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University

This is to certify that the

dissertation entitled

SINGLED OUT: TASK AND SOCIAL IMPLICATIONS OF

PROVIDING INDIVIDUAL LEVEL PERFORMANCE FEEDBACK
IN TEAMS

presented by

CHRISTOPHER OLDEN LEE HOWARD PORTER

has been accepted towards fulfillment
of the requirements for

Ph.D. degree in Business Administration

W

/ I Major prbfegr
Date ”/13/0 /

MS U is an Affirmative Action/Equal Opportunity Institution 0-12771

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SINGLED OUT: TASK AND SOCIAL IMPLICATIONS OF PROVIDING
INDIVIDUAL LEVEL PERFORMANCE FEEDBACK IN TEAMS

By

Christopher Olden Lee Howard Porter

A DISSERTATION

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

DOCTOR OF PHILOSOPHY
Department of Management

2001

ABSTRACT

SINGLED OUT: TASK AND SOCIAL IMPLICATIONS OF PROVIDING
INDIVIDUAL LEVEL PERFORMANCE FEEDBACK IN TEAMS

By

Christopher Olden Lee Howard Porter

This study examined and compared predictions from several different theoretical
frameworks, all of which suggested that there were task and/or social implications of
singling out a member of a team and providing him or her with individual level
performance feedback. Of particular interest was 1) what are the task performance effects
on both those who directly receive individual level performance feedback and those
others who observe its provision and 2) what, if any, effects does providing individual
level performance feedback in teams have on team social outcomes?

The research methodology utilized undergraduate students who were arranged in
four-person teams and worked interdependently on a computerized decision-making task.
Results of the study indicate that the provision of individual level performance feedback
to a singled out member of the team has small, yet nevertheless important, positive task
performance effects on both those who directly receive the feedback and those who
merely observe the provision of the feedback. No one theoretical framework adequately
explained those effects. Finally, the results of this study indicate that singling out one
team member and provided with him or her with individual level performance feedback
had no negative effects on the social dynamics and functioning of teams therefore raising
doubts about the admonitions offered by a number of team scholars regarding the

detrimental effects of providing such feedback to individuals working in teams.

C0pyfight by
CHRISTOPHER O.L.H. PORTER
2001

This work is dedicated to the family and friends who supported me through all these
years of graduate school, especially my son, Nickolas O.L.H. Porter. Nickolas, you have
been and continue to be my inspiration. Throughout my doctoral program and especially

throughout the dissertation process you were constantly on my mind. You gave me the
strength and motivation to keep striving for my goals when the going got tough. I hope
that I, and whatever my accomplishments may be, provide the same inspiration and
encouragement for you.

iv

ACKNOWLEDGEMENTS

This dissertation would not be complete with a special thank you and
acknowledgement to Dan 11 gen, without whom I would have not even pursued this
particular degree. Dan not only inspired me but he also provided guidance to me over the
last several years. Moreover, he helped to make my time at Michigan State University a
true learning experience from beginning to end.

Also, I thank both Dan and John Hollenbeck for giving me the opportunity to
work closely with them in the Team Effectiveness Laboratory. Simply put, that
opportunity was an invaluable experience. Those of us who have and continue to work in
the laboratory do not say it often enough but we truly appreciate your time, expertise,
willingness to help us develop, and patience. Thank you so much.

Don Conlon and Kevin Ford were also invaluable members of my dissertation
committee that deserve mention. Just as important, they have both been good friends to
me during my time at MSU. Their guidance and support, both academically and
personally, has been and continues to be greatly appreciated.

Finally, Alison Barber, while not a member of my dissertation committee, was
key to my entering into the Department of Management. She introduced me to human
resource management and her ability to bring this area of study to life and her passion
about the field had a major influence on my developing goals and my academic choices.

I also want to thank to Aleksander Ellis, Stephen Humphrey, and Ann Appledom,
all of who helped me collect the data for this dissertation. I truly appreciate all the hours

they put into this project. Best wishes to all of you in your future endeavors.

TABLE OF CONTENTS

LIST OF TABLES ............................................................................................................. xi
List OF FIGURES ............................................................................................................. xii
CHAPTER 1: INTRODUCTION ........................................................................................ 1
The Provision of Performance Feedback in Teams ............................................................. 3
The Debate Regarding the Provision of Performance Feedback in Teams ......................... 4
The Importance of Individual Level Performance Feedback in Teams ............................... 8
Outline ................................................................................................................................ 12
CHAPTER 2: A REVIEW OF THE LITERATURE ON FEEDBACK
INTERVENTIONS IN TEAMS ........................................................................................ 14
Summary of Previous Literature Reviews on Feedback Interventions in Teams .............. 17
Recent Literature on Team Level Feedback Interventions ................................................ 24
Effects of Team Level Performance Feedback on Task Performance ................... 25
Effects of Team Level Performance Feedback on Social Outcomes ..................... 29

Conclusions on the Recent Work on the Provision of Team Level
Feedback ................................................................................................................ 3 1

Recent Literature on Individual Level Feedback Interventions in Teams ......................... 32

Effects of Individual Level Performance Feedback in Teams
on Task Performance ............................................................................................. 33

Effects of Individual Level Performance Feedback in Teams
on Social Outcomes ............................................................................................... 37

Conclusions on the Recent Work on the Provision of Individual Level

Feedback in Teams ................................................................................................ 38
General Conclusions Regarding the Effects of Feedback Intervention in Teams ............. 40
The Present Research and Theoretical Model Overview ................................................... 42

vi

CHAPTER 3: THE EFFECTS OF PROVIDING INDIVIDUAL LEVEL

PERFORMANCE FEEDBACK IN TEAMS ON TASK PERFORMANCE ................... 46
Effects of Directly Receiving Individual Level Performance Feedback
on Task Performance ......................................................................................................... 47
Hypothesis la ..................................................................................................................... 50
Hypothesis 1b ..................................................................................................................... 50
Hypothesis 2a ..................................................................................................................... 57
Hypothesis 2b ..................................................................................................................... 57
Effects of Observing the Provision of Individual Level Performance Feedback
on Task Performance ......................................................................................................... 58
An Overview of Vicarious Reinforcement Processes ........................................................ 59
Hypothesis 3 ....................................................................................................................... 62
CHAPTER 4: THE EFFECTS OF PROVIDING INDIVIDUAL LEVEL
PERFORMANCE FEEDBACK IN TEAMS ON SOCIAL OUTCOMES ....................... 63
Effects of Providing Individual Level Performance Feedback on Cohesion
and Potency in Teams ........................................................................................................ 65
Hypothesis 4 ....................................................................................................................... 69
Empirical Investigation ...................................................................................................... 69
CHAPTER 5: METHOD ................................................................................................... 72
Research Design ................................................................................................................. 72
Power Analysis .................................................................................................................. 72
General Task Overview ..................................................................................................... 74
Space Partitioning in MSU-DDD ............................................................................... 76
Bases and Sub-Platforms ............................................................................................ 78
Identifying and Engaging Tracks ............................................................................... 80
Sample ................................................................................................................................ 84

vii

Procedure ........................................................................................................................... 84

Goal Setting and Task Strategies ........................................................................... 86
Feedback Intervention ............................................................................................ 88
Measures ................................................................................................................ 89

Information Collected in the Laboratory During the
First Task and Second Tasks ...................................................................... 89

Information Collected in the Laboratory After the First Task-Before
the Experimental Manipulation and After the Second Task ...................... 92

Information Collected in the Laboratory After the First Task-After
the Experimental Manipulation .................................................................. 93

Information Collected in the Laboratory After the Second

Task Only ................................................................................................... 94
Analyses ............................................................................................................................. 94
CHAPTER 6: RESULTS ................................................................................................... 95
Manipulation Checks ....................................................................................................... 105
Hypotheses 1a and 1b ...................................................................................................... 107

Hypothesis la: Effects of Publicly Provided Individual Level Performance
Feedback on Direct Recipients’ Self and Task-Focused Attention ..................... 110

Hypothesis 1a: Effects of Publicly Provided Individual Level Performance
Feedback on Direct Recipients’ Task Performance ............................................. 111

Hypothesis 1b: Effects of Privately Provided Individual Level Performance

Feedback on Direct Recipients’ Self and Task-Focused Attention ..................... 117

Hypothesis 1b: Effects of Privately Provided Individual Level Performance

Feedback on Direct Recipients’ Task Performance ............................................. 117
Hypotheses 2a and 2b ...................................................................................................... 118

Hypothesis 2a: Effects of Negatively Framed Individual Level Performance
Feedback on Direct Recipients’ Self and Task-Focused Attention ..................... 121

viii

Hypothesis 2a: Effects of Negatively Framed Individual Level Performance
Feedback on Direct Recipients’ Task Performance ............................................. 122

Hypothesis 2b: Effects of Positively Framed Individual Level Performance

Feedback on Direct Recipients’ Self and Task-Focused Attention ..................... 122
Hypothesis 2b: Effects of Positively Framed Individual Level Performance
Feedback on Direct Recipients’ Task Performance ............................................. 123
Summary of Effects of the Feedback Interventions on Direct
Recipients’ Self- and Task-Focused Attention ................................................................ 123
Summary of Effects of the Feedback Interventions on Direct
Recipients’ Task Performance ......................................................................................... 124
Hypothesis 3 ..................................................................................................................... 124

Hypothesis 3: Effects of Publicly Provided Individual Level Performance
Feedback on Observers’ Self and Task-Focused Attention ................................. 126

Hypothesis 3: Effects of Publicly Provided Individual Level Performance

Feedback on Observers’ Task Performance ........................................................ 127
Supplemental Analyses .................................................................................................... 128

Supplemental Analyses: Wave Track Performance as the Dependent

Variable ................................................................................................................ 129

Supplemental Analyses: Reduced Sample ........................................................... 13 1
Hypotheses 4a, 4b, and 4c ................................................................................................ 136

Hypothesis 4: Effects of Feedback Interventions on Social
Comparisons in Teams ......................................................................................... 138

Hypothesis 4: Effects of Feedback Interventions on Team

Cohesion, Viability, and Potency ......................................................................... 138
Summary of Effects of the Feedback Interventions on
Team Social Outcomes .................................................................................................... 140
CHAPTER 7: DISCUSSION ........................................................................................... 144
Effects of Feedback Interventions on Self-Focused Attention ........................................ 147

ix

Effects on Direct Feedback Recipients ................................................................ 147

Effects on Observers ............................................................................................ 149
Effects of Feedback Interventions on Task-Focused Attention ....................................... 151
Effects on Direct Feedback Recipients ................................................................ 151
Effects on Observers ............................................................................................ 152
Effects of Feedback Interventions on Task Performance ................................................ 155
Effects on Direct Feedback Recipients ................................................................ 155
Effects on Observers ............................................................................................ 161
Effects of Feedback Interventions on Social Comparisons ............................................. 163
Effects of Feedback Interventions on Team Social Outcomes ........................................ 164
Study Limitations ............................................................................................................. 167
Summary of Findings Related to the Model .................................................................... 170
APPENDIX A. Discussion of Wave Targets and Goal Setting ....................................... 175
APPENDIX B. Feedback Intervention ............................................................................ 178
APPENDIX C. Team Member Questionnaire ................................................................. 180
REFERENCES ................................................................................................................ 192

LIST OF TABLES

Table 1: List of Study Hypotheses ..................................................................................... 70
Table 2: Study Procedure Tirneline ................................................................................... 90
Table 3: Confirmatory Factor Analysis Results for Self- and Task-Focus Items .............. 96
Table 4: Exploratory Factor Analysis Results for Social Comparison Items .................... 97
Table 5: Internal Reliabilities of Study Measures .............................................................. 99
Table 6: Aggregation Indices for Study’s Team Level Constructs .................................... 99

Table 7: Means, Standard Deviations, and Zero-order Correlations of Individual
Level Study Variables ...................................................................................................... 102

Table 8: Means, Standard Deviations, and Zero-order Correlations of Team Level Study
Variables .......................................................................................................................... 104

Table 9: Multiple Regression Effects of Individual Level Feedback Conditions on Self-
and Task-focused Attention ............................................................................................. 112

Table 10: Hierarchical Mediated Regression Effects of Individual Level Feedback
Conditions and Self- and Task-focused Attention on Individual Task Performance ...... 113

Table 11: Multiple Regression Effects of Individual Level Feedback Conditions on Social
Comparisons .................................................................................................................... 141

Table 12: Hierarchical Mediated Regression Effects of Individual Level Feedback
Conditions and Social Comparisons on Team Social Outcomes ..................................... 142

xi

LIST OF FIGURES

Figure 1. A Model of Team Performance .......................................................................... 11
Figure 2. A Model of Task Group Feedback Effects ......................................................... 18
Figure 3. A General Framework of the Effects of Feedback Interventions in Teams ....... 22

Figure 4. Effects of Individual Feedback in Teams on Task Performance and Social
Outcomes ........................................................................................................................... 43

Figure 5. The MSU-DDD Task Screen .............................................................................. 77

xii

CHAPTER ONE: INTRODUCTION

The changing nature of work was recently noted in an insightfiil popular press
article entitled, “The End of the Job” by William Bridges. While Bridges (1994) wrote
specifically about the shift in emphasis on work scheduled around jobs to work scheduled
around tasks that need to be completed, there are a number of ways in which the nature of
work has dramatically changed in recent years. For example, a number of authors have
discussed how work roles have evolved from static, structured, and prescribed roles to
those that can be better characterized as having a more social, unstructured, and emergent
nature (Ilgen & Hollenbeck, 1991; Murphy & Jackson, 1999). Yet another recent change
that manifests itself at higher levels of organizational functioning is the changing
structure of organizations. Mohrman and Cohen (1995) discussed the changing forms of
organizations from ones in which people are connected through boxes and lines in a
hierarchical fashion to ones that are flatter, characterized by more “connectedness,” and
in which collectives of individuals perform work rather than individuals alone. Clearly,
organizational scholars’ and practitioners’ thinking about organizations has evolved
tremendously in recent years from lower level phenomena such as the extent to which
work is structured around jobs to higher level phenomena such as the structure of
organizations themselves.

One of the more prevalent recent changes noted by a number of organizational
scholars (e. g., Applebaum & Blatt, 1994; Cohen & Bailey, 1997; Gordon, 1992; Lawler,
Mohrman, & Ledford, 1992; Mohrman & Cohen, 1995; O’Leary-Kelly, 1998) is the
increasing use of groups and teams by contemporary work organizations. Teams can be

generally defined as groups of highly interdependent individuals working towards a

common goal (Sundstrom, De Meuse, & Futrell, 1990) and Reilly and McGourty (1997)
went so far as to suggest that the move to team-based work structures is perhaps the most
dramatic change in recent American business. In recent years, organizations have
increasingly relied on teams and team-based work structures for organizing the way in
which work is completed. Gordon (1992), for instance, reported that 82% of companies
with 100 or more employees reported using some form of team-based work units. As one
surveys all facets of work organizations, it becomes clear that much of the work
traditionally done by individuals working alone is now being done by individuals
working in groups and teams. As such, teams have and continue to be an important issue
for organizational practitioners and scholars alike.

The implications of the shift to team-based work arguably have the most impact
on human resource management scholars and practitioners whose interventions have
historically been aimed at levels of analysis lower than the team level. For example, most
if not all, human resource practices (e. g., recruitment, selection, and compensation) are
developed around an individual job via job analysis. Employees are recruited and
selected based on individual qualifications and fit with prospective employers.
Traditionally, compensation has been focused at the individual employee level. This is
the case for almost all human resource management practices yielding quite a dilemma
for human resource management practitioners.

Recently, organizational scholars have responded by shifting focus in
organizations to group and team levels. Researchers (e. g., Campion, Medsker, & Higgs,
1993; Campion, Papper, & Medsker, 1996; Cannon-Bowers, Tannenbaum, Salas, &

Volpe, 1995) have proposed team-based training interventions. Further, a number of

researchers have attempted to explore the impact of compensation systems designed to
reward employees at the team level (see DeMatteo, Eby, & Sundstrom, 1998 for a
review). Indeed, a survey of the current literature suggests that human resource
management scholars have begun to develop theories that better embrace today’s
organizations and their new forms (Ferris, Hochwater, Buckley, Harrell-Cook, & Frink,
1999). As it relates to the current state of knowledge regarding the use of teams, there is
still however quite an amount of work that must be done if organizational scholars and
practitioners hope to better close the gap between their recent popularity and
understanding of how to best utilize human resource management interventions with
those working in teams.

One particularly common human resource management intervention that has yet
to receive adequate attention in the context of the shift to team-based work structures is
the provision of performance feedback. Feedback can be generally defined as the process
of communicating information regarding the results and outcomes of actions or behaviors
(Taylor, Fisher, & Ilgen, 1984). Interestingly, little theoretical and empirical work has
been devoted to understanding the use and effectiveness of providing performance
feedback to those working in teams. This is unfortunate given that the provision of
performance feedback is likely to be critical for influencing team effectiveness (Campion
et al., 1993; O’Leary-Kelly, 1998; Sundstrom et al., 1990).

The Provision of Performance Feedbagkfin Teams

Despite a long history of research on the subject, debate still exists surrounding

the effectiveness of feedback interventions in influencing employee behavior. Kluger &

DeNisi (1996), in a meta-analytic investigation of the topic, found that one-third of all

feedback interventions have a negative effect on performance. This finding is particularly
interesting in that it undermines a commonly held assumption—that performance
feedback leads to increased performance. Despite this finding, feedback remains an
integral management tool (Barley, Northcraft, Lee, & Lituchy, 1990) that is, more often
than not, thought to enhance work performance. The changing nature of work, in
particular the shift from individuals to teams as the basic work unit, has presented an
additional layer of complexity to the uncertainty surrounding the effectiveness of
feedback interventions in enhancing work performance (Barr & Conlon, 1994; Hinsz,
Tindale, & Vollrath, 1997;Nad1er, 1979; O’Leary-Kelly, 1998). The proposed study is an
attempt to resolve some of this ambiguity. '

Whatever is understood regarding the effects of feedback in general, less is
understood regarding the effects of feedback in teams (McIntyre & Salas, 1995) despite
widespread acknowledgement by many scholars that feedback interventions are
important, if not critical to successful team development (Kozlowski, Gully, McHugh,
Salas, & Cannon-Bowers, 1996; Kozlowski, Gully, Nason, & Smith, 1999; Sundstrom et
al., 1990). A paucity of empirical work in this area is unsettling given the frequency in
which teams can be found in today’s workplace. Given the fi'equency in which teams are
now being relied upon to meet organizational goals, there is clearly a need to better
understand the effects of feedback interventions in groups and teams.

The Debate Regarding the Provision of Performance Feedback in Teams

Perhaps the most interesting debate regarding the use of feedback interventions in

teams concerns the level at which the performance feedback should be provided. Nadler

(1979), one of the first scholars to identify the need for increased understanding regarding

the role of feedback on group (or team) functioning, proposed three types, or levels, of
feedback that could be presented to those working in organizational contexts: feedback
provided at the individual level to individuals working alone, feedback provided at the
group level to individuals working in the context of a group, and feedback provided at the
individual level to individuals working in the context of a group. Nadler further suggested
that feedback received by individuals working alone (i.e., non-social settings) may be
very different from feedback received by individuals working in the context of a group.

Feedback provided at the individual level to individuals working alone has been
the most often explored type of feedback intervention in the organizational literature
(Conlon & Barr, 1989; Pritchard, Jones, Roth, Stuebing, & Ekeberg, 1988). Such
feedback entails simply providing information to a single employee about his or her
performance. As such, individual level performance feedback of this nature is devoid of
intervening social factors (Nadler, 1979).

Feedback at the group level to individuals working in the context of a group
entails providing aggregated feedback to a group of individuals who perform as a unit.
Such feedback provides information about the result of the joint performances in the
group (Conlon & Barr, 1989). Providing group level performance feedback is
increasingly becoming commonplace in work organizations where individuals are called
upon to work in groups and teams. Self-directed work teams and quality circles are
examples in which the provision of group or team level feedback is common.

Finally, feedback provided at the individual level to individuals working in the
context of a group entails providing information to an individual about only his or her

performance when that individual is working in a group or team setting. In this case,

information may or may not be given about the aggregate performance of the team unit.
Such feedback may be provided when the individuals work more independently as is
often the case in work groups but it can also be provided when the individuals work
interdependently as is the case of work teams. It should be noted that these latter two
types of feedback (i.e., individual level performance feedback provided in the context of
a group and group level feedback provided to a group) both include intervening social
factors (Nadler, 1979).

With the increased use of team-based work structures, both the provision of
performance feedback at the team level and performance feedback at the individual level
in the context of a team have the potential to become increasingly important interventions
for influencing team effectiveness and performance in contemporary work organizations
(DeNisi, 2000). To date, both are under-researched by scholars (McIntyre & Salas, 1995).
This is especially the case as it concerns the provision of individual level performance
feedback to those working in the context of a group or team. The lack of research on the
effects of providing individual level performance feedback to such individuals may be
due, in part, to the common recommendation by some scholars that individual level
performance feedback not be provided to those working in groups and teams (e. g., Reilly
& McGourty, 1998; Smither, 1998).

While most team scholars agree that performance feedback should be provided at
the team level, there is disagreement regarding whether or not performance feedback
should be provided about individual team member performance (i.e., individual level
performance feedback). Some scholars suggest that feedback provided to those working

in teams should be provided only in aggregate form (i.e., team level performance

feedback). In other words, many scholars (e. g., Smither, 1998) suggest that in teams the
only feedback provided should be feedback regarding how the team as a whole has
performed. Recommendations against the use of individual level performance feedback
in teams appear to be based on the belief that individual level feedback will have
detrimental effects on team social processes (e. g., coordination, cooperation, social
attraction) and team outcomes (e. g., cohesion). On the other hand, other scholars (e.g.,
Brannick & Prince, 1997; DeNisi, 2000) suggest that for feedback interventions to be
successful in increasing team effectiveness, the feedback should be provided at both the
team and individual levels.

It should be noted, however, that little to no empirical research has demonstrated
the negative effects of individual level performance feedback on social processes and
outcomes in teams. Rather, these recommendations are based wholly on anecdotal
evidence. Unfortunately, anecdotal evidence of this nature is insufficient in a number of
ways, most important of which is it provides little help to those attempting to further
theory and practice as it relates to the influence of feedback interventions on team
performance and effectiveness. As such, the extant literature that suggests that there are
negative consequences to providing individual level performance feedback to those
working in teams is, at best, of limited utility. Coupled with the ever-increasing
importance of teams in today’s work organizations and the need to better understand how
to best train, develop, utilize, and maintain effective teams, the state of knowledge

regarding the provision of individual level feedback to teams is clearly troublesome.

The Importance of IndividualLevel Performance Feedbfl in T ga_m_s

There are several reasons why the provision of individual level feedback to those
working in teams is both practically necessary and theoretically interesting despite
arguments to the contrary. First, employees have a tendency to want to know how they
are performing (DeNisi & Kluger, 2000; Kavanagh, 1997, Taylor et al., 1984). The fact is
that oftentimes employees expect and, in some cases, seek out some sort of feedback
about how they are performing. There is simply no reason to believe that working in a
team makes feedback about individual performance any less important to individual
performers.

Second, many problems with team performance are the result of individual
performances. There is little question that in most cases the performance of a team is a
function of some combination of individual team member contributions. As such,
feedback at the individual level may be necessary but not sufficient for increasing the
performance of the team as a whole.

Third, team level performance feedback is not likely to have the motivating and
informational effects that individual level performance feedback may have on individuals
in a team (Conlon & Barr, 1989). Performance feedback provided at the team level
usually is not aimed at any particular individual team member. As such, individual team
members may not accept personal responsibility for team level feedback. Indeed, some
empirical work has shown increased levels of social loafing among those working in
teams that have been provided team level feedback absent of any accompanying
individual level feedback (Latane, Williams, & Harkins, 1979; Williams, Harkins, &

Latane, 1981). Moreover, individual team members may be less likely to correctly

associate their individual behaviors with the feedback the team receives on its aggregate
performance. Therefore, failure to provide individual level performance feedback to those
working in teams may increase the probability that individual team members continue
displaying inappropriate behaviors when told that overall the team is performing well.
Similarly, failure to provide individual level performance feedback may increase the
probability that individual team members may discontinue displaying appropriate
behaviors when told that overall the team is performing poorly.

Finally, little is known about the implications of providing individual level
performance feedback in social contexts such as teams. A number of authors have noted
that most of the feedback literature deals with individuals working alone (Conlon & Barr,
1989; Pritchard et al., 1988). This state of affairs is unfortunate considering that the
feedback literature has typically neglected the role of the feedback context on the effects
of feedback interventions. Indeed, scholars have noted the lack of attention given to the
context in which feedback and performance appraisals take place (Bretz, Milkovich, &
Read, 1992; Waldman, 1997). Conlon & Barr (1989) suggested that the context becomes
more social as individuals become more interdependent with others, interact with others,
or are able to make comparisons against the feedback that others receive. When
individuals working in teams are provided with individual level performance feedback,
this is the just the sort of context that is created. As a result of being in such a social
context, several socially mediated processes may occur when individual level feedback is
provided to teams. These processes and their effects on individuals in teams have yet to

receive adequate theoretical and empirical attention.

This study seeks to fill a void in the empirical literature regarding the provision of
individual level performance feedback to those working in teams. In particular, it seeks to
determine whether providing individual level performance feedback yields benefits to
teams in terms of individual performance and at what social costs? In other words, are the
benefits, if any, that result from providing individual level performance feedback to those
working in teams outweighed by the detrimental effects that may result when individual
team members are provided with information about how they or the others with whom
they are interdependent have individually performed?

Figure 1 depicts a model of team performance that, while oversimplifying the
complexities of team performance, nevertheless brings an important issue to bear, namely
the importance of individual level performance in team performance. As can be seen in
the model, individual level performance has a direct effect on the performance of a team.
Accordingly, attempts to improve the effectiveness of teams must address performance at
the individual, team member level. It must be remembered that teams do not actually do
anything but rather it is the individuals in the team that do GBrannick & Prince, 1997;
Zalesny, Salas, & Prince, 1995) and thus attempts to influence team performance must
address individual team member performance as these individual performances are a
necessary component of successful team performance. Dickinson and McIntyre (1997)
stated that to improve team performance, one must focus attention on individual
performance. As such, feedback interventions directed at individuals working in teams,
represent no less of an important type of intervention for increasing team effectiveness

than feedback interventions directed at a team as a whole.

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11

Indeed, individual level performance feedback would seem to be more effective in
directly influencing individual performance (N adler, 1979). In fact, Brannick and Prince
(1997) stated that for teams to become effective, it is likely that both individual and team
level feedback must be provided. Given both the informational and motivational
functions that feedback has long been thought to serve (Ilgen, Fisher, & Taylor, 1979), it
is likely that feedback interventions directed towards individuals in teams will have at
least some positive effects on the individual feedback recipient’s performance, other team
members who observe the provision of the feedback, and thus the performance of the
team as a whole.

In this study, I attempt to determine the consequences of providing individual
level feedback in teams. Specifically, I examine the effects of receiving individual level
performance feedback in a team context on both the direct feedback recipient and those
who observe the provision of such feedback to another team member regarding his or her
performance. I address two distinct, but nevertheless, related research questions regarding
both those who directly receive performance feedback and those that observe a team
member receive performance feedback: 1) can both feedback recipients and observers
experience performance improvements as a result of providing individual level
performance feedback in teams and 2) what, if any, effects does providing individual
level performance feedback in teams have on team social outcomes?
am

As a first step in exploring these research questions, the next chapter provides a
review of the extant literature on feedback in teams. This review will serve two purposes.

First, the review will make apparent how little is currently known regarding the effects of

12

feedback in teams in general, but specifically, how little is known regarding the social
and task performance implications of providing individual level feedback in teams.
Second, the review will provide a framework from which the following discussion of the
effects of individual level feedback in teams will be based. Later, I develop explicit
hypotheses regarding the potential effects that both being directly provided with and
observing the provision of individual level performance feedback in teams will have on
team members’ task performance. Chapter Three discusses the performance
improvements that are likely to occur among individuals who are provided with
performance feedback in a team context and could potentially occur among team
members who are privy to the provision of individual level performance feedback to
others in their team. Thus, while previous research has emphasized the direct effects that
may result from receiving performance feedback, I place specific emphasis on both the
effects that may result from the direct experience of receiving feedback on one’s own
performance in addition to the effects that may result from the indirect experience of
observing another individual receive feedback on his or her performance. Chapter Four
discusses the effects that providing individual level performance feedback may have on
social outcomes in teams. Chapter Five describes the research method that is used to test
the hypotheses developed in Chapters Three and Four while Chapter Six reports the
results of the tests of the study’s hypotheses. Finally, Chapter Seven discusses, more

generally, the findings of the study and the study’s limitations.

13

CHAPTER TWO: A REVIEW OF THE LITERATURE ON FEEDBACK
INTERVENTIONS IN TEAMS

While feedback in teams can be provided at the team level, at the individual level,
or both (N adler, 1979), as mentioned in the previous chapter, researchers have
overwhelmingly suggested that the feedback provided to those working in teams should
only be manifested at the team level. Such recommendations are often made despite a
lack of research evidence that actually demonstrates that providing individual level
performance feedback has detrimental effects on those individuals working in teams and
teams’ social functioning. Presently, researchers have failed to systematically investigate
the effects of both team level an_d individual level feedback in teams (Conlon & Barr,
1989), thus the current state of affairs raises the possibility that the provision of
individual level feedback to those working in teams may represent an effective yet
underutilized leverage point for increasing team effectiveness.

The study proposed here is an attempt to fill this void in the current state of
knowledge regarding feedback interventions in teams. Specifically, I seek to determine
what, if any, are the effects of providing individual level performance feedback in teams?
Several types of outcomes are of particular interest. Clearly, performance improvements
are of primary interest as it is often the goal of feedback interventions to improve
employee performance (Kluger & DeNisi, 1996). As such, this study examines the effects
of providing individual level performance feedback in teams on task performance (i.e., a
behavioral outcome). However, as recently noted by Atwater, Waldman, Atwater, and
Cartier (2000), performance improvements are not the only potential outcomes of

feedback interventions. Social outcomes represent yet another particular type of outcome

14

that is also of interest here considering the social context in which the provision of
individual level performance feedback in teams presents. Thus, the approach taken here is
similar to that of Taylor et a1. (1984) in that it recognizes the importance of both social
(what they refer to as affective) and behavioral reactions to feedback. Moreover, this
approach is also consistent with recent calls from organizational scholars to explore a
broad range of outcomes including cognitive, affective, and behavioral reactions which
are often associated with employee developmental activities like performance feedback
(Kraiger, 1999; Kraiger, Ford, & Salas, 1993).

While there is currently some debate regarding the general effectiveness of
providing performance feedback in organizations (e. g., Kluger & DeNisi, 1996), in this
paper, I propose that individual level feedback interventions in teams should affect the
subsequent task performance of the direct recipient of the feedback and those other team
members who are observers of both the performance and the performance feedback that
another team member has received. In addition, given the concerns that some scholars
have raised regarding the provision of individual level performance feedback on team
social outcomes, in this study, I also explore to what extent providing such feedback has
on social dynamics and functioning in teams.

In accomplishing this end, the next several sections of the chapter provide a
review of the extant literature on feedback interventions in teams. It is important,
however, to note the boundaries of the literature review before proceeding. Similar to
others (e. g., Kluger & DeNisi, 1996), of particular concern here are feedback
interventions aimed towards specific persons or groups for the explicit purpose of

influencing or, more specifically, improving performance. However, unlike Kluger and

15

DeNisi (1996), who exclude research on interventions that include self-generated and
computer-generated feedback (e.g., feedback that comes from the actual task), the
following review excludes research on self- generated feedback interventions while
intentionally including research on computer-generated and other types of task-generated
feedback. Research on this latter type of feedback intervention (i.e., that which comes
from the task) is considered as both important and relevant here given recent advances in
workplace technology that allow employees to gain knowledge of the results of their
performance without reliance on some outsider but rather from the task itself. It is thus
becoming more commonplace for employees to rely on their work tasks for performance
feedback (e. g., consider the use of rejection rates or hourly output by self-managed,
autonomous manufacturing teams).

In addition, the review excludes research on feedback directed specifically
towards addressing interpersonal group processes (e. g., McLeod, Liker, & Lobel, 1992).
It is recognized that interpersonal process feedback provided to groups and teams may
indirectly impact group and team task performance, however, it is not the aim of such
feedback to m impact task performance. I focus only on task performance feedback
and its direct and indirect effects on individual and team outcomes as task performance
feedback is thought to have direct effects on task performance. The boundary
specification of limiting my focus to task performance feedback is consistent with
recommendations by Shea and Guzzo (1987) who advised that efforts towards creating
and maintaining effective groups and teams should focus primarily on task-focused
interventions rather than interpersonally-focused interventions, the latter of which

generally have an uninspiring record as it relates to improving task performance. It

16

should be noted, however, that the review does not exclude research on process related
task feedback (i.e., that which provides information regarding how the task is done) (see
Schein, 1987 for an elaboration on task process versus interpersonal process
interventions).
Summary of Previous Literature Reviews on Feedback Interventions in Teams

Nadler (1979) provided the first published review of the literature on feedback in
groups in an attempt to solidify the amassed knowledge in an area he believed was
fragmented and in desperate need of integration. From this review, he drew several
conclusions. Nadler (1979) noted that there was mixed evidence that feedback in groups
can influence behavior through its motivating effects, cueing effects, or both and firrther
proposed a number of possible factors that may account for the variations he found across
studies. Of these factors, Nadler suggested that the aggregation level of the feedback in
addition to the nature of the team’s task may influence whether the feedback has its
desired effects on groups. He further concluded from his review that goal setting (i.e., the
process of using feedback) works in tandem with the feedback itself to alter groups’
performance. In addition, he concluded that individual differences moderate the effects of
feedback in teams as they do the effects of feedback to individuals working alone.
Interestingly, he also suggested that the evaluative information that is often a component
of feedback, while potentially increasing performance and functioning, could also
decrease performance, increase defensiveness, or increase negative attributions. Nadler’s
conclusions are summarized in Figure 2.

The most recent review of the literature on feedback interventions in groups and

teams was provided by Conlon and Barr (1989). In their review, these authors explored a

17

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number of social phenomena likely to occur when feedback is provided to those working
in social contexts on interdependent tasks and argued that these phenomena often work to
obscure the reliability, or consistency, of the effects of such feedback. First, they
suggested that aggregated team level feedback may have a detrimental effect on
individual performance as individual performers are likely to have a difficult time
separating out how they performed as an individual when only provided information
regarding how the team as a whole has performed. Simply stated, they suggested that
information about the performance of the team may be misleading for individual team
members who use such information for determining how well they are performing. They
further proposed that individual feedback may provide more accurate information about
individuals’ personal actions. Related to the informational problems associated with team
level feedback, Conlon and Barr (1989) also noted that team level feedback may be less
motivating than individual level feedback. Specifically, they cited research suggesting
that aggregated feedback increases the likelihood of social loafing (i.e., the tendency for
individuals to reduce their individual efforts when performing as part of a group rather
than by themselves, Latane, Williams, & Harkins, 1979) among individuals working in
teams and groups. While these authors did not discourage the use of team level feedback,
they did however suggest that social loafing may be reduced by making individual team
members’ inputs more visible.

Conlon and Barr (1989) also proposed that the level of feedback provided should
be determined, in part, by the nature of the team’s task. Using Steiner’s (1972) typology
of group or team tasks (conjunctive, disjunctive, additive, and discretionary), they

suggested that team level feedback may be most effective for those working on

19

conjunctive, additive, and discretionary tasks while individual level feedback may be
most effective for those working on disjunctive tasks. The authors reasoned that when
provided with aggregated feedback, those working on conjunctive tasks should all put
forth effort since members would not know if they or some other team member was the
lowest performing team member who therefore provided the basis for the team’s
performance. With additive and discretionary tasks, aggregated feedback should
effectively motivate and direct behavior to the extent to which individual performance is
captured in the aggregated team score. On the other hand, since the team’s performance is
determined by the best performing team member on disjunctive tasks, the authors
reasoned that aggregated feedback would be likely to encourage social loafing among
poor performers especially when poor performers know that the team’s score is not
dependent on their performance. Unfortunately, Conlon and Barr (1989) provided no data
to support their propositions.

Of particular relevance to the present study, Conlon and Barr (1989) also
proposed that there are two socially mediated outcomes that occur when individual level
feedback is provided in groups and teams. Specifically, they first suggested that when
team members have information by way of individual level performance feedback
regarding each other’s individual performances, they may use such information to
classify themselves into majority and minority subgroups, or positions, in the team (what
the authors refer to as social influence). The authors went on to cite an example from a
mining study in which, based on information about the frequency in which individuals
engaged in job switching, work group members classified each other as “switchers” or

“non-switchers.” The authors suggested that publicly provided individual level

20

performance feedback can have negative social effects in teams when team members use
it to put each other into subgroups that have the potential for creating greater social
distance among the team as a whole.

Second, Conlon and Barr (1989) proposed that when individual level performance
feedback is provided to those in teams, it creates an opportunity for team members to
make social comparisons with others in their team. In other words, when individual team
members are aware of the feedback each other receives, as is the case when individual
level performance feedback is provided publicly to those working in teams, team
members can evaluate the feedback they receive relative to that received by others.

Clearly, the review by Conlon and Barr (1989) suggested that the provision of
individual level performance feedback is not only important to, but can also have a
significant impact on, team functioning. Their review highlighted two socially mediated
outcomes (i.e., social influence and social comparisons) which the authors argued are
important determinants of the effects of individual level feedback in teams.
Unfortunately, as the following review reveals, little theoretical and empirical work has
appeared in recent years that has significantly added to our knowledge about the general
effectiveness of feedback interventions in teams and, more important to the present study,
individual level performance feedback interventions in teams.

Figure 3 provides a general model of the effects of feedback interventions in
teams that serves two purposes. First, the model presents a simple framework for
understanding the effects of feedback in teams. As the model highlights, and also
consistent with Nadler (1979), there are two types of feedback interventions that can be

provided to those working in teams—team level performance feedback and individual

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level performance feedback. As the model firrther suggests, it is through socially
mediated processes that both team and individual level performance feedback have an
influence on task and social outcomes in teams. The second purpose of the model is to
provide an organizing framework for the following review of the literature on feedback in
teams that has appeared since Conlon and Barr’s (1989) review of the literature.
Specifically, I discuss the effects of both team level and individual level performance
feedback interventions on task performance and social outcomes in teams. Moreover,
when possible, the socially mediated processes through which both team and individual
level performance feedback interventions exert their effects will be highlighted and
discussed.

The next several sections of the chapter first discuss previous research regarding
the provision of team level performance feedback to those working in groups and teams,
first on task performance and then on social outcomes. While the effects of providing
individual level performance feedback in teams is of particular interest in the proposed
study, the review of the empirical findings regarding the provision of team level
performance feedback serves several purposes including demonstrating how little is
actually known regarding feedback interventions in teams. Perhaps more important, this
review also highlights several of the shortcomings of providing only team level
performance feedback to those working in teams.

The provision of individual level performance feedback to those working in teams
has already been suggested as having the potential to overcome several of these
shortcomings. Following the discussion of team level performance feedback interventions

in teams and groups, I move away from this area and focus specifically on the extant

23

literature on the effects of providing individual level performance feedback in teams on
both task and social outcomes. From this review, several themes will emerge regarding
the provision of individual level feedback in teams. In addition, the review will point to
several questions regarding the effects of providing individual level feedback to those
working in teams. These questions are further addressed and an empirical investigation
that sought to explore the effects of individual level performance feedback in teams will
be presented in later chapters.
Recent Literature on Team Level Feedbacic Intervention_s

Both Nadler (1979) and Conlon and Barr (1989) concluded that the empirical
research to date has not been altogether clear with regard to the effects of team, or group
level performance feedback on performance. Nevertheless, some recent theoretical and
empirical work has emerged since Conlon and Barr’s (1989) more recent review that may
serve to provide some insight regarding the performance implications of providing group,
or team, level performance feedback to those working in teams. As will be seen in the
following review of this literature, while performance effects have been of primary
interest to those studying the effects of group level feedback in teams, there is some
recent evidence that seems to suggest that the provision of group level feedback in teams
may also have some important social implications in teams as well. These effects will be
discussed following the discussion of the task performance implications of group level
feedback in teams. Similarly, recent work may also help promote understanding the

social effects of providing group level feedback in teams.

24

Effects of Team Level Performance Feedback on Talc Performance

Noting that most of the empirical work on the effects of feedback interventions on
performance have been primarily concerned with individual performance, Pritchard et a1.
(1988) sought to explore the effects of feedback on group performance. These researchers
specifically examined the influence of group level feedback, group goal setting, and
group incentives on group productivity as measured using their ProMES methodology.

ProMES (Pritchard, Jones, Roth, Stuebing, & Ekeberg, 1986; 1987) is rooted in
the theoretical perspective on work roles as outlined in the Naylor, Pritchard, and Ilgen
(1980) model of organizational behavior and ProMES extends this perspective from
individuals to organizational sections (Pritchard et al., 1988). ProMES is also based, in
part, on the work of Tuttle and his colleagues (e. g., Tuttle, 1981; Tuttle & Weaver,
1986a; 1986b; Tuttle, Wilkerson, & Matthews, 1985) on productivity measurement.
Simply stated, the ProMES methodology is based on four steps. First, one must identify
products, or objectives, that must be accomplished by the groups. Second, indicators of
the products must be identified. That is, indicators must be identified that represent the
extent to which the group or team has produced units that reflect the products or
objectives. Third, contingencies are established that represent the relationship between
the amount of the indicators and the effectiveness represented by the indicator. In other
words, the level of evaluation of outcomes is dependent, or contingent, on the amount of
those outcomes (Naylor et al., 1980). Finally, after agreement is reached regarding the
products, then indicators, and then the relevant contingencies, the entire system is put

together by collecting the indicator data for a specified time period, assigning

25

effectiveness scores for each indicator based on the contingencies, and sending back
performance data in terms of effectiveness to the groups.

After the creation of the ProMES system for five Air Force base units, Pritchard
et a1. (1988) first measured productivity for an eight to nine month period to establish
baseline productivity scores for each unit. Next, they delivered group level feedback for
five months, added goal setting to the feedback for an additional five months, and finally
added incentives to the feedback and goal setting for an additional five month period.
Overall, the results indicated a dramatic increase in productivity over the course of the
study. Specifically, the researchers reported a 50% increase in productivity over the
baseline period with the addition of the group level feedback intervention, a 75% increase
over the baseline period for the feedback with goal setting intervention, and a 76%
increase over the baseline period for the feedback, goal setting, and incentive
intervention.

In a similar investigation, Jones, Buerkle, Hall, Rupp, and Matt (1993) used the
ProMES methodology in a field experiment to examine the effects of productivity
feedback on group productivity in a manufacturing company. However, unlike Pritchard
et a1. (1988) who examined groups as the unit of analysis, Jones et 31. examined the
effects of providing aggregated feedback to an entire department in the company.

Specifically, after measuring baseline productivity over thirteen months the
authors examined changes in productivity over time in a manufacturing department that
received feedback compared to a buying department that received no such feedback. The

authors hypothesized and found support for a significant improvement in productivity in

26

the manufacturing department compared to no such improvement in the buying
department.

Goltz, Citera, Jensen, F avero, and Komaki (1989), while primarily interested in
the effects of individual level performance feedback over and above those of group level
performance feedback examined the effects of providing group level feedback after a
baseline period of no feedback and before the provision of individual level performance
feedback. The authors reported that providing group level feedback to employees did in
fact result in significant increases in the employees’ product handling.

Tinsdale (1989) compared the effects of both group level outcome feedback
provided to those working in groups to individual level outcome feedback to individuals
working alone on a decision-making task involving promotion decisions in a hypothetical
company. Participants worked either individually or in groups where consensus was
required on the decision-making task and received either total, partial, or no feedback.
Participants in the total feedback condition received feedback on how each of their
decisions compared to those made by an assessment center regardless of whether they
decided to promote the candidate. Those in the partial feedback condition received
feedback on how each of their decisions compared to those made by an assessment center
only when the participants made the decision to promote the candidate. Those in the no
feedback condition received no information concerning the correctness of their decisions
regardless of the nature (i.e., promote or not promote) of those decisions.

The results of the study indicated that performance generally increased over the
decision-making trials for both groups and individuals and that groups performed as well

as individuals. However, only those participants working in groups that received total

27

feedback experienced the most consistent performance improvements over individuals.
Moreover, groups receiving total feedback experienced the most significant performance
improvements over the trials while receiving partial feedback led to the most significant
performance improvements over the trials for those working individually.

Tinsdale (1989) concluded that groups do perform differently than individuals
under various feedback conditions and suggested that groups can socially process
performance information (e. g., using majority decision rules) in ways that individuals
cannot. It was further concluded that such social processing may allow groups to better
utilize additional feedback effectively.

Using data from forty—one railway crews, Pearson (1991) examined the effects of
receiving group level performance feedback on productivity. He found that crews that
received group level performance feedback had higher levels of productivity compared to
crews that received no such feedback.

Mesch, Farh, and Podsakoff (1994) examined the effects of feedback sign on both
group goal setting and group performance from a control theory perspective. Of its many
tenets, control theory proposes that individuals regulate their behavior in light of the
feedback they receive (Carver & Scheier, 1981; Taylor et al., 1984). Specifically,
individuals strive to minimize the gap between their performance and the internal
standards, or goals, they have accepted. Mesch et a]. hypothesized that control theory’s
predictions at the individual level regarding the effects of positive and negative feedback
on individual level goals and individual level performance may also explain the effects of

feedback sign on group goals and group performance. Specifically, they examined

28

whether the effects of feedback sign on group performance were mediated by group goal
setting.

In their study, Mesch et al. (1994) had subjects work in groups on a group task
that required group members to work interdependently to solve a number of word
recognition problems. After the groups’ first attempt on the task, they were provided with
either positive or negative performance feedback. The groups were then allowed to
strategize and set performance goals for the second attempt on the task. Groups then
provided self-reports of their group goals.

Their analyses revealed that groups receiving negative performance feedback set
significantly higher goals for the second task, spent more time strategizing, developed
more strategies, and had higher levels of performance compared to groups receiving
positive performance feedback. While the finding that positive performance feedback led
to significantly lower levels of task performance is interesting, the authors could not rule
out the possibility that the lower levels of task performance were the result of a more
difficult post-feedback task. Results of their follow-up path analyses nevertheless lent
strong support to the authors’ hypothesis that the effects of feedback sign on group task
performance are mediated by group goals. The results of this study provide additional
support to the belief that providing aggregated performance feedback can influence group
level task performance.

Effcfia offiam—Level Performance Feedback on Social Outcomes

Pearson (1991), in addition to examining the effects of group level performance

feedback on task performance, also examined the effects of group level performance

feedback on satisfaction using his sample of railway work crews. Results of his

29

investigation showed that there were higher levels of satisfaction in crews that received
feedback compared to those that did not receive feedback. Pearson concluded that the
effect of receiving performance feedback on satisfaction may be due in part to the lower
levels of role ambiguity and higher levels of motivation that resulted from receiving
group level performance feedback.

While Mesch et a1. (1994) were primarily interested in examining whether control
theory’s predictions regarding the effects of feedback sign on individual level goals and
performance also explained the effects of feedback sign on group level goals and
performance, they also tested control theory’s predictions regarding the effects of
feedback sign on group satisfaction. Results of their study revealed that receiving
negative group level performance feedback led to significantly higher levels of
dissatisfaction with the group compared to receiving positive group level performance
feedback.

In a more recent investigation, Bradshaw and Stasson (1998) had participants
complete a group decision-making task and then complete a questionnaire regarding their
impression of their group. The participants then received non-veridical performance
feedback indicating that the group was either successful or had failed and were then
asked to complete questionnaires regarding their attributions of the group’s performance
and their affect. The authors were specifically interested in the causal attributions made
by “shy” compared to “not shy” group members following feedback on their group’s
performance to determine if their attributions were different and whether their

attributions were related to levels of satisfaction with being a member of their group.

30

Results of the study indicated that group level feedback did affect affective
reactions among group members who were not shy with positive performance feedback
having a positive influence on affective reactions. Shy group members did not report
having more positive affective reactions after receiving positive feedback compared to
after receiving negative performance feedback. There was no significant difference in
affective reactions between shy and not shy group when the group level performance
feedback was negative. The authors concluded that these results were likely a function of
the tendency of shy group members to minimize their personal responsibility for both
group success and group failure whereas not shy group members have the tendency to
extemalize the causes of group failure and internalize the causes of group success.
Conclusions on the Recent Wtfl on the Provision of Team Level F eedlaagk

A number of themes emerge as one examines the literature on the effects of group
and team level performance feedback in teams. First, consistent with suggestions by
Conlon and Barr (1989), it appears that the provision of aggregated performance
feedback in teams can lead to social processing of the feedback. Tinsdale (1989)
concluded that groups socially processed their performance feedback in a way that
individuals who received performance feedback could not and attributed this processing
to the increases in task performance that groups experienced over and above those that
individuals experienced as a result of receiving performance feedback. Mesch and his
colleagues (1994) found that groups were able to use aggregated feedback to set group
performance goals and strategies which were both related to subsequent group

performance.

31

Another conclusion that can be drawn from the recent empirical work on
providing group and team level performance feedback in groups and teams is that
aggregated feedback can influence performance at the group and team level. While there
have been inconsistent findings regarding this effect (see Conlon & Barr, 1989 for a
comprehensive review), a number of researchers (Goltz et al., 1989; Mesch et al., 1994;
Pearson, 1991; Pritchard et al., 1988; Tinsdale, 1989) have all found evidence that group
and team level feedback has significant effects on group and team performance and
productivity. It should be noted, however, that positive aggregated feedback has been
found to have less of an effect on the performance of groups and teams (e. g., Mesch et
al,1994)

Finally, the review of the literature above also suggests that the provision of
aggregated performance feedback can influence social outcomes in groups and teams.
Both Pearson (1991) and Mesch et al. (1994) found that group level performance
feedback has an effect on satisfaction in groups, however Branshaw and Stasson (1998)
recently found evidence suggesting that individual differences may moderate these
effects.

Recent Literature on Individual Level Fem Interventioris in Tear_gs_

As previously mentioned, both Nadler (1979) and Conlon and Barr (1989) have
suggested that individual level performance feedback is an important type of feedback
that can be provided to those working in groups and teams. In recent years, researchers
have begun to explore the effects of individual level performance feedback in teams on

both task and social outcomes. In the following sections, I discuss these recent

32

investigations focusing first on the effects of such feedback interventions on task
performance then on the effects on social outcomes.
Effects of Individuai Level Performance F eedbafl in Teams on Taskjerformancg

Goltz et al. (1989) examined the extent to which the provision of individual level
performance feedback could yield increases in performance above that yielded from the
provision of group level feedback alone. First, they observed employees’ behavior during
a baseline period in which no feedback was provided. They then provided group level
feedback to the employees which, as mentioned above, resulted in a significant increase
in employees’ product handling. When individual level feedback was coupled with the
group level feedback an increase in employees’ performance was observed that was
significantly higher than that resulting from the provision of group level feedback alone.
When individual level feedback was no longer provided, there was a decrease in
employees’ behavior however the decrease was not significant which led the researchers
to reluctantly conclude that providing individual level feedback did not enhance group
feedback.

It should be noted, however, that Goltz et a1. (1989) offered two alternative
explanations for their results rather than dismissing the possibility that individual level
feedback enhances the effects of group level feedback. First, they suggested that if the
employees did in fact learn from the individual level feedback that was provided, it
would be difficult to reverse that learning. Second, they suggested that in their study it
may have been impossible to truly withdraw individual level feedback once it was
introduced. In other words, there was no way they could have prevented employees fiom

later working on problem areas that were identified when the individual level feedback

33

was being provided. In sum, the results of this study seem to suggest that providing
individual level feedback can have a positive influence on work groups over and above
that of group level feedback despite the design problems that prevented the researchers
from obtaining a definitive answer to their research question.

Using thirty-two groups of undergraduates working on a cognitive conflict task,
Harmon & Rohrbaugh (1990) explored the effects of providing individual level cognitive
feedback in the context of a group on both individual and group performance. While
much like decision-making tasks, rather than have the group make explicit decisions
about particular options or courses of actions, cognitive conflict tasks require the group to
establish a specific assessment technique or procedure/policy. Participants in this study
either received individual level performance feedback that was firlly shared among all the
group members or feedback that was provided individually and not shared among the
group. It should be noted that at the outset of the study, there was an additional no
feedback condition however these groups were later combined with the individually
provided/not shared feedback condition groups given that there were no significant
differences between the two conditions.

The researchers hypothesized that there would be significantly better group and
individual performance in groups that received shared feedback compared to groups that
did not receive shared feedback however they found no significant differences at the
group level in terms of group decision policies (i.e., group performance). On the other
hand, they did find significantly better individual decision policies (i.e., individual

performance) for those individuals in groups that received fully shared feedback. In sum,

34

the authors found that the provision of individual level performance feedback had a
significant and positive effect on individual learning in groups.

Reilly, Smither, Vasilopoulis, and their colleagues (Reilly, Smither, Vasilopoulis,
1996; Smither, London, Vasilopoulis, Reilly, Millsap, & Salvemini, 1995) suggested that
feedback itself may not be the most important variable for changing individual’s behavior
in organizations, but rather, exposure to prescriptive information (e.g., what behaviors are
desired, strategies for performance) about performance is most important for changing
employee behavior. Dominick, Reilly, and McGourty (1997) tested this hypothesis in a
study of the effects of peer feedback on team members’ performance. Specifically, they
examined whether mere exposure to the appropriate behavior via the performance
feedback instrument would influence the behavior of those who were not the direct
recipients of feedback. In this study, students were randomly assigned to one of three
group conditions—a feedback condition in which team members provided and received
performance ratings from their peers, an exposure condition in which team members
completed ratings on their peers but did not receive the any feedback from those ratings,
and a control condition in which team members did not rate their peers nor did they
receive feedback.

Results of their study revealed that teams in both the feedback and exposure
conditions significantly outperformed teams in the control group following the
experimental treatments. Furthermore, there was no significant difference in performance
between teams in the feedback and exposure conditions. The authors went on to suggest

that exposure to the feedback instrument both provided team members with a framework

35

for interpreting their own behavior and communicated to them what behaviors were
important and valued.

While theoretically interesting in-and-of-itself, the results of this study seem to
suggest yet another way that individuals working in teams may benefit from the provision
of individual level feedback, namely through exposure to the desired behaviors and the
outcomes they produce. While exposure in this study was in the form of a feedback
instrument, observing the behaviors and outcomes of other team members may also
represent yet another Opportunity for team members to learn appropriate behaviors and
strategies that will improve their own performance. In this way, the provision of
individual level performance feedback may have functional value not only for those who
experience the feedback directly (i.e., the feedback recipients), but it also may have
effects on those who observe the provision of the feedback.

More recently, Hollenbeck, Ilgen, LePine, Colquitt, and Hedlund (1998)
examined the effects of providing public, individual feedback on team performance on a
decision-making task. The results of this study indicated that teams in which members
were provided with individual feedback outperformed teams in which members did not
receive feedback. Team leaders in this study used the individual level performance
feedback regarding each of their team members’ accuracy to determine which team
member’s information was most valid (what the authors referred to as individual
validity). Thus, the feedback that team members received helped their team leaders better
determine the value of those team members. The leaders of the teams that received

feedback were able to better weigh the information provided by the members of their

36

teams (what the authors referred to as dyadic sensitivity) and thus made better team
decisions.
Effectsfiof Individual Level Performance Feedbgk in Teams on Social Outcomes

Roy, Gauvin, and Lirnayem (1996) explored the social loafing and social
matching behaviors of individuals working in electronic brainstorming groups when
individual level performance feedback was provided. Roy et a1. (1996) defined social
matching as attempts of team members to perform at levels consistent with those of
others within their social setting. According to the authors, social matching can have dual
effects—it leads high performers to reduce their effort on the task while it leads low
performers to increase their effort on the task. Team members engage in such altering of
inputs is order to obtain equity in contributions within the team. High performers seek to
avoid being “suckers” while low performers seek to avoid being “loafers.”

The researchers hypothesized that there would be less variance in the ideas
generated by team members in teams in which individual level feedback was provided
during the task compared to teams in which no feedback was provided or feedback was
provided at the end of the task as high and poor performers would alter their inputs to
seek equitable contributions within their teams. Results of their study supported their
hypothesis and thus the authors concluded that individual level performance feedback in
teams equalized performance. More important, this study suggests that individuals
working in teams do in fact engage in social matching with others in their team lending
some support to Conlon & Barr’s (1989) proposition that social comparisons are an

important socially mediated outcome of providing individual level feedback in teams.

37

Unfortunately, despite the authors’ discussion of social matching from an equity
perspective, they failed to measure justice perceptions thus they were unable to examine
the extent to which perceived fairness may have influenced team member behavior in
their study. Furthermore, the feedback provided to team members was outcome feedback
only and provided only objective information (i.e., the number of ideas generated by each
team member). Therefore, while subjects in their study could compare their inputs to the
inputs of others, there was no reason for subjects to believe that their outcomes, or
outputs (i.e., feedback) were inequitable. It is likely that in real work teams, team
members make comparisons of both their inputs and outputs relative to others as opposed
to just inputs. Furthermore, in real work settings the feedback that individuals receive is
also not likely to be as accurate and objective as that provided to the subjects in Roy et
al.’s study.

Conclusions on the Recent Work on the Provision of Individual Level Feedbacm
Earls

Similar to the recent findings regarding the effects of providing team level
performance feedback to those working in groups and teams, recent examinations of the
effects of providing individual level performance feedback have consistently shown that
providing individual level performance feedback influences both individual (Dominick et
al., 1997; Harmon & Rohrbaugh, 1990) and team (Goltz et a1, 1989; Hollenbeck et al,
1998) performance. In fact, Goltz et al. provided limited evidence that individual level
performance feedback may have more influence on performance than group level

feedback. Their findings are consistent with Conlon and Barr’s (1989) proposition that

38

feedback that is provided at the individual level should have more motivational and
informational influence than feedback that is aggregated.

Another conclusion that can be drawn from this literature—one that is also
consistent with propositions by Conlon and Barr (1989)—is that team members engage in
social processing when individual level feedback is provided in the social context of a
team. For example, Harmon and Rohrbaugh (1990) found that individuals were better
able to utilize, and thus experience higher levels of performance improvements, when
they were in teams in which each of their team members’ performance feedback was
fully shared compared to those in teams in which the feedback was not shared. More
important, their findings suggest that individuals can benefit from feedback that they do
not directly receive. Dominick et al. (1997) also found evidence that individuals can learn
from being exposed to other’s performance standards even when they do not directly
receive performance feedback.

In regards to the social outcomes of providing individual level performance
feedback in teams, the previously reviewed empirical studies suggest that team members
do in fact engage in social comparisons with each other after being made aware of each
others’ performance as a result of individual level performance feedback. For example,
while Hollenbeck and his colleagues found that providing individual feedback led to
better team decision making and hence better team performance, they also found that
team leaders were better able to weigh each team members’ input based on the team
member’s performance feedback. In this study, team leaders became less sensitive to
information provided by members of their team whose performance feedback indicated a

history of invalidity. This suggests that perhaps both team leaders and members made

39

comparisons regarding the performance of others in the team. Unfortunately, Hollenbeck
et al. (1998) were concerned primarily with and focused specifically on the performance
effects of providing individual level performance feedback. What remains to be further
examined are the potential social effects of such comparisons.

General Conclusion_s Regarding the Effects of Feedback Intervention in Tear_n§

In sum, although some research on feedback in teams has emerged over the last
twenty or so years since Nadler’s (1979) initial review, many unanswered questions
remain. Nevertheless, several themes emerge as one carefully considers the work that has
been done.

Perhaps one of the more interesting conclusions that can be drawn from the
existing literature on feedback in teams is that there is no ideal aggregation level (i.e.,
team or individual) for improving team effectiveness and performance. Clearly, the
evidence is mixed regarding whether or not group, or team, level feedback alone can
yield positive effects of the performance of individual team members. While some
researchers have found that the provision of team level performance feedback can result
in increased individual (Goltz et al., 1989) and team performance (e. g., Jones et al., 1993;
Pearson, 1991; Pritchard et al., 1988, Tinsdale, 1989), Goltz et al. (1989) found evidence
suggesting that team level feedback is not as effective in influencing individual
performance as individual level performance feedback.

Similarly, there is only limited evidence regarding the mechanisms by which
individual level feedback influences the behaviors of those in groups and teams. While
models of the effects of group level feedback have recently emerged (i.e., O’Leary-Kelly,

1998), researchers have yet to develop models of the effects of individual level feedback

40

and the process by which it exerts its effects. Nevertheless, a number of suggestions have
been offered as to why individual level performance feedback may have more influential
effects on team members’ performance than aggregated feedback including the ambiguity
that group or team level feedback may present for individuals regarding their own
individual performances in addition to the possibility that individuals in the group or
team may fail to accept any responsibility for aggregated feedback (Conlon & Barr, 1989;
Barr & Conlon, 1994).

A number of authors have noted that there are socially mediated processes and
outcomes that occur when feedback is provided to those working in teams (Conlon &
Barr, 1989; Roy et al., 1996). This seems to especially be the case when the feedback that
is provided is at the individual team member level. In such cases, researchers have
recognized that it is likely that team members will engage in social comparisons with one
another. To date, only one study (Roy et al., 1996) has provided an empirical examination
of these social processes.

Related to the social comparisons that are likely to occur when individual level
feedback is provided to those working in teams is yet another socially mediated process
that may occur when individuals are made aware of their own performance and outcomes
and that of others with whom they are interdependent, namely performance
improvements among observers. Social cognitive theory may provide a useful theoretical
framework for guiding future thinking about performance improvements through both
direct and vicarious experiences that should occur when individual level performance

feedback is provided to those working in a team context.

41

The Present Researchand Theoretical Model Overview

Figure 4 presents an initial attempt to develop a theoretical model of the effects of
individual level performance feedback on the behavior of individual team members. As
shown in the model, specific emphasis is placed on the socially mediated processes that
occur as a result of individual team members becoming aware of both their own
individual performance and the performance and outcomes of the others with whom they
are interdependent. As previously discussed, despite the potential influence that these
socially mediated processes may ultimately have on team members, the lack of a
theoretical framework and systematic research on such processes has left an important
void in the feedback in teams literature. The model proposed here addresses this issue. It
focuses on two types of socially mediated processes that should occur as a result of the
provision of individual level feedback in teams. First, individuals are believed to engage
in a social comparison process once they are provided information about individual
performances and outcomes within the team. As a result of these comparisons, team
members are expected to form impressions regarding their feelings about being a member
of the team. Socioemotional outcomes have been identified by a number of researchers
(Campion et al., 1993; Campion et al., 1996; Cannon-Bowers et al., 1995; Hackrnan,
1987) as an important aspect of team effectiveness. Moreover, as the previous review of
the literature on feedback interventions in teams suggests, it is believed that the provision
of individual level performance feedback in teams will have social effects on teams as a
result of the social comparisons that individual team members are likely to make

following the provision of performance feedback at the individual level in teams.

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In addition to the social effects that may result from social comparison processes
when individual level performance feedback is provided in teams, the model also
proposes that team members’ performance will be influenced by the provision of
individual level performance feedback. Directly provided individual level feedback
should have an influence on the task performance of those who directly receive it as it
should provide information to these individuals about their own previous performance.
However, as the above review suggests, this is but one way in which individuals may be
influenced by the provision of individual level performance feedback in team settings.
Specifically, the review suggested that individuals might also benefit vicariously from the
experiences of others. In the present case, observing the provision of individual level
performance feedback to a team member should have an influence on the task
performance of those other team members who observe its provision. These performance
effects are predicted to be mediated by the attention it directs team members to both
themselves and to the task itself (as elaborated on further in the chapter that follows). In
sum, it is assumed that both the direct experience of receiving individual feedback in
teams and the vicarious experience of observing the provision of individual level
feedback to others in a team can have an effect on the social and task behavior of team
members.

The present study explored the effects of providing individual level feedback in
teams on direct feedback recipients and those other than the direct feedback recipient.
The following chapters further develop and derive several hypotheses from the
theoretical model as it relates to both the direct recipients and those who observe the

provision of individual level performance feedback in teams. It is hoped that the model

44

will serve as a first step in guiding researchers seeking to understand the effects of

providing individual level performance feedback in teams.

45

CHAPTER THREE. THE EFFECTS OF PROVIDING INDIVIDUAL LEVEL

PERFORMANCE FEEDBACK IN TEAMS ON TASK PERFORMANCE

While Kluger and DeNisi (1996) provided strong evidence showing that many
feedback interventions are in fact unsuccessful in having their desired effects on
employee performance, as Hauenstein (1998) points out, they also took a proactive stance
regarding feedback by proposing Feedback Intervention Theory (FIT) which suggests
several reasons why attempts to improve employee performance through the provision of
performance feedback succeed or fail. Perhaps the most useful suggestion derived from
FIT concerns the level at which the feedback is both directed and interpreted.
Specifically, Kluger and DeNisi proposed that feedback can be focused at three levels of
linked processes—task-learning, task-motivation, and meta-task processes. Moreover,
these levels of processes are organized in hierarchical fashion.

Task-learning processes reside at the lowest level of the hierarchy and focus on
learning how to perform better. For example, feedback provided at the task-learning level
may suggest to employees better performance strategies. Task-motivation processes
reside in the middle of the hierarchy, above task-learning and below meta-task processes.
The target is the exertion and direction of effort. An example of feedback that directs
attention to task-motivation processes is feedback that indicates that an employee is
performing well or poorly (i.e., positive and negative feedback). Finally, meta-task
processes are at the highest level of the hierarchy and concern more abstract, general

statements regarding the perfonner’s personal characteristics and work—related tendencies

(Hauenstein, 1998).

46

While task—learning and task-motivation process direct attention to the task itself,
meta-task processes direct attention to individuals perceptions of self at a more general
level. For example, feedback that directs attention to meta-task process may lead an
employee to see him/herself as generally incompetent or inadequate or perhaps so
competent that they can do no wrong or perhaps are irreplaceable. While these three
processes are organized into distinct hierarchical levels, it should be noted that they can
influence each other. Furthermore, there is no guarantee that feedback interventions
directed any particular level will be successful.

Through meta—analytic procedures, Kluger and DeNisi tested several of the
propositions derived from FIT. Of particular interest was their finding that feedback
interventions in which cues were provided that focused attention on task-learning and
task-motivation level processes had positive effects on performance while those in which
cues were provided that focused attention on meta-task level processes had less positive
(and in many cases negative) effects on performance. Simply stated, feedback
interventions that direct attention to the self rather than the task often have debilitating
effects on performance.

Effects of Directly Receiving Individual Level Performance Feedback on Task
Performance

As FIT suggests, feedback interventions that direct attention to the self would
seem to be particularly likely to have negative effects on performance in many of today’s
work settings which often can be characterized as presenting employees with tasks of
increasing complexity. In teams, one might expect that the desire, or motive, to maintain

or create a positive self-image in such a social setting would increase the likelihood that

47

those who directly receive feedback on their task performance would direct attention to
the self, in particular self-enhancement and maintenance, rather than the actual task. In
other words, feedback interventions that provide individual level performance feedback
in the social context of a team, may affect meta-task rather than task-learning and task
motivation processes. Moreover, this induced attention to meta-task processes is
proposed to occur regardless of whether the performance feedback is positive or negative
thus, FIT does not make clear that the effects of feedback interventions are different
depending on the sign of the feedback.

Kluger and DeNisi (1996) tested several propositions derived from FIT regarding
the effects of feedback interventions that may direct attention to meta-task processes,
several of which are related to the public provision of individual level performance
feedback in team settings. For example, they examined the effects of feedback
interventions in which normative information is provided (i.e., information that can be
used to make comparisons with others), norms are provided (i.e., information about the
performance of others), those designed to discourage, those designed to praise, those in
which the feedback is made public, and those in which reference to the group’s
performance is made. Of these aspects of the content of the feedback, only reference to a
group’s performance was proposed to enhance performance as feedback of this nature
should divert attention from individual perceptions of self while the other aspects of the
feedback content were proposed to have negative effects on task performance as
theoretically they should all direct attention to the self.

Results of their meta-analytic moderator analyses revealed that consistent with

both FIT and other models of self-attention (e. g., Carver & Scheier, 1981;Wicklund &

48

Gollwitzer, 1982; Zajonc, 1965) feedback interventions that focused attention on meta-
task level processes had less positive (and in many cases negative) effects on
performance. Specifically, they found support for seven out of thirteen variables used to
test their propositions regarding the detrimental effects of inducing attention to meta-task
processes. Of those related to the provision of individual level performance feedback in
teams, they found that feedback interventions that provided normative information,
norms, discouragement, praise, and were delivered verbally had negative effects on
performance. Feedback interventions that referenced the performance of a group rather
than individual performance, as expected, had positive effects on performance. Contrary
to their propositions, they found that feedback that was provided publicly had positive
effects on task performance. Thus, overall there seems to be strong support for FIT’s
proposition that feedback interventions that direct attention to the self rather than the task
often have debilitating effects on both task performance and the effectiveness of feedback
interventions.

Kluger and DeNisi’s findings are particularly relevant to the present discussion
given that individual level performance feedback provided in the context of teams is
likely to provide normative information, may indirectly reference the performance of the
group, is likely to be interpreted as praise or discouragement, and when provided
publicly, may be verbal. Therefore, based on FIT and the previously mentioned findings
regarding the negative effects of feedback interventions that direct attention to the self,
one might expect that feedback interventions in which information is publicly given to an
individual within the social context of a team regarding his or her individual performance

may, by directing attention away from the task and towards the direct feedback

49

recipient’s perceptions of self, have a negative effect on his or her task performance. It is
important to also recognize that the attention to self rather than the task that results from
directly receiving publicly provided individual level performance feedback in the social
setting of a team should occur regardless of whether the feedback itself is positive or
negative. This leads to the first of the study’s hypotheses:

Hypothesis 1 a: Regardless of the sign of the performance feedback, the

direct experience of being publicly provided with individual level

performance feedback will have a negative effect on task performance, an

effect that will be partially mediated by both increased self-focused

attention and decreased task-focused attention.

Hypothesis 1 b: Regardless of the sign of the performance feedback, the

direct experience of being privately provided with individual level

performance feedback will have a positive effect on task performance, an

effect that will be partially mediated by both decreased self-focused

attention and increased task-focused attention.

It should be noted that FIT, unlike other major feedback theories (e. g., Carver and
Scheier’s (1981) control theory and Locke and Latham’s (1990) goal-setting theory), fails
to make explicit the different effects of feedback interventions in which the performance
feedback is positive compared to those in which the performance feedback is negative.
Perhaps the most widely recognized such theory is control theory (Carver & Scheier,
1981; 1998) as it has been applied to understanding reactions to performance feedback
(Taylor et al., 1984). As described by Taylor et al. (1984), the theory maintains that there

are four features to all control systems, whether the systems represent organizations or

50

individuals. First, there are inputs from outside the system’s enviromnent that initiate
action within the system. Second, there is a processing of the inputs that are received
from the system’s environment. Third, some products, or outputs, result from the
processing of the inputs. Finally, there is a feedback loop that provides the system with
information about the nature of its products or outputs. The theory further maintains that
it is the feedback loop that is essential for system functioning.

Taylor et al. (1984) applied such thinking to understanding individuals reactions
to performance feedback and emphasized three processes as critical to control systems: 1)
the organization of behavioral standards, 2) the comparison of behavior to the behavioral
standard, and 3) the reaction to the discrepancy indicated by the performance feedback
regarding the gap between behavior and the behavioral standard. It should be noted that
the control theory perspective maintains that the feedback loop is perhaps the most
important aspect of control systems. In the context of performance feedback, it is the
feedback loop (or what Carver and Scheier, 1981 refer to as the test stage) that provides
comparison information to individuals regarding the extent to which their behavior
differs from that of the behavioral standard. In this way, the feedback loop regulates
behavior relative to some comparison value.

Taylor et al. (1984) discussed, in detail, the three processes involved in individual
reactions to feedback from the control theory perspective. As it relates to the organization
of behavioral standards, they suggested that behavioral standards can originate from
several different sources including the individual’s values or attitudes, others, or higher-
level standards. As it relates to the comparison process, they suggested that the frequency

in which the individual engages in the comparisons and the extent to which the

51

comparisons were made either consciously or unconsciously were important. Finally, in
regards to reactions to the feedback, the authors discuss a number of possible reactions
including affective, behavioral, and cognitive reactions.

Of particular importance as it relates to the present study is control theory’s
emphasis on the sign of the feedback as a determinant of individuals’ reactions to
performance feedback. It follows from control theory that the sign of the feedback is
critical for understanding individuals’ reactions to feedback in that it indicates a
discrepancy between their performance (or behavior) and the performance (or behavioral)
standard. According to control theory, individuals are likely to adjust their behavior to
reduce the discrepancy between their performance and the standard when there is a
negative feedback loop, thus indicating that a discrepancy exists. On the other hand,
individuals are not as likely to adjust their behavior when the feedback indicates that
there is no such discrepancy, thus indicating that performance is consistent with the
standard. However, more recent developments as it relates to individuals’ reactions to
performance feedback (i.e., Taylor et al., 1984) suggest that all negative feedback loops
do not compel individuals to adjust their behavior to meet the standard. In other words,
all negative feedback loops, even those indicating the same level of discrepancy, do not
influence behavior in the same fashion.

It is in this way that sign becomes particularly important as it relates to the effects
of performance feedback on individual task performance. Taylor et al. suggested that the
receipt of positive feedback (i.e., information indicating that one has met or exceeded the

performance standard) should be treated differently from the receipt of negative feedback

52

(i.e., information indicating that one has failed to meet the performance standard) as they
lead to different cognitive, behavioral, and affective reactions among feedback recipients.

Take for example, the authors’ discussion of behavioral responses to performance
feedback. Taylor et al. (1984) suggested that upon receiving performance feedback,
individuals can change the direction of their behavior, alter their levels of effort, change
their levels of task persistence, and respond against the feedback system. According to
the authors, the nature of these changes are contingent, in part, on the sign of the
performance feedback received. As it relates to changes in the direction of their behavior,
they suggested that following the receipt of negative feedback an individual may engage
in a search for more effective alternative behaviors. As it relates to altering effort levels,
they suggested that an individual who receives negative feedback may either increase or
decrease their effort depending on the extent to which his or her expectancies remain
strong. In regards to task persistence, they suggested that upon receiving negative
feedback an individual is likely to quit, in particular if expectancies decrease. Finally, the
authors suggested that, related to responding against the feedback system, an individual
may attack the source of the feedback or the feedback system itself when provided with
negative feedback, especially if the feedback is considered unfair.

The aforementioned reactions must be considered against those predicted to occur
when the feedback is positive. As it relates to potential changes in the direction of
behavior, Taylor et al. (1984) seemed to suggest that an individual who receives positive
feedback would fail to look for more effective task behaviors. Related to altering effort,
they suggested that the receipt of positive feedback would only lead to increased effort if

the individual’s goals were raised, but would more likely lead to decreased effort as

53

positive feedback would likely lower the intrinsic value of achieving the performance
standard. This would also be the likely result if no additional rewards were associated
with surpassing the performance standard. In regards to task persistence, the receipt of
positive feedback, as discussed by the authors, would likely lead to quitting if the
recipient sees the positive feedback as a reason to “try something more challenging.”
Finally, positive feedback is not likely to result in an individual retaliating against the
feedback source or feedback system.

Similar to FIT, control theory would also predict that these effects are mediated,
in part, by the attention that the feedback directs towards the self and the task. Control
theory suggests that the discrepancies made apparent by a negative feedback loop leads
directly to both self- and task—focused attention, however the theory differs from F IT in
terms of the impact of these effects. According to control theory, self—focus (self-directed
attention) is often of positive influence on performance as attention to self is likely to
promote more engaged comparison processes or self-regulation. Such self-regulation is
necessary as it leads to individuals’ attempting to “match their behavior more to the
established standard or goal” (Carver & Scheier, 1998, p. 182). Therefore, contrary to
FIT, self-focused attention is predicted to be positively related to performance according
to control theory. Control theory further suggests that self-focus often promotes task-
focus (Carver & Scheier, 1998) and task-focus is seen as also critical to increased task
performance. As such, both FIT and control theory make similar predictions about the
effects of task-focus on task performance but opposite predictions regarding the effects of

self-focus on task performance. Clearly, the theoretical predictions that are derived from

54

FIT and control theory differ and thus provide an interesting theoretical debate that could
be addressed in the present study.

As the previous discussion of control theory and its application to performance
feedback highlights, individual reactions to feedback are largely dependent on the sign of
the feedback. Several researchers have provided empirical support for the some of the
arguments presented by Taylor et al. (e.g., Anderson & Rodin, 1989; Kernan & Lord,
1991; Podsakoff & Farh, 1989). Even Kluger and DeNisi (1996) discuss the discrepancy
reducing mechanisms individuals employ when presented with information that indicates
that there is a difference between their performance and the performance standard. In
their review of control theory, they discuss evidence that demonstrates that when
feedback indicates that an individual has met or exceeded the performance standard, it
often results in reduced or maintained effort, while feedback indicating that an individual
has not met the performance standard often results in increased effort. Interestingly
however, Kluger and DeNisi did not make much of a distinction between positive and
negative feedback in their later discussion of FIT. Further, their meta-analytic
examination of HTS predictions, yielded no evidence supporting the need for a
distinction between positive and negative feedback. In combination, this raises the
possibility that FIT, in emphasizing to what individuals will focus their attention on as a
result of the cues the feedback provides and by extension, the context in which the
feedback is provided, may be deficient in that it fails to make explicit the differential
effects of feedback of varying sign.

It remains clear that the most often experienced behavioral reaction to negative

feedback is to increase levels of performance to meet performance standards (provided

55

that behavioral changes are possible), while decreasing or maintaining levels of
performance following the receipt of positive feedback. Indeed, it is difficult to ignore the
distinction control theory and findings regarding control theory and individual reactions
to performance feedback make between the effects of positively framed and negatively
framed performance feedback.

From a practical perspective, it is important to recognize that control theory, in
combination with FIT provides a more complete picture of the options that are available
for those considering what sort of feedback to provide to those working in team contexts.
While FIT makes apparent the distinction in the various contexts in which the feedback
could be provided, control theory adds the importance of the sign of the feedback. In their
current form, each of the theories seems to ignore the other. The result is that not only are
organizational practitioners left with questions about the appropriate context in which to
provide individual level performance feedback to those working in teams, but also
questions about the best sort of feedback to provide in those contexts. For example, if
individual level performance feedback is to be provided to individuals working in teams,
should it be provided publicly or privately? Further, if publicly provided, should the
feedback be positively or negatively framed if it is to be effective? Does it matter whether
the feedback is positive or negative?

In sum, it remains to be seen whether or not FIT’s predictions hold across the
various signs of the feedback. Similarly, it has yet to be seen whether or not control
theory’s predictions hold across the various contexts in which individual level
performance feedback can be provided. As such, the present study sought to compare the

predictions made by FIT to those made by control theory. It is believed that, for the

56

aforementioned theoretical and practical implications, this is an important contribution of
this study. As such, what follows below are two hypotheses that run somewhat counter to
those of FIT. These hypotheses are based on control theory in that they make explicit the
role of the sign of the feedback yet at the same time, do not address the context in which
the performance feedback is provided. In addition, these hypotheses also recognize the
differential predictions control theory makes regarding the mediating influence of self-
and task-focused attention. The next of the study’s hypotheses directly test control
theory’s predictions:
Hypothesis 2a: Regardless of the public versus private context in which

the performance feedback is provided, the direct experience of being

provided with negative individual level performance feedback will have a

positive eflect on task performance, an effect that will be partially

mediated by both increased self-focused attention and increased task-

focused attention.

Hypothesis 2b: Regardless of the public versus private context in which

the performance feedback is provided, the direct experience of being

provided with positive individual level performance feedback will have a

negative effect on task performance, an effect that will be partially

mediated by both decreased self-focused attention and decreased task-

focused attention.

57

Effects of Observingfle Provision of Individual Level Performance Feedbafigalasjg
Performance

While organizations themselves can often be conceptualized as social systems
(Morgan, 1997), work teams are also social systems, albeit on a smaller scale, in that they
comprise an identifiable collection of individuals working in a specific place, over the
same period of time, and on a unique task (Guzzo & Shea, 1992; Sundstrom et al., 1990).
Team members are individuals who make up the social unit called a team and thus teams
represent smaller social units that are distinguishable yet nevertheless are a subunit of
larger social units (i.e., organizations).

When teams are conceptualized as social structures, social cognitive theory, in
addition to what is currently known about feedback interventions (e. g., Kluger & DeNisi,
1996), provide an avenue for understanding how teams, and more specifically, the
individuals who make up such teams, may be affected by the provision of individual level
performance feedback. Specifically, social cognitive theory addresses observational
learning. In other words, it calls attention to performance effects observers of the
provision of individual level performance feedback may experience. This is particularly
interesting since prior to the development of Bandura’s (1977; 1986) social cognitive
theory (i.e., social learning theory) much of the psychological literature on learning and
performance, in emphasizing learning via personal experiences, and had almost ignored
the learning and performance improvements that occur as a result of observing others
within one’s social setting. When one considers the informational and motivational role
that learning from others’ performances and the feedback that may result from those

performances can have on observers, it further calls into question the commonly made

58

recommendation that feedback in teams should only be provided at the team level. In
particular, it raises the possibility that observing a team member perform a task and
receive individual level performance feedback regarding his or her performance may
have an influence on the subsequent performance of other team members. Latham and
Saari (1979) stated that, “social [cognitive] theory. . .acknowledges that human thought,
affect, and behavior are influenced by observation as well as direct experience.”

In vicarious learning, reinforcement plays a primary role as an antecedent
influence. In other words, the reinforcement an individual receives signals to observers
what outcomes they themselves may receive if they behave, or perform, in a manner
consistent with that of the observed individual, or model. It is the learning and
performance increases that can result from observing others publicly receive feedback
that is believed to be of particular benefit for increasing the performance of those
working in team settings. The following section further explores the effects of vicarious
experiences and thus provides yet another step in the development of a model of the
effects that may occur when those working in teams are afforded the opportunity to learn
from the social cues provided from the provision of individual level performance
feedback to others in their work teams.

An Overview of Vicarious Reinforcement Processes

How do vicarious processes such as the ones discussed above relate to the
provision of feedback in teams? When one considers the functions that feedback serves, it
becomes clear that providing feedback is likely to have effects similar to those of
providing vicarious reinforcement and punishment. Ilgen et al. (1979) suggested that

performance feedback serves a number of purposes including motivational and

59

informational functions. As a motivator, feedback provides information about the
outcomes associated with rewards. In this capacity, feedback operates as an incentive,
increasing motivation by acting as a promise of future rewards. Moreover, this
motivational function is similar to the task-motivation processes identified by Kluger and
DeNisi (1996). In serving its informational function, feedback clarifies roles in
organizations by making specific those behaviors that should be performed (Ilgen et al.,
1979). This is quite consistent with the task-learning processes Kluger and DeNisi (1996)
identified. It should be noted that it is unlikely that these two interrelated functions of
feedback can be separated as they work in tandem thus allowing feedback to operate by
providing both motivation and information to individuals in organizations (Annett, 1969;
Ilgen et al., 1979).

Vicarious reinforcement processes also serve both informational and motivational
functions. In fact, both informational and incentive-motivational functions are among the
five different mechanisms through which vicarious reinforcement effects behavior
(Bandura, 1977). Bandura (1977, 1986) further suggested that consequences affect
behavior primarily through their informative and incentive value. Like performance
feedback, vicarious positive reinforcement/punishment has informational value in that it
alerts observers to what behaviors should be matched or avoided to produce particular
outcomes. In particular, observing models receive desired and/or undesired outcomes for
specific behavior indeed signals to observers what behaviors are either valued or
prohibited. Bandura suggested that observed outcomes can alter behavior just as can
directly received outcomes (Bandura, 1986). Bandura (1977) also proposed that observers

develop and confirm hypotheses about the types of responses that are required to obtain

60

and avoid rewards and punishment by observing the differential consequences that result
from a model’s behavior. Also like performance feedback, vicarious positive
reinforcement/punishment has motivational value in that the outcomes models receive
create expectations among observers as to the type, rate, and magnitude of the outcomes
they will receive following similar performances (Bandura, 1977). This is particularly
important as in work contexts feedback is often considered a valued outcome.

Following Bandura’s social cognitive theory (1977; 1986) and its assertions
regarding vicarious reinforcement processes, it is proposed here that individual level
performance feedback provided to those working in a social setting such as a team, while
likely to have some effects on the task performance of a direct feedback recipient, may
have a positive vicarious influence on the task performance of other members of the
teams (i.e., observers). In other words, in serving its informational and motivational
function, individual level performance feedback provided to a direct feedback recipient,
should positively influence the task performance of others in the team. Following FIT,
such feedback should induce attention to task—learning and task-motivation processes
while being less likely to induce attention to meta-task processes among observers since
as indirect feedback recipients, they should not perceive the feedback as relevant to
perceptions of themselves. Therefore, while direct recipients of such feedback are
proposed to divert attention away from the task and to their self-perceptions, indirect
recipients of such feedback are expected to direct their attention to the task and away
from their self-perceptions as a result of observing the public provision of such feedback.
Thus, while many team scholars discourage the provision of individual level performance

feedback in teams, it nevertheless may have value in its ability to increase displays of

61

desired work behaviors among those who experience the feedback indirectly, or
vicariously. Thus, the next of the study’s hypotheses:

Hypothesis 3: The indirect experience of observing a team member

publicly receive individual level performance feedback in teams will have

a positive effect on observers ’ subsequent task performance, an effect that

will be partially mediated by both decreased self-focused attention and

increased task-focused attention.

The previous discussion has thus far focused on the potential costs and benefits in
terms of increased levels of individual task performance that result from receiving
performance feedback directly and indirectly in teams, respectively. What has yet to be
discussed are the potential social effects that may also result from the provision of
individual level performance feedback in teams. Related to the indirect learning that
should follow the observation of an individual directly receiving individual performance
feedback in teams, Bandura (1977) stated that vicarious reinforcement introduces
comparative judgmental processes among observers. In other words, observing the
consequences that others receive for their behavior provides a standard for judging one’s
own consequences and behavior. Indeed, a number of researchers (e. g., Conlon & Barr,
1989; Roy et al., 1996) have suggested that the provision of individual level feedback in
teams raises the possibility that team members will engage in social comparisons with
one another. The next chapter examines the potential social effects of the social
comparisons that are likely to be made when individual level feedback is provided to

those working in teams.

62

CHAPTER FOUR. THE EFFECTS OF PROVIDING INDIVIDUAL LEVEL
PERFORMANCE FEEDBACK IN TEAMS ON SOCIAL OUTCOMES

Hackman (1987) suggested that team effectiveness is much more complex than
simply task performance. According to Hackman, team effectiveness also includes other
social or interpersonal criteria that have traditionally been ignored in the team’s literature.
In particular, Haclcman identified three criteria for team effectiveness—the actual output
of the group (task performance), the impact of the group experience on individual
members (member satisfaction), and the state of the group as a performing unit (ability to
remain as a group). Thus, Hackman’s view of team effectiveness is consistent with some
previous others (e. g., Gladstein, 1984; Goodman, 1979; Wall, Kemp, Jackson, & Clegg,
1986; Walton, 1972) who have defined effectiveness in work groups and teams in terms
of both their productivity and their satisfaction with the experience (Campion et al.,
1993)

More important, as scholars broaden their perspective of team effectiveness, it
becomes clear that considering the social effects of providing individual level
performance feedback should also be of critical importance in determining the impact of
individual level performance feedback interventions on teams and their members
regardless of their effects on task performance. The preceding chapter discussed
specifically the effects of providing individual level performance feedback in teams on
the individual task performance of both those who are the direct recipients of such
feedback and those who are observers of the provision of such feedback. What remains to
be discussed are the social effects of providing individual level feedback regarding how

team members are performing on the team’s task.

63

Clearly, recommendations against the provision of individual level feedback to
those working in teams have been based on the belief that such feedback will have a
negative impact on social interaction among those in teams. For example, Smither (1998)
suggested that in team environments performance appraisals should be directed at the
team level rather than the individual level.

However, as seen in the review of the feedback in teams literature provided
above, with the exception of only a few researchers (Barr & Conlon, 1994; Roy et al.,
1996), most have failed to empirically examine the social implications likely to occur
when feedback is provided to those in teams. As such, researchers know little about the
social effects of providing both team and individual level feedback in teams. In light of
Hackman’s more inclusive definition of team effectiveness, which includes such social
criteria, this also seems to suggest that we really know little regarding the effects of
providing performance feedback (both at the individual and team level) on team
effectiveness.

In this chapter, I explicitly explore the social implications of providing individual
level performance feedback in teams among both those who are the direct recipients of
individual level performance feedback in teams and those who observe its provision. I
focus on three social outcomes that are particularly important in teams in light of
Hackman’s (1987) explicit recognition that such social criteria are critical aspects of team
effectiveness. In particular, I discuss the effects that receiving individual level
performance feedback in a team context may have on team members’ perceptions of the
social dynamics and functioning in teams. Specific emphasis is placed on three social

outcomes, namely perceptions of team cohesion, viability, and potency.

64

Effects of ProvidingLIndividuagl Level Performance Feedbaikfi on Cohesion. Virgilitv. ajfl
Potency in Teafl

Clearly teams provide a context that can be best described as a social setting—one
that provides opportunities for individuals to make comparisons with each other
regarding both their own individual performances in addition to the feedback they receive
as a result of those performances (Conlon & Barr, 1989). Herein lies the potential
problem for performance feedback provided at the individual level in teams.

A number of scholars have expressed the concern that providing individual level
performance feedback is a useful mechanism for influencing task performance in teams
(e. g., Campion et al., 1993, McIntyre & Salas, 1995), yet at the same time other scholars
have suggested that doing so will have a detrimental effect on the social functioning of

the team. For instance, in a recently published book entitled, Performance Appraisal:

 

Sgte of the Art in Practice, Reilly and McGourty (1998) emphasized the importance of
individual level performance in teams, however several pages later Smither (1998)
warned against the “contradictory” practice of providing individual level performance
feedback in team environments (p. 538). Smither (1998) suggested that when using
appraisals to increase team performance, the appraisal should be geared toward the team
as a unit. Interestingly, he later stated that individual level competencies and
contributions should still be measured (p. 542). He then suggested that as task
interdependence increases, as is the case when individuals work in teams, “measuring
individual contributions becomes more difficult and individual appraisal becomes less

appropriate...” As evident by contradictions such as these, the state of affairs regarding

65

the social implications of providing individual level performance feedback and appraisals
in teams has proven to be more confusing than helpful.

As previously mentioned, admonitions against the provision of individual level
performance feedback in teams are based on the belief that individual level feedback will
have detrimental effects on team social processes (e. g., coordination, cooperation, social
attraction) and team outcomes. The quality management literature provides an exemplar
of the thinking of many scholars on this issue, albeit focusing at a higher level of
organizational functioning.

The quality management perspective promotes “the creation of an organizational
system that fosters cooperation and learning...” (Anderson, Rungtusanatham, &
Schroeder, 1994, pg. 473). Of the many tenets of the quality perspective, one is that
providing individual level performance feedback is counterproductive for promoting and
sustaining cooperative environments (such as teams) that are conducive for quality
management (Deming, 1982, 1986; Walton, 1986). In other words, the quality
perspective suggests that providing individual feedback in groups and teams distracts
from cooperation in that it may lead feedback recipients to internalize their performance
rather than accept that their performance is due, in part, to the total system in which they
operate. In addition, since individual level performance feedback is often based on
previous performance, quality proponents would argue against providing individual level
feedback in teams and instead suggest forward-looking performance evaluations aimed at
the group and team levels (Blackburn & Rosen, 1993).

However, it should be noted that no empirical evidence exists that demonstrates

that the provision of individual level performance feedback in teams has such negative

66

effects on team social outcomes. The extant literature regarding the effects of individual
level performance feedback in groups and teams does however suggest that team
members can and often do attend to and socially process performance feedback that is
provided to others (Conlon & Barr, 1989; Dominick et al., 1997; Harmon & Rohrbaugh,
1990). It also suggests that the provision of such feedback can also lead to social
comparisons (Conlon & Barr, 1989) and judgments regarding each other’s performances
(Hollenbeck et al., 1998).

As a result, one might conclude that the ability to make such social comparisons
as a result of providing individual level performance feedback in teams may be
detrimental to team social dynamics, yet no empirical study has shown that the provision
of individual level performance feedback has such negative effects on team social
processes and outcomes. Moreover, it remains to be empirically demonstrated that any
negative effects that the provision of individual level performance feedback in teams may
have on team social dynamics are the direct result of the ability of team members to make
social comparisons with each other regarding either each others’ individual performances
or the individual level performance feedback they receive for those performances. In this
regard, the present study sought to empirically determine if such an effect actually exists.
Of particular interest were three distinct, yet related social outcomes that have been
identified as important in teams.

First is team cohesion. Team cohesion has long been considered critical to team
functioning (Cannon-Bowers et al., 1995) and can be generally defined as the extent to
which team members see themselves as one collective unit. Cannon-Bowers and her

colleagues pointed out that it is often believed that the more cohesion there is in a team,

67

the more effective the team will be. They further pointed out that this is typically the
case, however, only when the team also promotes social norms for effectiveness. In other
words, cohesion is likely to support team effectiveness when members of the teams share
social norms such as a commitment to the organization in which the team is a part rather
than social norms for counterproductive behaviors.

A second social aspect of team effectiveness is what Hackman (1987) referred to
as team viability. Team viability represents the potential for the team to stay intact (i.e.,
the extent to which members of a team could continue working together in the future).
Hackman (1987) suggested that the ability of the team to continue functioning as a unit is
particularly important, as it is critical that team members’ experiences are not such that
they would resist working together on future team tasks.

Finally, team potency represents a third social aspect of team effectiveness.
Building on the work of Guzzo and Shea (1992) and Shea and Guzzo (1987), Campion
and his colleagues (Campion et al., 1993; Campion et al., 1996) defined potency as the
belief that a group can be effective. These researchers suggested that while similar to the
concept of team spirit and efficacy, potency is particularly related to the extent to which
individuals in a team are committed and willing to work hard for the team. Campion et al.
(1993) also noted that little research has been conducted on the potency construct.

The study’s hypotheses regarding the social effects of providing individual level
performance feedback in teams follow the arguments presented by a number of scholars
regarding the detrimental social effects of providing individual level performance
feedback in teams in addition to recommendations made by quality management

proponents against the provision of such feedback. In this sense, this study also attempted

68

to provide the first empirical test of whether providing individual level performance
feedback in teams does in fact have negative effects on the social dynamics and
functioning in teams. Thus, the final study hypotheses and the first concerning the social
effects of providing individual level performance feedback in teams:

Hypothesis 4: The provision of individual level performance feedback will

have a negative effect on team a) cohesion, b) viability, and c) potency, an

effect that will be mediated by increased levels of social comparisons in

teams.

Table 1 provides a list of all of the study’s hypotheses. As can be seen in the
Table, Hypotheses la, lb, 2a, and 2b concern the effect of providing individual level
performance feedback on the task performance of those who directly receive the
feedback. Hypothesis 3 concerns the effects of providing individual level performance
feedback on the task performance of those who, rather than directly receive the feedback,
observe its provision. Hypothesis 4 turns to the social implications of providing
individual level performance feedback and concerns the effects of providing such
feedback on team social outcomes.
Empirical Investigation

The next chapter describes an empirical study designed to test the hypotheses
developed in the Chapters 3 and 4. The study explores the effects of individual level
performance feedback on the direct and indirect feedback recipients in teams, as the
provision of individual level performance feedback in teams may have an influence on
the task performance of those who directly receive such feedback and those others who

indirectly receive (i.e., observe the provision of) such feedback. The research employed

69

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an untreated control group design with pre- and post-test measures (Cook & Campbell,
1979) and examined the effects of providing individual level performance feedback in the
context of a laboratory experiment in which individuals worked interdependently in
teams on a computer simulated task. The procedures, measures, and approach for

statistically analyzing the data are presented in the following chapter.

71

CHAPTER FIVE: METHOD
Research Design

The present investigation used an untreated control group design with pre- and
post-test measures (Cook & Campbell, 1979) to empirically test the relationships
depicted in Figure 4. Two variables were manipulated between teams. The first between
team manipulation was the context of the feedback (public versus private) that was given
to one team member in each team. The other between team manipulation was the sign of
the feedback (positive versus negative). Thus, five types of teams were used—public
positive, public negative, private positive, private negative, and a control group where no
one received performance feedback.

In addition to the between team manipulation, the design also included one within
team manipulation. Each team worked on a version of the team task twice thus task (task
#1 versus task #2) was a level in the design. All feedback treatments were randomly
assigned to teams; participants signed up for teams in an introductory management course
and, to my knowledge, there were no systematic reasons that altered the convenience for
their schedules.

Power Analysis

Following suggestions by Cohen (1977) and Cohen and Cohen (1983), power
analyses were conducted to determine the appropriate sample size necessary to ensure
that the statistical analyses, to be described later, had sufficient power to reject the null
hypotheses if they were in fact false. Two independent power analyses were conducted to
determine the sample size needed to detect the anticipated effects of the analyses

requiring the greatest statistical power—the hypotheses that were tested using

72

hierarchical mediated regression and the hypotheses were tested at the team level.
Specifically, the former concerned the hypothesized effects of providing individual level
performance feedback on the subsequent task performance of direct (Hypotheses 1a, lb,
2a, and 2b) and indirect feedback recipients (Hypothesis 3). The latter concerned the
hypothesized effects of providing individual level performance feedback on team
cohesion, viability and potency (Hypotheses 4a-4c).

Cohen and Cohen (1983) described three general strategies for determining the
size of the population effects that a research project is trying to detect. First, one can
determine what effect size to expect based on those reported in the relevant literature.
Second, one can posit a minimum effect size based on what is believed to be practically
or theoretically significant. Third, and finally, one can use conventional definitions of
small, medium, and large effect sizes (Cohen, 1977). In regards to the first of the most
conservative hypotheses (i.e., where hierarchical and hierarchical mediated regressions
were used to examine the effects of the feedback conditions on either direct or indirect
feedback recipients’ task performance), an effect size was taken from Kluger and
DeNisi’s (1996) meta-analysis on feedback interventions in organizations. The authors
reported a d of .38 for feedback interventions in general on task performance. The
formula provided by Rosenthal and Rosnow (1991, p. 442) for converting d to r suggests
that d = .38 is equal to r = .19 (r2 = .04). Therefore, assuming that the standardized
regression coefficients for the interaction terms could collectively explain an additional
4% of the variance in a regression that already explained 25% of the variance—25% of
the variance due to prior individual task performance—it was determined that 188

participants (47 teams) would provide a power of .80 at the .05 level of significance.

73

In regards to the other analyses requiring the greatest statistical power (i.e., that
which tested the hypothesized effects of providing individual level feedback on team
cohesion, viability, and potency), it was determined that a small to moderate negative
effect on levels of cohesion and potency in teams would be important to detect. Therefore
the conventional estimate of a small to moderate effect size (i.e., r = .30 and alternatively
r2 = .09) was used. Assuming that the standardized regression coefficients for the final
step in the regression analyses that tested these hypotheses could collectively explain an
additional 9% of the variance in a regression that already explained 41% of the
variance—40% of the variance due to previous levels of the dependent variable plus 1%
of the variance being explained by team performance—it was determined that 68 teams
would provide a power of .80 at the .05 level of significance.

The most conservative of the two power analyses was used to determine the
minimum number of teams necessary to appropriately test the study’s hypothesized
relationships. As such, a sample of no less than 68 teams (272 participants) was sought
for this study. Eighty teams (320 participants) were obtained for the final sample.
General Task Overview

Research participants worked on an interdependent team task. The task that was
used was a modified version of the Distributed Dynamic Decision-making (DDD)
Simulation developed for the Department of Defense for research and training purposes
(see Miller, Young, Kleinman & Serfaty, 1998 for a complete description). DDD is a
computer simulation of a military command-and-control context in which participants
work interdependently to protect a restricted airspace from enemy targets. The

participants were responsible for working as a team to detect, identify, and destroy any

74

enemies targets by using the bases and vehicles that they themselves occupied and
operated while, at the same time, they were to avoid destroying any friendly targets. As
such, DDD teams can be best described as “tactical decision-making teams” in which 1)
team members must make decisions under time pressure and threat; 2) team members
must interact, participate, and coordinate their inputs; and 3) teamwork is essential to
effective team performance (McIntyre & Salas, 1995).

The specific variant of this task used in this research, MSU-DDD, was developed to
be used in contexts where teams are comprised of anywhere from 2 to 5 members who have
little or no military experience. In this version of the simulation, each participant had a
networked PC at his or her workstation, and used a computer mouse to control various
military sub-platforms such as tanks, helicopters, jets and AWACS reconnaissance planes.
These sub-platforms were used in an effort to monitor and control a specific geographic area
represented in a 20 by 20 grid.

While the participants were able to verbally communicate with one another, they
were unable to see each others’ computer screens. Moreover, depending on the location
of a participant’s particular portion of the restricted airspace and the location of the
various vehicles he or she operated during the game, participants had very different
perspectives of what was happening across the whole territory represented on the screen.
For example, one participant may have seen many enemy vehicles in the restricted
airspace while the other participants had little, or no, indication that enemy vehicles were
even on the screen. As such, the task required high levels of interdependence among the

four participants.

75

At the end of each task, participants were provided with their offensive and
defensive scores that corresponded to the extent to which they successfully destroyed
enemy targets and defended their individual quadrants. The task also provided aggregate
team offensive and defensive scores, however participants within a single team have no
way of interpreting the aggregated score without either further information from the
experimenter or a comparison aggregated score from another team. Neither was provided
thus there is little reason to believe that the presence of aggregated, team level scores
confounded the individual level performance information that was provided at the end of
the task.

§p_ace Partitioning in MSU-DDD

A depiction of the grid used in MSU-DDD is shown in Figure 5. This grid is
partitioned in several ways. First, in terms of the team member's physical location in the
simulated geography, the grid is partitioned into four geographic quadrants of equal area
(NW, NE, SW, SE), and each area is assigned to one of the team members (or in DDD
terminology—decision makers or DMs). DMl is located in the middle of the Southeast (SE)
quadrant (see the small black rectangle), DM2 in the middle of the Northwest quadrant
(NW), DM3 in the SW quadrant, and DM4 in the NE quadrant.

Within this overall geographic space, there are friendly and neutral areas depicted on
the screen. In the centennost area of the screen is a 4 by 4 grid marked off in red that
represented a highly restricte_daflr. This highly restricted area is contained within a 12 by
12 grid that is demarcated in green that represented a restricted area. The area outside this

green restricted area is considered neutral territory. As is apparent from the figure, the two

76

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types of geographical partitioning were such that each quadrant had an equal amount of
space within it that represented neutral, restricted and highly restricted territory.

The object of the team's mission was to keep unfriendly vehicles from moving
into the restricted and highly restricted areas, while at the same time, allowing friendly
vehicles to move in and out of the same areas freely. The team's task, therefore, was to
monitor the geographic space, identify all "tracks" (i.e., the radar report of a vehicle) in
terms of their nature (friendly versus unfriendly), and then disable any unfriendly tracks
that entered the restricted space. At the same time, the teams were to avoid disabling any
friendly tracks.

Each team started with a set number of points, and lost points for each unit of time
(seconds) that an unfriendly vehicle resided in a restricted or highly restricted zone. Teams
also lost points whenever they disabled a friendly track in any area or an unfiiendly track in
neutral territory. The team with the most points left at the end of the experimental sessions
were awarded the cash prizes.

Bases and Sub-Platfonns

In terms of monitoring the geographic space, each team member's base (see the
small black rectangles labeled DMl, DMZ, etc. in Figure 5) had the same radar capacity as
every other team member. Specifically, each base had a detection ring radius of roughly six
grid units (demarcated by a black circle like the one shown in Figure 5). The team member
could detect the presence or absence of any track within this radius track. Each base also had
an identification ring radius of roughly 4 grid units (demarcated in blue) within which, he or

she could discern the nature of the track in terms of friendly versus unfriendly status.

78

Any track outside the detection ring was invisible to the team members, and
therefore they had to rely on their teammates to monitor regions of the space that were
outside their own quadrant. However, as is clear from the figure, there were areas within
each quadrant that could not be monitored from any of the bases. In these areas, the team
member had to rely on his or her sub-platforms to monitor the area outside the base's
detection ring.

Each DM had control of sub-platforms that represented various types of vehicles that
could be launched from the base, and then moved to different areas of the screen. These sub-
platforrns were semi-intelligent agents that could automatically perform certain functions
(e.g., return to base to refuel, etc.), and hence the DM was a manager of these semi-
intelligent agents. Most of the MSU-DDD simulation is played via the subcplatforrns, and
hence understanding the unique characteristics of each sub-platfonn is critical to
appreciating the complex nature of this task.

There were four different types of sub-platforms used in MSU-DDD; (a) AWACS
planes, (b) tanks, (c) helicopters, and ((1) jets. Each of these sub-platforms varied in its
capacities on four different dimensions; (a) range of vision, (b) speed of movement, (0)
duration of operability, and (d) weapons capacity.

The AWACS had the largest range of vision (radius of 4 grid units), followed by the
jet, the helicopter and finally the tank (radius of 2 grid units). In terms of speed of
movement, the jet moved the fastest (1 grid unit per second), followed by the AWACS, the
helicopter, and finally the tank (.1 grid units per second). While the tank was limited in
terms of speed and vision, it was the best asset in terms of duration of operation. It could be

away from the base for 8 minutes without having to refirel. The AWACS could operate

79

away from the base for 6 minutes, followed by the helicopter at 4 minutes, and the jet at 2
minutes. The tank also had the most weapons capacity, and could disable any track that
came within its attack radius (the third circle, demarcated in red, shown around each sub-
platfonn). The helicopter had the second best weapons capacity, followed by the jet,
followed by the AWACS which could not disable any track.

The various sub-platforms therefore constituted a complex set of assets that ranged
widely in their capacities. Each team member controlled four such sub-platforms that could
all be launched and Operated concurrently. In this version of the task, each team member had
equal assets in terms of sub-platforms such that each team member had one tank, one jet,
one helicopter, and one AWACS. This was particularly important as providing each team
member with equal assets in addition to equal levels of task demands allowed me to
compare task performance across the members of the team.

Identimag and Engaging Tracks

Tracks were radar representations of vehicles moving through the geographic space
monitored by the team. The tasks were configured such that there were 8 unique types of
tracks that varied in terms of (a) being fiiendly or unfriendly, (b) air-based or ground-based,
and (c) the amount of power it took to disable the track. All tracks originated from various
points along the edge of the screen and proceeded inward. Again, the team had to maintain
the integrity of the geographic space they were protecting by disabling (i.e., engaging) any
unfriendly track that entered the restricted area.

First, it should be noted that prior to identification (e. g., when the track was close
enough to be detected but not close enough to be identified) each track was represented by a

question mark, followed by a number that was set above a diamond (e. g., see Figure 5). The

80

number reflected each track's unique identification number. Once the track came within the
identification ring of either the base or a sub-platform, the DM had the opportunity to
identify the track. Identification was not automatically performed by the sub—platfonn.
Rather, the DM had to specifically direct the sub-platform to identify various tracks in a
specific order and at a specific time. Once identified, the symbol representing the track
changed flour a diamond, to a rectangle with a letter-number combination.

The nmnber referred to the level of power needed to disable the track (low = 1,
medium = 3 and high = 5), and had implications for what platform could perform certain
tasks. Tanks could disable all tracks, helicopters could disable those numbered 1 and 3, and
jets could only disable tracks numbered 1. As previously mentioned, AWACSs could not
disable any tracks. The number 0 next to a letter indicated that the track was fiiendly, and
that it should not have been disabled. The letter indicated whether the track was air-based
(A) or ground based (G). Air based tracks moved quickly, whereas ground-based tracks
moved slowly.

Once identified, the team member could opt to share this information with other
team members by clicking a "share information key." Although team members who were
too far away fi'om the track to detect it gained nothing immediately from such sharing, if the
track moved within their own detection zone, sharing the ID eliminated the need to repeat
the identification process. Thus, whereas the person who shared the identification with other
team members lost some time in doing this (and personally gained nothing because the track
was already identified on their own screen), this type of behavior helped increase the
efficiency of the team. In the long run, it eliminated the need for multiple identifications of

the same track.

81

Once a track was identified as an unfiiendly, its status with respect to the restricted
zone had to be monitored. If an unfiiendly track moved into the restricted zone, the DM had
to vector a weapons-bearing sub-platform with enough power over to the track and then
engage it. The sub-platforms did not automatically engage unfiiendly tracks that were
violating the restricted zone, but rather, the DM had to give a specific order to disable a
specific track at a specific time. Once a track was successfirlly engaged, it disappeared from
the screen, and the sub-platform then had to return to base to refuel and reload. To maintain
the integrity of the structures throughout the entire experiment, the sub-platforms could not
be disabled by each other or by the unfriendly tracks.

In configuring the two team tasks, each was designed so that each team would
experience 100 tracks during each task. Of the 100 tracks in each task, the majority of the
tracks’ (68 tracks) entry times were determined by a random number generator.
Furthermore, the point of entry and exit of this subset of tracks was also randomly
determined. While the entry and exit times for each of the tracks varied depending on the
task (first or second), the point of entry and exit did not to ensure that the two tasks were
essentially identical. Moreover, the power of the tracks was also determined by a random
number generator. As with the point of entry and exit of these tracks, the power of each of
the targets did not change from one task to the other to further ensure that the first and
second tasks were identical.

There were however, a subset of the tracks (four m consisting of 8 tracks per
wave = 32 tracks) that were designed to originate near the comers of the Northwest,
Northeast, Southwest, or Southeast quadrants and proceed in a straight line diagonally

towards the opposite comer of the task screen. Thus, each of the quadrants for which the

82

DM’s were responsible experienced one wave of tracks during each task. These waves
consist of two of each type of air track (A0, A1, A3, A5). Of these eight tracks, five stopped
once they reached the restricted zone of the quadrant from which they entered and stayed
there for ten minutes, or until they were successfully engaged. In this way, each DM had
primary responsibility for locating, identifying, and engaging if necessary, a
disproportionately greater amount of tracks at some point during each task.

The entry of the wave tracks were not randomly timed, but rather configured so that
no two DMs experienced a wave at the same time. As with the other tracks, the power and
entry time (within each wave) of the eight tracks in each of the four waves was identical.
Again, this ensured that task performance across each of the team members could be
compared. The only difference between the first and second tasks regarding the waves of
tracks was the order in which the DMs experienced their waves. In the first task, DMl
experienced the first wave, followed by DM3, DM4, and finally DM2. In the second task,
DM4 experienced the first wave, followed by DMl , DM2, and finally DM3.

It was in regards to task performance during the attack of wave tracks that
performance feedback was provided which referenced goals that were presented to the
participants before the first task. The feedback was provided immediately after the first task.
In this way, baseline performance measures of each of the team members was obtained prior
to any experimental manipulation between the first and second tasks. Both the goal setting
intervention and the individual level performance feedback intervention are described
below.

In summarizing, in the computer simulation, the team members were to monitor a

computer screen that presented a very complex and dynamic picture, filled with large

83

numbers of sub-platforms, rings, and tracks that were moving in different directions and at
different rates. They were also to use a mouse to launch and move various semi-intelligent
sub-platforms around the geographic area in an effort to identify all tracks, and engage those
that are enemies and violating the restricted area. While they were doing this, they
exchanged information with each other both electronically and verbally to more efficiently
manage the task, coordinate actions, support one another. Each team member experienced a
disproportional, heavy share of the workload relative to the other members of the team at
some point during each of the tasks. It was the individual level performance of one of the
DM’s during the wave attacks in which the feedback intervention was directed. In this way,
each four-person team had one direct feedback recipient and three indirect feedback
recipients (i.e., observers).
§ar_np_1§

Undergraduate business students currently enrolled in a human resource
management course served as the participants for this study. Participation in the study
was voluntary however participants were awarded course credit for their participation. In
addition, participants were informed that they could win a large cash prize ($100 per
person/$400 per team) based on the team’s performance on the task.
Procedure

Immediately after entering the laboratory, participants were randomly assigned to
a four-person work team in which to work interdependently on the computer simulated
team task. The team was then escorted into a room in which they worked on the team
task. Once in the room, each participant was randomly assigned to one of four computer

stations (e. g., DMl, DM2, DM3, or DM4). Afier being seated at their respective stations,

84

participants received the Team Member Questionnaire that contains the study’s survey
measures in addition to several individual difference measures. These measures will be
discussed further in the sections that follow.

Participants first completed Part I of the Team Member Questionnaire which
contained some individual difference measures. Participants then received training on the
team’s task. The training lasted approximately one hour and it was during the training
that participants became familiar with the team’s task and each other.

Immediately following the training, the team’s trainer set the goals for individual
performance for the each of the participants in the team (discussed further below). The
goals were publicly provided in the presence of the entire team and each team members’
goals were identical. Participants in all of the teams, regardless of the experimental
condition their team was assigned, received the same goals. Therefore, goals were a
constant across all teams and all participants and were not confounded with the
experimental manipulations. Finally, it should be noted that the goal setting intervention
was not an experimental manipulation in-and-of-itself, but rather it was a component of
the feedback intervention as the performance feedback provided information regarding
the extent to which feedback recipients met the performance standards set forth during
the goal setting intervention.

After the goal setting intervention, the trainer then provided several task strategies
for the participants to keep in mind as they worked on the task. Participants were advised
that the extent to which they employed the task strategies would affect the extent to
which they would meet their performance goals. After hearing both the goals and the task

strategies, participants received and completed the Part II of the Team Member

85

Questionnaire that contained several measures regarding their perceptions of their team,
fellow team members, and the team’s task.

Once all the participants completed the post-training questions section of the
Team Member Questionnaire (Part 11), they completed the first of the team’s tasks. At the
end of the first task, the trainer recorded the individual, group, and team scores. The
trainer then instructed the participants to complete the post-task #1 section of the Team
Member Questionnaire (Part Hla). Once all of the team members completed the post-task
#1 measures, the trainer provided performance feedback to the team member with the
highest or lowest individual defense score either publicly or privately (the feedback
intervention is furthered discussed below).

The performance feedback contained information regarding both the extent to
which team member met the performance goals set during the goal setting intervention
and the extent to which he/she utilized the task performance strategies discussed prior to
the first task. On the other hand, in control teams there was no feedback provided to any
team member regarding his or her performance on the wave tracks.

After the performance feedback was provided, the team completed Part IIIb of the
Team Member Questionnaire. They then worked on the second team task. Upon
completing the second task, team members completed the post-task #2 section of the
Team Member Questionnaire (Part IV). Once all of the team members completed the
post-task #2 measures, they were debriefed and dismissed.

Maing ancflask Strategies
At the end of the training for the team task, the trainer discussed the waves of

tracks that they would encounter during the actual tasks. During the hands-on training,

86

there were no waves of tracks thus no teams or individual team members had any actual
experience dealing with waves of tracks prior to the actual task. The experimenter
explained that there would be tracks that would attempt to enter the highly restricted area
in waves, or wave attacks, and that each team member could experience a wave in his or
her quadrant during the either of the tasks. Participants were also told that once these
targets reached the highly restricted area they would attempt to stay in that area as long as
possible thus causing the team as a whole to many lose points as they would be penalized
more severely for allowing tracks to reside in this area relative to other areas of the task
screen. The experimenter explained that each team member’s ability to effectively deal
with their wave of tracks would be essential to the team’s performing well and thus
potentially winning the cash prize. Participants were assured that they had most of the
skills required to handle a wave of tracks, and that some individual goals would be set
regarding their dealing with the wave of tracks.

In regards to these goals, participants were told that they should try to a) identify
all of the tracks before they reach the highly restricted area, b) begin engaging the tracks
within one minute of the onset of the wave attack, and 0) ensure that no enemy track
resided in the highly restricted area for more than three minutes.

In addition to setting these three goals for each participant in regards to dealing
with their waves of tracks, the experimenter provided some additional task strategies for
participants to keep in mind as they attempted to meet the goals. These strategies were
separate fi'om the information provided during the training each team received prior to
the task. Specifically, the experimenter informed participants that they should a) use their

AWACS plane more effectively to meet the goals by positioning and keeping it in the far

87

comer of the quadrant they were to protect as it would allow them to detect the wave
tracks more quickly since they would be entering the restricted areas from the comers of
the screen, b) move their most powerfirl assets to the highly restricted area as soon as
they became aware that they were experiencing a wave attack, and c) send their sub-
platforrns back to their base as soon as they had no more power (i.e., after having
engaged an enemy track) so that the sub-platform could quickly be redeployed back to
the highly restricted area after it had been used.

Finally, the trainer explained that the team member whose quadrant was under
attack by a wave of tracks had the primary responsibility for making sure that the goals
were met, however any member of the team could help if they wanted. The actual goal
setting intervention can be found in Appendix A and again, the goals and task strategies
were constant across all teams and all participants, thus they did not represent a study
manipulation.

Feedbaflt Intervention

 

Immediately following the end of the first task for the experimental teams, the
experimenter provided the appropriate team member (based on the experimental
condition assigned) with individual level performance feedback regarding his or her task
performance as it related to the wave of tracks. Specifically, the experimenter provided
individual level performance feedback regarding the extent to which the team member
met the goals discussed prior to the first task. It should also be noted that for teams in the
private feedback conditions, the experimenter told the appropriate feedback recipient that
there was a problem with a response on his or her consent form that needed to be

addressed outside of the presence of the rest of the team given the confidentiality of the

88

information. Once outside of the presence of the rest of the team, the experimenter
explained that there was no problem with the consent form, but rather, he or she wanted
to discuss the participant’s performance on the first task. The experimenter then informed
the feedback recipient about the extent to which he or she was effective in using the task
strategies discussed with the goal setting intervention. Appendix B provides the script
that was used to provide individual level performance feedback to the feedback
recipients. Both the goal setting and feedback intervention provided in Appendices A and
B, respectively, had been tested in a previous pilot investigation for this study.

It should be noted again that the feedback was provided at the end of the first task,
thus providing an opportunity to obtain baseline performance measures for each team
member prior to the provision of individual level performance feedback to the feedback
recipient. Post-treatment performance measures were collected in the second task for
comparison to the pre-treatment performance measures.

Measures

Table 2 provides a summary of the measures that were used in this study, as well
as the timing of the completion of each of the measures. Appendix C presents the actual
survey measures that were‘used. The following sections describe each of the measures
that were used.

Information Collected During the First amd Second Tas_k_§

During the actual task, a number of individual level performance measures were
recorded by the computers the participants used regarding their task performance (e. g.,
number of good attacks, number of wasteful attacks, number of times information about

tracks was transferred to other team members, the number of times the participant cleared

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an enemy track from a quadrant other than his or her own). A subset of these measures
were used to create an overall task performance measure.

Individual Task Performance. A weighted composite of both the number of good
attacks in addition to the number of waste attacks made by each participant was used to
measure overall individual task performance. The weights were determined with
principal components analysis in which a linear composite was constructed from the
original variables (i.e., good attacks and waste attacks) that maximized the variance of the
composite variable. The resulting principal component equation was PC = .734 (good
attacks) + .704 (waste attacks).

Good attacks were attacks made on enemy tracks with a vehicle (or sub-platform)
with the same amount of power as the enemy track the participant wanted to disable.
Thus, good attacks represented the extent to which the participant cleared enemy tracks
from the forbidden zones both effectively and efficiently. Good attacks also indicated that
a participant had a conceptual understanding of the task. Waste attacks were attacks made
on enemy tracks with a vehicle (or sub-platform) with more power than the enemy track
the participant wanted to disable. Therefore, similar to good attacks, waste attacks
represented the extent to which the participant was effective in clearing enemy tracks
from the forbidden zones, however waste attacks are a less efficient use of the
participants’ resources as it related to randomly entering enemy tracks. On the other
hand, waste attacks are not only effective, but also productive as it relates to disabling
tracks that entered during wave attacks in which the object was to destroy the tracks as

quickly as possible using whatever resources were available.

91

This overall task performance measure took into account how well the participant
helped keep the forbidden zones free of enemy tracks by destroying them once they
entered the forbidden zones. In addition, given the importance of, yet limited amount of
time in the task, this measure therefore also provided a relatively complete picture of
overall task performance as time spent making mistakes (i.e., disabling fiiendly tracks,
having difficulty launching sub-platforms, launching the wrong sub-platform, losing sight
of one’s sub-platforms), is time that could not be spent making successful attacks,
whether they were good attacks or waste attacks.

Information Collected in the Latwrtory After the First Task-Before the

Experimentad Manipulation and After the Second Task

Team Cohesion. Perceptions of team cohesion were measured with a five-item
scale adapted from Seashore’s (1954) work on group cohesion. Previous research using
adaptations of Seashore’s original scale have shown good reliability and validity. The
psychometric properties of the adapted items used in this study proved to have good
psychometric properties as is discussed in the next chapter and the items can be found on
page 184 of Appendix C.

Team Viability. Perceptions of team viability were measured with an eleven-item
scale adapted from the Mowday, Steers, and Porter (1979) organizational commitment
scale. The items were reworded such that they pertained to a work team rather than an
organization and two items were dropped from the original thirteen-item scale as, even
after rewording, they did not seem applicable to the teams used in this study. These items
can also be found in Appendix C (page 184) and their psychometric properties in this

study are discussed the chapter that follows.

92

Team Potency. Perceptions of team potency were measured with the three-item
scale developed by Campion et al. (1993) in addition to a fourth item that asked about the
extent to which the participant enjoyed working with his or her team. Campion et al.
(1996) reported Cronbach alpha coefficient of .80 thus indicating that the scale has good
reliability. The scale devised to measure potency in this study also proved to possess
good psychometric properties, as discussed later in the results. The items can be found on
page 184 of Appendix C.

Information Collected in the Laboratory Afier the First Task-After the

 

Experimentei Manipulation

Self-focused Attention. A scale was developed for this study that asked the extent
to which the participants devoted attention to self. This design of the scale was based on
the theoretical discussion of Kluger and DeNisi (1996) regarding attention to meta-task
processes. The scale contained seven items that measured the extent to which participants
attended to themselves, their own self-perceptions, and others’ perceptions of them. The
next chapter describes the psychometric properties of this newly created scale, however
the items can be found on page 185 of Appendix C.

M-focused Attention. Two scales were developed for this study that asked the
extent to which the participants devoted attention to the task. Following Kluger and
DeNisi’s (1996) theoretical discussion of attention to task-learning and task-motivation
processes, the scales’ items measured the extent to which participants attended to
learning and developing their skills on the task, and the extent to which participants
attended to putting forth effort on the task and obtaining performance-based rewards,

respectively. Each of the scales were originally composed of six items which can also be

93

found on page 185 of Appendix C. One item was dropped from the final task motivation
scale. As with the other scales, the psychometric properties of both of these two scales
will be discussed in the results that follow this chapter.

Information Collected in the Labo_ratory After the Second Task Only

Socfiial Comparison Perceptions. A 6-item scale was developed for this study that
asked about perceptions of social comparisons occurring in the team. The scale asked
specific questions regarding the extent to which participants perceived that the members
of teams made comparisons with each other. The items dealt with several different types
of comparisons that team members could potentially make with each other when working
on an interdependent task (e. g., effort, actual performance, outcomes for performances).
The newly created scale demonstrated good psychometric properties as they are
discussed in the next chapter. The actual items can be found on page 188 of Appendix C.

Manipulation Checks. A number of items were asked that measured the extent to
which the manipulations used in the study were effective (e.g., At any point after the
training, did you receive feedback from the experimenter on your task performance? and
Was the feedback you received more positive or negative?) These items can be found on
pages 188-189 of Appendix C.
Analyses

Multiple, hierarchical, and hierarchical mediated regression analyses were used to
test the hypotheses presented in Chapters Three and Four. The next chapter discusses in
more detail, psychometric properties of the study’s measures and the nature and results of

the hypotheses’ tests.

94

CHAPTER SD(: RESULTS

Tables 3 and 4 present the results of two analyses that were first conducted to
examine the factor structure of the items that were newly created for this study. Table 3
provides the results of a confirmatory factor analysis using all of the items designed to
measure self- and task-focused attention. These items were created around theoretical
discussions provided by Kluger & DeNisi (1996) on meta-task, task-motivation, and task-
leaming attention. As such, a confirmatory factor analysis of these items was appropriate
given their a priori factor structure. The items did, in fact, load on to their predicted
factors well. Results of the confirmatory factor analysis indicated that the three-factor
model fit the data well of = 363.80, df= 149, p < .01; CFI = .95; TLI = 94; SRMR =
.049; RMSEA = .07). Together, these three factors explained about 68 percent of the
variance in responses to the items, as indicated in Table 3, with the meta-task, task
motivation, and task learning factors each explaining 49.97, 12.24, and 5.48 percent of
the variance, respectively. One item, however, was dropped from the task motivation
scale as additional analyses revealed that the sixth item of the task motivation scale
loaded highly on both the task motivation and task learning factors. Dropping this item
only slightly improved the fit of the model (x2 = 323.40, df = 132, p < .01; CFI = .95; TLI
= 94; SRMR = .049; RMSEA =.07) but it did provide a more clear theoretical distinction
among the three factors.

Table 4 provides the results of a principal components factor analysis with
varimax rotation on the items designed to measure social comparisons in teams. As the
table indicates, the six items used to measure this construct loaded together on only one

factor which explained 60.45 percent of the variance in responses to the items.

95

Table 3

Confirmatorfiactor Analysis Results for Self- an_d Tgk-Focus Items

 

Item Eigenvalue % of Cumulative
Number Variance Variance Standardized Regression
Explained Explained Weights

 

(1) (2) (3)
Task Meta Task
Learning Task Motivation

Factor (1) 9.49 49.97 49.97
1 .82
2 .76
3 .85
4 .87
5 .87
6 .82
Factor (2) 2.33 12.24 62.21
1 .57
2 .77
3 .83
4 .86
5 .79
6 .71
7 .54
Factor (3) 1.04 5.48 67.69
1 .83
2 .84
3 .85
4 .74
5 .56
6 .79

 

96

Table 4

Exploratory Factor Analysis Results for Social Comparisons Items

 

Item Eigenvalue % of Cumulative
Number Variance Variance Unrotated Factor Loadings
Explained Explained

Social Comparisons

 

3.63 60.45 60.45
1 .71
2 .83
3 .83
4 .76
5 .79
6 .74

 

97

The reliabilities of all of the study’s measures were determined by calculating the
coefficient alpha for each scale. The alphas for each measure are presented in Table 5. As
the table indicates, the coefficient alpha for each scale proved to be more than adequate
for experimental purposes, with all being greater than .80 (Rosenthal & Rosnow, 1991, p.
50).

Following the theory developed throughout the previous chapters, there were a
number of measures collected in the study that sought to examine team level constructs.
While all of the study’s variables were measured at the individual, team member level,
Table 6 provides an examination of the extent to which there was support for aggregating
the individual level measures into team level constructs. Specifically, Table 6 provides
the ICC(1), ICC(2), AN OVA significance tests, and rwgo) values for each of the proposed
team level variables. ICC(l) indicates the extent to which individuals within the same
team agree in their perceptions of a team characteristic. In team and group level research,
it is the most often used measure for determining the extent to which there is sufficient
agreement across the members of each team to justify aggregating the data from
individual to higher levels of analyses. ICC(2) indicates the extent to which the
aggregated, team level measures are reliable. The F -statistics and their associated
significance test indicate the extent to which there is more between team agreement
compared to within team agreement. In other words, it provides evidence regarding the
extent to which there was more variability in responses to the scales between the teams
compared to within the teams. Finally, rwgg) provides yet another measure of the extent to
which there was high agreement within the groups (i.e., teams) relative to the agreement

between the groups or teams.

98

Table 5

Internal Reliabilities of Study Measures

 

 

 

 

 

 

Scale Individual Level Final Number
Coefficient Alpha of Items

Meta-Task Attention .89 7
Task Learning Attention .93 6
Task Motivation Attention .87 5
Social Comparisons .87 6
Time 1
Team Cohesion .84 4
Team Potency .82 4
Team Viability .87 8
Time 2
Team Cohesion .85 4
Team Potency .82 4
Team Viability .90 8
Table 6
Aggregation Indices for Study’s Team Level Constructs

Scale ICC(l) ICC(2) F/p-value rwgm
Social Comparisons .17 .45 l .82/ .001 1.51
Time 1
Team Cohesion .30 .63 272/001 1.42
Team Potency .31 .64 2.79/ .001 1.44
Team Viability .14 .51 203/001 1.19
Time 2
Team Cohesion .29 .62 264/001 1.42
Team Potency .28 .60 252/001 1.44
Team Viability .20 .40 1.68/01 1.19

 

99

As can be seen in Table 6, there was strong support for aggregating most of the
measures that sought to measure team level constructs to the team level. Most important,
the ICC(l) provides what is perhaps the best evidence of whether or not individual level
perceptions within each team are similar enough to be aggregated into team level
perceptions that could then be used to determine the extent to which the study’s
manipulations had an effect on the teams. In addition, most of the scales’ ICC(2) values
were acceptable based on the criteria provided by Ostroff and Schmitt (1993) (i.e., greater
than .60) and all of the ANOVA tests for the scales provided evidence that there was
significantly more between team variance than within team variance. Unfortunately, the
I'wgg) values for each of the scales were beyond the range acceptable for interpretation.
This occurs when the obtained variance within a group exceeds the expected variance
(James, Demaree, and Wolf, 1984), therefore only the ICC(1), ICC(2), and ANOVA tests
were used to justify aggregating the data to the team level. Despite the strong evidence
justifying aggregating the data, however, such procedures are not without at least one
major limitation.

Specifically, while it is generally thought that aggregate perceptions may have
important and powerful explanatory ability and thus be useful in organizational research
(James, 1982), the fact remains that aggregating data is only appropriate when sufficient
agreement can be demonstrated. Unfortunately this is often difficult to show. For
example, despite the calculation of ICC(l) being the most often employed means of
justifying data aggregation, there is no definitive guidelines on acceptable ICC(l) values
(Ostroff & Schmitt, 1993). James (1982) reported that ICC(l) values typically range fiom

.00 to .50 with a median of .12. Bliese (2000) argued that he believed James (1982)

100

provided overestimates of ICC(l) values and stated that in his own research on US.
Army data, he typically encountered ICC(l) values ranging from .05 to .20. He further
stated that he had never encountered an ICC(l) greater than .30 and that it would be
unlikely to encounter an ICC(l) value greater than .30 in applied field research.

The aforementioned problem therefore provides a dilemma for team researchers
who wish to provide evidence for aggregating individual level data to the team level of
analysis. However, Bliese’s experiences seem to suggest that one might expect ICC(l)
values in experimental research to be close to, or even somewhat higher than, those in
applied field research. In particular, one could argue that given the potential strength of
experimental designs (McClelland, 1997), one should expect levels of within tearn
agreement in between team experimental designs such as the one employed in this study
that are at least similar to, if not higher than, levels of within team agreement in between
team quasi-experimental and non-experimental designs. As such, the ICC(I) values
presented in Table 6 appear to indicate that there is sufficient agreement for aggregating
the individual level data to the team level of analyses. As can be seen in the Table, even
where ICC(l) values are the lowest (e. g., time 1 team viability measures and social
comparison measures), they are still higher than the median value reported by James
(1982) which was likely an overestimated value. Based on the evidence presented in
Table 6 that, in general, supports aggregating the individual level measures into team
level constructs; social comparisons, cohesion, potency, and viability were aggregated to
team level variables.

The means, standard deviations, and zero-order correlations of all of the study’s

individual and team level variables are presented in Tables 7 and 8, respectively. As can

101

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be seen in both of Table 7 and 8, there were relationships among the experimental
conditions ((18-- 1'DC Private/Positive Recipient-DC Private/Positive Observer = --10- P. < .10) SUCh
correlations were expected because the recipient and observer conditions were not
independent. The relationships were a function of the study’s design; persons selected to
directly receive performance feedback could not be observers. More important, these
correlations were not problematic as all participants were randomly assigned to both
teams and experimental conditions.

Manipulation Checks

 

A number of analyses were conducted to examine the saliency of the experimental
manipulations before going forward to analyze the data. The data demonstrate that the
manipulations were relatively successful. Specifically, analyses of the manipulation
check items revealed that 70.3% of those participants who actually received individual
level performance feedback were aware of that fact, but it should also be noted that
43.8% of those who directly received individual level performance feedback perceived
others in their team to have also received feedback. A closer examination of the data
reveal that 78.1% of those directly receiving positively framed individual level
performance feedback were aware that they received feedback and almost all (92.6%)
were aware that the performance feedback was positive. Similarly, 62.5% of those
participants who directly received negatively framed individual level performance
feedback were aware that they received feedback and 86.4% of these participants were
aware that the feedback was negative.

As for the effects of the manipulations on observers, most (72.9%) observers

realized that they did not directly receive individual level performance feedback during

105

the experiment. As expected, about half (45.8%) of the observers believed that some
other member of their team directly received feedback. Of those “observers” in the
private feedback conditions, 84.4% were not aware that any member of the team received
performance feedback thus lending support to the private nature of the performance
feedback provided in these conditions. On the other hand, 75.8% of those observers in
conditions in which a team member was publicly provided with individual level
performance feedback realized that fact. Of these observers, all who observed the
provision of positive feedback to one of their team members realized that the feedback
was in fact positive, while 82.4% of those observing the provision of negative feedback
to one of their team members realized that the feedback was negative.

While the manipulations could have been more effective (i.e., more salient to the
research participants), overall these data suggested that I could proceed with the data
analyses as planned. In the sections that follow, I describe each of the proposed tests and
the results of the tests of the study’s hypotheses. It should be noted that each of the
study’s hypotheses, predicted mediated effects of the feedback interventions on
individual task performance and team social outcomes. As such, the description of the
results from each test first describes the effects of the feedback interventions on the
mediating variables (i.e., self- and task-focused attention or social comparisons). Next, I
describe the effects of the feedback manipulations on the more distal outcomes (i.e.,
individual task performance or team social outcomes). In this way, the description of the
results is consistent with the method of testing for mediation outlined by Baron and
Kenny (1986). In addition, this method of describing the results allows me to discuss any

direct effects that may have been found for the feedback interventions on the study’s

106

outcome measures, whether or not there was support found for the full mediation
hypotheses. In cases in which I could not justify testing the mediation aspect of the
hypotheses, I discuss this and then go on to discuss the direct effects of the feedback
interventions only.

Hypotheses land 1b

Hypotheses 1a and 1b, the first set of hypotheses, sought to test predictions
derived from feedback intervention theory and examined the effects of directly receiving
individual level performance feedback in the context of a team on task performance,
regardless of the sign of the feedback. Hypothesis 1a predicted that regardless of the sign
of the performance feedback, the direct experience of being publicly provided with
individual level performance feedback would have a negative effect on task performance,
an effect that would be partially mediated by both increased self-focused attention and
decreased task-focused attention. Hypothesis lb predicted that regardless of the sign of
the performance feedback, the direct experience of being privately provided with
individual level performance feedback would have a positive effect on task performance,
an effect that would be partially mediated by both decreased self-focused attention and
increased task-focused attention.

The above hypotheses predicted that the effects of publicly and privately provided
performance feedback on task performance are mediated, in part, by both self- and task-
focused attention. As such, the test of these hypotheses employs the Baron and Kenny
(1986) method of testing for mediation. Several multiple and hierarchical mediated
regressions were used to test the above hypotheses. First, two multiple regressions

analyses were conducted—one for self-focused attention and the other for task-focused

107

attention. The predictors were eight dummy-coded variables created to represent both the
experimental condition of the participant and whether or not the participant was a direct
feedback recipient, an observer, or in a control group. While each of the hypotheses
independently concerned the effects of public (Hypothesis 1a) and private (Hypothesis
lb) feedback on direct recipients, the creation of the eight dummy-coded variables
allowed me to obtain more information from the regression analyses (e. g., it allowed me
to examine the effects of public feedback that is positively versus negatively framed). In
addition, the dummy-coding scheme employed here made more efficient use of the
regression technique and the study’s sample.

The first regression, regressed self-focused attention on the eight dummy-coded
predictors. Similarly, the second regression regressed task-focused attention on the eight
dummy-coded predictors. Support for Hypothesis 1a would have been contingent on first
finding evidence of the effect for being a direct recipient in both the public/positive
feedback condition and the effect for being a direct recipient in the public/negative
feedback condition was positive and significant on self-focused attention and negative
and significant on task-focused attention. Support for Hypothesis 1b would have been
contingent on first finding evidence of the effect for being a direct recipient in both the
private/positive feedback condition and the effect for being a direct recipient in the
private/negative feedback condition was negative and significant on self-focused
attention and positive and significant on task-focused attention.

These analyses preceded the hierarchical mediated analyses described below, as
suggested by Baron and Kenny (1986), which fithher examined the direct and indirect

effects of the feedback interventions. Two sets of hierarchical mediated regressions, one

108

to test the mediating effects of self-focused attention, the other to test the mediating
effects of task-focused attention, were used to further test these hypotheses. Specifically,
in Steps 1a, post-feedback task performance was regressed on pre-feedback task
performance. In Steps 2a, three dummy-coded variables constructed to indicate whether
the participant was assigned to either the DMl, DM2, or DM3 station were entered into
the regression as control variables. As previously mentioned, the task was designed so
that each team member, would experience exactly the same tracks during each task (in
terms of the number of tracks, the power of the tracks, and their point of entry within
each quadrant) both within and between teams and between the first and second tasks.
However given the random determination of both the tracks’ entry times and the order of
the waves in each task, depending on which station the team member was assigned, there
was the possibility that there were differences across the stations in terms of opportunities
to attack enemy tracks. In Steps 3a, eight dummy-coded variables created to represent
both the experimental condition of the participant and whether or not the participant was
a direct feedback recipient, an observer, or in a control group were entered into the
regression to test whether or not the feedback interventions had an effect on subsequent
task performance.

The mediation tests followed Steps 1a, 2a, and 3a. Steps la and 2a were first
repeated in Steps 1b and 2b, respectively. Steps 3b added either self-focused or task-
focused attention as a predictor while Steps 4b then added eight dummy-coded variables
from Step 3a to test whether or not the various feedback interventions still had an effect
on subsequent task performance. This method of testing for mediation was consistent

with that pr0posed by Baron and Kenny (1986).

109

Support for Hypothesis 1a would have been indicated if a significant effect for
being a direct feedback recipient in a public feedback condition, regardless of the positive
versus negative nature of the feedback was found in Step 33 of the regressions and after
controlling for self-focused attention the effect was reduced in Step 4b. In addition, the
same significant effect for being a direct feedback recipient in the public feedback
conditions found in Step 3a of the regressions would also have needed to be reduced in
Step 4b of the regressions where task-focused attention served as a control.

Similarly, support for Hypothesis 1b would have been indicated if the effect for
being a direct feedback recipient in a private feedback condition found in Step 3a of the
regressions for self-focused attention was reduced in Step 4b and if the effect for being a
direct feedback recipient in a private feedback condition found in Step 3a of the
regression for task-focused attention was reduced in Step 4b.

Hypothesis la: Effects of Publicly Provided Individual Level Performflcg

Feedback on Direct Recipients’ Self- and Task-Focused Attention

Hypothesis la predicted, in part, that directly receiving individual level
performance feedback publicly would have a positive effect on self-focused attention and
a negative effect on task-focused attention. As can be seen in Table 9, in particular, the
effect for being a direct feedback recipient in the public/positive and the public/negative
feedback conditions, there was only partial support for this aspect of Hypothesis la.
Consistent with FIT, the direct experience of publicly receiving individual level
performance feedback on self-focused attention was positive and significant, however
this was only the case for feedback that was positive (B = .15, Q < .05). There was no

such effect for directly and publicly receiving individual level performance feedback on

110

self-focused attention when the feedback was negatively framed. Also consistent with
FIT, the effect of the direct experience of publicly receiving individual level performance
feedback on task-focused attention was negative and significant but this was only the
case when the feedback was negatively framed (B = -.23, p < .05). The effect of directly
and publicly receiving individual level performance feedback on task-focused attention
was positive and insignificant when the feedback was positive ([3 = .03, p > .05).

Hypothesis la: Effects of Publicly Provided Individual Level Perforrna_n_c_e

Feedback on Direct Recipients’ Task PerformaM

As can be seen in Table 10, Steps la and 1b regressed post-feedback task
performance on pre-feedback task performance to remove any variance that could be
explained in post-feedback task performance that was simply a result of practice from the
first task to the second task. As expected, pre-feedback task performance explained a
significant portion of post-feedback task performance (AR2 = .15, p_ < .05). Steps Za
present the effects of the variables entered into the regression to serve as statistical
controls for the station in which the team member was randomly assigned. As can be seen
on Steps 2a, station assignment did, in fact, explain a significant portion of the variance
in post-feedback task performance (AR2 = .09, p_ < .05), thus supporting these variables
inclusion in the regression analyses as controls. As indicated in Steps 3a of Table 10,
overall the feedback interventions explained a significant, yet small amount of variance

in post-feedback task performance (AR2 = .04, p < .05). While this effect is small, it is

111

 

 

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consistent with Kluger and DeNisi’s (1996) assertion that feedback interventions have
small, but important effects on performance. In fact, it is identical to the effect they
reported in their own meta-analytic review.

Table 10 also reveals that there was no support found for the predicted effects of
publicly provided individual level performance feedback on direct recipients’ task
performance. Specifically, there was no effect for publicly and directly receiving
individual level feedback when it was positively framed ([3 = -.01, p_ > .05) and the effect
for directly receiving individual level performance feedback when it was negatively
framed was significant but in the direction opposite of that predicted (B = .11, p_ < .05).

It was nwessary to find these predicted effects in addition to the effects of
publicly provided performance feedback on self- and task-focused attention to test the
full mediated hypothesis. As previously mentioned, there was a significant effect for
directly and publicly receiving individual level performance feedback on self-focused
attention, however, the failure to find the predicted effect of publicly provided individual
level feedback on direct recipients’ task performance in addition to the failure to find an
effect of self-focused attention on task performance (as can be seen on Step 3b of Table
10) prohibited further tests for the mediating effects of self-focused attention on the
relationship between directly and publicly receiving individual level performance
feedback on task performance. Similarly, while directly and publicly receiving individual
level performance feedback had both a significant effect on task-focused attention and
task performance, task-focused attention did not have a significant effect on task
performance (as can be seen on Step 3b of Table 10) thus prohibiting a complete test for

the mediating effects of task-focused attention.

116

It should be noted that the failure to find significant effects between self-focused
attention and task performance (B = .04, p > .05) and task-focused attention and task
performance ([3 = -.01, p > .05) further prohibited a complete test of the remaining
hypotheses regarding the mediating effects of both self-focused attention and task-
focused attention on both the direct experience of receiving and the indirect experience of
observing the provision of individual level performance feedback in teams on task
performance. As such, only the direct effects of the feedback interventions will be
addressed below in the discussion of the remaining hypotheses.

Hypothesis 1b: Effects of Privéately Provided Individual Level Perfonngigg

Feedback on Direct Recipients’ Self- and Task-Focused Attention

Hypothesis 1b predicted, in part, that directly receiving individual level
performance feedback privately would have a positive effect on task performance, an
effect that would be partially mediated by both self- and task-focused attention. Table 9
also presents part of the results for the test of this hypothesis where it can be seen that the
effect for being a direct feedback recipient in either the private/positive or
private/negative feedback conditions had no significant effects on either self-focused
attention or task-focused attention.

Hypothesis 1b: Effects of Privately Provided Individual Level Performance

Feedback on Direct Recipients’ Task Performance

As can be seen in Table 10, there was partial support found for the effects of
privately provided individual level performance feedback on direct recipients’ task
performance. The regression analyses, which make a distinction between privately and

directly provided feedback that is positive compared to that which is negative indicate

117

that, somewhat consistent with Hypothesis lb, there is an positive and marginally
significant effect of privately and directly receiving positively framed individual level
performance feedback in teams on task performance (B = .10, p_ < .10) however this was
not the case when the feedback was negatively framed.

Hypotheses 2a and 2b

Hypotheses 2a and 2b sought to test predictions derived from control theory and
examined the effects of directly receiving individual level performance feedback in the
context of a team on task performance, regardless the private versus public context in
which the feedback was provided. Hypothesis 2a predicted that regardless of the private
versus public context in which the feedback was provided, individual level performance
feedback that was negatively framed would have a positive effect on task performance,
an effect that would be partially mediated by increased self-focused attention and
increased task-focused attention. Hypothesis 2b predicted that regardless of the private
versus public content in which the feedback was provided, individual level performance
feedback that was positively framed would have a negative effect on task performance,
an effect that would be partially mediated by decreased self-focused attention and
decreased task-focused attention. These hypotheses were also tested using the multiple
and hierarchical mediated regressions in Tables 9 and 10, respectively.

Similar to Hypotheses 1a and 1b, these hypotheses also predicted that the effects
of performance feedback on task performance were mediated, in part, by both self- and
task-focused attention. As such, the tests of these hypotheses also employed the Baron
and Kenny (1986) method of testing for mediation. Several multiple and hierarchical

mediated regressions were used to test the hypotheses. First, two multiple regressions

118

analyses were conducted—one for self-focused attention, and the other for task-focused
attention. As before, the predictors were eight dummy-coded variables created to
represent both the experimental condition of the participant and whether or not the
participant was a direct feedback recipient, an observer, or in a control group.

The first of these regressions, regressed self-focused attention on the eight
dummy-coded predictors. Similarly, the second regression, regressed task-focused
attention on the eight dummy-coded predictors. Support for Hypothesis 2a would have
been contingent on first finding evidence of an effect for being a direct recipient in both
the private/negative feedback condition and an effect for being a direct recipient in the
public/negative feedback condition was positive and significant on self-focused attention
and positive and significant on task-focused attention. Preliminary support for Hypothesis
2b would have been indicated if the effect for being a direct recipient in both the
private/positive feedback condition and the effect for being a direct recipient in the
public/positive feedback condition was negative and significant on self-focused attention
and negative and significant on task-focused attention.

The remaining test of these hypotheses proceeded in a manner similar to that of
the tests of Hypotheses 1a and 1b. Two sets of hierarchical mediated regressions, one to
test the mediating effects of self-focused attention, the other to test the mediating effects
of task-focused attention, were used. In Steps 1a, post-feedback task performance was
regressed on pre-feedback task performance. In Steps 2a, three dummy-coded variables
constructed to indicate whether the participant was assigned to either the DMl , DM2, or
DM3 station was entered into the regression as control variables. Steps 3a added eight

dummy-coded variables created to represent both the experimental condition of the

119

participant and whether or not the participant was a direct feedback recipient, an
observer, or in a control group to test whether or not the feedback interventions had an
effect on subsequent task performance.

The mediation tests followed Steps 1a, 2a, and 3a. Steps 1a and 2a were first
repeated in Steps 1b and 2b, respectively. Steps 3b added either self-focused or task-
focused attention as a predictor while Steps 4b then added the eight dummy-coded
variables from Step 3a to test whether or not the various feedback interventions still had
their hypothesized effects on subsequent task performance.

Support for Hypothesis 2a would have been indicated if the effect for being a
direct feedback recipient in a negative feedback condition found in Step 3a of the
regressions for self-focused attention was reduced in Step 4b and if the effect for being a
direct feedback recipient in a negative feedback condition found in Step 3a of the
regression for task-focused attention was reduced in Step 4b.

Finally, Hypothesis 2b would have been supported if an effect for being a direct
feedback recipient in a positive feedback condition found in Step 3a of the regressions for
self-focused attention was reduced in Step 4b and if the effect for being a direct feedback
recipient in a positive feedback condition found in Step 3a of the regression for task-
focused attention was reduced in Step 4b.

Again, according to the procedure outlined by Baron and Kenny (1986), to justify
testing the full mediation hypotheses presented above, there would first have to be
significant effects found in the first set of regressions (those examining the effects of the
feedback interventions on self- and task-focused attention, in addition to significant

effects for self-focused attention and task-focused attention on task performance in Steps

120

3b. As mentioned, this was not the case; therefore, for each of the hypotheses, I first
describe the effects of the feedback interventions on self- and task-focused attention then
I describe the effects of the feedback manipulations on individual task performance.
Thus, I will discuss any direct effects that may have been found for the feedback
interventions on direct recipients’ task performance, as there was no evidence justifying
tests of the full mediated hypotheses.

Hypothesis 2L Effects of Negatively Framed Individual Level Perfom

Feedback on Direct Recipients’ Self- and TaggFocused Attention

Hypothesis 2a implied that directly receiving negatively framed individual level
performance feedback would have a positive effect on self-focused attention and a
positive effect on task-focused attention. Table 9 shows that there was virtually no
support for this hypothesis. Specifically, the effects of being a direct feedback recipient
of negatively framed individual level performance feedback on self-focused attention was
positive but not significant for feedback that was privately provided (B = .05, p > .05) and
there was no effect of being a direct feedback recipient of negatively framed individual
level performance feedback on self-focused attention for feedback that was publicly
provided. Contrary to the predictions of Hypothesis 2a, the effects of directly receiving
negative individual level performance feedback on task-focused attention on task-focused

attention was negative regardless of whether the feedback was provided in private (B = -

.06, p_ > .05) or in public (B = -23, p < .05).

121

Hypothesis 2a: Effects of Negatively Framed Individual Level Performance

Feedbagkon Direct Recijgients’ Taglflerfomm

As shown in Table 10, there was partial support found for the predicted positive
effect of directly receiving negative feedback on task performance as negatively framed
and publicly provided individual level performance feedback had a significant effect on
task performance (B = .1 l, p < .05), however the effect was not significant when the
feedback was privately provided (B = -.04, p > .05).

Hypothesis 2b: Effects of Positively Framed Individual Level Performance

F eedbgc_k on Direct Recipients’ Self- and TefloFocused Attention

Hypothesis 2b predicted, in part, that the direct experience of being provided with
positive individual level performance feedback would have a negative effect on self-
focused attention and a negative effect on task-focused attention. As can be seen in Table
9, this aspect of the hypothesis received no support. Specifically, while Hypothesis 2a
implied that the effect of directly receiving positive individual level performance
feedback would be negative on self-focused attention, there was no effect on self-focused
attention when the feedback was provided in private (B = .02, p_ > .05) and a positive
effect on self-focused attention when the feedback was provided in public (B = .15, p <
.05). Positively framed individual level feedback that was directly experienced had no
significant effects on task-focused attention, regardless of the context in which is was

provided as can be seen in Table 9.

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Hypothesis 2b: Effects of Positively Framed Individual Level Performanae

Feedfllaon Direct Recipients’ Task PerformflLe

Hypothesis 2b, the final hypothesis regarding the effects of directly received
individual level performance feedback predicted that positively framed individual level
performance feedback would have a negative effect on task performance, regardless of
the context in which the feedback was provided. There was no support for this hypothesis
as also indicated in Table 10, where it can be seen that positively framed individual level
performance feedback that was privately provided actually had a marginally significant
effect on task performance that was opposite of the predicted direction (B = .10, p < .05)
and virtually no relationship on task performance when the feedback was publicly
provided (B = -.01, p > .05).
Summary of Effects of the Feedback Interventions on Direct Recipients’ Self- Ed flak;
Focused Attention

In summary, there was limited support for the effects of directly receiving
individual level performance feedback in a team context on self- and task-focused
attention. Of the effects found, they appear to partially support the predictions derived
from FIT. In particular, the public provision of individual level performance feedback
had a significant, positive effect on self-focused attention, consistent with FIT, however
this was only the case when the feedback was positively framed. Also consistent with
FIT, the public provision of individual level feedback to a team member had a negative
effect on that team member’s task-focused attention. Both of these findings were found to

be contingent on the sign of the feedback however. There was no support for control

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theory’s predictions in these data. A more thorough presentation of the implications of
these findings will be presented later in the study’s discussion.
Summary of the Effects of the Feedback Intervention_sg Direct Recipients’ Task
Performance
In summary, there was no support for the mediating effects of either self- or task-

focused attention on the effects of directly receiving individual level performance
feedback on task performance, contrary to all of the hypotheses. There was however,
partial support for the hypotheses derived from feedback intervention theory and those
derived from control theory. The results suggest a contingency with both theories. As
hypothesized, privately provided individual level performance feedback had a positive
effect on task performance, but only when it was positively framed. Also as predicted,
negatively framed individual level performance feedback had a positive effect on task
performance, but only when it was publicly provided. The theoretical and practical
implications of these findings appear in the discussion that follows this chapter.
Hypotheses 3

Hypothesis 3 was the first of the study’s hypotheses dealing specifically with the
effects of individual level performance feedback on those who indirectly experienced
(i.e., observed the provision of) feedback to another while working in the context of a
team. This hypothesis was derived from both FIT and social cognitive theory and while
ignoring the sign of the feedback, predicted positive effects of the indirect experience of
observing the public provision of individual level performance feedback to another team
member on observer’s task performance, effects that would be partially mediated by both

decreased self-focused attention and increased task-focused attention.

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Since this hypothesis also predicted a mediated relationship between the feedback
intervention and task performance, it was tested similar to the previous hypotheses and
used multiple and hierarchical mediated regressions as shown in Tables 9 and 10. Unlike
Hypotheses 1a, lb, 2a, and 2b, which concerned the direct feedback recipients in the
teams (of which there were 64 of them), Hypothesis 3 concerned only the observers in the
teams. There were 192 actual observers total given that there were three observers in each
of the experimental teams (3 multiplied by 64 experimental teams).

The first regressions used to test Hypothesis 3, regressed self-focused attention
and task-focused attention on the eight dummy-coded variables created to represent both
the experimental condition of the participant and whether or not the participant was a
direct feedback recipient, an observer, or in a control group. Initial support for
Hypothesis 3 would have been indicated if the effect for being an indirect feedback
recipient (i.e., observer) in both the public/positive feedback condition and the
public/negative feedback condition was negative and significant on self-focused attention
and positive and significant on task-focused attention.

The remaining tests of this hypothesis were the same hierarchical and hierarchical
mediated regressions used to test Hypotheses la, 1b, 2a, and 2b. As mentioned above,
Steps 1a regressed post-feedback task performance on pre-feedback task performance.
Steps 2a added three dummy-coded variables constructed to indicate whether the
participant was assigned to either the DMl, DM2, or DM3 station. Steps 3a added eight
dummy-coded variables created to represent both the experimental condition of the
participant and whether or not the participant was a direct feedback recipient, an

observer, or in a control group.

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As also previously mentioned, in this set of regressions, mediation tests followed
Steps la, 2a, 3a in subsequent Steps 1b, 2b, 3b, and 4b. While Steps 1b and 2b were
identical to Steps 1a and Steps 2a, respectively, Steps 3b added either self-focused or
task-focused attention as a predictor while Steps 4b then added the eight dummy-coded
variables from Step 3a to test whether or not the various feedback interventions, and in
particular, those concerning the effects of observing the provision of individual level
feedback, still had an effect on subsequent task performance.

Further support for Hypothesis 3 would have been indicated if a significant effect
for being an indirect feedback recipient in a public feedback condition, regardless of the
private versus public nature of the feedback was found in Step 3a of the regressions and,
after controlling for self-focused attention, the effect was reduced in Step 4b. In addition,
the same significant effect for being a direct feedback recipient in the public feedback
conditions found in Step 3a of the regressions would also have needed to be reduced in
Step 4b of the regressions where task-focused attention served as a control. Again, to
justify testing the full mediation hypotheses, however, there would first have to be
significant effects for being an indirect feedback recipient found in the first set of
multiple regressions, in addition to significant effects for self-focused attention and task-
focused attention (Steps 3b) on task performance consistent with the mediation test
proposed by Baron and Kenny (1986).

Hypothesis 3: Effects of Publicly Provided Individual Level Performm

Feedback on Observers’ Self- and Task-Focused Attention

Turning again to Table 9, it can be seen that there was no support for the

predicted (and implied) direct effects of publicly provided individual level performance

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feedback on observers’ self- and task-focused attention. Contrary to FIT, the sign of the
performance feedback did matter. As the table indicates, publicly provided individual
level performance feedback had a significant, but positive effect on observer’s self-
focused attention (B = .13, p < .05), but only when it was positively framed. Publicly
provided feedback had no effect on observer’s self-focused attention when it was
negatively framed (B = -.02, p > .05). As it relates to the effects of publicly provided
individual level performance feedback on observer’s task-focused attention, consistent
with FIT, the sign of the feedback was unimportant, however, the effect was not
significant and in the opposite direction from that predicted (B = -.06, p > .05).

Hypothesis 3: Effects of Publicly Provided Individual Level Perforrmga

Feedbfikr on Observers’ Task Performance

Hypothesis 3 predicted that regardless of the sign of the performance feedback,
the effects of the indirect experience of observing the public provision of individual level
performance feedback would have a positive effect on task performance that would be
partially mediated by both decreased self-focused attention and increased task-focused
attention. However, as previously mentioned, the failure to find significant effects
between self-focused attention and task performance (B = .04, p > .05) and task-focused
attention and task performance (B = -.01, p_ > .05) prohibited a full test of the mediated
hypothesis. Thus, as with the effects of the feedback interventions on direct recipients’
task performance, only the direct effects of the feedback interventions on observers are
discussed below.

Turning back to Table 10, it can be seen on Steps 3a that there was partial support

for this aspect of the hypothesis. In particular, observing the provision of publicly

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provided individual level performance feedback did, in fact, have a positive effect on the
task performance of observers when it was negatively framed (B = .12, p < .05). There
was no significant effect for observing the provision of publicly provided individual level
performance feedback on the task performance of observers when it was positively
fi'amed (B = .03, p > .05).
Supglemental Analyses

Finding so few effects regarding the effects of the experimental conditions (for
both those who directly experienced the individual level performance feedback and those
who indirectly experienced the feedback by observing its provision) on task performance,
raised the possibility of two potential problems. First, there was the possibility that the
task performance measure utilized in the above analyses might have been problematic. In
particular, the overall task performance measure used in the previous analyses may have
been too distal a performance outcome given that the feedback intervention dealt
specifically with performance on the wave tracks only. Second, given that the
manipulation checks revealed that the manipulation was only somewhat successful, it was
possible that the predicted effects may have been found if I were to only analyze a subset
of the study’s participants—namely, only those who were successfully manipulated. The
sections that follow describe, in detail, two sets of independent, supplemental (post-hoe)
analyses that were conducted to evaluate these possibilities. The first set of supplemental
analyses use wave track performance rather than overall task performance as the
performance measure, or dependent variable. These analyses were conducted for each of
the analyses in which overall task performance was regressed on the experimental

conditions. The second set of supplemental analyses uses only those participants that

128

correctly (based on the condition in which they were randomly assigned) responded to
the each of their manipulation check items.

Supplemental Anialyses: Wave Traci Performanch as the Dependent M

Wave track performance, like overall task performance, was operationalized as
the number of good attacks (i.e., attacks made on enemy tracks with a vehicle with the
same amount of power as the enemy track) and waste attacks (i.e., attacks made on
enemy tracks with a vehicle with more power than the enemy track) made by the
participant, however this number was only calculated on the tracks that entered the
participant’s quadrant of the forbidden zone during his or her wave attack. In addition, an
additional principal components analysis was conducted to obtain the appropriate weights
for the variables used to calculate the composite. The resulting principal component
equation was PC = .675 (good attacks) + .767 (waste attacks) which was similar to that of
the planned analyses, however, it can be seen that waste attacks are even more predictive
of performance during wave attacks. Moreover, waste attacks are more important than
good attacks when participants experienced waves. This was expected given that the clear
objective during wave attacks was to destroy the tracks as quickly as possible using
whatever resources were available to prevent the wave tracks from occupying the highly
restricted area for extended periods of time. It should be remembered that each DM had
limited time and resources for accomplishing this end, so good performers recognized the
need to deploy their most powerful resources to the forbidden zone during wave attacks
and use less discretion with them as it related to which tracks to have the sub-platforms

destroy.

129

The supplemental analyses yielded results almost identical to those in the initial
analyses. In other words, the experimental conditions explained no more variance in task
performance when task performance was operationalized as wave track performance than
they did when task performance was operationalized as overall task performance (as
originally planned). Specifically, the experimental conditions explained 4.5% of the
variance in wave track performance compared to the 4% of the variance they explained in
overall task performance.

As it relates to the effects of directly experiencing individual level performance
feedback in the context of a team, the significant effect for directly receiving positively
framed individual level performance feedback in the original analyses (B = .10, p < .10)
was similar to that found in the supplemental analyses (B = .11, p < .10). There was a
similar consistency in the effect of publicly receiving negatively framed individual level
performance feedback in the original analyses compared to that found in the
supplemental analyses (B = .11, p < .05 compared to B = .16, p < .01, respectively).

Turning to the effects of indirectly experiencing (i.e., observing the provision of)
individual level performance feedback, the effect that was found in the original analyses
for observing the public provision of negatively framed individual level performance
feedback to another team member (B = .12, p < .05) was larger but consistent with that
found in the original analyses when I used wave track performance as the dependent
variable (B = .20, p < .01). In addition, there was only one additional effect found—a
significant positive effect for being an “observer” in the feedback condition in which a
fellow team member privately received negatively framed individual level performance

feedback. In the original analyses, this effect was not significant as expected (B = .04, p >

130

.05), but it was marginally significant in the supplemental analyses (B = .11, p_ < .10).
Given that the direct feedback recipient in this condition received his or her feedback in
private, there is no clear explanation for performance improvements on the part of the
other members of these teams (i.e., observers).

Supplemental Anglyses: Reduced Sample

As previously mentioned, the study’s manipulations were relatively successful
however there was considerable room for improvement. A more extensive examination of
the manipulation check items revealed that only 60% of the study’s participants correctly
answered all of the manipulation check items based on the condition in which they were
randomly assigned. Take for instance, participants who were randomly assigned to a team
in which the highest performing team member was to privately receive positive
individual level performance feedback. Those who were feedback recipients should have
indicated that 1) at some point after the training, they received feedback from the
experimenter on their task performance, 2) the feedback they received was positive, and
3) no other person in their team received such feedback. On the other hand, observers in
this condition should have indicated that 1) they did not receive any feedback from the
experimenter at any point after the training and 2) no other person in their team received
feedback. Another example is those participants in a team in which the highest
performing team member was to publicly receive positive individual level feedback. In
such case, those who were observers should have indicated that 1) they did not receive
any feedback from the experimenter at any point afier the training and 2) some other

person in their team did in fact receive feedback afier the training. Additionally, these

131

participants should have indicated the correct member of the team as the feedback
recipient and correctly identified the positive or negative nature of the feedback.

Given that 40% of the participants failed to correctly answer all of their
manipulation check items, I reexamined the data using a reduced sample of only those
participants who were manipulated as intended. However, before conducting this
analysis, I first determined how many participants correctly answered all of their
manipulation check items. Next, I examined the data to determine what, if any patterns,
account for the shortcomings of the manipulations. Specifically, I conducted analyses to
determine whether or not differences across the study’s four experimenters and/or
differences across the experimental conditions could explain the apparent failed
manipulations.

An examination of the data indicated that the manipulations were not successful
for a large number of the study’s participants. Of the 320 participants, 181 correctly
answered each of their manipulation check items, 127 incorrectly answered at least one of
the their manipulation check items, and 12 failed to provide an answer for at least one of
their manipulation check items. In other words, according to this more stringent criteria
for evaluating the success of the manipulation, only 60% of the study’s participants were
successfully manipulated.

When examined across the four experimenters, it seems that none of the
experimenters were overly successful in manipulating the participants in the teams in
which they were responsible with them each individually having 43%, 56%, 60%, and
66% of their participants correctly answer all of their relevant manipulation check items.

Further there was considerable variance across the experimenters with the most

132

successful experimenter having 66% of his or her participants correctly answer all of
their manipulation check items while the least successful experimenter having 43% of his
or her participants correctly answer all of their manipulation check items. It should be
noted though that while the percentage of successfully manipulated participants across
the experimenters did in fact vary, the overall lack of success across all the experimenters
(even the best experimenter successfully manipulated less than 2/3 of his or her
participants) nevertheless suggests that the manipulations themselves, rather than the
experimenters, might have been what presented the biggest problem in the study.

An additional analysis was conducted to determine what, if any, patterns in the
data might explain the failure of the study’s manipulations. For this analysis, I examined
differences in the number of successfully manipulated participants across the study’s
conditions. These results seemed to suggest that the manipulations themselves were
problematic, in particular those targeted to direct feedback recipients. Specifically, 56%,
31%, 31%, and 37% of the direct feedback recipients in the private/positive,
public/positive, private/negative, and public/negative feedback conditions, respectively,
correctly answered all of their manipulation check items. As for the observers, 74%,
57%, 70%, and 43% of the observers in the private/positive, public/positive,
private/negative, and public/negative feedback conditions, respectively, correctly
answered all of their manipulation check items. Finally, 73% of those participants in the
control condition correctly answered each of their manipulation check items. These
results suggest that the manipulations were not as effective as hoped.

It should be noted that one might be tempted to conclude that the seemingly

unsuccessfiil nature of the study’s manipulation might have been less a function of a

133

failing on the part of the manipulations, but rather a function of participants’ fatigue or
carelessness since all of the manipulation check items were given at the end of the study
and were placed near the end of a relatively long, 248-item survey the survey instrument.
For this study, the manipulation check items were intentionally placed near the end of the
survey to eliminate the possibility that they would adversely affect the study’s integrity
by cueing participants to the study’s purpose. Unfortunately, the placement of these items
near the end of the survey in addition to the amount of time that participants had already
devoted to the task itself does raise the possibility that participants may have simply
rushed through the items or perhaps were tired of participating in the study, and thus took
less care in answering the manipulation check items.

While this represented a reasonable guess as to why the responses could have
been so inaccurate, I dismissed this possibility since if this was in fact the case, one
would expect the accuracy to vary less across the experimental conditions. In other
words, if either fatigue and/or carelessness led to the apparent lack of success of the
manipulation, one would not expect the level of variation in the number of participants
who correctly answered all of their manipulation check items to vary so much across the
conditions as was observed in these data. For example, the least effective conditions (in
terms of the accuracy on the participants assigned to these conditions on their
manipulation check items) were those in which participants directly received
public/positive and private/negative feedback (31% were accurate on all items). In
comparison, the most effective condition was that in which the participants were assigned
to the condition where the direct feedback recipient in their team privately received

positive feedback (74% were accurate on all items).

134

Given the problems with the effectiveness of the manipulation, I therefore
reduced the sample to just those participants who correctly answered each of their
manipulation check items to better examine whether or not the provision of individual
level performance feedback in teams had more of an impact on the task performance of
those who both directly received it and those who observed its provision. In addition, I
sought to determine if using only the reduced sample might eliminate the unanticipated
and unexplainable significant correlation found between post-feedback overall task
performance and being an “observer” in a team in which the direct feedback recipient
privately received positively framed individual level performance feedback (r = -.14, p <
.05, see Table 7). The reduced sample was composed of 181 participants that were
accurate on all of their manipulation check items. As for the supplemental analyses of the
data, I reran the hierarchical regression presented in Table 10 and unfortunately gained no
additional insight into the data and the effects of the manipulations.

While using just the reduced sample eliminated the significant correlation
between post-feedback task performance and being an “observer” in a team in which the
direct feedback recipient privately received positive individual level performance
feedback (from r = -. 14, p_ < 05 to r = -.04, p > .05), the regression results proved to be no
real improvement over that of the original analyses. In particular, the regression using the
reduced sample explained 36% of the variance in overall task performance compared to
27% explained in the original analysis and this additional variance explained was
attributed primarily to a larger effect for being a direct recipient of publicly provided,
negatively framed individual level performance feedback (B = .27, p < .01 compared to B

= .l 1, p_ < .05 from the original analysis). Moreover, no effects were found for any of the

135

other experimental conditions on participants’ overall task performance and the two
previous steps of the regression (i.e., that predicting post-feedback task performance with
pre-feedback task performance and that predicting post-feedback task performance with
DM station assignment as control variables) yielded identical results.

In sum, while it was fruitful to adjust the sample size by taking into consideration
only those participants that were successful recipients of the manipulation, the results of
the supplemental analyses did not provide any additional insights into the lack of effects
for the experimental conditions beyond the conclusion that the effects were simply small
in nature. Moreover, all of these analyses were conducted post-hoc and given the small,
and arguably insignificant, differences in the results yielded from the original analyses
compared with that of the supplemental analyses, only the original, planned analyses are
discussed in the chapter that follows. The remaining a priori hypotheses are presented in
the sections below. These hypotheses go beyond more object task performance measures
and concern the effects of the experimental conditions on social outcomes in the teams.
Hypotheses 4gb, and 4c

The study’s final hypotheses predicted that providing individual level
performance feedback in teams would have a negative effect on levels on cohesion
(Hypothesis 4a), viability (Hypothesis 4b), and potency (Hypothesis 4c) in teams and that
these effects would be mediated by increased levels of social comparisons in teams. As
such, these hypotheses implied that there would be a significant, positive effect of
providing individual level performance feedback in teams on levels of social comparisons
in teams. This aspect of the hypotheses, while addressing a theoretically interesting

relationship in-and—of-itself, sets the stage for the full test of the hypotheses which sought

136

to examine the mediating effects, if any, that social comparisons in teams have on the
relationship between the provision of individual level performance feedback in teams and
team social outcomes.

To test these hypotheses, a multiple regression and hierarchical mediated
regression analysis was employed using the eighty teams. The multiple regression
predicted social comparisons levels in the teams. Given that the level of social
comparisons in each team was the dependent variable of interest, the predictors were the
experimental conditions in which each team experienced. As such, four dummy-coded
variables were created to represent the experimental condition in which the team was
randomly assigned. That is, four dummy-coded variables were constructed that accounted
for the study’s four experimental conditions. There was no dummy-coded variable for the
effects of being in the control condition as these teams served as the reference group in
the regression analysis.

The regression contained one step in which social comparisons were regressed on
the four dummy-coded predictors. Support for Hypotheses 4a, 4b, and 4c would have
been contingent on there first being evidence of positive and significant effects found for
being in the experimental conditions on levels of social comparisons in the teams.

The hierarchical mediated regressions followed. Steps 1a regressed post-feedback
measures of each team social outcome on each of their respective pre-feedback measures.
Steps 2a added four dummy-coded variables created to represent the experimental
condition in which the team was assigned. Given the hypothesized mediating effects of
social comparisons on the effects of the feedback conditions on the team social outcomes,

the mediation tests followed Steps 1a and 2a in subsequent Steps lb, 2b, and 3b. Steps 1b

137

are identical to Steps la. Step 2b added social comparisons to the analyses while Steps 3b
then added the four dummy-coded variables from Step 2a to test whether or not the
various feedback conditions still had an effect on subsequent task performance.

Support for Hypothesis 4a, 4b, and 4c would have been further indicated if there
was a significant effect for each of the various feedback conditions on team cohesion
(Hypothesis 4a), team viability (Hypothesis 4b), and team potency (Hypothesis 4c) in
Steps 2a of the regressions and those effects were no longer significant in Steps 3b after
controlling for social comparisons in Step 2b of the regression. Consistent with Baron
and Kenny’s (1986) method of testing for mediation, there would first have had to be
significant effects found in the first multiple regressions, in addition to significant effects
for social comparisons on team cohesion, viability, and potency, Hypotheses 4a, 4b, and
4c, respectively, to justify testing the full mediation hypotheses.

Hypothesis 4: Effects of the Feedback Interventions on Social Comparisons in

Igams

As can be seen in Table 11, there was no support for the implied effects of the
feedback interventions on levels of social comparisons in teams. Overall the provision of
individual level performance feedback in teams, did not explain a significant amount of
variance in social comparisons (AR2 = .06, p > .05).

Hypothesis 4: Effects of the Feedbaik Intervention_s on Team Cohesion, Viability.

and Potency

Given that there was no support for the predicted effects of the feedback
interventions on social comparisons in teams, there was no support for testing for the

mediating effects of social comparisons on the relationship between the provision of

138

individual level performance feedback in teams and team social outcomes. In other
words, the failure to find support for the more proximal effects of the feedback
interventions precludes a full test of the remainder of the study’s hypotheses. As a result,
only the direct effects of the feedback interventions on team social outcomes are
discussed below.

Table 12 presents the results of three hierarchical mediated regression analyses
that were used to test each of the hypotheses. Steps 1a regressed post-feedback levels of
each of the social measures on each of their respective pre-feedback levels. In Steps 2a,
the four dummy-coded variables created to represent the experimental condition the
teams were assigned were entered into the regression analyses. As mentioned, the
mediation tests followed in Steps 1b, 2b, and 3b however they will not be discussed given
the inability to support any mediation given the lack of effects of the feedback conditions
on social comparisons discussed above.

Hypothesis 4a: Team Cohesion. As can be seen in Table 12, pre-feedback levels
of team cohesion predicted almost all of the variance in post-feedback levels of team
cohesion (AR2 = .83, p_ < .05). Overall, the feedback interventions only predicted an
additional 1% of the variance in post-feedback levels of team cohesion (AR2 = .01, p >
.05). While all of the effects were in the predicted direction only the public provision of
negatively framed individual level performance feedback had a significant effect on post-
feedback levels of team cohesion (B = -.13, p_ < .05). Therefore there was very limited
support for Hypothesis 4a.

Hypothesis 4b: Tezfl Viability. Turning to Hypothesis 4b, which predicted negative

effects of providing individual level performance feedback on levels of team viability,

139

there was no support for this hypothesis as also seen in Table 12. Similar to team
cohesion, pre—feedback levels of team viability explained almost all of the variance in
post-feedback levels of team viability (AR2 = .73, p_ < .05) (Step 1a). The addition of the
dummy-coded variables representing the various feedback conditions in Step 2a yielded
almost no additional variance explained in post-feedback levels of team viability (AR2 =
.01, p_ > .05). Table 12 further shows that of the effects of providing individual level
performance feedback to a member of the teams, none were significant.

Hypothesis 4c: Team Potency. Finally, Hypothesis 40 which predicted that
providing individual level performance feedback in teams would have a negative effect
on team potency received no support. Pre-feedback levels of team potency explained
much of the variance in post-feedback levels of team potency (AR2 = .68, p < .01) as seen
in Step la of Table 12, while the addition of the dummy-coded variables representing the
feedback conditions explained only an additional 1% of the variance in post-feedback
levels of team potency. Further, none of the effects were significant.

Summmf Effects of the Feedback Interventions on Team 8031 Outcomes

In summary, there was no support for the mediating effects of social comparisons
on the effects of the provision of individual level performance feedback on team social
outcomes. In addition, there was virtually no support for any direct negative effects of
providing individual level performance feedback to a member of the team on social
outcomes. The only support found was a significant, negative effect of publicly providing

a team member with negative individual level performance feedback on team cohesion.

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CHAPTER SEVEN: DISCUSSION

This study sought to explore the effects of individual level performance feedback
on the direct and indirect feedback recipients in teams by testing several hypotheses
derived from a number of theoretical frameworks, all of which seemed to suggest the
implications of providing individual level performance in teams. Kluger and DeNisi’s
(1996) Feedback Intervention Theory (FIT) in addition to Carver and Schier’s (1981)
control theory provided the theoretical frameworks for examining the effects of directly
receiving such feedback in teams. FIT and control theory both predicted that feedback
interventions influence task performance through the attention that the feedback
interventions direct to both the self and the task, however, the nature of these effects
differed dependent on the theoretical framework.

FIT predicted that, dependent on the public versus private nature of the
performance feedback, more or less attention would be directed to both the self and the
task. Specifically, FIT predicted that public feedback interventions would increase
attention to the self and decrease attention to the task while private feedback
interventions would decrease attention to the self and increase attention to the task. FIT
further predicted that increased attention to the self would have a detrimental effect on
task performance and increased attention to the task would have positive effect on task
performance. Moreover, since FIT makes no explicit mention of the sign of the feedback,
the aforementioned predictions did not take into consideration the positive versus
negative nature of the feedback.

Control theory, on the other hand, focused primarily on the sign (positive versus

negative nature) of the feedback, with negatively framed performance feedback directing

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more attention to the self and to the task and positively framed performance feedback
directing less attention to the self and the task. Control theory further predicted a positive
relationship between both self- and task-focused attention and task performance (i.e.,
increased attention to the self and increased attention to the task both positively influence
task performance while decreased attention to the self and decreased attention to the task
both have detrimental effects on task performance).

The control theory predictions, however, are based on what the theory would
predict for those who directly receive the performance feedback and ignore the potential
effects that observing the provision of individual level performance feedback to a fellow
team member may have on the task performance of those who indirectly experience the
feedback by observing its provision. Turning to these effects (i.e., those on the
observers), social cognitive theory and an extension of FIT provided some insight into
how being privy to the provision of individual level performance feedback might
influence the task performance of observers—a situation that is made possible when
individuals work in a social context such as a team and when individual level
performance feedback is publicly provided. Social cognitive theory suggested that
individuals do not have to directly experience feedback in order to learn from it (or in this
case experience performance improvements). In fact, social cognitive theory suggested
that much of the learning (and performance improvements) that occurs in social contexts
occurs from learning indirectly from the experiences of others. Further, FIT predicted that
the indirect experience of observing a fellow team member receive individual level
performance feedback would influence the task performance of observers, through its

direct effects on observers’ self- and task-focused attention. Specifically, FIT predicted

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that observing the public provision of individual level performance feedback, regardless
of the sign of the feedback, would decrease attention to the self and increase attention to
the task. Again, F IT further predicted that decreased attention to the self would have a
positive effect on task performance and increased attention to the task would have
positive effect on task performance. Again, since FIT makes no explicit mention of the
sign of the feedback, these aforementioned effects did not take into consideration the
positive versus negative nature of the feedback.

Finally, the study here attempted to explore what effects, if any, the provision of
individual level performance feedback would have on the social dynamics and
functioning in teams, as a number of scholars have insisted that singling out the
individual performance of an individual who is working in a social context such as a team
would have negative effects on the team’s social outcomes. It has further been suggested
that the negative effects of providing individual level performance feedback on team
social outcomes would occur through its direct effects on the extent to which the team
members engage in social comparisons with one another.

The theoretical model presented in Figure 4, which was based on the theoretical
relationships described above between individual level feedback interventions and task
performance and social outcomes, received very limited support in the test of the data
presented in the previous chapter. As expected, it appears that the effects of feedback
interventions on the task performance of those who directly receive them is small
however the effects that were found do not provide overwhehning support for one
theoretical foundation over another. Moreover, the provision of individual level

performance feedback had very few effects on direct feedback recipients’ self- and task-

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focused attention therefore suggesting that whatever effects the direct provision of
performance feedback had on team members’ task performance is not completely
mediating, if mediated at all, by self— and task-focused attention. There was only little
support found for the hypothesized effects of observing the provision of individual level
performance feedback on observers’ task performance and these effects were not
mediated by either self- or task-focused attention. Finally, there was almost no support
found for the hypothesized negative effects of providing individual level performance
feedback in teams on teams’ subsequent social dynamics. Each of these effects will be
discussed in more detail below. The one effect that was found was not mediated by social
comparisons.
Effects of Feedbagk Interventions on Self-Focused Attention

Effects on Direct FeedbaleKecipients

Following both FIT and control theory, the model predicted that directly receiving
individual level performance feedback in the context of a team would influence direct
feedback recipients’ self-focused attention, however the nature of this effect differed
depending on the theoretical framework. FIT predicted that public feedback interventions
would increase direct feedback recipients’ attention to self while private feedback
interventions would decrease their attention to self. These predictions placed no emphasis
on the sign of the feedback. Control theory, on the contrary, placed specific emphasis on
the sign of the feedback, and predicted that regardless of the public versus private context
of the feedback, self-focused attention would be increased when the feedback was

negative and decreased when the feedback was positive.

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Neither of these two conflicting theories received overwhehning support in these
data, as the feedback interventions had almost no effects on direct recipient’s self—focused
attention, however the one effect that was found was found suggests that both theories
ignore an important component of the feedback as it relates to the provision of individual
level performance feedback in teams.

In particular, it was found that the public provision of individual level
performance feedback increased attention to the self however this was only the case when
the feedback was positive. In other words, team members who were singled out in the
presence of the rest of their team, commended on their performance, and told that the
performance strategies they used were critical in improving the team’s overall
performance, focused more attention on demonstrating their skills and abilities and thus
maintaining other’s perceptions of themselves. This finding is consistent with FIT,
however is it contrary to control theory as these individuals did not decrease their
attention to self. Control theory predicted that these individuals would become “de-
motivated” so-to-speak and disengage from the process of devoting attention to
demonstrating their competence on the task (i.e., fail to maintain a particular perception
of themselves and their performance), which control theory goes on to predict can be
harmful to task performance.

Interestingly, the positive effect of publicly receiving individual level
performance feedback on self-focused attention was not found for those who publicly
received negatively framed feedback, as the public provision of negative feedback had no
effect whatsoever on direct feedback recipients’ self-focused attention. This finding was

inconsistent with both FIT and control theory and has some important theoretical

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implications. Clearly, it suggests that not all publicly provided feedback increases self-
focused (or what Kluger & DeNisi, 1996 would refer to as meta-task attention). Further,
it suggests that only publicly provided positive feedback leads team members to try to
maintain that impression of themselves and consequently, devote attention to their selves.
In other words, it appears that positively framed public feedback leads individuals to
perceive that they are accountable for maintaining the perception of being competent on
the task in front of others. In this study, negatively framed public feedback did not have
the same effects. Team members who received such feedback did not appear to devote
attention to creating better impressions of themselves and their task-related skills and
abilities. More important, this finding suggests that FIT may be limited in its
predictability, at least in its current form, as it fails to make explicit the importance of the
sign of the feedback. The differential effects of positively and negatively fi'amed
performance feedback highlight this potential deficiency.

Effects on Observers

The model proposed here also predicted that observing the provision of individual
level performance feedback to another team member would influence the extent to which
the observers directed attention to self. The hypotheses developed in regards to the
potential effects of the observing provision of performance feedback to a fellow team
member were based on both social cognitive theory and FIT and suggested that observing
another team member receive individual level performance feedback would influence the
observer via the decreased attention it would direct toward the observers own self (i.e.,

meta-task) attention. Very little support was found that supported this hypothesis.

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Contrary to FIT, observing the provision of individual level performance
feedback to another member significantly increased observers’ self-focused attention
when the feedback was positively flamed. Only when the feedback was negatively
flamed did it affect observer’s attention in the predicted direction, however this effect
was not significant. Thus, again, these data seem to suggest that an important future
direction for the development of FIT is to place more importance on the sign of the
feedback as positively and negatively flamed individual level performance feedback had
different effects on self-focused attention in this study.

Beyond the theoretical contributions that these findings make towards the
development of FIT, these findings also suggest some interesting practical implications.
In particular, it appears that even those team members who are not the direct feedback
recipients of individual level performance feedback when one individual in the team is
singled out and provided such feedback are, to at least a small extent, affected by the
feedback. In this study, those team members who observed a team member being
commended for their good performance, directed their attention to creating their own
perceptions of being a competent performer. This seems to suggest that rewarding one
individual in a team for his or her performance may result in fostering self-consciousness
among the other members of the team. Observing a team member being singled out for
his or her poor performance, on the other hand, apparently had no effect on team
members’ need to prove themselves to be competent performers suggesting that perhaps
the absence of directly received individual performance feedback when a fellow team
member is singled out for his or her poor performance leads others to perceive that they

are performing well.

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Effects of Feedba_c_l_( Interventions on Task-focused Attention

Effects on Direct Feedback Recipients

The model also predicted, following both FIT and control theory, that directly
receiving individual level performance feedback in the context of a team would influence
direct feedback recipients’ task-focused attention. Again, the nature of this effect differed
depending on the theoretical flarnework. Turning first to FIT, FIT predicted that,
regardless of the sign of the feedback, public feedback interventions would decrease
direct feedback recipients’ attention to the task while private feedback interventions
would increase their attention to self. Control theory, on the other hand, specifically
addressed the sign of the feedback and predicted that task-focused attention would be
increased when the feedback was negative and decreased when the feedback was
positive, regardless of the context in which the feedback was provided.

The predictions derived from FIT were partially supported, while none of control
theory’s predictions were supported in these data. Specifically, only one significant effect
was found for directly receiving individual level performance feedback on task-focused
attention. In particular, only publicly provided negatively flamed feedback influenced
direct feedback recipients’ task-focused attention, and this effect was negative. Again,
this finding suggests that any theory that seeks to determine how the provision of
individual level performance feedback affects those working in team contexts must
consider both the sign of the feedback and the context in which it is provided.

Consistent with FIT, the public provision of individual level performance
feedback led to decreased attention to the task, however this was only the case when the

feedback was negatively flamed. Thus, in this study, those who, while in the presence of

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others, directly received performance feedback that indicated that they were performing
poorly, focused less on the task-at-hand. These individuals appeared to become less
concerned with the amount of effort they put toward the task and less concerned with
better learning the appropriate task performance strategies. This effect was not found
when the feedback was positively flamed.

The negative effect of publicly receiving negatively flamed performance feedback
on task-focused attention was opposite of control theory’s predictions as was the finding
that privately provided, negatively flamed performance feedback had a negative,
although not significant effect on task-focused attention. These findings suggest that the
context in which the feedback is provided might offer some important boundary
conditions for the predictions made by control theory, in that control theory clearly
suggested that negative feedback loops that indicate that performance standards are not
being met should have led feedback recipients to direct more attention to the task, and
thus minimizing the gap between their performance and their performance standards. As
such, the findings of this study provide interesting insights regarding both control and
FIT theories.

Effects on Observers

Based on social cognitive theory and FIT, the model predicted that observing the
provision of public individual level performance feedback would lead observers to direct
more attention to the task. While social cognitive theory predicted that team members
would learn flom feedback even when were not the direct recipients of that feedback, this
prediction was based primarily on the FIT and what it suggests about the effects of

feedback that is publicly provided in a social context such as a team. Specifically, FIT

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predicted that feedback observers would be more likely to divert attention to the task
when they merely observed its provision unlike those who directly received it who would
be more likely to have their attention diverted to creating and maintain perceptions of
their selves.

These data provided no support for this prediction as all of the observers in this
study directed less attention to the task after being privy to the public provision of
individual level performance feedback to a singled out member of the team. This, in
combination with the previously discussed findings, suggests that the public provision
may not only direct attention away flom the task for those who directly receive the
feedback but also those who observe its provision. As such, these data raise some
questions regarding the validity of some of F IT’s predictions.

As an aside, it is interesting to note the empirical relationship between self- and
task-focused attention observed in these data. As shown in Table 7, self-focused attention
and task-focused attention were positively and significantly correlated (r = .58, p < .01).
While the positive nature of their relationship is consistent with Carver and Scheier’s
(1998) theoretical discussions of the self- and task-focused attention (e. g., the authors
stated that self-focus is often associated with task-focus and that increases in self—focus
can promote increases in task-focus), it should be noted that there was no a priori reason
to believe that empirically the relationship between the two would be so strong.
Moreover, the positive nature of this relationship is inconsistent to the theoretical
discussions of Kluger and DeNisi (1996) in that their discussion of FIT, namely their
discussion of meta-task, task-learning, and task-motivation processes, suggested that the

relationship between self-focused attention and task-focused attention is negative.

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Specifically, FIT argues that attention devoted to the self takes away attention that can be
devoted to the task. The conflicting predictions regarding the relationship between self-
focus and task-focus are interesting and there are a number of possible reasons why such
a strong positive relationship was found between the two in these data.

First, it is possible that one or both of the measures (self- or task-focused
attention) were not accurate, or valid, measures. Fortunately, I included an additional
measure of self-focused attention, one that was adapted flom a measure designed by
Fenigstein, Scheier, and Buss (1975). The Festigstein et al. measure is a commonly used
self-focus scale that purports to measure self-focused attention as a stable and
dispositional difference (Hollenbeck & Williams, 1987). There was no other, backup,
measure of task—focused attention used in this study. When self-focus was measured with
the Fenigstein et al. (1975) measure, the relationship between self-focused attention and
task-focused attention, while lower (r = .43 compared to r = .58) was no less statistically
significant. While this finding does not eliminate the possibility that the task-focused
attention measure was problematic in this study, it more likely suggests that self- and
task-focused attention are in fact positively related to each other.

The possibility that there is in fact a positive relationship between self- and task-
focused attention deserves even more support in light of the fact that, in these data, there
appears to be at least some support for the discriminant validity between the two
constructs as they were measured in this study. For example, while self- and task-focused
attention were highly related to one another, only self-focused attention was significantly
affected by the direct and public receipt of positively flamed feedback (r = .13, p < .05)

while there was no effect on task-focused attention (r = .07, p > .05). Similarly, only task-

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focused attention was significantly affected by the direct and public receipt of negatively
flamed feedback (r = -.19, p < .01) while there was no effect on self-focused attention (r
= -.04, p > .05). Taken together, it appears that the results of this study lend support to
Carver and Scheier’s (1998) notion that self-focused attention, rather than interfering
with task-focused attention, actually promotes it, contrary to FIT.

Carver and Scheier (1998) suggested that researchers should take care to
distinguish between discussions of self-focus in which self-focus is used to represent
negative rumination (i.e., a focus on self-doubt and perceptions of inadequacy) flom
those in which self-focus is used to represent attention directed inwards as in self-
regulation. Thus, it appears that either 1) the present study failed to clearly distinction
such rumination flom FIT’s meta-task attention, 2) FIT should better articulate how
meta-task attention is distinct flom Carver and Scheier’s notion of self-focus, or that 3)
FIT may make some incorrect theoretical predictions regarding the relationships between
attention to meta-task processes, task-learning processes, and task-motivation.
Nevertheless, it is clear that this subject deserves more empirical attention, as a review of
the literature on self-focused attention and task-focused attention failed to produce any
published studies that have explicitly examined the empirical relationship between the
two constructs.

Effects of Feedbaflrterventions on Esk Performance

Effects on Direct Feedback Recipients

As seen in Figure 4, the model also predicted that directly providing individual
level performance feedback to a member of a team would influence the team members

task performance. These effects were predicted to be mediated by the attention directed to

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both self- and task-focused attention. There was no support whatsoever for the mediated
effects of either self- or task-focused attention, however the provision of such feedback
did have some direct effects on direct recipients’ task performance.

FIT predicted that, regardless of the sign of the feedback, publicly provided
feedback would negatively influence direct recipients’ task performance, while privately
provided feedback would positively influence direct recipients’ task performance. These
hypotheses (Hypotheses la and 1b) received partial support in this study. As predicted by
FIT, privately provided individual level performance feedback did, in fact, have a
marginally significant, positive effect on direct recipients’ task performance. However,
this was only the case when the feedback was positive. There was no support found for
FIT’s prediction that publicly provided individual level performance feedback would
have a negative effect on direct feedback recipient’s task performance.

The above findings, however, must be examined in light of the findings regarding
control theory’s predictions that, regardless of the context in which the feedback is
provided, negatively flamed individual level performance feedback would have a positive
effect on direct feedback recipients’ task performance while positively flamed individual
level performance feedback would have a negative effect on direct feedback recipients’
task performance. In this study, contrary to control theory, positively flamed feedback
had a marginally significant, positive effect on direct recipient’s task performance when
it was privately provided. On the other hand, consistent with control theory, negatively
flamed individual level performance feedback had a significant, positive effect on direct

feedback recipients’ task performance when it was publicly provided.

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Taken together, these data suggest that neither FIT nor control theory present a
complete picture of the effects of feedback interventions as it relates to the provision of
individual level performance feedback in team contexts. Specifically, FIT’s failure to
address the sign of the performance feedback, and control theory’s failure to speak to the
context in which the feedback is provided, limit both of the theories’ predictability. The
results of this study, clearly suggest that there is an interaction among the predictions of
the two theories in regards to the effects of feedback interventions on task performance in
teams. Privately provided individual level performance feedback had a positive effect on
direct feedback recipients’ task performance, however this was only the case when it was
positively flamed. Negatively flamed individual level performance feedback had a
positive effect on direct feedback recipients’ task performance, however only when the
feedback was publicly provided. In fact, publicly provided, negative individual level
feedback had the most significant effects on direct recipients’ task performance during
task #2.

The theoretical implications of these findings are clear. FIT and control theory
both have boundary conditions that each ignores. Moreover, the theories have the ability
to inform each other, in that when one takes into account the factors that each of the
theories ignore, significant insight is gained into the effects that individual level feedback
interventions have on the individual task performance of those working in team based
work structures. These data make clear the fact that neither theory has a monopoly on
valid predictions as it regards the effects of feedback in teams. Future attempts towards
understanding the implications of providing individual level performance feedback in

teams should therefore take into account, at the least, both the sign of the feedback in

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addition to the context in which it is provided. The fact that these effects (those for
privately provided, positive flamed feedback and for publicly provided, negatively
flamed feedback) were not mediated by either self- and task-focused attention however,
highlights that there remains aspects of both FIT and control theory that deserve further
empirical attention and perhaps even theoretical refinement.

As for what happened in these data, in particular the effects found for the
feedback interventions on performance, it is important to note that these effects were not
mediated by either self- or task-focused attention. In fact, the results of this study failed
to provide support for partially mediated effects for either self- or task-focused attention.
This finding, while unexpected, suggests that the provision of individual level
performance feedback can have some effects on direct recipients’ task performance in
teams however the effects are due to some other mediating mechanism or mechanisms
not measured in this study.

In light of the specific effects that were found in regards to those who directly
received the individual level performance feedback in this study (i.e., those direct
feedback recipients in the private/positive and public/negative conditions), there are a
number of potential mediators that might have played some role in affecting, more
proximally, the task performance of direct feedback recipients. Those participants who
received positive feedback in private, while not necessarily trying to maintain positive
perceptions of their performance with the other members of their group, might have
attempted to maintain those positive perceptions with regards to their experimenter.
While the experimenter did present somewhat of an audience, thus potentially triggering

some of the negative effects of social facilitation (Zajonc, 1965) and other forms of self-

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maintenance, the fact that there was only an audience of one for these participants (i.e.,
one experimenter who was not an actual member of the team) might have led to a
situation unlike that created when one is attempting to maintain a perception, or
impression, with a larger group of vested others. Stated another way, the effort put into
managing impressions in flont of a group of others might not be detrimental to task
performance when the “others” are smaller in number and less connected to the actual
task and its outcomes.

Unfortunately, the failure to find any significant effects of this experimental
condition on direct feedback recipients self-focused attention in addition to the
unsuccessful nature of the manipulation makes it difficult to draw such a conclusion
(only 56% of these participants correctly answered each of their manipulation check
items), however it is worth noting that the private/positive condition was the most
successful of the experimental manipulations on direct feedback recipients. Thus, it
appears that directly receiving private/positive feedback had no significant effects on
self-maintenance activities therefore future research should examine other potential
mediators of the effects of individual level performance feedback on task performance on
individuals working in groups beyond those typically considered when examining the
effects of performance feedback on individuals working alone.

At the least, the findings of this study reaffinn the importance of the feedback
context in that effects that one might expect to find when studying individuals working
were not found when studying individuals working in teams despite strong theoretical
arguments and empirical support at the individual level. Again, and as previously

discussed, the majority of what scholars and practitioners know about the effects of

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performance feedback on task performance has been learned in contexts in which
individuals worked alone, unlike the context studied here. The theoretical flarneworks
used to develop the theoretical model tested in this study, in particular FIT, may not
readily apply to situations in which one is dealing with teams of interdependent
individuals rather than individuals working alone. Further, given the relative newness of
FIT, it might be worthwhile for researchers to first test its predictions at the individual
level prior to testing it at the team level. This would seem especially appropriate given
that there are currently no published empirical studies that set out, a priori, to test FIT’s
predictions.

As for the direct recipients of negative feedback that was given publicly, the
increases in their task performance might be attributed to increased perceptions of
accountability. Clearly, these participants found out first hand that there were unpleasant
repercussions for performing poorly. Specifically, they were singled out in flont of the
rest of their team and told how unsuccessfully they had performed. Oddly, this seemed to
have no effect on their levels of self-focused attention despite strong theoretical
hypotheses to the contrary. Moreover, receiving such feedback had a significant, negative
effect on their task-focused attention. Thus, while it appears that these individuals
disengaged flom the task, they nevertheless improved perhaps since they felt an
obligation to the team, rather than themselves, the experimenter, or the task itself. Future
research should explicitly examine the potentially mediating role of accountability on the
relationship between individual level feedback and task performance in teams. This
finding suggests that researchers should consider whether the predictions made by both

FIT and control theory hold across multiple levels of analysis.

160

Beyond the theoretical questions and implications raised by the results of this
study, the data also suggest some interesting practical implications as well. Contrary to
popular belief, it appears that providing positively flamed feedback is not the de-
motivator that it has historically been believed to be. This is particularly the case when
the feedback is privately provided, as individuals who directly received privately
provided and positively flamed individual level performance feedback in this study
improved in task #2. This finding was inconsistent with control theory in that it predicted
that these individuals would have not reason to improve as the discrepancy between their
performance and their performance standards would indicate that they have already met
or exceeded their performance standard. Yet in this study, these individuals still
experienced performance improvements that could not be explained simply by practice
effects.

Effects on Observers

Social cognitive theory in addition to FIT provided the theoretical underpinnings
of the model’s predictions regarding the effects of observing the provision of individual
level performance feedback to a fellow team member on the task performance of other
members of the team who were privy to its provision. The model predicted that when
publicly provided, individual level performance feedback directed to another member of
the team would lead to increased levels of task performance among those who observed
its provision. This hypothesis was partially supported in these data, yet the results of this
study again bring to light the fact that there are boundary conditions that FIT fails to
address, namely the sign of the performance feedback. In this study, observers

experienced the largest effect of the provision of individual level performance feedback

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in teams, however this effect was found only when the feedback was negatively flamed
and publicly provided. Observers in this condition significantly improved during task #2,
an effect that could not be accounted for solely by practice effects on the task. While this
provides both some support and theoretical insights for FIT, perhaps what is most
interesting are the practical implications of this finding.

A number of scholars have suggested that singling out an individual team member
for his or her individual task performance can have debilitating effects on a team as a
whole while they have failed to consider the performance improvements that can
potentially occur among those who are privy to the provision of such feedback. The
results of this study demonstrate that observers can in fact experience increases in their
own performance, simply from being present when such feedback is provided. This is
particularly the case when the feedback is negative. As discussed in previous chapters,
this is an important oversight, as it fails to consider the learning, and subsequent
performance improvements, that can occur via indirect experiences. Social cognitive
theory places specific emphasis on these opportunities and these data highlight the
benefits of this indirect experience.

Further, since these effects were not mediated by either self- or task—focused
attention, it might again be fluitful for researchers to consider other potential mediators
such as accountability since it would seem reasonable to believe that observers, having
observed a fellow team member receive negatively flamed performance feedback, which
as discussed in previous chapters operates as a form of punishment, felt it necessary to
improve themselves if they believed that they themselves might be singled out for their

performance in the future. It also seems plausible that these observers, rather than

162

perceiving increased accountability for their own performance, may have felt the need to
maintain perceptions of themselves as adequate, if not good, performers since the absence
of their own individual level feedback may have led them to believe that their
performance was, at the least, satisfactorily. However, in these data, these observers’ self-
focused attention was not affected by having observed the provision of individual level
performance feedback to another member of their team. Thus, accountability seems to
again be a potential mediator that deserves future attention flom researchers. Finally, it
deserves mention that while it seems very possible that accountability is a likely mediator
of the effects of having observed a team member publicly receive negatively flamed
performance feedback, it is difficult to make specific predictions about what might have
happened given the unsuccessful nature of the study’s manipulations.
Effects of F eed_ba£k Interventions on Social Comparisons

Turning now to the team level effects of providing individual level performance
feedback in teams, this study sought to test whether or not the provision of individual
level performance feedback in teams actually has negative effects on social dynamics and
functioning in teams as often suggested by a number of scholars (e. g., Smither, 1998).
One particular goal of this study was to examine whether the hypothesized negative
effects on team social outcomes were actually mediated by increased levels of social
comparisons among the members of the teams in which a member of the team received
individual level performance feedback. As a first step, the study examined the effects of
providing individual level performance feedback on levels of social comparisons in

teams.

163

The model predicted, in part, that the provision of individual level performance
feedback to a member of the team would lead to increased levels of social comparisons in
teams, in particular when the feedback was publicly provided. While these data showed
that there were, in fact, higher levels of social comparisons in teams in which individual
level performance feedback was publicly provided, the effects were not significant, thus
failing to provide empirical support for this prediction. This finding precluded a test for
the mediating effects of social comparisons in teams on the relationship between the
provision of individual level performance feedback and team social outcomes, however it
does suggest that publicly providing such feedback does in fact lead to, at least some,
increased levels of social comparisons in teams. The fact that these effects were not
statistically significant, however, demonstrates that scholars may be overly concerned
with the effects of providing individual level performance feedback on subsequent social
comparisons made in teams. Further support that scholars may have unfounded concerns
about social comparisons is provided in these data which reveal that social comparisons
are positively, rather than negatively related to team social outcomes (see Table 8).
Effects of Feedback Interventions on Team Social Outcomes

Finally, the model predicted that the provision of individual level performance
feedback would have detrimental effects on various aspects of social functioning in
teams. These effects, as previously mentioned, were hypothesized to be mediated by
social comparisons in teams, however the failure to find significant effects of the
feedback interventions on social comparisons precluded a full test of these hypotheses.
Therefore, only the direct effects of the feedback interventions on team social outcomes

are discussed below.

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The model predicted that the provision of individual level performance feedback
would negatively affect team cohesion, team viability, and team potency. These data
reveal that there was virtually no support for any of these hypotheses. The only
significant effect found was for the influence of publicly providing negatively flamed
individual level performance feedback to a team member on the teams’ sense of
cohesion. This effect was negative as hypothesized however the feedback interventions as
a whole only predicted an additional one percent of the variance in team cohesion.
Further it should be noted that almost all of the variance in team cohesion, team viability,
and team potency during task #2 was explained by previous levels of team cohesion,
team viability, and team potency, respectively thus indicating that there was little, if any,
changes in these team outcomes that could be explained by the experimental
manipulations. Therefore, the provision of individual level performance feedback to a
member of the teams, in this study, had no effect on team social outcomes. Thus, it
appears that the admonitions of team scholars who recommend against the provision of
individual level performance feedback to those working in teams are largely unwarranted.
In this study, team social outcomes were not affected by the provision of individual level
performance feedback to a member of their team.

It should be noted, however, that in this study attempts to elucidate the effects of
providing individual level performance feedback on team social outcomes is further
complicated by the fact that overall there were no changes in team social outcomes flom
task #1 to task #2. While this may have been due to stability in these outcomes across the
two tasks, one cannot dismiss the possibility that it was due to the teams not being able to

accurately perceive any measurable differences in the team social outcomes flom task #1

165

to task #2. In other words, the inability to explain any significant incremental variance in
team cohesion, viability, and potency, while potentially due to there simply being no
effect for the provision of individual level performance feedback in teams, might have
been a result of the teams’ inability to discriminate between high and low levels of each
of these outcomes in the teams.

Moreover, it is very likely that participants in this study were unable to
discriminate not only between high and low levels of team cohesion, viability, and
potency, but also among the three constructs altogether. While a confirmatory factor
analysis of the data revealed that the three team social outcomes all loaded on separate
factors, the fact remains that they were all highly correlated (see Table 8). Such high
correlations among each of the team social outcomes suggests that one should be cautious
in interpreting the results of this study as it relates to the effects of the feedback
manipulations on team social outcomes.

Unfortunately, this is a potential problem of research of this nature—team level
research using participants who are working together for a short duration of time on a
hypothetical task (e. g., laboratory teams). As such, it would be wise for this hypothesis to
receive further empirical examination under more realistic and longitudinal conditions.
Indeed, it may have been the case that when working together for a period of only three
hours the participants of this study had little information to base their responses to
questions about the extent to which they share a common fate, their potential for working
together in the future, and their perceptions of the extent to which their teams would be
effective. This clearly raises some concern about the finding that the provision of

individual level performance feedback has no effects on team cohesion, viability, and

166

potency, respectively. Other potential study limitations are considered and discussed in
the section below.
Study Limitations

While the findings of this study, or lack thereof, suggest both some interesting
theoretical and practical implications, the study was not without some limitations. One
potential limitation of this study was the laboratory context in which it occurred. In this
study, the individual task performance and team social implications of providing a team
member with individual level performance feedback was examined using undergraduate
student participants working on a computerized military simulation. The research method
allowed for the examination of both objective individual and subjective team outcomes
under conditions of high realism without sacrificing experimental control (Ilgen, 1999).
Unfortunately however, the laboratory setting in which the study occurred raises some
concerns regarding the generalizability of the findings to settings outside of the
laboratory. This is only a potential limitation for several reasons.

First, despite working in the context of a laboratory in which participants may not
develop an overwhelming concern for their team or their individual roles, the participants
worked on a realistic team task with performance-based rewards. In fact, the teams
utilized in this study could be best described as “tactical decision-making teams” in
which 1) team members must make decisions under time pressure and threat; 2) team
members must interact, participate, and coordinate their inputs; and 3) teamwork is
essential to effective team performance (McIntyre & Salas, 1995). The teams therefore
were quite similar to many teams that actually exist in a number of real-world contexts

(e. g., police and military organizations, hospitals, and airline crews). The laboratory

167

context, nevertheless, is one in which one cannot simulate the exact same psychological
processes associated with the levels of urgency that may be involved with such real-
world teams. However, observations of the research participants suggest that they did in
fact take their individual and team roles seriously as indicated by participants’ enthusiasm
regarding the task and participants’ verbally expressed concerns about the rewards.

It is also important to consider the research question when evaluating the
generalizability of the study’s findings. The focus here was on the predictability of
individual task performance and team social outcomes using various types of individual
level feedback interventions. While the teams utilized in this study worked on a
computer-simulated team task in a laboratory setting, there is nothing about the model
and the predictions derived in the previous chapters that would suggest that they would
not hold in a laboratory context. In other words, given the nature of the research
questions, the laboratory provided an appropriate context for theoretically driven,
preliminary examinations of what n_iigl_i_t happen in the field (Ilgen, 1986).

One final limitation of the present study that deserves mention is that fact that
give the nature of the study’s design, only one team member in each of the experimental
teams was actually provided individual level performance feedback. As such, the results
of this study cannot speak to the effects of providing individual level performance
feedback to all members of the team. This is an important limitation since providing
individual level performance feedback to all members of a team may have very different
effects on individual task performance among the team members and team social

outcomes.

168

However, given that the purpose of the study was to examine not only the effects
of the provision of individual level performance feedback on those who directly received
the feedback, but also those who indirectly experienced the feedback by observing its
provision, it was necessary to provide the performance feedback to only a subset of the
members in each of the experimental teams. In this case, one team member directly
received the performance feedback while three team members observed it provision. In
this way, it was possible to test the predictions derived flom social cognitive theory as it
relates to observational learning via vicarious experiences.

This latter limitation, while limiting the generalizability of the findings to only
teams in which one team member is provided with individual level performance
feedback, provided a “strong manipulation” (McClelland, 1997) for examining the effects
of the provision of individual level feedback on team social outcomes. One might expect
that whatever negative effects that providing individual level performance feedback to
team members that indicates that they are exceptionally poor or exceptionally good
performers may have on team social outcomes might be more dramatic when only one
member of the team directly receives such information in the presence of others. In this
way, the fact that only one team member in the teams studied here received individual
level performance feedback, while limited the generalizability of the study’s findings,
does not invalidate the experimental manipulations.

Finally, the deficiencies of the manipulations deserve further mention here as only
60% of the study’s participants correctly answered each of their manipulation check
items. In future studies of this nature, it will be critical for researchers to closely examine

the extent to which the manipulations are in fact effective, consistency across the study’s

169

experimenters, and just as important, clarity of the manipulation check items. Clearly, the
failings of this study’s manipulation make it difficult to both draw conclusions flom the
study’s results and hypothesize about what might explain whatever effects were found.
Summary of Findings Related to the Model

The current debate that exists in the literature regarding the provision of
individual level performance feedback to those working in teams has unfortunately raised
more questions than answers about how to provide feedback to those working in team
based work structures. A number of scholars have suggested that performance feedback
provided to teams should be provided at the team level. Nevertheless, there remains many
reasons for providing individual level performance feedback as well. Current theoretical
developments provide conflicting recommendations about the nature of the feedback that
should be provided, however they also suggest a number of options available regarding
the feedback that could be provided to at the individual level to those working in teams,
namely positive feedback, negative feedback, privately provided feedback, and publicly
provided feedback.

This study sought to explore the influence of each type of feedback on both
individual level task performance and team level social dynamics and functioning. The
findings flom the research conducted here suggest that individual level performance
feedback interventions provided in teams have small, yet significant, effects on the task
performance of both those who directly receive them and those other in teams who
observe their provision. There was partial support for Feedback Intervention Theory’s
predictions regarding the nature of these effects on task performance, however,

inconsistent with the theory, the sign of the feedback was found to be important in

170

explaining the nature of these effects. There was also partial support for control theory’s
predictions regarding the nature of the effects of the feedback interventions on task
performance, however, inconsistent with this theory, the context in which the feedback
was provided proved to be an important factor in explaining the nature of these effects.
As such, it appears that FIT and control theory have the potential to inform each other.
While there were some significant direct effects found for the provision of
individual level performance feedback in teams on the task performance of both those
who directly received the feedback and those who simply observed its provision, there
was no support found for the model’s predictions that these effects were mediated by
self- and task-focused attention. This is a particularly interesting finding in that it
suggests that, at least in team settings, there are other mechanisms operating that
influence the effects of singling out a team member for his or her performance on other
members of the team, individually and the team as a whole. For example, and as
previously mentioned, perceived accountability seems to be one potentially mediating
mechanism. It would be fluitful for future research to explore the existence of other
potential mediating mechanisms. In this way, one might gain additional insight as to how
the provision of individual level performance feedback in teams affects task performance
and perhaps even why the effects are so small.
The study also examined the effects of singling out a team member and providing
him or her with individual level performance feedback on team social outcomes as a
number of researchers have previously suggested that this would have negative effects on
team social fimctioning. Generally, there was no support for this prediction and overall

the provision of individual level performance feedback had no effects on team cohesion,

l7l

team viability, or team potency. This finding is particularly interesting as the social
outcomes examined in the study are thought to be of critical importance to teams
(Campion, et al., 1993; Hackman, 1987). The results of this study suggest that
researchers’ admonitions regarding the social implications of providing individual level
performance feedback in teams might be largely overstated.

This study had two purposes: 1) to determine the effects of providing individual
level performance feedback on the task performance of both direct feedback recipients
and observers and 2) to determine what, if any, negative effects result flom providing
individual level performance feedback in teams on team social outcomes. While the
model of the effects of individual level performance feedback on task performance and
social outcomes received limited support, the findings were nevertheless insightful as
they pointed to some important deficiencies in the theoretical flameworks that the study
compared. As such, this study should provide a useful foundation for future theoretical

development and further research in this area.

172

APPENDICES

173

Appendix A

Discussion of Wave Targets and Goal Setting

174

Discussion of Wave Targets and Goal Setting

We are almost ready to start the actual task. Before we do, there is one other thing that we
have yet to discuss regarding the task—targets that come into the forbidden zone in
waves, or wave attacks in which targets head for the really forbidden zone where they
will sit causing you and your team to lose the maximum amount of points possible.
Effectively dealing with the wave attacks is essential to performing well and is perhaps
the most difficult aspect of this task. Moreover, how well you handle the wave targets
will have a big impact on both your individual and team scores and consequently whether
or not your team will be one of the teams that will eventually earn a prize.

What occurs when wave targets enter the forbidden zone is somewhat similar to what you
have already seen during the training. As before, targets will enter the forbidden zone,
however you have only seen targets enter your quadrant of the forbidden zone one at a
time. During a wave attack, several targets will enter a particular quadrant of the
forbidden zone at the same time thus making it more difficult to identify the targets,
transfer information about those targets if necessary, and then clear them flom the
forbidden zone quickly as to prevent you and your team from losing a lot of points.

You already have been trained on all of the skills required to effectively handle a wave
attack. You should expect several wave attacks during each game and wave attacks can
occur flom any direction. In other words, wave attacks can come flom any one of your
team’s four quadrants therefore any member of your team may be hit with a wave of
targets. To effectively deal with the attack, the team member whose quadrant is the
source of the attack must identify the targets then quickly work to clear them flom the
really forbidden zone. Remember, you do not want targets to stay in the really forbidden
zone too long. The longer the wave targets stay in the really forbidden zone, the worst the
impact on your individual and team scores.

To help you be more effective at the task, I’m going to set three goals related to
performance with the wave targets. If you keep these goals in mind, and try to meet them,
it should help your team perform well.

These goals are as follows:

You should:
1. try to identify all (i.e., 100%) of the wave targets that come through your quadrant
before they reach the really forbidden zone.

You should also:
2. begin attacking the wave attack targets within 1 minute of the onset of the attack

Finally, you should:

35. make sure that no wave attack targets remain in the really forbidden zone longer
than 3 minutes.

175

The team member whose quadrant is the source of the wave attack has primary
responsibility for making sure that these goals are met but others can help. Keep in mind
that while somewhat difficult, all of the above goals are achievable.

Now, there are a couple of things you should do to help ensure that you meet these goals.

The first is regarding your AWACS radar plane. Remember that during the hands-on
training many of the targets came flom the comer of the screen. By keeping your
AWACS near the comers of the task screen, you will be able to see much further than if
you relied only on the detection rings around your bases. The more of the comer that you
can see, the sooner you can tell whether you are being attacked by a wave of targets. You
will find that the sooner you are able to detect a wave of targets entering your quadrant,
the sooner you can begin identifying the targets. Obviously, the sooner you begin
identifying these targets, the more likely that you will have them all identified before they
reach the really forbidden zone.

Another thing you should do is quickly begin sending your most powerful vehicles (i.e.,
your helicopter and tank) to the really forbidden zone as soon as you realize that you are
experiencing a wave attack. Remember, these vehicles are the slowest so the sooner they
are launched, the quicker they can be ready to clear the wave targets flom the really
forbidden zone. You do not want to wait until the wave targets have stopped before
getting these vehicles out on the screen or back into your quadrant to attack the wave
targets. They will be particularly useful for removing wave targets flom the screen.

Finally, you should send your vehicles back to your base immediately afier you use them
to attack wave targets so that they can refuel and reload. 'You should relaunch them
immediately afier the have returned to the base. Again, they are somewhat slow and the
sooner they go back to the base, the sooner they will be ready to use again to clear more
wave targets. I suggest that you send them back to the base as soon as you use them to
attack.

I’ve seen several teams work at this task since I’ve been working in the lab and have
gotten a feel for what constitutes good versus poor performance in dealing with wave
attacks when they occur in your quadrants. Just keep in mind that good performers
identify and attack the wave targets quickly. Good performers also use their own vehicles
to clear enemy targets flom the screen once they have been identified. If you focus on
doing the things I just mentioned, then you should each do well.

176

Appendix B

Feedback Intervention

177

Feedback Intervention

Scripted Positive Performance Feedback

INSERT NAME, you did a good job dealing with the wave targets. Your performance in
particular probably helped improve the team’s score. The positioning of your AWACS
plane near the comer of your quadrant which helped you have more time to identify the
wave targets as they moved toward your quadrant. It seems as if you were able to identify
about 80 percent of targets before they reached the really forbidden zone which is pretty
close to the goal we set of 100 percent.

Being able to anticipate the wave attack early also seemed to help you to begin attacking
the wave targets sooner and you did appear to begin attacking the targets within 1minute
of the onset of the attack as we discussed. 1 also noticed that you were quick to move
your attacking vehicles to the really forbidden zone when you realized that your quadrant
was experiencing a wave attack. And you sent them back to your base to refuel and
reload immediately. Doing these things appeared to help you clear the really forbidden
zone of the wave targets within 3 minutes of the targets stopping in it.

Scripted Negative Performance F eedbaLk

INSERT NAME, you did not do well with the wave targets. Your performance in
particular probably hurt the team’s score. By not positioning your AWACS plane near the
comer of your quadrant you did not have as much time to identify the wave targets as
they moved toward your quadrant. It seems as if you were able to identify about 20
percent of targets before they reached the really forbidden zone which is pretty far flom
the goal we set of 100 percent.

Not being able to anticipate the wave attack early also seemed to keep you flom attacking
the wave targets sooner and you did not appear to begin attacking the targets within 1
minute of the onset of the attack as we discussed. I also noticed that you were slow to
move your attacking vehicles to the really forbidden zone when you realized that your
quadrant was experiencing a wave attack. And you sent them back to your base to refuel
and reload rather slowly. Not doing these things appeared to keep you flom clearing the
really forbidden zone of the wave targets within 3 minutes of the targets stopping in it.

178

Appendix C

Team Member Questionnaire

179

Team Member Questionnaire

Instructions:

The following survey contains several items regarding your attitude towards your team, your
teammates, and the task you will complete. This survey contains several parts, each of which you will
complete only when instructed by your team’s experimenter. Some of the items appear in more than
one part of the survey. This is because your answers to some of the items may change over time as
you spend more time with your team and more time working on the task. There are no right or
wrong answers to any of these questions. It is expected that there will be differences in attitudes
among members of the same team therefore you should not share your answers with any other
members of your team. Any answers you provide are confidential, have no impact on your team’s
performance, and will not affect your eligibility for the cash prizes.

Part I. Pre—Training Questions

Use the following S-point scale to answer questions #1 - 13.

 

1 2 3 4 5
Strongly Disagree Neutral Agree Strongly
Disagree Agree

The following questions concern your attitude towards achievement situations.

I am willing to select a challenging work assignment that I can learn a lot flom.
I often look for opportrmities to develop new skills and knowledge.

I enjoy challenging and difficult tasks at work where I’ll learn new skills.

For me, development of my work ability is important enough to take risks.

I prefer to work in situations that require a high level of ability and talent.

VFW-N?"

I’m concerned with showing that I can perform better than my coworkers.
I try to figure out what it takes to prove my ability to others at work.

I enjoy it when others at work are aware of how well I am doing.

I prefer to work on projects where I can prove my ability to others.

95”."?

10. I would avoid taking on a new task if there was a chance that I would appear rather incompetent to
others.

11. Avoiding a show of low ability is more important to me than learning a new skill.

12. I’m concerned about taking on a task at work if my performance would reveal that I had low ability.

13. I prefer to avoid situations at work where I might perform poorly.

Continue on the next page.

180

Use the following S-point scale to answer questions #14 - 29.

 

1 2 3 4 5
Strongly Disagree Neutral Agree Strongly
Disagree Agree

The following questions concern your attitude towards achievement situations.

14. The things I enjoy most are the things I do best.

15. The opinions others have about how well I can do certain things are important to me.

16. I feel smart when I do something without making any mistakes.

17. I like to be fairly confident that I can successfully perform a task before I attempt it.

18. I like to work on tasks that I have done well on in the past.

19. I feel smart when I can do something better than most other people.

20. Even if I know that I did a good job on something, I’m satisfied only if others recognize my
accomplishments.

21. It’s important to impress others by doing a good job.

22. The opportunity to do challenging work is important to me.

23. When I fail to complete a difficult task, I plan to try harder the next time I work on it.

24. I prefer to work on tasks that force me to learn new things.

25. The opportunity to learn new things is important to me.

26. I do my best when I’m working on a fairly difficult task.

27. When I have difficulty solving a problem, I enjoy trying several different approaches to see which one
will work.

28. On most jobs, people can pretty much accomplish whatever they set out to accorrrplish.

29. Your performance on most tasks or jobs increases with the amount of effort you put into them.

Do not go on to the next page until instructed.

181

Part II. Post-Training Questions
Listed below are a number of events that are related to your development at the task. For each one,
please indicate how desirable it is to you. Use the following scale to respond to questions #30 - 34.

l 2 3 4 5
Undesirable Neutral Desirable

 

30. Improving task performance

31. Improving my self confidence

32. Getting a cash prize

33. Gaining respect flom my teammates
34. Achieving success on the task

Please indicate the degree to which you agree with the following statements regarding your task
skills. Use the following scale to respond to questions #35 - 38.

 

 

l 2 3 4 5
Disagree Neutral Agree
35. I will exert considerable effort to develop my skills.
36. Developing my skills is important to me.
37. I will try hard to develop my skills.
38. It is very important to me to develop my skills.
Use the following 5—point scale to answer questions #39 - 45.
1 2 3 4 5
Strongly Disagree Neutral Agree Strongly
Disagree Agree

The following questions concern your beliefs in your team’s ability to perform and achieve the goals
that were set for its performance on the first task. When responding to the following items, answer in
reference to the entire team’s task-related ability.

39. The team I work with has above average ability.

40. This team is probably poor compared to other teams working on similar tasks.
41. This team is not able to perform as well as it should.

42. The members of this team have excellent task skills.

43. The members of this team should be replaced due to lack of ability.
44. This team is not very effective.
45. Some members in this team cannot complete the task well.

Continue on the nwct page.

182

Use the following 5-point scale to answer questions #46 - 64.

1 2 3 4 ‘

Strongly Disagree Neutral Agree Strongly
Disagree Agree

The following questions concern your beliefs in your own personal ability to perform and achieve the
goals that were set for your performance on the first task. When answering the following questions,
answer in reference to your own personal task skills and ability to perform your role.

46. I have confidence in my ability to perform my role.

47. There are some tasks required by my role that I cannot do well.

48. When my performance is poor, it is due to my lack of ability.

49. I doubt my ability to perform my role.

50. I have all the skills needed to perform my role very well.

51. Most people who complete this task, can perform this role better than I can.
52. I am an expert at my role.

53. My future in this team is limited because of my lack of skills.

54. I am very proud of my skills and abilities as it relates to this task.

55. I feel threatened when others watch me work at this task.

The following questions concern the goals that were set for your performance on the first task.

56. It’s hard to take these goals seriously.

57. It’s unrealistic for me to expect to reach these goals.

58. It is quite likely that these goals may need to be revised, depending on how things go.

59. Quite flankly, I don’t care if I achieve these goals or not.

60. I am strongly committed to pursuing these goals.

61. It wouldn’t take much to make me abandon these goals.

62. I think these goals are good goals to shoot for.

63. I am willing to put forth a great deal of effort beyond what I’d normally do to achieve these goals.
64. There is not much to be gained by trying to achieve these goals.

Use the following numbers to represent different feelings about how often the first word leads to the
second for questions #65 - 71.

1

V

I9
Ji-

1 5
Rarely Sometimes Usually

Below you will see a number of pairs of factors that look like this:
Example: Warm weather —> Sweating

Please indicate how true you feel that it is for you personally that the first word leads to the second
word.

65. Trying hard —> Developing skills

66. Putting forth effort —> Developing skills

67. Developing skills -> Improving task performance

68. Developing skills —-) Improving my self-confidence

69. Developing skills —r Getting the cash prize

70. Developing skills —> Gaining respect flom my teammates
71. Developing skills —-> Achieving success on the task

Do not go on to the next page until instructed.

183

Part III. Post-Task #1 Questions (A)

Use the following 5-point scale to answer questions #72 - 86.

 

1 2 3 4 5
Strongly Disagree Neutral Agree Strongly
Disagree Agree

The following questions concern your attitudes about the team with whom you just completed the
first task.

72. I am willing to put in a great deal of effort beyond that normally expected in order to help this team
be successful.

73. I would talk up this team to my fliends as a great team to work with.

74. I feel very little loyalty to this team.

75. I would accept almost any type of task assignment in order to keep working with this team

76. I would be proud to tell others that I am part of this team.

77. I could just as well be working with a different team as long as the type of task was similar.

78. This team really inspires the very best in me in the way of task performance.

79. I am extremely glad that I was placed into this team rather than another.

80. I really care about the fate of this team.

81. For me this is the best of all possible teams for which to complete the task.

82. Getting myself placed into this team was a definite mistake on my part.

The following questions concern your attitude about your team during the first task.

83. Members of my team have great confidence that the team can perform effectively.

84. My team can take on nearly any task presented while in the laboratory and complete it.
85. My team has a lot of team spirit.

86. I enjoyed working with this team on the task.

Use the following 5-point scale to answer questions #87 - 91.

1 2 3

U

4}.

5
To a small extent To a moderate extent To a large extent

The following questions concern the interaction among your team members during the first task.

87. To what extent did you feel that you are really a part of your team?

88. To what extent would you be willing to work with a different team that was working on the same
task?

89. To what extent did the members of your team get along with each other well?

90. To what extent did the members of your team stick together?

91. To what extent did the members of your team help each other out?

Do not go on to the next page until instructed.

184

Part III cont’d. Post-Task #1 Questions (B)

Use the following 5-point scale to answer questions #92 - 116.

1 2 ’

«Ii

.- 5
To a small extent To a moderate extent To a large extent

At this moment, to what extent are you concerned about each of the following:

92. Your general ability and skills.

93. Demonstrating your abilities to the experimenter.

94. Demonstrating your abilities to your team members.

95. Other’s perceptions of your task abilities.

96. Creating a particular perception of yourself and your general abilities.
97. What your task performance says about you personally.

98. Demonstrating your abilities on something other than this task.

99. Learning the strategies necessary to perform the task.

100. Your understanding of the task.

101. Developing your own strategies for improving your task performance.
102. Increasing your knowledge of the task.

103. Determining the best way to work on the task.

104. The use of appropriate performance strategies.

105. Putting forth the effort necessary to perform the task effectively.
106. The challenge of doing well on the task.

107. Doing the best you can on the task.

108. Motivating yourself to perform well on the task.

109. The rewards associated with successful task performance.

110. Meeting your performance goals for the task.

The following questions concern what your thoughts and feelings at this point in the experiment.
Please respond to each item based on how you are feeling right now.

At this moment, to what extent are you...

1 l 1. concerned about the way your performed?

1 12. concerned about the way your performance appears to others?
113. self-conscious about the way your performed?

114. concerned about making a good impression in front of others?
115. concerned about what other people think of you?

116. aware of your performance?

Continue on the nart page.

185

Use the following 5-point scale to answer questions #117 - 142.

 

l 2 3 4 5
Strongly Disagree Neutral Agree Strongly
Disagree Agree

The following questions concern your beliefs in your team’s ability to perform and achieve the goals
that were set for its performance on the second task. When responding to the following items, answer
in reference to the entire team’s task-related ability.

117. The team I work with has above average ability.

118. This team is probably poor compared to other teams working on similar tasks.
119. This team is not able to perform as well as it should.

120. The members of this team have excellent task skills.

121. The members of this team should be replaced due to lack of ability.

122. This team is not very effective.

123. Some members in this team cannot complete the task well.

The following questions concern your beliefs in your own personal ability to perform and achieve the
goals that were set for your performance on the second task. When answering the following
questions, answer in reference to your own personal task skills and ability to perform your role.

124. I have confidence in my ability to perform my role.

125. There are some tasks required by my role that I cannot do well.

126. When my performance is poor, it is due to my lack of ability.

127. I doubt my ability to perform my role.

128. I have all the skills needed to perform my role very well.

129. Most people who complete this task, can perform this role better than I can.
130. I am an expert at my role.

131. My future in this team is limited because of my lack of skills.

132. I am very proud of my skills and abilities as it relates to this task.

133. I feel threatened when others watch me work at this task.

The following questions concern the goals that were set for your performance on the second task.

134. It’s hard to take these goals seriously.

135. It’s unrealistic for me to expect to reach these goals.

136. It is quite likely that these goals may need to be revised, depending on how things go.

137. Quite flankly, I don’t care if I achieve these goals or not.

138. I am strongly committed to pursuing these goals.

139. It wouldn’t take much to make me abandon these goals.

140. I think these goals are good goals to shoot for.

141. I am willing to put forth a great deal of effort beyond what I’d normally do to achieve these goals.
142. There is not much to be gained by trying to achieve these goals.

Do not go on to the next page until instructed.

186

Part IV. Post-Task #2 Questions

Use the following 5-point scale to answer questions #143 - 157.

 

l 2 3 4 5
Strongly Disagree Neutral Agree Strongly
Disagree Agree

The following questions concern your attitudes about the team with whom you just completed the
second task.

143. I am willing to put in a great deal of effort beyond that normally expected in order to help this team
be successful.

144. I would talk up this team to my friends as a great team to work with.

145. I feel very little loyalty to this team.

146. I would accept almost any type of task assignment in order to keep working with this team.

147. I would be proud to tell others that I am part of this team.

148. I could just as well be working with a different team as long as the type of task was similar.

149. This team really inspires the very best in me in the way of task performance.

150. I am extremely glad that I was placed into this team rather than another.

151. I really care about the fate of this team.

152. For me this is the best of all possible teams for which to complete the task.

153. Getting myself placed into this team was a definite mistake on my part.

The following questions concern your attitude about your team during the second task.

154. Members of my team have great confidence that the team can perform effectively.

155. My team can take on nearly any task presented while in the laboratory and complete it.
156. My team has a lot of team spirit.

157. I enjoyed working with this team on the task.

Use the following 5-point scale to answer questions #158 - 162.

l 2 3

u

4i

5
To a small extent To a moderate extent To a large extent

The following questions concern the interaction among your team members during the second task.

158. To what extent did you feel that you are really a part of your team?

159. To what extent would you be willing to work with a different team that was working on the same
task?

160. To what extent did the members of your team get along with each other well?

161. To what extent did the members of your team stick together?

162. To what extent did the members of your team help each other out?

Continue on the next page.

187

Use the following 5-point scale to answer questions #163 - 173.

1 2 3

U

45

5
To a small extent To a moderate extent To a large extent

The following questions concern any comparisons that may have been made among members of your
team while working on the second task.

163. To what extent did the members of your team show a concern about how much effort each other
put into the task?

164. To what extent did the members of your team corrrpare the effort each other put into the task?

165. To what extent did the members of your team show a concern about how each other perform on the
task?

166. To what extent did the members of your team monitor each other performances during the task?

167. To what extent did the members of your team compare how they individually performed?

168. To what extent did the members of your team seem concerned about their individual outcomes
relative to other members of the team?

169. To what extent did the members of your team ask about each other individual scores?

170. To what extent were you acquainted with DMl before the experiment?
171. To what extent were you acquainted with DM2 before the experiment?

172. To what extent were you acquainted with DM3 before the experiment?
173. To what extent were you acquainted with DM4 before the experiment?

Use the scales below each item to respond to questions #174 - 180. MAKE SURE ALL OF YOUR
ANSWERS ARE ON THE CORRECT LINE OF YOUR SCAN TRON.
174. During the training, did you receive feedback flom the experimenter on your task performance?

l=yes
2=no (if you answer no, leave question #175 blank and go to question #176)

175. Was the feedback you received more positive or negative?
l=positive
2=negative

176. At any point after the training, did you receive feedback from the experimenter on your task
performance?

1 =yes
2=no (if you answer no, leave question #177 blank and go to question #178)

177. Was the feedback you received more positive or negative?

l=positive
2=negative

Continue on the next page.

188

178. At any point afier the training, did any of your fellow team members receive feedback regarding
their task performance?

l=yes
2=no (if you answer no, leave questions #179 and #180 blank and go to question #181)

179. Which team member received the feedback?
l=DM1
2=DM2
3=DM3
4=DM4
5=more than one DM received feedback
180. Was the feedback he or she received more positive or negative?
l=positive

2=negative

Use the following 5-point scale to answer questions #181 - 190.

 

1 2 3 4 5
Strongly Disagree Neutral Agree Strongly
Disagree Agree

The following questions concern your attitudes regarding seeking feedback on your performance
during the experiment.

181. I think my experimenter would have thought worse of me if I had asked him/her for feedback.

182. I would not have been nervous about asking my experimenter how he/she evaluated my behaviors.

183. It is not a good idea to ask your teammates for feedback; they might think you are incompetent.

184. It would have been embarrassing to ask my teammates for their impression of how I was doing on
the task.

185. It would not have bothered me at all to ask my experimenter for feedback

186. It is not a good idea to ask your experimenter for feedback; he/she might think you are
incompetent.

187. It would have been embarrassing to ask my experimenter for feedback.

188. I think my teammates would have thought worse of me if I asked them for feedback.

189. I would not have been nervous about asking my teammates how they evaluated my behaviors.

190. It is better to try and figure out how you are doing on your own rather than ask your teammates for
feedback.

Continue on the next page.

189

Use the following 5-point scale to answer questions #191 - 212.

 

1 2 3 4 5
Strongly Disagree Neutral Agree Strongly
Disagree Agree

The following questions concern your attitude about working in groups.

191. I prefer to work with others in a group rather than working alone.

192. Given the choice, I would rather do a job where I can work alone rather than doing a job where I
have to work with others in a group.

193. Working with a group is better than working alone.

194. People should be made aware that if they are going to be part of a group then they are sometimes
going to have to do things they don’t want to do.

195. People who belong to a group should realize that they’re not always going to get what they
personally want.

196. People in a group should realize that they sometimes are going to have to make sacrifices for the
sake of the group as a whole.

197. People in a group should be willing to make sacrifices for the sake of the group’s well-being.

198. A group is more productive when its members do what they want to do rather than what the group
wants them to do.

199. A group is most efficient when its members do what they think is best rather than doing what the
group wants them to do.

200. A group is more productive when its members follow their own interests and concerns.

The following questions concern how you tend to view stressful situations.

201. I am not a worrier.

202. I ofien feel inferior to others.

203. When I’m under a great deal of stress, sometimes I feel like I’m going to pieces.
204. I rarely feel lonely or blue.

205. I often feel tense and jittery.

206. Sometimes I feel completely worthless.

207. I rarely feel fearful or anxious.

208. I often get angry at the way people treat me.

209. Too often, when things go wrong, I get discouraged and feel like giving up.
210. I am seldom sad or depressed.

211. I often feel helpless and want someone else to solve my problems.

212. At times I have been so ashamed I just wanted to hide.

Continue on the nut page.

190

Use the following 5-point scale to answer questions #213 - 248.

 

l 2 3 4 5
Strongly Disagree Neutral Agree Strongly
Disagree Agree

The following questions concern how you tend to interact with others.

213. I try to be courteous to everyone I meet.

214. I ofien get into arguments with my family and co-workers.

215. Some people think I’m selfish and egotistical.

216. I would rather cooperate with others than compete with them.
217. I tend to be cynical and skeptical of others’ intentions.

218. I believe that most people will take advantage of you if you let them.
219. Most people I know like me.

220. Some people think of me as cold and calculating.

221. I’m hard-headed and tough-minded in my attitudes.

222. I generally try to be thoughtful and considerate.

223. If I don’t like people, I let them know it.

224. If necessary, I am willing to manipulate people to get what I want.

The following questions concern how you tend to be socially.

225. I like to have a lot of people around me.

226. I laugh easily.

227. I don’t consider myself especially “light-hearted.”
228. I really enjoy talking to people.

229. I like to be where the action is.

230. I usually prefer to do things alone.

231. I often feel as if I’m bursting with energy.

232. I am a cheerful, high-spirited person.

233. I am not a cheerful optimist.

234. My life is fast paced.

235. I am a very active person.

236. I would rather go my own way than be a leader of others.

The following questions concern how you tend to go about completing tasks and your work habits.

237. I keep my belongings clean and neat.

238. I’m pretty good about pacing myself so as to get things done on time.
239. I am not a very methodical person.

240. I try to perform all the tasks assigned to me conscientiously.

241. I have a clear set of goals and work toward them in an orderly fashion.
242. I waste a lot of time before settling down to work.

243. I work hard to accomplish my goals.

244. When I make a commitment, I can always be counted on to follow through.
245. Sometimes I’m not as dependable or reliable as I should be.

246. I am a productive person who always gets the job done.

247. 1 never seem to be able to get organized.

248. I strive for excellence in everything I do.

End of survey. T hanks for your participation!
Make sure your last response is on #248 on your Scantron.

191

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