skills, and immediate feedback may not be common to other environments (e.g.,
traditional work settings). However, the importance of competitiveness as an
individual difference variable in sport situations suggests that attention should be paid

to the construct in other settings as well.

[I . . l B l l [2

While the previous literature review has described what competitiveness is, it is
also necessary to consider what it is not. The following sections address this issue by
presenting a review of some related concepts. Specifically, achievement motivation,
learning/outcome orientation, and self-efficacy are examined to identify definitional
elements that distinguish each from competitiveness.

AchicxemcntMmiMatiQn. Achievement motivation has traditionally been
acknowledged as a ”trait" theory of motivation (e. g., Kanfer, 1990). The fundamental
assumption characterizing theories within this perspective (e. g. , Alderfer's Existence-
Relatedness-Growth Theory, 1969; Maslow's Need Hierarchy, 1943, intrinsic
motivation, job characteristics theory, and organizational fairness/ justice theories) is
that behavior is determined primarily by individual difference factors, rather than
environmental or situational characteristics. Additionally, theories adopting this view
have typically suggested that these individual difference factors are innate and relatively
unchangeable (Kanfer, 1990).

Within the achievement motivation literature, there have been a number of

24

perspectives. One of the most prominent of these perspectives is Atkinson's (1957)
definition of achievement motivation as a broad framework for considering individual
behavior. Alternatively, a second important perspective associated with McClelland
(1965) has considered Need for Achievement (nAch) to be a simple personality factor.

Atkinson (1957) offered one of the original theories of achievement motivation.
This theory assumed that the achievement motive was a unitary construct represented as
a basic dispositional tendency to strive for excellence (Kanfer, 1990). Specifically,
Atkinson. (1957) suggested that an individual's tendency to approach a task was
determined by (a) motives to achieve success, (b) motives to avoid failure, (c)
perceived probability of task success, and (d) the incentive value of success. An
important feature of Atkinson's (1957) theory is that the incentive value of success ((1
above) is proposed to be positively correlated with task difficulty. This leads to the
specific prediction that individuals classified as ”success-oriented” should perform best
on tasks of intermediate difficulty, and persist longer at these tasks in the face of failure
than persons classified as ”failure-oriented” (Kanfer, 1990). Conversely, ”failure-
oriented" persons should prefer either easy or difficult task levels.

Reviews of research testing Atkinson's model have reported mixed support (see
Campbell & Pritchard, 1976; Kanfer, 1990). Support for the predictions made by the
original model has been found in tightly controlled situations, but less than robust
support has been found in more unconstrained settings 0(anfer, 1990). As a result,
achievement motivation as conceived by Atkinson has undergone various

reformulations.

25

A number of theorists (Nicholls, 1984; Heckhausen, 1977; Kuhl, 1978, 1984)
have offered modified views of achievement motivation. For example, Nicholls (1984)
proposed a distinction between performance and learning motives contending that these
motives involve different motivational processes and, in turn, should result in different
outcomes (e. g., learning and task persistence) in various contexts (Kanfer, 1990). By
contrast, Heckhausen and Kuhl (1985) have proposed an action-control framework
based on the idea that individuals have either an action orientation (i.e. , are task
focused) or a state orientation (i.e., are focused on internal or emotional states) (Kuhl,
1984).

McClelland's (1965) more limited perspective on achievement motivation
proposed that need for achievement (nAch) was an important personality factor, but did
not consider the larger framework suggested by Atkinson (1957). Research testing
McClelland's (1965) theory has demonstrated that individuals with high nAch would
tend to: (1) prefer moderately challenging tasks, (2) have a strong need for
performance feedback, (3) prefer situations in which they can take responsibility for
performance, and (4) try new ways of doing things. O'Reilly, Chatman, and Caldwell
(1991) further suggested that individuals high in nAch prefer outcome-oriented
contexts. Finally, Miner (1980) has suggested that high nAch individuals prefer tasks
and situations in which success is attained through their own efforts as opposed to
chance or luck. Current research (e. g., Turban & Keon, 1993) has attempted to
examine the boundary conditions of nAch as well as the interactive effects of situational

characteristics and nAch on critical individual outcome variables.

26

Additional research related to nAch has incorporated it as part of the "Big Five"
personality dimensions where it has most frequently been considered as part of the
dimension labelled ”Conscientiousness" or "Conscience” (Barrick & Mount, 1991).
While there has been considerable disagreement regarding the components of this
dimension (Barrick & Mount, 1991; Botwin & Buss, 1989; Digman, 1989; Hogan,
1991), there has been some evidence that nAch represents a stable, enduring,
personality factor that includes traits such as dependable, hardworking, achievement-
oriented, and persevering (Barrick & Mount, 1991).

The previous description of nAch indicates at least some similarity to
competitive orientation. The critical feature differentiating these two constructs would
appear to be that achievement motivation typically has been presented as a motivational
construct applicable to any situation involving individual task performance
(McClelland, 1965). By contrast, investigators have usually defined competitiveness as
domain specific. Moreover, the term competitiveness has been reserved for situations
in which one individual's performance is assessed relative to another ”competing"
individual (Gill et al., 1991). As a result, while achievement motivation has been
applied to situations and contexts involving stable standards that can be internal or
external, competitive orientation has generally been applied to contexts when
performance has been compared to that of an external, potentially shifting, standard
(Gill et al., 1991).

IaarningxersuLQutcomeflrientation. Research on the C01 and SOQ has

illustrated the importance of considering competitiveness as a multidimensional

27

construct. In this vein, one of the primary differentiations has been between learning
and outcome orientations. A teaming, or mastery, orientation has been defined as one
in which individuals seek to increase their competence and to understand or master
something new (Dweck, 1986). By contrast an outcome, or performance, orientation
has been defined as one in which individuals seek to gain favorable judgments of their
competence or avoid negative judgments of their competence (Dweck, 1986).

A number of researchers (e. g., Dweck, 1986; Elliott & Dweck, 1988; Glaser,
1982; Weiss, 1990) have identified the influence of type of orientation on a number of
individual outcome factors. For example, Dweck (1986) found that orientation can
interact with self-confidence to affect a number of behaviors. Dweck (1986) asserted
that individuals with a performance orientation and high self-confidence in present
ability levels will display a "mastery—oriented" behavior pattern characterized by
seeking challenges and persisting in the face of obstacles. By contrast, individuals with
a performance orientation and low confidence in their abilities will display a "helpless"
behavior pattern characterized by challenge avoidance and low persistence. Dweck
(1986) further suggested that individuals with a learning orientation will display a
"mastery-oriented” behavior pattern, irrespective of self-confidence. Elliott and
Dweck's (1988) subsequent test of these predictions provided support for these
predictions.

In a related study, Butler (1990) examined the effects of performance versus
mastery orientations on another individual outcome, children's self-assessment of

ability. The influence of two conditions were examined in this study. A performance

28

condition, which Butler (1990) labelled "competitive," presented children with the goal
of drawing a figure better than anyone else. Alternatively, the mastery condition set
the goal of drawing a figure as close to a given standard as possible. These conditions
were considered analogous to the outcome and learning conditions described in
previous research (e.g., Elliott & Dweck, 1988; Martin & Gill, 1991).

Results indicated that younger children were more likely than older children to
overestimate the quality of their drawings in the performance (i.e., competitive)
condition. No effects were found in the mastery condition. Older children tended to
be accurate in the assessment of their performance regardless of condition. The
explanation offered for these results was that as children mature they adopt normative
criteria when in competitive conditions. This adoption of normative goals and criteria
allows older children to more realistically evaluate their performance in a variety of
situations. Thus, the results of this study in conjunction with results reported by Elliott
and Dweck (1988) have suggested that although type of orientation may affect some
behavioral responses, it does not impact the ability of individuals to accurately evaluate
their performance.

Ames (1984) similarly examined the impact of different goal structures on
performance and self-assessment. Ames (1984) used the terms competitixe and
mdnndual conditions to refer to outcome and learning orientations, respectively.
Participants were told either to attempt to perform better than another participant (i.e. ,
competitive) or try to achieve some externally set standard of performance (i.e.,

individual). Results indicated that children made more ability attributions in the

29

competitive than in the individual condition. Additionally, participants in the
individual condition displayed mastery orientations in that they made more effort
attributions. In explaining the data, Ames (1984) hypothesized that participants asked
themselves, ”Was I smart?” in the competitive condition and, "How can I do this
task?” in the individualistic condition. Unfortunately, performance was a manipulated
variable so that the comparison between competitive and individual conditions in terms
of effects on performance could not be examined.

When the previous results are integrated with related research regarding
competitiveness by Gill and Deeter (1988) and Vealey (1986), a clear conclusion can
be drawn regarding the relationship between competitiveness and performance
orientations. Specifically, the results of studies that have examined learning versus
outcome orientations (e. g., Ames, 1984; Butler, 1990; Dweck, 1986; Elliott & Dweck,
1988) and competitiveness have suggested that in less competitive situations individuals
having a mastery orientation tend to perform better than individuals with a competitive
orientation. However, when the situation is more competitive, just the opposite has
been observed.

Self-Efficacy. A final construct that has often been considered in discussions of
competition-related individual difference variables is self-efficacy. This construct had
its origins in social cognitive theory (Bandura, 1977b, 1986), which is predicated on
the idea that behavior, cognitions, and the environment are dynamically related to each
other in a model of reciprocal causation (Gist & Mitchell, 1992). Wood and Bandura

(1989) defined self-efficacy as ”beliefs in one's capabilities to mobilize the motivation,

30

cognitive resources, and courses of action needed to meet given situational demands. "
Gist and Mitchell (1992) defined self—efficacy as ”a person's estimate of his or her
capacity to orchestrate performance on a specific task. " The critical features of these
definitions have been that self—efficacy is: (1) an individual difference construct, (2)
perceived by the individual, and (3) task, or situation specific.

Self-efficacy has received a great deal of research attention since it was
presented by Bandura (1977a). The diversity of topics to which this construct has been
related has been reviewed recently by Gist and Mitchell (1992). Although an extensive
review of the literature related to self-efficacy is well beyond the scope of the current
proposal, key theoretical ideas and relevant empirical results are presented in order to
highlight the relationship between self—efficacy and competitiveness.

In the original formulation of self-efficacy, Bandura (1977a) suggested that an
individual's previous task experiences form the foundation for making efficacy
judgments. Specifically, four broad categories of experience were postulated as
influencing an individual's perceptions of self-efficacy: personal attainments (enactive
mastery), vicarious experience (modeling), verbal persuasion, and physiological arousal
(anxiety) (Gist & Mitchell, 1992). Although these four types of experiences were
suggested as critical in determining efficacy levels, it is the cognitive appraisal and
integration of these experiences that ultimately determines self-efficacy (Bandura,
1982).

The importance of self-efficacy judgements has been demonstrated through the

relationship between efficacy and task performance. Gist and Mitchell (1992)

31

presented a model of this relationship. From this model a number of evaluations
related to individual judgments of self-efficacy are suggested. First, task requirements
are assessed. This assessment process generates inferences about what is required to
perform a given task at a variety of levels. This analysis is expected to be most explicit
in situations where a task is novel. By contrast, extensive experience with a task will
reduce reliance on this type of analysis and increase efforts to interpret the causes of
previous performance (Gist & Mitchell, 1992).

This second type of assessment involves an attributional analysis resulting from
an appraisal of the four categories of experience proposed by Bandura (1982). As Gist
and Mitchell (1992) pointed out, the outcome of this analysis is initiated by the
question, "Why did I perform at a particular level?” That individuals do, in fact, ask
this question of themselves has been substantiated by Weiner (1985), who has
suggested that answers to this question (i.e. , the outcome of this attributional analysis)
generally revolve around three major dimensions of performance: ability, motivation,
and external factors. Thus, students evaluating their efficacy with respect to
performance on an upcoming final examination would examine the causes of their
performance on previous examinations in the class. Answering the performance
attribution question by concluding, ”I performed poorly because I did not have the
knowledge required” indicates an ability attribution, while, "I performed poorly
because I was not trying very hard,” is an example of a motivational attribution. ”I did
poorly because I was unlucky” is an example of an external attribution.

A third assessment that is critical to an individual's self-efficacy judgment

32

concerns the availability of specific resources and/or constraints for task performance
(Gist & Mitchell, 1992). This analysis includes a consideration of a variety of personal
factors (e. g., anxiety, available effort), as well as situational factors (e. g., distractions,
competing demands) that might impact performance (Gist & Mitchell, 1992).

The manner in which these three assessment outcomes are integrated to form a
self-efficacy judgment is not well understood (Gist & Mitchell, 1992). Although
progression through each phase is proposed to be relatively independent, there is
theoretical support for the suggestion that it might be more of an iterative process
(Bandura, 1988; Gist & Mitchell, 1992). Indeed, as Gist & Mitchell (1992) pointed
out, the conceptualization of self-efficacy as task-specific implies the progression
through each of these analyses is task-specific as well.

There is extensive research evidence on the effects of various experience factors
on self-efficacy (Bandura, 1982; Gist, 1987; Gist & Mitchell, 1992; Kanfer, 1990;
Russell & McAuley, 1986; Schunk, 1983). The most basic finding is that people who
think they can perform well on a task actually do better than those who think they will
fail (Bandura, 1977a). More important than this obvious conclusion are some of the
other empirical results associated with this theory. First, self-efficacy differences are
generally associated with actual differences in skill level. That is, those individuals
who have objectively greater skill levels also tend to have higher self-efficacy than
those with lower skill levels (Gist & Mitchell, 1992). Second, as previously described,
a variety of individual differences related to both personal and situational factors affect

self-efficacy judgments (Gist & Mitchell, 1992). For example, Kavanagh and Bower

33

(1985) examined the impact of positive and negative arousal on judgments of self-
efficacy for a task. Results indicated higher self-efficacy scores for those in positive
mood states versus those in negative mood states. Gist and Mitchell (1992) reported
results from a study by Cervone (1985) that demonstrated when people were asked to
focus on the difficult aspects of a task, self-efficacy was lowered. Alternatively, when
asked to focus on the easier aspects of a task, individuals' self—efficacy scores
increased.

Despite the recognition of competitiveness as an important situational
characteristic, few studies have examined the impact of competitiveness on self-efficacy
judgments. Weinberg (1985) reported a study that examined the effects of self—efficacy
on cognitive strategies on the performance of a physically demanding, competitive task.
Specifically, this study investigated Bandura's (1982) hypothesis that high arousal
debilitates performance, thus decreasing people‘s expectations of success when they are
beset by aversive physiological feedback. Weinberg also examined the effects of
cognitive strategies (see Weinberg, 1985, or Weinberg, Smith, Jackson, & Gould,
1984 for a thorough description of cognitive strategies related to physical performance)
on performance of a physical task. Finally, Weinberg (1985) examined the interaction
of these two variables (i.e., cognitive strategies and self—efficacy). In all cases,
Weinberg and colleagues used a competitive muscular-leg endurance task.

Results replicated the positive relationship between self-efficacy and task
performance, with highly efficacious participants outperforming those with lower

efficacy. However, no main effect for cognitive strategies or interaction between

34

efficacy and strategies was found. Weinberg's (1985) interpretation of these results
was that efficacy was such a powerful agent in this situation that strategies could not
exert any influence. He also reasoned that because the cognitive strategies used had
been demonstrated to be effective in previous investigations, there must be additional
strategies for enhancing performance that led to the reported effects.

These results can be further clarified when considered along with previous
research (e. g., Weinberg, Gould, and Jackson, 1979). While primarily a simple test of
Bandura's (1977b) self-efficacy theory in a competitive situation, the Weinberg et al.
(1979) study also reported evidence related to the influence of strategies. Specifically,
though higher self-efficacy individuals performed significantly better on an endurance
task than did low self-efficacy individuals, it appeared that subjects with high self-
efficacy engaged in the strategy of "positive self-talk” to a greater extent than those
with low self-efficacy. An example of positive self-talk would be an individual saying
to her- or himself, "I know I can do this," while performing the task. Although this
effect was not significant, perhaps due to inadequate sample size, it does suggest that
strategies may have a relationship with self-efficacy.

Lee (1982) presented a study which examined not only the relationship of self-
efficacy to performance, but also the factors that may result in perceptions of efficacy.
Using a sample of gymnasts, Lee (1982) operationalized self—efficacy as an individual's
estimate of her score on each piece of apparatus. Although this operationalization of
efficacy is not necessarily consistent with recent views of efficacy (e. g., Gist &

Mitchell, 1992), interesting results were nonetheless obtained. Most notably, two of

35

the best predictors of performance were the gymnast's estimate (i.e., the efficacy
measure) and task experience. Another interesting, albeit puzzling, result was that
previous scores (i.e., past performance) did not significantly predict future
performance. However, Lee (1982) acknowledged that this could have been due to
small sample size in this particular setting. Additional explanations included the
instability of peak physical performance and the extreme restriction of range in a
sample of elite performers. However, these results conflict with data reported by
Krane, Williams, & Feltz (1992), in which past performance was a significant predictor
of future performance. Taken together, these studies suggest that efficacy and past
performance are likely to be good predictors of future performance and should be
examined in the same situation to determine which has greater predictive power.
Taylor (1989) posited two different types of self-efficacy as critical in
competitive situations: personal (i.e. , expectations based on an internally derived
standard of performance) and competitive (i.e. , expectations based on an externally
derived standard of performance). Based on the idea that different situations can
produce different cognitions (Ames, 1984), Taylor (1989) suggested that if an
individual performs a task under noncompetitive situations, personal self—efficacy will
be the more salient cognition. Alternatively, if an individual is under competitive
conditions, competitive self-efficacy will become more salient. Taylor (1989) also
suggested that this distinction is determined by the individual's point of reference
(internal vs. external standard) and the impact of different types of feedback

(performance vs. outcome). Competitive feedback (e.g. , you are beating your

36

opponent) should have greater impact on performance of an individual focused on
external standards of performance. In addition, personal self-efficacy should be a
better predictor of performance in noncompetitive situations while competitive self;
efficacy should be related to competitive performance. Taylor (1989) acknowledged
that these two types of self-efficacy are not independent, but did suggest there should
be little overlap. Results indicated the variance shared between the two efficacy
measures was small (ranging from 5% to 17%). Additionally, personal, but not
competitive, self-efficacy was predictive of subsequent performance and competitive
outcome feedback affected competitive self—efficacy.

These results from studies examining the impact of self-efficacy in competitive
situations have identified a number of still unresolved issues. Key among these are the
results from the Weinberg (1984, 1985) studies that suggest additional questions need
to be asked about the interaction of efficacy and strategies in both the physical and
cognitive performance domains. Specifically, what is the relative influence of self-
efficacy and various strategies of performance in competitive situations? and, how is

efficacy affected by various situations and performance levels?

If] [C "5"1Cl .. El'

In addition to competitiveness as an individual difference variable, an extensive
amount of research on competition-related behavior has examined the effects of
situational characteristics. As with the review of competitiveness as an individual trait,

this section presents a representative review of the common questions asked, key

37

variables studied, and typical results of this literature.

De Moja & De Moja (1986a) examined the effects of a particular competitive
situation on the individual outcome variables of anxiety and performance. An adapted
version of the State-Trait Anxiety Inventory was administered to a sample of motocross
riders at two separate times before an important race. Results indicated that the
expectation of participation in a high-level competition was associated with increased
state anxiety in the 17 hours before the race started for higher A-trait riders, but not for
those who scored lower on the A-trait measure. Additional research reported by these
authors also indicated that the relationship between state anxiety and performance was
negative (De Moja & De Moja, 1986b).

Matheson and Mathes (1991) examined the relationships among experience,
difficulty of task, type of event, competitive anxiety, and self—confidence among a
sample of high school female gymnasts. At the level of main effects, it was predicted
that anxiety would become greater with the stakes of the competition; operationalized
as a practice session, a dual meet, and a district championship competition. Anxiety
was measured with the Competitive State Anxiety Inventory-2 (CSAI-2). Results were
similar to those predicted, except that the dual meet resulted in greater anxiety than the
district championship. The authors suggested that this may have been due to the fact
that the dual meet occurred earlier in the season when gymnasts were more uncertain
about their own and others' abilities. Results for the self-confidence measure were
consistent with those for the anxiety scores; self—confidence was highest in the practice

session and lowest at the dual meet. Thus, prior experience with both self and others'

38

performance was hypothesized to be a key factor in determining if a competitive
situation engenders feelings of high self-confidence and anxiety.

Other results of this study indicated that overall experience, measured by years
as a gymnast, and task difficulty, measured in terms of the difficulty of the routine
performed, were unrelated to gymnasts' anxiety levels. These results conflict with
those reported by Martens, Burton, Vealey, Bump, and Smith (1983) which
demonstrated athletes with less experience had significantly higher anxiety levels. The
Martens et al. (1983) results support conclusions from Martens (1969) suggesting more
difficult tasks result in greater anxiety levels.

A limitation of the Matheson and Mathes (1991) study that may have resulted in
the failure to produce findings consistent with those described above was the potential
range restriction on both the experience and difficulty dimensions. The authors
acknowledged that with such a young, homogeneous sample it was difficult to account
for the effects of these variables on anxiety and self-confidence. Another shortcoming
of this study, not identified by the authors, was that there was no measure of
performance. While it proved interesting to gather information regarding the
relationships among the variables in this study, the observed relationships have practical
significance only to the extent that they have an impact on task performance or other
salient individual outcomes.

Martin and Gill (1991) reported a study that examined the relationships among
competitive orientation, measured with the COI (Vealey, 1986) and SOQ (Gill &

Deeter, 1988); sport-confidence, measured with the Trait Sport-Confidence Inventory

39

(TSCI) and State Sport-Confidence Inventory (Vealey, 1986); self-efficacy, measured
with a developed set of items based on Bandura (1977b); anxiety, measured with the
CSAI-2 (Martens, Burton, Vealey, Bump, & Smith, 1990); and performance.
Participants were high school middle- and long-distance runners competing in a
mid-season dual track meet. Responses to these self-report measures, as well as the
performance measures of finishing time and place, were used to examine the
relationships among the constructs.

Because the terms ”confidence” and ”efficacy” are often used interchangeably,
it is important to consider how Martin and Gill (1991) differentiated between the two.
In this particular study, sport-confidence referred to how confident athletes usually feel
in a sport achievement situation. Specifically, this study predicted that sport-
confidence was related to an individual's competitive orientation. Competitive
orientation, as described in the earlier discussion of the COI's development (Vealey,
1986), was defined in terms of an outcome or a performance orientation.

In contrast to confidence, self-efficacy has generally referred to how sure
individual's are about their performance on a paniculat task in a panicnlat situation
(Bandura, 1977b). Martin and Gill (1991) operationalized efficacy by asking runners
how they felt about achieving both a specific performance goal and achieving a specific
outcome goal. By identifying efficacy as important to both types of competitive
orientation in this particular study, the Martin and Gill (1991) operationalization was
consistent with other investigators' conceptual izations of efficacy.

Martin and Gill (1991) proposed two primary hypotheses about the relationships

40

among the variables previously described. The first hypothesis was that performance
orientation and trait sport-confidence would be positively related to self-efficacy and
state sport-confidence and negatively related to state anxiety. Results provided some
support for this prediction. Although state and trait sport-confidence and self-efficacy
were related, performance orientation did not contribute to predicting state sport-
confidence. The authors acknowledged that these results were inconsistent with
previous literature regarding this relationship (e.g., Vealey, 1986). However, they
suggested that range restriction of experience and homogeneity of performance
orientation in their sample may have influenced the results.

The second hypothesis examined in this study was that state sport-confidence
and self-efficacy would be positively associated with performance and that anxiety
would be negatively related to performance (Martin & Gill, 1991). While results
indicated that athletes who scored high in sport-confidence and high in self—efficacy
expectations for outcomes performed better than those low on the sport—confidence and
efficacy measures, a stepwise regression indicated that sport-confidence did not
contribute a significant increment to the prediction of finishing time beyond that made
by self-efficacy. As the authors noted, these results were consistent with previous
research that has examined similar relationships (e. g., Okwumabua, 1986).

Krane, Williams, and Feltz (1992) described a study in which a model of the
relevant variables in a competitive situation was developed and tested. Like Martin and
Gill (1991), Krane et al. (1992) examined the relationships among anxiety, state

confidence, performance expectations, and performance. However, their sample

41

consisted of female collegiate golfers who were older and had more variability in
experience than Martin and Gill's (1991) runners. In this study, anxiety was measured
using the SCAT (Martens, 1977) and state confidence was measured with the CSAI-2
(Martens et al. , 1990). Performance expectations were measured by asking each
participant to provide a goal score for each round of golf. Performance was measured
by golfers' season-long average score, as well as by their scores for the first and second
rounds of the tournament.

Krane et al. (1992) hypothesized two models with respect to the key study
variables. The first model proposed that a variety of factors such as season-long
average score, years of experience, competitive state anxiety, and pre-competitive
anxiety would influence pre—first round self-confidence. Self-confidence, in turn, was
hypothesized to be a predictor of first-round performance. Similar predictions were
generated using first round performance as the antecedent to pre-second round
confidence and second round performance. The alternate model proposed a similar
relationship pattern as the first, except that performance expectations (i.e. , performance
goals) were substituted in place of self-confidence.

Tests of both models resulted in the failure of either to adequately account for
the variability in performance. With respect to the first model, the only significant
findings were that competitive trait anxiety and pre-competitive anxiety significantly
predicted pre-first round confidence. Within the second model, average score was the
only significant predictor of first round performance. In fact, the best predictor of

performance in both models was previous performance.

42

At this point, it is important to note that all of the studies described in this
section have been conducted within the domain of sport situations. Despite some
strong results from this literature related to certain key variables in competitive
situations, there may be significant limits to the generalizability of the conclusions.

For example, the situations studied in sport psychology paradigms have been almost
exclusively explicitly competitive situations. All participants are aware that they are
taking part in the activity with the express purpose of demonstrating their ability versus
one, or a number of, competitors. Not all, or even very many, interactions in work
settings take place in such explicitly competitive environments. Thomas (1992), in a
review of the literature of the related construct of conflict, offered a similar suggestion
that different situations have particular cues that affect how explicitly competitive a
situation is perceived.

Key questions when applying the previous results to typical work settings
include: Can some work settings be defined/perceived as competitive?, If so, does this
type of competition differ from the explicitly competitive situations studied in sport
environments?, and, What is the impact of this competition in terms of personal and
organizational outcomes? Implicit in the last question is the broader problem of how
competition fits in with more widely accepted theories of work motivation (e. g. , goal

setting).

43

C .. lGlS'B 1

One area of the work motivation literature that has recognized the importance of
situational competitiveness is goal setting (Locke & Latham, 1990). In particular,
several key studies (Chung & Vickery, 1976; Mitchell, Liden, & Rothman, 1985;
Shalley, Oldham, & Porac, 1987; White, Mitchell, & Bell, 1977) have examined the
impact of situational competitiveness, but definitions, operationalizations, and results
have been inconsistent.

Chung and Vickery (1976) presented a study of the effectiveness of three
different types of reinforcement conditions and knowledge of results (KR) on
performance in a repetitive task situation. Competition in this experiment was
operationalized through a KR manipulation in which normative information regarding
performance standards was presented to individuals. As noted by Locke and Latham
(1990), the situation in the Chung and Vickery (1976) study may be thought of as
competitive because of participants' comparison of their performance with the typical
performance of others. While the comparison of performance with external, pallid,
interpersonal standards has been thought of in terms of competitiveness (cf. Deci &
Ryan, 1980), the authors (Chung & Vickery, 1976) did not originally suggest that
situational competitiveness was the mechanism by which KR and performance standards
influenced performance. Although they discussed their results in terms of these
conditions affecting intrinsic motivation, the suggestion that situational variables affect
all individuals in the same manner is inconsistent with trait conceptions of

competitiveness (e. g., Butt, 1979).

44

White, Mitchell, & Bell's (1977) definition of competition was similar to Chung
and Vickery's (1976) except that they also recognized the importance of social
facilitation. Based on the work of Zajonc (1965), White et al. (1977) predicted that
individuals who were working in situations in which others were present would be
more productive because of (1) evaluation apprehension and (2) expectations from
social cues. In addition to task performance, job satisfaction was also used as a
dependent variable in this experiment. Results were consistent with predictions
regarding the effects of evaluation apprehension and social cues on performance.
However, no effects were observed with respect to job satisfaction. As with Chung
and Vickery's (1976) study, a potential limitation of this study in terms of addressing
the impact of situational competitiveness on performance is the failure to consider the
fact that individuals may differ in their competitive orientations.

Mitchell, Rothman and Liden (1985) reported a study that examined the
influence of normative information and goal setting on task performance. In addition
to using normative information as an operationalization of situational competitiveness,
this study also employed "actual" performance by another participant. Some
participants were asked to perform a task in which the performance of a previous
participant was made salient (i.e. , actual performance condition). The task the
participants were asked to complete was placing lids onto ice cream containers. In the
"normative performance" condition, individuals were provided feedback in terms of the
average performance level achieved by individuals working on this task. In the ”actual

performance” condition, individuals were shown the performance (i.e. , the covered

45

containers) of the person immediately preceding them in the experiment. In fact, the
amount completed was manipulated by the experimenters and was equivalent for all
participants in this condition.

Results indicated performance for participants in the actual performance
condition was significantly greater than in the normative condition. While Mitchell et
al. (1985) offered several potential reasons for their results, the most probable
explanation is that their operationalization of situational competitiveness was more
consistent with the notion of direct competition observed in many of the preceding
studies. However, as with the other studies described in this section, competitiveness
was defined only in terms of situational factors. No individual differences were
addressed.

Shalley, Oldham, and Porac (1987) examined the impact of goals and external
evaluation on intrinsic motivation. Situational competitiveness in this study was
manipulated by participants being told that their performance would (competitive) or
would not (non-competitive) be compared to others. While this study used a
manipulation similar to those previously described, Shalley et al. (1987) believed that
evaluation apprehension would affect not only performance, but also intrinsic
motivation for the task. Results demonstrated no support for this hypothesis. The only
effect for intrinsic motivation was with respect to how the goals were set (i.e., assigned
versus participative).

According to Locke and Latham (1990), these studies lead to the following two

conclusions. First, the results of these four studies provide evidence for the assertion

46

that goals and situational competitiveness are similar constructs and affect behavior in
the same fashion. Specifically, these authors suggested that situation competitiveness
and goals are ”two sides of the same coin. "

Second, Locke and Latham (1990) concluded that the influence of situational
competitiveness on task performance reflects the importance of goal commitment as a
mediator. In fact, Locke and Latham (1990) recommended that future goal setting
research should be focused on the impact of competitiveness on goal commitment.
While the latter suggestion seems a reasonable conclusion to draw from these studies,
the implication that competitiveness, as a construct, is well understood within the goal
setting framework is a bit premature considering the inconsistency of the previous
conceptualizations. Further, while previous goal setting studies do have some
interesting implications for research related to situational competitiveness, the effect of
competitiveness as an individual difference variable in goal setting situations has

remained unexplored.

An Integration and Development of a Conceptual Model
The previous literature review has illustrated the attempts of researchers to
identify the ways in which competitiveness as an individual difference variable and as a
situational characteristic affects performance. A critical question arising from this
research is, "What are the joint effects of these variables - additive or interactive?"
The aim of the present study is to examine these effects within a traditional work

setting. Because many of the constructs and relationships included in previous

47

literature were tested by means of paradigms other than those commonly used in 1/0
research, it is necessary to operational ize these constructs in ways that are more
consistent with work situations. In particular, goals are an important feature of work
situations that warrant investigation. Moreover, the paradigm associated with goal
setting research has been used by a number of investigators to study the effects of
situational competitiveness (Locke & latham, 1990). The review of goal setting
literature has illustrated that this integration would also have key benefits for goal
setting theory. Locke and Latham's (1990) assertion that goals and situational
competitiveness represent ”two sides of the same coin” is empirically tested within the
current study by considering competitiveness of the situation and goals as two
independent factors. The current study also allows for the assessment of the
importance of individual competitiveness as a potential moderator of goal effects.
Figure 2 presents a synthesis of the previous literature on competitiveness and
goals in the form of a conceptual model. A key construct of this heuristic model is
competitive orientation. As previous literature (e. g., Butt, 1979) has suggested,
individuals differ with respect to their competitiveness which, in turn, exerts an
influence on a variety of outcomes. The current study examines the influence of
competitive orientation within a complex, cognitively demanding task that is
representative of many work situations. A second critical construct in this model is
situational competitiveness. The inclusion of this variable is based on the results of
previous literature that have shown effects for situational competitiveness on individual

outcomes (e.g., Mitchell et al., 1985). The third critical antecedent component is goal

 

Situation

 

48

 

 

 

 

 

 

Ass' ed
Commitment

 

 

 

 

I'I' Y
83ientatione T

 

 

 

 

 

Task
Satisfaction

 

/

 

 

 

 

SW‘

 

 

 

Personal
Goal _
Commnment

Task

Performance

 

 

 

 

 

 

 

 

\

 

 

Self-
Efficacy

 

Figure 2. Conceptual Model of Relationships Among Key Study Variables

 

 

49

difficulty. Previous research (Locke et al. , 1981) has consistently demonstrated the
beneficial effects of specific, difficult goals on task performance. Thus, a unique
feature of this model is that situational competitiveness and goals are defined as
independent factors that can jointly influence the overall situational cues.

Moreover, the model also builds on the results of previous literature (e. g., Gill
et al., 1991) by including task satisfaction and self-efficacy as important individual
outcomes. The remaining variables in the model, assigned and personal goal
commitment, are included as mediators. Specific predictions regarding these
relationships are presented in a later section.

Operationalizing the constructs in the model required consideration of a number
of issues. Specifically, despite the demonstrated construct validity of existing measures
of individual competitiveness (e. g., SOQ, COI), there were several reasons for
believing they could not be used without modification in the current study. First,
although there are jobs which require primarily physical performance, many jobs in
today's work environment are more strongly dominated by cognitive demands than the
tasks typically examined with previous scales of competitiveness. The disparity
between types of tasks appropriate for sports and I/O psychologists means that there
could be a potential problem in using a measure based on primarily physical tasks to
understand mental activities.

Another potential difficulty with transferring the sport psychology scales of
competitive orientation to I/O settings is that the very nature of the competitive

situations may be different. More specifically, the tasks typically used in the sport

50

psychology literature are explicit forms of competition (e. g., golf tournaments,
basketball games, gymnastic meets). Explicit forms of competition are likely to be
defined as competitive by an external source and would generally be agreed to be
competitive by all individuals taking part as well. These situations are conceptually
distinct from implicitly competitive situation. Implicitly competitive situations are
characterized as being defined as competitive only by the participants. Thomas (1976;
1992) stated this difference in terms of the salience of competitive cues. An explicitly
competitive situation is one in which there are critical outcomes at stake and a definite
conflict of interest among outcomes. By contrast, implicitly competitive situations
often contain little, or no direct conflict among participants' outcomes. This latter
situation would likely be the type most often found in work settings. That is, two
individuals working on similar tasks in a particular environment may or may not
perceive themselves to be in competition. Whether or not other observers would define
the situation as competitive, it is the perceptions of situational competitiveness of the
individuals involved that are important.

Though competitiveness in work and sport may be different, there are areas of
overlap between the two disciplines. It is on these similarities that a construct of
competitive orientation relevant to work settings can be developed. Thus scales such as
the SOQ and C01 were carefully scrutinized to identify components relevant to
cognitive tasks in organizational settings and modifications made as necessary. Because
work situations are more likely to include the more implicit types of competitiveness

described earlier, it is important for measures of competitiveness within this context to

51

assess the tendency for individuals to interpret an ambiguous situation as competitive.
Specifically, items were developed that related to how individuals perceived situations
that contained critical competitive characteristics.

The characteristics that define situations as competitive or non-competitive
within a goal setting framework were similarly critical for the current study. The
proposed model has suggested the potential independence of situation competitiveness
and goals. As a result, each of these variables are considered in turn.

As previous research (Ames, 1984, Johnson et al., 1981, Tjosvold, 1993) has
demonstrated, a number of cues may result in situations being perceived as
competitive. One aspect that influences the competitiveness of a situation is an
individual's comparison performance standard. Specifically, situations that define
success in terms of achieving a higher level of performance than a relevant other are
perceived as more competitive than situations that do not suggest such interpersonal
comparisons (Tjosvold, 1993). Additionally, situations that provide feedback to
individuals regarding performance are perceived to be more competitive than situations
in which feedback is not available (Chung & Vickery, 1976). If individuals do not
know the level at which they are performing a task, comparisons with other individuals
is not possible (Chung & Vickery, 1976). Finally, feedback must be made public in
order for situations to perceived as competitive (Zajonc, 1965). That is, individuals
must be told not only how well they are performing, but the performance level of
relevant others in the environment (Zajonc, 1965).

In addition to these critical competitive characteristics, goal setting researchers

52

have concluded that more difficult goals lead to greater perceived situational
competitiveness (Locke and Latham, 1990). Consistent with previous research (cf.
Locke et al. , 1981), the current study adopted an operationalization of goals such that
difficult goals reflected a performance level achieved by roughly 20% of a previous
sample, while easy goals were set at a level of performance achieved by approximately
80% of a previous sample. Additionally, goals were included which provided
participants with instructions that directed them to ”do your best. "

A final key characteristic of the conceptual model is the role of commitment.
Goal setting research (Locke & Latham, 1990) has consistently demonstrated that the
primary mechanism by which goals affect performance is through the commitment an
individual feels toward the assigned goal. More specifically, it has been suggested that
commitment moderates the relationship between goals and performance (Locke &
Latham, 1990). While the proposed heuristic model in Figure 2 indicates commitment
as a mediator, it is not inconsistent with previous goal setting research. The reason for
the apparent discrepancy is that commitment is typically measured only with respect to
assigned goals, while the current conceptualization suggests that commitment to
personal goals may also be important. In situations where only assigned goal
commitment is measured, it is logically correct to view it as a moderator. If there is no
commitment to the assigned goal, then goal level will have no effect on performance.
However, the current model suggests that while commitment to assigned goals may be
low, if an individual is highly committed to another goal, performance can still be

high. In sum, the model suggests that individuals make a decision to pursue, to some

53

degree, either the assigned goal or a personal goal. Once this choice is made,
commitment to the chosen goal actually mediates the goal-performance relationship:
the stronger the commitment, the greater the performance. Specific predictions

regarding the role of commitment are presented in the following section.

Hypotheses

The relationships indicated in the conceptual model presented in Figure 2
summarize a number of specific hypotheses that were examined in this study. This
section describes each hypothesis, as well as offers a brief rationale for the inclusion of
each in the current study.

The first hypothesis is based on literature that has examined competitiveness as
an individual difference variable (e. g., Butt, 1976). As previously reviewed research
has indicated, the competitiveness of an individual has an effect on subsequent task
performance. With this in mind the following hypothesis was generated:

H1: There will be a significant, positive relationship between individual
competitiveness (i.e., competitive orientation) and task performance.

The next two hypotheses are related to the research that has suggested various
situational characteristics affect the perceived competitiveness of particular contexts
(Locke & Latham, 1990). Situations that emphasize interpersonal comparisons and
provide public feedback regarding performance levels typically have been defined as
more competitive than situations that do not provide public feedback (White et al. ,
1977). These researchers have further suggested that perceptions of situational

competitiveness are directly related to task performance. With these considerations in

54

mind, the following predictions were made with respect to perceived situational

competitiveness:

H2:

H3:

Individuals performing a task in conditions where they are given
instructions that emphasize interpersonal comparisons and provided
public feedback regarding their performance will perceive the situation
as more competitive than individuals who are not given instructions that
emphasize interpersonal comparisons or provided with public feedback.

Individuals performing a task in conditions where they are given
instructions that emphasize interpersonal comparisons and provided
public feedback regarding their performance will perform better than
individuals who are not given instructions that emphasize interpersonal
comparisons or provided with public feedback.

The fourth and fifth hypotheses are related to the expected effects of goal

situations on perceived competitiveness and task performance. Previous theory (Locke

and Latham, 1990) regarding the impact of goal level on perceived situational

competitiveness (i.e., that goals and competition are two sides of the same coin) and

task performance (i.e. , that difficult goals lead to better performance than easy or do

your best) provided the following predictions:

H4:

H5:

Individuals with specific, difficult goals will perceive the situation to be
more competitive than individuals with either easy or "do your best”
goals.

Individuals with specific, difficult goals will perform better than
individuals with either easy or ”do your best" goals.

In addition to the predicted main effects for each of the three key exogenous

variables (competitive orientation, situational competitiveness, and goal conditions) in

the current study, interactive effects are expected. Previous research has demonstrated

that individuals with a competitive orientation perform better in situations that are

55

competitive. By contrast, in situations that are not competitive, individual differences
in competitive orientation have not been related to performance differences. Within the
context of the current study, situational cues refer to the extent to which instructions
are provided that emphasize interpersonal comparisons and public feedback is provided.
The general predictions regarding these effects were included in hypothesis 6, while
predictions regarding the specific effects of the interaction were included in hypotheses
6a and 6b.

H6: Situation competitiveness will moderate the relationship between
competitive orientation and task performance.

H6a: Non-competitive situations will result in no performance differences
between non-competitive and competitive individuals.

H6b: Directly competitive situations (i.e., when instructions that emphasize
interpersonal comparisons and public feedback are provided) will result
in higher performance for individuals with a competitive orientation than
for those with a non-competitive orientation.

Based on the assertion of Locke & Latham (1990) regarding the similarity of
goals and situation competitiveness, the interactive effects of goals and competitive
orientation were predicted to mirror those for situation competitiveness and competitive
orientation with ”do your best” and easy goals analogous to non-competitive situations
and difficult goals similar to competitive situations. The general and specific

predictions were as follows:

H7: Goal situation will moderate the relationship between competitive
orientation and task performance.

H7a: Situations in which "do your best" goals are assigned will result in no
performance differences between non-competitive and competitive
individuals.

56

H7b: Difficult goal and easy goal situations will result in higher performance
for individuals with a competitive orientation than for those with a non-
competitive orientation.

H7c: In situations with difficult goals, the expected interaction with
competitive orientation will be stronger than in situations when easy
goals have been assigned.

Because of the lack of theoretical and/or empirical evidence regarding the three-
way interaction between competitive orientation (CO), competitive situation (CS), and
goal situation (GS), predictions regarding the proposed model were restricted to the 2-
way interactions of CO x CS and CO x GS. The following set of hypotheses are
related to the expected role of commitment to assigned performance standards. Based
on previous research (Locke & Latham, 1990), it was expected that high task
performance would result only when individuals were committed to their assigned
performance objective. As a result, with respect to the CO x GS interaction, it was
predicted that commitment to an assigned goal would be high when individuals were
non—competitive. By contrast, it was expected that individuals who displayed a high
level of competitiveness would tend to focus more on interpersonal standards of
performance and therefore be less committed to the assigned goal. However, even
though these individuals were predicted to be less committed to the assigned goal, they
could still realize high performance due to their commitment to their personal, goal.

A similar prediction was made with respect to the CO x CS interaction.
Individuals who were high on the competitiveness measure would be more committed

when instructions were provided that emphasized performance standards based on

interpersonal comparisons. By contrast, individuals who were non—competitive would

57

be less committed to the stated objectives in these situations, instead focusing on their
own personal performance level, and wouldl subsequently demonstrate less
commitment to the assigned performance standards. However, it was expected that
these individuals could still realize high task performance through their commitment to
their personal goals. Consistent with the previous discussion, the following specific
predictions were offered:

H8a: In situations when objective performance goals are assigned to
individuals, individuals who score low on the CO measure will display
higher commitment to those goals than individuals who score high on the
CO measure.

H8b: In situations when instructions that emphasize interpersonal comparisons
are assigned, individuals who score high on the CO measure will display
higher commitment to those goals than individuals who score low on the
CO measure.

The implication of the preceding hypotheses and the proposed model is that
commitment, broadly defined, is fundamentally predicted to be a mediator between the
key interactions and task performance. However, the nature of commitment is of
critical importance. Higher commitment is predicted to lead to increased performance.
Further, when individuals display low commitment to an assigned goal, it is expected
that they will alter the goal to be more consistent with their own expectations. Thus, in
situations where objective goals are assigned and individuals are competitive, although
the individuals will display low commitment to the assigned goal, it is expected that
they will display high commitment to their own, personal goal. This is indicated by the

inclusion of two paths from the interactions to task performance. Specifically:

H9a: In conditions in which CO is low and objective performance goals are
provided and conditions in which CO is high and instructions are

58

provided that emphasize interpersonal comparisons, commitment to the
assigned performance standard will mediate the effects on task
performance.

H9b: In conditions in which CO is high and objective performance goals are
provided and conditions in which CO is low and instructions are
provided that emphasize interpersonal comparisons, commitment to
personal performance standards will mediate the effects on task
performance.

Two affective outcomes were hypothesized to result from the interaction
between competitive orientation and the situational cues. Specifically, individuals' self-
efficacy judgments after performing in these situations were expected to be significantly
correlated with individual differences in pre-task self-efficacy, perceived situational
competitiveness, goal level, and task performance. These effects were expected based
on the fact that research examining the effect of competitive situations on self-efficacy
has demonstrated that competition affects subsequent self-efficacy judgments through
its effects on performance. Specifically, the following hypothesis was offered:

H10: Post-task self-efficacy will be positively related to individuals' task
performance. Specifically, those who perform well on the task will
report greater efficacy for the task than those who perform poorly.

Task satisfaction was also predicted as an outcome variable in the current study,

based on research that has shown that individuals who perform well on a task typically
report higher levels of task satisfaction (cf. Riggio, 1990). As a result, the following

hypothesis was proposed:

H11: There will be a significant, positive correlation between task
performance and task satisfaction.

The key variables and analytical tests of the previous set of hypotheses

are summarized in Table 1.

59

 

 

 

 

 

 

 

 

 

 

 

 

Table 1
Summary of Study Hypotheses
Ho's KEY VARIABLES TEST
H1 Competitive Orientation Multiple
Task Performance Regression
H2 Competitive Situation Multiple
Perceived Competitiveness Regression
H3 Competitive Situation Multiple
Task Performance Regression
H4 Goal Situation Multiple
Perceived Competitiveness Regression
H5 Goal Situation Multiple
Task Performance Regression
H6 Competitive Situation Multiple
Competitive Orientation Regression
Task Performance
H7 Goal Situation Multiple .
Competitive Orientation Regression
Task Performance
H8 Competitive Situation Hierarchical
Goal Situation Multiple
Competitive Orientation Regression
Goal Commitment
H9 Competitive Situation Hierarchical
Goal Situation Multiple
Competitive Orientation Regression
Goal Commitment
Task Performance
H10 Task Performance Multiple
Self-Efficacy Regression
H11 Task Performance Bivariate

 

Task Satisfaction

 

Regression

 

 

METHOD

E . .
A power analysis was conducted to determine the necessary sample size to
detect a moderate effect with power of approximately .80. Results of this analysis
suggested cell sizes of 25, which resulted in a total sample of 150. Participants were
undergraduate psychology students at Michigan State University who took part in the

experiment as part of a course requirement.

Design

The study was a 3 (goal condition) x 2 (competitive condition) factorial design.
Three levels of goals (difficult, easy, and "do your best”) were crossed with 2 levels of
situation competitiveness (competitive and non-competitive) to which participants were
randomly assigned. A more detailed description of the specific manipulations is
presented in the Procedure section. The remaining variables in the study involved

measured, as opposed to manipulated, factors.

The task used in the current study was based on the multiple-cue probability
learning (MCPL) paradigm. According to Abelson and Levi (1985) MCPL tasks

require a decision maker to choose an alternative from a set of options that vary on a

60

61

number of attributes, or cues. In order to make the most accurate judgments the
decision maker must understand the relationships (i.e. , weights) between the cues and
the criterion. The process by which the decision maker typically learns these
relationships involves observing a cue profile, selecting an alternative, receiving
feedback regarding the correct alternative, and repeating the process a number of times.
Depending on the task characteristics, predictive accuracy (the correlation between the
decision maker's judgments and the correct answers) can range from zero to one. With
respect to learning the weights, feedback can either take an 9111mm: form, in which
feedback simply indicates the accuracy of an individual's response or a ptocess form, in
which feedback is provided in terms of how close an individual's weighting structure is
to the weights as they exist in the environment (Balzer, Doherty, & O'Connor, 1989).
An MCPL task addressed several critical issues related to the current study.
First, this type of task is largely cognitive and requires the same critical skills necessary
for performance of many non-laboratory decision making tasks. Second, cues and cue
values can be presented for tasks in which the decision makers lack experience
(Quit‘tones, 1993). A novel task is important because it avoids any confounds of prior
individual difference variables. Third, feedback can be manipulated so that
performance of individuals can be made public. Fourth, MCPL tasks provide discrete
stages at which individuals can easily compare performance with an external, or
internal, standard, thereby affording them the opportunity to change strategies or
modify standards of performance. Finally, research utilizing these types of tasks has

typically demonstrated variability in individual performance through acquisition of

62

proper cue weighting strategies. As individuals become more or less engaged in the
task, performance differences result.

A computer simulation of a Naval Air Defense scenario developed by
Hollenbeck, Sego, Ilgen, and Major (1991) was chosen for this study. This task
required individuals to command a United States Naval Carrier and to make decisions
regarding the "threat level” of a series of targets presented on a microcomputer.
Specifically, individuals were asked to choose from one of five defensive postures
(Ignore, Monitor, Warn, Ready, Defend) depending on a target's standing on nine
attributes (speed, altitude, size, angle, IFF, direction, corridor status, radar type,
range). Each trial in this task required individuals to select one defensive posture for
each target within a specified time limit. After each trial, individuals received
feedback regarding the accuracy of their response and then were presented with the
next target. Individuals were allowed to use as much, or as little, of the allotted time
as necessary, so the number of targets viewed varied depending on how quickly
individuals proceeded through the trials. As a result, both performance quality (i.e.,
accuracy of assessing targets) and performance quantity (i.e. , number of targets
assessed) was measured on the task.

Consistent with the MCPL paradigm, the level of threat associated with each
target was determined by the values of each of the nine target attributes. The task
structure included four interactions and one main effect. Interactions only indicated a
threat when both attributes of the interaction had values considered threatening. If

either attribute had a value that was non-threatening, the interaction was also non-

63

threatening. Thus, this task required individuals to know the pattern of interactions
among the attributes, as well as the threat level for each attribute (Hollenbeck, Sego,
Ilgen, & Major, 1991). Pages 5 and 6 of Appendix A provide the ranges of threat
level for each of the nine attributes as well as the rules for interactions.

One of five potential outcomes resulted after an individual selected one of the
decision alternatives. These outcomes, which were based on the accuracy of an
individual's prediction of the correct response, ranged from "hit", indicating that the
individual's decision was exactly correct, to ”disaster”, indicating that the individual's
decision was off by four in terms of aggressiveness. Page 7 of Appendix A provides a
complete description of all possible decision outcomes.

Each outcome had a point value associated with it. A "hit” was worth 2 points,
a "near miss" 1 point, a ”miss” 0 points, an ”incident" -1 point, and a ”disaster” -2
points. An individual's accuracy score was the number of points achieved across the

completed trials.

GllC "ll'l'

The conditions under which individuals completed the task varied in terms of
(1) the level of the assigned performance goal and (2) the level of situational
competitiveness. With respect to the goal manipulation, individuals performed the task
in one of three conditions: difficult, easy, or ”do your best” goals. Difficult goals

were set at a performance level achieved by roughly 20% of a previous sample of

64

individuals working independently on this task (Quifiones, 1993)‘. Similarly, easy
performance goals were set at a level achieved by roughly 80% of the Quiflones (1993)
sample. ”Do your best” instructions emphasized performing as well as possible with
no explicit standards.

Situational competitiveness was manipulated by varying instructions
emphasizing interpersonal comparisons and ”publicness" of the provided feedback. In
directly competitive situations, instructions emphasized that an individual should
attempt to outperform a relevant other. In addition, individuals received feedback
regarding their performance relative to their competitor and were told that their
competitor received the same information. In contrast, individuals in noncompetitive
conditions did not receive either instructions emphasizing interpersonal comparisons or
public feedback. Specific instructions provided to the participants in the resulting six

cells of this design are presented in the Broccdnte section.

Measutes
The following measures were collected as part of this experiment. The
measures are presented in the order in which they were collected. All participants
completed all measures. Scale reliabilities are reported where appropriate.
Competitiyofltientation. Competitive orientation was assessed using a measure
developed explicitly for the current study. This measure identified an individual's

competitive orientation as related to typical work situations. The ll—item scale

 

‘ Characteristics of the Quifiones (1993) sample were N=217, M = 1.30, SD = .22.

65
contained modified items from the SOQ, the C01, and the scales reported by Butt

(1979). Items measured performance versus outcome orientations, tendency to seek out
competitive situations, preferences for competitive versus non—competitive situations,
and previous experience with competitive situations. Responses were made on a 5-
point Likert scale. Scores were coded such that high values represented a competitive
orientation. The observed reliability for this scale was a = .83. A copy of this scale
can be found in Appendix B.

W. Knowledge of threat levels and rules for interactions
among the nine attributes was measured using a 30-item, multiple-choice test. This
measure (see Appendix C) was adapted from similar measures used by Hattrup (1992),
Landis (1992), and Quifiones (1993) and was used to assess initial differences in skill
level of study participants. Because the items in this test measure different aspects of
the task and the fact that coefficient alpha is an index of unidimensionality, the current
study adopted a split-half approach for assessing the reliability of this measure. The
split-half reliability (odd-even) was r = .70.

EtezfletfotmancoSelEEfflcacy. Participants' expectations regarding
performance levels on the task were assessed using a 10-item measure adapted from
Hattrup (1992) and Quihones (1993). Responses were made using a 5-point Likert
scale. The observed reliability was a = .87. This measure can be found in Appendix
D.

IaleEcthrmanchmmm. This measure was administered at the beginning

of task performance and at two 15 minute intervals thereafter. This inventory included

66

a measure of individuals' knowledge of conditions, personal goals, and commitment to
assigned and personal goals. A one-item, manipulation check, measure (see Item #1 in
Appendix E) was included to assess individuals' knowledge regarding the conditions in
which they were performing and the goal level originally assigned by the experimenter.
Also included in this questionnaire was a one-item measure (see Item #9 in Appendix
E) designed to assess an individual's personal goal with respect to task performance.
Additionally, participants responded to 7-item measures of commitment to both
personal and assigned goals. This measure was a modified version of the goal
commitment scale developed by Hollenbeck, Klein, O'Leary, & Wright (1989).
Reliabilities for these scales ranged from a = .77 to a = .85. Reliabilities at each of
the three time intervals are reported in the ”Results" section.

Eutmmanceflnantity. The number of trials completed by each participant was
recorded by the computer and used as a measure of performance quantity. There were
60 targets in the simulation set, allowing scores on this measure to range from 0 to 60.

Eetfoi'mancoAcentacy. Performance quality was measured using the point
system described earlier. For each target, an individual could score between -2 and
+2. Performance quality was computed by taking an individual's score across
completed trials and dividing by the number of trials completed, yielding a measure
with a range from -2 to +2.

EetceptionsoLSiniationCompetitixeness. Participants' perceptions about the
competitiveness of the situation was assessed using a 6-item measure (see Appendix F).

Responses to this scale were made using a 5-point Likert format and reflected

67

participants' perceptions of ”publicness" of feedback, awareness of others'
performance, and overall perceptions of the competitiveness of the situation. The
observed scale reliability was a = .79.

EostietfotmanmSelfl-Efficacy. Participants' expectations regarding future
performance levels was measured using a 10—item scale similar to the pre-performance
self-efficacy measure. The scale reliability was a = .88.

Wes. Reactions to the competitive aspects of the
situation was addressed by means of a 9-item measure of satisfaction with the task and
general attitudes toward the situation. Again, a 5—point Likert scale format was used.

The scale reliability was a = .91. A copy of this measure is presented in Appendix G.

Emcedune

Each participant attended a single two hour experimental session. Upon arrival,
participants were asked to read and sign a consent form that provided them with a brief
description of the task they would be performing. A copy of the consent form is
included in Appendix H.

After signing the consent form, individuals were given oral instructions for
completing the Naval Air Defense Simulation. In addition, a handbook (see Appendix
A) adapted from Landis (1992) and Quiiiones (1993) containing an in-depth description
of the situation, target attributes and values, decision Options, and decision outcomes
was provided for the participants to read and study. At this time, the experimenter also

informed the participants that the purpose of the present investigation was to examine

68

task performance within different goal conditions. Participants were given 15 minutes
to review the handbook. Questions regarding information contained in the handbook or
about the experiment itself were answered at this time. The handbooks then were
collected and individuals taken to a computer station and given 15 minutes to practice

the actual task.

After this training, participants completed the CommtitixLQtientation measure,

We: test. and EttfierformanceSelfiEfficacx measure. Responses

were collected and individuals provided with information relevant to their assigned
condition. Appendix I contains the specific protocols that were used in explaining the
situation to the participants. After receiving these instructions, participants completed
the IasLBetfotmanceJnyentory. They were then given 45 minutes to work on the
task. At 15 minutes and 30 minutes into the task, participants' performance was
assessed and feedback provided. In those conditions where appropriate, participants
were informed of their competitor's performance levels. In order to present all
participants with the same situation, competitor's feedback was bogus and reflected the
mean of the Quitlones (1993) sample. At each of these times, participants also
completed the WWW.

After the 45 minute period ended, participants' overall point performance was
measured. They were then asked to complete the We test, the Post;
BetfotmanceSeIEEfficacy measure, and the PoskfietfotmanceAttinides measure.
Participants were then debriefed, asked not to discuss the experiment with anyone, and

allowed to leave.

69
W

The analytic strategy for this experiment followed the logic of causal direction
suggested by the model described in Figure 2 and described specifically in Table 1.
However, before analyses of the primary hypotheses were conducted, the psychometric
properties of the various measures was assessed. These included analyses of item-level
statistics and reliability for each of the scales.

To assess the effects of competitive situation on both performance outcome
measures (quality and quantity) and goal commitment, a multiple regression approach
was used. Depending on the specific hypothesis being tested, the endogenous variables
(performance and goal commitment) were regressed on the exogenous variables
(competitive orientation, situation competitiveness, and goal situation). While no
significant differences across conditions in terms of participants' self—efficacy or pre-
task knowledge were found, these measures were used as covariates in the appropriate
analyses. In all analyses, covariates were entered at the first step. Again, depending
on the specific hypothesis being tested, main effects for one, or more, of the three

exogenous variables were entered next followed by appropriate interaction terms.

RESULTS

Desmimixfllata

Table 2 presents the means, standard deviations, and scale reliabilities for the
experimental groups. In general, the scales showed sufficient reliabilities to proceed
with the data analyses related to the primary hypotheses. In addition, the scales
showed sufficient range and there appeared to be no floor or ceiling effects. The
intercorrelations among the variables are reported in Table 3.

Because performance was assessed at three points in time, a multivariate
analysis of variance (MANOVA) was conducted to assess performance differences
across each of these periods. Analyses with performance accuracy as the dependent
variable (DV) and time as a within-subjects factor demonstrated a significant overall
effect for time, E (2,298) = 13.65, p< .01. Additional analyses of differences
between pairs of time periods indicated significant differences between performance
accuracy at Time 1 (M = 1.31, SD = .25) and Time 2 (M = 1.44, SD =.25), t(149)
= -4.78, p< .01, as well as between Time 1 (M = 1.31, SD =.25) and Time 3 (M =
1.42, SD =.25), t(149) = -4.31, p< .01. However, the observed difference between
Time 2 (M = 1.44, SD =.25) and Time 3 (M = 1.42, SD =.25) was not significant,
t(149) = .39, p> .05. Figure 3 illustrates the effect of time on performance accuracy,
suggesting that asymptotic levels were reached at Time 2.

Similar analyses were performed using performance quantity as the DV. Again,

70

71

Table 2

Means, Standard Deviations, and Reliabilities of Study Variables

 

 

VARIABLE # ITEMS MEAN SD RELIABILITY

Task Knowledge 30 16.13 3.72 .70'
Pre-Task Self-Efficacy 10 3.66 .63 .87
Competitive Orientation 11 3.02 .62 .83
Assigned GC" (T 1)° 7 3.46 .58 .78
Personal GC" (T 1)° 7 3.69 .55 .79
Assigned GCb (T2)° 7 3.59 .58 .79
Personal GC" ('1‘2)c 7 3.71 .52 .77
Assigned GC" (T3)° 7 3.59 .65 .82
Personal GC" (T3)c 7 3.73 .61 .85
Post-Task Self-Efficacy 10 3.83 .59 .88
Perceived 6 2.46 .78 .79
Competitiveness

Post-Task Attitudes 9 3.81 .64 .91
# of Targets (T1)° --- 9.37 2.14 ---
Accuracy (T1)° --- 1.31 .25 ---
# of Targets (T2)c -—— 10.48 2.62 ' ---
Accuracy (T2)c --- 1.43 .25 ---
# of Targets (T3)c --- 10.97 2.77 ---
Accuracy (T3)° --- 1.42 .25 ---

Note. 11 = 150.

‘ Split-half reliability estimate (odd-even). All others are coefficient alpha. bGC =

Goal Commitment. ° T1 = Time 1, T2 = Time 2, T3 = Time 3.

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1.44
1.42:

1.41
1.381
1.36.
1.34.1
1.32.

1.3 :

Performance Accuracy

 

 

 

T1 T2 T3
Time

Figure 3. Performance Accuracy Scores at Three Time Periods.

75

a significant overall effect, F (2,298) = 48.72, p< .01, was found. Paired
comparisons between time periods revealed significant differences among all three:
Time 1 (M = 9.37) and Time 2 (M = 10.48), t(149) = -8.76, p< .01, Time 1 (M =
9.37) and Time 2 (M = 10.97), t(149) = -8.28, p< .01, and Time 2 (M = 10.48) and
Time 3 (M = 10.97), t(149) = -2.88, p< .01. Figure 4 illustrates the pattern of
means. These performance differences on both accuracy and quantity suggest that task
performance in this study was multidimensional.

Additional evidence in support of the multidimensionality of task performance
can be found in the pattern of relationships among the two measures of performance
across the three time periods (see Table 3). If task performance were unidimensional,
the intercorrelations among accuracy and quantity measures would be expected to be
the same both within and across time periods. In fact, a strikingly different pattern of
relationships was observed. Strong correlations were observed among performance
quantity measures across the three periods (.81, .56, and .70) and modest, albeit
significant, correlations were observed among the three accuracy measures (.21, .19,
and .16). Moreover, the correlations observed between quantity and accuracy
measures within and across time periods were, for the most part, non-significant (-.03,
-.02, .18, .23, .01, .15, -.08, -.09, and -.11). These data provided further evidence
for the multidimensionality of task performance.

Given these results, each applicable hypothesis was tested using both

performance accuracy and quantity. In addition, because of the differences across all

76

A
_L

 

_\
.0
01

Performance Quantity
0 _.
'cn o

 

9 4

 

 

T1 T2 T3
Time

Figure 4. Performance Quantity at Three Time Periods.

77

three time periods with respect to these performance dimensions, all were retained for

subsequent analyses.

AnalstDLErimarLHmchcs-es

Hypothesis I predicted a significant, positive correlation between competitive
orientation and task performance. The zero-order correlations contained in Table 3
show that competitive orientation was, with one exception, not significantly related to
either performance quality or quantity. The one significant correlation occurred at time
2, [(149) = .23, p< .01. Although it was unlikely that the non-significant correlations
would be affected, given the logic of the proposed relationships and the presence of a
significant zero-order correlation, hierarchical regression analyses were then conducted
using ability (i.e., W31 scores) as a covariate. Tables 4 and 5
present the results of these analyses for both measures of task performance. These
tables again show that competitive orientation was only significantly associated with
performance accuracy at Time 2.

These results provided some support for the first hypothesis in that no effects
would be expected for performance quantity because instructions and goals emphasized
accuracy comparisons. Further, the effect for competitive orientation on performance
accuracy at Time 2 is consistent with the hypothesis because feedback regarding
competitor performance was first presented before Time 2 performance. As a result,
Time 2 was the first time individuals had an interpersonal standard of comparison

against which to compete. However, the relationship between competitive orientation

Table 4

Results of Hierarchial Regression Analyses with Performance Accuracy Regressed

on Competitive Orientation and Ability

 

 

 

 

 

111le
VARIABLE [3 SE B R2 AR2
STEP 1:
Pre-Task Knowledge .19* .08 .O3* .03"‘
STEP 2:
Competitive Orientation .07 .08 .04“ .00
Iime_2
VARIABLE 8 SE B R2 AR2
STEP 1:
Pre-Task Knowledge .25** .08 .06** .06**
STEP 2:
Competitive Orientation .22** .08 .11** .05**
Iimej
VARIABLE [5 SE [3 R2 ARz
STEP 1:
Pre-Task Knowledge .35** .08 .12** .12**
STEP 2:
Competitive Orientation -.04 .08 .12** .00

 

n=150

*p<.05, **p<.01

79

Table 5
Results of Hierarchial Regression Analyses with Performance Quantity Regressed

on Competitive Orientation and Ability

 

 

 

 

 

 

Iime_l

VARIABLE [S SE B R2 AR2

STEP 1:

Pre-Task Knowledge -.01 .08 .00 .00

STEP 2:

Competitive Orientation .06 .08 .00 .00
Timu-

VARIABLE [3 SE B R2 AR2

STEP 1:

Pre-Task Knowledge .01 .08 .00 .00

STEP 2:

Competitive Orientation .07 .08 .01 .01
Time}

VARIABLE [3 SE B R2 AR2

STEP 1:

Pre-Task Knowledge -.10 .08 .01 .01

STEP 2:

Competitive Orientation .13 .08 .03 .02
n = 150

* p<.05, ** p<.01

80

and performance quality at Time 3 was not supportive of Hypothesis 1. One potential
explanation for the lack of significance at Time 3 may be related to the task itself.
Given the probabilistic nature of the task and the fact that perfect performance is
practically impossible, it is possible that a performance ceiling reached at Time 2
influenced individual performance at Time 3. The fact that mean performance
increased from Time 1 to Time 2 suggests that individuals had not yet reached this
ceiling. However, the similarity in means and variance of Time 2 and Time 3
performance, the negative relationship between accuracy at these times, and the lack of
an observed relationship between competitive orientation at Time 3 suggests that
competitive individuals in an attempt to increase their performance accuracy may have
altered their performance strategies. Because they had likely reached the ceiling of
performance, these new strategies did not lead to greater accuracy.

Hypothesis 2 predicted a significant, positive correlation between perceived
competitiveness of the situation and the situational competitiveness manipulation. This
hypothesis was offered to provide support for the idea that "publicness" of feedback is
a strong cue to the competitiveness of a situation. Specifically, this prediction was
based on the work of Zajonc (1965) and Mitchell, Liden, and Rothman (1985). The
observed correlation between the two variables, [(148) = .64, p< .01 indicated support
for the second hypothesis. In addition to replicating previous research, the significance
of this relationship suggested that the manipulated conditions differed on the
competitiveness dimension and allowed for the examination of additional related

hypotheses.

81

Hypothesis 3 predicted a significant, positive correlation between situational
competitiveness and task performance. Although no significant zero-order relationships
were observed, analyses in which ability was covaried were conducted in order to
specifically test the logic of the hypotheses. Tables 6 and 7 contain the results of these
hierarchical regression analyses using both performance accuracy and quantity. As
these tables show, there were no significant effects for situation competitiveness on
either performance measure. As a result, no support was obtained for the third
hypothesis.

The fourth hypothesis predicted a positive correlation between goal situation
(i.e., difficulty) and perceived situational competitiveness. This prediction was based
on the suggestion of Locke & Latham (1990) that goals and competition were "two
sides of the same coin. " If this hypothesis were true, the observed relationship between
goal situation and perceived competitiveness should mirror that between competitive
situation and perceived competitiveness (see Hypothesis 2 above). In fact, the observed
correlation was non-significant, [(148) = .00, p> .05.

As a result, these data fail to provide evidence for the assertion made by Locke
and Latham (1990). If these situational characteristics are the same, as Locke and
Iatham proposed, individual perceptions regarding them should also be similar. Since
these factors were experimentally manipulated, the relationships between perceptions
and each of the situational characteristics should be the same. As these results
demonstrate, these relationships were not identical.

One possible reason for observing this non-significant relationship between

Table 6

Results of Hierarchial Regression Analyses with Performance Accuracy Regressed

on Situation Competitiveness and Ability

IimeJ.

 

 

Time-.2

 

 

Time-.3

 

VARIABLE [3 SE B R2 AR2
STEP 1:

Pre-Task Knowledge .19* .08 .03* .03*
STEP 2:

Situation Competitiveness -.05 .08 .04 .00

VARIABLE [1 SE p R2 AR2
STEP 1:

Pre-Task Knowledge .25** .08 .06** .06**
STEP 2:

Situation Competitiveness .06 .08 .06" .00

VARIABLE t) SE B R2 AR’
STEP 1:

Pre-Task Knowledge .35 ** .08 .12** .12**
STEP 2:

Situation Competitiveness .00 .08 .12" .00

 

n=150

*p<.05, **p<.01

83

Table 7
Results of Hierarchial Regression Analyses with Performance Quantity Regressed

on Situation Competitiveness and Ability

 

 

 

 

 

 

Iime_l

VARIABLE 8 SE B R2 AR2

STEP 1:

Pre-Task Knowledge -.01 .08 .00 .00

STEP 2:

Situation Competitiveness .00 .08 .00 .00
Iime_2

VARIABLE 8 SE 0 R2 ARz

STEP 1:

Pre-Task Knowledge .01 .08 .00 .00

STEP 2:

Situation Competitiveness .10 .08 .01 .01
Time-.3

VARIABLE B SE B R2 AR2

STEP 1:

Pre-Task Knowledge -.10 .08 .01 .01

STEP 2:

Situation Competitiveness -.08 .08 .02 .01
n = 150

* p<.05, ** p<.01

84

goals and perceived situation competitiveness could be that the goal manipulation was
not consistent with previous research. However, data found in Table 3 do not support
this alternative explanation. As would be expected from the voluminous body of goal
setting research (cf. Locke & Latham, 1990), the observed relationships between goal
difficulty and commitment are significant and negative. That is, the more difficult that
goals are, the less committed are individuals to them. As a result, this data provided
additional evidence that goals and competitiveness are independent situational
characteristics by demonstrating the adequacy of the goal level manipulation.

Hypothesis 5 predicted a significant, positive correlation between goal situation
and task performance. Although some significant zero-order correlations were
observed, because motivational effects were again the focus, analyses that included
ability as a covariate were conducted. Tables 8 and 9 contain the results of the
hierarchical regression analyses for performance accuracy and quantity, respectively.
These tables show significant effects for goal difficulty with both performance accuracy
at Time 2 and performance quantity at Time 1. However, the effects of goal difficulty
in both instances were in the opposite direction as that predicted. In fact, the data
suggest that performance was improved most under ”do your best” instructions and
least under difficult goal instructions. While these effects are contrary to those
predicted, they are not necessarily inconsistent with existing goal setting literature
(e.g., Earley, Connolly, & Ekegren, 1989). A more detailed discussion of these
observed effects is presented later in the paper.

The sixth hypothesis predicted an interactive effect for competitive situation and

85

Table 8
Results of Hierarchial Regression Analyses with Performance Accuracy Regressed

on Goal Situation and Ability

 

 

 

 

 

 

Time-.1

VARIABLE B SE B R2 AR2

STEP 1:

Pre-Task Knowledge .19* .08 .03* .03*

STEP 2:

Goal Situation -.03 .08 .04 .00
Iime_2

VARIABLE [3 SE B R2 AR2

STEP 1:

Pre-Task Knowledge .25** .08 .06** .06**

STEP 2:

Goal Situation -. 16* .08 .09** .03*
Iimej

VARIABLE [1 SE a R2 AR2

STEP 1:

Pre-Task Knowledge .35 ** .08 .12** .12**

STEP 2:

Goal Situation -.10 .08 .13** .01
n= 150

* p<.05, ** p<.01

86
Table 9

Results of Hierarchial Regression Analyses with Performance Quantity Regressed

 

 

 

 

 

 

on Goal Situation and Ability

Time-.1

VARIABLE 5 SE [3 R2 AR2

STEP 1:

Pre-Task Knowledge -.01 .08 .00 .00

STEP 2:

Goal Situation -.23** .08 .05* .05**
Timez

VARIABLE [3 SE B R2 AR2

STEP 1:

Pre-Task Knowledge .01 .08 .00 .00

STEP 2:

Goal Situation -.15 .08 .02 .02
Timed

VARIABLE 8 SE [3 R2 AR2

STEP 1:

Pre-Task Knowledge -.10 .08 .01 .01

STEP 2:

Goal Situation -. 1 1 .08 .02 .01
n = 150

*p<.05, ** p<.01

87
competitive orientation on task performance. Hierarchical regression analyses that
tested this hypothesis are presented in Tables 10 and 11. No interactive effects were
observed for competitive orientation and situation competitiveness on any of the
performance accuracy or quantity measures. This result is unexpected considering the
substantial amount of previous research demonstrating this effect. While the possibility
exists that the competitive manipulation was not strong enough, given that there was a
strong relationship between competitive situation and perceived competitiveness makes
this possibility unlikely.

Another possibility is that the regression analytical technique is not powerful
enough to detect the interaction (Alexander & DeShon, 1994). Alexander & DeShon
(1994) demonstrated that when the assumption of homogeneity of error variance is
violated, the resulting F test of the equality of slopes in the regression analysis is not
robust. In the current case, the mean squared residuals were different across the
competitive conditions within each time period (Time 1: .25 and .26, Time 2: .27 and
.22, and Time 3: .23 and .27). As a result, an additional analysis was done to
examine the relationship between competitive orientation and performance accuracy as
a function of the situation competitiveness. Specifically, the correlations between
competitive orientation and performance accuracy within each competitive condition
were compared (Alexander & DeShon, 1994).

Even with this more powerful test, the interactive effects of competitive

orientation and situation competitiveness were not observed. At Time 1, the Fisher-z

correlations were I = .03 between competitive orientation and performance in non-

88

Table 10
Results of Hierarchial Regression Analyses with Performance Accuracy Regressed

on Situation Competitiveness and Competitive Orientation

 

 

 

Iimel
VARIABLE [3 SE 8 R2 AR2
STEP 1:
Pre-Task Knowledge .19* .08 .03* .03*
STEP 2:
Sit. Competitiveness‘I (C) -.05 .08 .04 .01
Comp. Orientation (CO) .07 .08
STEP 3:
C x CO .19 .42 .04 .00
Time-.2
VARIABLE [3 SE B R2 AR2
STEP 1:
Pre-Task Knowledge .25** .08 .06** .06**
STEP 2:
Sit. Competitiveness‘I (C) .07 .08 .11** .05 *
Comp. Orientation (CO) .22** .08
STEP 3:
C x CO -.41 .40 .12** .01

 

n=150. ‘ Coded: 0=Noncompetitive, 1=Competitive. * p<.0 , ** p<.01

89
Table 10 (cont'd)

Results of Hierarchial Regression Analyses with Performance Accuracy Regressed

on Situation Competitiveness and Competitive Orientation

 

Timed
VARIABLE [3 SE B R2 AR2
STEP 1:
Pre-Task Knowledge .35 .08 .12** .12**
STEP 2:
Sit. Competitiveness‘I (C) .00 .08 .12*"‘ .00
Comp. Orientation (CO) -.04 .08
STEP 3:
C x CO .04 .40 .12** .00

 

n=150. ' Coded: 0=Noncompetitive, 1=Competitive. * p< .05, ** p< .01

90
Table 11

Results of Hierarchial Regression Analyses with Performance Quantity Regressed

on Situation Competitiveness and Competitive Orientation

 

 

 

Time-J
VARIABLE [3 SE B R2 AR2
STEP 1:
Pre-Task Knowledge -.01 .08 .00 .00
STEP 2:
Sit. Competitiveness‘ (C) .00 .00 .00 .00
Comp. Orientation (CO) .06 .08
STEP 3:
C x CO -.34 .43 .01 .00
m2
VARIABLE [3 SE B R2 AR2
STEP 1:
PTe-Task Knowledge .01 .08 .00 .00
STEP 2:
Sit. Competitivenessa (C) .10 .08 .01 .01
Comp. Orientation (CO) .07 .08
STEP 3:
C x CO -.18 .43 .02 .00

 

n= 150. ‘ Coded: 0=Noncompetitive, 1=Competitive. * p< .05, ** p< .01

91

Table 11 (cont'd)
Results of Hierarchial Regression Analyses with Performance Quantity Regressed

on Situation Competitiveness and Competitive Orientation

 

Time}

VARIABLE [3 SE B R” AR”
STEP 1:

Pre-Task Knowledge -.10 .08 .01 .01
STEP 2:

Sit. Competitiveness‘ (C) -.08 .08 .03 .02
Comp. Orientation (CO) .13 .08

STEP 3:

C x CO -. 15 .42 .03 .00

 

n=150. ‘ Coded: 0=Noncompetitive, 1=Competitive. * p< .05, ** p< .01

92

competitive situations and r = .11 in competitive situations (x” (1) = .23, p> .05), at
Time 2 the correlations were i'_= .28 and r = .18 (12(1) = .36, p> .05), and at Time 3
the correlations were r = -.03 and t = -.02 (1”(1, = .00, p> .05). Additional potential
reasons for the lack of significance associated with this interaction are presented later.

The seventh hypothesis predicted an interactive effect for goal situation and
competitive orientation on task performance. Hierarchical regression analyses related
to this hypothesis are presented in Tables 12 and 13. Results suggested no support for
the predicted interactive effects. Again, since there was a possibility that the lack of
significance in these analyses could have been due to the fact that regression technique
is not powerful enough to detect the interaction (Alexander & DeShon, 1994), an
additional analysis was done. Again, this analysis failed to find support for the
predicted interaction. At Time 1, the F isher-z correlations were r = .07 between
competitive orientation and performance accuracy in ”do your best” conditions, i =
.27 in easy goal conditions, and t = -.17 in difficult goal conditions (x” (2, = 4.56,
p> .05), and at Time 2 the correlations were L: .11, t = .31, and I = .25,
respectively (x20, = .99, p> .05), while at Time 3 the correlations were r = .10, r = -
.17, and r = -.01 (fig) = 1.73, p>.05).

Hypothesis 8 predicted that the three exogenous variables of goal situation,
situation competitiveness, and competitive orientation would have interactive effects on
the prediction of goal commitment. Implicit in this hypothesis, as well as the
theoretical review leading up to it, was that in competitive situations individuals who

were competitive would be more likely to accept their assigned goal than individuals

93

Table 12
Results of Hierarchial Regression Analyses with Performance Accuracy Regressed

on Goal Situation and Competitive Orientation

 

 

 

Time-1
VARIABLE B SE B R” AR”
STEP 1:
Pre-Task Knowledge .19 .08 .03 .03
STEP 2:
Goal Situation‘ (G) -.02 .08 .04 .01
Comp. Orientation (CO) .07 .08
STEP 3:
G x CO -.42 .41 .05 .01
Iimel
VARIABLE B SE B R” AR”
STEP 1:
Pre-Task Knowledge .25** .08 .06“ .06“
STEP 2:
Goal Situation‘ (G) -. 15 .08 . 13* .07“
Comp. Orientation (CO) .21“ .08
STEP 3:
G x CO .40 .39 .14“ .01

 

n=150. ‘ Coded: 0=Do Your Best, 1=Easy, 2=Difficult. * p< .05, ** p< .01

94

Table 12 (cont'd)
Results of Hierarchial Regression Analyses with Performance Accuracy Regressed

on Goal Situation and Competitive Orientation

 

Time-1.3
VARIABLE B SE B R” AR”
STEP 1:
Pre-Task Knowledge .35** .08 .12** .12**
STEP 2:
Goal Situation ‘ (G) -. 10 .08 .13** .01
Comp. Orientation (CO) -.04 .08
STEP 3:
G x CO -.18 .40 .14** .00

 

n=150. ‘ Coded: 0=Do Your Best, 1=Easy, 2=Difficult. * p< .05, ** p< .01

95

Table 13
Results of Hierarchial Regression Analyses with Performance Quantity Regressed

on Goal Situation and Competitive Orientation

 

 

 

1‘1le
VARIABLE B SE B R” AR”
STEP 1:
Pre-Task Knowledge -.01 .08 .00 .00
STEP 2:
Goal Situation‘ (G) -.22* .08 .05 .05
Comp. Orientation (CO) .05 .08
STEP 3:
G x CO .50 .41 .06 .01
Time-.2
VARIABLE B SE B R” AR”
STEP 1:
Pre-Task Knowledge .01 .08 .00 .00
STEP 2:
Goal Situation‘ (G) -.14 .08 .02 .02
Comp. Orientation (CO) .06 .08
STEP 3:
G x CO .62 .42 .04 .01

 

n=150. ‘ Coded: O=Do Your Best, 1=Easy, 2=Difficult. * p< .05, ** p< .01

96

Table 13 (cont'd)

Results of Hierarchial Regression Analyses with Performance Accuracy Regressed

on Goal Situation and Competitive Orientation

 

Iime3

VARIABLE B SE B R” AR”
STEP 1:

Pre-Task Knowledge -.10 .08 .01 .01
STEP 2:

Goal Situation ‘ (G) -.10 .08 .03 .03
Comp. Orientation (CO) .12 .08

STEP 3:

G x CO .24 .42 .04 .00

 

n=150. ‘ Coded: 0=Do Your Best, 1=Easy, 2=Difficult. * p< .05, ** p< .01

97

low in competitive orientation. Similarly, individuals who were in non-competitive
situations and who were low in competitive orientation would be more likely to accept
assigned goals than individuals who were high in competitive orientation. To test
whether acceptance of goal differed as a function of competitive orientation and
situation competitiveness, a logistic regression was run with acceptance (yes/no) as the
categorical criterion, and competitive orientation, situation competitiveness, and their
interaction as predictors. The entry of terms in the logistic regression followed the
same logic as that used in the preceding hierarchical multiple regression analyses. That
is, main effects were entered first followed by the interaction. This procedure in
logistic regression results in the test of model fit for each of the two models: Model 1
including just the main effects and Model 2 including the main effects and interaction.
Model fit is assessed using a Ax” index. Within each model, significance of individual
variables is indicated by the Wald x”. Table 14 contains the results of this analysis.
As these results illustrate, a main effect for situational competitiveness was
observed at all three time periods. Specifically, individuals in non-competitive
situations reported greater goal acceptance. Goal acceptance for non-competitive
versus competitive conditions within each time period was: T1 -- 48% to 16%, T2 --
44% to 12%, and T3 -- 43% to 15%. On the other hand, no main effects were
observed for competitive orientation. The predicted interactive effects of competitive
situation and competitive orientation on goal acceptance received mixed support. As
predicted, a significant interaction was observed at Time 1 (Wald 1”“, = 5.61, p <

.05. Additionally, this interaction was in the predicted direction with the correlation

98
Table 14

Results of Logistic Regression Analyses with Assigned Goal Acceptance Regressed on

Situation Competitiveness and Competitive Orientation

 

 

 

 

 

Iimel
VARIABLE Ax” B SE B Wald
STEP 1:
Situation Competitiveness ‘ (C) 18.34“ -1.58 .39 16.33**
Comp. Orientation (CO) -.09 .31 .09
STEP 2:
C x CO 6.06" 1.61 .68 5.61*
n = 149
IimeZ
VARIABLE Ax” B SE B Wald
STEP 1:
Situation Competitiveness ‘ (C) 21.30** -1.77 .43 17.18**
Comp. Orientation (CO) -.38 .33 1.33
STEP 2:
C x CO 2.77 1.15 .71 2.68
n = 150
Time-.3
VARIABLE Ax” B SE B Wald
STEP 1:
Situation Competitiveness ‘ (C) 15.04” -1 .47 .40 13.37**
Comp. Orientation (CO) -. 14 .31 .19
STEP 2:
C x CO 1.75 .86 .66 1.70

 

n=150. ‘ Coded: 0=Non—Competitive, 1=Competitive. * p< .05, ** p< .01

99

between competitive orientation and acceptance in the competitive condition of [(74) =
.20, p=.08 and in the non-competitive condition [(74) = -.19, p=.10. Competitive
individuals were more likely to accept their goals when the goals were framed in terms
of interpersonal comparisons (i.e., outperform another person working on a similar
task) than if they were framed in terms of intrapersonal comparisons (i.e., achieve a
certain level of task performance). In contrast, noncompetitive individuals were more
likely to accept goals stressing intrapersonal, rather than interpersonal, comparisons.
In spite of these encouraging results, significant interactions were not observed at either
Time 2 or Time 3. As a result, some support, although mixed, was gathered
concerning the relationship among the exogenous variables and the critical intervening
variable of goal acceptance allowing analyses of the relationships predicted in
Hypothesis 8 to be conducted.

Support for the predicted interactive effects of goal situation, situation
competitiveness, and competitive orientation on goal commitment was examined again
using hierarchical multiple regression. Because acceptance of a goal previously has
been demonstrated to be a critical precursor to commitment (Locke & Latham, 1990),
the commitment measure used in the following analyses was related to assigned goals
when individuals did not report a different personal goal and to personal goals when
they differed from assigned goals. Results of these analyses are presented in Table 15.

At both Time 1 and Time 2, no significant 2- or 3-way interactions were
observed (all p's > .05). In fact, the only significant effect at either of these times

was for competitive orientation at Time 2 (B = .20, p< .05). This effect suggests that

100

Table 15
Results of Hierarchial Regression Analyses with Goal Commitment Regressed on
Goal Situation, Situation Competitiveness, Competitive Orientation, and

Respective Interaction Terms

 

Time-.1

VARIABLE B SE B R” AR”
STEP 1:

Goal Situation‘ (G) -.14 .08 .04 .04
Situation Competitivenessb (C) .01 .08

Comp. Orientation (CO) .15 .08

STEP 2:

C x G .16 .15 .05 .01
STEP 3:

G x CO .46 .43 .06 .01
C x CO -.31 .43

STEP 4:

C x G x CO —.42 79 07 .00

 

n=149. ‘ Coded: 0=Do Your Best, 1=Easy, 2=Difficult. " Coded: 0=Non-
competitive, 1=Competitive. * p < .05, ** p < .01

101

Table 15 (cont'd)

Results of Hierarchial Regression Analyses with Goal Commitment Regressed on

Goal Situation, Situation Competitiveness, Competitive Orientation, and

Respective Interaction Terms

 

Time-.2

VARIABLE B SE B R” AR”
STEP 1:

Goal Situation‘ (G) -.13 .08 .06* .06*
Situation Competitivenessb (C) .01 .08

Comp. Orientation (CO) .20“ .08

STEP 2:

C x G .13 .15 .06 .00
STEP 3:

G x CO .20 .42 .07 .00
C x CO .22 .43

STEP 4:

C x G x CO -.49 .78 07 00

 

n=150. ‘ Coded: O=Do Your Best, 1=Easy, 2=Difficult. " Coded: 0=Non-
competitive, 1=Competitive. * p < .05, ** p< .01

102

Table 15 (Cont'd)

Results of Hierarchial Regression Analyses with Goal Commitment Regressed on

Goal Situation, Situation Competitiveness, Competitive Orientation, and

Respective Interaction Terms

 

Iimel

VARIABLE B SE B R” AR”
STEP 1:

Goal Situation‘ (G) -. 14 .08 .07* .07*
Situation Competitiveness” (C) .00 .08

Comp. Orientation (CO) .22** .08

STEP 2:

C x G .30* .15 .10** .03*
STEP 3:

G x CO -.20 .42 .10“ .01
C x CO .30 .42

STEP 4:

C x G x CO -.30 .76 .10“ .00

 

n=150. ‘ Coded: 0=Do Your Best, 1=Easy, 2=Difficult. b Coded: 0=Non-
competitive, 1=Competitive. * p < .05, ** p < .01

103

individuals who scored high on the competitive orientation measure tended to be more
committed to their goals than those low on this measure. At Time 3, in addition to a
main effect for competitive orientation (B = .22, p < .01), a significant interaction
between situation competitiveness and goal situation was observed (B = .30, p< .05)
(see Figure 5). Because the levels of commitment to assigned difficult goals in both
competitive and non-competitive conditions was roughly equivalent, the significance of
this interaction is derived mainly from the disordinal interaction between situation
competitiveness and the ”do your best” and easy goal levels of goal situation.
Individuals in competitive situations reported higher goal commitment in the easy and
difficult goal conditions. Alternatively, individuals in non-competitive situations
reported higher commitment under the relatively ambiguous "do your best” goals. The
effects related to commitment in the non-competitive conditions replicate what has
typically been found in goal setting research (Locke & Iatham, 1990). This is not
surprising given that goal setting studies have typically used tasks and situations that
were non-competitive (e. g., anagram tasks). These results provided additional support
for the appropriateness of the manipulation of goal level in the current study.

Results related to commitment in the competitive situations are more difficult to
reconcile with the existing goal setting literature. If goals and situation competitiveness
have the same effect, then commitment in these situations should be the same.
However, the disordinal interaction suggests that situation competitiveness has a
different effect on commitment than does goal level. In competitive situations

individuals expressed greater commitment to easy goals than to either "do your best" or

104

 

 

 

 

 

 

 

4.1
l
4
.. 3.9
C
E +
a: Non-Com titive
53.8 + 9"
8 . Competitive
3.7
l
3.6
3'5 Do Yot'lr Best Ea'sy Difficult
Goal Situation

Figure 5. Interaction of Goal Situation and Competitive Situation on Goal

Commitment

 

105

difficult goals. These differences, along with the fact that the goal manipulation
produced results on goal commitment that were consistent with previous goal setting
literature provide more evidence for the independence of goals and situation
competitiveness. In addition, these results call into question the equivalence of ”do
your best" instructions across the competitive conditions. However, in light of the lack
of significant interactions elsewhere in these analyses, strong conclusions regarding
these effects must be tempered.

Hypothesis 9 predicted a mediating effect for goal commitment on the
relationship between situation characteristics (i.e., goal situation and situation
competitiveness) and competitive orientation on task performance. Because previous
analyses demonstrated that the relationship between the proposed mediator (i.e.,
commitment) and task performance was not significant, the hypothesis of mediation
was not tested (James & Brett, 1984).

Despite evidence that a significant portion of individuals did not accept their
assigned goals, the intercorrelations between commitment measures (see Table 3)
suggest that when individuals did pursue personal, rather than assigned, goals, these
self-set goals were similar to those that were assigned. This evidence suggests the
unidimensionality of the commitment measures. As a result of this lack of distinction
between assigned and personal goals, the hypothesized role of commitment in the
proposed model was not supported. However, since goal commitment has frequently
been identified as a moderator in the difficulty-performance relationship, hierarchical

analyses were conducted to test the viability of this effect. Results of these analyses for

106

performance accuracy are reported in Table 16. No effects were observed for this
alternate hypothesis.

Hypothesis 10 predicted a significant relationship between task performance and
self-efficacy. This relationship was examined through hierarchical regression
techniques by first controlling for pre-task self-efficacy. Results of this analysis are
presented in Table 17 for performance accuracy and Table 18 for performance quantity.

These results provide support for the prediction that performance accuracy has a
positive effect on self-efficacy. Stated another way, the better one performs a task, the
higher one's self-efficacy for task performance. While these results may be viewed as
simply a replication of previous research on the construct of self-efficacy (Gist &
Mitchell, 1992), it is of interest that these effects were only true for performance
accuracy. Viewing more targets did not have a significant effect on self-efficacy. One
of the dimensions suggested as important in self-efficacy judgments (i.e., experience
with a task) was demonstrated to be insufficient to increase self-efficacy assessments.
In order to significantly alter perceptions of efficacy, not only must individuals perform
a task and receive feedback (i.e. , gain task experience), but also they must perform the
task accurately.

The final hypothesis predicted a significant, positive relationship between task
performance and task satisfaction. From Table 3, the correlation between performance
accuracy at Time 1 and task satisfaction was observed to be [(149) = .15, p< .05, at
Time 2 [(149) = .20, p< .05, and at Time 3 [(149) = .24, p< .01. As predicted,

performing well was associated with more favorable perceptions of the task. Indeed,

107

Table 16
Results of Hierarchial Regression Analyses with Performance Accuracy Regressed on
Goal Situation, Situation Competitiveness, Competitive Orientation, Goal

Commitment, and Respective Interaction Terms

 

Time-.1
VARIABLE B SE B R” AR”
STEP 1:
Goal Situation‘ (G) -.06 .08 .01 .01
Goal Commitment (GC) .43 .08
STEP 2:
G x GC .79 .57 .02 .01

 

n=149. ‘ Coded: 0=Do Your Best, 1=Easy, 2=Difficult. " Coded: 0=Non-
competitive, 1=Competitive. * p< .05, ** p<.01

 

Iime_2
VARIABLE B SE B R” AR”
STEP 1:
Goal Situation‘ (G) -. 19* .08 .04* .04*
Goal Commitment (GC) .22 .08
STEP 2:
G x GC -.02 .59 .04 .00

 

n=150. ‘ Coded: 0=Do Your Best, 1=Easy, 2=Difficult. " Coded: 0=Non-
competitive, 1=Competitive. * p< .0 , ** p< .01

108

Table 16 (cont'd)
Results of Hierarchial Regression Analyses with Performance Accuracy Regressed on
Goal Situation, Situation Competitiveness, Competitive Orientation, Goal

Commitment, and Respective Interaction Terms

 

Time-.3
VARIABLE B SE B R” AR”
STEP 1:
Goal Situation‘ (G) -.13 .08 .04* .04*
Goal Commitment (GC) . 15 .08
STEP 2:
G x GC .34 .51 .05 .00

 

n=150. ‘ Coded: 0=Do Your Best, 1=Easy, 2=Difficult. " Coded: 0=Non-
competitive, 1=Competitive. * p < .05, *“ p < .01

109
Table 17

Results of Hierarchial Regression Analyses with Post-Task Self-Efficacy Regressed on

Pre-Task Self-Efficacy and Performance Accuracy

 

 

 

 

 

Iime_1
VARIABLE B SE B R” AR”
STEP 1:
Pre-Task Self-Efficacy .68** .06 .46** .46**
STEP 2:
Task Performance .12** .06 .50“ .04**
Time-2
VARIABLE B SE B R” AR”
STEP 1:
Pre-Task Self-Efficacy .68“ .06 .46** .46**
STEP 2:
Task Performance .22** .06 .50" .05**
Time-.3
VARIABLE B SE B R” AR”
STEP 1:
Pre-Task Self-Efficacy .68“ .06 .46** .46“"‘
STEP 2:
Task Performance .23** .06 .51** .05**

 

n=149. “‘ p<.05, ** p< .01

110

Table 18

Results of Hierarchial Regression Analyses with Post-Task Self-Efficacy Regressed on

Pre-Task Self-Efficacy and Performance Quantity

 

 

 

 

 

Iimel
VARIABLE B SE B R” AR”
STEP 1:
Pre-Task Self-Efficacy .68** .06 .46** .46**
STEP 2:
Task Performance -.04 .06 .46** .00
Time-.2
VARIABLE B SE B R” AR”
STEP 1:
Pre-Task Self-Efficacy .68** .06 .46** .46**
STEP 2:
Task Performance .01 .06 .46** .00
Time 3
VARIABLE B SE B R” AR”
STEP 1:
Pre-Task Self-Efficacy .68** .06 .46** .46**
STEP 2:
Task Performance .07 .06 .46** .00

 

n=149. *p<.0 , **p<.01

111

this relationship got progressively stronger through the three time periods.

DISCUSSION

The current study examined the construct of competitive orientation within a
traditional I/O paradigm. Specifically, predictions regarding the interaction between
competitive orientation and situation competitiveness (Mitchell, Liden, and Rothman,
1985) and the independence of situation competitiveness and goals (Locke & Latham,
1990) were tested. To provide a framework for considering the observed results, this
discussion is organized into three sections. The first presents a brief review of the
results as they relate to specific study hypotheses, as well as describes some of the
strengths of the current study. The second section focuses on the potential limitations
to generalizability from the results, while the third considers future research directions
and a summary of the potential implications, both theoretical and applied, for the

construct of competitiveness.

B' [B I ll . '11: I'

In the Introduction section of this paper, a review and synthesis of previous
research led to the development of a model of competitiveness (see Figure 2). Because
the hypotheses offered and tested in the current study were based on the relationships
indicated in this model, this section reviews the results of key analyses with respect to
how they might be integrated with previous literature.

As previously stated, one of the primary aims of the current study was to

provide evidence for the importance of individual competitiveness as a key construct

112

113

within contemporary work settings. Since much of the research related to the construct
of competitive orientation has been done in the area of sport psychology, the
conceptualization and measurement of the construct in the current study attempted to
apply it within a work context. Because the construct has generally been defined as a
relatively stable personality characteristic (e.g., Monsaas & Engelhard, 1990), the
current conceptualization of competitiveness was similar to previous definitions. Due
to this similarity, the measure used was comprised of questions that are quite similar to
those that have typically been used in the sport psychology domain.

Results were supportive of some of the critical psychometric properties of the
measure. Specifically, adequate variability was observed in responses to this measure
and reliability was considered acceptable (a = .83). As predicted, competitiveness
was positively related to performance at Time 2 with more competitive individuals
being more accurate in their assessments of target threat level than less competitive
individuals. However, these effects were not observed for the other two time periods.
The lack of an observed relationship at Time 1 can be attributed to the fact that
interpersonal comparisons were not possible. On the other hand, the lack of a
significant correlation at Time 3 is more difficult to interpret given the significant
results observed at Time 2. Given the weak correlation between performance accuracy
measures at Time 2 and 3, r(148) = .16, p < .05, the non-significant correlation
between competitive orientation and Time 3 accuracy may be interpreted as an artifact
arising from the multidimensional nature of task performance. A more complete

discussion of the dimensionality issue is presented later in this section.

114

These mixed results are similar to previous literature that has examined this
relationship in that some studies have demonstrated a positive relationship (e. g.,
Monsaas & Englehard, 1990) while others have found no relationship (e.g., Martin &
Gill, 1991). One suggestion for why some studies find these effects and others do not
is that there is no ”main effect" for competitive orientation on performance, but rather
an interaction between competitive orientation and situations that produces an impact on
performance. Results from the current study with respect to this proposed interaction
are discussed shortly.

Additional evidence for the usefulness of the current measure of competitiveness
was found in the observed relationship between competitive orientation and ability.
Previous research (Martin & Gill, 1991) has typically demonstrated no relationship
between these two variables. Results of the current study similarly found no
relationship. Suggesting that the lack of an observed relationship is significant is
analogous to affirming the null hypothesis and cannot be used as the sole basis for
addressing the issue of construct validity. However, given the statistical power of the
current tests, a non-significant effect would only be expected in roughly 2 out of 10
replications. Not only is the non-significant correlation unlikely given the associated
power, but it also provides some evidence of discriminant validity for the measure
given the results of previous research. Thus, the current study provides some
psychometric support for the current measure of competitive orientation from both
reliability and discriminant validity perspectives. However, there are still many

unanswered questions about the construct of competitiveness in terms of understanding

115

the underlying psychological mechanisms by which it develops or operates.

Based on the assertion of Locke & Latham (1990) that goals and
competitiveness are "two sides of the same coin, " the current study included
independent manipulations of both of these situational factors. Indeed, a unique feature
of the current study was the experimental design that allowed for an examination of
these independent effects. Several interesting results emerged from the manipulations
of both situational competitiveness and goal level.

The current conceptualization and operational ization of situation competitiveness
was based on previous research (Mitchell, Liden, & Rothman, 1985, and Zajonc,
1965). In short, this research has suggested that the key characteristic that defines a
situation as competitive versus noncompetitive is the presence of public performance
feedback. In addition to the presentation of public feedback, instructions that were
given to individuals either stressed interpersonal (competitive) or intrapersonal
(noncompetitive) comparisons. To assess whether there was a difference between
experimental situations, individuals were asked for their perceptions regarding situation
competitiveness. Results suggested support for the role of public feedback and
interpersonal comparison instructions in influencing individual perceptions of
competitiveness with a significant correlation between perceptions and the manipulated
situation factors (r(148) = .64, p< .01). Specifically, individuals in situations that
included instructions that emphasized interpersonal comparisons and the presentation of
”public" feedback rated those situations as more "competitive” than those in situations

with instructions that emphasized intrapersonal comparisons and no ”public” feedback.

116

Because the hypotheses regarding the role of situation competitiveness both as a main
effect and also as a component of several interactions depended on demonstrating the
relationship between situation characteristics and individual perceptions, the strength of
the observed correlation suggested that the manipulation was effective in producing the
desired perceptions and that the remaining hypotheses could be examined. While these
results provide support for the role of both instructions and feedback, these situational
cues were not manipulated independently (i.e., instructions emphasizing interpersonal
comparisons with no public feedback and vice versa) and the relative importance of
these factors cannot be determined.

In addition to affecting perceptions of the situation, competitiveness was also
predicted to influence task performance. Specifically, based on previous research
(Locke & Latham, 1990), the effect of situation competitiveness on performance
accuracy was expected to mirror the often replicated goal effect (e. g., Locke, Shaw,
Saari, & Latham, 1981). However, results suggested no significant relationship
between situation competitiveness and performance accuracy at any of the three time
periods. Thus, the implicit suggestion that goals and situation competitiveness would
similarly affect task performance received no empirical support from this set of
analyses.

In addition to the main effect for situation competitiveness, hypotheses related
to this variable's interaction with competitive orientation were also tested. Specifically,
it was predicted that individuals who were in competitive situations would perform

better (i.e., be most accurate) if they scored high on the competitive orientation

117

measure, while those in noncompetitive situations would perform better if they scored
low on the competitive orientation measure. Unexpectedly, the results were not
supportive of this prediction. However, failure to find this effect is not unprecedented
(e.g., Matheson & Mathes, 1991). With respect to the current study, a potential reason
for failing to find support for the predicted interaction, as well as the main effect, is
related to the strength of the experimental manipulation. That is, although there were
significant perceptual differences across the two experimental conditions, it is possible
that the "absolute" magnitude of competitiveness in the competitive condition may not
have been strong enough to affect individual behaviors. As some research has
suggested (e. g., Thomas, 1992), there may be a continuum of competitiveness on
which situations may be placed. It is possible that the current manipulation, unlike
those typically reported in the sport psychology literature, was simply not powerful
enough (i.e., far enough along the continuum) to elicit the expected effects on task
performance.

Goals were the other situational factor assessed in the current study. Based on
extensive previous research (cf. Locke, Shaw, Saari, and Latham, 1981), the expected
effect for goals was that more difficult goals would lead to better performance (i.e.,
greater accuracy) than easy or "do your best" goals. However, results demonstrated
the opposite. Difficult goals were associated with lower performance, while easy and
"do your best" goals resulted in greater performance accuracy. As already presented in
the Results section, some goal setting studies have reported similar results (e. g., Barley

et al., 1989). These "negative" goal effects have generally been observed in situations

118

involving complex tasks. One proposed explanation for this effect has been that when
tasks are complex, setting specific, difficult goals leads to lower performance because
the direct goal mechanisms of effort, persistence, and choice are not sufficient when
task strategies must be learned (Locke & Iatham, 1990). Kanfer and Ackerman (1989)
provided additional evidence and explanation for these effects from a skill acquisition
perspective. Because performance on complex tasks is dependent on allocating
resources to the development of successful strategies, difficult performance goals divert
the allocation of these resources and therefore result in poorer task performance
(Kanfer & Ackerman, 1989). More specifically, this interference and resulting poor
performance has been demonstrated during learning of the task (Kanfer & Ackerman,
1989). When the task and strategies are well-known, specific, difficult goals have been
shown to lead to greater performance (Locke & Iatham, 1990). With respect to the
current results, since the task was similar in structure to those used by the previously
described studies, it is not surprising that the negative goal effects were found.
Although training was provided in the current context, it may simply have not been
enough. The improvement in average performance accuracy between Time 1 and Time
2 provides additional evidence in support of this explanation.

Given the previous results with respect to the main effect for goals, little
support was expected for the hypotheses related to the interaction of goals and
competitive orientation. In fact, no significant interactive effects were observed when
either accuracy or quantity was used as the performance measure.

However, despite the lack of significant effects on the primary outcome variable

119

(i.e., performance), results did provide a basis for testing the hypothesized similarity of
goals and situation competitiveness. Based on the assertion of Locke & Latham (1990),
these independently manipulated factors should have demonstrated similar relationships
with other key study variables. In fact, their respective relationships with a key
perceptual variable were not the same. The observed correlation between situation
competitiveness and the measure of perceived situational competitiveness was [(148) =
.64, p < .05, while the correlation between goal situation and the measure was [(148)
= .00, n.s. Additionally, the relationships among commitment across conditions (see
Table 3) further suggested that these situational characteristics had independent effects.
Specifically, significant relationships were observed between goals and commitment to
assigned and personal goals for all three time periods, while only assigned commitment
at Time 1 and Time 2 was significantly related to situation competitiveness. In short,
goals were significantly related to key goal perceptions and situation competitiveness
was related to key competitiveness perceptions, but the various perceptions were
unrelated. These data are taken as further evidence that situation competitiveness and
goals are not the same. However, due to the lack of significant results with respect to
the performance measures for either of these situational factors, it is unclear to what
extent these perceptual differences impact individual processes and outcomes.

This study also examined the roles of acceptance and commitment to assigned
instructions. Specifically, it was predicted that competitive individuals would be more
likely to accept instructions that emphasized interpersonal comparisons than non-

competitive individuals. Conversely, non-competitive individuals would be more likely

120

to accept instructions that emphasized intrapersonal comparisons than competitive
individuals. While these predictions were supported at Time 1, they did not receive
empirical support at either of the other time periods. Instead of the predicted
interactive effects, only situation competitiveness was significantly related to
acceptance. Thus, these results suggest that competitive situations (i.e., where
individuals are given instructions emphasizing interpersonal comparisons and provided
public feedback regarding their performance) will yield greater goal acceptance than
non-competitive situations. However, the mixed results preclude drawing strong
generalizations.

Predictions regarding the expected role of commitment were also tested in the
current study. Because acceptance was defined as a necessary precursor to
commitment, commitment to assigned or personal goals was hypothesized to mediate
the relationships among goal situation, situation competitiveness, competitive
orientation, and performance. Since there were no zero order relationships between
commitment and performance, the hypothesis of mediation was not examined (James &
Brett, 1984).

Although hypotheses were presented only in terms of performance accuracy, the
structure of the experimental task allowed the gathering of performance quantity data as
well. Given that most of the significant effects were observed in analyses including
performance accuracy, there is some evidence to suggest that the structure of the task
did result in people focusing on the accuracy dimension of task performance. An

interesting research design would be to provide instructions which alternatively directed

121

individuals to focus on the quantitative aspects of their performance.

Self-efficacy was another variable predicted to be an important component in
the conceptual model. Specifically, the current study examined its role as an
endogenous variable. Results were generally supportive of the expected relationship
between self-efficacy and performance. Specifically, individuals who performed more
accurately reported greater post-task self-efficacy. Additionally, experience alone was
not enough to increase self-efficacy evaluations, as evidenced by the non-significant
relationship between the quantity measures of performance and post-task self-efficacy
judgments. That is, individuals who reported efficacy for this task were those who had
more positive task feedback. These results have a number of applied implications. For
example, consider the implications of these results to employee training programs.
Given the results of the current study, these programs should not simply expose
individuals to new processes and procedures with repeated exposure, but also these
exposures should provide individuals with positive task experiences as a way toward
increasing feelings of self-efficacy. In fact, recent research has suggested that training
programs should not only focus on teaching critical skills, but should also enhance
trainees' self-efficacy for the task (Tannenbaum & Yukl, 1992).

An additional effect observed with respect to self-efficacy was the relationship
between competitive orientation and pre-task self-efficacy. Specifically, a significant
correlation, [(148) = .18, p < .05, was found. The fact that competitiveness and self-
efficacy may be related has important implications. Consider that competitiveness was

found to be related to performance accuracy, with more competitive individuals

122

performing better. Also, the relationship between performance accuracy and self-
efficacy was significant. Because people with feelings of greater pre-task self-efficacy
may be more likely to take on new tasks, the fact that they may be more competitive
suggests that they will likely perform better which would then result in greater post-task
self-efficacy. Additional research examining the underlying relationship between these
two constructs would be likely to provide important information about the
psychological mechanisms that may be responsible for an individual's competitive
orientation.

A final variable that was examined in the current study, task satisfaction, also
demonstrated significant effects with other key variables. Specifically, predictions that
performing well on a task would be positively related to resulting satisfaction with the
task were supported. These results provide some support for the assertion that the
direction of causality between job satisfaction and performance to be opposite from
early satisfaction research (Riggio, 1990). That is, people who are satisfied at work
are those that perform well and not that satisfaction causes better performance. Of
course, these data cannot completely refute the hypothesis that satisfaction causes
performance because no additional performance measures were collected after
individuals provided responses to the satisfaction scale. Additional research related to
this relationship should be directed toward gathering this type of information.

To summarize, support for some of the predicted relationships in the current
model was found. Interestingly, early relationships in the proposed model and later

relationships tended to have been supported, while the intervening processes were not.

123

Specifically, manipulated factors had significant effects on proximal perceptual
variables as well as some performance and individual outcome variables. However, the
intervening processes may have been complicated by individual's learning processes
and focus on the development of task performance strategies. This may suggest that
the relatively simple models that have been offered to describe the underlying processes
associated with competitive orientation, situation competitiveness, and goals (e.g.,
Monsaas and Englehard, 1990; Matheson and Mathes, 1991; and Locke and Iatham,
1990) should be closely examined in order to understand the motivational mechanisms
that operate within a complex work environment. It was suggested earlier that
integrating theories and constructs across areas of psychology might lead to a greater
understanding of motivation. The results of the current study have supported this
suggestion by demonstrating the potential importance of competitiveness, both as an
individual and a situational characteristic, within the area of work motivation.
Specifically, the integration of ideas within the current study has suggested one aspect

of goal setting theory that requires further examination.

I"' ll] 1.1.1.“!

A number of problems with the current experiment may have resulted in the
failure to support some of the key research hypotheses. Specifically, the impact of the
complexity of the research design, the complexity of the task itself, the
conceptualization and operationalization of the commitment variable, and the nature of

the situation competitiveness manipulation on the observed results are discussed in the

124

current section.

One potential limitation of the current study may have been associated with the
complexity of the study design. Consider the two primary issues addressed in the
current study: (1) the independence of situation competitiveness and goals and (2) the
role of competitive orientation within traditional work situations. The current study
attempted to examine both of these issues within the same research design. As a result,
individuals were exposed to situations which had instructions that emphasized both goal
and competitive dimensions. In fact, results did provide important evidence related to
the issue of situation competitiveness and goal independence. However, the interactive
effects of either goals or situation competitiveness with competitive orientation were
not observed. This may have been due to the presence of both factors in all situations.
For example, consider the hypothesized relationships involving the goal level
manipulation. Primarily, these predictions were derived from traditional goal setting
research that has used relatively simple tasks (e.g., solving anagrams) in which the only
situational variant was goal level. As more recent goal setting research has
demonstrated (e.g., Locke & Latham, 1990), as experimental situations become more
complex (i.e., multiple independent variables), the typical effects for goals are not
always observed. Likewise, studies that have examined the impact of situation
competitiveness on behavior (e. g., Martin & Gill, 1991) have not traditionally included
other situational factors. With the previous considerations in mind, the failure to find
evidence in support some of the predicted hypotheses may have been related to the

differences in experimental design of this study from those that were used to gather

125

data on which the specific predictions were based.

Another potential limitation of the current study is related to the task itself.
Specifically, the task may have been too complex to test the basic propositions of the
current research. Both of the situational characteristics (situation competitiveness and
goals) were proposed to influence individuals' basic motivation to perform a task.
However, the variance in task performance in the current study may have been due to
factors other than motivation. Evidence for this is the finding of "negative” (i.e., ”do
your best” goals resulting in better task performance than difficult goals) goal effects.
Such results have typically been observed in experiments that have utilized complex
decision tasks. As the previous discussion of these effects has suggested, a potential
reason for observing these results is that when tasks are complex (i.e., require the
development of strategies), goals may interfere with performance by detracting from an
individual's available cognitive resources. In short, when individuals are in the process
of learning a task, goals do not generally result in positive effects on performance. In
the current study, although individuals were provided with training and given practice
on the task, there was additional learning occurring during the experiment. As a result,
the current task may have presented a more complex situation than the theory was able
to describe.

A third potential problem related to the current study is the conceptualization
and operationalization of commitment. Because commitment has been demonstrated to
be an important intervening variable within the goal setting literature (Locke &

Latham, 1990), the proposed model included it as a mediator. However, given that

126

instructions included not only a goal dimension, but also a competitive dimension,
commitment was conceptualized and operationalized to reflect these dimensions. While
the operationalization was consistent with the construct in the current study, an
important question is "With goals and competition instructions mixed, is the construct
of commitment the same as commitment as traditionally defined in the goal setting
literature?” Within the context of the current study, a better understanding of this
modified conceptualization and resulting operationalization of commitment are clearly
needed. Additionally, these issues related to commitment may be important to consider
in other goal setting studies as well. That is, when other situational factors are present,
goal commitment may no longer be a relevant construct as it has been traditionally been
defined. This issue further illustrates the fact that goal setting research has often taken
a fairly myopic view of goals. It is likely that in most ”real world" contexts, goals
occur in situations that are rich and varied including other motivational forces such as
rewards/punishments, expectancies, and competition. These other situational
characteristics may change the nature of the goal-performance relationship. More
research examining goals in more richly developed contexts is needed to further
understand the effects and processes of goals.

One final problem to be addressed is the potential lack of "true” competition.
While the manipulation of situation competitiveness was perceived by individuals, there
is no way of knowing the absolute strength of this manipulation. Theoretically, there is
likely a continuum on which situations can vary in terms of competitiveness. Within

the relatively narrow scope of the current study (i.e. , two situations), there is little way

127

of knowing where the manipulations were on this continuum. For example, another
competitive situation may have been used in which individuals not only received public
feedback, but could also directly observe the performance of each other. For reasons
of control, the current study did not examine the effect of this type of situation on
performance. However, if this latter situation is ”more” competitive than the one used
in the current study, difference results may have been observed. As already discussed,
the issue of situation "strength” could have important implications for observing the
predicted interactions of competitive orientation and situation competitiveness. Future
research on the effects of situation competitiveness should examine the relative strength

of various situations.

EututeResearch

A number of research questions that could be pursued by future researchers in
this area have already been presented in various sections of this paper. The purpose of
this final section is to describe the critical questions that must be addressed in terms of
examining the role of competitiveness as an individual difference variable within
organizational contexts.

The current study has illustrated the potential importance of competitive
orientation as a construct within traditional work settings. However, many unanswered
questions remain regarding this construct. First, although previous research has
demonstrated the influence of competitive orientation on a variety of indices of

performance, little work in the area of construct development has been done.

128

Specifically, little, or no, research evidence has been presented that speaks to the
construct validity of competitive orientation or the number of measures that have been
used to assess it. Additionally, there have been few systematic attempts that have
examined the set of relationships between competitive orientation and other similar
constructs (i.e., achievement motivation, self-efficacy, cooperative orientation). Future
research should take a more basic focus of the competitive orientation construct and try
to establish some evidence that would address these very fundamental construct-related
concerns. A more detailed examination of the construct would provide a better
understanding of the motivational role that competitive orientation plays within a
variety of performance contexts.

Yet another set of research questions related to understanding the fundamental
mechanisms underlying competitive orientation should focus on the proposed
relationship with situation competitiveness. As previously discussed, situations likely
vary in terms of their competitiveness. Until a thorough understanding of this
"competitiveness continuum" is achieved, the nature of a proposed person/situation
interaction will not be known. This interaction has important implications for
researchers in the area of I/O within the areas of personnel selection and job redesign.
For example, consider the importance of understanding the nature of situation
competitiveness within the framework of job analysis. If sound measures of
competitive orientation and situation competitiveness existed, this information could

ultimately be used to aid in the selection of new employees.

129

In conclusion, although there have been questions about the role of
competitiveness as both an individual difference and a situational factor, there continue
to be many people and situations that are defined as competitive. The current study
was an initial attempt toward understanding the nature of this relationship within a
traditional organizational paradigm. While evidence regarding the independence of
situation competitiveness and goals, there was little evidence with respect to the
predicted person-situation interaction. As a whole, the integration of concepts across
research areas has demonstrated some useful relationships and also suggested some
interesting areas for future research. Because of the importance of the topic of
motivation within the psychological literature, future attempts toward the integration of
concepts would likely provide additional critical information. Thus, not only did this
study provide useful answers to some important questions, but also it stimulated the
development of new research questions that will continue to provide an integration of

ideas and methods across psychological areas.

APPENDICES

APPENDIX A

130

APPENDIX A

NAVAL AIR DEFENSE SIMULATION

TRAINING MANUAL

131

INIRQDILCIIQN

The year is 1996 and you are part of a US naval carrier group's command and control
team stationed in the Middle East. A regional conflict between two nations in this area
has recently broken out, and your mission is to protect seagoing commercial traffic in
the area from accidental or intentional attacks. As history indicates, this is a highly
sensitive task. For example, in 1987, an Iraqi jet accidentally fired two Exocet missiles
into the Frigate U.S.S. Stark, killing 37 American servicemen and crippling the vessel.
One year later, the USS. Cruiser Vincennes accidentally shot down an Iranian
passenger plane killing 290 innocent civilians. Any repeat of mistakes of this kind will
probably lead to a withdrawal of American forces from the area. Such a withdrawal
would have disastrous economic and political ramifications that would spread well
beyond this region.

IHEIASKIQRSE

A naval carrier battle group team is an awesome array of ships and support units. It
has a concentric ring of missile firing warships which protect the aircraft carrier at its
center. The aircraft carrier in return provides an overall umbrella of air protection for
the entire task force. The carrier's 90 planes can unleash air strikes against targets at
land, sea, and even under water. A carrier group can dominate up to 196,000 square
miles of ocean. A standard carrier group consists of six ships; the Carrier itself, two
Ticonderoga class Aegis Cruisers, two anti-air Destroyers, and a submarine.

A carrier group is also supported by AWACs reconnaissance planes and a land based
Coastal Air Defense (CAD) unit. Although the Carrier itself is equipped with some air
patrol capacities, the Cruisers, AWACs, and CAD units provide the bulk of air traffic
patrol. Taken together, the air patrol groups on the Carrier, the Cruiser, the AWACs,
and the CAD unit make up the command and control team.

MISSION

You role in this simulation is the Commanding Officer (C0) of a Carrier. Your
mission is to monitor the air space surrounding the carrier group, making sure that
neutral ships are not attacked. In performing this role, you must make certain that you
do not allow loss of life resulting from accidental or intentional attacks on ships in the
task force. At the same time, it is also of paramount importance that you do not
inadvertently shoot down friendly military aircraft or any civilian aircraft. Many
passenger flights move in and out of the region, and friendly military aircraft from
nations not involved in the conflict also patrol the area. The navy can ill-afford any
mistakes of either the Stark or Vincennes variety.

DECISIONS

132

Your task is to decide what response the carrier group should make toward incoming
aircraft. Aircraft that are being tracked on radar are called tatgets. You base your
decisions on data you collect by measuring characteristics of the air targets. These
measures are obtained from sophisticated radar equipment. You must make a critical
choice regarding each target. There are five potential responses, IGNORE,
MONITOR, WARN, READY, DEFEND. These are described below:

IGNORE:

MONITOR:

WARN:

DEFEND:

This means that the carrier group should devote no further attention to
the target and instead focus on other possible targets in the area. The
group should never ignore a target that might possibly attack. This
would most assuredly lead to loss of lives on the ship attacked.

This means that the carrier group should continuously track the target on
radar. A carrier group can only monitor a few targets, thus monitoring
diminishes the group's overall patrol capacity.

This means that the carrier group sends a message to the target
identifying the group and alerting the target to steer clear. Warning
targets that should be ignored detracts from the salience of legitimate
warnings. Warning targets that intend to attack is also bad, since the
warning makes it easier for the attacker to locate the ship.

This means to steer the ship into a defensive posture and to set defensive
weapons on automatic. A ship in a readied position is rarely vulnerable
to attack. This stance should not be taken to non-threatening targets
since weapons set to automatic often fire mistakenly at innocent targets
that fly too close to the carrier group. A ship in this position cannot
readily take offensive action toward the target.

This is ”weapons away" and means to attack the target with Tomahawk
cruise missiles. A defend decision cannot be aborted once initiated.
Defend is an appropriate response only when you feel an attack is
imminent.

 

The
21101

133

W

The incoming air targets can be measured on nine attributes. These are listed below
along with the ranges of possible values on the attributes:

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

SPEED:

ALTITUDE:

SIZE:

ANGLE:

DIRECTION:

CORRIDOR
STATUS:

RADAR TYPE:

RANGE:

150 to 800 miles per hour (mph)

5,000 to 35,000 feet

size of the target ranging from 10 meters to 65 meters

-15 degrees (rapid descent) to +15 degrees (rapid ascent)

stands for ”Identification Friend or Foe". This is a radio
signal that identifies whether an aircraft is civilian,
para-military or military, and ranges from 0.2 Mhz (an
airliner) to 1.8 Mhz (a fighter)

from +30 degrees (passing far to the east or west of the
carrier) to 0 degrees (coming straight to the carrier)

a corridor is a lane open to commercial air traffic. It is
expressed in terms of miles from the center of the
corridor, ranging from 0 miles (in the middle of it) to 30
miles (way out of it)

the kind of radar possessed by the aircraft ranging from
Class 1 (weather radar only) to Class 9 (weapons radar)

distance of the aircraft from the Carrier ranging anywhere
from 20 to 200 miles

134

WWI

In general, the degree to which an incoming target is threatening depends on its
standing on the nine attributes. There are five simple rules to remember in determining
the danger associated with any target:

(a)

(b)

(C)

(d)

(6)

all else equal, in terms of IFF, military targets are more threatening than
civilian targets (see attribute #5).

SPEED and DIRECTION go together, so that fast targets coming straight in are
most threatening (see #1 & #6 above). Speed alone and direction alone mean
nothing. There is nothing to fear if fast targets are not headed toward the
group. There is nothing to fear from objects headed directly for the group that
are moving slowly.

ANGLE and RANGE go together, so that descending targets that are close are
especially threatening (see #4 & #9 above). Angle alone and range alone mean
nothing. Descending targets that are far away, or close targets that are on the
way up are not threatening.

ALTITUDE and CORRIDOR STATUS go together, so that low flying targets
that are way outside the corridor are especially threatening (see #2 & #7 above).
Altitude alone and corridor status alone mean nothing. There is nothing to fear
from high targets flying well outside the corridor or low flying targets in the
middle of the corridor.

SIZE and RADAR go together, so that small objects with weapons radar are
especially threatening (see #3 & #8 above). There is nothing to fear from small
targets with weather radar or from large targets with weapons radar.

135
W

The following chart will help you determine the level of threat associated with the
different values on all nine attributes.

DEGREE OF THREAT
Non Somewhat Very
Threatening Threatening Threatening
Speed 100-275 mph 325-500 mph 600-800 mph
Altitude 35 ,000-27,000 ft 23,000-17,000 ft 13,000—5,000 ft
Size 65-43 m 37-23 m 17-10 m
Angle +15 to +8 dgs +3 to -3 dgs -8 to -15 dgs
IFF .2 to .6 Mhz .9 to 1.1 Mhz 1.4 to 1.8 Mhz
Direction 30 to 22 dgs 18 to 12 dgs 8 to 0 dgs
Corridor Status 0 to 8 mi 12 to 18 mi 22 to 30 mi
Radar Type Class 1 & 2 Class 5 Class 8 & 9
Range ' 200 to 110 mi 90 to 60 mi 40 to 1 mi

W

The five rules combine to determine the overall threat represented by the target. For
example, if you detected (1) a military aircraft that is (2) flying in straight and fast, (3)
was close and descending, (4) was flying low and way outside the corridor and (5) was
small and had weapons radar; the ship is being attacked and should DEFEND.

If the you detected (1) a civilian aircraft, (2) passing slow at an angle, (3) was far away
and ascending, (4) was flying high and in the middle of the corridor and (5) was large
and had weather radar; this is a passenger plane that should be IGNORED.

Intermediate responses like MONITOR, WARN, or READY are to be used when the
target is threatening according to some of the rules, but not all. For example, a
military aircraft that is close and descending (see Rule c), small and with weapons
radar (see Rule e), but is travelling slowly at an angle to the group (see Rule b), and is
high and in the middle of the corridor (see Rule (1) might need to be WARNED. It
should not be IGNORED, but also should not be shot down.

136
EAIRQLSESSIQNS

Ihe_"Sea_Sc[cenZ. A patrol session is the time that you are responsible for monitoring
air traffic in your designated area. While you are monitoring traffic, you will be
stationed at a computer monitor. When this screen has a Carrier icon on it, you are in
the "Sea Screen" mode. This means that there is a target (i.e. a red dot) in your
airspace that needs to be assessed. The target will begin to blink and beep at an
increasing rate when there is less than 30 seconds to respond. If you fail to make any
decision with respect to the target, this will be treated as if you decided to IGNORE it.

WW. When a patrol session is over, you will receive an immediate
report telling you how well you performed. It will inform you of your decision, the
correct decision, and the outcome of the session. There are five possible outcomes
from an encounter, HIT, NEAR MISS, MISS, INCIDENT, and DISASTER. Your
effectiveness will be expressed in terms of points associated with each of these
outcomes. The outcomes and their point values are:

HIT: A hit means that your decision was exactly correct. For
example, the target should have been ”warned" and that was
exactly what you decided. A hit is worth 2 points to your overall
score. The color bars at the top and bottom of the screen will be
green when this occurs.

NEAR MISS: A near miss means that you were off by one place in terms of
your aggressiveness level. For example, if your decision was a
"warn" when it should have been "monitor" this would be a near
miss (a little too aggressive). It would also be a near miss if your
decision was ”warn" when it should have been "ready" (a little
too passive). A near miss is a pretty good outcome. A near miss
is worth I point. The color bars at the top and bottom of the
screen will be aquamarine when this occurs.

MISS: A miss means that your decision was off by two places. This is
worth 0 points. The color bars will be purple when this occurs.

INCIDENT: An incident means that your decision was off by three places.
An incident means that you just narrowly avoided disaster (e. g.,
being hit yourself or mistakenly shooting down a friendly target).
This outcome results in a loss of 1 point. The color bars will be
red when this occurs.

DISASTER: A disaster means that your decision was off by four places. This
outcome results in a loss of 2 points. The color bars will be
black in this case.

APPENDIX B

137

APPENDIX B

Competitive Orientation Measure

Using the scale below indicate your agreement with the following items. Do not
answer how you think you are expected to answer. Answer in an honest fashion.

10.

11.

1 = Strongly Disagree

2 = Disagree

3 = Neither Agree nor Disagree
4 = Agree

5 = Strongly Agree

When taking part in games or sports contests, I feel determined to
always come in first, or otherwise win.

When I take a test for a class, I try to get the best grade in the class.
Winning is not that important to me.

If someone does better than me at something, I feel irritated.

I don't care if I get the highest grade in a class.

When I play a game, I try to do the best I can.

It's important to win in order to impress other people.

When I was growing up, I always competed against my siblings, or
friends.

I only enjoy tasks that result in a winner and loser.

When I take part in a game I try to perform as well as I can and don't
worry about winning or losing.

Knowing how well others are performing a task affects my performance
by making me try to do better than them.

APPENDIX C

138

APPENDIX C

TASK KNOWLEDGE TEST

PART 1: Select the correct answer for each of the questions below. Make sure to
mark your answers ONLY on the computer form provided. PLEASE
DO NOT MAKE ANY MARKS ON THE TEST BOOK!!

1. 650 miles per hour represents which of the following?

a) - A non-threatening target.

b) A somewhat threatening target.

c) A very threatening target.

d) A target on the border between two threat levels.

2. 14 degrees of direction represents which of the following?

a) A non-threatening target.

b) A somewhat threatening target.

c) A very threatening target.

(1) A target on the border between two threat levels.

3. 50 meters represents which of the following?

a) A non-threatening target.

b) A somewhat threatening target.

c) A very threatening target.

(I) A target on the border between two threat levels.

4. Class 3 radar type represents which of the following?

a) A non-threatening target.

b) A somewhat threatening target.

c) A very threatening target.

d) A target on the border between two threat levels.

10.

139

1.5 Mhz represents which of the following?

a)
b)
C)
d)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.

0 degrees of angle represents which of the following?

a)
b)
C)
d)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.

175 miles for range represents which of the following?

a)
b)
C)
d)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.

15,000 foot altitude represents which of the following?

a)
b)
C)
d)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.

25 miles outside the corridor represents which of the following?

a)
b)
C)
d)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.

20 meters represents which of the following?

a)
b)
C)
d)

' A non-threatening target.

A somewhat threatening target.
A very threatening target.
A target on the border between two threat levels.

12.

13.

14.

15.

16.

140

Class 8 radar type represents which of the following?

a) A non-threatening target.
b) A somewhat threatening target.
c) A very threatening target.
(I) A target on the border between two threat levels.

.5 Mhz represents which of the following?

a) A non-threatening target.
b) A somewhat threatening target.
c) A very threatening target.
d) A target on the border between two threat levels.

300 miles per hour represents which of the following?

a) A non-threatening target.
b) A somewhat threatening target.
0) A very threatening target.
(I) A target on the border between two threat levels.

28 degrees of direction represents which of the following?

a) A non-threatening target.
b) A somewhat threatening target.
c) A very threatening target.
d) A target on the border between two threat levels.

-12 degrees of angle represents which of the following?

a) A non-threatening target.
b) A somewhat threatening target.
c) A very threatening target.
(I) A target on the border between two threat levels.

55 miles for range represents which of the following?

a) A non-threatening target.
b) A somewhat threatening target.
c) A very threatening target.
(I) A target on the border between two threat levels.

17.

18.

19.

20.

21.

141

27,500 foot altitude represents which of the following?

a)
b)
C)
d)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.

5 miles outside the corridor represents which of the following?

a)
b)
C)
d)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.

All else equal, which of the following is/are characteristic(s) of a threatening

target?

a)
b)
C)
d)
C)

High flying targets.

Military targets.

Targets with weather radar

2 of the above are characteristics of a threatening target.
3 of the above are characteristics of a threatening target.

All else equal, which of the following is/are characteristic(s) of a threatening

target?

a)
b)
C)
d)
C)

Targets that are high flying.

Targets with weather radar.

Targets that are fast and inside the traffic corridor.
Targets that are descending and close.

Targets that are large and descending.

All else equal, which of the following is/are characteristic(s) of a threatening

target?

a)
b)
C)
d)
C)

Targets that are large.

Targets with weather radar.

Targets that are fast and coming straight in.

Targets that are small and inside the traffic corridor.
Targets that are ascending and close.

22.

23.

24.

25.

142

Which of the following combinations represents a more threatening target?

a)
b)
C)
d)
C)

Weather radar and small targets.

High flying and inside the traffic corridor.

Fast and straight on targets.

Close and land radar targets.

Outside the traffic corridor and descending targets.

Which of the following combinations represents a more threatening target?

a)
b)
C)
d)
C)

Slow and land radar targets.

High flying and fast targets.

Descending and inside the traffic corridor targets.
Small targets with weapons radar.

Close and ascending targets.

Which of the following combinations represents a more threatening target?

a)
b)
C)
d)
C)

Slow and land radar targets.

High flying and fast targets.

Descending and inside the traffic corridor targets.
Inside the traffic corridor and low flying targets.
Close and descending targets.

Which of the following combinations represents a more threatening target?

a)
b)
C)
d)
C)

Slow and land radar targets.
High flying and fast targets.
Descending and inside the traffic corridor targets.
Outside the traffic corridor and low flying targets.
Close and ascending targets.

143

PART 2: For the following targets, make the appropriate decision regarding the
defensive posture which you should take. Mark your answers QNLX on
the computer form provided. PLEASE DO NOT MAKE ANY
MARKS ON THE TEST BOOKII

26. SPEED: 172 mph
ALTITUDE: 10,248 ft

SIZE: 10 m
ANGLE: -14 dgs
IFF: 1.3 Mhz

DIRECTION: 4 dgs

RADAR: Class 2

RANGE: 31 miles
CORRIDOR STATUS: 29 miles

If E”:

a) IGNORE
b) MONITOR
c) WARN

d) READY

e) DEFEND

27. SPEED: 321 mph
ALTITUDE: 26,605 ft

SIZE: 41 m
ANGLE: +9 dgs
IFF: .7 Mhz

DIRECTION: 21 dgs

RADAR: Class 4

RANGE: 108 miles
CORRIDOR STATUS: 19 miles

1CD":

a) IGNORE
b) MONITOR
c) WARN

d) READY

e) DEFEND

28.

29.

144

SPEED: 291 mph
ALTITUDE: 14,321 ft

SIZE: 21 m
ANGLE: -6 dgs
IFF: .7 Mhz

DIRECTION: 9 dgs

RADAR: Class 6

RANGE: 101 miles
CORRIDOR STATUS: 21 miles

ICU":

a) IGNORE
b) MONITOR
c) WARN

d) READY

e) DEFEND

SPEED: 591 mph
ALTITUDE: 14,016 ft

SIZE: 19 m
ANGLE: -6 dgs
IFF° 1.3 Mhz

DIRECTION: 9 dgs

RADAR: Class 7

RANGE: 43 miles
CORRIDOR STATUS: 11 miles

I: E”:

a) IGNORE
b) MONITOR
c) WARN

d) READY

e) DEFEND

30.

145

SPEED: 172 mph
ALTITUDE: 10,248 ft

SIZE: 14 m
ANGLE: -14 dgs
IFF: 1.6 Mhz

DIRECTION: 4 dgs

RADAR: Class 2

RANGE: 31 miles
CORRIDOR STATUS: 23 miles

ICE":

a) IGNORE
b) MONITOR
c) WARN

d) READY

e) DEFEND

APPENDIX D

146

APPENDIX D

Self-Efficacy Scale

Using the scale below indicate your level of agreement with the following items. These
items are intended to measure your confidence in performance the Naval Air Defense
Simulation. Do not answer how you think you are expected to answer. Answer in an
honest fashion.

10.

1 = Strongly Disagree

2 = Disagree

3 = Neither Agree nor Disagree
4 = Agree

5 = Strongly Agree

I feel confident in my ability to perform the Naval Air Defense
Simulation effectively.

I think I can eventually reach a high level of performance on the Naval
Air Defense Simulation.

1 am sure I can learn how to perform this task effectively in a relatively
short period of time.

I don't feel that I am as capable of performing the Naval Air Defense
Simulation as other people.

On average, other people are probably much more capable of performing
this task as I am.

I generally perform poorly on tasks like this.
I am sure that I can reach a high level of performance on this task.

It would take me a long time to learn how to perform this task
effectively.

I am not confident that I can perform this task successfully.

I doubt that my performance will be very adequate on the Naval Air
Defense Simulation.

APPENDIX E

147

APPENDIX E

Task Performance Inventory

Name:

 

ID#:

 

The following items are intended to measure various aspects of your task performance.
Please respond honestly and completely to all of the following items.

 

To maintain a performance level of at least 0.22 greater than my competition.

 

To maintain a performance level of no less than 0.22 lower than my competition.

 

To try to outperform my competition.

 

To maintain a performance level of at least 1.52.

 

To maintain a performance level of at least 1.08.

 

 

 

 

‘ To perform as well as possible.

 

With the above goal in mind, please respond to the following set of items using the
scale below.

5: Strongly Disagree

4: Disagree

3 = Neither Agree nor Disagree
2 = Agree

1 = Strongly Agree

2. It's hard to take this goal seriously.
3. It's unrealistic for me to expect to reach this goal.

4. It is quite likely that this goal may need to be revised, depending on how
things go.

148

_ 5. Quite frankly, I don't care if I achieve this goal or not.

_ 6. I am strongly committed to pursuing this goal.

_ 7. It wouldn't take much to make me abandon this goal.

_ 8. I think this goal is a good goal to shoot for.

9. Sometimes, even when an individual has been assigned a particular goal, he or

she may choose to work toward a different goal. Please indicate what your
personal goal is in this experiment. It may be the same or different from the
one that you were assigned. Also, it may be a specific average score (i.e., 1.3
points) or it may be to simply beat the other person you are completing the task

with.

My personal goal in this experiment is

 

With the above personal goal in mind, please respond to the following set of items
using the scale below.

10.

11.

12.

13.

14.

15.

16.

5 = Strongly Disagree
4 = Disagree
3 = Neither Agree nor Disagree
2 = Agree
1 = Strongly Agree
It's hard to take this goal seriously.
It's unrealistic for me to expect to reach this goal.

It is quite likely that this goal may need to be revised, depending on how
things go.

Quite frankly, I don't care if I achieve this goal or not.
1 am strongly committed to pursuing this goal.
It wouldn't take much to make me abandon this goal.

I think this goal is a good goal to shoot for.

17.

18.

149

Please divide 100 points to indicate the relative importance to you of:

a. completing a large number of targets

 

b. being as accurate as possible on each target

 

Past experience with this task has indicated that individuals use different
strategies in attempting to perform well. In the space below, please indicate the
strategy that you will, or are currently, using.

APPENDIX F

150

APPENDIX F

Perceptions of Situation Competitiveness

Using the scale below indicate your agreement with the following items. Do not
answer how you think you are expected to answer. Answer in an honest fashion.

10.

1 = Strongly Disagree

2 = Disagree

3 = Neither Agree nor Disagree

4

5 = Strongly Agree
It didn't matter to me how well I did on this task because no one else
knew how well I was doing.
I wasn't aware of how well others were performing on this task.

This situation was structured so that it was highly competitive.

Other participants were aware of how well I was performing on this
task.

I felt pressured to perform better than others on this task because they
knew how well I was doing.

It was clear that my performance was being directly compared to
another's.

I really had to work hard to do well on this task.
My performance on this task depended on things not under my control.
I was not sure what my goal in this study was.

I was concerned about what other people would think about my
performance on this task.

APPENDIX G

151

APPENDIX G

Post-Performance Attitudes

Using the scale below indicate your level of agreement with the following items. These
items are intended to measure your attitudes about performing the Naval Air Defense
Simulation. Do not answer how you think you are expected to answer. Answer in an
honest fashion.

1 = Strongly Disagree

2 = Disagree

3 = Neither Agree nor Disagree

4 = Agree

5 = Strongly Agree
1. I enjoyed participating in the Naval Air Defense Simulation.
2. I liked the task.
3. I didn't enjoy participating in this experiment.
4. If I had the opportunity, I would participate in this experiment again.
5. I wish that I hadn't signed up for this experiment.
6. After having completed the experiment, I felt satisfied.

7. I would continue working on this task for a longer period of time if
asked by the experimenter.

8. All in all, I thought this task was boring.

9. I would recommend participating in this experiment to my friends just
because I enjoyed it.

APPENDIX H

152

APPENDIX H

CONSENT FORM

NAVAL AIR DEFENSE SIMULATION

This study investigates the impact of various goal situations on performance on a
computer task. This session will last approximately 2 hours. You will be asked to
work on the Naval Air Defense Simulation and to complete a series of questionnaire
items.

Your participation in this study is strictly voluntary and you may refuse to answer any.
questions that you may find inappropriate without penalty. In addition, you can
discontinue the experiment if you feel it necessary to do so. However, in order to
receive credit you must FINISH the entire experiment. Your individual results in this
study will be STRICTLY CONFIDENTIAL. The experimenter will only report data in
an aggregate form. This procedure will ensure that no responses will be identified to
particular individuals. These aggregate results of the experiment will be available from
the experimenter.

If you have any questions or concerns following your participation in this study you
may contact Ron Landis at 353-9166.

I have read the consent form and choose to participate in this study:

NAME:

 

SIGNATURE:

 

DATE:

 

APPENDDC I

153

APPENDIX I

Protocols for Experimental Conditions

After individuals completed the various pre-task measures, they were told the
characteristics of the situation in which they would be working. The protocols for each
condition are presented below.

11' C .. {E'Efi ID 1211121103:

The experimenter said, ”Now that you have had an opportunity to perform this task, I
would like you to spend 1 hour working independently on it. Your goal is to maintain
an average score of at least 0.22 higher than your competition. I will come into the
room every 15 minutes to ask you to complete a brief questionnaire and to provide you
with feedback on your performance level relative to your competition and will do the
same for your competition. It is critical that you complete this task independently. As
a result, I am asking you to refrain from speaking to others as you complete the task.
If you talk during the experiment, you will forfeit your extra credit. If there aren't any
questions, you may begin.”

12' C .. [E G ICECEGI:

The experimenter said, ”Now that you have had an opportunity to perform this task, I
would like you to spend 1 hour working independently on it. Your goal is to maintain
an average score of no less than 0.22 lower than your competition. I will come into the
room every 15 minutes to ask you to complete a brief questionnaire and to provide you
with feedback on your performance level relative to your competition and will do the
same for your competition. It is critical that you complete this task independently. As
a result, I am asking you to refrain from speaking to others as you complete the task.

If you talk during the experiment, you will forfeit your extra credit. If there aren't any
questions, you may begin."

154

The experimenter said, "Now that you have had an opportunity to perform this task, I
would like you to spend 1 hour working independently on it. Your goal is to
outperform your competition. I will come into the room every 15 minutes to ask you
to complete a brief questionnaire and to provide you with feedback on your
performance level relative to your competition and will do the same for your
competition. It is critical that you complete this task independently. As a result, I am
asking you to refrain from speaking to others as you complete the task. If you talk
during the experiment, you will forfeit your extra credit. If there aren't any questions,
you may begin. "

II C .. {E‘Efi lG 1111121101:

The experimenter said, "Now that you have had an opportunity to perform this task, I
would like you to spend 1 hour working independently on it. Your goal is to achieve
an average performance level of 1.52. 1 will come into the room every 15 minutes to
ask you to complete a brief questionnaire and to provide you with feedback on your
performance level relative to the assigned goal. It is critical that you complete this task
independently. As a result, I am asking you to refrain from speaking to others as you
complete the task. If you talk during the experiment, you will forfeit your extra credit.
If there aren't any questions, you may begin. "

II S .. [E G lleCEGI:

The experimenter said, "Now that you have had an opportunity to perform this task, 1
would like you to spend 1 hour working independently on it. Your goal is to achieve
an average performance level of 1.08. I will come into the room every 15 minutes to
ask you to complete a brief questionnaire and to provide you with feedback on your
performance level relative to the assigned goal. It is critical that you complete this task
independently. As a result, I am asking you to refrain from speaking to others as you
complete the task. If you talk during the experiment, you will forfeit your extra credit.
If there aren't any questions, you may begin. "

155
W:

The experimenter said, ”Now that you have had an opportunity to perform this task, I
would like you to spend 1 hour working independently on it. Your goal is to do your
best on this task. I will come into the room every 15 minutes to ask you to complete a
brief questionnaire and to provide you with feedback on your performance level. It is
critical that you complete this task independently. As a result, I am asking you to
refrain from speaking to others as you complete the task. If you talk during the
experiment, you will forfeit your extra credit. If there aren't any questions, you may
begin. "

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