-:: -X‘r. £511

'59

4:17

A
Z‘
‘
E7
m
!
1"
;

 

...,. ‘
w ‘

‘

”—— “
«‘44.. 5
If .-

. u»
‘2‘?“ ..

n .4.“ “I

. A. ‘
3‘}£g~fl‘iim
“2’

 

w.
>-

This is to certify that the
dissertation entitled

NEW FINDINGS IN VIRTUAL TEAM LEADERSHIP

presented by
ALEX J. BARELKA

has been accepted towards fulfillment
of the requirements for the

Ph.D. _ degree in Management

ié//7 74%

Major Professor’s Signature

</////a7

Date

MSU is an affirmative-action, equal-opportunity employer

-.-.—--—-— _4

 

 

LIBRADrY
Michigan State
University

 

 

 

PLACE IN RETURN BOX to remove this checkout from your record.
TO AVOID FINES return on or before date due.
MAY BE RECALLED with earlier due date if requested.

 

DATE DUE DATE DUE DATE DUE

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

6/07 p:/ClRC/DateDuelindd-p.1

NEw FINDINGS IN VIRTUAL TEAM LEADERSHIP
By

Alex J. Barelka

A DISSERTATION

Submitted to
Michigan State University
In partial fulfillment of the requirements
For the degree of

DOCTOR OF PHILOSOPHY

Department of Management

2007

ABSTRACT
NEW FINDINGS IN VIRTUAL TEAM LEADERSHIP
By

Alex J. Barelka

This study examines the impact different virtual team structural configurations,
leadership style training sessions, and task complexity can have on team performance
outcomes. To date, most studies that have examined leadership style and performance
outcomes have been performed in a collocated context. These studies have shown that
teams whose leader exhibits a transformational leadership style typically outperforms
teams whose leader use transactional style. However, this study predicted that when all
the team members are virtually connected by computer mediated communication systems
a transformational leadership style will not be preferable. Specifically, it suggests that
different team structural configurations, leadership styles and task complexity will impact
the communication quantity, quality and leader centrality. These mediators will then
impact team performance and affective reactions (as operationalized in terms of

satisfaction with the team and leader).

ACKNOWLEDGEMENTS

I would first like to thank my wife and daughter for putting up with the long days, late
nights, and non-existent weekends. Next I would like to thank my office mate Dr.
Michael Johnson for answering all of my questions and listening to the constant
complaining. I would also like to thank Dr. Daniel 11 gen and Dr. John Hollenbeck for
providing access to the Team Effectiveness Laboratory and Dr. Fred Morgeson for taking
the time to be part of my committee. Finally, I would like to thank Dr. Cheri Speier and
Dr. Vernon Miller for listening to me describe the issues I faced while completing this
study and providing excellent instruction and guidance on how to address them. I would
also like to thank the professors and teaching assistants who provide all the subjects for

this study.

The views expressed in this dissertation are those of the author and do not reflect the
official policy or position of the United States Air Force, Department of Defense, or the
United States Government.

iii

TABLE OF CONTENTS

LIST OF TABLES ............................................................................................................. vi
LIST OF FIGURES ......................................................................................................... viii
INTRODUCTION ............................................................................................................... 1
Virtual Teams Leadership Literature ............................................................................... 6
Literatures examined ...................................................................................................... 10
Contributions .................................................................................................................. 1 2
CHAPTER 1 - DIRECT EFFECTS ................................................................................... 14
Teams ............................................................................................................................. 14
Structure ......................................................................................................................... 17
Communication .............................................................................................................. 21
Structure and Communication ....................................................................................... 22
Leadership style ............................................................................................................. 26
Leadership Style and Communication ........................................................................... 29
Task Complexity ............................................................................................................ 32
Task complexity in a team ......................................................................................... 34
Team Task Complexity and Communication ................................................................ 38
Leader Centrality ........................................................................................................... 40
Structure and Leader Centrality ..................................................................................... 42
Leadership Style and Leader Centrality ......................................................................... 45
Objective Performance ................................................................................................... 46
Satisfaction with the team .............................................................................................. 47
Satisfaction with the leader ............................................................................................ 47
Communication and Team Effectiveness ...................................................................... 47
Leader Centrality and Team Effectiveness .................................................................... 48
CHAPTER 2 - INTERACTION EFFECTS ...................................................................... 51
Structure, Leadership Style, and Communication Quality ............................................ 51
Leadership style, Task Complexity, and Communication Quantity .............................. 52
Structure, Leadership Style, and Leader Centrality ....................................................... 55
CHAPTER 3 - METHOD .................................................................................................. 58
Choice of setting ............................................................................................................ 58
Participants ..................................................................................................................... 58
Power analysis ............................................................................................................... 58
Task Description ............................................................................................................ 60

iv

Manipulations, Measures and Reliability ...................................................................... 61

Structure .................................................................................................................... 62
Leadership Style ........................................................................................................ 64
Task Complexity ........................................................................................................ 66
Communication Quantity .......................................................................................... 68
Communication Quality ............................................................................................ 72
Leader Centrality ...................................................................................................... 73
Objective Performance ............................................................................................. 74
Satisfaction with Team .............................................................................................. 75
Satisfaction with Leader ........................................................................................... 75
Procedure ....................................................................................................................... 75
Data Analysis Strategy ................................................................................................... 76
CHATPER 4 - RESULTS .................................................................................................. 78
Manipulation Checks ..................................................................................................... 78
Scales, missing and deleted data .................................................................................... 79
Test of Hypotheses ......................................................................................................... 80
Direct Eflects ............................................................................................................ 81
Moderation effects .................................................................................................... 89
Mediation effects ..................................................................................................... 101
Eflects of Structure and Leadership on Distal Outcomes ....................................... 104
Results using a modified leadership coding scheme ............................................... 105
CHAPTER 5 - DISCUSSION ......................................................................................... 109
Review of results .......................................................................................................... 109
Mediators ................................................................................................................ 1 1 8
Limitation and future studies ....................................................................................... 122
SUPPLEMENTAL TABLES .......................................................................................... 128
Appendix A MEASUREMENT INSTRUMENTS ......................................................... 146
PRE-TRAINING SURVEY: ....................................................................................... 146
Leader post game 2 survey: ......................................................................................... 156
Team post game 2 survey: ........................................................................................... 165
Appendix B TRAINING MATERIAL ............................................................................ 177
Appendix C TRAINING ROOM PICTURES ................................................................. 213
BIBLIOGRAPHY ............................................................................................................ 214

LIST OF TABLES

Table 1. Task complexity in a team .................................................................................. 37
Table 2. Summary of test results ..................................................................................... 103
Table 3. Means, Standard Deviations, and Intercorrelations (simple task) .................... 128
Table 4. Means, Standard Deviations, and Intercorrelations (complex task) ................. 129

Table 5. Regression results between independent variables and communication quantity
(simple task) .................................................................................................................... 130

Table 6. Regression results between independent variables and communication quantity
(complex task) ................................................................................................................. 130

Table 7. Regression results between independent variables and communication quality
(simple task) .................................................................................................................... 131

Table 8. Regression results between independent variables and communication quality
(complex task) ................................................................................................................. 131

Table 9. Structure x Leadership style x Task Complexity as they relate to Comm quantity
(Hypotheses 5) ................................................................................................................ 132

Table 10. Regression results between independent variables and leader centrality (simple
task) ................................................................................................................................. 133

Table 11. Regression results between independent variables and leader centrality
(complex task) ................................................................................................................. 133

Table 12. Regression results between mediator variables and performance (simple task)
......................................................................................................................................... 1 34

Table 13. Regression results between mediator variables and performance (complex task)
......................................................................................................................................... 134

Table 14. Regression results between mediator variables and team satisfaction (simple
task) ................................................................................................................................. 135

Table 15. Regression results between mediator variables and team satisfaction (complex
task) ................................................................................................................................. 135

vi

Table 16. Regression results between mediator variables and leader satisfaction (simple

task) ................................................................................................................................. 1 36
Table 17. Regression results between mediator variables and leader satisfaction (complex
task) ................................................................................................................................. 136
Table 18. Regression results between independent variables and performance (simple
task) ................................................................................................................................. 137
Table 19. Regression results between independent variables and performance (complex
task) ................................................................................................................................. 137
Table 20. Regression results between independent variables and team satisfaction (simple
task) ................................................................................................................................. 138
Table 21. Regression results between independent variables and team satisfaction
(complex task) ................................................................................................................. 138
Table 22. Regression results between independent variables and leader satisfaction
(simple task) .................................................................................................................... 139
Table 23. Regression results between independent variables and leader satisfaction
(complex task) ................................................................................................................. 139
Table 24. Comparison between all dependent variables ................................................. 140
Table 25. Regression for Mediation (simple) ................................................................. 141
Table 26. Regression for Mediation (complex) .............................................................. 141
Table 27. Regression for Mediation (simple) ................................................................. 142
Table 28. Regression for Mediation (complex) .............................................................. 142
Table 29. Regression for Mediation (simple) ................................................................. 143
Table 30. Regression for Mediation (complex) .............................................................. 143
Table 31. Regression for Mediation (performance) ........................................................ 144
Table 32. Regression for Mediation (team satisfaction) ................................................. 144
Table 33. Regression for Mediation (leader satisfaction) ............................................... 145

vii

LIST OF FIGURES

Figure 1. Basic model ......................................................................................................... 6
Figure 2. Teams with a different number of nodes ........................................................... 18
Figure 3. Team structures (M=Members; L = Leader) ..................................................... 21
Figure 4. Predicted hypotheses 1-4 ................................................................................... 26
Figure 5. Predicted hypotheses 5 and 6 for a collocated team .......................................... 32
Figure 6. Predicted hypotheses 8 and 9 ............................................................................ 45
Figure 7. Predicted hypothesis 14 ..................................................................................... 52
Figure 8. Predicted hypothesis 16 ..................................................................................... 57
Figure 9. Predicted and results for hypotheses l and 2 (simple) ...................................... 82
Figure 10. Predicted and results for hypothesis 1 and 2 (complex) .................................. 82
Figure 11. Predicted and results for hypotheses 3 and 4 (simple) .................................... 83
Figure 12. Predicted and results for hypotheses 3 and 4 (complex) ................................. 83
Figure 13. Predicted and results for Hypothesis 5 (simple) .............................................. 84
Figure 14. Predicted and results for Hypothesis 5 (complex) ........................................... 84
Figure 15. Results for Hypothesis 7 .................................................................................. 86
Figure 16. Predicted and results for Hypothesis 8 and 9 (simple) .................................... 87
Figure 17. Predicted and results for Hypothesis 8 and 9 (complex) ................................. 87
Figure 18. Predicted Hypothesis 14 .................................................................................. 90
Figure 19. Results for Hypothesis 14 (simple) ................................................................. 90
Figure 20. Results for Hypothesis 14 (complex) .............................................................. 91
Figure 21. Results for Hypothesis 15 ................................................................................ 92

viii

Figure 22. Predicted Hypothesis 16 .................................................................................. 93
Figure 23. Results for Hypothesis 16 (simple) ................................................................. 93
Figure 24. Results for Hypothesis 16 (complex) .............................................................. 94

Figure 25. Communication Quality x Leader Centrality and its effect on Performance
(simple task) ...................................................................................................................... 95

Figure 26. Communication Quality x Communication Quantity and its effect on
Performance (complex task) ............................................................................................. 96

Figure 27. Communication Quality x Communication Quantity and its effect on Team
Satisfaction (complex task) ............................................................................................... 97

Figure 28. Communication Quantity x Leader Centrality and its effect on Performance
(complex task) ................................................................................................................... 98

Figure 29. Communication Quantity x Leader Centrality and its effect on Team
Satisfaction (complex task) ............................................................................................... 98

Figure 30. Communication Quality x Leader Centrality and its effect on Team
Satisfaction (complex task) ............................................................................................... 99

Figure 31. Communication Quality x Leader Centrality and its effect on Leader
Satisfaction (simple task) ................................................................................................ 100

Figure 32. Communication Quality x Leader Centrality and its effect on Leader
Satisfaction (complex task) ............................................................................................. 101

Figure 33. Structure x Leadership Style and its effect on Performance (second game). 105
Figure 34. Training Room A ........................................................................................... 213

Figure 35. Training Room B ........................................................................................... 213

ix

INTRODUCTION

Teams have become increasingly important in recent years due to a shift in the
1980’s and 90’s towards organizing around large clusters of tasks. This shift has
occurred as organizations recognize that teams are well suited to respond to the changing
business landscape. Increased global competition, consolidation, and innovation are
driving a need for diverse skills, expertise, and experience. Teams are now being
recognized as structures which are capable of providing the flexible and adaptive
responses necessary to meet these new pressures (Kozlowski & Bell, 2003).

In an attempt to make teams even more relevant in today business environment,
advanced communication systems are employed to more effectively and efficiently form
and manage them. Information Technology (IT) has enabled work teams to migrate from
the face-to-face to the virtual world and allow its members the flexibility of participating
in several new arrangements including video teleconferences, e-mail, and mobile cellular
phone conversations. Teams using this technology are no longer constrained by their
physical location but can exist over vast distances (Lipnack & Stamps, 1997). In the past,
members of a team had to be relatively collocated to work together but the flexibility that
modern communications system offer allows groups to exist in multiple locations while
still conforming to the basic attributes and principles of a team.

Such teams have several advantages over more traditional collocated
organizational structures including (a) increasing the amount of potential knowledge
available (Sanders, 2000), (b) providing more immediate feedback to management and
other team members (Opper & Fersko-Weiss, 1992), (c) saving money on travel costs,

and (d) establishing a “relay race” based work routine pattern (Cascio, 1999). Such a

“relay race” allows teams to hand-off a days work to another team in another time zone
who have just begun their day. Once the second group finishes their day they hand-off
their work to yet another team. This cycle repeats until the output of one team is the
input of the original team. This continuous cycle can go on indefinitely allowing
organizations to develop what has been referred to as software shift work (Gorton &
Motwani, 1996).

Virtual teams also give organizations the added flexibility of bringing together the
best and brightest people they have to work on a particular problem in a comparatively
inexpensive and quick manner, rather than being restricted to only utilizing people that
are employed at a particular geographical location (Townsend, DeMarie, & Hendrickson,
1998). Obviously, this becomes even more important to large organizations that are
international or have many divisions spread over multiple time zones, countries, or even
continents. This additional flexibility might fimction as a proxy or surrogate for the
flexibility enjoyed by smaller, more agile firms. However, it might also allow these
smaller firms to take advantage of the global marketplace by making it easier to integrate
temporary or outsourced employees from outside their firms or stakeholders not
collocated.

These technologies can also impact team processes. These effects can either be
drastic such as when traditional team structures are fully supplanted by virtual teaming
arrangements or they can be more modest such as when voice or e-mail are integrated
into existing work patterns and routines. In the former, the use of information technology
is critical to the existence of the team itself while in the later information technology

might simply be regarded as a mechanism that allow traditional teams to extend their

productivity and/or reach. Regardless of the final effect, team leaders need to understand
how to react and perform given the new and unique challenges they face as a result of
such shifts in their setting and environment (Bell & Kozlowski, 2002). Complicating
this situation is the fact that innumerable combinations of virtual team structures can
exist.

Most research on virtual teams has ahnost exclusively treated spatial distance as a
dichotomous variable. However, this might be considered a simplistic assumption
(Kirkman, Rosen, Tesluk, & Gibson, 2004; Mortensen & Hinds, 2001). Many times,
variation in the spatial distance between team members exists. Specifically, an
increasingly larger percentage of teams are structured such that some team members are
collocated (i.e., located at the same worksite), whereas others are distributed at various
locations (Burke, Aytes, Chidambaram, & Johnson, 1999). Such a team structure as this
can be thought of as a partially distributed team (PDT) or a team with an intermediate
level of collocatedness. At the very minimum, a team in which one team member
telecommutes from home could be labeled a PDT. More broadly, PDTs are likely to
occur in organizations comprised of autonomous groups, (Allred, Snow, & Miles, 1996),
as sets of team members span cells, and joint ventures or partnerships (Townsend,
DeMarie, & Hendrickson, 1998), as each company provides a set of individuals for the
team.

In 2001, nearly 28 million Americans utilized a distributed work setting and most
of these were arrayed in some form of a PDT (Davis & Polonko, 2001). Yet, as prevalent
as PDTs are, there has been very little research conducted that examines them. For

leadership researchers this deficit can be particularly troubling given that there are

differences between PDTs and collocated teams (CTs) or even virtual teams (VTs) that
could impact team leadership processes. For example, one major difference is that in a
PDT, there can be large differences in the physical proximity between specific subsets of
the team. The existence of these subsets might lead to the formation of subgroups each
with separate group identities (Armstrong & Cole, 2002; Cramton, 2002; Humphrey,
2003). The development and strength of these subgroups might then impact the level of
leader centrality inside each of these teams. Thus the purpose of this paper is to examine
the impact of leadership styles, specifically, transformational and transactional leadership
in teams that operate in collocated environment versus two other configurations of a
virtual team.

In order to understand leadership in a virtual team, I feel there are three
dimensions, or independent variables, that must be considered. First, it is important for
leaders to understand how a change in collocatedness might impact team processes. For
this study three different structures will be examined, a fully collocated structure, a fully
virtual structure, and a partially distributed structure. To date, no single study has
simultaneously examined all three of these structures so the insights gleaned from
directly comparing and contrasting these different structures should be valuable. Second,
it is important to consider different types of leadership. There are several different
conceptualizations of leadership today but this study will focus on what is perhaps
currently the most popular paradigm in the leadership literature and the one which is
thought to be the most visibly influenced by in the introduction of virtual nodes into a
team. This is the full range leadership model which includes both transactional and

transformational leadership behaviors. Finally, it is also important to understand how

perceived leadership effectiveness in a virtual team might change based on the task
complexity. For several decades the contingency perspective of leadership has shown
that the environment and contextual variables within it play an important role in
leadership (T. Burns & Stalker, 1961; Leavitt, 1951). It is important for those who are
selected to be virtual leaders to understand how such variables might impact a virtual
team so that they can operate in it as effectively as possible. It will later be proposed that
each of these dimensions impacts both communication processes in the form of quality
and quantity as well as leadership process. Further, it will be proposed that each of these
constructs has a relationship with both performance and affective components of
effectiveness.

In summary, this paper proposes that the outcomes of team performance and
affective reactions (as operationalized in terms of satisfaction with the team and leader)
are, in part, determined by three factors. First, it will describe the role of co-locatedness,
highlighting the distinguishing feature of three different configurations including (a) face-
to-face, where all of the team members are collocated, (b) totally distributed, where none
of the members are collocated, and (c) a “reachback” a condition where all of the team
members are co-located except the leader. Second, it will examine the role of
transformational and transactional leadership styles and how they are effected by the
nature of the co-locatedness. Finally, it will also examine the impact of complexity on
leadership styles inside both collocated and virtual team configurations. The general
proposition that will be examined in the proposed study is that these three features of the
team influence performance and satisfaction because of the impact they have on

communication quantity, communication quality, and the centrality of the leader in the

communication network. This conceptualization of team leadership maps very closely to
the IPO model of teams popularized by McGrath and Hackman (Hackman, 1987). For
example, the independent variables of structure, leadership style, and task environment
can be considered input to the model while the mediators of communication and leader
centrality can be considered processes within the team. Finally, the decomposed aspects
of effectiveness selected provide a rich conceptualization of team output. Therefore, it is
thought that an examination of these constructs will provide a rich and comprehensive
window into virtual team leadership. Figure 1 below provides an overview of the general

model guiding this research.

 

 

LVJ
1. Team structure

 

 

 

 

 

 

a. Collocated ,
. Mediators DVs
b. Virtual -— . . .—
1. Com Quantity 1. Objective Performance
c. Reachback . . .
. . . 2. Com Quality 2. Satisfaction w/ Team
2' Leadership Trarnrng 3 Leader Centrali 3 Sati faction w/ Le der
a. Transformatronal ' ty ' s a

 

 

b. Transactional
3. Task Complexity

 

 

 

 

 

 

Figure 1. Basic model

Virtual Teams Leadership Literature
Given the ubiquity and ever growing popularity of virtual teams, it is surprising to

learn that only a handful of studies have examined leadership within these structures
especially given the major impact a shift from collocated teams to a virtual arrangement
can have on leadership (Zigurs, 2003). This is an important topic to examine since as one
executive has expressed, “The number one key success factor for virtual teams is strong

leadership” (Blackburn, Furst, & Rosen, 2003, p. 102).

While a few articles have been written to date about leadership and virtual teams,
most of them are seemingly intended for the practitioner (Avolio & Kahai, 2003; Cascio
& Shurygailo, 2003; Zaccaro & Bader, 2003; Zigurs, 2003). Such research typically
explains obvious differences between virtual and traditional collocated teams, providing
general guidance on how negative issues associated with these differences can be
minimized and how any new opportunities that technology may provide to such teaming
arrangements can be maximized. For example, these articles suggest leaders build trust,
clearly communicate their intent, and use a balance of new and old technology to lead.
Unfortunately, most of the guidance provided in these articles is high level and might be
considered common sense by those who are already accustomed to working with
technology and people. Although this literature is important to new virtual team leaders,
it does not provide much new insights or do much to further our understanding regarding
how leadership can develop and mature in a virtual world.

Other studies have attempted to use more of a theory building (Bourgeois, 1979)
approach to not only review and apply theoretical and empirical literature to the existing
question of virtual team leadership but also to construct a new theory from this empirical
base and then extend it into a set of propositions using deduction. However, this research
has also only provided heuristics or high level guidance to overcome many of the innate
challenges of leading a virtual team (Avolio & Kahai, 2003; Avolio, Kahai, & Dodge,
2001; Bell & Kozlowski, 2002; Gretchen M. Spreitzer, 2003). For example, conclusions
in this type of research are that high levels of trust, media richness and leadership
processes lead to positive team outcomes. Although this literature provides virtual team

leadership theories that are more grounded to previous research, it still does not provide

many new insights or revelations regarding why leading a virtual team might be different
than leading a collocated team.

Perhaps the most compelling research that has examined virtual team leadership
are the empirical studies which have either used deductive strategies based on previous
literature to develop conceptual ideas that suggest how virtual team leaders might
increase effectiveness and test these notions using case studies and survey data, or
inductive strategies which form theories after an examination of the data. The ideas that
have been presented in these studies have all assumed that potential differences between
leadership in a virtual and traditional teams can be moderated by the judicious application
of leadership behaviors previously tested to Show their efficacy (Kayworth & Leidner,
2001; Lee-Kelley, 2002; Pauleen, 2003, 2004). However, assuming that leadership
behaviors which work in a collocated environment have the same impact in the virtual
word might be a simplistic viewpoint given that “research suggests that virtual team
members cannot rely on simply transferring their behavior in traditional teams and expect
to be successful in virtual environments.” (Zigurs, 2003, p. 341).

Another potential gap in the literature is that the few studies which have examined
leadership in computer mediated environments have used technologies or tasks that are
commonly associated with virtual teams. For example, Hoyt and Blascovich (2003)
examined the impact a virtual reality simulator can have on leadership. This is
admittedly an interesting technology to study but it does not represent the predominate
form of asynchronous communication typically used virtual teams (Tyran, Tyran, &
Shepherd, 2003) or even simple voice based communication. Similarly, there are a few

studies which consider the effects of different leadership styles when using group

decision making software systems (GDSS) (Kahai & Cooper, 1999; Kahai, Sosik, &
Avolio, 1997, 2003, 2004; Sosik, Avolio, & Kahai, 1997; Sosik, Avolio, Kahai, & Jung,
1998; Sosik, Kahai, & Avolio, 1998). Again, while this might be an interesting context
to study, the use of a single idea generation task does not allow for much task
interdependence. As a result it is difficult to classify such studies as teams related
research (Goodman, Ravlin, & Schmike, 1987).

Further, few studies to date have examined the effects of partially distributed
teams and none have examined their impact on leadership. These types of teams exhibit
different types of communication patterns (D. Cohen & Prusak, 2001; Walther, 1995),
and patterns of contact (Kiesler & Cummings, 2002; Kraut, Fussell, Brennan, & Siegel,
2002) but Since structure has not been manipulated in these groups, little knowledge
regarding the differential effects of virtualness has been gained.

Finally, many of the studies that have examined leadership in virtual teams have,
much like most any other leadership study, focused only on correlations or relationships
but have not examined the underlying causes or mediators that connect these phenomena
to outcomes. This study will attempt to develop a theory of leadership inside virtual
teams using communication process and leadership variables to connect the structure of a
virtual team with team effectiveness in an attempt to explain why leadership impacts
situations rather than simply detailing the existence of an impact.

One of the interesting ramifications of this paper is to introduce the idea that
leadership behaviors and traits which have proven highly effective in a collocated
environment might not have the same effect in a virtual environment. That is, the nature

of perceptual experience associated with face-to-face leadership versus virtual leadership

can be quite different, and hence different standards may apply in terms of predicting the
relationship between various leader behaviors, styles, or traits on the one hand and
outcomes on the other. In fact, recent research has unexpectedly found that leadership
behaviors and traits which are known to be effective in collocated environments
sometimes are not the most effective the virtual world, therefore, a complete theory
which explains why this might be true is required (Balthazard, Potter, & Warren, 2004;
Hoyt & Blascovich, 2003).

Literatures examined
There are several literatures that this paper will attempt to unite in order to explain

the impact of the collocatedness on leadership, team processes, and team effectiveness.
First, the literature that examines media effects will be used to better understand the
impact of different structural configurations on the team. This literature relies heavily on
communication process so that will be a major focus of this part of the paper. Second,
the literature on task complexity will be examined to determine its potential impact on
communication processes. Specifically, the potential relationship between task
complexity and communication processes will be examined. Next, the leadership
literature will be examined to help understand what type of impact a structural change
might have on communication outcomes. Here, the impact of transformational and
transactional leadership behaviors on communication outcomes will be examined.
Transformational leadership can be considered a neo-classical form of charismatic
leadership which incorporates many of the previous conceptualizations of leadership
(Y ukl, 1998). In contrast, transactional leadership, is a more ordered and structured
approach that builds on rewards. The voluminous research that has examined both of

these approaches has concluded that the transformational approach is typically more

10

desirable (Bass, Avolio, & Goodheim, 1987; Deluga, 1988; Dumdum, Lowe, & Avolio,
2002; House, Woycke, & Fodor, 1988; Keller, 1992; Lowe, Kroeck, &
Sivasubramaniam, 1996; Seltzer & Bass, 1990; Waldman, Bass, & Einstein, 1987;
Waldman, Bass, & Yammarino, 1990; Yammarino & Bass, 1990). However, in the
virtual environment, leaders and followers are no longer able to freely communicate face-
to-face thus lost are a multitude of natural communication signals, cues, and associated
processes that are important to this leadership process (Gitter, Black, & Fishman, 1975;
Gitter, Black, & Goldman, 1975; Gitter, Black, & Walkley, 1976; Masters & Sullivan,
1989; Masters, Sullivan, Lanzetta, McHugo, & et al., 1986; Pauleen, 2003). This
especially weighs heavily on the transformational leadership style given that so much of
this style is based on the ability to communicate using non-verbal behavior (Sashkin,
2004). Therefore, this paper suggests that given the communication restrictions between
virtual team members, the behaviors associated with a transactional leadership style are
preferable and should lead to higher team effectiveness as compared to when a
transformational style is employed. This is not to say that high quality transactional
leaders somehow become more effective in a virtual environment but simply that the
natural communication channels that a transformational leader relies on are unavailable
in such a setting and thus render this approach much less effective for them.

It is important to understand that this theory is not intended to be an indictment of
the transformation style. It is fully recognized that in many situations the transformation
style will still be preferable. The presented theory is merely an attempt to develop more

of a balance within the leadership literature and continue to point out that in some

11

situations the behaviors consistent with the transactional style might still have merit and
should not be forgotten (Judge, Piccolo, & Ilies, 2004).

In addition to the potential impact that each of these antecedents might have on
communication outcomes, their impact on leadership centrality will also be examined.
Centrality relates to the number of connections an individual has within a social network
(Klein, Lim, Saltz, & Mayer, 2004). As such, it reflects the extent to which interactions
are concentrated in certain individuals rather than distributed equally among all members
(Sparrowe, Liden, Wayne, & Kraimer, 2001). Individuals who are perceived to have a
high amount of centrality are viewed as being more influential (Brass, 1984). This
literature will be combined with diversity studies to better understand how structural
changes, leadership behaviors and task environment might impact this construct.

Contributions
It is hoped that this paper will make at least four major contributions to the

existing literature. First, it will investigate the implications of different types of virtual
structure on effectiveness. Instead of testing a single static virtual team configuration, the
level of collocatedness will be defined and varied during the experiment. Second, it will
examine the impact of the task complexity in both collocated and virtual team
configurations. Third, it will examine what impact different types of leadership behavior
can have on effectiveness. Finally, interactions between each of these dimensions will be
examined. It is hoped that all of this will presented a rich and comprehensive picture of
virtual team leadership.

Another interesting aspect of this study is that it will be performed as an

experiment using a real time virtual team task using technology more associated with

12

virtual teams. Instead of using a GDSS task or virtual reality technology, this experiment

will use a real time, multi-player, military command and control simulation.

13

CHAPTER 1 - DIRECT EFFECTS

In the proposed model three independent variables have a relationship with three
different mediators which in turn are predicted to have a relationship with three outcome
variables. The three independent variables are structure, leadership style, and task
complexity. The three mediators are communication quantity, communication quality,
and leadership centrality. Finally, the three dependent variables are objective
performance, team satisfaction, and leader satisfaction. Each of these constructs will be
presented below and then linked using specific hypotheses.

Teams
There are several definitions of what a team is but a fair amount of emerging

literature on this subject tends to focus on a few common themes (Kozlowski & Bell,
2003). First, a team exists to perform organizationally relevant tasks. This implies that
instead of existing as a stand alone entity, teams function within a larger organizational
context which sets the boundaries between teams and constrains their action. Second,
teams share one or more common goals. This suggests that team members work towards
a common purpose rather then each working on divergent and unconnected tasks. Third,
teams interact socially which has the potential to either improve or disrupt the processes
that exist inside them. For example, social interaction allows teams to learn or become
more cohesive, yet it also provides opportunities for conflict to emerge. Fourth, a team
exhibits task interdependencies such as work flows, goals, and outcomes. Some feel that
it is this important characteristic which separates teams from simple groups (Goodman,
Ravlin, & Schmike, 1987).

In an attempt to better define the boundaries of such arrangements, and emphasize

the teaming structures being examined, this research also includes the concepts of task

14

interdependence and goal orientation as part of this definition (1] gen, Major, Hollenbeck,
& Sego, 1993). Task interdependence stresses that the work teams require the efforts of
the entire team and goal orientation implies that team members have a focused purpose.
Further, this paper concentrates on teams that are project or deliverable orientated rather
than collaboration work groups where information sharing is the ultimate goal (S. G.
Cohen & Bailey, 1997). These task orientated teams many times have a hierarchical
team structure that helps increase decision making accountability and speed (Humphrey,
Hollenbeck, Meyer, & Ilgen, 2002). As a result, this paper only considers teams which
have a formal leader rather than a self-managed structure. This is an important
distinction when examining leadership in teams since self-managed teams many times
tend to have different leadership requirements (Druskat & Wheeler, 2003). In such
structures, leaders must pay closer attention to team boundaries and interfaces and
requests for information can be initiated and satisfied by team members themselves
without a leader present. Further, the mix of different types of coaching that work best in
a self-managed team might be different than it is in a traditional teaming arrangement
(Morgeson, 2005). Given that the need for leadership is different in these two types of
teams, any single study that examines both of them would be expected to obtain different
results.

In an attempt to make this investigation even more applicable and interesting it
will consider teams which operate in real time situations. Real time situations are defined
here as those which unfold unpredictably and require all participants to take immediate
action in order to solve the problem. Such a categorization could be considered similar to

that of an action team (S. G. Cohen & Bailey, 1997) so long as it is understood that the

15

team would not necessarily disband after the completion of one task, as action teams
many times do, but would continue to exist to solve a number of different issues each
related to a larger problem. As a result, the intended lifespan of such a team is what
could be thought as the primary differentiator between it and an action team.

Traditionally most studies that have examined teams have focused on collocated
structures. In this situation, all team members are geographically collocated with the
leader and as a result, everyone in the team is not only able to see and hear everything
that is being communicated but also how it is being communicated. For example, they
are able to easily perceive and use the non-verbal behaviors important to the
communication process. Further, they are able to understand and interpret the emotional
content embedded within verbal communication. On the other hand, members of a
virtual team use information technology to communicate so they are usually not
collocated.

Usually, virtual teams are defined as a team that is (a) geographically distributed
to some degree and (b) uses technology as a communications mediation device
(Townsend, DeMarie, & Hendrickson, 1998). However, this is a rather vague definition
which have lead some researchers to go so far as to propose that all teams possess some
type of a virtual component (Griffith, Sawyer, & Neale, 2003; Martins, Gilson, &
Maynard, 2004). Therefore, in an attempt to better define the boundaries of such
arrangements this paper will define a virtual team as one in which each team member
exists in a different geographical location. In other words, the team is considered to be
“fully virtual.” As a result, team members and leaders are unable to participate in any

verbal team communication which makes it much more difficult for them to attach any

16

emotional content to their messages. Further, even though the predominate form of
communication in a virtual team is still based on asynchronous computer mediated
communication systems (Tyran, Tyran, & Shepherd, 2003) this study will define it as one
in which members can still communicated using voice channels. It is thought that this
will remove any potential confounds in the research design between team structure and
communication media.

Although this definition is the one that most previous virtual team studies have
subscribed to, recent research has begun to attack the notion that virtual teams solely
exist in a fully virtual environment. Now, partially distributed teams, or teams that can
be part collocated and part virtual are now being investigated.

Structure
New studies have begun to investigate the subtleties associated with how virtual

teams Structurally differ from traditional teams and each other (Martins, Gilson, &
Maynard, 2004). For example, while past research has treated spatial distance inside a
virtual team as a dichotomous variable (teams are either fully collocated or fully
distributed), Griffith (2003) recently proposed that the amount of team virtualness can be
described using three separate dimensions (a) technological support used by the team, (b)
the percentage of work that the team does with its members distributed across time or
space and (c) the distribution of the physical locations occupied by the team members.
With regards to the last dimension, others have investigated the effects of partially
distributed virtual teams or teams comprised of nodes. Here, a node is simply a
physically separated location that can contain either a collocated group or just a single
individual (Burke, Aytes, Chidambararn, & Johnson, 1999; Humphrey, 2003). Examples

of teams with different a number of nodes is shown below in Figure 2.

17

 

 

O

 

 

 

 

 

 

1 node 2 nodes 3 nodes 4 nodes
(collocated)

 

 

 

Figure 2. Teams with a different number of nodes

These studies tend to view virtual team structures as forming a continuum
between traditional collocated teams that only interact using a face-to-face arrangement
and teams that exist solely in the virtual environment where members only communicate
via a technical platform. Between these two poles exists any number of partially
distributed team configurations (Humphrey, 2003). In an attempt to better define this
continuum, this study will focus on fully collocated teams, fully virtual teams, and a
‘reachback’ configuration.

A reachback structure is a specific type of team configuration that combines both
collocated and virtual elements. In this configuration all team members are collocated
but the team leader is remote. As a result, all of team members act as a collocated team
but the geographically separation of the leader introduces a virtual component to this
structure. Therefore, all of the collocated team members are able to participate in the rich
communication available to collocated individuals but the leader is restricted only to
communicating via voice only. This configuration is based on teams who have a home
base for training and administrative purposes but deploy a majority of their action and
operational components to a specific area when their services are required. This structure
is called a “reachback” configuration because the collocated members of the team must

reach back to the home base for leadership or resources. Teams that typically might use

18

this configuration are those who are able to provide a rapid response to situations but still
need leadership from superiors due to dynamic nature of the environment or a need to
obtain additional resources. Examples of these teams include military teams, news
collection teams, as well as disaster response teams in both the public (e. g. FEMA) and
private sector (e. g insurance companies). To realize how important these contexts are
you do not have to do anything more then open a newspaper or turn on a television. The
recent increase in destruction caused by natural disasters such as hurricanes and tsunarnis,
as well as countless terrorist attacks coupled with the inability to private and public
agencies and leaders to sometimes respond adequately to these situations only
underscores how important an examination of leadership is in these contexts. Given the
highly interconnected and technological advanced reality we now exist in, it is more
important then ever to understand how to lead in these virtual team settings.

Specific to the military, “Reachback” or distributed operations (Colarusso &
Trowbridge, 2004), has become an essential component of any current or future
deployments. In the military reachback is “the electronic ability to exploit organic and
non-organic resources, capabilities and expertise, which by design are not located in-
theater” (Neal, 2000). This is not a new concept but today’s military is increasing its
scope and reach to touch more aspects of warfare. For example, imagery analysts,
intelligence experts, sensor operators, and mission planners now no longer need to be
deployed together in order to perform their mission as they once did (Colarusso &
Trowbridge, 2004). Instead, they can continue to operate as a seamless team in a virtual
environment by communicating electronically. Given that Joint Vision 2020 (Defense,

2002) establishes that information superiority will be a key component to winning future

19

conflicts, a major element of Reachback, “refers to the ability of combat forces to receive
intelligence, surveillance, and reconnaissance (ISR) data directly from databases and
experts located in the US” (Tirpak, 2000). It is thought that by using such teaming
arrangements, the amount of deployed support personnel can be reduced thus allowing
whole teams that would have once been deployed into a hostile area to now remain out of
harms way and in essence, telecommute to the war. Proponents think that this concept
could ultimately lower required troop strengths at forward command posts from 1,500 to
about 300 (Tirpak, 2000).

Developing a capability that keeps military personnel from having to deploy not
only decreases the disruption created in their lives but also saves money. Already Air
Force officials have estimated they have saved between $6M-$15M by not having to
forward base a portion of the intelligence assets that help prosecute Operation Enduring
Freedom in Afghanistan and Operation Iraq Freedom (Herbert, 2004). This also
translates into over 150 transport'aircraft flights that did not need to be assigned for this
activity and could therefore be applied elsewhere (Colarusso & Trowbridge, 2004).

It is thought that by addressing these types of teams, this paper also responds to
the call by several prominent researchers in a recent issue of the Academy of
Management Journal (Shapiro & Rynes, 2005) to better unite management scholarship
and public policy formation. The two primary problems listed in the introduction to this
issue that could have been avoided had management scholarship been better prepared and
linked to policy development were the leadership issues associated with the September
11, 2001 attacks and the confusion caused by hurricane Katrina. In both these situations,

reachback teams were in heavy use by the Government. A graphical representation of

20

each of the team configurations that will be examined in this study are provided in Figure

3.

 

 

in ED
o

Collocated Virtual Reachback

 

 

 

 

 

 

 

 

Figure 3. Team structures (M=Members; L = Leader)
Having now explained which structural configurations will be examined in this
study, we can now turn our attention to how different structures might impact
communication processes within a team.

Communication
Communication is a major behavioral process associated with teams. A recent

literature review on teams considers it to be a lens that helps to define the level of
coordination and cooperation within a team (Kozlowski & Bell, 2003). To best capture
these elements, communication in this study will be conceptualized as both
communication quantity and quality.

Communication quantity is a team level construct and is defined as the number of
comments that are made during a discrete amount of time. In a collocated team it can be
thought of as the number of comments made by the team members and leader. In a
reachback team such a count would be added to the number of comments made by, or
sent to, the leader electronically. Finally, in a virtual team it could be conceptualized as

the number of electronic comments made between all the team members and the leader.

21

Communication quality can also be thought of as a group level construct (J ablin
& Sias, 2001). At this level it is often conceptualized as communication competence or
the communication effectiveness of group communication, and as such can be thought of
as quality of the interaction between team members. Traditionally, this construct has
been examined fi'om both the behavioral or cognitive perspective. Using the behavioral
perspective, communication quality can be thought of as the ability of a group to gather,
transmit, and interpret information (J ablin, Cude, House, Lee, & Roth, 1994). From the
cognitive perspective, communication quality can be viewed as the cognitive resources
associated with group rules, structure, culture, and history (J ablin, Cude, House, Lee, &
Roth, 1994). Studies that focus on this perspective tend to examine distributed
cognitions, group knowledge structures, and transactive memory (Hinsz, Tindale, &
Vollrath, 1997; Liang, Moreland, & Argote, 1995; Walsh, 1995). For the purposes of this
study both the behavioral and cognitive perspectives will be considered.

Structure and Communication
It is thought that communication outcomes will be impacted by the structural

aspects of the team. As teams become more virtual the amount of co-locatedness
decreases and the level of computer mediated communication typically increases (Tyran,
Tyran, & Shepherd, 2003). As this occurs, all three major theories used to describe the
effects of computer mediated communication (media richness theory, social media
theory, media naturalness theory) predict that communication processes will be
negatively impacted. There are two reasons for this. First, the amount of communication
will decrease and second the quality of the communication will decrease.

With regards to communication quantity it is thought that as teams become less

collocated and use more computer mediated technology the amount of communication

22

they engage in will decrease. Several studies have shown that communication quantity is
lower in virtual teams compared to a collocated team (Bhappu, Griffith, & Northcraft,
1997; Hiltz, Johnson, & Turoff, 1986; Hollingshead, 1996; Ibarra, 1993; Straus, 1996).
The simple explanation for this is that people can not type as fast they can talk.

However, it has been Shown that even after the natural ability of most to speak faster than
they can type has been controlled for, over 10 times as many words are communicated in
a face-to-face context than they are in a virtual environment (Kock, 1998). As a result, it
is predicted that less communication will occur in a virtual team compared to a collocated
team. What is less clear is how much communication occurs in a reachback team
compared to a collocated and a virtual team.

As mentioned earlier, a reachback team is one in which all the team members are
collocated except for the leader who is remote. Compared to a collocated team, this
configuration can be considered to be a collocated structure minus one individual. Given
that one person is being removed from the group the number of communication channels
or links between the remaining individuals also decreases. In fact, it decreases
exponentially based on the number of people in the group (V avelas, 1950; J. Wofford,
Gerloff, & Cummins, 1977). As a result, the overall amount of communication within
the group will also decrease. However, this decrease will be partially offset by any
comments the leaders make using the computer mediated communication devices
present. Yet given that previous research has shown that virtual team members do not
communicate as much as collocated team members, it is thought that this offset will not

overcome the decrease caused by the structural change. As a result I would expect that a

23

reachback team would exhibit less communication than a collocated team but more than a
virtual team. As a result the following hypotheses are presented.

H1: Overall team communication quantity will be higher
in a collocated team than a reachback team

H2: Overall team communication quantity will be higher
in a reachback team than a virtual team

With regards to the quality of communication it has been shown that in a virtual
team, members are not able to clearly communicate their ideas, thoughts, or intentions to
each other. This leads to a decrease in the level of communication quality or an increase
in the level of communication ambiguity. There are two reasons for this. First, computer
mediated technology tends to decrease the emotional content of communication. For
example, Kahi and Cooper (2003) shows that as media richness decreases so does the
level of socio-emotional communication. Second, computer mediated technology tends
to decrease non-verbal communication which carries a large amount of the emotional
content found in messages. Potential information derived from non-verbal
communication such as facial expressions, voice inflections, and gestures are severely
retarded or distorted when using computer based communication channels.
Communicating via text or audio based media alone does not provide the rich non-verbal
behaviors that can be crucial to determining an individuals true feelings (Pauleen, 2003).
This has the effect of decreasing social presence, or the amount of communication that is
inherent in a collocated environment (Kiesler & Sproull, 1992; Warkentin, Sayeed, &
Hightower, 1997).

Further, team members can communicate several messages simply by their

physical presence. It has been shown that individuals use physical and linguistic co-

24

presence to make inferences about each others knowledge and that these inferences have
been shown to be antecedents of successful communication (Hollingshead, 1998).
Similarly, it has been shown that when conversing electronically it is more difficult for
individuals to form impressions of each other since it takes longer to decode social cues
(Sproull & Kiesler, 1986; Walther, 1993). Additionally, where they sit, what their
appearance is, how many times they arrive early or late to a meeting can all convey
different messages (F errara, Brunner, & Whittenmore, 1990; Spears & Lea, 1994). In a
virtual team most of these signals and cues are lost, as well as the messages that
accompany them.

Turning again to a reachback team many of these issues are not thought to be as
acute as they are in a virtual team. For example, a reachback team has a significant
number of members that are collocated. This allows members to interact face-to-face and
increase the overall emotional content of the team communication. Further, since they
can see each other they will also be able to use non-verbal behaviors to communicate.
Therefore, it is thought that the overall communication quality of a reachback team will
be higher than a virtual team but lower than a collocated team.

H3: Overall team communication quality will be higher in
a collocated team than a reachback team

H4: Overall team communication quality will be higher in
a reachback team than a virtual team

The nature of hypotheses 1-4 are plotted in Figure 4.

25

 

.5

(a)

d

_o . l9 . .
our-sorroorworhorm

Communication Quantity/Quality

 

Face-to-face Reachback Virtual

 

 

 

Figure 4. Predicted hypotheses 1-4

Leadership style
Leadership can sometimes be a difficult concept to grasp and understand given

the extensive focus that has been applied to it in the area of psychology and
organizational behavior. In fact, over 30 years ago Fiedler (1971) and Stogdill (1974)
concluded that there are as many definitions of leadership as there are researchers who
have studied it.

Despite the fact that it is difficult to define leadership, core elements of the
definition have begun to emerge (Northbouse, 2004; Yukl, 1998). At the highest level
leadership can be considered a process for influencing groups to achieve specific goals.

It is difficult to add anything else to this definition and still have it generalize to most any
context because so many other aspects of leadership are situationally dependent. Several
different conceptualizations of leadership have been developed over time to examine the
different aspects of leadership, however, this study will focus on what is perhaps the most
dominant paradigm in the leadership literature today and the one which is thought to be

the most visibly influenced by in the introduction of virtual nodes into a team. This is the

26

full range leadership model which includes both transformational and transactional
leadership behaviors.

Transformational leadership can be considered a neo-classical form of charismatic
leadership which incorporates many of the previous trait and behavioral
conceptualizations of leadership (Yukl, 1998). Transformational leadership concerns the
process of influencing major changes in the attitudes and assumptions of team members
and building commitment for major changes in a team’s objectives and strategies.
Transformational leaders motivate followers to work towards transcendental goals or an
organizational vision (J. C. Wofford & Goodwin, 1994). It was first introduced by Burns
in 1978 but later Bass (1985) expanded it by decomposing it into four specific
dimensions: idealized influence, inspirational motivation, intellectual stimulation, and
individualized consideration.

Idealized influence refers to leaders who demonstrate behaviors consistent with
high ethical standards and doing the right thing. These individuals typically provide
followers with a vision and a sense of mission. Many times they result in followers
placing a great deal of trust in leaders who exhibit them. The second transformational
dimension is inspirational motivation. This factor describes leaders who communicate
high expectations to followers, inspiring them through motivation to become committed
to and a part of the shared vision of the organization. To accomplish this, leaders many
times use symbols and emotional appeals to focus the effort of group members. The third
dimension is intellectual stimulation which relates to the ability of leaders to stimulate
followers to be creative and innovative, and to challenge their own beliefs. The final

transformational dimension is individualized consideration which relates to a leaders

27

ability to provide a supportive climate in which they listen carefully to the individual
needs of followers.

Transactional leadership behaviors views the relationships between leaders and
followers as an exchange process in which followers’ needs can be met if their
performance is adequate (J. M. Burns, 1978). It is comprised of two components:
contingent reward and management-by-exception. Contingent reward refers to an
exchange process between leaders and followers in which the effort of followers is
exchanged for specific rewards (Komaki & Barnett, 1977; Stajkovic & Luthans, 2003).
When leaders use this type of leadership they try to obtain agreement from followers on
what needs to be done and what the payoffs will be for doing the work. Management-by-
exception refers to leadership that is based on setting standards and monitoring deviations
from these standards (Bass, 1985; Bono & Judge, 2004; Northhouse, 2004). Given this
focus on external rewards and standards it has been shown that individuals who
emphasize a transactional style focus on tasks and the cognitions that accompany them
(Goodwin, Wofford, & Boyd, 2000; J. C. Wofford, Goodwin, & Whittington, 1998).

The primary strengths of the full range leadership model is that it is intuitively
appealing, treats leadership as a process, offers a broad view of leadership, and provides a
strong emphasis on followers’ needs, values and morals. Further, it has been widely
researched and supported. For instance, Lowe, Kroeck, & Sivasubramaniam (1996) used
a meta analysis to show that discriminate validity exists between transformational and
transactional leadership and that the correlation between transformational leadership and
job performance is .73. More recently, Judge and Piccolo (2004) used a meta-analysis to

show that transformational leadership correlates .44 with job performance and

28

transactional leadership correlates .39. Despite the fact that the numbers were not as high
as those associated with Lowe et al., (1996) they were still appreciable.

However, criticisms of this approach exist including a claim that the theory lacks
conceptual clarity since it does not provide clear evidence of discriminate validity
between charismatic or visionary leadership. Other drawbacks of this approach is that it
treats leadership as a trait or predisposition rather than a learned behavior (Bryman,
1992), is elitist, antidemocratic, suffers from a “heroic leadership” bias (Yukl, 1999), and
was conceived based on data collected from CEO’s (Bryman, 1992). However, despite
these claims, the full range model still remains the dominate paradigm in leadership

studies.

Leadership Style and Communication

It is proposed here that for each structural configuration, teams whose leader has
been trained to use a transformational style will exhibit a higher level of communication
compared to teams whose leaders have been trained to use a transactional style. This is
thought to be true for three reasons.

First, transactional leaders focus mainly on the task (Goodwin, Wofford, & Boyd,
2000; J. C. Wofford, Goodwin, & Whittington, 1998) but transformational leaders attend
to a much broader range of member behavior and processes. For example,
transformational leaders exhibit behaviors consistent with the dimension of idealized
influence, inspirational motivation, intellectual stimulation, and individualized
consideration. On the other hand, transactional leaders are only concerned with
contingent reward and management by exceptions. Therefore, transformational leaders
have more behaviors to attend to and as a result, more messages to communicate.

Additionally, in order to perform well transformational leaders will also need to focus at

29

least part of their effort on task orientated communication. It cannot be assumed that
teams can perform well if the leader does not at least in part attend to the task. Therefore,
transformational leaders will not only concentrate on the emotional behaviors
transactional leaders do not, they will also focus on the task behaviors they do. This is
consistent to the augmentation effect which suggests that high performing
transformational leaders focus not only focus on transformational behaviors but on task
orientated transactional behaviors as well (Bass & Avolio, 1993).

The second reason why it is thought that communication quantity will be higher
in a transformational team has to do with the nature of the messages themselves. A major
aspect of transformational leadership is based on encouraging followers to share there
ideas with the group. It has been shown that in such a cooperative environment,
followers are more inclined to ask questions, help others to clarify the problem or
solution, and assess peer input (Slavin, 1996). As a result, we can expect to see an
increase in communication due to these activities in a transformational condition that are
not present in a transactional condition.

Third and finally, leader communication used to support the transformational
behaviors is more likely to spawn additional communication between team members
compared to transactional leader communication. This is due to the fact that
transformational communication has a highly affective component to it. If the leader
makes comments that address these affective dimensions, it is possible that they could act
as a catalyst or contagion and lead to others in the team making similar affectively based
comments (Kelly & Barsade, 2001; Pugh, 2001) which will increase the overall level of

comments made in the team. On the other hand, communication associated with

30

transactional behaviors is more task orientated and directed towards meeting the goals of
specific team members. It is predicted that this type of communication will be far less
likely to spawn additional comments by other team members than will affective leader
comments. Therefore, based on these three reasons we can expect that there will be more
communication in a transformational team than a transactional team.

H5: In each structural configuration, teams whose leader

used a transformational leadership style will have a higher

level of communication quantity than teams whose leader

used a transactional style.

It is also expected that collocated teams whose leader have been trained to use a
transformational style will have a higher level of communication quality compared to
teams whose leaders have been trained to use a transactional style. This is due to the fact
that followers will more favorably interpret leader behaviors that are targeted towards
their affective states than their simple task based performance. This will lead to a
perception that the communication quality in transformational teams is higher than it is in

transactional teams.

H6: Communication quality will be higher in a collocated
transformational team than in a transactional team.

The collocated nature of hypotheses 5&6 are plotted in Figure 5.

31

 

 

Q 5
g 4.5
E 4
c 3.5
g 3

2.5
S
:5 2
.g 1.5
E
5 0.5 ~-
0 0

Transfonnatlonalfl’ransacflonal leadership In a taco-to-
faco tum

 

 

 

Figure 5. Predicted hypotheses 5 and 6 for a collocated team

Task Complexity
When investigating team processes it is important to consider the task being

accomplished given that many times the task can dictate the team processes employed
and the degree to which they apply. Tasks are so important to teams that they can
actually define a team. For example, Sundstrom, McIntyre, Halfhill and Richards (2000)
suggested that there are six different types of teams: action, advisory, service, project,
management, and production. Each of these kinds of teams performs a different set of
tasks and therefore has different knowledge, skills, and resources. “All tasks contain three
essential components; products, (required) acts, and information cues” (Wood, 1986, p.
64). These are the “building blocks” for a general theory of tasks and can be arranged to
explain to any number of task characteristics such as complexity.

Task complexity describes the relationship between task actions, information, and
products. Any changes in the levels of these components, or the relationships between
them can impact task complexity. Given such degrees of freedom, it is best not to view

task complexity as a uni-dimensional construct but rather as a linear combination of three

32

different variables: coordinative complexity, dynamic complexity, and component
complexity (Wood, 1986).

Coordinative complexity is defined as the number of tasks and the precedence of
relations between each act and every other act in the task. It refers to the sequencing of
actions and the strength of the relationships between information cues, actions, and
products. More specifically, it deals with the timing, fiequency, intensity, and location
requirements of the actions. The more precise the timing, higher the frequency, greater
the intensity, and dispersion of locations, the greater the complexity. As an example,
painting a wall has low coordinative complexity while assembling a car has high
coordinative complexity. In the painting example, it really does not matter what side of
wall you start from or whether you paint top to bottom or vice versa. In the end the wall
is painted just the same. However, a car must be assembled in a very specific order. The
hood can not be installed until the engine is in place and the wheels can not be attached
until the axles are connected.

The second type of task complexity is component complexity. This type of
complexity relates to the number of actions which must be taken by individuals and the
number of informational cues that must be processed. In situations where a large number
of actions must be taken or a high number of informational cues must be processed, a
high degree of component complexity exists. For example, making your bed has less
component complexity than building car. In the case of making your bed, there are only
a few steps which need to be accomplished and they relatively easy to perform.

The final type of task complexity is dynamic complexity. This type exists when

environmental changes impact the relationship between task actions and information cues

33

and products over time. Therefore, it is defined as changes over time in the amount of
coordinative and component complexity (Wood, 1986). As a result, coordinative and
component complexity can be considered to be more static indicators of complexity while
dynamic complexity refers to the degree that these other types of complexity change over
time (Wood, 1986). An increase in dynamic complexity often times accompanies a
change in the environment. For example, air traffic controllers realize an increase in
dynamic complexity by a change in the winds, mechanical breakdowns, or medical
emergencies. Each of these events impacts the dynamic complexity of the task.
Task complexity in a team

The problem with all of these types of task complexity is that they were created with
a focus on the individual and not the team in mind (Wood, 1986). The literature also
follows this trend by typically examining individual task complexity rather than team task
complexity (Campbell & Gingrich, 1986; DeShon & Alexander, 1996; Earley, Lee, &
Hanson, 1990; Gardner, 1990; Kozlowski & Hults, 1986; Paquette & Kida, 1988; Swait
& Adamowicz, 2001a, 2001b). In fact, recent experiments that are advertised to examine
team task complexity fail to do so. These studies either use subjective measures which
generate responses at the individual level (Man & Lam, 2003), use survey items that
focus on the individual level (Akgun, Byme, Keskin, Lynn, & Imamoglu, 2005) or only
vary the individual level aspects of task complexity (Roberts, Cheney, Sweeney, &
Hightower, 2004). However, there is little reason why the types of task complexity
developed by Wood can not be extended to the team level so long as the resulting

conceptualization focuses on that level. Doing so has the added benefit of allowing

34

individual and team task complexity to be compared directly rather than using separate
typologies for each type.

The question then becomes how to define team task complexity using this typology.
In order to answer this question each type must be examined from a team level
perspective in order to determine what aspects of the work performed by teams might
relate to each of these types. To begin, a major aspect of a team that can define its
coordinative complexity is its structure.

Structure is an inherently team based attribute because it defines the way teams
organize themselves. Structure varies based on several different dimensions including
the degree of centralization, specialization, and departmentation (T. Burns & Stalker,
1961; Donaldson, 2001). Another aspect of structure is the degree to which it is arranged
in a functional or divisional structure (Hollenbeck et al., 2002). In a functional structure
each member or group has a specialized function and therefore must work with others in
order to finish tasks which require more than one function to complete. A common
example of this might be a corporation that has dedicated accounting, marketing, and
operations groups. All three of these functions must work together in order for the
corporation to be successful. In contrast, a divisional structure is characterized by
independent groups, each with a complete set of functions that are able to be used in
order to complete the task. An example of this would be a corporation with different
product divisions each with their own, accounting, marketing, and operations department.
Given that the amount of interdependence between groups is higher in a functional

structure we can see that the amount of coordinative complexity would also greater.

35

A major dimension of a task that defines the level of component complexity in a team
is the amount of learning it must accomplish in order to perform well. When the amount
of learning required is high, team members must be connected to a multitude of different
communication channels each providing a different piece of information. They must then
cognitively process this information in order to be able to use it. All of this leads to an
increase in the component complexity of a task since it adds additional actions that must
be performed in order to complete the task.

As with coordinative complexity, it is important to consider the distinction between
the individual and team level. Team level learning derives from the social cognition
movement (F iore & Schooler, 2004), in the sense that it examines “those social
processes... that relate to the acquisition, storage, transmission, manipulation and use of
information for the purpose of creating a group-level intellective product” (Larson &
Christensen, 1993, p. 6). Thus in the end “...teams can process information not only
within, but also between the minds of team members.” Ellis et al.’s (2003, p. 822).
Unless information is transmitted between team members, true team-level learning does
not take place (Johnson, 2006). Therefore, it is the team learning which impacts team
component complexity.

An aspect of a task that can define the level of team dynamic complexity is the
amount of uncertainty it faces. In environments with a high degree of uncertainty team
members need to exhibit problem solving skills and adapt to a constantly changing set of
conditions. However, in a low uncertainty environment team members are exposed to
more routine or patterned activities which do not require the same level of cognitive

processing. Therefore, if a lot of uncertainty exists, the environment changes over time

36

and team members must work in order to counteract any negative impacts that they face
as a result of this. As a result, an increase in the uncertainty of the environment leads to
an increase in the dynamic complexity of a task.

In summary, coordinative, component and dynamic complexity are all types of
complexity that are well suited for a team level analysis when they are defined using
team level conceptualizations. As a result, a high level of task complexity within a team
will be defined as an environment in which a high level of coordinative (conceptualized
using a functional structure), component complexity (conceptualized as the amount of
team learning) and dynamic complexity (conceptualized as the amount of uncertainty)
exists. This typology is summarized in Table 1.

Table 1. Task complexity in a team

 

 

 

 

 

 

 

liigh task complexity Low task complexity
Coordinative Functional structure Divisional structure
Component High team learning Low team learning
Dynamic High uncertainty Low uncertainty

 

 

Such differences in complexity, corresponds in part to the differences between
working harder and working smarter. Within the popular management press there has
been a substantial amount written about the differences between working harder vs.
working smarter (Suj an, Weitz, & Kumar, 1994). Working smarter has been
conceptualized as being based on adaptive behaviors (Sujan, Weitz, & Kumar, 1994) and
the ability to plan, both of which have a heavy cognitive component to them (Fang,
Palrnatier, & Evans, 2004). Here the focus is not on the number of actions that are
required to complete a task but rather on the level of interdependence, precedence, and
dynamism of the actions and information cues. In this situation there is not so much of

an increase in the physical task demand but rather in the cognitive task demand. In this

37

environment teams are forced to work together in order to develop a set of information
complete enough to base good decisions on. Such a state can be characterized by a large
number of interdependencies, elevated need for learning, and increased uncertainty, all of
which correspond to a high level of task complexity.

One the other hand, working harder can be thought of as an increase in the
amount of labor that an individual performs (Suj an, Weitz, & Kumar, 1994). In this
situation the amount of physical effort used to accomplish the task is greater but there is
no change to the task itself. As a result, team members are forced to work quicker in
order to perform well but the task complexity of the task is low. Therefore, this condition
corresponds to a situation in which a team works harder but not necessarily smarter.

'_I‘_e_am Task Complexity and Communication
In the past task complexity has been shown to impact a number of different constructs

including information processing strategies (Paquette & Kida, 1988), non-task related
movements (Gardner, 1990), goal acceptance, personal goals, and performance (Earley,
1985). This study adds to this list by proposing that higher task complexity leads to a
greater amount of team communication

As previously mentioned, a high level of task complexity is defined as an
environment in which a high level of coordinative complexity (functional structure),
component complexity (team learning) and dynamic complexity (high level of
uncertainty) exists. With regards to structure, it has been thought that a functional
structure has the potential to lead to an increase in communication as compared to a
divisional structure (Johnson et al., 2006). This is due to the fact that when a functional
structure is present each team member only has access to a particular asset. If each team

is exposed to a variety of different problems, it is not until the specialized assets of

38

individual members are combined that an effective system to complete the assigned task
is realized. In other words, each person has a different “piece of the puzzle” in a
functional structure which leads to an increased level of interdependence. It is therefore
hypothesized that managing the increase in the level interdependence between groups or
people will lead to higher levels of communication. However, if a divisional structure is
used, each team member has a number of different assets from which to draw. If a
member is again exposed to the same variety of problems, we would expect that they
would be able to solve them without the help of others. This would decrease the required
level of coordination within the group and therefore the overall level of communication
between members.

When it comes to team learning we can expect that an increase here would
also drive up the level of communication. It has been shown that communication,
in terms of sharing information, ideas, and cognitive processes, is an important
component of team level learning (Hinsz, Tindale, & Vollrath, 1997). In order to
effectively learn at the team level, team members must communicate their ideas to
the rest of the team. MacMillan, Entin, and Serfaty (2004, p. 61) call this “the
hidden cost of team cognition,” noting that communication between team
members has no analogue at the individual level.

With regards to uncertainty, an increase here can force team members to work
together more closely in order to understand what is happening in the environment and
then determine the most appropriate course of action. Supporting this notion is Kraatz
(1998) who showed that increases in communication lead to decreases in overall

uncertainty. Therefore, it can be expected that in teams which are sufficiently motivated

39

to perform well, a positive relationship will exist between the level of uncertainty and
team communication.

Such a predicted increase in communication relates to a condition in which a team
is working smarter and not harder. As mentioned earlier, working smarter is
characterized by the ability of a team to plan and remain agile. By communicating more
and sharing information the team is exhibiting behaviors consistent with working smarter
not harder. No one is required to do more, they just need to work together which
increases the level of planning, coordination, and cooperation within the team. In the
end, this will increase the amount of communication.

H7: The quantity of communication will be greater in
environments with a high level of task complexity than it
will be in environments with a low level of task

complexity.

Leader Centrality
Besides communication related variables, leader centrality is also proposed to act

as a mediator between team structure, leadership styles, task complexity and performance
outcomes. Traditionally, centrality has been conceptualized as the strength of an
individual’s social network within an organization (Brass, 1984) and reflects the extent to
which interactions are concentrated in certain individuals rather than distributed equally
among all members (Sparrowe, Liden, Wayne, & Kraimer, 2001). The strength of these
connections has been shown to directly relate to an individual’s power (Ibarra &
Andrews, 1993), performance (Sparrowe, Liden, Wayne, & Kraimer, 2001), and the
amount of influence they wield within a group (Brass, 1984). Using the resource

dependency perspective, it has been theorized that much of this comes from the ability of

40

highly central individuals to have greater access to, and control over information (Brass,
1984; Salancik & Pfeffer, 1977).

Centrality has been conceptualized as the number, strength, and significance of
connections an individual has within a social network. More specifically, it has been
thought of as the (a) degree, or number of contacts, (b) closeness or proximity, and (b)
the betweenness (Freeman, 1979). Degree can be thought of as the number of direct
connections an individual has to others within a social network, closeness or proximity is
the ease with which someone can access another individual in that network (Burkhardt &
Brass, 1990) and betweenness can be thought of as the potential control that individuals
have over others (Brass, 1984). One common thread between these different
conceptualizations of centrality is that they all are objective. However, more recent
studies have started to consider the more subjective nature of centrality. In addition to
examining the simple objective presence of connections within a network these studies
also consider the subjective strength of these connections. Such studies tend to downplay
the degree and closeness in a network and emphasize the betweenness that exists. For
example, Ibarra (1993) used an “aggregate prominence” scale to examine not only the
existence of connections between individuals in a network but also the centrality of those
who were connected. Drawing from this study, Sparrowe et al., (2001) asked subjects to
characterize the strength of their own network connections. Using such an approach not
only characterizes the existence of connections but also the strength of these connections.
Since, in the present study the existence of the connections is preordained by the given

structure, it is the subjective strength of these connections which will be emphasized.

41

In addition to different conceptualizations of centrality there are also several
different types of social networks. For example, Brass (1984) considers workflow
networks, communication networks, and friendship networks while Iberra (1993)
examined communication, advice, support, influence and friendship networks. Each of
these networks might yield different outcomes for the same set of initial conditions so it
is important to also specify what type of network is being considered when examining
centrality. For this study an advice network will be selected. As a result, leader
centrality for this study will be defined as the subjective strength of the leader’s
betweenness or the potential control that they have over others in an advice network

Structure and Leader Centraliir
Several different antecedents of centrality have been investigated including

individual attributes, formal position (Ibarra, 1993), technologies (Burkhardt & Brass,
1990) and LMX (Sparrowe, 2005). To this list the present study adds structure such that
the centrality of the leader is predicted to be higher in a collocated team compared to
virtual team. This difference is thought to exist because as teams migrate from a
collocated team to the virtual world there will be a different amount of perceived control
and influence that the leader is expected to have over the team members. For example, in
a collocated team all of the team members, including the leader, can see each other face-
to-face. In this configuration the perceived level of centrality, as conceptualized as
betweenness or the amount of control, that the leader is able to exert will probably be
high due to the fact that it is very salient to all who the leader is in this configuration. In
this structure, the leader’s guidance is given directly to each team member and without a
good reason it would probably be considered counterproductive, tasteless, or even

damaging to overall team performance to ignore their direction.

42

However, in a virtual team all the members exist within remote nodes, which
causes a decrease in co-locatedness and an increase in the use of computer mediated
communication systems. It is proposed that these changes will lead to a decrease in the
level of perceived leader centrality for at least two reasons. First, the increased use of
computer mediated communication systems will make it more difficult for the leader to
effectively influence team members. For example, he or she will no longer able to use
non-verbal behaviors or emotions to persuade team members. Second, due to the
decrease in the social presence, the leader is not immediately visible to the members of
the group which has been shown to be an important antecedent of centrality (Klein, Lim,
Saltz, & Mayer, 2004).

It is predicted that in a reachback team the amount of leader centrality will
actually decrease further. This is due to the fact that in a reachback team the leader is the
only one who is not collocated with the team. This will establish a strong faultline within
the team between collocated team followers and the remote team leader (Lau &
Mumighan, 1998) which will make the leader feel partially ostracized and alienated
relative to a co-located group that is growing in cohesiveness over time. As has been
written, “The faultline model (Lau & Mumighan, 1998) suggests that, when groups split
into subgroups, (even implicitly), the members’ group-related identities are associated
more with their subgroups than with the entire group” (Lau & Mumighan, 2005, p. 646).
Given that the group identities of the members in the collocated group will be associated
more with this subgroup than the entire team, a cohesiveness will begin to emerge within
this subgroup that does not include the leader. This cohesiveness can be a substitute for

leadership (Kerr & J errnier, 1978) and local emergent leadership could develop among

43

the co-located team members. It is predicted that this will have the effect of causing
remote team members to discount the leadership offered by their leaders which will
manifest itself as a reduction in their influence and perceived centrality. However, when
all of the team members are remote, as is the case in a virtual team, this faultline will
disappear and with it the negative feelings associated with it. In this situation remote
team members will understand that everyone else on the team is in the same situation and
feel more connected to each other and the leader.

This set of relationships is significant because they suggest that leader centrality
in a reachback team is lower than it is in either a collocated or virtual team. This is
potentially interesting because one would expect that leadership centrality would increase
as individuals in remote nodes combine to form one large group. However, it is predicted
here that if the team leader is remote, the amount of leader centrality will decrease
regardless of the number of people in the subgroup. Therefore, it is not the number of
people in each subgroup which is important but rather the number of subgroups. This is
because as the number of subgroups increase the saliency of the faultlines between them
will decrease. Therefore, the effect of the faultlines will be greatest when there are only
two subgroups, as is the case of a reachback team.

H8: Team member perceptions of leader centrality will be
higher in a collocated team than in a reachback team

H9: Team member perceptions of leader centrality will be
lower in a reachback team than a virtual team

Hypotheses 8&9 are plotted in Figure 6.

44

 

h

or
oar-smmurooinc-moi

A

Leadership Contrallty.
N

O

 

Face-to-face Reachback Virtual

 

 

 

Figure 6. Predicted hypotheses 8 and 9

ngdership Style and Leader Centrality
It is proposed that in a collocated team, a transformational leadership style will

increase perceived leader centrality more than a transactional style. As already
mentioned a transformational style is based on the ability of leader to motivate and
influence members to achieve higher performance. Similarly, centrality can be thought
of as the amount of influence that members have over others in their group (Sparrowe,
Liden, Wayne, & Kraimer, 2001). As a result, the amount of leader centrality can be
thought of as the amount of influence that a leader has over his team members. Given
then that transformational leadership is based on many of the same antecedents and
constituents of leader centrality, it stands to reason that if the leader exhibits stronger
transformational leadership behaviors, the amount of perceived leader centrality will also
increase. For example, one of the dimensions of transformational leadership is idealized
influence. If this dimension was to increase, leader centrality would also increase given
that it can be considered a proxy for influence. Further, leaders who are better able to
motivate, intellectually stimulate, and provide individualized consideration could also be

expected to have a higher level of centrality. In contrast, a transactional leadership style

45

is based on rewards and focusing on mistakes. If leaders exhibit behaviors consistent
with this style, members might respond but they may do so because they feel coerced
rather then influenced. As a result the following hypothesis is forwarded:

H10: A positive relationship exists between

transformational leadership and the perceived leader

centrality in a collocated team

Having now completed the examination of the relationships between the proposed

independent variables and the mediators we can now examine how overall team
effectiveness is impacted by these constructs. Effectiveness can be conceptualized in
many different ways but for this study it will be comprised of three different variables:
objective performance, team satisfaction, and leader satisfaction. Objective performance
is often thought of in terms of speed and accuracy while satisfaction subscribes to the
notion that teams must also be able to remain viable and keep making high quality
decisions over an extended period of time (Kozlowski & Bell, 2003). The following
section provides additional details regarding each of the selected components of
effectiveness after which the relationships between these variables and the mediators

already described will be explored.

Objective Performance
The first characteristic of objective team performance is the speed at which they

work. Speed can be considered a dimension of performance because teams that work
faster can perform more work. This becomes especially important when teams have a
limited amount of time to complete multiple tasks. Teams that can accomplish more
tasks in a fixed amount of time will then be considered to be better performers. The
second dimension of objective performance is accuracy. Teams might be very fast but if

they are not accurate or make poor decisions their speed will not be important. In fact, a

46

quick team might even be detrimental in this situation given that they will be making
more bad decisions.

Satisfaction with the tea_n_r
Traditionally team effectiveness has been thought of as being comprised as the

quantity and quality (speed and accuracy) of team related decisions (Shea & Guzzo,
1987). However, Hackman (Hackman, 1987, 2002) and others have proposed that team
viability, or the satisfaction of the team, should also be considered. The thought is that
without the team being satisfied with the experience there is little chance that they will
continue to perform. Therefore, this study will not only examine the more traditional
“external” team effectiveness constructs of speed and quality but also the “internal”
construct of team satisfaction.

Satisfaction with the leader
As a compliment to the level of satisfaction with the team, the level of

satisfaction with the leader will also be explored. Team satisfaction is important but
given the important position that leaders play in hierarchical teams it is also important to
examine the effects associated with how the team feels about these individuals.

Communication and Team Effectiveness
As previously mentioned, communication quality at the team level has both a

behavioral and cognitive component. From a behavioral viewpoint communication
quality is the ability of the team to gather, transmit, and interpret information (J ablin,
1994). When communication quality is low team members are not able to clearly
communicate their ideas, thoughts, or intentions to each other. In these situations they
need to spend more time making sure that what they communicate is what they want to
communicate. For example, Propp and Nelson (1996) found that teams which where able

to more effectively communicate how to analyze the problem or task and orientate or

47

establish procedures made more effective decision. In the same way it is theorized here
that groups which have a higher level of communication quality will realize a higher level
of performance.

From a cognitive viewpoint quality is the ability of a team to establish common
team cognitions and use those cognitions to promote communication quality. In the same
way, the present theory suggests that the ability of teams to form these cognitive
connections also leads to an increase in performance. If the team is unable to quickly
establish these links then the time spent correcting these problems is time that cannot be
applied to other task work. As a result the following hypothesis is presented:

H11: A positive relationship exists between
communication quality and performance (objective and
subjective)

As the amount of communication increases there is a natural positive relationship
that exists with performance attributes. This is due to the fact that as the level of team
communication increases there will be more information that is available to each member
to processes, and use (Propp & Nelson, 1996). This will lead to more informed decisions
which will increase their quality (Hollenbeck, Ilgen, LePine, Colquitt, & Hedlund, 1998).

H12: A positive relationship exists between
communication quantity and performance (objective and
subjective)

Le;_ader Cemlitv and Team Effectiveness
Centrality has been shown to be an antecedent of influence such that as an

 

individual’s centrality grows so does their influence over other team members (Bass,
1985). Given that influence can be considered an enabler of leadership, studying leader

centrality helps form a richer picture of the leadership process. Further, as a more

48

proximal indicator of leadership compared to leader effectiveness, it helps isolate the
specific effects of the phenomena.

Leaders are not only classified as such due to the power which has been conferred
upon them by the organization, but also due to the fact that they have access to
information that other members do not have. Based on this access they are presumed to
have a latent value to the team that may not be realized because of the structure,
leadership style, or task environment. This value is realized when the leader provides this
information to the team which then acts on it. The chance that a team will actually
receive this information and then use it is partially a function of the leader centrality.
Since leader centrality can be thought of as a proxy of influence, there is a greater chance
that team members will use the information provided to them if centrality is high. Thus,
team with leaders who have high centrality, and thus more influence, stand a greater
chance of using this information.

In this study the leaders will have aggregated information related to threats and
opporttmities in the environment that no other member has. Therefore, if they are more
central and have more influence, there is more of a chance that this information will be
used by the team. The more this information is used, the more that the threats will be
avoided and opportunities will be exploited.

H13: A positive relationship exists between perceived
leader centrality by remote workers and performance
(objective and subjective)

Now that all the direct effects in the model have been considered we can turn our

attention to the interactions that these constructs might have with each other. The

49

purpose of this is to provide a more complete and accurate picture of leadership within

virtual structures.

50

CHAPTER 2 - INTERACTION EFFECTS
Although it has been suggested that communication and leadership outcomes may
suffer in virtual and reachback teams, it is now proposed that different leadership styles
and task complexity might play a significant role in terms of ameliorating these effects.

Structure, Leadership Style, and Communication Quality
Even though Hypothesis 6 proposes that teams whose leaders exhibit a

transformational leadership style tend to have greater levels of communication quality in
a collocated team, it is suggested that communication quality in teams whose leader uses
a transactional style will be higher in both a virtual and reachback structure. This is
based in part on the fact that transformational leaders rely on highly affective based
communication but since computer mediated communication cannot easily support such
content, leaders who must use these systems will be at a disadvantage. Further,
transactional leaders do not rely on emotionally laden communication. They focus on
contingent reward and management by exception, which are based more on unemotional
exchange processes. As a result, an increase in the usage of computer mediated
technology between team members will not negatively impact their leadership style as
much.

In a reachback team the difficulties that a transformational leader faces are not
quite as pronounced. They still must lead using only computer mediated communication
devices but the collocated nature of the larger subgroup promotes transformational
behaviors within the subgroup because these members can still interact face-to-face and
thereby increase the emotional content of their communication. This might make it
appear that overall team communication quality is not as low as it is when everyone in

the team is remote. On the other hand, the effect of a reachback team when a

51

transactional style is used will probably be much the same as it was in a virtual team. In
this situation, the existence of a collocated subgroup does not promote transactional
behaviors as it does transformational behaviors. Here, the team members might be
collocated but the leadership being provided still comes from a remote source. As a
result, there is not expected to be a major change in the overall level of communication
quality between virtual and reachback teams who have a transactional leader.

H14: The relationship between structure and

communication quality is contingent on leadership style,

such that transformational style is superior in collocated

contexts, but a transactional leadership style is superior in

reachback and virtual contexts.

This is shown below in Figure 7.

 

9‘
01 01
r I
l
l
l

 

 

-‘ + Transformational

--- I'-- Transactional
1.5 a - -—-— ~—--—- —~/ ‘
1] - , ._____--,. _ . _
0.5

Face-to-face Virtual Reachback

 

 

 

Communlcation Quality
N s»
M O! (A) at b

 

 

 

 

 

 

Figure 7. Predicted hypothesis 14

Leadership style, Task Complexity, and Communication Quantity
One of the important revelations in the evolution of leadership studies was the

conclusion that contextual variables can be a major determinant of what type of
leadership style is most appropriate (Y ukl & Fleet, 1992). This notion is classically
referred to as the contingency approach to leadership and suggests that environmental

factors can influence the effectiveness of different leadership styles. For example,

52

Fiedler (1967) showed that the best leadership style to use is dependent on situational
variables of leader-member relations, task structure, and position power. Other popular
contingency leadership theories include Houses’ (1971) path- goal theory, and Hersey and
Blanchards (1969) Situational leadership model. Path-goal theory states that leaders
motivate higher performance in subordinates by acting in ways that influence them to
believe valued outcomes can be attained by making a serious effort and Situational
Leadership suggests that the optimal amount of task-oriented and relations-oriented
behavior by a leader depends on subordinate maturity.

Consistent with these theories it is suggested here that the effectiveness of the
transformational or transactional leadership style is contingent on task complexity.
Specifically, I propose that in an environment with a high level of task complexity, a
transactional leadership style will increase leadership centrality, whereas in an
environment with a low level of task complexity a transformational leadership style will
lead to high leadership centrality. This is due to the fact that in an environment with a
high level of task complexity, a larger amount of communication and coordination is
necessary. If a transformational leader attempts to form an emotional connections with
his team in order to increase his or her perceived level of inspirational motivation,
idealized influence, or individual consideration, this is time that is not being applied to
those coordination activities and communications that need to be occur. On the other
hand, both dimensions of transactional leadership focus on the tasks performed by the
followers. For example, contingent reward is based on rewarding followers for their task
performance and management by exception focuses on the mistakes the followers make

while performing certain tasks. This is consistent with previous studies which have

53

shown that transactional leaders tend to focus on task related cognitions more than
anything else (Goodwin, Wofford, & Boyd, 2000; J. C. Wofford, Goodwin, &
Whittington, 1998). It is this focus on the tasks that will make a transactional leadership
style preferable when task complexity is high.

On the other hand, in environments with a low level of task complexity there is
not as much of a need for communication or coordination. As are result leaders do not
have to spend as much time addressing such task work related activities and can spend
more time appearing transformational. In fact, if the level of task complexity is low it is
suspected that a transformational leader will thrive. In this situation leaders do not have
to worry so much about making sure that the team communicates task orientated
activities but instead can concentrate on keeping the motivational level of individuals
high as they perform boring or uninteresting tasks. It is in this environment that the
ability of a transformational leader will begin to shine for it is here that they can
capitalize on their ability to appear charismatic, motivating, and inspiring.

Support for such a theory is provided by studies which have shown that positive
affect has a positive impact on outcomes including motivation, judgment, and decision
making ability (Erez & Isen, 2002; Forgas & George, 2001; George & Brief, 1996).
Given that boredom has been shown to be an antecedent of lower positive affect (Gordon,
Wilkinson, McGown, & J ovanoska, 1997) and low task complexity is the primary reason
for such boredom (Fisher, 1993) the potential exists that positive affect will decrease
when task complexity is low. However, by expressing confidence that goals will be met,

coaching individual members, and inspiring subordinates to perform better,

54

transformational leaders can lift the spirits of followers and increase their positive affect.
Such behaviors might then mitigate the negative effects of a boring task.

H15: The relationship between leadership style and

leadership centrality is contingent on the task complexity,

such that a high task complexity is superior for a

transactional leadership style, but low task complexity is

superior for a transformational leadership style.

Structure. Leaderslm) Stvle. and Leader Centrality
The present theory suggests that in a collocated team a transformational

leadership style will result in a higher level of leader centrality. This is due to the fact
that in a collocated team, leaders who exhibit a transformational leadership style are
attending to both the individual needs of the group members and the goals of the team. If
members feel that their leaders are focusing on their own needs there will be a greater
chance they will form a positive affective attachment to the leader and such an
attachment will lead to a higher leader centrality. In contrast, transactional leaders are
more focused on the task itself and any relationship with the followers is based on a
contingent reward or comparisons to standards rather than affective components.
Therefore, followers will not feel as connected to their leaders in this context.

However, in a virtual team it is thought that these results will be reversed. In this
situation, teams whose leaders have been trained to use a transformational style will have
a much lower level of leader centrality. This is due to the fact that in this structure there
will be a complete loss of any face-to-face communication and as a result very few
affective components will be present. Given that transformational leaders heavily rely on
these components their absence will cause them to have less influence over team
members. However, if a transactional style is exhibited, it is predicted that the level of

centrality will not fall nearly as dramatically. In this situation the leaders behaviors do

55

not require an affective component to be present so not having them present will not be as
much of an issue as it was for the transformational leader.

In a reachback team it is proposed that the level of leader centrality will increase
(compared to a virtual team) for teams lead by a transformational leader. This is due to
the fact that if a transformational style is being used it is possible that there could be
some affective components at work within the collocated group that could be attributed to
the leader. In contrast, when a reachback team is lead by someone who has been trained
to use transactional behaviors the level of leader centrality will be lower in a reachback
team compared to a virtual team. This is primarily driven by the increase in the saliency
of faultlines between remote workers and collocated workers. In a reachback
configuration the impact of the leadership provided by a transactional leader will be the
same as it was in a virtual configuration. The only thing that has changed is the increased
saliency of the faultline. As a result the amount of perceived leadership centrality will
decrease in a reachback team compared to a virtual team for transactional leaders.
However, due to the fact that this structure still severely restricts the affective
mechanisms that transformational leaders need to operate, it is suggested that teams lead
by a transactional leader will still exhibit a higher level of leader centrality.

H16: The relationship between structure and leader
centrality is contingent on leadership style such that a
transformational style enhances centrality in collocated
contexts, but a transactional style enhances centrality in

reachback and virtual contexts.

This is shown below in Figure 8.

56

 

 

Leadership Centrality

9°
or
.1

 

.0 r‘ I”
O 01 A 0‘ N U? (D
I I I I 1 I

 

 

Face-to-face Virtual Reachback

 

 

—o—- Transfonnationall
-~I~-- Transactional

 

 

Figure 8. Predicted hypothesis 16

57

 

CHAPTER 3 - METHOD

Choice of setting
This study was performed as a laboratory experiment. There are several

advantages this approach has over other research designs including the ability to infer
cause and manipulate variables One of the primary goals of experimentation is to derive
causal relationship. This process involves identifying specific causal events and their
relationship to outcomes along with any intervening mediators. Experiments have an
advantage over other popular research designs such as the cross-sectional survey in that
they do not simply describe a covariation between constructs but also establishes
temporal precedence as defined by John Stuart Mills. An experiment also allows
researches to manipulate active variables, which means that they can control variance
instead of relying on natural occurring conditions favorable to answering the particular
research question. This has the effect of allowing the researcher to create the most
efficient research design possible (McClelland, 1997) and maximize the systemic

variance of the active variables (Kerlinger & Lee, 1999).

Participants
The participants for this study where three hundred and forty four undergraduate

students enrolled in an upper-level management course at Michigan State University.
The sample was comprised of 56.6% male and the mean age was 21.74. These subjects
where arrayed into 86 four-person teams for the task. Participants signed up for a
research session at their discretion, and were randomly assigned to teams in order to play

two 30-minute simulations. Each subject was given course credit for their participation.

Power analysis
For this experiment an a priori power analysis was performed to establish the

desired sample size in order to achieve a power or .8. Four different types of statistical

58

tests were performed in order to test the hypotheses so four different calculations needed
to be performed, each with their own input variables, to determine the power level. The
first test was multiple regression with three independent variables (Hypotheses 1-4, 8-9,
11-13). The second was an independent t-test (Hypotheses 5, 7). The third was a
moderated regression that included one independent variable, one dependent variable and
a single categorical moderator (Hypotheses 14-16) and the fourth was a hierarchical
moderated regression (Hypotheses 6,10). Equations for the first two tests came from
Cohen (1992; , 2003) while the moderated regression came from Aguinis (2004).
Equations for the hierarchical moderated regression came from a combination of both
sources.

For this analysis several assumptions needed to be made. First, all the tests
assumed an alpha level of .05 for a one-tailed test. For the multiple regression and t-tests,
the effect size needed to be estimated. The effect size for multiple regression is f’2 (based
on R2) while for a t-test it is Cohen’s d. To estimate f2 (using R2) several previous studies
which have investigated similar phenomena were referenced. Recent empirical studies
that examined the effects of media on teams have shown R2 ranging from between .24 to
.43 with a mean of .35 (Kahai & Cooper, 2003). Therefore, a conservative estimate R2
for this study was .30 which yields a f‘2 of .4285. Cohen’s d was set at .8 for the
independent t-test which is similar to an R2 of .3. For the moderated regression a
correlation between the IV and DV for each group was estimated at .3 for one group and -
.3 for the other. The correlation between the IV and moderator was set at .3 also.

Finally, the standard deviation was assumed to be one. For the hierarchical moderated

regression the number of predictors in the first set was two and one in the second set.

59

Also, the anticipated incremental effect size f2 for the second set was assumed to be .2.
Using these values the required sample size for the multiple regression was found to be
30, for the independent t-test it was 42, for the moderated regression it was 210, and for
the hierarchical regression it was 43.

Task Description
Participants played a networked computer game based on a military command

and control context. This game is a modified version of the Distributed Dynamic
Decision-making (DDD) simulation developed for the Department of Defense for
research and training purposes (Miller, Young, Kleinman, & Serfaty, 1998). The version
of the simulation played in this experiment was developed for use by four member teams
with little or no military experience (MSU-DDD).

The game playing area is comprised of a 20x20 grid that is further broken down
into a quad cell with 10x10 regions. Each region has a base that is located in the middle
of it. The purpose of the game is for players to monitor the ground and air space around
the bases and keep enemy targets out of the region which has been assigned to them. To
perform this function, each player is assigned assets allocated to their base which have
the ability to be directed towards and prosecute targets

The game is programmed to present a fixed radar representation only of the
region they have been assigned. Therefore, any target outside of radar range of an
individual’s base is usually invisible to them. However, each mobile asset also has the
ability to detect and identify targets. As a result, team members can determine the nature
of a target outside their bases radar display either by working together and asking their
teammates to share information or by launching a vehicle and moving it near the target.

Typically, the mobile assets for each team are comprised of AWACS planes,

60

tanks, helicopters and jets. Each of these vehicles varies in its capacities on four different
dimensions: (a) range of vision, (b) speed of movement, (0) duration of operability, and
((1) weapons capacity. However, for this study the AWACS was not but the leader sat in
the position typically assigned to this role. To ensure that they were given an
informational advantage over the other team members, they were allowed to see all the
targets on the entire screen.

There were eight types of “standard targets” that were known a priori to have
specific characteristics. These were taught in the training session prior to the start of the
simulation. Each target had a combination of three different attributes; air or ground,
friendly or unfriendly, and the three different levels of power it takes to disable them if
they are unfriendly. There were also four types of unknown targets. These were targets
that even. after the players identify them they still do not know what they were. Each
correspond to a different type of ground target so they had to figure out which is which in
order to perform well.

During the games, subjects were given a number of different episodes to
complete. Each episode could be considered a different task which relates to a larger
problem. Typically these episodes consisted of a number of enemy targets that
simultaneously attacked the team’s bases. In order to score well on the simulation, the
followers needed to work hard to complete the tasks and the leader needed to effectively
fulfill their role.

Manipulations, Measpresfiaknd Reliability
This experiment consisted of a 3(structure) x 2(leadership style) x 2 (task

complexity) mixed factorial design. It is mixed factorial design because task complexity

was a within subjects manipulation. The three different types of structure (collocated,

61

virtual, and reachback) were crossed with the two different types of leadership styles
taught (transformational and transactional) which were crossed with a high and low
complexity environment. Each of variables examined along with their measures is
presented below. A complete listing of measurement items can be found in Appendix A.

Structure
Structure was manipulated by having all the participants play the simulation in the

same room if they were in a collocated team or different rooms if they were in a virtual
and reachback team. For the collocated condition, all team members were assigned to the
same room and arranged such that they could see each other (see Appendix C for pictures
of the rooms). For the virtual team, subjects where assigned to stations in separate rooms
after the training. In the reachback teams only the leader was assigned to a station in a
different room. It is thought that training the members together and then dividing them
up is consistent with the population that this study was intended to model. For example,
most response teams typically have a home base and are trained together but when a
disaster strikes, a portion of the team is forward deployed into the effected area.

Subjects in the virtual and reachback teams were able to communicate with their
non-collocated teammates via a voice over intemet (VOIP) computer network
application. By using such an application all members of the group could hear what
everyone else was saying. Such an application is analogous to a telephone switch since it
allows all those who are connected to it via a computer network to communicate using
headset and microphones. All subjects in all three structures wore a headset which
consisted of a single speaker that covered one ear and a boom microphone. Even thought
they were all in the same room, those in the collocated structure also wore headsets to

both record their conversation and to decrease the chance that the headsets could act as a

62

confound. A headset with only one speaker was used to allow followers in the reachback
configuration to easily hear their remote leader and collocated teammates simultaneously.
In the collocated and virtual structures the VOIP application used was Ventrilo by
Flagship Industries, Inc. Everyone’s voice was recorded on a common audio channel
using Ventrilo’s internal recording capability. Communication in the reachback
structure performed using using Skype which is now owned by eBay.

Ventrillowas the preferred application because all of the software and hardware
used was fully controllable and able to be isolated. Skype on the other hand is an Internet
based application so it relies on a, very high quality and reliable intemet connection which
is based on factors which are usually uncontrollable. The reason it was used at all was
because it was discovered during data collection that a 0.7 second communication delay
existed using Ventriloa between when someone talked and when others heard it. While
this was acceptable for the virtual configuration because everyone was in a different
room, and for the collocated structure because everyone’s headset’s were disabled, it was
not acceptable for the reachback structure. In this configuration, everyone’s headsets
needed to be activated to hear the remote leader but a 0.7 second communication delay
would have created a severe echo effect in the room with the follower subgroup. Once
this issue was discovered, several other industry leading VOIP applications were tested
like TeamSpeak, but all were found to have the same 0.7 second delay. As a result,
Skype was used to communicate between team members and HotRecorder was used to
record the conversation. In the end, no problems materialized while using this
application. It should be noted that each player’s voice was also recorded on a separate

audio channel using Jet Audio by Cowan America, Inc.

63

In this study the different structures will be dummy coded using the reachback
team as the control group. This way all three groups can be compared to each other.

Leadership Style
One of the more difficult problems to overcome when performing lab experiments

that investigate the effects of leadership behaviors is ensuring the desired behaviors are
actually exhibited during the experiment. Two solutions for this problem involve either
training participants to exhibit specific behaviors or using confederates. Confederates are
covert agents of the researchers and are typically trained to perform a specific purpose in
the group. As such, they represent a manipulation performed on the group. For example,
confederates who have been trained to exhibit either a transactional or transformational
and a participative or directive leadership style have been used in several laboratory
experiments (Kahai, Sosik, & Avolio, 1997, 2004; Sosik, Avolio, & Kahai, 1997).
Training subjects is another common method used to examine the effects of
leadership style. Using this approach, a subject is chosen to receive instruction that will
teach them how to exhibit behaviors associated with a certain leadership style: This
individual is then introduced into the group so that the effect of that style on the group
can be studied. This approach was selected for this experiment for several reasons. First,
training has been shown in previous studies to have an impact on leader behaviors. For
example, training to increase the procedural justice exhibited by leaders was shown to
have a definite relationship with the perceived procedural justice behaviors displayed by
the leader (Skarlicki & Latham, 1997). More specific to leadership behaviors, it has been
shown that training can increase the number of behaviors associated with
transformational and charismatic leadership (Barling, Weber, & Kelloway, 1996; Dvir,

Eden, Avolio, & Shamir, 2002; Towler, 2003). Of course, this approach relies on the

64

strength of the training to elicit the correct behaviors. Because of this it might be argued
that behaviors can be changed only after extended training sessions and long exposure to
the material. However, it has been shown that training to improve decision making that
has only lasted three hours has been shown to have an effect on behavior over two years
later (Ganzach, Pazy, Ohayun, & Brainin, 2002).

The training for this experiment began by randomly identifying a leader, subject
to their ability to fluently speak English, from the group of people that attended each
session. The leader was then given a 30 minute presentation which explained what types
of behaviors they were expected to exhibit. This material was developed based on
similar instructional information developed for previous studies (Dvir, Eden, Avolio, &
Shamir, 2002; Kirkpatrick & Locke, 1996; Towler, 2003) and was consistent with
previous studies that involved leadership training (Barling, Weber, & Kelloway, 1996;
Dvir, Eden, Avolio, & Shamir, 2002). The training consisted of a Microsoft Powerpoint
presentation, with a integrated soundtrack, that explained the type of leadership they had
been asked to exhibit, what the different dimension of this style are, and general and
specific examples of behaviors that are consistent with this style of leadership. General
examples of behaviors included comments like “speak in a captivating voice” for
transformational style. Specific comments (which were game dependent) included
statements like “make it clear to each of your followers who is in charge of each action”
for transactional leaders.

In order to keep them interested and engaged during the training several different
contemporary movie clips were shown to demonstrate the dimensions of each style. To

aid them in appearing transformational or transactional, they were given a summary of

65

the slides and a list of comments, similar to the quiz, which included both
transformational and transactional comments specific to the task, both of which they
could refer to during the game. Finally, they were given a statement to read before the
games began which was intended to make them appear more transformational or
transactional (Kirkpatrick & Locke, 1996). All of these items appear in Appendix B
along with the soundtrack script for each type of training.

It was hoped that administering the training so temporally proximal to the
manipulation would increase the number of specific behaviors each leaders would
exhibit. For each session one leader exhibited a transformational style and the other
exhibited a transactional style. Since transactional leadership is based on economic
exchange principles and the contingent reward, leaders who were selected to exhibit
transactional behaviors were asked to emphasize the financial incentives in the game but
the transformational leader was not told to do this. Instead the trainer informed the
transformational teams of the financial incentives before the games began. At the end of
each data collection period, the team with the highest normalized offensive and defensive
score was awarded $300. The second place team was awarded $200, and the third place
team was given $100. There were three separate data collection periods used for this
experiment so these incentives were paid out three separate times.

In this study, leadership style will be manipulated via a training program and
coded as 0 for those who receive transactional leadership training and a 1 for those who
receive transformational leadership training.

Task Complexity
The task complexity of the games where manipulated so that one game had a high

complexity and the other had a low complexity. As mentioned earlier, a high complexity

66

environment is characterized by a functional structure, high team learning, and a high
level of uncertainty. Each of these were intended to manipulate the three types of
complexity discussed by Wood (1986) (component, coordinative, and dynamic) as shown
in Table l.

The structure was manipulated by changing the type of vehicles that each team
member had. This was done to manipulate the dimension of component complexity. In
the functional structure each team member had all the same type of vehicle. For
example, one member had all the tanks, another had all the jets, and the other had all the
helicopters. For the divisional structure each team member had one of each vehicle such
that each member had one tank, one jet, and one helicopter.

The level of learning was modified by changing the number of unknown tracks in
the game. This was done to manipulate the dimension of coordinative complexity.
Again, unknown targets are targets which the players still do not know the status of even
after they identified them so they must work together as a team to figure it out. In the
high complexity task the number of unknown tracks was high while it was low in the
simple task.

Finally, the level of uncertainty was manipulated by changing the location that the
targets appeared on the screen. This was done to manipulate the dimension of dynamic
complexity. In the high complexity environment the entrance of the tracks on the screen
was completely random whereas for the low complexity task the tracks always entered
from the same location.

To ensure that the order in which the teams received the tasks did not act as a

confound the teams were counterbalanced by alternating task order. For example, odd

67

numbered teams were administered the high complexity task first while even numbered
teams received it second.

In this study task environment was manipulated by having the teams play
different games. The high task complexity environment was coded as a 1 and the low
task complexity environment was coded as a 0.

Communication Quantity
Communication quantity is conceptualized as the amount of cormnunication

within the team and therefore could be measured by summing-the temporal length of all
comments made by all members of the team during a 30 minute game. A common
instrument used to perform this measurement would be a stopwatch which is started
when any member of the team speaks and ends when they finish. This process would be
repeated throughout the entire 30 minute game each time a team member spoke. The
final total amount of time that all members of the team spoke during the game would be
considered as a measurement of team communication quantity. However, due to the
constant string of pauses that people use while speaking it was deemed impractical to use
human coders to make this measurement. If subjects frequently started and stopped
speaking this strategy would overwhelm coders and made it nearly impossible to obtain a
reliable measurement. Instead, a computer seemed well suited for this task given the very
fast reactions that are necessary to obtain an accurate measurement. To provide input to
the computer for this analysis each team member’s voice was digitally recorded at 24
kHz and 16 bits. A common channel was also recorded that combines everyone’s voice.
The next problem of course was how to get a computer to recognize human speech and

discriminate it from background noise or other non-speech related artifacts. Given that

68

all of the audio files used in this experiment were already digitally based, a technique
known as a variable bit rate (VBR) encoding was selected to address this problem.

Often digital files are stored by sampling a time based signal at regular intervals
and assigning the same number of bits to each sample, regardless of the amount of signal
contained at that moment. As a result, the same numbers of bits are used to encode
silence as are used to encode voice patterns. This is despite the fact that much fewer bits
(if any) are required to represent silence. As a result, those bits which are assigned to
encode periods of silence are “wasted”. An alternative to this approach is variable bit
rate encoding which senses the strength of the signal and applies fewer bits when silence
is present and more bits when a signal is present. The stronger the signal, the more bits
that are assigned and the larger the final file size will be. The number of bits that are
assigned is based on the quantization error used in the encoding algorithm. This process
is analogous to factor analysis continuing to search for factors if the Eigenvalue is above
one. If the quantization error (eigenvalue) is above a certain present quality level more
bits (factors) are applied until the quantization error falls below the predetermined quality
level. As a result, an audio file in which a team spoke more will have a higher file size
after VBR encoding than a team which spoke less. Therefore, it is the final file size, in
bytes, after VBR encoding that will be used as a measure of communication quantity.

Given that this is a computerized process, it is not the reliability of the technique
that needs to be examined but rather its concurrent criterion validity. In other words, the
ability of the file size after VBR encoding to accurately represent the length of time all
members of the team speak needs to be established. The most common procedure for

doing this is to inspect the correlation between the predictor (file size) and the criterion

69

(length of all speech) (Binning & Barrett, 1989; Dooley, 1995; Nunnally, 1978).
However, since all the games where 30 minutes, the predictor must also be shown to be
invariant to periods of silence. Therefore, two questions need to be asked. First, does the
file size have a high correlation to the length of time people speak and second, is the
process able to accurately discriminate between people speaking and silence? If the
results to the these questions are deemed satisfactory, than two more questions need to be
asked regarding how invariant the technique is to less than perfect input data. The first of
these questions is how invariant is this technique to heavy breathing, which was recorded
on many of the audio files and second, how invariant is the process to changes in the
amplitude, or loudness, in the input signal?

The first question was answered by selecting six people at random to read the
same 650 word statement. The correlation between the length of time it took them to
read it and the final file size was r = 1.0. To answer the second question four test files
were created that were each four minutes long. In the first file a 1 minute statement was
read, in the second the same statement was read twice, in the third it was read three times,
and in the fourth it was read four times. The correlation between the final file size and
the amount of speech in each file was r = 0.98. Having deemed these to be acceptable
answers to the first two questions, the next two questions were asked. With regards to
how invariant variable bit rate encoding is to breathing, two tests were preformed. First,
three files were created that were each again four minutes long. One file contained two
minutes of heavy breathing, one contained just background noise and the third contained
nothing because the microphone was disconnected. The largest difference in the final

size of these files after encoding was less than one percent. The second test to examine

70

the effects of breathing was performed using pilot test data. For this test two 30 minute
audio files from two different teams were compared. One contained heavy breathing and
the other did not. A direct comparison of the output could not be made between these
files since the amount of communication was different in each so to overcome this
problem the frequencies in both files that carried the heavy breathing were eliminated.
After performing a spectral analysis, it was discovered that most all of the heavy
breathing was contained in fiequencies below 500Hz so any signal below this was
minimized using a digital frequency equalizer. Since the frequency of human voice falls
between 500-4000Hz this action did not have a major impact on the actual voice pattern
data. The modified files were then encoded and compared to the same files before
modification. If heavy breathing does indeed substantially increase the encoded files
size, it was expected that the percentage difference between the size of the encoded files
before and after the frequency modification would be much larger for the pair that
contained the heavy breathing than for the pair that did not. However, this was not
observed. In fact the difference was again less than one percent. These two tests provide
strong evidence that the final size of a file after variable bit rate encoding is fairly
invariant to heavy breathing. The last test examined how invariant VBR is to changes in
ammitude. Some people speak louder than others so it is important that this technique is
not heavily influenced by such changes. To test this, pilot test data of a subject reading
the same 650 word statement mentioned above was used. In this case the subject read the
statement very loudly. A copy of this file was then created in which the total audio level
was decreased by 10 percent. Both files were then encoded. The final difference in file

size was less than one percent. This test was later repeated with 28 30-minute audio

71

recordings. The difference in the games ranged between 0.3%-l .7% with an average of
1.5%. This test was repeated but with a 20 percent decrease instead of a 10 percent
decrease. As expected, the difference in the games ranged between 0.6%-3.4% with an
average of three percent. This suggests that a team which spoke twice as loud as another
would only have a final encoded file size that is 7.5 percent larger. This is strong
evidence that VBR encoding is invariant against amplitude changes.

The program used to perform all VBR encoding was LAME which is not only the
industry standard to perform variable bit rate encoding but is also the most popular
engine used to convert audio files into the Motion Pictures Expert Groups, Standard 1,
Layer 3, commonly referred to as MP3. This application is used in most every
commercial audio program that offers such a conversion option. LAME not only allows
the maximum number of bits used during the VBR encoding process to vary but also
allows the minimum number of bits and the quality of the encoding to be selected. It is a
command line interface program with each setting being represented by a different
software switch. It was determined that for this experiment, the switch settings which
provided the highest variance, most linear output, and were the most invariant to
unwanted audio artifacts such as breathing and changes in signal amplitude were a
minimum bit rate of eight, a maximum variable bit rate of 112, and a quality level of
seven. The final command line interface command for encoding was “-b 8 —V 7 —B 112”

Communication Quality
Communication quality is a team level construct which can be thought of as

quality of the interaction between persons in a team based setting. This construct was
measured using a 12 item communication competence instrument developed by Monge,

Backrnan, Dillard, & Eisenberg (1994) is used. This was the first instrument designed to

72

examine competence from an organizational rather than an interpersonal perspective.
Some of its strengths include an other-orientated evaluation of competence and a focus
on both encoding and decoding skills. Examples of these items include, “My teammates
are difficult to understand when they communicate” and “My teammates expresses their
ideas clearly.” Coefficient alpha was used to test the reliability of each self-reported
continuous scale used as a variable in the study. For communication quality alpha was
0.93, ICC(l) was .18, and ICC(2) was .39

Two secondary measures of communication quality were also collected but not
used to test the hypotheses. The purpose of these measures was to act as back-ups to the
proposed measure. The second measure is task clarity which is the degree to which team
members are satisfied with the task specific information that has been given to them. It is
a four—item measure developed by Kirkpatrick and Locke (1996) to measure the effects of
leadership in a group setting. Examples of these items include, “I knew exactly what to
do on this task” and “I was not very sure how to complete the task (R).” The coefficient
alpha for this scale was 0.72. The last measure examines the timeliness, accuracy, and
usefulness of the communication. It is a four item measure that was developed by Frone
and Major (1988). Examples of these items include, “To what extent is information you
receive usually timely (you get information when you need it—not too early or too late)”
and “To what extent is information you receive usually accurate (you can rely on the
information — it is generally correct)” The coefficient alpha for this scale was 0.89.

Leader Centrality
Centrality relates to the number of connections an individual within a social

network has (Klein, Lim, Saltz, & Mayer, 2004). As such, it reflects the extent to which

interactions are concentrated in certain individuals rather than distributed equally among

73

all members (Sparrowe, Liden, Wayne, & Kraimer, 2001). For this study, network
centrality was measured by using an instrument developed by Sparrowe et al., (2001)
which is based on the work of Burt (1992) and Ibarra (1993). This measure was
originally intended to measure the network centrality of each member in a team but since
this study targets leaders it has been modified for this purpose by simply substituting the
work “leader” in place of the team member names. Additionally two extra questions
were also created based directly on the definition. The coefficient alpha for this scale
was 0.88, ICC(l) was 0.19, and ICC(2) was 0.42

Objective Performance
As mentioned before, this construct is comprised of both speed and accuracy

dimension. Therefore, both were measured and combined to form a composite measure
of objective performance. Speed was measured by recording the final team defensive
score in DDD. This is a very visible score to all members of the team throughout the
game and in the past has been considered to have construct validity because how quickly
individuals and teams are able to destroy incoming targets is directly related to their final
defensive score.

Accuracy of performance was measured by recording the final team offensive
score. This is also a very visible score to all members of the team throughout the game
and in the past has been considered to have construct validity because how precisely the
team attacks only enemy targets is directly related to their final offensive score. The final
composite performance scores were created by standardizing the data within measure

(game not complexity) and taking the mean of team offense and defense score.

74

Satisfaction with Team
This is the level of satisfaction each team member has of the team. It was

measured using the four item quality of team interaction and three item satisfaction with
team relationships measures developed by Wageman, Hackman, and Lehman (2005).
The items from the first instrument include questions like, “There is a lot of
unpleasantness among members of this team (R)” and “The Working together energizes
and uplifts members of our team.” The items from the second instrument include
questions like, “My relations with other team members are strained (R)” and “I very
much enjoy talking and working with my teammates.” The coefficient alpha for this scale
was 0.79, ICC(l) was 0.24, and ICC(2) was 0.48

Satisfaction with Leader
This is the level of satisfaction each team member has with the leader. It was

measured by adopting a 14 item supervisor satisfaction scale developed by Scarpello and
Vandenberg (1987). The items include questions like, “The way my leader listens when I
have something important to say” and “The way my leader sets clear work goals.” The
coefficient alpha for this scale was 0.97, ICC(l) was 0.10, and ICC(2) was 0.25

Procedure
All subjects for this experiment signed up to participate on a website by selecting

the session they wanted to attend. Two teams of four members could be run during each
session. When this happened, both teams had the same structural configuration. Once all
the subjects arrived at the laboratory they were asked to wait in the waiting room until all
the subjects arrived. Random assignment to teams was then made and the team members
were directed into one of two rooms for training. Random assignment to condition was
satisfied because the subjects were not aware of which team configuration would be

selected for their particular session before they sign up.

75

Once the subjects were in their seats, they were asked to electronically complete a
consent form and a pre-training survey. Following this, the entire team was given a 20
minute electronic slide show presentation, which included a pre-recorded audio track, on
how to operate the game. Training was only performed by qualified research staff
members. Once this was completed the leaders were separated for their specific
leadership training and the remaining members where given detailed hands on training
using the simulation. It was thought that since the leaders were not given any vehicles to
control, missing the hands-on training was not significant. Further, it was hoped that by
removing the leader from the group, their role would be made more salient to the group.

Following the training, all subjects were assigned to their proper stations and
prepared to play the game. After the first game the subjects were electronically
administered the applicable instruments. To give the leader a chance to appear more
transformational or transactional away for the game context, they were each asked to
summarize the performance of the group at this point or make any other comments while
exhibiting behaviors consisted with the leadership style they had been trained to use.
After the second game subjects were again electronically administered the applicable
instruments. They were then debriefed and thanked for their time.

Data Analfiis Strategy
There are several techniques that were used to analyze these data. In each case

the technique selected was based on the type of data being analyzed, the nature of the
hypothesis, and an attempt to keep the analysis as parsimonious as possible. First, the
means, standard deviations, and intercorrelations between all the variables were
calculated and reported in Table 3 and 4. These variables were created by aggregating

individual measures to the team level. Next the model presented in Figure l was tested

76

using a series of t-tests, and multiple regressions, hierarchical multiple regressions, and
moderated regressions

The first set of analyses examined the direct effects between the independent
variables and the mediators. Next, the proposed direct effects between the mediators and
the final outcome variables were considered. Then, the direct effects between the
independent variables and dependent variables were also reported. Moderation between
all the independent variables was also calculated and reported in each of these steps.

A mediation analysis was also performed using the methodology presented by
Baron and Kenny (1986). This is a four step procedure that first includes examining
whether the relationship between the independent variables and the mediators is
significant. Next, the relationship between the mediators and the dependent variables
also must be shown to be significant. Third, the direct relationship between the
independent variables and the dependent variables must be shown to be significant.
Finally, this relationship must be shown to be non-significant when a regression is
performed that includes the independent variables and the mediator, where the mediators

are entered in a prior hierarchical step.

77

CHATPER 4 - RESULTS

Wipulmon Check_s
As mentioned, a major concern when performing experimental leadership studies

is to ensure that the intended behaviors were exhibited and perceived by the followers.
To ensure that this was accomplished, two manipulation checks were performed.

The first consisted of a 15 item quiz administered to the leader after the training
(see Appendix B). Nine of the items were items from the transformational scale on the
multifactor leadership questionnaire (MLQ) and six were items from the transactional
scale on the MLQ. The MLQ is the most popular instrument for measuring
transformational and transactional leadership behaviors (Antonakis, Avolio, &
Sivasubramaniam, 2003; Lowe, Kroeck, & Sivasubramaniam, 1996). None of these
items were previously presented in the training. The leaders were asked to circle those
items which were consistent with the style of leadership they had been asked to
demonstrate. Both types of leaders were administered the same test. The average on this
test was 73.2% with a standard deviation of 2.67, a low of 4, and a high of 15. In the
transformational condition, the mean number of transformational items identified as
transformational behaviors was 0.90 while the mean number of transactional items
identified as transformational behaviors was 0.30. A paired t-test showed that this
difference was significant t(41) = 17.191 (p<.05). In the transactional condition, the
mean number of transactional items identified as transactional behaviors was 0.72 while
the mean number of transformational items identified as transactional behaviors was
0.42. A paired t-test showed that this difference was significant t(37) = 5.008 (p<.05).

The second manipulation check was performed by having everyone in the team

rate the performance of the leader using the MLQ immediately after the experiment. A t-

78

test was then performed to compare the mean scores of leadership behaviors across the
conditions. The purpose of this test was to determine if for each behavior, the scores
where higher in the appropriate condition. This approach is consistent with that taken by
Sosik, Avolio, and Kahai (1997) and showed that for each behavior there was a
significantly higher score for the intended manipulation. Team members rated
transformational behaviors higher in the transformational condition t(84) = 2.710, p < .05
and transactional behaviors higher in the transactional condition t(84) = -1.807, p < .05.

Scales, missing and deleted (12%
Communication quality, Leader centrality, Team Satisfaction and Leader

Satisfaction scales were all standardized within game order (not task complexity) because
of significant differences in the means of these variables between games.

Communication quantity did not have such a difference so it was not standardized. These
scales were created using follower responses only.

There were only two variables that had missing data; performance and
communication quantity. To determine if the missing data points were missing
completely at random (MCAR), they were each analyzed with respect to the independent
variables. For the performance data there were only three missing data points. With
respect to structure, these three data points were each from a different condition. With
respect to leadership, two were from the transformational condition and one was fi'om the
transformational condition and with respect to complexity two were from the low
complexity condition and one was from the high complexity condition. For
communication quantity, there were 24 out of 169 (14.5%) missing data points. These
points were missing because the team audio recorders did not activate properly during

these games. With respect to structure, seven of these 24 where in the collocated

79

structure, eight were in the virtual structure, and nine were in the reachback structure.
With respect to leadership, 11 were in the transformational condition and 13 were in the
transactional condition. Finally, with respect to task complexity, 13 were in the low task
complexity condition and 11 were in the high task complexity condition. Given that no
discemable pattern was present with respect to any of the independent variables the
missing performance and communication quantity values were treated as MCAR.

The only data removed from the analysis was the low complexity performance
score of one team’s second game. Their score was removed because several members of
this team seemingly decided to stop participating after the first game was over. This was
due to the fact that between games one member of the team realized that this was a
military command and control simulation and asked the trainer if the data collected might
help the United States military. The trainer confirmed that the simulation had come from
the military and that they might be interested in the results. This evidently upset the
individual because according to her, she was born and raised in Lebanon and this
experimental session took place in the first few weeks of an Israeli Military Campaign
into Southern Lebanon which some thought had the tacit approval of the United States.
This individual, along with one other team member who seemingly sympathized with this
person, where then intermittently observed not playing the simulation. These behaviors
were thought to have led to this team having the lowest objective performance score, -

2.645.

Test of Hypotheses
The following section presents the results for each hypothesis test. The first

section examines the direct effects, the second looks as the proposed moderation, the

third at mediation, and the fourth and other significant interactions which were found.

80

For each hypothesis, both the simple and complex task data was analyzed separately. All
regression coefficients reported are the standardized beta values and all significance
testes (p values) were based on a one-tailed alpha value of .05.

Direct Eflects
Hypothesis 1 predicted that communication quantity will be higher in a collocated

team compared to a reachback team and hypothesis 2 proposed that communication
quantity will be higher in a reachback team compared to a virtual team. Both of these
hypotheses were tested using hierarchical regression for both the simple and complex
task. First, two dummy variables were coded as a 1 0 for collocated teams, a 0 l for
virtual teams and 0 0 for reachback teams (control). These} were entered into a regression
equation as independent variables with communication quantity as the dependent
variable. If the first dummy variable was significant hypothesis 1 would be supported
and if the second dummy variable was significant hypothesis 2 would be supported. As
shown in the Tables 5 and 6, the dummy variable for the collocated groups were
significant for both levels of complexity, B = .418, t(7l) = 3.276, p < 0.05; B = .524,
t(7l) = 4.805, p < 0.05 and the dummy variable for the virtual groups were also
significant in both cases but in the wrong direction, B = -0.534, t(71) = -4.189, p < 0.05;
B = -0.683, t(71) = -6.265, p < 0.05. This model shows that team structure explained a
significant proportion of variance in communication quantity for both types of tasks. For
the simple tasks R2 = .310, F(3, 68) = 9.781, p < .05 and for the complex tasks R2 = .472,
F(3, 69) = 19.539, p < .05. As a result hypothesis 1 is supported but hypothesis 2 is not
supported. Figures 9 and 10 below show the mean level of communication quantity for

each of the three types of structure in both the simple and complex tasks.

81

 

 

 

 

 

 

 

 

 

 

g 8

a L i 4..

E 7

.E 6 a ,

g. 5 _ ... . W, . , ..

5 4 _ ,, . En Predicted
a 2;: llActual
c 3 ~ ~::: ' ., '

g 2 - ::: _ H A ,

s TEES

'E 1 v a ,

=1 I:

E 0 ‘

8 Collocated Reachback Virtual

 

 

 

Figure 9. Predicted and results for hypotheses l and 2 (simple)

 

 

  

ED Predicted
II Actual

    

III-IIIIII

1

  

    

 

 

   

   
 

Collocated Reachback Virtual

 

 

Communication Quantity (in Mbytes).
O -| M to J?- UI O) \i on

 

 

Figure 10. Predicted and results for hypothesis 1 and 2 (complex)

Next, hypothesis 3 predicted that communication quality will be higher in a
collocated team compared to a reachback team and hypothesis 4 stated that
communication quality will be higher in a reachback team compared to a virtual team.

As above, both of these hypotheses were tested using hierarchical regression for both the
simple and complex task. As shown in the Table 7 and 8, the dummy variable for a
collocated team was not significant in either case, B = -0.119 t(84) = -0.929, p =.178; B =
-0.079, t(84) = -0.617, p =.270 and the dummy variable for a virtual team was also not

significant in either case, B = -0.138, t(84) = -1.080,p = .142; B = -O.156, t(84) = -1.212,

82

p = .115. As a result hypotheses 3 and 4 are not supported. Figures 11 and 12 below
show the mean level of communication quality for each of the three types of structure in
both the simple and complex games. The large difference between actual and predicted
data is due to the fact that the original prediction was based on raw data whereas the

actual data is standardized within game (first versus second game played by the team).

 

 

 

 

 

 

.E'

'3

3

o

C

«71°. __ 3 Predicted
.2 I Actual
: i

3

8

O

 

Collocated Reachback Virtual

 

 

 

Figure 11. Predicted and results for hypotheses 3 and 4 (simple)

 

 

 

 

 

 

5‘

Ti

:

G

c .

é - Cl Predicted
2 I Actual
:

a

E

E

o

O

 

Collocated Reachback Virtual

 

 

 

Figure 12. Predicted and results for hypotheses 3 and 4 (complex)
Hypothesis 5 suggested that teams whose leaders were taught a transformational
leadership style will make more comments than teams whose leader were taught a

transactional style for each structural configuration. This was tested by performing a t-

83

test on the mean number of comments made in the transformational and transactional
conditions for each structure. As shown in Table 9, hypothesis 5 was fully supported in
both simple and complex games for collocated (t(24) = 1.864, p < .05; t(24) = 2.256, p <
.05) and reachback (t(l9) = 1.971,p < .05; t(22) = 1.801,p < .05) structures and
marginally supported in a virtual structure (t(23) = 1.635, p = .058; t(20) = 1.636, p
=.059). Therefore, hypothesis 5 is supported Figure 13 and 14 shows the mean value of
communication quantity in transformational and transactional conditions across structures

for both simple and complex tasks.

 

‘D
l
l
l
l
l
r
l
r
l
l
l

on

 

‘1
J

0')
I

01
.1

A
I

 

 

 

Communication Quantity (in Mbytes).
(a)

 

Co Ilocated Reachback Virtual

 

 

Figure 13. Predicted and results for Hypothesis 5 (simple)

 

(D
I

on
i

‘1

m
1

EDTA
"TE

0!
1

&
r

 

rummwm

  

Communication Quantity (in Mbytes).
U

Collocated Reachback Virtual

 

 

 

Figure 14. Predicted and results for Hypothesis 5 (complex)

84

Hypothesis 6 states that communication quality will be higher in a collocated
transformational team than a transactional team. This hypothesis was tested by
performing a moderated regression. To do this a dummy variable representing leadership
style was created. This variable was coded as “1” for the transformational condition and
a “0” for the transactional condition. Two interaction terms were then created between
this variable and the two structure dummy variables from hypothesis 1 and 2. The
leadership dummy variable and the resulting interaction variables were then each loaded
into the regression equation in a separate hierarchical regression step, allowing for an
examination of the change in R2 between the each of the direct and the interaction effects.
The hypothesis was tested by examining the significance of the interaction terms. As
shown in Tables 7 and 8, there was no significant interaction between collocated and
reachback or virtual and reachback teams for simple tasks, B = -0.221, t(84) = -1.052, p
=.148, B = -0.040, t(84) = -0.204, p =.42 or complex tasks, B = 0.033, t(83) = 0.159, p
=.44, B = -O.236, t(83) = -1.169, p =.123. Therefore hypothesis 6 is not supported.

Hypothesis 7 predicted that a positive relationship exists between task complexity
and overall team communication quantity. This hypothesis was tested by using an
independent t-test. For this test, the mean number of comments made during the high
complexity game was shown to be significantly higher than it was during the low
complexity game. For this test, only data from the first game were used, to ensure that
the measures used were independent. Results show that hypothesis 7 was supported,

t(72) = 2.967, p < .05.

85

 

9:9
(DON

995»
Nb

Communication Quantity

 

9'5»an
(hNhOJGO)

 

 

Low task complexity High task complexity

 

Figure 15. Results for Hypothesis 7

Hypothesis 8 states that team member perceptions of leader centrality will be
higher in a collocated team than a reachback team and hypothesis 9 states that team
member perceptions of leader centrality will be lower in a virtual team than a reachback
team. Both of these hypotheses were tested by using hierarchical regression for both the
simple and complex task. As before two dummy variables were coded to represent
collocated teams, reachback teams, and virtual teams. These were entered into a
regression equation as independent variables with leader centrality as the dependent
variable. If the first dummy variable was significant hypothesis 8 would be supported
and if the second dummy variable was significant hypothesis 9 would be supported. As
shown in the Tables 10 and 11, the dummy variable for the collocated groups was not
significant in either case, B = —0.160, t(84) = -1.252,p = .107; B = 0.148, t(83) = 1.159, p
=.125. The dummy variable for the virtual groups were also not significant, B = -0.l61,
t(84) = -1.267, p = .105; B = -0.053, t(83) = -0.420, p =.338. As a result both W
Ed 9 are not supported. Figures 16 and 17 shows the mean level of leader centrality
for each of the three types of structure in both the simple and complex games. Again, the

large difference between actual and predicted data is due to the fact that the original

86

prediction was based on raw data whereas the actual data is standardized within game

(first versus second game played by the team).

 

 

 

 

 

Q

3

a

i - 1 EB Predicted
g ' lActual
I; .

3

 

 

Collocated Reachback Virtual

 

 

Figure 16. Predicted and results for Hypothesis 8 and 9 (simple)

 

   
  
   

 

in Predicted
: I Actual

r
J

l

“.4

 

 

 

  

Leadership Centrality

-1

Collocated Reachback Virtual

 

 

 

Figure 17. Predicted and results for Hypothesis 8 and 9 (complex)
Hypothesis 10 states that leader centrality will be higher in a collocated
transformational team than a transactional team. This hypothesis was tested using the
same methodology explained above for hypothesis 6 except that the dependent variable
was leader centrality. As shown in Tables 10 and 11, there is also no significant
interaction between collocated and reachback or virtual and reachback teams for simple

tasks, B = -0.062, t(84) = -0.299, p =.383, B = 0.096, t(84) = 0.490, p =.3l3 or complex

87

tasks, B = -0.002, t(83) = -0.010, p =.496, B = -0.226, t(83) = -1.140 p =.129. Therefore,
hypothesis 10 is not sapported.

Regarding the relationships with the outcome variables, hypothesis ll proposes a
positive relationship exists between communication quality and effectiveness variables.
This hypothesis was tested by using multiple regression after segregating the data based
on complexity. To test this, and next two hypotheses, communication quality,
communication quantity (see hypothesile) and leadership centrality (see hypothesis 13)
were used as independent variables against objective performance, team satisfaction
leader satisfaction in separate regression equations. As shown in Tables 12 - 17,
significant relationships were found in the simple game for objective performance B =
0.385, t(69) = 2.175,p < .05, team satisfaction B = 0.616, t(71)= 4.715,p < .05, and
leader satisfaction B = 0.234, t(71) = 1.980, p < .05. For the complex game significant
relationships were found for team satisfaction B = 0.501, t(71) = 4.378, p < .05 and leader

satisfaction B = 0.429, t(71) = 3.813, p < .05. Therefore, hypothesis 11 is mostly
supported.

Hypothesis 12 proposes a positive relationship exists between communication
quantity and effectiveness constructs. This hypothesis was tested by using multiple
regression alter segregating the data based on complexity. As shown in Tables 12 - 17,
no significant relationships were found. Therefore, hypothesis 12 is not supported

Hypothesis 13 proposes a positive relationship exists between perceived leader
centrality and performance elements. Again, this hypothesis was tested by using multiple
regression after segregating the data based on complexity. As shown in Tables 12 - 17,

significant relationships were found in the simple game for leader satisfaction B = .594,

88

t(71) = 4.990, p < .05 and in the complex game for objective performance B = 0.433,
t(71) = 3.021, p < .05, team satisfaction B = 0.248, t(71) = 2.145,p < .05, and leader

satisfaction B = 0.345, t(71) = 3.033, p < .05. Therefore, hypothesis 13 is mostly

supported

Moderation effects
Regarding the hypotheses that test for interactions, hypothesis 14 proposes that

the relationship between structure and communication quality is contingent on leadership
style, such that a transformational style leads to higher scores in collocated contexts, but a
transactional style leads to higher scores in reachback and virtual contexts. This
hypothesis was tested using moderated regression. First a structure dummy variable

‘61,,

coded as a for collocated teams and a “0” for all others was entered into a regression
equation as an independent variable with communication quality as a dependent variable.
Next a dummy variable coded as “1” for the transformational condition and a “0” for the
transactional condition were loaded into the same equation as a second independent
variable. Finally, an interaction term which was the product of the first two dummy
variables was loaded into the equation in a separate step. The moderation was tested by
examining the significance of this interaction term. However, this term was not
significant for simple or complex tasks, B = -.201, t(84) = -1 .123, p =.132, B = 0.158,
t(83) = 0.894, p =.187. Further, as shown in Tables 7 and 8, there is also no support for
interaction between collocated and reachback or virtual and reachback teams for simple
tasks, B = -.221, t(84) = -1.052, p =.148, B = -.040, t(84) = -0.204, p =.420 or complex
tasks, B = 0.033, t(72) = 0.159, p =.436, B = -0.236, t(72) = -1.169, p =.123. Therefore,
hypothesis 14 is not supported. Figures 18, 19 and 20 Show predicted and actual mean

level of communication quality for each of the three types of structure in both the simple

89

and complex games. The large difference between actual and predicted data is due to the
fact that the original prediction was based on raw data whereas the actual data is

standardized within game (first versus second game played by the team).

 

syn-"~- “a, -_ *wwq—nw
4.5i J- , 7 7 m,

9°
u or as
L 4

 

-——+—- Transformational
— - -I - - - Transactional

 

 

 

r‘ .
or N
1 ? 1

Communication Quality
'0
00

d
1

 

 

 

.0
or

 

 

O

 

Collocated Reac hback Virtual

 

 

 

Figure 18. Predicted Hypothesis l4

 

 

 

 

 

 

 

4 WWW.“ _.
e
g 3 ”“7 ‘*“*~*"*W~—u~e~ 4
'5' 2 -——-—_-.._-. -_. ___ __ -- ”WA —+—Transformarional
5 ---l---Transactional
E
E 1‘
0 0‘
-1

 

 

 

Collocated Reachback Virtual

 

 

 

Figure 19. Results for Hypothesis 14 (simple)

90

 

 

 

——o—— Transformational
- - -I - - - Transactional

 

 

 

 

g
S
a
5
If 2 7 ’ 7 7
73
E
8
o

 

 

 

 

 

 

Collocated Reachback Virtual

 

 

Figure 20. Results for Hypothesis 14 (complex)

Hypothesis 15 suggests that the relationship between leadership style and
leadership centrality is contingent on task complexity, such that a high task complexity
leads to higher scores for a transactional leadership style, but low task complexity leads
to higher scores for a transformational leadership style. An examination of Tables 10 and
11 show that the unstandardized B weights of leadership centrality are almost identical
for both types of task. This suggests that there was no moderation present. This
hypothesis was also tested using moderated regression. For this test, only data from the
first game were used to ensure that the measures used were independent. First a
leadership dummy variable coded a as “l” for the transformational conditions and a “0”
for transactional conditions was entered into a regression equation as an independent
variable with leader centrality as a dependent variable. Next a dummy variable coded as
“1” for the high complexity game and a “0” for the low task complexity game were
loaded into the same equation as a second independent variable. Finally, an interaction
term which was the product of the first two dummy variables was loaded into the
equation. The moderation was tested by examining the significance of this interaction

term. However, the term was not significant, B = .026, t(82) = -.012, p = .44, so

91

hypothesis 15 is not supported. This hypothesis was also unsupported when examining

just game 1, game 2. It was also unsupported after testing all team structures in isolation.

 

r
l
l
r

 

 

 

 

 

 

 

 

 

0.8 «- — —e —
0.6 . -—— A - a i
g g .-
g 0.4 « —~;. ----- ,
5 0.2« '42:... - __,
:- 0 . __ _ 1 —-—+——-LowTask Complexity
4: ---I--- High Task Compleny
g -o.2 — —_
3 .04 a-
3 ~08 - --—- - l
as — _—__ - _-_- W- J
-1 . 4
TA TF
Leadership Style

 

 

 

Figure 21. Results for Hypothesis 15

Finally, hypothesis 16 suggests that the relationship between structure and leader
centrality is contingent on leadership style such that a transformational style enhances
centrality in collocated contexts, but that a transactional style enhances centrality in
reachback and virtual contexts. This was tested using the moderated regression. First a
structure dummy variable coded as a “1” for collocated teams and a “O” for all others was
entered into a regression equation as an independent variable with leader centrality as a
dependent variable. Next a dummy variable coded as “1” for the transformational
condition and a “0” for the transactional condition were loaded into the same equation as
a second independent variable. Finally, an interaction term which was the product of the
first two dummy variables was loaded into the equation. The moderation was tested by
examining the significance of this interaction term. However, the term was not
significant for simple or complex tasks, B = -.1 l7, t(84) = -O.658, p =.257; B = 0.77,
t(83) = 0.675, p =.250. Further, as shown in Tables 10 and 11, there is also no support

for interaction between collocated and reachback or virtual and reachback teams for

92

simple tasks, B = -.062, t(84) = -0.299, p =.383; B = 0.096, t(84) = -0.490, p =.313 or
complex tasks, B = -0.002, t(83) = -0.010, p =.496; B = -0.226, t(83) = -1.140, p =.129.
Therefore, hypothesis 16 is not supported. Figures 22, 23 and 24 show predicted and
actual mean level of communication quality for each of the three types of structure in
both the simple and complex games. The large difference between actual and predicted
data is due to the fact that the original prediction was based on raw data whereas the

actual data is standardized within game (first versus second game played by the team).

 

 

 

 

—e— Transformational
— - I --- Transactional

 

 

 

 

 

 

 

 

Face-to-tace Virtual Reachback

 

 

 

Figure 22. Predicted Hypothesis l6

 

 

 

 

 

V ' —e—Transformational
—--e---Transactional

 

 

 

Leadership Centrality
N w

l

r

l

l

:

l

l

 

 

 

 

 

 

 

Face-to-face Virtual Reachback

 

Figure 23. Results for Hypothesis 16 (simple)

93

 

 

. —e—— Transformational
- - -e - . - Transactional

 

 

 

Leadership Centrality
o _e
l r
i l '
r
l

 

 

 

 

 

 

Face-to-face Virtual Reachback

 

Figure 24. Results for Hypothesis l6 (complex)

All the above hypothesized moderations were between the independent variables
and the mediators. However, there were some interesting interactions between the
mediators and the distal effectiveness outcomes. For example, Table 12 shows that the
interaction term between communication quality and leader centrality when compared to
performance is significant in a simple task. This relationship is plotted in Figure 25. It
suggests that when communication quality is low, performance is actually higher when
leader centrality is low. However when communication quality is higher, a greater level
of leader centrality leads to higher performance. What is perhaps most interesting about
this interaction is the degree to which the high leadership centrality condition changes so
drastically from the low communication quality condition to the high one. One potential
reason for this is that leaders with high levels of centrality might be acting as an
information bottleneck when communication quality is low. In this situation, leaders who
are perceived to have a high level of influence might be restricting the amount of
information in the group. Such a situation might be the result of the leader acting as an
information gatekeeper and simply not being able to single-handedly manage all of the

group communication. However, when leader centrality is low, the communication

94

between followers is more distributed so the information bottleneck no longer exists. In
contrast, when communication quality is high, leaders with high centrality are able to
better mange information flows among group members. Such improvements would
increase the probably that followers would be exposed to the important information they

need in order to do their jobs better.

 

 

+LowLC
---e---l-ligh LC

 

 

 

Performance

 

 

Low Comm Qual High Comm Qual

 

 

 

Figure 25. Communication Quality x Leader Centrality and its effect on
Performance (simple task)

Tables 13 and 15 show that communication quality and communication quantity
interact when compared to performance and team satisfaction in a complex task. Figures
26 and’27 show that when communication quality is low, low communication quantity
leads to higher performance and team satisfaction but when communication quality is
high, high communication quantity is more effective. This might be explained by the fact
that when communication quality is high, teams that communicate more do better. What
is perhaps more interesting is that the opposite also appears to be true. When
communication quality is low, teams that communicate less do better. One reason why
this might only be true for complex tasks, and not simple tasks, is that there is a greater

need for coordination in more complex tasks. When coordination requirements are high,

95

teams will need to work together more in order to perform well. As a result, they will be
more sensitive to team communication quality. Therefore, they will be more likely to be
damaged by poor communication quality. Such a theory is supported by Kacmar, Witt,
Zivnuska, and Gully (2003) who found that communication frequency moderates the
relationship between LMX (communication quality) and performance ratings. They
show that when LMX is high, employee performance ratings were greatest when
communication frequency between supervisor and subordinate was higher but when
LMX was low, performance ratings where highest when communication frequency was

low.

 

 

 

 

—e— Low Comm Quant
-~-I--- High Comm Quant

 

 

 

Performance

 

 

 

Low Comm Qual High Comm Qual

 

 

 

Figure 26. Communication Quality x Communication Quantity and its effect on
Performance (complex task)

96

 

 

__,.. — - 4 —e—Low Comm Quant
. ,*____, ---e--- High Comm Quant

 

 

 

Team Satisfaction

 

 

 

 

 

Low Comm Qual High Comm Qual

 

 

Figure 27. Communication Quality x Communication Quantity and its effect on
Team Satisfaction (complex task)

Another interesting set of interactions from Table 13 and 15 is between
communication quantity and leader centrality for complex tasks. Here, when leader
centrality is low, higher performance and team satisfaction is realized from higher
communication quantity. However, when leader centrality is high lower communication
quantity is associated with higher effectiveness. These relationships are plotted in Figure
28 and 29 and suggest that when teams do not communicate very much it is important to
have a central leader. In this situation, leaders with high levels of centrality might use
their influence to direct team members. On the hand, when the level of communication is
high, the importance of a central leader is diminished. In this scenario, the team is able to
manage their own communication and the need for a central figure to coordinate between
members is reduced. Again, the reason this might be true only in a complex task is
because of the need for increased coordination and interdependence among team
members. When the task is simple, there is not as much of a need for a highly central
figure to coordinate actions. If this were true we would also expect that in a simple game
there would be no direct relationship between leader centrality or communication

quantity and performance, and according to Table 12, that is exactly what was observed.

97

 

 

5f: _ , _ - i +LOWLC
' ---I---HighLC

 

 

 

Performance
1
l

 

 

 

Low Comm Quant High Comm Quant

 

 

 

Figure 28. Communication Quantity x Leader Centrality and its effect on
Performance (complex task)

 

 

 

 

 

 

 

 

 

 

 

3 Tr —_—_ — "#1
2.5 i - — I. —~ A #9
C 2 _w ,, , ‘. ‘
8 .
g 1.5 4 \_
a 1 .,, 'e—v - we; -* - ,_ - ~ 1 —e—LowLC
I 05 _ __,___,,,______ "e._,___._- _ _ A -' ---I---Hi hLC
in -, 9
E _ _, ‘- ./{.__-_L-_l
“ .
o _ . .- __ __.... ."\ _. .. __ _ '
i- a,
'i' a-” _ l
Low Comm Quant High Comm Quant

 

 

 

Figure 29. Communication Quantity x Leader Centrality and its effect on Team
Satisfaction (complex task)

The data from Figure 30 also comes from Table 15 but this time the interaction is
not crossed. In this situation a higher level of leader centrality leads to greater team
satisfaction when communication quality is high. However, when communication quality

is low there is little difference between high or low leader centrality.

98

 

 

 

——e—-LowLC
---I---High LC

 

 

 

Team Satisfaction

 

 

 

 

Low Comm Qual High Comm Qual

 

 

 

 

Figure 30. Communication Quality x Leader Centrality and its effect on Team
Satisfaction (complex task)

Table 16 shows a small significant (p < .10) interaction between communication
quality and leader centrality as it relates to leader satisfaction in a simple task. AS shown
in Figure 31, when communication quality is low, high leader centrality leads to a much
higher leader satisfaction score, compared to low leader centrality, than when
communication quality is high. This is primarily because the amount of growth in leader
satisfaction scores for leaders with low centrality is much larger between low and high
communication quality conditions than it is for leaders with high centrality. What is
perhaps most interesting here is that, as shown in Figure 32, the same interaction is
present (p < .05) for complex tasks almost with the opposite direction. Instead of a larger
difference between leader satisfaction scores for leaders with a high and low level of
centrality when communication quality is low, there is no difference and instead of this
difference getting smaller when communication quality is greater it gets larger. A
potential explanation for this must then address two issues. First, why there is such a
large difference in leader satisfaction scores for different levels of leader centrality for a

simple task but not a complex task when communication quality is low. Second, why is

99

there such a large difference in leader satisfaction scores for different levels of leader
centrality for complex tasks but not simple tasks when communication quality it high.
One potential explanation for the first question might be that when the task is simple and
communication quality is low, followers expect leaders to display a high level of
centrality and influence. In these situations, it is the leader who, despite a lack of team
communication quality, is able to display a high level of centrality and influence which is
rewarded with a higher satisfaction score. However, in a complex task there is not as
much of an expectation that leaders will exhibit a high level of centrality when
communication quality is low. In this situation the data shows that leaders are neither
rewarded nor punished based on their level of centrality. Here, the standardized scores
for both types of leaders is nearly zero. However, when leader centrality is low and
communication quality is high, followers might feel that the leader did not display the
proper amount of leadership and influence which they were expected to and subsequently
rate their scores lower. In total this shows that the expectation of followers for leaders in

simple and complex tasks is different depending on the quality of the communication.

 

14 -_-_--__.____ . __.
0.5 « —
0
-0.5 « -
-1 Jl.
-1.5
-2 - -
-2.5 — —~~ -
-3 ,
Low Comm Qual High Comm Qual

 

 

 

——e—LowLC
---e---High LC

 

 

 

 

 

 

Leader Satisfaction

 

 

_JL._. .

 

 

 

Figure 31. Communication Quality x Leader Centrality and its effect on Leader
Satisfaction (simple task)

100

 

 

 

 

 

 

 

_-

r: 1.5~»~ - m a , -
O ..’
g 1 I'll
8 __ __ _ _._ ‘ ..':,L--..___- fi_ _
.3 . -’ —e—Low LC
a 05 « —— ,—.-—- —— -— - —— -—— .
a: -~l---High LC
3 0~ a - - , .._ I
8

'1 I Jr

 

 

Low Comm Qual High Comm Qual

 

 

 

Figure 32. Communication Quality x Leader Centrality and its effect on Leader
Satisfaction (complex task)

Mediation effects
As mentioned, a mediation analysis was also performed using the four step

procedure explained by Baron and Kenny (1986). The first step is to examine whether
the relationship between the independent variables and the mediators is significant. The
second step is to determine if the relationship between the mediators and the dependent
variables is also significant. The third step is to determine if the direct relationship
between the independent variables and the dependent variables is significant. Finally,
this previous relationship must be shown to be non-significant when a regression is
performed that includes the independent variables and the mediator, where the mediators
are entered in a prior hierarchical step.

An examination of the hypothesized paths between the independent variables and
the mediators shows that only the relationship between team structure and
communication quantity was significant. However, the only significant hypothesized
relationships between the mediators and the dependent variables were between

communication quality, leader centrality and the effectiveness variables. Given that no

101

continuous path exists between the independent variables, mediators, and dependent
variables, mediation can not occur based on the hypothesized relationships.

However, in the interest of being as thorough as possible, any significant
relationships between the initial independent and the final dependent variables were
examined to determine if their effects significantly decreased when the effects of the
proposed mediators were partialed out. Any interactions between the mediators were
also partialed out to ensure that any remaining variance was indeed attributable to the
independent variables.

Table 25 shows that the significant relationship reported in Table 18 between
leadership style and performance for a simple task was no longer significant after
controlling for the mediators. For the complex game Table 26 shows that the significant
relationship reported for the first structure dummy variable in Table 19 is also no longer
present after controlling for the mediators.

With regards to team satisfaction, Table 27 shows that the significant effect with
the structural variables reported in Table 20 persists for simple tasks. For the complex
task, no direct significant effects were reported in Table 21 so it is not surprising that
Table 28 also shows no significant effects between the independent and dependent
variables. With regards to leader satisfaction, Table 29 shows that the first dummy
variable for structure is no longer significant for a simple task, as reported in Table 22
and for complex tasks, the significant effect reported in Table 23 with leadership style
disappears, however, the effect with the first dummy variable persists

Additionally, other non-hypothesized significant relationships form continuous

paths between the independent variables, mediators, and dependent variables so

102

mediation might occur though these paths. For example, as seen in Table 8 the
relationship between leadership style and communication quality was mildly significant
for a complex game. Also, as shown in Tables 10 and 11, the relationship between
leadership style and leader centrality was also significant for both simple and complex
games. Finally, Table 24 suggests that complexity also had a significant relationship
with each of the other constructs. Therefore, communication quality and leader centrality
were examined as potential mediators which sit between the independent variables of
leadership style and task complexity and the dependent variables of performance, team
satisfaction, and leader satisfaction. Specifically, there are 6 potential paths listed below:
Leadership Style 9 Leader Centrality 9 Performance (complex)

Leadership style 9 Communication Quality 9 Team Satisfaction (complex)
Leadership style 9 Leader Centrality 9 Team Satisfaction (complex)
Leadership style 9 Communication Quality 9 Leader Satisfaction (complex)

Leadership style 9 Leader Centrality 9 Team Satisfaction (simple)
Leadership style 9 Leader Centrality 9 Team Satisfaction (complex)

99:59192"

To examine whether this mediation existed, hierarchical regression was again used to
partial out the effects of the mediators from the relationship between the independent and
dependent variables for both simple and complex games. As shown in Tables 31-33 the
relationships between the independent variables and the dependent variables were no
longer significant after partialing out the effects of the mediators for each of the paths
listed above. Therefore, it can be claimed that communication quality and leader

centrality fully mediate the paths above. Table 2 is a summary of all the hypotheses

 

 

 

 

 

 

testing.
Table 2. Summary of test results
Simple Complex
H1 Fully Supported Fully Supported
H2 Not Supported Not Supported

 

103

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

H3 Not Supported Not Supported
H4 Not Supported Not Supported
H5 Mostly Supported Mostly Supported
H6 Not Supported Not Supported
H7 Fully Supported
H8 Not Supported Not Sigiported
H9 Not Supported Not Supported
H10 Not Supported Not Supported
H11 Fully Supported: 3/3 Mostly: 2/3 (not obj pert)
H12 Not Supported Not Supported
H13 Partially Supported: 1/3 (only Fully Supported: 3/3
leader)
H14 Not Supported Not Supported
H15 Not Supported Not Supported
H16 Not Supported Not Supported
Mediation Not Supported Not Supported

 

 

 

Eflects of Structure and Leadership on Distal Outcomes

While none of the proposed moderation was significant, there were other

interaction terms that were significant. Perhaps the most interesting characteristic of this

entire study is that leadership style does indeed moderate the direct relationship between

structure and performance outcomes. The crux of this study was to determine how

modern team structures impact modern conceptualizations of leadership. If just these

dimensions are isolated along with performance outcomes, we see a strong moderation

effect based on leadership styles. For example, using the same procedure to test for

moderation as was used in hypothesis 14 but switching the dependent variable from

communication quality to objective performance, leadership style significantly moderated

the relationship. For example, in the low complexity condition B = .516, t(82) = 1.96, p

< .05, AR2 = .044, p < .05 for the interaction term. In the collocated group each of these

variables was significantly higher for a transformational condition, as the literature would

predict. However, there was no difference in non-collocated groups. A similar result is

104

 

seen for the second game as well B = .429, t(82) = 2.18, p < .05, AR2 = .052, p < .05.

Figure 33 shows this interaction.

 

0.4 __fi-,_-__z___,,
0.35 ~-e~—-——l.,——-—- —~ , —~ ’1
0.3 -._-__._-_~__ —‘~-.—--.— — w A W
0.25+--l- -- a

 

 

02- — __s._-,_--_. ‘—

0.15 ~~ — —-—~~— ————'1‘.——-7~--——«- - —«J —e—Transactional
0-1 7 T '““ ':’\.“""" --~l---Transfomtationa|
0.05 - 'y

0 as - __ _. ._ . __- .._ ‘.,_. _ _
-0.05 __.--_____- -— -— - - -- ~—
-0.1 — .__~-._ —— — - -
p.15 4 l

Collocated Non-Collocated

 

 

 

Performance

 

 

 

 

 

 

Figure 33. Structure x Leadership Style and its effect on Performance (second
game)

Based on this, it can be claimed that while a transformational leadership style is
indeed preferable in a collocated group, it does not lead to similar benefits in a non-
collocated team structure. This then represents a heretofore unknown boundary condition
to the benefits enjoyed by the transformational leadership style. This is a very interesting
conclusion given that so much literature has concluded that a transformational style is
seemingly always preferable.

Results using a modified leadership coding scheme

As an interesting exploratory analysis all the hypotheses related to leadership
style were retested using the MLQ as the measure of the leader behavior instead of the
dichotomous manipulation. For this analysis the data were not coded based on which
manipulation group they came from but rather on the transformational or transactional
scales collected during the manipulation check. Specifically, if the transformational scale

was higher than the transactional scale, the team was coded as being transformational and

105

vice versa. Given that such a modified coding scheme would only impact the hypotheses
that examine the effects of leadership style, only hypothesis 5, 6, 10, 14, 15, and 16 were
retested.

For hypothesis 5, the original coding scheme showed that the amount of
communication quantity was significantly higher in almost every structure for both the
simple and complex games. However, this was not entirely the case when using the new
coding scheme. The modified scheme showed that for the simple game the difference in
the amount of communication quantity was not significant for the collocated (t(24) =
1.120, p = .14), reachback(t(19) = 0.778, p = .22) or virtual structures (t(23) = 1.275, p =
.108). However, for the complex game it was significant for the collocated (t(24) =
1.749, p < .05), and virtual team (t(21) = 2.866, p = .22) but not for the reachback
structure (t(22) = 0.033, p = .50). Therefore, hypothesis 5 is part—ially supported using the
new coding scheme

For hypothesis 6, the original coding scheme showed that the amount of
communication quality was not significantly higher in a collocated transformational team
compared to a transactional team. Originally, no significant interaction was found
between leadership style and the dummy variables representing the difference between
collocated and reachback or virtual and reachback teams for either the simple or complex
tasks. Almost the same results were obtained when using the modified coding scheme.
However, the new coding scheme did reveal a weak interaction between leadership style
and the dummy variable representing the difference between virtual and reachback teams

for complex tasks, B = 0.535, t(84) = 1.305, p <.l. Therefore, hypothesis 6 is partially

supported using the new coding scheme

106

For hypothesis 10, the original coding scheme showed that the level of leader
centrality was not significantly higher in a collocated transformational team than in a
transactional team. The results obtained for the new coding scheme were the same as
they were for the old scheme for simple tasks and the dummy variable representing the
difference between virtual and reachback structures for complex tasks. However, there
was a significant effect between leadership style and the dummy variable representing
difference between collocated and reachback teams for the complex game, B = 0671,
t(83) = -1.702, p < .05. This shows that the level of leader centrality is significantly
higher in a collocated transformational team than in a transactional team. Therefore,
hypothesis 10 is pa_rt_ially supported using the new coding scheme

Regarding the hypotheses that test for interactions, hypothesis 14 proposed that
the relationship between structure and communication quality is contingent on leadership
style, such that a transformational style leads to higher scores in collocated contexts, but a
transactional style leads to higher scores in reachback and virtual contexts. This was not
found to be true using the original coding scheme. It was also found not to be true using
the new coding scheme for either the simple or complex tasks, B = -.133, t(84) = -0.419,
p =.34, B = 0.0, t(83) = 0.0, p =.5. However, unlike the results obtained with the original
coding, after categorizing the data based on specific structural configuration, there was a
significant interaction between the diunmy variable representing the difference between
virtual and reachback teams and leadership style for the simple task B = .535, t(84) =
1.305, p <.1. This partjally supports hypothesis 14.

Hypothesis 15 suggested that the relationship between leadership style and

leadership centrality is contingent on task complexity, such that a high task complexity

107

leads to higher scores for a transactional leadership style, but low task complexity leads
to higher scores for a transformational leadership style. Using the original coding scheme
this was not shown to be true. Hypothesis 15 was also not supported when the modified
coding scheme was used, B = -0.246, t(82) = -l.175, p = .12.

Finally, hypothesis 16 suggested that the relationship between structure and leader
centrality was contingent on leadership style such that a transformational style enhances
centrality in collocated contexts, but that a transactional style enhances centrality in
reachback and virtual contexts. Using the original coding scheme and moderated
regression this hypothesis was not supported. It was also not supported using the
modified coding scheme for either simple or complex tasks, B = 0.055, t(84) = 0.183, p
=.43; B = -0.362, t(83) = -1 .214, p =.12. However, unlike the results obtained with the
original coding, after categorizing the data based on specific structural configuration,
there was a significant interaction between the dummy variable representing the
difference between collocated and reachback teams and leadership style for the complex

task B = -.671, t(83) = -1 .702, p <.05. This partialb/ supports hypothesis 16.

108

CHAPTER 5 - DISCUSSION

Review of results
The underlying crux of this study was to determine how modern team structures

impact. popular conceptualizations of leadership. Most studies which have examined
leadership have done so using collocated teams. However, modern computer and
communication systems now allow teams to more easily form across time and space. No
longer do teams need to exist in the same room or even at the same time in order to
effectively function. Given the benefits that such virtual teams offer, and the increasing
ubiquity of the technologies that power them, their popularity has recently surged. This
is a trend which shows no sign of abating. As a result, it is imperative that a serious
effort be made to examine how such structures impact leadership processes.

Another interesting feature of this study is the introduction of a reachback team.
A reachback team is one in which all the members are collocated but the leader is virtual.
Examining such a structure responds to a recent call made by some to study differences
between partially distributed teams rather than on simply concentrating on how purely
virtual teams differ from collocated teams (Martins, Gilson, & Maynard, 2004). A
reachback team is a particularly important type of partially distributed team to study
because of its prevalence and growing popularity in organizations as well the demanding
contexts it is used within such‘as those involving disaster response teams and the
military.

Given that communication processes are such an important characteristic of
leadership, and perhaps the only obServable manifestation of it when the leader is not
collocated, it figured prominently in this study. Hypothesis 1 suggested that

communication quantity would be lower in a reachback team compared to a collocated

109

team and hypothesis 2 suggested that communication quantity would be lower in virtual
team compared to a reachback team. While hypothesis 1 was supported for both simple
and complex tasks, hypothesis 2 was not. In fact, the exact opposite relationship was
supported. Their were so many comments made in the virtual team that when
communication quantity was regressed on a dummy variable representing collocated vs.
virtual teams, the result was nearly significant after controlling for complexity, B = .153,
t(99) = 1.586, p = .058. This suggests that there were almost a significantly higher
number of comments made in the virtual teams than the collocated teams. This result is
surprising given that several other studies have shown the opposite to be true (Martins,
Gilson, & Maynard, 2004). As a result, it is possible that moderators exits which might
account for this difference. Given that a few other studies have also received results
similar to those obtained by this study (J essup & Tansik, 1991) it might be fruitful to
search for similarities between them in an effort to find these potential moderators.

One potential moderator that might exist is the nature of the task. For example,
Bell and Kozlowski (2002) have proposed that the task might lead to substantial
differences in outcome. In fact, when these data are segregated based on high and low
complexity games, the significant difference in communication quantity between
structures disappears for a low complexity game t(49) = .865, p =.195 but is still partially
present in a high complexity game t(47) = 1.390, p < .1.

The next set of hypotheses suggested that the quality of communication changes
based on the team structure. However, no significant changes in quality were observed
across the three structures. This was true for both the primary as well as two secondary

measure of communication quality. This result was interesting given the large changes in

110

communication quantity across structures. Perhaps most notable is the fact that the
reachback team had the lowest communication quantity but. exhibited a higher level of
communication quality when compared to the two other structures. If overall
communication quantity goes down but quality tends to rise than a reachback team might
prove to be a very efficient structure combining the “best of both worlds.” In fact, in
unstructured exit interviews with a limited number of subjects who participated in the
experiment as a member of reachback team and a collocated or virtual team, many stated
that they enjoyed working in the reachback configuration over the virtual and collocated
structures. A few of them made the unexpected comment that when they were part of the
collocated subgroup in a reachback team they were better able to “understand who was
saying what” compared to when they were in a fully collocated team. When asked why
this was true, they suggested that it was because the headsets, which they used to
communicate with their leader and each other in a reachback team, made all team
communication more structured and therefore easier to process.

Another interesting outcome of this study was the correlation between
communication quantity and quality. In a collocated and reachback team the bivariate
correlation was rather low in both the simple (r(26)=.206, p=.157 and r(21)=.073,
p=.377) and complex tasks (r(26)=.099, p=.315 and r(24)=.026, p=.451). However, in a
virtual team this number climbs dramatically, (r(25)=.355, p=.06 and r(23)=.450,
p=.228). This suggests that in situations with a large number of collocated individuals, a
higher level of communication might not lead to a higher level of communication quality.

However, when everyone is remote this relationship might become more important.

lll

Hypothesis 5 saw the introduction of leadership orientated hypotheses. It
proposed that for each structural configuration, transformational teams will exhibit a
greater number of comments compared to transactional teams. This was suggested due to
the fact that transformational leaders need to attend a greater number of leadership
behaviors and because a transformational style will lead to greater cooperation and
therefore more comments by followers. This hypothesis was supported for both
collocated and reachback teams. However, it was not significant for virtual teams but
only because the standard error was so much larger in this structure.

Hypothesis 6 proposed that communication quality will be higher in a collocated
transformational team than in a transactional team. This hypotheses was not supported
with the regression results, however, when the data is segregated based on structure and
only the collocated teams are examined, the correlation between transformational
leadership scale in the MLQ and communication quantity is nearly significant for the
simple (r(26)=0.266 p=0.056) and complex r(26)=0f.189 p=0.177)task. Further, the
correlation between transformational leadership and quality is significant for the simple
(r(30)=0.464 p<.05) and complex (r(29)=0.406 p<.05) task.

The most unexpected aspect of this two relationship is that they extend to the
virtual teams as well. In the reachback teams the relationship between the same measure
of transformational leadership and communication quality is r(27)=0.550 (p<.05) for
simple tasks and r(27)=0.485 (p<.05) for complex tasks. In a virtual team it is
r(28)=0.628 (p<.05) for simple tasks and r(28)=0.506 (p=.142) for complex tasks.
Perhaps most interesting is the fact that this relationship is stronger in a virtual and

reachback teams compared to the collocated teams. This suggests any transformational

112

behaviors which are manifest in a non-collocated team might actually be more important
to overall communication quality than they are in a collocated team.

Hypothesis 7 predicted that a positive relationship exists between task complexity
and overall team communication quantity. This relationship was fully supported which
suggests that when task complexity increases teams are more likely to engage in more
communication. These results are especially significant given that the low complexity
condition had a higher task scope which is characterized by the amount of objective work
required. In this condition the task complexity was low (as conceptualized by
component, coordinative and dynamic complexity) but the number of targets was actually
greater by 47%. Therefore, it is not the level of task scope that matters to communication
but rather the level of task complexity. In these high complexity situations teams need to
work smarter to understand and process the action and information cues which are
presented to them. They also need to work smarter to coordinate information between
each other. When a task is complex, the ordering and sequencing of information and
actions becomes critical. Therefore, teams need to work together more and as a result
communicate to a higher degree in order to make this happen. Further, high task
complexity environments are also those in which the situation is dynamic. In these
situations action and information cues might be either hidden or change over time.
Therefore, teams need to communicate more with each other in order to discover the true
nature of these cues.

Hypothesis 8 and 9 introduced the idea of leader centrality. This concept was
presented as a way to capture how the experimental manipulations impacted leadership

processes. Hypothesis 8 suggested that team member perceptions of leader centrality will

113

be lower in a reachback team than a collocated team and hypothesis 9 proposes that team
member perceptions of leader centrality will be lower in a reachback team than a virtual
team. Neither hypothesis was supported.

Originally, it was suspected that leader centrality would fall due to the formation
of faultlines. It was theorized that leader centrality would be lower in a reachback team
due to the formation of salient subgroups since the presence of diverse subgroups would
keep the centrality of the leader low. However, it is now suspected that while diversity
might still play a role in this process it might do so in a very different way. It is now
suspected that in a reachback team, primary diversity dimensions such as gender, height,
and attractiveness are masked or at least not made as salient. Such individual traits as
these have been found to have an impact on perceived leadership ability (Anderson,
Lievens, van Dam, & Born, 2006; Hogg et al., 2006; Kirkpatrick & Locke, 1991; Lewis,
2000) so if they are unavailable, other traits which are available become a more
influential indicator of leader centrality. The implication here is that if an individual trait
has a negative effect on perceived leadership ability in a collocated team it may not have
the same effect in a non-collocated team since the trait is blocked by the communication
medium. This means that for the purposes of leadership, individual traits associated with
social category diversity may not mean as much in non-collocated teams as they do in
collocated teams.

Hypotheses ll, 12 and 13 tested whether the mediators had a significant
relationship with the dependent variables. Communication quantity (hypothesis 12) was
not found to be significant with any of the dependent variables. This might be interesting

given that intuitively it would seem that more communication leads to higher team

114

performance. However, communication quality and leadership centrality did have strong
effects with team satisfaction and leader satisfaction.

The relationship between communication quality and team satisfaction was
expected given that positive attributes and outcomes have been linked to communication
quality in the past. For example, high quality communication and competence has been
shown to be based on information giving, information seeking, information verifying and
socioemotional communication (Cegala, Coleman, & Turner, 1998) as well as the quality
of a performance (Alrneida, 2004). Communication quality has also been linked to
several positive organizational related outcomes such as higher performance for teams
working on innovative projects (Hoegl & Gemuenden, 2001) and higher rating for
managers (Penley, 1991). It has also been shown to have a positive influence on attitudes
towards instruction (Bolls & Tan, 1996), productivity, and job satisfaction (Campion,
Medsker, & Higgs, 1993; Campion, Papper, & Medsker, 1996). Therefore it was
expected that high communication quality would lead to high team satisfaction.

An explanation for the relationship between communication quality and leader
satisfaction is provided by leader member exchange (LMX) theory (Graen & Uhlbien,
1995). This theory suggests that differences in the quality of the communication and
relationship between supervisor and subordinates impacts performance. This theory is
based on the social exchange perspective (Blau, 1964) which states that if one party is
perceived to act in the best interest of another they will be rewarded for it later.
Communication quality has been shown to be a dimension of LMX (Graen & Ginsburgh,
1977) as well as an outcome of it (Fairhurst, 1993). From this it can be seen that high

levels of communication quality will lead to, and result from, high levels of LMX which

115

itself is characterized by a strong and satisfying relationship with leaders. Therefore, we
can expect that teams with high level of communication quality to have high levels of
LMX and as a result a high level of leader satisfaction.

As mentioned earlier, leader centrality was also shown to have a significant
relationship with team and leader satisfaction. Centrality can be considered the degree to
which individuals in a team are thought to exist at the nexus of activity within a network.
Leader centrality is therefore the degree to which team leaders are thought to hold such a
position and as a result can bethought of as the amount of influence they have over team
members. Therefore, leaders who have a high level of centrality can be thought of as
being at the center of the action and fully engaged in team operations. It is suspected that
when leaders have such an attribute, followers will tend to feel better and more complete
about their experience and as a result have a higher team satisfaction. This process
becomes even more pronounced if leaders, due to their superior location in organizational
hierarchies, have important information that other team members do not have. If this
information helps teams perform their task, as it did in this experiment, then followers
will be even more likely to view their experiences favorably if this information is shared
and used.

Given that the behavior of the leader can impact the team satisfaction ratings we
can expect that such behavior would correlate even stronger with leader satisfaction
ratings and in fact, this is exactly what was observed. The relationship between leader
centrality and leader satisfaction was more than twice as strong as it is with team
satisfaction. This is evidence that while leader behavior might impact team satisfaction,

it impacts leader satisfaction even more.

116

Finally with regards to hypotheses 11-13, it is interesting to note that
communication quality had a significant relationship with performance when task
complexity was low but not when it was high, however, leader centrality had a significant
relationship with performance when task complexity was high but not when it was low.
One possible explanation for the first result is that when task complexity is low, high
levels of communication quality can be taken advantage of and processed so as to lead to
higher objective scores. However, when complexity is high team members might not be
able to capitalize on high levels of communication quality and as a result, a significant
relationship with the outcome variables will not exist. In this situation team members are
so cognitively challenged by the situation that the level of communication quality in the
group is discounted. This is consistent with the Resource Allocation Model which
suggests that goals have a much stronger relationship on performance when perceived
task complexity is low (Kanfer & Ackerman, 1989). This model suggests that when the
task is complex or novel, attentional resources are applied more towards mastering basic
task functions rather than achieving goals. In the same way it is possible that when task
complexity is high, team members are not able to effectively process and capitalize on
high levels of communication quality. Only when working on low complexity tasks are
members able to focus on, and effectively utilize, high levels of communication quality.

One possible explanation for why leader centrality had a significant relationship
with performance when task complexity was high but not when it was low is that when it
is low team members don’t rely as much on the leader. In this situation, they might feel
as though they can complete the objective on their own so they don’t need leader input to

help them execute the task. Given that the low complexity task did not require any

117

leaming, had a functional structure, and very predictable targets this becomes even more
of a possibility. Given that no learning was required, members did not need to
communicate with anyone in order to better understand the task, therefore, they did not
need a leader with a high degree of centrality that would help everyone learn from
everyone else. A functional structure meant that they all had the same vehicles so that a
leader with high centrality was not required to coordinate resource allocation and usage
between members. Finally, since all the targets were predictable each member knew in
advance from which direction all the targets would come from. Therefore, they did not
require a leader which was able to detect targets sooner, as was the case in the
experiment.
Mediators

As already shown the proposed mediators did not perform as expect. Such an
outcome begs the question as to what constructs might actually explain why the proposed
proximal independent variables impact the distal outcome variables. Not performing
such a retrospective examination would be to irresponsibly ignore all that has been
learned while performing this study. Therefore, this section will attempt to identify these
constructs. To do so it is perhaps best to consider the training given to the leaders. By
identifying the exact behaviors each type of leader was trained to exhibit a better
understanding of the potential individual and team level responses may be achieved.

As previously mentioned, the transformational leadership training tended to focus
on the affective dimensions of leadership, while the transactional leadership training
tended to focus on the more rational or cognitive aspects of it. For example, the

transformational dimension of idealized influence has to do with the leader speaking

118

about their most important values and beliefs, instilling a sense of pride, purpose or
mission, and building respect. Similarly, individual consideration is based on the leader
acting as a coach or mentor, developing strengths and considering everyone’s needs,
abilities, and aspirations. In contrast, the transactional dimension of contingent reward
and management-by—exception tends to focus on mistakes, exceptions, deviations from
standards. This style of leadership is based more on developing and utilizing a
contractual exchange relationship.

As a result, these two types of leadership might differentially impact the affective
dimension of an individual or team. At the individual level we might expect that these
two leadership styles would differentially impact state based affective dimension such as
mood and emotions. For example, transformational leadership has been linked to such
individual level constructs as increased levels of pride, optimism, enthusiasm, and
decreased levels of frustration (Kiipers & Weibler, 2006; McColl-Kennedy & Anderson,
2002) which have been linked to performance (Barsade, Brief, & Spataro, 2003).
Transformational leadership has also been linked to increases in subordinate creativity
(Shin & Zhou, 2003). This relationship might have particularly profound implications for
virtual team leaders since in this environment, subordinates may be required to solve
problems on their own due to a lack of access to superiors or advice structures.
Individuals who are more creative might be at an advantage in this situation due to their
ability to develop multiple unique solutions to a problem independent of outside
influence. However, if leaders are unable to effectively exhibit transformational
behaviors in a virtual environment the amount of team member creativity may not be

maximized. This means that when creativity is needed the most it has the smallest

119

chance of being increased by the leader. In contrast, we can expect that, a transactional
leadership style would not have as much of a positive influence on such affective
components. The behaviors associated with this style of leadership are not based on
emotional aspects but instead are based on a more impersonal and calculating contractual
form of leadership.

At the team level, transformational leadership might increase the strength of
shared vision or organizational commitment. A stronger shared vision in a team might be
realized given that transformational leaders focus on the emotional health of the team,
rapport building, and empathetic language. These behaviors might also result in
increased levels of organizational commitment as leaders provide an exciting image of
the organizational vision or by getting followers to put in extra effort and go beyond what
they thought possible. On the other hand transactional leadership might lead to a
decrease in organizational commitment due to the leaders focus on mistakes and
deviations fiom standards. As a result, transformational leadership might positively
impact affective team mechanisms while transactional leadership negatively impacts
these same mechanisms.

In addition to differentially impacting emotional dimensions, these leadership
styles might also impact cognitive motivational differences at the individual and team
level as well. At the individual level self-efficacy might be raised. For example,
inspirational motivation has to do with expressing confidence that goals will be achieved
and disseminating a compelling vision of the future. Such behaviors might make
subordinates feel as though they can transcend their current limitations and transform

themselves to be more capable. This might increase their self-efficacy and make them

120

feel as though they are more capable than they originally thought they were. Such a
process might also extend to the team level. Leaders might cause the entire team to
believe that they are more potent and are able to transcend the sum of their abilities,
work, or output. As a result, this might increase the collective self efficacy, or potency,
of the team. In a similar way inspirational motivation might also increase empowerment
which is defined as, “increased intrinsic task motivation manifested in a set of four
cognitions reflecting and individual’s orientation to his or her work role: competence,
impact, meaning, and self-determination.” (G. M. Spreitzer, 1995, p. 1443). Given both
the cognitive and motivational aspects of this construct it seems particularly relevant
when examining the cognitive aspects of inspirational motivation. Based on this
definition it might be suggested that by increasing team self-efficacy, reminding teams of
the importance of their task and goals, focusing on the larger context of their mission, and
giving team members a certain degree of autonomy, transformational leaders are able to
increase empowerment to a level that transactional leaders are unable to.

Finally, by exhibiting behaviors consistent with the transformational dimension of
intellectual stimulation, leaders might be able to increase the amount of positive conflict
within the team and decrease the amount of negative conflict. As mentioned earlier,
intellectual stimulation relates to the ability of leaders to stimulate followers to be
creative and innovative, and to challenge their own beliefs. As such we can expect that
leader’s who exhibit a high level of intellectual stimulation to seek differing perspectives,
suggest new ways of how to look at problems, and encourage novel thinking. This has
the potential to increase substantive, task orientated conflict within a team. This type of

conflict is characterized by team members considering different viewpoints pertaining to

121

a task. It includes debate related to different ideas, opinions, or strategy on how to
complete a particular task. As such, this type of conflict is a key defense against group-
think and has been repeatedly shown to have a positive relationship with task-related
outcomes (Dirks & McLean Parks, 2003). Others have proposed that exercising the type
of conflict might actually strengthen relationships between team members and as a result,
lower the level of unhealthy team conflict (Dirks & McLean Parks, 2003). By increasing
the amount of positive conflict, healthy team attitudes, norms and processes on how to
handle conflict within the team might start to form. This has the potential to improve the
ability to a team to handle future conflict constructively. ’

Limitatiowd future studies
Of course as with any study there are limitations. The first limitation is that only

one task was used. As already mentioned, it appears that task might moderate the link
between structure and communication quantity. Therefore, it would be important to
examine this possible interaction in the future. Another limitation is that the low
complexity task in this experiment had a larger scope. In other words, there were more
targets in the low complexity condition than there were in the high complexity condition.
Future research might want to keep complexity or scope constant while only
manipulating the other. Another extension of this study might be to examine different
mediators. While several elements of mediation are present, it was not firmly established
that the proposed mediators explain why the independent variables impact the dependent
variables. A future study might attempt to probe other reasons why these relationship
exit. For example, a newly published study also uses faultlines to explain why levels of
conflict and trust in a team might change depending on virtual team structure (Polzer,

Crisp, J arvenpaa, & Kim, 2006). This study found that reachback like structures have

122

high levels of conflict and lower levels of trust compared to fully virtual teams. This is
similar to the unsupported theory presented here that leader centrality would be lower in a
reachback team compared to a virtual team due to the presence of faultlines. Therefore,
while the impact of structure on performance is not mediated by leader centrality it might
be by the level of conflict and trust in the team.

A final idea for a follow-on study would be to examine the effects of leader
presence. This construct can be thought of as the percentage of followers which are
collocated with a leader. In this experiment, leader presence was low in the reachback
team so it would be interesting to conduct an experiment in which leader presence was
high and compare the results. It is possible that the relationship between such structural
changes and performance might also be moderated by individual traits like personality or
task complexity. For example, it might be that when leader presence is low, followers
with high conscientiousness might not be effected very much. However, followers with
low conscientiousness might have lower performance because they don’t feel the need to
work as hard if their leader is not in the room. Further, if task complexity is high
performance might be better when leader presence is high because a majority of the
followers will feel more connected to the leader.

Another limitation of this paper is the use of the MLQ to measure
transformational and transactional leadership. While the MLQ is still considered the
most popular measure to access transformational and transactional behaviors (Heinitz,
Liepmann, & F elfe, 2005) there have always been questions regarding its validity. For
example, Den Hartog, Van Muijen and Koopman (1997) found that the MLQ cannot

discriminate between different sub-factors of transformational and transactional

123

leadership. They also found there is not discriminate validity between the sub-
dimensions of laissez-fair and passive management-by-exception. Later, in a meta-
analysis, Lowe, Kroeck, and Sivasubramaniam (1996) showed that average correlation
between the transformational sub-dimensions of charisma and individual consideration
was 0.74. In a separate study, Bass and Avolio (1997) reported the same correlation was
even higher at 0.81. However, for the present study there were no hypotheses that
differentiated between the sub-dimensions of transformational and transactional
leadership so the inability of the instrument to discriminate between them is of little
consequence here. What is much more relevant to this study is the tendency of
transactional contingent reward scale to correlate with those associated with
transformational leadership. This is more of an issue because it might cause a
transactional leader to be measured as a transformational leader. Lowe, et al. (1996)
reported that average correlation between the transactional dimension of contingent
reward and the transformational dimensions of charisma and individual consideration was
0.68 and 0.70, respectively. Similar results have been obtained by others (Tejeda,
Scandura, & Pillai, 2001; Vandenberghe, Stordeur, & D'Hoore, 2002). In fact, two
different exploratory factor analyses have confirmed that contingent reward loads with
the transformational scales rather then the transactional scales (Heinitz, Liepmann, &
Felfe, 2005; J. C. Wofford, Goodwin, & Whittington, 1998). These results bring the
discriminate validity of transformational and transactional leadership, as measured by the
MLQ, into serious question.

In addition to the discriminate validity of the MLQ, a question regarding its

construct validity has also emerged over time. The question here is whether or not the

124

MLQ is truly measuring transactional leadership. If as suspected the MLQ is not
measuring transactional leadership but some variant of laissez faire leadership then it is
possible that the measured transactional leadership scores will not be valid. This would
be a particularly acute issue for the transactional condition of the present study since the
transactional leadership scale was the primary measure used to determine the strength of
leaders in this situation. If this scale was measuring something other than transactional
leadership, we would never truly know the actual level or transactional leadership
exhibited by those individuals.

Initially, Burns conceptualized transactional leadership as a style of leadership
that promotes cohesion and consensus while reducing conflict. He felt that this could
occur at both the organizational and small group level. In fact, his chapter titled, “Group
Leadership” is in the transactional part of his book. To him transactional leadership is a
positive and legitimate form or leadership which has the potential to consider the values,
attitudes, beliefs and emotions of follows. It is not a style which is naturally predisposed
to colder or stoic aspects of leadership. For example, he writes that transactional leaders
“know how to personalize their influence” (J. M. Burns, 1978, p. 263). These sentiments
are echoed later by those who suggest that the actions of transactional leaders are “in the
best interest of their followers” and that such leaders “must regularly fulfill the
expectations of their followers” (Kuhnert & Lewis, 1987, p. 649). However, it has been
noted that this can be accomplished by using either a high or low quality exchange
relationship. A high quality relationship’is based on the interpersonal bond between
leaders and followers (Landy, 1985). Such a relationship focuses on the exchanges of

trust, commitment, and respect. In contrast, a low quality relationship is based on the

125

exchange of goods or rights. In this type or relationship leaders are more interested in the
extrinsic motivating forces of rewards and pay. Not surprisingly, higher quality
relationships have been shown to relate more strongly to positive organizational
outcomes compared to low quality relationships (Ferris, 1985). Therefore, it is the high
quality relationships that the MLQ should be measuring. Unfortunately, the opposite
seems to be true. In fact, the transactional leadership scale in the MLQ seems to be
measuring a form of laissez faire leadership or anti-leadership. In fact, every question in
both the active and passive management-by-exception leadership scales, 3 full two-thirds
of all transactional items, asks followers to either rate the degree to which leaders only
concentrate on follower mistakes and failures or identify the lack of involvement by the
leader. Perhaps the most egregious example is the item, “Fails to interfere until problems
become serious”. It seems rather odd to expect that anyone would rate or characterize
any type or strong leader as a ‘failure’.

For those who might suggest that the true nature of transactional leadership is
irrelevant in this experiment because the training was based on the MLQ itself, three
things need to be stressed. First, the training was built around the concepts contained in
the MLQ and not the pejorative comments made in it. In fact, leaders where even told in
the training that they do not need to be mean or nasty to exhibit transactional behaviors.
Second, even if the leaders thought they were supposed to behave in an unappealing way,
followers would probably have been unwilling to provide accurate feedback confirming
this. It has been shown in other studies that followers are much less likely to give
feedback that they perceived as negative especially when there is little temporal sc0pe

within the team (Audia & Locke, 2003). Third and finally, because most leadership

126

training today is based on positive behaviors, we can expect that if the training was
ineffectual for any of the transactional leaders, they would probably revert to more of the
transformational behaviors which they have been taught are the more valid forms of
leadership. This would especially be true of undergraduate students who probably have a
high social desirability bias.

In conclusion, while this was a very rich study that examined many aspects of
virtual teams and leadership, it only the scratched the surface of what needs to be
examined when it comes to the interaction between these constructs. Future studies
should continue to examine this relationship as these structures become more common

and grow in importance.

127

395.». mm c com .8388 mm _ ”cocoa .3539 v

_meouoamcg mm o 28 Engagement a ~ ”we—coo 3:55 o
Ada—ETC “—03:08.— .m> _QEFHNQ “vowed >885 a
€88.58 u: xoannoeoc .9 pounce—Bola ”vowed 5555 a
8V9... "3V9. ”scammed a E 0332. one “we“: an 3283 3:588 on Loaded 93
mm 8 Nb HZ

 

 

_ t8. 3 :S. :2. :S. :5 3 3o 85 2.? a: and. Seascapes: .:
_ E :2. :8. :K. 85 3 8.? :6- 85. m3 ”3. Succeed ESP .2
3 E E E 3 3 E E E . . 35.38
awn: conga—om .m
_ :8. :3. 3o 3 .2. :6- 26 So 3.0 38388
263 coca—notch .w
_ tom. 25 3 :5 8.? 3o- 2: Sec- 3:885an N
_ m3 3 25 mod. 8.? S.— Rd- ease
couaogou .o
. 3 ram. :8. MS :24: _NSNS budge
connoisfifioo .m
3 E 3 3 o o a 3:238 as... .4
_ 3.? cod no $3 02% nieces“: .m
_ in. :8 «do a a 58:8
vacuum Each. .N
_ med «3 a c 3:58
0525.0. 83,—. A
2 E a w n o m e m m _ Om 502

 

97.3 29:5 meets—ocuouaoauu can £83359 FEE—Sm Jade—Z .m 03:.

max—med. :HZHEHAAA—Dm

128

0886 mm c EB 5888 m_ g 6080 88:5 v

383888 a o 88 _8ougemaab fl _ 638 >85 0
£583an xomnnuaou .m> __BEWNQ 60on >88=Q p
388230 n: “—03:82 .m> cog—woozoon—Q 688 >88=Q a

8V8: HQVP. 38388 a mm 0389» one .23— 3 8:83 3888 on 8883 Aav
«w 3 mm. HZ

 

 

_ :ov. LA. 3 :8. :8. mod 3 .8. SS. 2.? mg mg Swoemuam 533 .:
_ :2. 3 :vm. :5. mod 3 So So- 83. 8d 2d 888:6 Ema. .2
_ 3 :3. :8. m3 3 Ed .2.- :R. 93 o 332858
:35 3588883 6
3 3 3 E 3 3 3 3 3:238
Bo: coagotom .w
_ :8. Ed E .3. MS. a; no 35 3238323 .5
_ 3o 3 Ed NS- :56 mg mg €96
cousin—88800 .0
_ E :8. .39.. Ed 358— «32$ 95%
858888855 .m
3 3 E 3 o _ chaoiuoo “.3 .v
_ o 8d no no 03?. @3533 .m
_ : _ n- as and A. a 3.5.8
2828..” 83B .N
8 £3 mg a 2 Ease
”Suva—hm Each. .—
: 2 a w n o m w m m _ am :82

 

Ema. 5.983V macaw—0889.8:— 88 £853.59 aha—=85 .2302 .v 03.;

129

35:085.: .8 o 88... _mcozgemfib fl _ ”cacao >88=Q a
22:3": finance: .2, _gugnma ”BBQ €55 a
$830.30 u: x2353: .m> cognac—Bola 638 >885 a
avg: 7:... ”8:8: mmnz

 

33 «.388 8:8
m8. 2% 3883 8:8
:38. «and 10822 9 $8 03m 839533
$3. :888 ._ 38 832:5 58.:
Vde gimm~39~ a 98 obdonm Each.
35%. :83? “588
my? sum m caeacaséo

 

>382? 8538:88e0
$7.3 5.28:3 >388? 8538—8—83 an: 333:? 8282—35 83.50: 313.9. 8.6853— .e «Emu.

3805888 mm o 28 _8oum8uofiqg mm _ ”cacao >885 o
22%,“: :0358: .9 _StEuS ”880 ESE n
3030230 HG x0353: .m> meoo=oou_fl ”cocoa >888 a
movat: ~.Vm_.. $553 KHZ

 

NS .c was? 8:8
:8. Ed ”was? 8:8
:35. 33 :3 88: o :8 25m 3:533
32 :8:§ a £8 eaofim 88,—.
:35 _ .3882 u :8 eaofim 88H
:3. :38? “5:88
”:2 sum m caaaucsé:

 

>388: 83:88:88.5

323 2985 >583: 53385883 88 833...; 82.85er :3an 333.. nommmouwom .m 03:.

130

3828888 8 o 98 3803888888 3 3 3688 >88=Q 9
23:3": “.8882 .9 _§E>u8 ”BBQ 8:38 5.
888280 HS 83:82 .m> 338:0"le 638 >889 a
nova: Va... mama mwuz

 

831 88°. 8:8

8o. 83 8:. 8:8

.38 8:. $98 183:8 838.88
8.? £8. a 68 2328 588
fled. 83. a :8 832:5 ESP

:8. :22. .5328

:84 sum 8 caeécsa:

 

>333. 8333388880

 

223 8.8883 >338: 833838883 38: 8.838; 82823283 5952— 388.. 833083— .w 038,—.

3808888 8 o 2.8 380380.388 m3 3 688 >885 o
2833": 88:03." .m> ~833H~Q 60.89 >85 3
888280": 83:88 .m> B~a8__oW~Q €088 >885 a

131

88...... Va... m8:3 guz

 

 

986. M: _.c. mama
m S. RN? mood. main—
w 5. 23 $8 0 $8 25 82323
wmfio. She. nfime obsosbm 83H
2 3. 88- a :8 8:885 E88.
So. was. 88880
:8 98 8 8.36558:
>338. 8333888880

 

28» 2885 >585 833338.888 .8: 83883 8282—88 83.52. 8.88.. 8.8295 .5 «Bah.

 

132

m3"; nova nova .me
5 mm E a.
83 53 $2 052% H
.3. _ we; 81S 53m} «8ng :82
323 ”$.33 83?.» 535:5
03.33 ”3.3% 838.5 _mcoaéceaee
.3.—:50
flown nova Eva .3
mm a E .6
23 :3 «9: 835.0. H
«8.83 at _ a 33%; 855:6 :82
5.33 5.23 83w? _Souoacee
£5.me 23.83 92.3% _aozécemnae
33> xosgosm 838:8
29:5

 

Am 885255 bran—__. 8:80 8 820.. >2: 3 bus—AEGU swan. x “it. 35.—auscu— x 9.32:5 d 035‘

$828885 8 o can 382385.355 8 5 6098 >885 o
23%": €3,882 .2, EESuS ”BBQ 8&5 n.
€038.30 HG #83:an .m> cognac—Eula ”woven. >885 a
avg: Va... was“ mwnz

 

owmd. $36. mama

omo. wood. wood- max—Q

:03. :3 3.6.3.6 a $8 23m newscafi

3?? god. a ANA: ago—Em 83H
wEd wvmd a 98 chaosbm 88H

98. 2.5de 83.880

Rd «:5 m 38938383

bah-$0 “__.—82.35

 

 

97.3 518:335583 83.no— vua 833...; 8282368 5952. 3.58.. 8339.3”— .: 03:8

3828385 mm c 28 8838:8885 fl 5 638 >885 0
23:3": 83:88 .9 _gttnmn 608° 3:38 9
8882—8 HS Joan—:88 .m> “fiasco—Bola 638 >5 a
8.x... V? was. 3T2

 

 

god cwmd mama
ace. Necdl 3: 6: mafia
as. at... $98 0 Ge 25 82333
"Edi Gmdl a QB chaosbm 88:.
SET 83: a CB ufiofim 88,—.
m8. 986: 88.850
~84 sum m @3638332
bay—800 3:32:85

 

393 9385 bars—So .563— EE 833...; 80682—065 .5253 8.58.. 838052: .3 035.

133

avg: ..v.._._ £52 :uz

 

 

.20 ~30 0,. x :30 8:80
at... :80 .550 .580 x 0..
8o. 8... :80 .530 8&8 x :30 8:50
BS :8. .0 £350 028.08..
80.0. Sod. >380 808.058.8800
mmod cod b08000 80500808800
.3.. a _. R 3 .0. 88800
~02 .30 0 03638380
ouflaahctoh

 

90... 0.038000 0088.800.— E... 0,038.8.» .0830... 800.503 3.5.0.. 830.00..»3— .2 035.

2.x... .2.... was. Sn

 

 

.2... 2.02.0 0. x .30 6&8
30.0. 8.0 .85 .850 x 0..
:wa 08.0. 8.0 .530 880 x .20 5:80
08.? 08.... 8850 8.832.
210 3.. . mmd . >580 8050808800
306 cod >380 80500808800
:02. E... 25250
«0.4 sum 0 uaegcséa
00.88.030.—

 

98. 0385 00.88.020.— 08. 0030......» 88.008 800.503 3.30.. 80.20.80,: .3 035.

134

8.x... 3.... 058. :nz

 

 

$3 .88 00 x .20 580
5.? .88 .530 880 x 0..
.88. SH. :88 .530 8:50 x .80 :800
$3 :83 £380 82.3.08.
.88 :82 0.8.0 8828880
:20 8.8 5530 808.8580
:08. 8...? 85.80
02 sum 0 08638980
=0uuaumflam 800,—.

 

903 53803 80.008302 8000 0.... 0030...: .3838 800.50.. 3800.. 80.0833— .3 0.8:.

8.x... V... £53 :uz

 

 

5.... .8.... 0.. x .sfl 8.80
3.8. 8... .530 580 x 0..
So. Rmd cod 80:0 8800 x 300 8800
3: .8 8.... 8.380 88083
20.8 :80... 0:80 808855.00
30.0. 00.0 8.8000 80.58808800
{icmfl mend 33950
.8. sum 0 086305.80
80305303 800,—.

 

305 0.085 80308032 8000 .08. «038.3 808—008 80050.. 3:50.. 80.80%3— .3 030,—.

135

8v... 7... .232 :uz

 

 

8m... :82. 0. x .80 .850
.8.? 8... .580 880 x 0.
.88. EN... 8... .530 880 x .80 880
3m... :82. 8.2.80 n.888.
30.0 00mg... .3030 80.000808800
mood. coo... b.5880 80000808800
1&0... ommd. 88800
0... a... m 0303.05.80
00:00.0..aw 3000..

 

$.00. 5.0800. 00.000.00.20. .0000. 0.... 0030......» 8.8008 000.50.. 8.000.. 00.3.0.9”. .5 0.8....

3v... ..v... 058. :uz

 

 

.2.? .8.... 0.. x .20 .880
.8.... 8... .530 .580 x 0..
NS. .8.... 8... .520 8.80 x .20 880
00m... .1. .00... 3.00800 0.8800001.
0mm... I. .02. .0285 80.000.88.800
wmod. 00.0 b.8000 00000808800
:30. 8.... 0.5.80
.04 sum 0 0383.05.80
nomgaummuaw hofiao‘u

 

0.08 0.08.0. 00.000.00.00 .0000. 0.... 00.00.83 800.008 000.50.. 3.30.. 00.0.0053. .0. 030,—.

136

.0800000000 0. 0 0:0 300.08.500.88. 0. . ”00000 x8809 0
20303100300502 .m> .ESHNQ ”00000 >883. 0
300000.60 u: 0.009.008 .m> 00.000..00H.Q ”00000 >85 0

MOVE: _.VQ_.. mg. me2

 

 

02.0. 00.0. mama

0.0. N000. .000. main.

000. 000.0 08.0 0 Ana 000m 0280000..
03.0. 2.0.0. 0 Ame 0.3.00.0w 800 ...
52. .080 . :0. 83250 680

1&8. $0.0. 8000800
”ya 0.00 0 0000000088:
000080020.—

 

3000 00.0800. 0000800200 000 0030...: 800000000. 000.500 8.000.. 00.000031 .0. 0.00M.

3000000000 0. 0 0:0 .000008000800 0. . ”00000 >883. 0
0.3.3.: 003008. .2, 3th0 “0.80 €500 3
33000.30 u: 0.008.008 .m> 00.000..00H.Q ”00000 >85 0
8.x... 0v... .253 8.2

 

 

.N~.0 $.00 mama
3.00. 30.0 t... :0. mafia
0:..me mw—d gin—Nd 0 Ame 000m 0.30.5000..—
.03. and. a .08 05250 880
08.0 03.0 0 Ce obsogm 800...
0.0. R00 8000000
0% 80m m 000.000.8800:
0000800000..

 

3000 0.0800 0000800000.. 0:0 0030...: 800000000. 000.50.. 8.000.. 00.0000uoy— .0. 030,—.

137

3000000000 0. 0 000 3000080000000 0. . ”00000 0.88.5 0
2030.5": 0.009.000. .m> .gtSHNQ ”00000 >883. A.
€808.30 n: 0.008.008 40> 0000023019 ”00000 08805 0

3v... 0v... £33 mwuz

 

 

80.0. 23. «.900
ms. 080. 0:0. 850
000. 000.0 0N..0 0 Ame 0.3m 02000000..
0. S. 000.? a .00. 83250 880
83.. ~03. . A :0 238% 680
08. , .33 65.80
.00 sum 0 03.285080
00.80.0300 800...

 

0.0.0. 00.08000 00.000.00.00 800. 000 00.00.05, 0000000000. 000.500 3.000.. 00.0000u0fl AN 030,—.

3000000000 0. 0 000 3000000000000 0. . ”00000 >82. 0
080.31.003.08. .9 0:03.00 ”808 05:30 9
83000.30 u: 0.0000002 .m> 00.000..00H.Q ”00000 >885 0

8.1.: 0V0. .833 mwuz

 

 

.30. 80.0. 8000

.8. $0.0 20.0 850

08. 03.0. 08.0. u .8. 20.0. 000508..
20.0. 5.02.0. a .8. 83250 580
30.9 103.0. . 00. 05250 88.0

.08. $3 050.80

.00 sum 0 080300330

00.000.00.000 .000...

 

900. 0.0.0.0. 00.00.000.000 8000 000 00.00.00> «00000000000350: 3.000.. 00.000.003— .0N 0.00...

138

.0000000080 0. 0 000 3000080000000 0. . “00000 08809 0
0.3.3.0 0.03082 .0, _ESHS 6008 00:50 0
93000.30 ".0 0.008.002 .m> 00.000:00N.Q ”00000 x8809 0
8.x... 0v... .053 3.2

 

 

mod. 0.. . .0. meNQ
woo. w0.0 0w . .0 main.
00mg. 0N0 ..im0m.0 0 Ame 000m 0.0.0.5000...
00.0. 02.0. a an. onuosbm 800...
83. L03. . 08 23800 03.0
£0. 00300 080.0000
.8. sum 0 8005508:
00.30.0000 00000..

 

$.00. 00.08000 00.00.000.000 00000. 000 00.00.00.» 0000000000. 000300.. 3.0000 00.0000w3— .3 0.00...

.0000000000 0. 0 000 3000080000000 0. . ”00000 80809 0
030;": 08288 9 _sfifma ”BBQ 050:0 0
68000.60 ".0 0.0000008 .m> 00.08.3019 ”00000 80809 0
2.x... 0v... was. 3.2

 

83. 0%.? 8000
So. 8.? $30. 850
80. 08.0 2 3 u .8. 0.0m 02308..
ES. 02.? 4 a .00. 23250. 88.0
000.0. .200. a :0. 003905 800.0
08. 08.0. 050800
.00 sum 0 086305080
00.00.000.05 00000.—

 

 

200. 0.0.0.0. 00.000.00.00 00000. 000 00.00.00.» 0000000000. 000.500 0.0.0000 00.000003. .NN 030,—.

139

 

00.x. .0000- n .0000

00.0. .0000- u @000
00.x. .0000 . 0.0.00
0020 .35. n .0000

00.x. .000. - n .0000

00.x. .002- u 650
000.-.

00.0 3.0
00.0 m . .0
3.0 0.0.0.
00.0 0.0
00.0 3.0
3.00m. 302$
>0n. Em 000.).
00.0.0030

m0.
m0.
.00
00..
00..

0. mg.

>0Q Em

0.0.8.0

0N0.
w . .0.
0. .0
000.
3.0.
.NNON00
0000.).

08.000.00.00m 00000..

08.000.00.08 E00...
0000000008000.
00.3000 00000..
.0030

000.000.580.000

b.0530

COEMBGSEEOU

 

0030.00.» 0000:0000 :0 0003000. 000.000.00.00 .3 030,—.

140

0080000000.

0. 0 0:0 000.000.00.000... 0. . “00000 xEEsn. 0
00303":

0.0005000 .0> .030.>HNQ ”00000 xEEsn. 0
0000808

".0 0.0000008 .0> 00008..00H.Q ”00000 >EE=Q 0
00.x... V0... 0803 00.2

0000.00.00.00.

0. 0 0:0 000.000.00.000... 0. . ”00000 >EEan. 0
0030.5":

0.0005000 .0> .030.>HNQ “00000 AEER. 0
000002.00

”.0 0.0000008 .0> 00.000..00H.Q ”00000 zEEDQ 0
0.0.x... ..V0. ”8080 00-2

 

 

 

 

 

000. magma.
000. 00.. main. m
00..- u .80 0.00 0200008..
:02..- 0 .80 0008000 880
1.0:. 000.- a :8 003250 8000 0
3.0.0..- . 0.00:0 EEo0 x 0..
0000. .0090 EEoU x .030 EEoU
:2... 0.0080 00000..
02.0. .0035 00000005500
SLNN. 00.0 00.0.0030 000.500.000.200 .
00.4 0.0m. 0.000
00000000000000.
0.0.0.0030. 00.00.00: .8.. 000.000.0000. .3 0.0.0...
.000 . mama.
0:..Nw0. 0.00090 MONK. m
0. .0 0 GD. 0.05 02000000..
03.0. 0 Ame 00:00:05 E00 ...
0N0. 000.0 0 Se 0030=bm E00 ... N
00.. 0.. x .0000 5:000
30.. 00.8050 0008..
2.0:. :03. 0030 808035080 .
00.0 0.0m. 0.80
000080000.

 

0.0.00.0. 00.00.00: 00. 03.000003. .3 0.00...

141

.080000808

0. 0 0:0 300008030808 0. . ”00000 >885 0
003.3":

0.008.000. .m> .08..>HNQ ”00000 >883. a
38000.30 ".0

0.008.000. .m> 00.000..00u.n. ”00000 >85 0
nova: ..v... .253 fiuz

.080000080...

0. 0 0:0 3800080888. 0. . ”00000 >85 0
_ 002E":

0.00.5000. .m> .08..>HNA. ”00000 >88:Q 0
6308...; u:

0.009.000. .m> 00.000:00H.Q ”00000 >85 0
8%.: ..v..... .208. swuz

 

NNO. mama.

 

 

 

80. 8...- 850 m
2.... o .8. 0.0m 0.5508.
0N0; a and 0.8.0.5m 800...
.8. a. ..- a .5. 23250 page N
.50.- .530 5&8 x 0.
:20. .530 855 a .80 885
:30. £8.50 508..
3.... 0:30 808.5888
:80 E..- 00:80 8.5.9.858 .
02 0.0m. 08m
806003.05 800...
80.0800. 0030.002 .8.. 00.000003. .3 0.00...
03.... «.98
:08. :02... Bx... m
t. .3.... .o .20 2% 0.5.008.
1%.... a .08 23030. 58.0
:8... .2. .o. a :8 83250 585 N
.I an. :02. 0:30 808.8868 .
My? 0.0m. 08m

 

00.80.33 800...

0.08.... 00.00.00: .0. 80.3050“ SN 0.00...

142

3:283:08

m. 0 0:0 3500.80.80: m. . ”00000 >85 0
208:3":

0.0000000. .m> .08....»HNQ ”00000 >882. ..
€308.30

”.0 0.0000000. .m> 00.000..00u.n. ”00000 >883. 0
81...... ..v... 088. mwnz

.0:0000m:0.:

m. 0 0:0 .0:0.:0::0.m:.8 0.. . ”00000 >82. 0
003.3":

0.009.000. .m> .08..>HNQ ”00000 >88 0
A00.000..00

n: 0.008.000: .m> 00.000..00u.n. ”00000 >83. 0
3%.: 0v... 088. «wuz

 

 

 

 

 

as... 80.0:
8... 08... 8...: m
80... u .8. 0.00 020008..
0.0.0. 0 Ge 0.8035 800 H
:03. £20.- a :8 23250 ESP N
:00... 0.. x .30 5800
:8... 0.8.80 008..
:08. i. . 00. 0.85 808.0050“. .
”:4 0.0m. 00%
8.000.058 00000.
3.0.0800. 5.8.002 .8.. 8.000091 .0m 0.00...
.00.... 80.8
:08. N. .0 8...: m
30.0. 0 Ana 0.>.m 00.80000.
30.0 .. .08 00308.0. 8005
to. 00...... a :8 05.8% 0.000 N
8..- 0.. x .000 .850
:00... 0.8.80 508..
:20. :08. 0:05 808.5558 .
N08 0.5 080
flcguhmmuum hofiaofl

 

A0385 8.00.003. .8.. 5.000000... .3 0.00...

143

3:288:08 m. 0 0:0 380088.80: m. . ”00000 >88=Q 0

 

mo.VQ** 3V0...
3... 08.0. 0.8. :83. a .8. 0.00 0.5.008. N
08... R0... 0.. x .000 8:80
«$0 .000 b.3880 00000..
:2... ~30 3.00m. 1.0000 >03:0 5000808800 .
0:: 30: NM: 0.0m. 00%
.mwu:.x0.:800 cuwué 0.08m
flcgahmmufiw Each.

 

 

80.30.0600 8000. 8.00.005. :0. 8.000003. .Nm 030...

35000080.: 0. 0 0:0 3802:0358 m. . ”00000 >883. 0

 

Eva: 0v... 0&8. 00"..

8... 3...? 2... R... a :8 0.00 023008.. N
08... 02... 0.. x .000 5&8
:5... 3...... 0:280 .008.

1.8.. E... :0. .. :20... 0.30 803.5858 .

0.... 80m. 0.»... 0.0.. :05
0.0.0800 0.085
evades—Lehma—

 

 

A00:08..0....0... 5.00.005. .8.. 8.000..»3. ..m 0.00...

144

35.—800:0: m. 9 6:0 3:032:83”: 0. ~ 60:00 3:55 0

 

 

nova—.1. 3V9...
8... 8... 2.... 00...? a .5. 2.5 0.3.523 0
1.3.»: 2...... 0.. x 3:0 5:80
:80. .30.... £280 .38..
1.0%. :30. it... :80... E000 03.8.8855 .
“.2 0.0m my... sum 3%
AmeEonEOU Avwnfi £95m
Hogahmmuam .36on

 

3330330.. .8600: :33ng :8 5.08:?“ .nm 030,—.

145

Appendix A MEASUREMENT INSTRUMENTS

PRE-TRAINING SURVEY:

Team Name
DM#
ID#

 

 

 

Demographic Information

Age:
GPA:

 

 

Gender
Male
Female

Ethnicity
White / Caucasian
O African-American
0 Hispanic / Latin-American
0 Asian/ Pacific Islander
0 Arab/ Middle-Eastem
O Other
0 Prefer not to answer

 

General Computer Self-efficacy

Often in our jobs we are told about software packages that are available to make
work easier. For the following questions, imagine that you were given a new
software package for some aspect of your work. It doesn’t matter specifically
what this software package does, only that it is intended to make yourjob easier
and that you have never used it before.

The following questions ask you to indicate whether you could use this unfamiliar
software package under a variety of conditions. For each of the conditions,
please rate your confidence about your first judgment, where 1 indicates “Not at
all confident,” 3 indicates “moderately confident,” and 5 indicates “totally
confident”

 

 

...if there was no one around to tell 0 O O O 0
me what to do as I go

 

 

 

 

 

 

 

 

146

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

...if I had never used a package

like it before 0 O O O 0
...if I had only the software

manuals for reference 0 O O O 0
...if I had seen someone else using

it before trying it myself 0 O O O 0
...if I could call someone for help if

lgot stuck O O O O 0
...if someone else had helped me

get started 0 O O O 0
...if I had a lot of time to complete

the job for which the software was O O O O O
provided :

...if I had just the built-in help

facility for assistance 0 O O O 0
...if someone showed me how to

do it first 0 O O O O
...ifl had used similar packages .
before this one to do the same job 0 O O O O

 

 

Computer Affect

For each of the condition, please rate your confidence about your first judgment,
where 1 indicates “Not at all confident,” 3 indicates “moderately confident,” and 5
indicates “totally confident.”

 

 

 

 

 

 

 

 

 

 

 

1 2 3 4 5
I like working with computers O O O O O
I look forward to those aspects of
my job that require me to use a O O O O O
computer
Once I start working on the
computer, I find it hard to stop 0 O O O 0
Using a computer is frustrating for O O O O O
me
I get bored quickly when working on O O O O O
a computer

 

 

 

How skilled are you in using computers?

0 Unskilled
O Low Skill
O Somewhat Skilled
O Moderately Skilled

147

0 Very Skilled

How skilled are you in using a mouse?
O Unskilled
O Low Skill
O Somewhat Skilled
O Moderately Skilled
O Very Skilled

How often do you play video games?
0 Rarely
O Occasionally
0 Sometimes
O Fairly Often
0 Very Often

Have you ever played 000 before?

O Yes
O No

NE O-FFI

This section contains 60 statements. Read each statement carefully. For each

statement, choose the option that best represents your opinion.

 

Strongly
Diggree

Disagree

Neutral

Agree

Strongly
Agree

 

I am not a worrier. O

O

O

O

O

 

I like to have a lot of people
around me.

 

I don't like to waste my time
daydreaming.

 

I try to be courteous to
eveflone I meet.

 

I keep my belongings clean and
neat

 

I often feel inferior to others.

 

I laugh easily.

 

Once I find the right way to do
somethinil stick to it.

 

I often get into arguments with
my family and co-workers.

00000000

00000000

00000000

00000000

00000000

 

I'm pretty good about pacing
myself so as to get things done
on time.

0

O

O

O

O

 

When I'm under a great deal of O
stress, sometimes I feel like I'm

 

 

 

 

 

 

 

148

 

 

going to pieces.

 

I don't consider myself
especially "light-hearted."

 

I am intrigued by the patterns I
find in art and nature.

 

Some people think I'm selfish
and egotistical.

 

I am not a very methodical
person.

 

I rarely feel lonely and blue.

 

I really enjoy talking to people.

 

I believe letting students hear
controversial speakers can only
confuse and mislead them.

OOOOOOO

OOOOOOO

OOOOOOO

OOOOOOO

OOOOOOO

 

I would rather cooperate with
others than compete with them.

 

I try to perform all the tasks
assigned to me conscientiously.

 

I often feel tense and jittery.

 

I like to be where the action is.

 

Poetry has little or no effect on
me.

 

I tend to be cynical and
skeptical of others' intentions.

O 0000 O

O 0000 O

O 0000 O

O 0000 O

O 0000 O

 

I have a clear set of goals and
work toward them in an orderly
fashion.

0

O

O

O

O

 

Sometimes I feel completely
worthless.

O

O

O

O

O

 

I usually prefer to do things
alone.

 

I often try new and foreign
foods.

 

I believe that most people will
take advantage of you if you let
them. ,

 

I waste a lot of time before
settling down to work.

 

I rarely feel fearful or anxious.

 

I often feel as if I'm bursting with
energy.

 

I seldom notice the moods or
feelings that different
environments produce.

 

Most people I know like me.

 

 

I work hard to accomplish my

 

OO

 

OO

 

OO

 

OO

 

OO

 

149

 

 

oals.

 

I often get angry at the way
people treat me.

 

I am a cheerful, high-spirited
person.

 

I believe we should look to our
religious authorities for
decisions on moral issues.

 

Some people think of me as
cold and calculatigng.

 

When I make a commitment, I
can always be counted on to
follow throggh.

 

Too often, when things go
wrong, I get discouraged and
feel like giving up.

 

I am not a cheerful optimist.

 

Sometimes when I am reading
poetry or looking at a work of
art, I feel a chill or wave of
excitement.

 

I'm hard-headed and tough-
minded in my attitudes.

 

Sometimes I'm not as
dependable or reliable as I
should be.

 

I am seldom sad or depressed.

 

My life is fast-paced.

00

00

OO

00

OO

 

 

I have little interest in
speculating on the nature of the
universe or the human
condition.

 

I generally try to be thoughtful
and considerate.

O

O

 

I am a productive person who
always gets the job done.

0

O

O

O

 

I often feel helpless and want
someone else to solve my
roblems.

 

I am a very active person.

 

I have a lot of intellectual
curiosi’g.

 

If I don't like people, I let them
know it.

 

I never seem to be able to get
organized.

 

OOOOO

 

OOOOO

 

OOOOO

 

OOOOO

 

OOOOO

 

150

 

 

At times I have been so
ashamed ljust wanted to hide.

 

I would rather go my own way
than be a leader of others.

 

 

 

I often enjoy playing with
theories or abstract ideas.

 

If necessary, I am willing to
manipulate people to get what I
want.

 

I strive for excellence in
everythingl do.

 

 

 

 

 

 

 

MLQ

This section contains 51 statements. Read each statement carefully. For each
statement, choose the option that best represents your opinion of yourself.

 

Not at all

Once in a
while

Sometimes

Fairly
often

Frequently,
if not
always

 

I provide others with assistance
in exchange for their effort

0

O

O

O

O

 

I re-examine critical assumptions
to question whether they are
appropriate .

O

O

O

O

O

 

I fail to interfere until problems
become serious

 

I focus attention on irregularities,
mistakes, exceptions, and
deviations from standards

0

O

O

O

O

 

I avoid getting involved when
important issues arise

 

I talk about my most important
values and beliefs

 

I am absent when needed

 

I seek differing perspectives
when solving problems

 

I talk optimistically about the
future

 

I stay informed of mistakes,
complaints, and failures

 

l instill pride in others for being
associated with me

OOOOOOO

OOOOOOO

OOOOOOO

OOOOOOO

OOOOOOO

 

I discuss in specific terms who is
responsible for achieving
erformance targets

0

O

O

 

 

O

 

O

 

 

 

O

 

 

I wait for things to go wronL

151

 

 

 

before takingaction

 

I explain what incentives can be
expect in exchange for effort

 

I talk enthusiastically about what
needs to be accomplished

 

l specify the importance of
having a strong sense of
purpose

 

I spend time teaching and
coaching

 

I make clear what one can
expect to receive when
performance goals are achieved

0

O

O

O

O

 

I draw attention to missed
opportunities

 

I show that I am a firm believer in
“If it ain't broke, don’t fix it.”

 

I go beyond self-interest for the
cod of the group

 

I treat others as individuals rather
than just as a member of a group

0000

0000

0000

0000

0000

 

I make clear what economic
rewards one can expect to
receive when performance goals
are achieved

0

O

O

O

O

 

l demonstrate that problems
must become chronic before I
take action

 

I act in ways that built others’
respect for me

 

 

I focus my followers when they
didn't meet standards

0

O

O

O

 

| concentrate my full attention on
dealing with mistakes,
complaints, and failures

0

O

O

O

O

 

I consider the moral and ethical
consequence of decisions

 

I keep track of all mistakes

 

I display a sense of power and
confidence

 

l articulate a compelling vision of
the future '

 

I directe my attention toward
failures to meet standards

 

I do not act until problems
needed attention

 

OOOOOO

 

OOOOOO

 

OOOOOO

 

OOOOOO

 

OOOOOO

 

152

 

 

I avoid making decisions

0

O

O

 

I consider an individual as having
different needs, abilities, and
aspiration from others

0

O

O

O

 

I get others to look at problems
from manydifferent angles

 

I help others to develop their
strengths

 

I suggest new ways of looking at
how to complete assignments

 

l delay responding to urgent
questions

0000

0000

0000

0000

0000

 

I emphasize the importance of
having a collective sense of
mission

0

O

O

O

O

 

I express satisfaction when
others meet expectations

 

I express confidence that goals
will be achieved

 

I am effective in meeting others’
'ob-related needs

 

I use methods of leadership that
are satisfying

 

I get others to do more than they
expected to do

 

I am effective in representing
others to higher authority

 

I work with others in a
satisfactory way

 

I heighten others’ desire to
succeed

 

I am effective in meeting
organizational requirements

 

I increase others’ willingness to
try harder

 

I lead a group that is effective

 

OOOOOOOOOOO

 

OOOOOOOOOOO

 

OOOOOOOOOOO

 

OOOOOOOOOOO

 

OOOOOOOOOOO

 

 

153

 

Current Mood Questionnaire

This scale has several statements that can describe someone's mood. Please
respond to each statement by indicating how much the statement describes how
you are feeling right now.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Describes D . Describes . Describes
escribes Descnbes
me not at me a little me me well me very
all moderately well

I'm full of energy and tension. 0 O O O 0
I'm keyed up. 0 O O O O
I am stirred up. 0 O O O 0
I'm feeling placid, low in energy. 0 O O O 0
My internal engine is mnning
slow and smoothly. O O O O 0
My body is in a quiet, still state. O O O O 0
My mind and body are resting, O O O O 0
near sleep.
PANAS

Like the previous scale, this one also asks about how you are feeling right now.
Please Indicate to what extent you are feeling each of these emotions right now.

 

Very slightly or
not at all

A little

Moderately

Quite a bit

Very much

 

Interested

 

Distressed

 

Excited

 

Upset

 

Strong

 

Guilty

 

Scared

 

Hostile

 

Enthusiastic

 

Proud

 

Irritable

 

Alert

 

Ashamed

 

Inspired

 

Nervous

 

Determined

 

Attentive

 

 

Jittery

 

OOOOOOOOOOOOOOOOOO

 

 

OOOOOOOOOOOOOOOOOO

OOOOOOOOOOOOOOOOOO

 

OOOOOOOOOOOOOOOOOO

 

OOOOOOOOOOOOOOOOOO

 

154

 

 

 

Active

 

Afraid

 

Sleepy

 

Still

 

Quiet

 

 

Emotionally
aroused

 

0 00000

 

0 00000

 

0 00000

 

0 00000

 

0 00000

 

155

 

Leader DOSt game 2 survey:

This is the survey taken by the leader after game 2. The only difference between the post
game 1 and post game 2 leader surveys is that the second included the MLQ and exit
questions related to their satisfaction with the experiment itself.

Team Name
DM#
ID#

 

 

 

Current Mood Questionnaire

This scale has several statements that can describe someone's mood. Please
respond to each statement by indicating how much the statement describes
how you felt during the game.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Describes . Describes . Describes
me not at 3965215383 me 03:35:38 me VBW
all moderately well
I m full of energy and O O O O o
tensron.
I'm keyed up. 0 O O O O
I am stirred up. 0 O O O O
l m feeling placrd, low In O O O Q 0
energy.
My Internal engine IS O O O O 0
running slow and smoothly.
My body rs In a quiet, still 0 O O O 0
state.
My mind and body are O O O Q o
resttninear sleep.
PANAS

Like the previous scale, this one also asks about your feelings. Please
Indicate to what extent you felt these emotions during the game.

 

 

 

 

 

Very slightly A little Moderately Quite a bit Very much
or not at all
Interested O O O O O
Distressed O O O O O
Excited O O O O O
Upset O O O O O

 

 

 

 

 

 

 

 

156

 

Strong

 

Guilty

 

Sca red

 

Hostile

 

Enthusiastic

 

Proud

 

Irritable

 

Alert

 

Ashamed

 

Inspired

 

Nervous

 

Determined

 

Attentive

 

JitterL

 

Active

 

Afraid

 

Sleepy

 

Still

 

Quiet

 

O OOOOOOOOOOOOOOOOOOO

Emotionally
aroused

 

 

 

O OOOOOOOOOOOOOOOOOOO

O OOOOOOOOOOOOOOOOOOO

 

 

O OOOOOOOOOOOOOOOOOOO

 

O OOOOOOOOOOOOOOOOOOO

 

MLQ (Leader self-report)

This section contains 51 statements. Read each statement carefully. For each
statement, choose the option that best represents your opinion of yourself.

 

 

 

 

 

 

 

 

 

 

 

 

 

Not at all OWN a Sometimes Fairly often Freiqugtttly,
rle
always
I provided others with
assistance in exchange for O O O O O
their effort
I re-examined critical
assumptions to question O O O O O
whether they were
appropriate
I failed to interfere until 0 O O O 0
problems became senous
I focused attention on
irregularities, mistakes, O O O O O
exceptions, and deviations
from standards
I avoided getting involved O
when important issues arose
I talked about my most
important values and beliefs 0 O O

 

157

 

 

 

 

I was absent when needed

 

I sought differing perspectives
when solving problems

 

I talked optimistically about
the future

 

I stayed informed of mistakes,
complaints, and failures

 

I instilled pride in others for
being associated with me

00000

00000

00000

00000

00000

 

I discussed in specific terms
who is responsible for
achieving performance

Mgas

O

O

O

O

O

 

I waited for things to go
wrong before takigq action

 

I explained what incentives
can be expect in exchange
for effort .

 

I talked enthusiastically about
what needs to be
accomplished

 

I specified the importance of
having a strong sense of

purpose

 

I spent time teaching and
coaching

 

I made clear what one can
expect to receive when
performance goals are
achieved

 

I drew attention to missed
opportunities

 

I showed that I am a firm
believer in “If it ain’t broke,
don’t fix it.”

 

I went beyond self-interest for
the god of the group

 

I treated others as individuals
rather than just as a member
of group

 

I make clear what economic

rewards one can expect to

receive when performance
oals are achieved

 

I demonstrated that problems
must become chronic before I

 

 

 

 

 

 

 

158

 

 

take action

 

I acted in ways that built
others’ respect for me

 

I focused my followers when
they didn't meet standards

 

I concentrated my full
attention on dealing with
mistakes, complaints, and
failures

0

 

I considered the moral and
ethical consequence of
decisions

 

I kept track of all mistakes

 

I displayed a sense of power
and confidence

 

I articulated a compelling
vision of the future

 

I directed my attention toward
failures to meet standards

 

I did not act until problems
needed attention

 

I avoided making decisions

OOOOOOO

OOOOOOO

OOOOOOO

OOOOOOO

OOOOOOO

 

I consider an individual as
having different needs,
abilities, and aspiration from
others -

O

O

O

O

O

 

I get others to look at
problems from many different
angles

 

I helped others to develop
their strengths

 

I suggested new ways of
looking at how to complete
assignments

 

I delayed responding to
urgent questions

 

 

I emphasized the importance
of having a collective sense
of mission

0

O

O

O

O

 

I expressed satisfaction when
others met expectations

 

I expressed confidence that
goals would be achieved

 

I was effective in meeting
others’ job-related needs

OOOO

 

I used methods of leadership

 

OOOO

 

OOOO

 

OOOO

 

OOOO

 

 

159

 

 

that were satisfyigg

 

I get others to do more than
they expected to do

 

l was effective in representing
others to higher authority

 

I worked with others in a
satisfactory way

 

l heightened others’ desire to
succeed

 

I was effective in meeting
organizational requirements

 

I increased others’ willingness
to try harder

 

I lead a group that was
effective

 

 

OOOOOOO

 

OOOOOOO

 

OOOOOOO

 

OOOOOOO

 

OOOOOOO

 

Task Complexity

Read each statement carefully. For each statement, choose the option that
best represents your opinion of the last game you played

 

Strongly
Disam

Disagree

Neutral

Agree

Strongly
Agree

 

I found this to be a complex game

0

O

O

O

O

 

I pefon'ned a high number of
actions while playing this game

 

During the game, I had to
coordinate my actions with others

 

It was difficult to learn the power of
all the targets

 

This game was mentally
demanding

 

This game required a lot of thought
and problem-solving

 

There were a large number of
information cues in this game

 

Sequencing my actions with others
was important in thiigame

 

The targets were unpredictable in
this game

 

I found this to be a challenging
ggme

 

 

000000000

000000000

 

 

OOOOOOOOO

 

OOOOOOOOO

 

OOOOOOOOO

 

Communication Quality

160

 

 

Communication Competence

Read each statement carefully. For each statement, choose the option that
best represents your opinion of your team.

 

Strongly
Disagree

Disagree

Neutral

Agree

Strongly
Agree

 

My teammates have a good
command of the language

0

O

O

O

 

My teammates are sensitive to
others' needs of the moment

 

My teammates typically get right to
the point

 

My teammates pay attention to
what other people say to them

 

My teammates deal with others
effectively

 

M teammates are good listeners

 

My teammates are difficult to
understand when they
communicate

000000

000000

000000

000000

0000000

 

My teammates express their ideas
clearly

 

My teammates are difficult to
understand when they speak

 

My teammates generally state the
Light thing at the right time

 

My teammates are easy to dialog
with

 

My teammates usually respond
quickly

 

 

00000

00000

 

 

OOOOO

 

OOOOO

 

OOOOO

 

 

Task Clarity

Read each statement carefully. For each statement, choose the option that

best represents your opinion.

 

 

 

 

 

 

was to be done

 

 

 

 

32233;); Disagree Neutral Agree 8:33:er
{aksnkew exactly what to do on this O O O O Q
I was not very sure how to O O O O 0
complete the task
I knew how I was supposed to O O O O 0
complete the task
I was not clear about how the task O O O Q Q

 

 

 

161

Information timeliness, accuracy, and usefulness
Read each statement carefully. For each statement, choose the option that

best represents your opinion.

 

Strongly
Diggree

Disagree

Neutral

Agree

Strongly
Agree

 

|_got information when I need it

 

I could rely on the information

 

I could use the information

 

too early

The information was not too late or

 

The information was generally
correct

 

 

The information was useful

 

CO 0000

 

00 0000

 

00 0000

 

00 0000

 

00 0000

 

Satisfaction

Satisfaction with Team

Read each statement carefully. For each statement, choose the option that
best represents your opinion of your team.

 

 

 

 

 

 

 

 

 

parts of working on this team

 

 

 

 

 

gigging Disagree Neutral Agree 8::ng
There is a lot of
unpleasantness among O O O O O
members of this team
The longer we work together 0 O O O O
as a team the less well we do
Working together energizes
and uplifts members of our . O O O O O
team
Every time someone attempts
to correct a team member
whose behavior is not 0 O O O O
acceptable things seem to get
worse rather than better
My relations with other team O O O
members are strained
I very much enjoy working with O O O
my teammates
The chance to get to know my
teammates is one of the best 0 O O O O

 

DDD Knowledge

162

 

 

If you had unknown targets in your last game, please anwser the following
question as best as you can. If you did not have unknown targets in your last
game, please just click on any answer and hit ”Submit".

Based on your own knowledge, please indicate the power levels of the
different U-targets:

 

 

 

 

 

A0 A1 A3 A5
UX O O O O
U+ O O O O
U- O O O O
U# 0 O O O

 

 

 

 

 

 

 

1. If the target moves diagonally across the screen without stopping, which of
the following targets is most potentially damaging to your defensive score?

O G1

O A3

O Enemy U target

0 All of the above are equally damaging

2. If the target moves diagonally across the screen without stopping, which of
the following targets is least potentially damaging to your defensive score?

O G3

O A5

O G1

O All of the above are equally damaging

3. Which of these vehicles is most important to launch before your team
needs it to attack a target?

0 Tank

0 AWACS

0 Jet

O Helicopter

4. If you want to figure out the power level of a U target, which vehicle should
your team attack it with first?

O Tank

O AWACS

O Jet

O Helicopter

5. Which team member(s) have the capability of successfully attacking A5
targets? (check all that apply)

Cl DM1

III DM2

163

Cl DM3
CI DM4

6. Which team member(s) have the capability of successfully attacking 63
targets? (check all that apply)

CI DM1

CI DM2

El DM3

Cl DM4

7. Which team member(s) have the capability of successfully attacking A1
targets? (check all that apply)

III DM1

CI DMZ

CI DM3

D DM4

Satisfaction with Experiment

Read each statement carefully. For each statement, choose the option that
best represents your opinion of your leader.

 

 

 

 

 

3:35;: Disagree Neutral Agree 8:235?

This Teamlab experience O O O O O
was well-organized.
The Teamlab researcher
who provrded the training O O O O O
was professronal In hrs/her
behavior.
The Teamlab researcher
who provrded the training O O O O O
was courteous to the

articipants.
Overall, I was satisfied with
my experience in the O O O O O
Teamlab today.

 

 

 

 

 

 

 

164

 

Team postggame 2 survey:

This is the survey taken by the team member after game 2. The only difference between
the post game 1 and post game 2 leader surveys is that the second included the MLQ and
exit questions related to their satisfaction with the experiment itself.

Team Name

 

DM#

 

ID#

 

Current Mood Questionnaire
This scale has several statements that can describe someone's mood. Please
respond to each statement by indicating how much the statement describes

how you felt during the game.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

31838:??? Describes Desrc‘reibes Describes 0:25:65
all me a little moderately me well wellry
l m full of energy and O O O O O
tensron.
I'm keyed up. O O O O O
I am stirred up. 0 . O O O O
l m feeling placrd, low In 0 O O O O
energy. ~
My Internal engine IS O O O O O
runnigq slow and smoothly.
My body rs in a quret, still O O O O O
state.
My mind and body are O O O O O
resting, near sleep.
PANAS
Like the previous scale, this one also asks about your feelings. Please
Indicate to what extent you felt these emotions during the game.
$207.33.!) A little Moderately Quite a bit Very much
Interested O O O O O
Distressed O O O O O
Excited O O O O O
Upset O O O O O
Strong O O O O 0
Guilty O O O O O

 

 

 

 

 

 

 

165

 

 

 

Sca red

 

Hostile

 

Enthusiastic

 

Proud

 

Irritable

 

Alert

 

Ashamed

 

Inspired

 

Nervous

 

Determined

 

Attentive

 

Jittery

 

Active

 

Afraid

 

Sleepy

 

Still

 

Quiet

 

Emotionally
aroused

O OOOOOOOOOOOOOOOOO

 

 

 

O OOOOOOOOOOOOOOOOO

 

O OOOOOOOOOOOOOOOOO

 

O OOOOOOOOOOOOOOOOO

 

O OOOOOOOOOOOOOOOOO

 

Task Complexity

Read each statement carefully. For each statement, choose the option that
best represents your opinion of the last game you played

 

Strongly
Disagree

Disagree

Neutral

Agree

Strongly
Agree

 

I found this to be a complex game

0

O

O

O

O

 

I peforrned a high number of
actions while playing this game

 

During the game, I had to
coordinate my actions with others

 

It was difficult to Ieam the power of
all the targets

 

This game was mentally
demanding .

 

This game required a lot of thought
and problem-solving

 

There were a large number of
information cues in this game

 

Sequencing my actions with others
was important in thfigame

 

The targets were unpredictable in
this ggme

 

I found this to be a challenging
game

 

 

OOOOOOOOO

 

OOOOOOOOO

 

OOOOOOOOO

 

OOOOOOOOO

 

OOOOOOOOO

 

166

 

 

MLQ (team)

This section contains 51 statements. Read each statement carefully. For each
statement, choose the option that best represents your opinion of your leader.
Remember that all of your answers are 100% anonymous so please provide

your honest answer.

 

Not at all

Once in a
while

Sometimes

Fairly often

Frequently, if
not always

 

Provided me with
assistance in exchange
for my effort

0

O

O

O

O

 

Re—examined critical
assumptions to question
whether they were
appropriate

 

Failed to interfere until
problems become
senous

 

Focused attention on
irregularities, mistake,
exceptions, and
deviations from
standards

 

Avoided getting involved
when important issues
arose

 

Talked about their most
important values and
beliefs

 

Was absent when
needed

 

Sought differing
perspectives when
solving problems

 

Talked optimistically
about the future

 

Stayed informed of
mistakes, complaints,
and failures

 

Instilled pride in me for
being associated with
him/her

 

Discussed in specific
terms who was
responsible for achieving

 

 

 

 

 

 

 

167

 

 

erformance targgm

 

Waited for things to go
wrong before taking
action

 

Explained what
incentives I could expect
in exchange for my
efforts

 

Talked enthusiastically
about what needed to be
accomplished

 

Specified the importance
of having a strong sense
ofjurpose

 

Spent time teaching and
coaching

 

Made clear what one can
expect to receive when
performance goals were
achieved

 

Drew attention to missed
opportunities

 

Showed that he/she is a
firm believer in “If it ain’t
broke, don't fix it.”

 

Went beyond self-
interest for the good of
the group

 

Treated me as an
individual rather than just
as a member of a group

 

 

Made clear what
economic rewards one
can expect to receive
when performance goals
were achieved

 

Demonstrated that
problems must become
chronic before they take
action

 

Acted in ways that built
my respect

 

Focused me when I
didn't meet standards

 

Concentrated his/her full
attention on dealing with

 

 

 

168

 

 

 

 

 

mistakes, complaints,
and failures

 

Considered the moral
and ethical consequence
of decisions

 

Kept track of all mistakes

 

Displayed a sense of
ower and confidence

 

Articulated a compelling
vision of the future

0000

0000

0000

0000

0000

 

Directed my attention
toward failures to meet
standards

0

O

O

O

O

 

Did not act until
problems needed
aflenfion

 

Avoided making
decisions

 

Considered me as
having different needs,
abilities, and aspiration
from others

 

Got me to look at
problems from many
different angles

 

Helped me to develop
my strengths

 

Suggested new ways of
looking at how to
complete assignments

 

Delayed responding to
urgent questions

 

 

Emphasized the
importance of having a
collective sense of
mission

 

Expressed satisfaction
when I meet
expectations

 

Expressed confidence
that goals would be
achieved

 

Was effective in meeting
my job-related needs

 

Used methods of
leadership that are

 

 

 

 

 

 

169

 

 

satisfying

 

Got me to do more than I
expected to do

 

Was effective in
representing others to O
gigher authority

 

Worked with me in a
satisfactory way

 

Heightens my desire to
succeed

 

Was effective in meeting
organizational . 0
requirements

 

Increased my willingness
to try harder

 

Led a group that was
effective

 

 

 

 

 

 

 

Task Complexity

Read each statement carefully. For each statement, choose the option that
best represents your opinion of the last game you played

 

Strongly
Disagree

Disagree

Neutral

Agree

Strongly
Agree

 

I found this to be a complex game

0

O

O

O

O

 

l peformed a high number of
actions while playing this game

 

During the game, I had to
coordinate my actions with others

 

It was difficult to learn the power of
all the targets

 

This game was mentally
demanding

 

This game required a lot of thought
and problem-solving

 

There were a large number of
information cues in this game

 

Sequencing my actions with others
was important in this game

 

The targets were unpredictable in
this game

 

I found this to be a challenging
ggpne

 

 

OOOOOOOOO

 

OOOOOOOOO

 

OOOOOOOOO

 

OOOOOOOOO

 

OOOOOOOOO

 

170

 

 

Communication Quality

Communication Competence

Read each statement carefully. For each statement, choose the option that
best represents your opinion of your team.

 

Strongly
Disggree

Disagree

Neutral

i

Agree

Strongly
Agree

 

My teammates have a good
command of the language

0

O

O

O

O

 

My teammates are sensitive to
others’ needs of the moment

 

My teammates typically get right to
the point

 

My teammates pay attention to
what other people say to them

 

My teammates deal with others
effectively

 

My teammates are good listeners

 

My teammates are difficult to
understand when they
communicate

000000

000000

000000

000000

000000

 

My teammates express their ideas
clearly

 

My teammates are difficult to
understand when they speak

 

My teammates generally state the
right thing at the right time

 

My teammates are easy to dialog
with

 

 

My teammates usually respond
quickly

 

 

00000

00000

 

 

OOOOO

 

00000

00000

 

Task Clarity

Read each statement carefully. For each statement, choose the option that

best represents your opinion.

 

 

 

 

 

 

 

 

 

 

ggggel: Disagree Neutral Agree Signage”
{aksnkew exactly what to do on this O O O O O
I was not very sure how to O O O O O
complete the task
I knew how I was supposed to O O O O O

 

171

 

 

 

complete the task

 

I was not clear about how the task

 

 

was to be done

 

 

 

 

 

Information timeliness, accuracy, and usefulness
Read each statement carefully. For each statement, choose the option that

best represents your opinion.

 

 

 

 

 

 

 

 

 

 

 

 

 

3223?; Disagree Neutral Agree 8:33;”

l_got information when I need it 0 O O O O

I could rely on the information 0 O O O O

I could use the information 0 O O O O
The information was not too late or O O O O O
too early

The information was generally 0 O O O O
correct

The information was useful 0 O O O O

 

Leader Centrality

Read each statement carefully. For each statement, choose the option that

best represents your opinion.

 

 

 

 

 

 

 

leader

 

 

 

 

 

3:21;: Disagree Neutral Agree 8:21:81),

It is easy to ask my leader for help O O O O O

I communicate with my leader O O O O 0
My leader makes it difficult for me O O O O O
to do my job

My leader is "well connected" in O O O O O
our team

Everyone communicates with my 0 O O O O

 

Satisfaction

Satisfaction with Team

Read each statement carefully. For each statement, choose the option that
best represents your opinion of your team.

 

 

 

 

 

 

 

 

 

3:23;); Disagree Neutral Agree SXOrnegely
There is a lot of
unpleasantness among O O O O
members of this team
The longer we work together O O O O

 

172

 

 

 

 

 

as a team the less well we do

 

Working together energizes
and uplifts members of our
team

 

Every time someone attempts
to correct a team member
whose behavior is not
acceptable things seem to get
worse rather than better

 

My relations with other team
members are strained

 

I very much enjoy working with
my teammates

 

The chance to get to know my
teammates is one of the best
parts of working on this team

 

 

 

 

 

 

 

Satisfaction with Leader

Read each statement carefully. For each statement, choose the option that
best represents your opinion of your leader.

 

Very
Dissatisfied

Dissatisfied

Neutral

Satisfied

Very
Satisfied

 

The way my leader listens
when l have something
important to say

0

O

O

O

O

 

The way my leader sets clear
work goals

0

O

O

O

 

The way my leader treats me
when I make a mistake

 

My leader’s fairness in
appraising my job performance

 

The way my leader is
consistent in his/her behavior
toward subordinates

 

The way my leader helps me to
get the job done

 

The way my leader gives me
credit for my ideas

 

The way my leader gives me
clear instruction

 

The way my leader informs me
about work changes ahead of
time

 

The way my leader follows
through togggt problems

 

 

 

 

 

 

 

173

 

 

 

resolved

 

The way my leaders
understands the problems I O O O O O
might run into doing my job

 

The frequency with which I get

 

 

a pat on the back for doing a O O O O O
goodjob

The technical competence of

my leader 0 O O O O
The way my job responsibilities O O O O

 

 

 

 

 

 

are clearly defined

 

 

DDD Knowledge

If you had unknown targets in your last game, please answer the following
question as best as you can. If you did not have unknown targets in your last
game, please just click on any answer and hit "Submit".

Based on your own knowledge, please indicate the power levels of the
different U-targets:

 

 

 

 

 

A0 A1 A3 A5
UX O O O O
U-i- O O O O
U- 0 O O O
U# 0 O O O

 

 

 

 

 

 

 

1. If the target moves diagonally across the screen without stopping, which of
the following targets is most potentially damaging to your defensive score?

0 G1 .

O A3

0 Enemy U target

0 All of the above are equally damaging

2. If the target moves diagonally across the screen without stopping, which of
the following targets is least potentially damaging to your defensive score?

O G3

O A5

0 G1

O A" of the above are equally damaging

3. Which of these vehicles is most important to launch before your team
needs it to attack a target?

O Tank

O AWACS

O Jet

174

O Helicopter

4. If you want to figure out the power level of a U target, which vehicle should
your team attack it with first?

O Tank

0 AWACS

0 Jet

O Helicopter

5. Which team member(s) have the capability of successfully attacking A5
targets? (check all that apply)

Cl DM1

CI DM2

D DM3

CI DM4

6. Which team member(s) have the capability of successfully attacking G3
targets? (check all that apply)

El DM1

CI DM2

CI DM3

Cl DM4

7. Which team member(s) have the capability of successfully attacking A1
targets? (check all that apply)

Cl DM1

CI DM2

El DM3

El DM4

Satisfaction with Experiment
Read each statement carefully. For each statement, choose the option that
best represents your opinion of your leader.

 

 

 

 

 

 

 

 

 

 

 

1832:2252; Disagree Neutral Agree 8:235?
This Teamlab experience 0 O O O O
was well-organized.
The Teamlab researcher
who provrded the training O O O O O
was professronal in his/her
behavior.
The Teamlab researcher
who provrded the training O O O O O
was courteous to the
participants.
Overall, I was satisfied with O O O O O

 

175

 

 

 

my experience in the
Teamlab today.

 

 

 

176

 

 

 

 

Appendix B TRAINING MATERIAL

Transactional Leadership Statements

To the reader: Remember to read this statement a normal even voice.

fltement to be read at the beginning of the game

It is important that we try to get the highest score that we can in this exercise. We will do
this attacking as many enemy targets as possible without killing any friendly targets. We
will also be responsible for determining what the unknown targets are. Remember that
unknown targets are targets that, even after you identify them, you still don’t know what
they are. They’re the UX, U-, U+, and U#. They correspond to GO, G1, G3, and G5 (but
not necessarily in that order), so we’ll have to f1 gure out which is which in order to
perform well. However, these targets do not change power so once we figure out what
they are we can continue to use that information. There is scrap paper if you want to
write anything down.

In order to keep our motivation up it’s important for all of us to remember the reward
structure. If we are the highest performing team this semester we will win $300. If we
are the second highest performing team we will win $200 and if we are the third we will
get $100. Therefore, the better team score that we get the more money that we each
make. Does everyone understand this payout system? Please always remember that we
are playing for this cash prize.

Also, remember that we are getting course credit for our participation here today.
Therefore, it’s important that we try as hard as we can in this simulation.

[In the practice game each person had one type of vehicle]

I also want to make sure that each person is aware of their assignments. One of the
games we will play will be just like the training game. However, the other game is a
little different. Instead of everyone having one type of vehicle as they did in the practice
game, everyone will have 3 of the same type of vehicle. For example, DM1 will have 3
jets but no other vehicles. Jets have a power level of l but can move very fast and see a
fairly long distance. DMZ will be in charge of the tanks. Tanks have a power level of 5
but move very slowly and cannot see very far. DM3 will be in charge of helicopters.
Helicopters have a power level of 3, move quicker then tanks but slower then jets and can
see almost as far as a jet. It is important that everyone know their assignments. When
you open your launch window, then, you will only see one vehicle type at your base.
Make sure when you launch your vehicles that they say “Yes” in the aboard column. As
long as everyone understands their assignments, and works to keep our scores high I will
be satisfied.

My job as leader will be to focus on any actions which do not help us achieve our goals.

Once we all start to execute our strategy I do not plan to interfere until problems become
serious.

177

Now let’s talk a little about the strategy. First I want to make sure that we know how to
properly communicate the status of targets to each other. After you have identified a
target make sure that you communicate three pieces of information. First let everyone
know what target you are referring to. You can use the targets identification number to
do this. This number will always be between 200 and 399. Second, tell everyone what
type of target it is. In other words let them know if it is an a, g or u target and what
power it has. Third, tell them were it is. To do this, use the coordinates at the left and at
the top of the game playing area to direct your teammates. So a final communication
would state something like “number 200 is a GI and it is at .40 and .40.”

We are ready to start the game. When everyone pushes the start button, the game will
begin.

STOP

Statement you can gilor and use between g_ames

Currently, our score is [state amount]. It is important that we try to get the highest score
that we can in this exercise so we have the chance to get the most money. Remember
that we will do this attacking as many enemy targets as possible without killing any
fi‘iendly targets. Killing friendly targets takes is -25 offensive points so we need to avoid
doing this. I think I saw a few people doing this so let’s try to avoid that in the future.

[Mention anything else you saw that you didn ’t like during the game and would like to
see the followers do dzflerently]

178

Transformational Leadership Statement

T 0 the reader: Remember to read this statement using a captivating and dynamic voice.
Vary your loudness and pace.

Thank you for all being here today. I am very excited about this exercise and being your
leader here today. I think that our team has a real chance to play this game better than
anyone else has in the past. In order for us to do this I think it is important that we have a
vision. I think that our team vision should be that “we will all work together as a team in
order to achieve the highest possible score while enjoying the entire process” This means
that we will not only try to maximize our score on the game but that we will all have fun
doing it. It is my hope that we all enjoy this game.

COLLOCATED TEAMS ONLY: Before we go any farther, I thought that we would go
around the room and introduce ourselves. At a minimum, please say your name, degree,
and where you are from. Also, let’s write our names on the placards in front of us so we
don’t just have to keep refereeing to each other by number. [wait for everyone to finish]

VIRTUAL TEAMS ONLY: Before we go any farther, I thought that we introduce
ourselves. At a minimum, please say your name, degree, and where you are from.

REACHBACK TEAMS ONLY: Before we go any farther, I thought that we introduce
ourselves. At a minimum, please say your name, degree, and where you are from. Also,
please write your names on the placards in front of you so you can refer to each other by
name. [wait for everyone to finish]

Great, OK. . .I think that it’s also important that we have some specific team goals.
Having reviewed all the training material for this task I think that we should have four
different goals. First, I think that we should try to get the highest team offensive and
defensive team score as possible. This is the most visible measure of success to us and
the researchers. Second, it is important that we don’t shoot down any friendly targets.
Each time we shoot down one friendly it is minus 25 points which is like erasing the
gains we made by shooting down 5 enemy targets. Third, I think that we should avoid
inadvertently killing any friendly targets. Shooting these targets down is wrong and
should be avoided. Fourth and finally, I think that we need to learn what the unknown
targets are. I have been told that we will be tested on this after the game so we need to
try our best to learn their identity. Remember that unknown targets are targets that, even
after you identify them, you still don’t know what they are. They’re the UX, U-, U+, and
U#. They correspond to G0, G1, G3, and G5 (but not necessarily in that order), so we’ll
have to figure out which is which in order to perform well. However, these targets do not
change power so once we figure out what they are we can continue to use that
information. There is scrap paper if you want to write anything down.

[In the practice game each person had one type of vehicle]

179

I also want to let you know that one of the games will be playing today is a little different
than the practice game you just played. One of the games will be just like the training
game you just played but the other one is a little different. Instead of everyone having
one type of vehicle as they did in the practice game, everyone will have 3 of the same
type of vehicle. For example, DM1 will have 3 jets but no other vehicles. DMZ will be
in charge of the tanks. DM3 will be in charge of helicopters. When you open your
launch window, then, you will only see one vehicle type at your base. Make sure when
you launch your vehicles that they say “Yes” in the aboard column.

Also, I think that it is important that we all think of as many new ideas on how we can
improve our strategy during the game as possible. If at any time you think you have a
good suggestion or idea on how we can do things better, please don’t hesitate to let me
know. I think that we can all learn from each other.

I also want to let everyone know that if at any time you are having trouble with the game
please just ask me for help and I will do my best to answer your question. If I can’t
answer it, I’ll find someone in the lab that can.

Now let’s talk a little about the strategy. I think it is important that as a team we all
understand how to properly communicate the status of targets to each other. After you
have identified a target I think we should communicate three pieces of information to
each other. First, to make sure that we all know which target you are talking about please
use the targets identification number to reference it. This number will always be between
200 and 399. Second, let everyone know what type of target it is. In other words let
them know if it is an a, g or u target and what power it has. Third, tell them were it is.

To do this, I think it would be a good idea to use the coordinates at the left and at the top
of the game playing area to direct each other. So a final communication would state
something like “number 200 is a G1 and it is at .40 and .40.” Does anyone have any
ideas on how to do this better? [pause for response] OK, before we start the game is
does anyone else have any ideas on how we can improve our strategy? [listen and
consider commnets] ‘

I know some of you might be thinking that this task might be difficult, but I really think
that each of you can do well. I have been informed by the researchers that students like
us pick up this task pretty quickly and are able to score very high. I’m counting on you,
and I think you’ll do a super job. Just remember. We will succeed!! Good luckll

We are ready to start the game. When everyone pushes the start button, the game will
begin.

STOP

Statement you can tailor grid uge between the games
To the reader: Remember to read this statement using a captivating and dynamic
voice. Vary your loudness and pace.

180

You may also want to stand and walk around during this period

Potential comment you could use during these intermissions:

O

O
O
0

“So far I think that we are doing [insert your own words here] ”

“So far how does everyone think we are doing?”

“Does anyone think we can do anything better?”

“I really think we need to remember our vision. Remember our vision is to work
together as a team in order to achieve the highest possible score while enjoying
the entire process”

“Does anyone need any help?”

181

Transactional quiz

Below is a list of phrases. Please circle those phrases which describe a transactional
leader.

0 Displays a sense of power and confidence

0 Talks enthusiastically about what needs to be accomplished

o Specifies the importance of having a strong sense of purpose

0 Waits for things to go wrong before taking action

0 Re-examines the critical assumptions to question whether they are appropriate

0 Treats others as individuals rather than just as a member of a group

0 Concentrates their full attention on dealing with mistakes, complaints, and failures
0 Considers the moral and ethical consequence of decisions

- Helps others to develop their strengths

0 Keep track of all mistakes

0 Seeks differing perspectives when solving problems

0 Provide others with assistance in exchange for their effort

0 Talks optimistically about the fiiture

0 Makes clear what one can expect to receive when performance goals are achieved

0 Demonstrates that problems must become chronic before taking action

182

Transformational quiz

Below is a list of phrases. Please circle those phrases which describe a
transformational leader.

0 Displays a sense of power and confidence

0 Talks enthusiastically about what needs to be accomplished

0 Specifies the importance of having a strong sense of purpose

0 Waits for things to go wrong before taking action

- Re-examines the critical assumptions to question whether they are appropriate

0 Treats others as individuals rather than just as a member of a group

0 Concentrates their full attention on dealing with mistakes, complaints, and failures
0 Considers the moral and ethical consequence of decisions

0 Helps others to develop their strengths

0 Keep track of all mistakes

0 Seeks differing perspectives when solving problems

0 Provide others with assistance in exchange for their effort

0 Talks optimistically about the future

0 Makes clear what one can expect to receive when performance goals are achieved

0 Demonstrates that problems must become chronic before taking action

183

 

TRANSACTIONAL NOTES

Contingent Reward
0 General examples

0 A manager explaining to his sales force how much more money they could
make by having more sales

0 Discuss in specific terms who is responsible for achieving performance
targets

0 Express satisfaction when others meet expectations

0 Specific examples you can use in the simulation
0 Set criteria level using transactional leadership statement
0 Make it clear to each of your followers who is in charge of each action

Management-by-exception
0 General examples

0 Focus attention on irregularities, mistake, exceptions, and deviations from
standards
0 Direct attention toward failures to meet standards
0 Don’t interfere until problems become serious
0 Show that I am a firm believer in “If it ain’t broke, don’t fix it.”
0 Specific examples you can use in the simulation
0 Warn team if they are getting close to a specific level of performance
0 Read transactional leader statement

184

Identifying and Transferring
0 Identifying
1. Right click on the target and then choosing Identify. Now another window
will pop up. This window will appear every time you want to identify a
target.
2. You always do the same thing to identify a target using this window — first
click on “Fused” and then go down and click on “ok.”
«- Transferring
1. Right click on the target again and go down to “Transfer Info.”
2. Then click on “all linked DMs” in the next box that appears.

185

TRANSFORMATIONAL NOTES

Idealized influence
0 Specific examples you can use in the simulation
0 Speak with a captivating voice tone by:
' Varying the pace and loudness of speaking
I Pausing to emphasize points
0 Repeatedly emphasize purpose
0 Consider the moral and ethical consequence of decisions

Inspirational Motivation
0 Specific examples you can use in the simulation

0 Articulate a compelling vision of the future

0 Have a powerful, confident, and dynamic interaction style by:

0 Shaking hands, alternating between sitting and walking between
participants, making eye contact, using hand gestures for emphasis while
speaking, displaying animated facial expressions

0 Express confidence that goals will be achieved

Intellectual Stimulation
0 General examples
0 I get others to look at problems from many different angles
0 I suggest new ways of looking at how to complete assignments
0 Specific examples you can use in the simulation
0 Ask teammates for suggestions
0 Ask teammates to look for new ways of doing their job
0 Update strategy as necessary

Individual Consideration
0 Specific examples you can use in the simulation
0 Recognize individual accomplishments
Providing individual support
Spend time teaching and coaching
Consider an individual as having different needs, abilities, and aspiration
from others

000

186

Identifying and Transferring
0 Identifying
3. Right click on the target and then choosing Identify. Now another window
will pop up. This window will appear every time you want to identify a
target.
4. You always do the same thing to identify a target using this window — first
click on “Fused” and then go down and click on “ok.”
0 Transferring
3. Right click on the target again and go down to “Transfer Info.”
4. Then click on “all linked DMs” in the next box that appears.

187

Potential comments you can use in DDD

About half of the following comments relate to the leadership style you have jut been
trained on. To help you during the simulation you may now circle those comments which
you think relate to your leadership style and refer to them during the game.

“Remember the specific reward structure we discussed”

“We need to make sure we keep the purpose of the game in mind”
“Let’s try not to make so many mistakes.”

“Good job meeting expectations.”

“Does anyone need help?”

“Do we need to update our strategy?”

“Is there anything I can do for you” (communicated to one person only)
“Are we using the right strategy?”

“I really like our chances of succeeding”

“Does anyone need some help with the game?”

“The harder you work the more money _I can give you”

“I we stay above or current performance level we will make more money”
“Remember your assignments”

“We are getting close to a specific level of performance”

“I really fell like we can achieve our goals”

“Does anyone have any suggestions on how we can do better?”
“Remember you can be rewarded with money for your effort”
“Let’s all try to make as much money as possible”

“Are there other ways we can do our job?”

“I think we can do better meeting our goals”

“Do we have any serious problems?”

“Let’s make sure we keep the mistakes to a minimum”

“Killing those friendly targets really hurts our score”

“Remember the purpose of the game”

“Try not to kill friendly target’s -- that would be wrong”

“That was a really great job!”

“Remember our vision to get that high score and have fim"

188

Transactional leadership training script

Slide #1: Introduction

Congratulations on your selection as team leader. As leader, it will be your job to
help your team achieve its maximum potential by facilitating their tasks using a
transactional leadership style. Since you play such an important role as the team leader
you will need to exhibit as many transactional leadership behaviors as possible. There
will be a short quiz following the training to ensure that you understand what behaviors
you need to exhibit.

You will be leading a team that is responsible for identifying and attacking enemy
targets in two 30 minute simulations. There are only a few functions on the computer
that you will need to perform in this simulation so you don’t need the in-depth, hands on
training that your team is currently receiving but you will be responsible for leading them
using a transactional leadership style which is what this presentation teaches how to do.
All the game functions which you need to know for the simulation will be taught to you
in this presentation.

Overview

You and your team will play two 30 minute simulations and answer several
questions after they are over. Throughout the game you should exhibit the same
leadership style. It cannot be overstressed that it is critical to the success of this
experiment that you only exhibit those leadership behaviors which you have been asked
to demonstrate. If you exhibit other types of leadership behavior it could negatively

impact the efficacy of this experiment.

189

To help remind you of what you learned in this presentation and increase your
chances of exhibiting the required leadership behaviors, you have been given notes of this
presentation that you can reference during the simulation. These behaviors are associated
with transactional leadership. Please feel free to refer to these sheets during the training
or write any notes on them. They are yours to keep and use during the simulation.

Also, some of the comments or behaviors that will be suggested to you might
seem somewhat foreign or unusual to say in front of a group of people you don’t know.
Just do your best to find a time to exhibit as many of the suggested behaviors as possible.
You don’t have to say all the comments or exhibit all the behaviors but try your best to
include as many as possible. Also, feel free to repeat as many comments or behaviors as
you would like. In fact, the more times you repeat something the better so long as you
don’t just dwell on one or two items.

Alright, let’s begin...

Slide #2: What is leadership?

Leadership is the process of influencing a team to achieve specific goals. There
are many different styles or conceptualizations of leadership but transactional leadership
is currently one of the most popular. Transactional leadership is reward and mistake
orientated. It has to do with the leader establishing specific levels of expected
performance that team members must meet and then monitoring whether or not those
levels have been achieved or not.

Slide #3: Transactional Leadership
Transactional leadership views the relationships betWeen leaders and followers as

an exchange process in which followers’ needs can be met if their performance is

190

adequate. Transactional leadership is based more on directing followers to initiate and
execute specific tasks rather then forming an emotional tie with them. It is based on
leaders setting a specific performance level and comparing follower output to that level.

Examples of this type of leadership include when a supervisor explains that higher
performers make more pay, when a coach tells the team which play to run and they are
rewarded by winning the game, or when a military General explains his strategy to his
troops and they are rewarded by winning the battle.

Transactional leadership has two dimensions: contingent reward and management
by exception

Let’s now watch a view video clip of a transactional leader at work.
Slide #4: Transactional Leadership

The following clip is from the movie Apollo 13 which was the third mission to
the moon. In April of 1970 Apollo 13 experienced a nearly catastrophic malfimction that
almost killed all three astronauts while they were on their way to the moon. If it wasn’t
for the heroic efforts of the crew and ground team they surly would have perished. The
ground team was lead by the flight director Gene Krantz who is played by Ed Harris in
the movie.
[First Apollo 13 clip]
Slide #5: Contingent reward

The first dimension of transactional leadership is contingent reward which refers
to an exchange process between leaders and followers. When leaders use this type of
leadership they try to obtain agreement from followers on what needs to be done and

what the payoffs will be for doing it. Therefore, contingent reward is simply rewarding

191

followers contingent on their performance. In other words, leaders reward high
performance more than low performance. Leaders provide tangible or intangible support
and resources to followers in exchange for their efforts and performance

General examples of contingent reward include a manager explaining to his sales
force how much more money they could make by making more sales. Leaders who
exhibit contingent reward also discuss in specific terms who is responsible for achieving
performance targets and express satisfaction when others meet expectations.

When playing the simulation, the biggest thing you will be able to do to increase
your perceived level of contingent reward is to set specific performance criteria for your
team. On the last page of the handout you have been given is a statement that you should
read to the entire team before you begin the game. The first part of this statement
provides details regarding the reward structure used in this game. For example, you will
inform your team that if they are the highest performing team this semester they will win
$300. If we are the second highest performing team they will win $200 and if we are
third they will get $100. It is important that throughout the simulation you remind your
team mates what the performance criteria are and tell them how they are doing compared
to them. Make certain that your teammates always remember that they are playing for a
cash prize

Another specific reward that you can remind your team of during the simulation is
that that they are getting course credit for their participation here today. Make sure that
everyone remembers that they are performing this game for credit. This information is

also contained in the leader statement so you don’t forget it.

192

A final specific behavior that you can use in the simulation to increase your level of
contingent reward is it to discuss who is responsible for achieving performance targets.
For example, you will want to make it very clear to each of your followers who is in
charge of what actions

It was clear in the previous movie clip that this is exactly the type of behavior
Gene Krantz was exhibiting. He first clearly set the success criteria and made sure that
everyone knew exactly what the penalty was if they did not achieve it.

Slide #6: Contingent reward clip

So now let’s watch another movie clip that exemplifies this type of behavior. The
following scene is from the movie Coach Carter. Samuel L. Jackson’s character of Ken
Carter has just become the coach of an underperforrning high school basketball team. In
order to motivate his players he has them sign contracts to keep their grades up. He is
very clear that if they live up to their end of the bargain they will succeed and win.
Unfortunately, the team breaks the agreement and he is forced to act.

[Coach carter video clip]

As in the previous Apollo 13 clip, we can see that Coach Carter clearly defines
what the expected level of performance is and what will occur if it is not met. After the
team fails to meet these criteria, Coach Carter does not allow the team to practice or play
despite their unprecedented perfect record and first place ranking in their conference.
However, once the team is exceeding the required level of performance he reinstates their
playing privileges.

Slide #7: Management by Exception

193

The second and last transactional dimension is management by exception.
Leaders with a high level of management by exception focus on events that are not
normal or expected to happen. This dimension has to do with setting standards,
monitoring deviations from these standards, and taking corrective action as necessary.
Examples of this include focusing attention on irregularities, mistakes, exceptions, and
deviations from standards. Leaders who have a high level of management by exception
direct their attention toward failures to meet standards and typically don’t interfere until
problems become serious. They could also be characterized as firm believers in the
phrase “If it ain’t broke, don’t fix it.”

Specific behaviors you can exhibit when leading your DDD team to make
yourself appear to have a higher level of management by exception is to warn the team
that they are close to dropping below a specific level of performance. For example if you
feel your team’s score is getting too low, make sure you warn them.

Also, be sure to read the entire leader statement before you begin the game. The
first part of this statement relates to the reward structure used in this game but the second
is directed towards ensuring that you appear to exhibit the highest level of management
by exception to your team.

Finally, don’t be afraid to bring mistakes to the attention of your teammates. For
example, if someone destroys a friendly target make sure you bring it to their attention
and tell them not to do that in the future. In fact, brining this to their attention is actually
a good thing. Many times people get so involved in the game they might not realize that

they have destroyed a friendly. If this happens, or if they do something else they should

194

not have, make sure you bring this to their attention. You don’t have to be mean about it,
just let them know what happened and ask nicely to not to it again.
Slide #8: Management by Exception clip

Let’s watch our last video clip which exemplifies management by exception. In
the following clip from Apollo 13 Gene Krantz is presented with a situation that was
previously not thought of. In this scene his team brings a deviation to a norm to his
attention and he tells them that they-needed to find a way to correct the problem.
[Second Apollo 13 video clip]
Slide #9: Your role in DDD

Even though we have covered numerous ways that you can appear to be a
transactional leader, there are a few more specific things that you can do to exhibit this
leadership style. First, read the introductory statement to your team using a normal and
even toned voice. In other words you will want to use the most normal sounding voice
possible. Avoid large changes in your pace or loudness

Second, you will want to make sure that your team develops strategies on how to
operate. As a leader you can decided how to do this but it is important that it gets done.

Third, you will be the only person on your team that can see the entire screen.
This allows you to direct the actions of others to specific threats even when they cannot
see them. For example, when targets appear outside of their detection rings you can warn
them that they are coming.

Finally, you will be given an opportunity between the games to summarize
everyone’s progress, talk about future strategies or make any other comments to the

group that you would like to. Please do your best to concentrate on only exhibiting

195

transactional behaviors during this period. During the first game, please make notes that
you can refer to during this time of things you would like to see the team do differently,
the same, or simply just better.
Slide #10: A short quiz

As promised you will now take a short quiz to ensure that you understand exactly
what type of behavior you should exhibit. In a moment, your trainer will hand you a
piece of paper with a list of phrases on it. Some of these phrases describe a transactional
leader and others do not. Simply circle those phrases that describe a transactional leader
and pass the sheet back to your trainer when you are done. Feel free to refer back to your
notes page. After you have finished that we will finish your training with a short
description of how DDD works.
Slide #11: Things you need to know about DDD - Starting

Even though you will not be required to operate any of the vehicles in the
simulation it is important for you. to understand how the game works.

The first thing you need to know is how to start it.
Slide #12: Things you need to know about DDD - Starting picture

When your team is ready to start the game make sure everyone, including
yourself, uses the mouse to left-click on the start button on the right hand side of the
screen in the report area. It should say refresh if you clicked correctly.
Slide #13: Things you need to know about DDD - Identifying/Transferring

The only other function you will need to know how to perform on the computer is
identifying and transferring the identity of targets to your teammates. Once the target

gets within the blue rings of your base you will be allowed to identify it as either a fi'iend

196

or foe and transfer the identity of that target to your teammates. While you can see all the
targets on the screen you will only be able to identify and transfer target identities while
the targets are inside the blue identification ring of your base.
Slide #14: Things you need to know about DDD - Identifying/Transferring - Picture

Identify targets by first right clicking on the target and then choosing Identify.
Now another window will pop up. This window will appear every time you want to
identify a target. You always do the same thing to identify a target using this window —
first click on “Fused” and then go down and click on “ok.” If you did it correctly the
diamond with a question mark it in will change to the type of target it is.

However, after you identify a target you still must transfer it to you teammates.
This allows them to know what type of target it is without needing to re-identify once it
gets within range of their base or one of their vehicles. To transfer the identity of a pre-
identified target, right click on the target again and go down to “Transfer Info.” Then
click on “all linked DMs” in the next box that appears. Remember that even though you
transferred the identity to you teammates they cannot see it unless it is in range of their
base or one of their vehicles.

A summary of how to identify and transfer the identity of target is printed on the
notes sheets you have been given.
Slide #15: Things you need to know about DDD - Zooming

You should also be aware of the “zoom in” command. If there are a lot of targets
in one portion of the screen, you will find it difficult to specify which one you want to
identify and which you want others to attack. So you can zoom in on that portion of the

screen.

197

Slide #22: Things you need to know about DDD — Zooming picture

To do this click the “zoom in” button and move your cursor back onto the game
playing area. Keeping the button down, drag your mouse around the area you want to
zoom in on and let go. To zoom out you just have to click on the “zoom out” button in
the report area. Remember the zoom in function during the game. Most people forget
about it and it makes the game much more difficult.
Slide #16: Things you need to know about DDD - Vehicle Information

Now lets talk about the vehicles for a second. After a vehicle is launched it
always takes a few seconds to appear. Also you should know that its direction can be
changed at any time. Additionally, each vehicle has only one shot. As it was said in the
video training, you must remember that you only get one shot with each vehicle, then you
are out of ammunition and you must return that vehicle to the base to reload. Even if you
attack an enemy with a power of 1 with a tank, which has a power of 5, you still get one
shot. After attacking, you MUST return your vehicle to your base in order to reload.
Slide #17: DDD training slide 2

You also need to keep a few things about the targets in mind. Targets need to be
identified after they have been detected. The black ring is the detection ring and the blue
ring is identification ring. Once identified, this information can then be transferred to
other teammates including you. In other words, once someone identifies a target only
they get information about it. It is not until this information is transferred to the rest of
the team that they can see what kind of target it is. Remember, only you can see what’s
outside of your own detection rings. No one else can see anything outside of their base’s

rings without the help of a vehicle.

198

Another thing to remember is that you want to attack enemies only after they are
inside of the green forbidden zone but before they get to the red forbidden zone
Slide #18: Summary

In summary, make sure that you don’t make your direction or strategies too
complicated. This game can get confusing so it’s best to keep everything simple. Also,
remember your notes pages. If you ever get to a point that you don’t know what to say,
refer back to them for some hints. Last but not least, remember to have fun and good
luck.

Now please take a few moments to read over the Transactional Leadership
Statement you will be making to you teams before the beginning of the game. The
italicized words in the brackets are suggestions you can use to help you better present the
statement. If you and your team have already discussed a certain comment or topic
contained in the statement, you don’t need to repeat it if you don’t think it’s necessary.
Please don’t hesitate to ask a staff member if you have any questions. Also, to make your
job easier, you have been given a list of phrases similar to the quiz you took. Take a
moment to pick out and circle those phrases which you might think might be consistent
with a transactional leadership style. Once you have circled them, feel free to refer to

them and use them during the simulation.

199

Transformational leadership training script

Slide #1: Introduction

Congratulations on your selection as team leader. As leader, it will be your job to
help your team achieve its maximum potential by facilitating their tasks using a
transformational leadership style. Since you play such an important role as the team
leader you will need to exhibit as many transformational leadership behaviors as possible.
There will be a short quiz following the training to ensure that you understand what
behaviors you need to demonstrate.

You will be leading a team that is responsible for identifying and attacking enemy
targets in two 30 minute simulations. There are only a few functions on the computer
that you will need to perform in this simulation so you don’t need the in-depth, hands on
training that your team is currently receiving but you will be responsible for leading them
using a transformational leadership style which is what this presentation teaches how to
do. All the game fimctions which you need to know for the simulation will be taught to
you in this presentation.

Overview

You and your team will play two 30 minute simulation and answer several
questions after they are over. Throughout the game you should exhibit the same
leadership style. It cannot be overstressed that it is critical to the success of this
experiment that you only exhibit those leadership behaviors which you have been asked
to demonstrate. If you exhibit other types of leadership behavior it could negatively

impact the efficacy of this experiment.

200

To help remind you of what you learned in this presentation and increase your
chances of exhibiting the required leadership behaviors, you have been given notes of this
presentation that you can reference during the simulation. These behaviors are associated
with transformational leadership. Please feel free to refer to these sheets during the
training or write any notes on them. They are yours to keep and use during the
simulation.

Also, some of the comments or behaviors that will be suggested to you might
seem somewhat foreign or unusual to say in front of a group of people you don’t know.
Just do your best to find a time to exhibit as many of the suggested behaviors as possible.
You don’t have to say all the comments or exhibit all the behaviors but try your best to
include as many as possible. Also, feel free to repeat as many comments or behaviors as
you would like. In fact, the more times you repeat something the better so long as you
don’t just dwell on one or two items.

Alright, let’s begin...

Slide #2: What is leadership?

Leadership is the process of influencing a team to achieve specific goals. There
are many different styles or conceptualizations of leadership but transformational
leadership is currently on of the most popular. Transformational leadership is based on
forming an emotional connection with followers. It is founded on the premise that a
strong personal connection exists between leaders and followers. Many times it also goes
by the terms charismatic or visionary leadership. There are 4 specific dimensions of this
type of leadership and we will soon go over each of these in more detail. As mentioned

before, you should use a transformational style as all times during the simulation.

201

Slide #3: Transformational Leadership

Transformational leadership is based on forming an emotional connection with
followers. This type of leadership can be broken down into 4 specific dimensions which
are commonly referred to as the “4 I’s”: Idealized Influence, Inspirational motivation,
Intellectual Stimulation, and Individual consideration. However, it is sometimes easier to
think of them simply as influencing, charming, thinking, and caring

Sometimes it is difficult to tell the difference between each of these dimensions.
If at any time you get confused during the simulation just remember that transformational
leaders always attempt to be motivational and uplifting. Before we begin dissecting each
of these dimensions lets watch a short video clip of a transformational leader at work.
Slide #4: Transformational Leadership
[Animal House clip]

While this is a humorous example from the movie Animal House, we will soon
see that there were several genuine transformational leadership behaviors that were
exhibited by John Belushi’s character, Bluto
Slide #5: Idealized influence

The first dimension of transformational leadership is idealized influence.
Idealized influence is realized when followers believe that leaders have high standards of
moral and ethical conduct, when leaders are held in high personal regard, and when they
engender loyalty from followers.

Let’s now watch a short video clip which exemplifies this type of leadership.

This clip is from the movie Braveheart with Mel Gibson. His character of William

202

Wallace is attempting to free the Scottish people from the tyrannical rule of the English
King Longshanks.

Slide #6: Idealized influence clip

[First Braveheart clip]

From this clip we can see that William Wallace’s chief concern was not for
himself but his people. Further, it is obvious that he was concerned with the moral and
ethical consequences that internal disagreements among the Scottish nobles had on the
commoners. This exemplifies the type of selfishness that engenders loyalty from
followers and demonstrates a keen sense of right and wrong.

Slide #7: Idealized influence cont.

As the leader in this simulation there are several things you can do to make your
followers believe that you have a high level of idealized influence. First you can speak
with a captivating voice. Make sure that your followers see you as interesting and in
control. To do this you can vary the pace of your speaking. Sometimes speak fast but
other times speak slow. You may also vary the loudness of your speaking. Sometimes
you can speak loud and other times soft. You may also want to pause to emphasize
different points. If you have something important to say, pausing at the right time can
often help drive home your point. Remember in the Animal House clip how John
Belushi’s character of Bluto changed his voice several times and used pauses to better
make his point.

Another way to increase your idealized influence is by continually emphasizing
the purpose of the simulation. The purpose of this simulation is to maximize scoring by

destroying as many enemy targets as possible without attacking friendly targets and to

203

learn the identity of the unknown targets. It will be important for you to constantly
remind your followers of this fact.

A final way to increase your idealized influence is to show your followers that
you have considered the moral and ethical consequences of making the wrong decisions.
Let themknow that it is important not to kill friendly targets because that would be
wrong. Let them know that if they do inadvertently kill a friendly target it is important
for them to try even harder in the future in order to keep this from happening again. You
will know someone has destroyed a friendly target because after they attack it, the target
will turn into a big black X and it say “error -25 points” after this your team offensive
score will go down by 25 points. However, when your team properly attacks an enemy
target the icon will change into what looks like a fire.

Slide #8: Inspirational Motivation

The second dimension of transformational leadership is Inspirational motivation.
Often, inspirational motivation is considered to be a type of charisma. Therefore,
inspirational motivational has to do with the ability of leaders to build confidence and
inspire followers using symbolic elements and persuasive language. Leaders with a high
level of inspirational motivation also have a strong vision for the firture based on values
and ideals.

Let’s again look at another video clip from the movie Braveheart to better
understand this dimension.

Slide #9: Inspirational Motivation clip

[First Braveheart clip]

204

In this clip we can see that William Wallace is using his charisma, charm and wit
to be as persuasive as possible. He is so successful that in the end he convinces the
people to die for their cause.

Slide #10: Inspirational Motivation cont

In this exercise there are several things you can do in order to increase your level
of inspirational motivation. The first thing is to read them the transformational leadership
statement that you will be given before the simulation begins. This will shown them that
they you are capable of articulating a strong vision for the upcoming task. The next thing
you can do is to exhibit a powerful, confident, and dynamic interaction style.
Specifically, it would be wise for you to alternate between sitting and walking, making
eye contact with people if they look at you, using hand gestures for emphasis while
speaking, and displaying animated facial expressions. In fact, walking around during the
simulation is an excellent way to exhibit a high level of inspirational motivation so try
your best to walk around as much as possible. Finally, you want to try your best to
express confidence that your team goals will be achieved. While people aren’t speaking
tell everyone that you are confident that the team goals will be met.

Slide #11: Intellectual Stimulation

The third dimension of transformational leadership is intellectual stimulation.
Leaders with a high degree of intellectual stimulation challenge organizational norms,
encourage divergent thinking, and push followers to develop innovative strategies. For
example, they will often get others to look at problems from many different angles and

suggest new ways of looking at how to complete assignments.

205

Let’s watch one more video clip fiom the movie Braveheart which exemplifies
this dimension
Slide #12: Intellectual Stimulation clip

In this clip William Wallace conceives a plan to defeat the heavy horse calvary of
Longshanks which later turns out to be very successful.

Slide #13: Intellectual Stimulation cont

During these simulations there are several different things you can do to increase
your level of intellectual stimulation. First, you can ask your team mates for suggestions.
If you’re ever uncertain as to what to do, ask your followers. Second, you can ask your
teammates to consider different ways of performing their job. Ask them to come up with
more efficient ways to complete the tasks. Finally, feel free to update or refine your
strategy. If you select a specific strategy and it’s not working, feel free to change it, just
make certain that everyone on the team knows you are changing the strategy otherwise
miscommunications might occur.

In the first clip we watched, John Belushi’s character of Bluto first convinces his
team mate Otter to go along with his plan who then provides additional intellectual
stimulation for the rest of the group. For example, Otter convinces the group to devise a
grand gesture to act as a statement. From this we can see that it is not important for the
leader to directly exhibit all the elements of transformational leadership themselves so
long as they can inspire others to do it for them.

Slide #14: Individual Consideration

‘ 206

The final transformational behavior is individual consideration. Leaders with a
high level of this dimension are able to recognize the unique growth and development
needs of followers as well as coaching followers and consulting with them.

As with the other dimensions, there are specific behaviors that you can exhibit
with your team to appear to have a greater level of individual consideration. First, you
can recognize individual accomplishments. You want to make sure that when someone
does a good job that you praise them to the whole team. For example, you might simply
say, “Hey Joe, nice job getting that target.” Second, you can also spend some time
providing individual support. If you notice that someone is having difficulty performing,
you might want to spend some more time with them. Specifically, you could just ask
them if there is anything that you can do to make their job easier. However, make certain
that if you do spend more time with them that you appear helpful and useful. Sometimes
there is a fine line between being supportive and annoying
Slide #15: Your role in DDD }

Even though we have covered numerous ways that you can appear to be a
transformational leader, there are a few more specific things that you can do to exhibit
this style of leadership. First, read the introductory statement to your team using a
commanding and dynamic voice. Remember to vary your pace and loudness.

Second, you will want to make sure that your team develops strategies on how to
operate. As a transformational leader it is important that you consider everyone’s input
when you develop these strategies so make sure you ask everyone for their input.

Third, you will be the only person on your team that can see the entire screen.

This allows you to direct the actions of others to specific threats even when they cannot

207

see them. For example, when targets appear outside of their detection rings you can warn
them that they are coming.

Finally, you will be given an opportunity between the games to summarize
everyone’s progress, talk about future strategies or make any other comments to the
group that you would like to. Please do your best to concentrate on only exhibiting
transformational behaviors during this period. During the first game, please make notes
that you can refer to during this time of things you would like to see the team do
differently, the same, or simply just better.

Slide #16: A short quiz

As promised you will now take a short quiz to ensure that you understand exactly
what set of leadership behaviors you should exhibit. In a moment, your trainer will hand
you a piece of paper with a list of phrases on it. Some of these phrases describe a
transformational leader and others do not. Simply circle those phrases that describe a
transformational leader and pass the sheet back to your trainer when you are done. Feel
flee to refer back to your notes page. After you have finished that we will finish your
training with a short description of how DDD works.

Slide #17: Things you need to know about DDD - Starting

Even though you will not be required to operate any of the vehicles in the
simulation it is important for you to understand how the game works.

The first thing you need to know is how to start it.

Slide #18: Things you need to know about DDD - Starting picture

208

When your team is ready to start the game make sure everyone, including yourself, uses
the mouse to left-click on the start button on the right hand side of the screen in the report
area. It should say refresh if you clicked correctly.
Slide #19: Things you need to know about DDD — Identifying/Transferring

The only other function you will need to know how to perform on the computer is
identifying and transferring the identity of targets to your teammates. Once the target
gets within the blue rings of your base you will be allowed to identify it as either a friend
or foe and transfer the identity of that target to your teammates. While you can see all the
targets on the screen you will only be able to identify and transfer target identities while
the targets are inside the blue identification ring of your base.
Slide #20: Things you need to know about DDD — Identifying/Transferring - Picture

Identify targets by first right clicking on the target and then choosing Identify.
Now another window will pop up. This window will appear every time you want to
identify a target. You always do the same thing to identify a target using this window —
first click on “Fused” and then go down and click on “ok.” If you did it correctly the
diamond with a question mark it in will change to the type of target it is.

However, after you identify a target you still must transfer it to you teammates.
This allows them to know what type of target it is without needing to re-identify once it
gets within range of their base or one of their vehicles. To transfer the identity of a pre-
identified target, right click on the target again and go down to “Transfer Info.” Then
click on “all linked DMs” in the next box that appears. Remember that even though you
transferred the identity to you teammates they cannot see it unless it is in range of their

base or one of their vehicles.

209

A summary of how to identify and transfer the identity of target is printed on the
notes sheets you have been given.
Slide #21: Things you need to know about DDD - Zooming

You should also be aware of the “zoom in” command. If there are a lot of targets
in one portion of the screen, you will find it difficult to specify which one you want to
identify and which you want others to attack. So you can zoom in on that portion of the
screen.
Slide #22: Things you need to know about DDD - Zooming picture

To do this click the “zoom in” button and move your cursor back onto the game
playing area. Keeping the button down, drag your mouse around the area you want to
zoom in on and let go. To zoom out you just have to click on the “zoom out” button in
the report area. Remember the zoom in function during the game. Most people forget
about it and it makes the game much more difficult.
Slide #23: Things you need to know about DDD — Vehicle Information

Now lets talk about the vehicles for a second. After a vehicle is launched it
always takes a few seconds to appear. Also you should know that its direction can be
changed at any time. Additionally, each vehicle has only one shot. As it was said in the
video training, you must remember that you only get one shot with each vehicle, then you
are out of ammunition and you must return that vehicle to the base to reload. Even if you
attack an enemy with a power of 1 with a tank, which has a power of 5, you still get one
shot. After attacking, you MUST return your vehicle to your base in order to reload.

Slide #24: DDD training slide 2

210

You also need to keep a few things about the targets in mind. Targets need to be
identified after they have been detected. The black ring is the detection ring and the blue
ring is identification ring. Once identified, this information can then be transferred to
other teammates including you. In other words, once someone identifies a target only
they get information about it. It is not until this information is transferred to the rest of
the team that they can see what kind of target it is. Remember, only you can see what’s
outside of your own detection rings. No one else can see anything outside of their base’s
rings without the help Of a vehicle.

Another thing to remember is that you want to attack enemies only after they are
inside of the green forbidden zone but before they get to the red forbidden zone
Slide #25: Summary

In summary, make sure that you don’t make your direction or strategies too
complicated. This game can get confusing so it’s best to keep everything simple. Also,
remember your notes pages. If you ever get to a point that you don’t know what to say,
refer back to them for some hints. Last but not least, remember to have fun and good
luck.

Now please take a few moments to read over the Transformational Leadership
Statement you will be making to you teams before the beginning of the game. The
italicized words in the brackets are suggestions you can use to help you better present the
statement. If you and your team have already discussed a certain comment or topic
contained in the statement, you don’t need to repeat it if you don’t think it’s necessary.
Please don’t hesitate to ask a staff member if you have any questions. Also, to make your

job easier, you have been given a list of phrases similar to the quiz you took. Take a

211

moment to pick out and circle those phrases which you might think are consistent with a
transformational leadership style. Once you have circled them, feel free to refer to them

and use them during the simulation.

212

Appendix C TRAINING ROOM PICTURES

    

.5

Figure 34. Training Room A

.w-‘hk

 

Figure 35. Training Room B

213

BIBLIOGRAPHY

Aguinis, H. (2004). Regression Analysis for Categorical Moderators New York, NY:
Guilford Press.

Akgun, A. E., Byme, J ., Keskin, H., Lynn, G. S., & Irnamoglu, S. Z. (2005). Knowledge
networks in new product development projects: A transactive memory
perspective. Information & Management, 42(8), 1105-1120.

Allred, B. B., Snow, C. C., & Miles, R. E. (1996). Characteristics of managerial careers
of the let century. The Academy of Management Executive, 10(4), 17-27.

Almeida, E. P. (2004). A discourse analysis of student perceptions of their
communication competence. Communication Education, 53(4), 357-364.

Anderson, N., Lievens, F ., van Dam, K., & Born, M. (2006). A construct-driven
investigation of gender differences in a leadership-role assessment center. Journal
Of Applied Psychology, 91(3), 555-566.

Antonakis, J., Avolio, B. J., & Sivasubramaniam, N. (2003). Context and leadership: An
examination of the nine-factor full-range leadership theory using the Multifactor
Leadership Questionnaire. Leadership Quarterly, 14(3), 261.

Armstrong, D. J ., & Cole, P. (2002). Managing distances and differences in
geographically distributed work groups. In P. Hinds & S. Kiesler (Eds),
Distributed work (pp. 167-189). Cambridge, MA, US: MIT Press.

Audia, P. G., & Locke, E. A. (2003). Benefiting from negative feedback. Human
Resource Management Review, 13(4), 631-646.

Avolio, B. J., & Kahai, S. (2003). Placing the "E" in E-Leadership: Minor Tweak or
Fundamental Change. In S. E. Murphy & R. E. Riggio (Eds), The Future of
Leadership Development. Mahwah, New Jersey: Lawrence Erlbaum Associates.

Avolio, B. J., Kahai, S., & Dodge, G. E. (2001). E-Leadership: Implications for Theory,
Research, and Practice. Leadership Quarterly, 11(4), 615-668.

Balthazard, P., Potter, R. E., & Warren, J. (2004). Expertise, Extraversion and Group
Interaction Styles as Performance Indicators in Virtual Teams. Database for
Advances in Information Systems, 35(1), 41.

Barling, J ., Weber, T., & Kelloway, E. K. (1996). Effects of transformational leadership
training on attitudinal and financial outcomes: A field experiment. Journal Of
Applied Psychology, 81(6), 827-832.

Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in
social psychological research: Conceptual, strategic, and statistical considerations.
Journal of Personality and Social Psychology, 51 (6), 1 173-1 182.

214

Barsade, S. G., Brief, A. P., & Spataro, S. E. (2003). The affective revolution in
organizational behavior: The emergence of a paradigm. In J. Greenberg (Ed.),
Organizational behavior: The state of the science (pp. 3-52). Mahwah, NJ:
Erlbaum.

Bass, B. M. (1985). Leadership and performance beyond expectations. New York, NY:
Free Press.

Bass, B. M., & Avolio, B. J. (1993). Transformational leadership: A response to critiques.
In M. M. Chemers & R. Ayman (Eds), Leadership theory and research:
Perspectives and directions (pp. 49-80). San Diego, CA: Academic Press.

Bass, B. M., & Avolio, B. J. (1997). Full range leadership development: Manuel for the
Multifactor Leadership Questionnaire. Palo Alto, CA: Mind Garden.

Bass, B. M., Avolio, B. J., & Goodheim, L. (1987). Biography and the Assessment of
Transformational Leadership at the World-Class Level. Journal of Management,
13(1), 7-19.

Bell, B. S., & Kozlowski, S. W. J. (2002). A typology of virtual teams: Implications for
effective leadership. Group & Organization Management, 27(1), 14.

Bhappu, A. D., Griffith, T. L., & Northcraft, G. B. (1997). Media effects and
communication bias in diverse groups. Organizational Behavior And Human
Decision Processes, 70(3), 199-205.

Binning, J. F. I. S. U. N. U. S., & Barrett, G. V. (1989). Validity of personnel decisions:
A conceptual analysis of the inferential and evidential bases. Journal of Applied
Psychology, 74(3), 478-494.

Blackbum, R., Furst, S., & Rosen, B. (2003). Building a winning virtual team. In C. B.
Gibson & S. G. Cohen (Eds), Virtual teams that work .° creating conditions for
virtual team effectiveness (pp. 95-120). San Francisco, CA: Jossey-Bass.

Blau, P. (1964). Exchange and power in social life. New York, NY: Wiley.

Bolls, P. D., & Tan, A. (1996). Communication anxiety and teacher communication
competence among Native American and Caucasian students. Communication
Research Reports, 13(2), 205-213.

Bono, J. E., & Judge, T. A. (2004). Personality and transformational and transactional
leadership: A meta-analysis. Journal Of Applied Psychology, 89(5), 901-910.

Bourgeois, L. J. (1979). Toward a method of middle-range theorizing. Academy of
Management. The Academy of Management Review (ore-1986), 4(000003), 443.

Brass, D. J. (1984). Being in the right place: A structural analysis of individual influence
in an organization. Administrative Science Quarterly, 29(4), 518-539.

215

Bryrnan, A. (1992). Charisma and leadership in organizations. London: Sage.

Burke, K., Aytes, K., Chidambaram, L., & Johnson, J. J. (1999). A study of partially
distributed work groups: The impact of media, location, and time on perceptions
and performance. Small Group Research, 30(4), 453.

Burkhardt, M. E., & Brass, D. J. (1990). Changing Patterns Or Patterns Of Change - The
Effects Of A Change In Technology On Social Network Structure And Power.
Administrative Science Quarterly, 35(1), 104-127.

Burns, J. M. (1978). Leadership. New York, NY: Harper & Row.
Burns, T., & Stalker, G. M. (1961). The management of innovation. London: Tavistock.

Burt, R. S. (1992). Structural Holes: The social structure of competition. Cambridge,
MA: Harvard University Press.

Campbell, D. J., & Gingrich, K. F. (1986). The Interactive Effects Of Task Complexity
And Participation On Task-Performance - A Field Experiment. Organizational
Behavior And Human Decision Processes, 38(2), 162-180.

Campion, M. A., Medsker, G. J ., & Higgs, A. C. (1993). Relations Between Work Group
Characteristics And Effectiveness - Implications For Designing Effective Work
Groups. Personnel Psychology, 46(4), 823-850.

Campion, M. A., Papper, E. M., 8: Medsker, G. J. (1996). Relations between work team
characteristics and effectiveness: A replication and extension. Personnel
Psychology, 49(2), 429-452.

Cascio, W. F. (1999). Virtual Workplaces: Implications for organizational behavior. In C.
L. Cooper & D. M. Rousseau (Eds), Trends in organizational behavior: The
virtual organization (pp. 1-14). Chichester, England: Wiley.

Cascio, W. F ., & Shurygailo, S. (2003). E-Leadership and virtual teams. Organizational
Dynamics, 31(4), 362-376.

Cegala, D. J., Coleman, M. T., & Turner, J. W. (1998). The development and partial
assessment of the medical communication competence scale. Health
Communication, 10(3), 261-288.

Cohen, D., & Prusak, L. (2001). In good company: How social capital makes
organizations work. Boston: Harvard Business School Press.

Cohen, J. (1992). A Power Primer. Psychological Bulletin, 1 12(1), 155-159.

Cohen, J ., Cohen, R, West, S. G., & Aiken, L. S. (2003). Applied Multiple
Regression/Correlation Analysis for the Behavioral Sciences. Mahwah, New
Jersy: Lawrence Erlbaum Associates.

216

Cohen, S. G., & Bailey, D. E. (1997). What makes teams work: Group effectiveness
research from the shop floor to the executive suite. Journal of Management,
23(3), 239.

Colarusso, L. M., 8: Trowbridge, G. (2004). The future is now 'Reach-back' technology
lets airmen fight in Iraq from comfort of home. Air Force Times.

Cramton, C. D. (2002). Attribution in distributed work groups. In P. Hinds & S. Kiesler
(Eds), Distributed work (pp. 191-212). Cambridge, MA, US: MIT Press.

Davis, D. D., & Polonko, K. A. (2001). T elework America 2001 Summary: International
Telework Assocation and Council.

Defense, D. o. (2002). Joint Vision 2020. Pentagon: Joint Chiefs of Staff.

Deluga, R. J. (1988). Relationship of Transformational and Transactional Leadership
with Employee Influencing Strategies. Group & Organizational Studies, 13(4),
456-467.

DenHartog, D. N., VanMuijen, J. J ., & Koopman, P. L. (1997). Transactional versus
transformational leadership: An analysis of the MLQ. Journal Of Occupational
And Organizational Psychology, 70, 19-34.

DeShon, R. P., & Alexander, R. A. (1996). Goal setting effects on implicit and explicit
learning of complex tasks. Organizational Behavior And Human Decision
Processes, 65(1), 18-36.

Dirks, K. T., & McLean Parks, J. (2003). Conflicting stories: The state of the science of
conflict. In J. Greenberg (Ed.), Organizational behavior (pp. 324). Mahwah, NJ:
Erlbaum.

Donaldson, L. (2001). The Contingency Theory of Organizations. Thousand Oaks, CA:
Sage.

Dooley, D. (1995). Social Research Methods (3rd ed.). Upper Saddle River, NJ.

Druskat, V. U., & Wheeler, J. V. (2003). Managing from the boundary: The effective
leadership of self-managing work teams. Academy of Management Journal, 46(4),
435-457.

Dumdum, U. R., Lowe, K. B., & Avolio, B. J. (2002). A meta-analysis of the
transformational and transactional leadership correlates of effectiveness and
satisfaction: An update and extension. In B. J. Avolio & F. J. Yammarino (Eds),
Transformational and Charismatic leadership: The road ahead (pp. 35-66).
Amsterdam: J A1.

217

Dvir, T., Eden, D., Avolio, B. J ., & Shamir, B. (2002). Impact of transformational
leadership on follower development and performance: A field experiment.
Academy Of Management Journal, 45(4), 735-744.

Earley, P. C. (1985). Influence Of Information, Choice And Task Complexity Upon Goal
Acceptance, Performance, And Personal Goals. Journal Of Applied Psychology,
70(3), 481-491.

Earley, P. C., Lee, C., & Hanson, L. A. (1990). Joint Moderating Effects Of Job
Experience And Task Component Complexity - Relations Among Goal Setting,
Task Strategies, And Performance. Journal Of Organizational Behavior, 11(1), 3-
1 5.

Ellis, A. P. J ., Hollenbeck, J. R., Ilgen, D. R., Porter, C. O. L. H., West, B. J., & Moon,
H. (2003). Team learning: Collectively connecting the dots. Journal of Applied
Psychology, 88(5), 821-835.

Erez, A., & Isen, A. M. (2002). The influence of positive affect on the components of
expectancy motivation. Journal Of Applied Psychology, 87(6), 1055-1067.

Fairhurst, G. T. (1993). The Leader-Member Exchange Patterns Of Women Leaders In
Industry - A Discourse Analysis. Communication Monographs, 60(4), 321-351.

Fang, E., Palmatier, R. W., & Evans, K. R. (2004). Goal-setting paradoxes? Trade-offs
between working hard and working smart: The United States versus China.
Journal Of The Academy Of Marketing Science, 32(2), 188-202.

Ferrara, K., Brunner, H., & Whittenmore, G. (1990). Interactive written discourse as
emergent register. Written Communication, 8(1), 8-34.

Ferris, G. R. (1985). Role of leadership in the employee withdrawal process: A
constructive replication. Journal of Applied Psychology, 70(4), 777-781.

F iedler, F. E. (1967). A theory of leadership effectiveness. New York, NY: McGraw-Hill.
Fiedler, F. E. (1971). Leadership. Morristown, NJ: General Learning Press.

Fiore, S. M., & Schooler, J. W. (2004). Process mapping and shared cognition:
Teamwork and the development of shared problem models. In E. Salas & S. M.
F iore (Eds), Team cognition: Understanding the factors that drive process and
performance (pp. 133-152). Washington, DC: USical Association.

Fisher, C. D. (1993). Boredom at work: A neglected concept. Human Relations, 46(3),
395-417.

Forgas, J. P., & George, J. M. (2001). Affective influences on judgments and behavior in

organizations: An information processing perspective. Organizational Behavior
And Human Decision Processes, 86(1), 3-34.

218

Freeman, L. C. (1979). Centrality in Social Networks: Conceptual clarification. Social
Networks, [(21 5-239).

Frone, M. R., & Major, B. (1988). Communication Quality And J ob-Satisfaction Among
Managerial Nurses - The Moderating Influence Of Job Involvement. Group &
Organization Studies, 13(3), 332-347.

Ganzach, Y., Pazy, A., Ohayun, Y., & Brainin, E. (2002). Social exchange and
organizational commitment: Decision-making training for job choice as an
alternative to the realistic job preview. Personnel Psychology, 55(3), 613-637.

Gardner, D. G. (1990). Task Complexity Effects On Non-Task-Related Movements - A
Test Of Activation Theory. Organizational Behavior And Human Decision
Processes, 45(2), 209-231.

George, J. M., & Brief, A. P. (1996). Motivational agendas in the workplace: The effects
of feelings on focus of attention and work motivation. In Research In
Organizational Behavior (V 01. 18, pp. 75-109). Greenwich: Jai Press Inc.

Gitter, A. G., Black, H., & F ishman, J. E. (1975). Effect of race, sex, nonverbal
communication and verbal communication on perception of leadership. Sociology
& Social Research, 60(1), 46-57.

Gitter, A. G., Black, H., & Goldman, A. (1975). Role of nonverbal communication in the
perception of leadership. Perceptual & Motor Skills, 40(2), 463-466.

Gitter, A. G., Black, H., & Walkley, J. (1976). Nonverbal communication and the
judgment of leadership. Psychological Reports, 39(3, Pt 2), 1117-1118.

Goodman, P. S., Ravlin, E., 8: Schmike, M. (1987). Understanding groups in
organizations. In L. L. Cummings & B. M. Staw (Eds), Research in
organizational behavior (Vol. 9, pp. 121-173): J AI press.

GoodWin, V. L., Wofford, J. C., & Boyd, N. G. (2000). A laboratory experiment testing
the antecedents of leader cognitions. Journal of Organizational Behavior, 21(7),
769.

Gordon, A., Wilkinson, R., McGown, A., & Jovanoska, S. (1997). The psychometric
properties of the Boredom Proneness Scale: An examination of its validity.
Psychological Studies, 42(2-3), 85-97.

Gorton, I., & Motwani, S. (1996). Issues in co-operative software engineering using
globally distributed teams. Information And Software Technology, 38(10), 647-
655.

Graen, G. B., & Ginsburgh, S. (1977). Job Resignation As A Function Of Role-
Orientation And Leader Acceptance - Longitudinal Investigation Of

219

Organizational Assimilation. Organizational Behavior And Human Performance,
19(1), 1-17.

Graen, G. B., & Uhlbien, M. (1995). Relationship-Based Approach To Leadership -
Development Of Leader-Member Exchange (me) Theory Of Leadership Over
25 Years - Applying A Multilevel Multidomain Perspective. Leadership
Quarterly, 6(2), 219-247.

Griffith, T. L., Sawyer, J. E., & Neale, M. A. (2003). Virtualness and knowledge in
teams: Managing the love triangle of organizations, individuals, and information
technology]. MIS Quarterly, 27(2), 265.

Hackman, R. (1987). The Design of Work Teams. In J. Lorsch (Ed), Handbook of
Organizational Behavior (pp. 315-342). New York Prentice Hall.

Hackman, R. (2002). Leading Teams. Boston, MA: Harvard Business School Press.

Heinitz, K., Liepmann, D., & F elfe, J. (2005). Examining the factor structure of the
MLQ: Recommendation for a reduced set of factors. European Journal of
Psychological Assessment, 21(3), 182-190.

Herbert, A. (2004). Operation Reachback. Air Force Magazine, 87(4), 56-58.

Hersey, P., & Blanchard, K. H. (1969). Life-cycle theory of leadership. Training and
Development Journal, 23, 26-34.

Hiltz, S. R., Johnson, K., & Turoff, M. (1986). Experiments in group decision making:
Communication process and outcome in face-to-face versus computerized
conferences. Human Communication Research, 13(2), 225-252.

Hinsz, V. B., Tindale, R. S., & Vollrath, D. A. (1997). The emerging conceptualization of
groups as information processes. Psychological Bulletin, 121(1), 43-64.

Hoegl, M., & Gemuenden, H. G. (2001). Teamwork quality and success of innovative
projects: A theoretical concept and empirical evidence. Organization Science,
12(4), 435-449.

Hogg, M. A., Fielding, K. S., Johnson, D., Masser, B., Russell, E., & Svensson, A.
(2006). Demographic category membership and leadership in small groups: A
social identity analysis. Leadership Quarterly, 1 7(4), 335-350.

Hollenbeck, J. R., Ilgen, D. R., LePine, J. A., Colquitt, J. A., & Hedlund, J. (1998).
Extending the multilevel theory of team decision making: Effects of feedback and
experience in hierarchical teams. Academy Of Management Journal, 41(3), 269-
282.

Hollenbeck, J. R., Moon, H., Ellis, A. P. J., West, B. J., Ilgen, D. R., Sheppard, L., et al.
(2002). Structural contingency theory and individual differences: Examination of

220

external and internal person-team fit. Journal Of Applied Psychology, 87(3), 599-
606.

Hollingshead, A. B. (1996). Information suppression and status persistence in group
decision making: The effects of communication media. Human Communication
Research, 23(2), 193.

Hollingshead, A. B. (1998). Communication, learning, and retrieval in transactive
memory systems. Journal of Experimental Social Psychology, 34(5), 423-442.

House, R. J. (1971). A path-goal theory of leadership effectiveness. Administrative
Science Quarterly, 16, 321-328.

House, R. J ., Woycke, J., & Fodor, E. M. (1988). Charismatic and noncharismatic
leaders: Differences in behavior and effectiveness. In C. J .A. & K. R.N. (Eds),
Charismatic Leadership (pp. 98-121). San Francisco: J ossey-Bass.

Hoyt, C. L., & Blascovich, J. (2003). Transformational and transactional leadership in
virtual and physical environments. Small Group Research, 34(6), 678.

Humphrey, S. E. (2003). Out of Sight, Out of Mind: Partially Distributed Teams and
Team Eflectiveness. Unpublished doctoral dissertation, Michigan State University,
East Lansing, MI.

Humphrey, S. E., Hollenbeck, J. R., Meyer, C. J ., & Ilgen, D. R. (2002). Hierarchical
team decision making. Research in Personnel and Human Resources
Management, 21, 175-213.

Ibarra, H. (1993). Network Centrality, Power, And Innovation Involvement -
Determinants Of Technical And Administrative Roles. Academy Of Management
Journal, 36(3), 471-501.

Ibarra, H., & Andrews, S. B. (1993). Power, Social-Influence, And Sense Making -
Effects Of Network Centrality And Proximity On Employee Perceptions.
Administrative Science Quarterly, 38(2), 277-303.

Ilgen, D. R., Major, D. A., Hollenbeck, J. R., & Sego, D. J. (1993). Team research in the
1990s In M. M. Chemers & R. Ayman (Eds), Leadership theory and research:
Perspectives and directions (pp. 245-270): San Diego, CA, USnc, 1993, xx, 347.

Jablin, F. M. (1994). Communication Competence. In L. v. Waes, E. Woudstra & P. v. d.
Hoven (Eds), Functional Communication Quality (pp. 30-41). Amsterdam:
Rodopi.

J ablin, F. M., Cude, R. L., House, A., Lee, J., & Roth, N. L. (1994). Communication
competence in organizations. In L. Thayer & G. Barnett (Eds), Organization-
Communication: Emerging Perspectives (Vol. 4) (pp. 114-140). Norwood, NJ:
Ablex.

221

J ablin, F. M., & Sias, P. M. (2001). Communication Competence. In F. M. Jablin & L. L.
Putnam (Eds), The new handbook of organizational communication: Advances in
theory, research, and methods (2nd ed.) (pp. 819-864). Newbury Park, CA: Sage.

Jessup, L. M., & Tansik, D. A. (1991). Decision-Making In An Automated Environment
- The Effects Of Anonymity And Proximity With A Group Decision Support
System. Decision Sciences, 22(2), 266-279.

Johnson, M. D. (2006). The eflects of workload on individual and team cognition, affect,
and performance. Michigan State University, East Lansing MI.

Johnson, M. D., Hollenbeck, J. R., Humphrey, S. E., Ilgen, D. R., Jundt, D., & Meyer, C.
J. (2006). Cutthroat cooperation: Asymmetrical adaptation to changes in team
reward structures. Academy Of Management Journal, 49(1), 103-119.

Judge, T. A., & Piccolo, R. F. (2004). Transformational and transactional leadership: A
meta-analytic test of their relative validity. Journal Of Applied Psychology, 89(5),
755-768.

Judge, T. A., Piccolo, R. F., & Ilies, R. (2004). The Forgotten Ones? The Validity of
Consideration and Initiating Structure in Leadership Research. Journal of Applied
Psychology, 89(1), 36-51.

Kacmar, K. M., Witt, L. A., Zivnuska, S., & Gully, S. M. (2003). The interactive effect of
leader-member exchange and communication frequency on performance ratings.
Journal of Applied Psychology, 88(4), 764-772.

Kahai, S. S., & Cooper, R. B. (1999). The effect of computer-mediated communication
on agreement and acceptance. Journal of Management Information Systems,
16(1), 165.

Kahai, S. S., & Cooper, R. B. (2003); Exploring the core concepts of media richness
theory: The impact of cue multiplicity and feedback immediacy on decision
quality. Journal of Management Information Systems, 20(1), 263.

Kahai, S. S., Sosik, J. J., & Avolio, B. J. (1997). Effects of leadership style and problem
structure on work group process and outcomes in an electronic meeting system
environment. Personnel Psychology, 50(1), 121-146.

Kahai, S. S., Sosik, J. J ., & Avolio, B. J. (2003). Effects of leadership style, anonymity,
and rewards on creativity-relevant processes and outcomes in an electronic
meeting system context. Leadership Quarterly, 14(4-5), 499-524.

Kahai, S. S., Sosik, J. J ., & Avolio, B. J. (2004). Effects of participative and directive
leadership in electronic groups. Group & Organization Management, 29(1), 67-
105.

222

Kanfer, R., & Ackerman, P. L. (1989). Motivation And Cognitive-Abilities - An
Integrative Aptitude Treatment Interaction Approach To Skill Acquisition.
Journal Of Applied Psychology, 74(4), 657-690.

Kayworth, T. R., & Leidner, D. E. (2001). Leadership effectiveness in global virtual
teams. Journal of Management Information Systems, 18(3), 7.

Keller, R. T. (1992). Transformational leadership and the performance of research and
development project groups. Journal of Management, 18(3), 489-501.

Kelly, J. R., & Barsade, S. G. (2001). Mood and emotions in small groups and work
teams. Organizational Behavior And Human Decision Processes, 86(1), 99-130.

Kerlinger, F. N., & Lee, H. B. (1999). Foundations of Behavioral Research (4th ed.). Fort
Worth, TX: Harcourt College Publishers.

Kerr, S., & J ermier, J. M. (1978). Substitutes For Leadership - Their Meaning And
Measurement. Organizational Behavior And Human Performance, 22(3), 375-
403.

Kiesler, S., & Cummings, J. N. (2002). What do we know about proximity and distance
in work groups? A legacy of research. In P. Hinds & S. Kiesler (Eds), Distributed
work (pp. 57-80). Cambridge, MA, US: MIT Press.

Kiesler, S., & Sproull, L. (1992). Group Decision Making and Communication
Technology. Organizational Behavior and Human Decision Processes, 52(1), 96.

Kirkman, B. L., Rosen, B., Tesluk, P. E., 8: Gibson, C. B. (2004). The Impact Of Team
Empowerment On Virtual Team Performance: The Moderating Role Of Face-To-
Face Interaction. Academy of Management Journal, 4 7(2), 175.

Kirkpatrick, S. A., & Locke, E. A. (1991). Leadership: do traits matter? Academy Of
Management Executive, 5(2), 49-60.

Kirkpatrick, S. A., & Locke, E. A. (1996). Direct and indirect effects of three core
charismatic leadership components on performance and attitudes. Journal of
Applied Psychology, 81(1), 36-51.

Klein, K. J ., Lim, B. C., Saltz, J. L., & Mayer, D. M. (2004). How do they get there? An
examination of the antecedents of centrality in team networks. Academy Of
Management Journal, 4 7(6), 952-963.

Kock, N. (1998). Can communication medium limitations foster better group outcomes?
An action research study. Information & Management, 34(5), 295-305.

Komaki, J ., & Barnett, F. T. (1977). Behavioral-Approach To Coaching Football -
Improving Play Execution Of Offensive Backfield On A Youth Football Team.
Journal Of Applied Behavior Analysis, 10(4), 657-664.

223

Kozlowski, S. W. J ., & Bell, B. S. (2003). Work Groups and Teams in Organizations. In
W. C. Borman, D. R. Ilgen & R. J. Klimoski (Eds), Handbook of psychology:
Industrial and organizational psychology (Vol. 12, pp. 333-375). London: Wiley.

Kozlowski, S. W. J ., & Hults, B. M. (1986). Joint Moderation Of The Relation Between
Task Complexity And J ob-Perforrnance For Engineers. Journal Of Applied
Psychology, 71(2), 196-202.

Kraatz, M. S. (1998). Learning by association? Interorganizational networks and
adaptation to environmental change. Academy Of Management Journal, 41(6),
621-643.

Kraut, R. E., Fussell, S. R., Brennan, S. E., & Siegel, J. (2002). Understanding effects of
proximity on collaboration: Implications for technologies to support remote
collaborative work. In P. Hinds & S. Kiesler (Eds), Distributed Work (pp. 137-
162). Cambridge, MA: MIT Press.

Kuhnert, K. W., & Lewis, P. (1987). Transactional and Transformational Leadership - a
Constructive Developmental Analysis. Academy of Management Review, 12(4),
648-657.

Kiipers, W. D., & Weibler, J. (2006). How emotional is transformational leadership
really? Some suggestions for a necessary extension. Leadership & Organization
Development Journal, 27(5), 368-383.

Landy, F. L. (1985). Psychology of work behavior. Homewood Il: Dorsey Press.

Larson, J. R., & Christensen, C. (1993). Groups as problem-solving units: Toward a new
meaning of social cognition. British Journal of Social Psychology, 32(1), 5-30.

Lau, D. C., & Mumighan, J. K. (1998). Demographic diversity and faultlines: The
compositional dynamics of organizational groups. Academy Of Management
Review, 23(2), 325-340.

Lau, D. C., & Mumighan, J. K. (2005). Interactions within groups and subgroups: The
effects of demographic faultlines. Academy Of Management Journal, 48(4), 645-
659.

Leavitt, H. J. (1951). Some effects of certain communication patters on group
performance. Journal of Abnormal and Social Psychology, 46, 38-50.

Lee-Kelley, L. (2002). Situational leadership: Managing the virtual project team. The
Journal of Management Development, 21 (5/6), 461.

Lewis, K. M. (2000). When leaders display emotion: how followers respond to negative
emotional expression of male and female leaders. Journal Of Organizational
Behavior, 21 , 221-234.

224

Liang, D. W., Moreland, R., & Argote, L. (1995). Group Versus Individual Training And
Group-Performance - The Mediating Role Of Transactive Memory. Personality
And Social Psychology Bulletin, 21(4), 384-393.

Lipnack, J ., & Stamps, J. (1997). Virtual teams: Reaching Across Space, Time and
Organizations with Technology. New York, NY: John Wiley.

Lowe, K. B., Kroeck, K. G., & Sivasubramaniam, N. (1996). Effectiveness correlates of
transformation and transactional leadership: A meta-analytic review of the MLQ
literature. Leadership Quarterly, 7(3), 385-425.

MacMillan, J ., Entin, E. E., & Serfaty, D. (2004). Communication overhead: The hidden
cost of team cognition. In E. Salas & S. M. Fiore (Eds), Team cognition:
Understanding the factors that drive process and performance (pp. 61-82).
Washington, DC: USical Association.

Man, D. C., & Lam, S. S. K. (2003). The effects of job complexity and autonomy on
cohesiveness in collectivistic and individualistic work groups: a cross-cultural
analysis. Journal Of Organizational Behavior, 24(8), 979-1001.

Martins, L. L., Gilson, L. L., & Maynard, M. T. (2004). Virtual Teams: What Do We
Know and Where Do We Go From Here? Journal of Management, 30(6), 805.

Masters, R. D., & Sullivan, D. G. (1989). Nonverbal displays and political leadership in
France and the United States. Political Behavior, 11(2), 123-156.

Masters, R. D., Sullivan, D. G., Lanzetta, J. T., McHugo, G. J ., & et al. (1986). The facial
displays of leaders: Toward an ethology of human politics. Journal of Social &
Biological Structures, 9(4), 319-343.

McClelland, G. H. (1997). Optimal Design in Psychological Research. Psychological
Methods, 2(1), 3-19.

McColl-Kennedy, J. R., & Anderson, R. D. (2002). Impact of leadership style and
emotions on subordinate performance. Leadership Quarterly, 13(5), 545-559.

Miller, D. L., Young, R, Kleinman, D., & Serfaty, D. (1998). Distributed dynamic
decision-making simulation phase I release notes and user’s manual. Woburn,
MA: Aptima, Inc.

Monge, P. R., Backrnan, S. G., Dillard, J. P., & Eisenberg, E. M. (1994). Communicator
competence questionnaire. In R. B. Rubin, P. Palrngreen & H. E. Sypher (Eds),
Communication Research Measures: A Sourcebook (pp. 130-133). New York,
NY: Guilford Press.

Morgeson, F. P. (2005). The external leadership of self-managing teams: Intervening in
the context of novel and disruptive events. Journal Of Applied Psychology, 90(3),
497-508.

225

Mortensen, M., & Hinds, P. (2001). Conflict and shared identity in geographically
distributed teams. International Journal of Conflict Management, 12(3), 212-238.

Neal, J. M. (2000). A look at Reachback. Military Review, 80(5), 39-43.
Northhouse, P. G. (2004). Leadership: Theory and Practice. Thousand Oaks, CA: Sage.
Nunnally, J. M. (1978). Psychometric Theory. New York, NY: McGraw Hill.

Opper, S., & Fersko-Weiss, H. (1992). Technology for teams: Enhancing productivity in
networked organizations. New York, NY: Van Nostrand Reinhold.

Paquette, L., & Kida, T. (1988). The Effect Of Decision Strategy And Task Complexity
On Decision Performance. Organizational Behavior And Human Decision
Processes, 41(1), 128-142.

Pauleen, D. J. (2003). Leadership in a global virtual team: An action learning approach.
Leadership & Organization Development Journal, 24(3), 153.

Pauleen, D. J. (2004). An Inductively Derived Model of Leader-Initiated Relationship
Building with Virtual Team Members. Journal of Management Information
Systems, 20(3), 227.

Penley, L. E. (1991). Communication abilities of managers: the relationship to
performance. Journal of Management, 1 7(1), 57-76.

Polzer, J. T., Crisp, C. B., Jarvenpaa, S. L., & Kim, J. W. (2006). Extending the faultline
model to geographically dispersed teams: How collocated subgroups can impair
group functioning. Academy of Management Journal, 49(4), 679-692.

Propp, K. M., & Nelson, D. (1996). Problem-solving performance in naturalistic groups:
A test of the ecological validity of the functional perspective. Communication
Studies, 4 7(1-2), 35.

Pugh, S. D. (2001). Service with a smile: Emotional contagion in the service encounter.
Academy Of Management Journal, 44(5), 1018-1027.

Roberts, T. L., Cheney, P. H., Sweeney, P. D., & Hightower, R. T. (2004). The effects of
information technology project complexity on group interaction. Journal Of
Management Information Systems, 21 (3), 223-247.

Salancik, G. R., & Pfeffer, J. (1977). Who Gets Power - How They Hold On To It -
Strategic-Contingency Model Of Power. Organizational Dynamics, 5(3), 3-21.

Sanders, C. (2000). Virtual Team: Piecing Together the Puzzle. In B. Zmud (Ed.),
Framing the Domains of IT Management (pp. 29-50). Cincinnati, Ohio: Pinnaflex.

226

Sashkin, M. (2004). Transformational Leadership Approaches. In J. Antonakis, A. T.
Cianciolo & R. J. Stemberg (Eds), The Nature of Leadership (pp. 171-196).
Thousand Oaks, CA: Sage.

Scarpello, V., & Vandenberg, R. J. (1987). The Satisfaction With My Supervisor Scale -
Its Utility For Research And Practical Applications. Journal Of Management,
13(3), 447-466.

Seltzer, J ., & Bass, B. M. (1990). Transformational leadership: Beyond initiation and
consideration. Journal of Management, 16(4), 693-703.

Shapiro, D. L., & Rynes, S. L. (2005). Public Policy and the Public Interest: What if we
mattered more? Academy Of Management Journal, 48(6).

Shea, G. P., & Guzzo, R. A. (1987). Groups as human resources. In K. M. Rowland & G.
R. Penis (Eds), Research in personnel and human resource management (Vol. 5,
pp. 323-356). Greenwich CT: JAI Press.

Shin, S. J ., & Zhou, J. (2003). Transformational leadership, conservation, and creativity:
Evidence from Korea. Academy of Management Journal, 46(6), 703-714.

Skarlicki, D. P., & Latham, G. P. (1997). Leadership training in organizational justice to
increase citizenship behavior within a labor union: A replication. Personnel
Psychology, 50(3), 617-633.

Slavin, R. E. (1996). Research on cooperative learning and achievement: What we know,
what we need to know. Contemporary Educational Psychology, 21(1), 43-69.

Sosik, J. J., Avolio, B. J ., & Kahai, S. S. (1997). Effects of leadership style and
anonymity on group potency and effectiveness in a group decision support system
environment. Journal Of Applied Psychology, 82(1), 89-103.

Sosik, J. J ., Avolio, B. J ., Kahai, S. S., & Jung, D. I. (1998). Computer-supported work
group potency and effectiveness: The role of transformational leadership,
anonymity, and task interdependence. Computers In Human Behavior, 14(3), 491-
51 1.

Sosik, J. J ., Kahai, S. S., & Avolio, B. J. (1998). Transformational leadership and
dimensions of creativity: Motivating idea generation in computer-mediated
groups. Creativity Research Journal, 11(2), 1 1 1-121.

Sparrowe, R. T. (2005). Social networks and organizations. Academy Of Management
Review, 30(1), 207-209.

Sparrowe, R. T., Liden, R. C., Wayne, S. J ., & Kraimer, M. L. (2001). Social networks
and the performance of individuals and groups. Academy Of Management
Journal, 44(2), 316-325.

227

Spears, R., & Lea, M. (1994). Panacea or panopticon? The hidden power in computer-
mediated communication. Communication Research, 21 (4), 427.

Spreitzer, G. M. (1995). Psychological Empowerment in the Workplace - Dimensions,
Measurement, and Validation. Academy of Management Journal, 38(5), 1442-
1465. .

Spreitzer, G. M. (2003). Leadership Development in the Virtual Workplace. In S. E.
Murphy & R. E. Riggio (Eds), The Future of Leadership Development. Mahwah,
New Jersey: Lawrence Erlbaum Associates.

Sproull, L., & Kiesler, S. (1986). Reducing Social Context: Electronic Mail in
Organizational Communication. Management Science, 32(11), 1492.

Stajkovic, A. D., & Luthans, F. (2003). Behavioral management and task performance in
organizations: Conceptual background, meta—analysis, and test of alternative
models. Personnel Psychology, 56(1), 155-194.

Stogdill, R. M. (1974). Handbook of leadership: A survey of theory and research. New
York, NY: Free Press.

Straus, S. G. (1996). Getting a clue: The effects of commrmication media and information
distribution on participation and performance in computer-mediated and face-to-
face groups. Small Group Research, 27(1), 115-142.

Sujan, H., Weitz, B. A., & Kumar, N. (1994). Learning Orientation, Working Smart, And
Effective Selling. Journal Of Marketing, 58(3), 39-52.

Sundstrom, E., McIntyre, M., Halfl'rill, T., & Richards, H. (2000). Work groups fi'om the
Hawthorne studies to work teams of the 1990's and beyond. Group Dynamics:
Theory, Research and Practice, 4, 44-67.

Swait, J ., & Adamowicz, W. (2001a). Choice environment, market complexity, and
consumer behavior: A theoretical and empirical approach for incorporating
decision complexity into models of consumer choice. Organizational Behavior
And Human Decision Processes, 86(2), 141-167.

Swait, J ., & Adamowicz, W. (2001b). The influence of task complexity on consumer
choice: A latent class model of decision strategy switching. Journal Of Consumer
Research, 28(1), 135-148.

Tejeda, M. J ., Scandura, T. A., & Pillai, R. (2001). The MLQ revisited - Psychometric
properties and recommendations. Leadership Quarterly, 12(1), 31-52.

Tirpak, J. A. (2000). Reachback. Air Force Magazine, 83.

Towler, A. J. (2003). Effects of charismatic influence training on attitudes, behavior, and
performance. Personnel Psychology, 56(2), 363-381.

228

Townsend, A. M., DeMarie, S. M., & Hendrickson, A. R. (1998). Virtual teams:
Technology and the workplace of the future. The Academy of Management
Executive, 12(3), 17-29.

Tyran, K. L., Tyran, C. K., & Shepherd, M. (2003). Exploring Emerging Leadership in
Virtual Teams. In C. B. Gibson & S. G. Cohen (Eds), Virtual teams that work:
creating conditions for virtual team effectiveness (pp. 183-195). San Francisco,
CA: Jossey-Bass.

Vandenberghe, C., Stordeur, S., & D'Hoore, W. (2002). Transactional and
transformational leadership in nursing: Structural validity and substantive
relationships. European Journal of Psychological Assessment, 18(1), 16-29.

Vavelas, A. (1950). Communication Patters in Task-Orientated Communication. Journal
of the Acoustical Society of America, 22, 725-730.

Wageman, R., Hackman, R. J ., & Lehman, E. (2005). Team Diagnostic Survey:
Development of an Instrument. Journal of Applied Behavioral Science, 41(4),
373-398.

Waldman, D. A., Bass, B. M., & Einstein, W. O. (1987). Leadership and outcomes of
performance appraisal processes. Journal of Occupational Psychology, 60(3),
1 77 -1 86.

Waldman, D. A., Bass, B. M., & Yammarino, F. J. (1990). Adding to contingent-reward
behavior: The augmenting effect of charismatic leadership. Group &
Organization Studies, 15(4), 381-394.

Walsh, J. P. (1995). Managerial And Organizational Cognition - Notes From A Trip
Down Memory Lane. Organization Science, 6(3), 280-321.

Walther, J. B. (1993). Impression development in computer-mediated interaction.
Western Journal of Communication, 57(4), 381.

Walther, J. B. (1995). Relational aspects of computer-mediated communication:
Experimental observations over time. Organization Science, 6(2), 186-203.

Warkentin, M. E., Sayeed, L., & Hightower, R. (1997). Virtual teams versus face-to-face
teams: An exploratory study of a Web-based conference system. Decision
Sciences, 28(4), 975.

Wofford, J ., Gerloff, E., & Cummins, R. (1977). Organizational Communication. New
York, NY: McGraw Hill.

Wofford, J. C., & Goodwin, V. L. (1994). A cognitive interpretation of transactional and
transformational leadership theories. Leadership Quarterly, 5(2), 161.

229

Wofford, J. C., Goodwin, V. L., & Whittington, J. L. (1998). A field study of a cognitive
approach to understanding transformational and transactional leadership.
Leadership Quarterly, 9(1), 55-84.

Wood, R. E. (1986). Task Complexity - Definition Of The Construct. Organizational
Behavior And Human Decision Processes, 37(1), 60-82.

Yammarino, F. J ., & Bass, B. M. (1990). Transformational leadership and multiple levels
of analysis. Human Relations, 43(10), 975-995.

Yukl, G. (1998). Leadership in Organizations (4th ed.). Upper Saddle River, NJ: Prentice
Hall.

Yukl, G. (1999). An evaluation of conceptual weaknesses in transformational and
charismatic leadership theories. Leadership Quarterly, 10(2), 285-305.

Yukl, G., & Fleet, D. D. V. (1992). Theory and research on leadership in organizations.
In M. Dunnette & L. Hough (Eds), Handbook of I/O psychology (V 01. 3, pp. 147-
198). Palo Alto, CA: Consulting Psychologists Press.

Zaccaro, S. J., & Bader, P. (2003). E-Leadership and the challenges of leading E-teams:
Minimizing the bad and maximizing the good. Organizational Dynamics, 31 (4),
377-387. '

Zigurs, I. (2003). Leadership in virtual teams: Oxymoron or opportunity? Organizational
Dynamics, 3] (4), 339-351.

230

IIIIIIIIIIIIIIIIIIIIIIIIIIIIIII

Ill/IlllllllllIll/IllIIIIIIlllllllllllllllljllII

3 1293 02845 814