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thesis entitled

THE EFFECTS OF TEAM COMPOSITION AND INCENTIVES
ON TEAM PERFORMANCE ON AN
INTERDEPENDENT TASK

presented by

Ronald Stephen Landis

has been accepted towards fulfillment
of the requirements for

M. A. Psychology

degree in

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THE EFFECTS OF TEAM COMPOSITION AND INCENTIVES
ON TEAM PERFORMANCE ON AN
INTERDEPENDENT TASK

By

Ronald Stephen Landis

A THESIS

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

MASTER OF ARTS

Department of Psychology

1992

/t/..:’“ [ll/l 7 7

ABSTRACT

THE EFFECTS OF TEAM COMPOSITION AND INCENTIVES
ON TEAM PERFORMANCE ON AN
INTERDEPENDENT TASK

By
Ronald Stephen Landi s

This thesis sought to address two factors which contribute to team
task performance: incentives and team composition. Literature on
incentives and composition was reviewed and hypotheses were
proposed concerning the anticipated interactive effect of these two
variables on team performance. The task used was adopted from
Hollenbeck, Sego, Ilgen, & Major (1991) and required participants to
assume roles within a hypothetical naval carrier team. As members
of such a team, participants were asked to make decisions regarding
the threat level presented by a hypothetical target aircraft which
had entered the team's airspace. Results suggested that neither
incentives nor team composition affected team performance.
However, previous research on the relationship of team member
ability and team performance (i.e. Tziner & Eden, 1985) was
replicated. A discussion of the results, possible limitations of the

current study, and avenues for future research are presented.

ACKNOWLEDGMENTS

I would like to take this opportunity to thank several people who
have been instrumental in helping me complete this thesis. First, I
would like to thank Dan Ilgen and John Hollenbeck, not only for their
guidance as members of my committee, but also for providing me
with the use of laboratory space, materials, and finances I needed to
collect this data. I would also like to thank several of my colleagues,
notably Mickey, Jose, Jeff, Keith, and Stephen for helping me work
through some of the issues and problems that naturally arose along
the way. Also, Jean Phillips and Doug Sego deserve thanks for
helping me collect data and showing me around the lab. In
particular I would like to thank Neal Schmitt who, as my
Chairperson, helped me through all phases of this project by
providing me with invaluable advice and incredible turnaround of
revisions. Thanks a lot Neal for keeping me focused and helping me
produce a thesis for which I can be proud. Finally, I would like to
say thanks to Sandy. You helped and supported me through all those
times that I thought about trashing the whole thing and, more
importantly, showed me what you can accomplish if you believe in

something.

TABLE OF CONTENTS

Page

LIST OF TABLES .................................................................................................. vii
LIST OF FIGURES ................................................................................................. viii
INTRODUCTION .................................................................................................... 1
Group Performance ...................................................................................... 4
Incentives ........................................................................................................ 8
Organizational Justice ................................................................................. l 4
Groups versus Teams .................................................................................. 1 6
Task Interdependence ............................................................................... 1 8
Team Composition ........................................................................................ 1 9
Proposed Model ...................... I ....................................................................... 2 4
Hypotheses ...................................................................................................... 2 4
Interaction Effects on the Endogenous Variables ..................... 2 7
METHOD .................................................................................................................. 3 6
Participants ..................................................................................................... 3 6
Design ................................................................................................................ 3 6
Simulation Task ............................................................................................. 3 6
Simulation Roles ...................................................................................... 3 7
Attributes of Targets ............................................................................ 3 8
Coordination of Roles ............................................................................ 3 8
Patrol Sessions .......... I ............................................................................... 4 0
Feedback .................................................................................................... 4 1
Procedures ....................................................................................................... 4 1

iv

 

Session 1 ..................................................................................................... 4 2

Composition Manipulation .................................................................. 42
Session2 ..................................................................................................... 42
Incentive Manipulation ....................................................................... 43
Manipulation Checks ................................................................................... 44
Dependent Measures ................................................................................... 4 4
Performance ............................................................................................. 4 4
Perceptions of Equity ............................................................................ 4 5
Cooperation ............................................................................................... 4 5
RESULTS .................................................................................................................. 46
Manipulation Checks ................................................................................... 46
Adequacy of the Individual Ability Variable............... ................... 46
Analyses of Primary Hypotheses .......................................................... 48
Hypothesis 1 ............................................................................................. 48
Hypothesis 2 ............................................................................................. 50
Hypothesis 3 ............................................................................................. 54
Hypothesis 4 ............................................................................................. 54
Hypothesis 5 ............................................................................................. 56
Hypothesis 7 ............................................................................................. 56
DISCUSSION ........................................................................................................... 6 1
Review of Results and Integration with Current Literature ...... 61
Limitations ...................................................................................................... 6 4
Directions for Future Research ............................................................... 65
LISTOFREFERENCES .......................................................................................... 68
APPENDIX A: Handbook for Team Members ........................................ 7 6
APPENDIX B: Task Knowledge Test ............... . .......................................... 84
APPENDIX C: Incentive Manipulations ................................................... 96

APPENDIX D: Questionnaire ......................................................................... 9 7
APPENDIX E: Communication Measures Used in the Calculation
of the Cooperation Index ................................................... 9 9

vi

 

LIST OF TABLES
Page
TABLE 1: Means and Standard Deviations for the Endogenous
Variables ........................................................................................... 5 1
TABLE 2: Analysis of Variance Summary for Endogenous
Variables..............................’ ............................................................. 5 2
TABLE 3: Intercorrelations Among Key Variables .............................. 5 8

vii

FIGURE 1:
FIGURE 2:
FIGURE 3:
FIGURE 4:
FIGURE 5:
FIGURE 6:

FIGURE 7:
FIGURE 8:

FIGURE 9:
FIGURE 10:

FIGURE 11:
FIGURE 12:

LIST OF FIGURES

Pages
Proposed Model of the Relationships Among Key
Variables......- .................................................................................. 2 5
Proposed Effect of Team Ability on Team
Performance ................................................................................. 2 6
Proposed Interaction of Pay and Composition on .
Fairness Perceptions ................................................................. 28
Proposed Interaction of Pay and Composition on
Degree of Cooperation Exhibited .......................................... 3 0

Proposed Interaction of Pay and Composition on Team
Performance ................................................................................. 3 2

Proposed Effect of Pay on Team Performance with

Homogeneous or Heterogeneous Teams ........................... 35
Effect of Team Ability on Team Performance ................ 4 9
Interaction Between Pay and Team Ability on

Perceptions of Fairness ............................................................ 5 3
Interaction. of Ability and Pay on Cooperation .............. 5 5

Interaction of Ability and Pay on Team

Performance .............................................................................. 5 7
Observed Relationships Among Key Variables ........... 59
Relationship Between Pay and Homogeneous

versus Hetergeneous Groups and Performance ......... 6O

viii

INTRODUCTION

As Sundstrom, De Meuse, and Futrell (1990) suggested, two
terms commonly used interchangeably in discussions of today's
organizations are work team and work group. The increased use of
these terms in discussions of business reflects the fact that teams
occupy a pivotal role in what has been described as a management
revolution (Sundstrom et al. 1990). As Hackman (1986) predicted
and Peters (1988) advised, organizations should organize every
function into self-managing work teams.

In addition to forming a critical link between the individual
and the organization, task groups are the central building blocks for
getting work done in organizations (Goodman, Ravlin, & Schminke,
1987). And as Mills (1979) points out, because groups are so
pervasive in organizations, determine, in part, the effectiveness of
organizations, and greatly affect the lives of group participants, it is
becoming increasingly important that we understand the factors that
determine high performance in task groups. It has been over
eighteen years since Steiner (1972, p. vii) suggested that, "the group
seems to have gone out of fashion." He points specifically to the fact
that researchers had shown much interest in groups until the late

1950's, when the focus was shifted to the individual level of analysis.

2
After that time, Steiner suggests that task groups, as a research area,
were largely ignored. Similarly, 'Goodstein and Dovico (1979)
asserted that research on groups has become relatively dormant. In
a recent review, Austin and Bobko (1985) also suggested that there
has been relatively little research conducted on group processes and
group performance given the fact that the productivity of a work
group is a critical component of an organization's productivity. The
relative paucity of research on groups and the growing importance of
performance involving interdependent work groups on
organizational success suggest there is a need to better understand
the factors which affect group performance.

Given the large body of research earlier in this century that
examined the extent to which incentives alter motivation and
behavior (e.g. Hull, 1943; Skinner, 1938, Taylor, 1947), and, more
recent reviews of this relationship (Campbell & Pritchard, 1976;
Guzzo, 1979), it is quite clear that financial and nonfinancial
incentives can lead to higher performance, if the incentive system is
properly designed. These conclusions have been reached by many
researchers examining the issue of incentives affecting individual
performance (Guzzo, 1979; Korman, Glickman, & Frey, 1981; Lawler
& Porter, 1967; Opsahl & Dunnette, 1966; Pritchard & Sanders,
1973). Recent literature indicates that group-based incentive
systems may also be effective in motivating groups and increasing.
group performance (Bullock & Lawler, 1984; Deutsch, 1985; Kim,
Park, & Suzuki, 1990). However, the conditions under which

different group incentive systems may be successful has received

 

3
less attention and would seem to be an important area of research
interest (Deutsch, 1975, 1985).

Because members of a small group are its most important
resource, and the subsequent outcomes of a group are a function of
the people who belong to it, Levine and Moreland (1990) assent that
understanding the characteristics and attributes of group members is
important to understanding the ultimate effectiveness of the group.
Research in the area of group composition has sought to address such
concerns. Although there have been some studies looking at how
group composition affects various group outcomes (Kerr, 1989;
Mannix, Thompson, & Bazerman, 1989; Shaw, 1981; Wood, 1985),
very little is known about how composition affects performance in
highly interdependent tasks (Tziner & Eden, 1985).

Group composition may be conceptualized in several different
ways (Levine & Moreland, 1990). In the research described in this
paper, the mix of abilities of the group's members constitutes the
manipulation of group composition. This definition of composition is
consistent with the fact that member ability is positively related to
group productivity (Hill, 1982). However, as O'Brien and Owens
(1969) pointed out, the specific ways that the different combinations
of ability and motivation affect group productivity have yet to be
satisfactorily investigated. Therefore, because group performance on
interdependent tasks remains an integral part of the success, or
failure, of organizations, it is important to determine the factors
which may affect performance. It will be argued here that (1) the

incentive system the group is operating under and (2) the ability

 

4
composition of the group members are two critical factors which

influence group performance.

Group Performance
McGrath & Kravitz (1982) pointed out that one major thrust of

group research has been a concern with the task performance
effectiveness of groups, as opposed to individuals, and with effects of
a variety of input factors and operating conditions on such task
performance. While no comprehensive theories of group behavior
have been systematically developed and tested (Dyer, 1984), several
researchers have offered descriptive models of group behavior. A
cursory examination of these existing "models" of group effectiveness
(Dyer, 1984, Klein & Mulvey, 1989) may serve to illustrate the
numerous factors which have been suggested as influential in
determining group performance. For example, Steiner (1972)
proposed that group productivity was a function of potential
productivity (the combined capability of group members) minus

. process losses (factors such as those related to low motivation and/or
coordination). However, this conceptualization of group productivity
suggests that group processes always must have a negative effect on
group output.

Another general model of groups is the systems input-process-
output approach (Hackman & Morris, 1975; Roby, 1968; Shiflett,
1979). The Hackman & Morris (1975) view hypothesized three
major variables, effort by group members, task performance

strategies, and member knowledge and skills, as the primary

5
influences of group performance. Specifically, it was expected that
the group interaction process would influence these variables in that
in instances where individual skills are most important in
determining effectiveness, process loss should be low, whereas in
situations requiring interdependence, this process loss should be
high. In contrast, Roby (1968) viewed group performance as
resulting from inputs to the group from the task environment. At
the time these input observations are made, they are "digested" and
placed in the service of an "executive" faculty, which in turn relates
the input information into group goals and tactics (Dyer, 1984).
According to Dyer, four input subfunctions are related to this
processing of information by the group; observation, information
routing, storage and forecasting, and patterning, while three
functions are seen as handling the cumulative effects of actions, the
pacing of the performance cycle, and procedural changes during
continuous group performance; mapping and planning, addressing,
and phasing. While this approach is potentially the most detailed
general input-process-output model, it'has received little empirical
support.

Gladstein (1984) offered a model which included variables like
group composition and structure, group process, and the task itself as
possible factors which might influence group performance.
Specifically, Gladstein suggested that factors such as the group
composition, group structure, resources available to the group, and
rewards would influence certain group processes (i.e. communication,

strategy development, etc,). These variables were then expected to

6
influence group effectiveness, through the moderator of task type.
Once again, however, this model has received limited support. Two
other theorists, Shaw (1976) and Dieterly (1978), have also focused
on the task as central to understanding group performance and
behavior. For example, Shaw (1976) proposed that group tasks
differ on the following dimensions: difficulty, solution multiplicity,
intrinsic interest, cooperation requirements, population familiarity,
and intellectual-manipulative requirements. Alternatively, Dieterly
(1978) discriminated between tasks not dependent upon a team
context and those that did depend upon use of a team. Along similar
lines, Naylor and Dickinson (1969) suggested that team performance
was a function of task structure, work structure, and communication
structure (Dyer, 1984).

While these models represent several researchers' attempts at
describing group behavior and performance, Goodman, Ravlin, &
Argote (1986) and Goodman, Ravlin, & Schminke (1987) criticized
these, and other current, models of group productivity for being too
general and difficult to test. They have suggested that theorists' time
would be better spent developing more specific models, defining
group effectiveness more carefully, and considering new ways in
which effectiveness is influenced by a group's task, structure, reward
systems, and composition.

From the above discussion it is obvious that much ambiguity
exists with respect .to understanding the antecedents of group
performance. Taking the advice of Goodman et a1. (1986, 1987), the

proposed research represents an attempt to develop a more specific

7
model of group performance. Examining the current models of
performance, it becomes apparent that while these authors differ
with respect to what specific aspects of groups they believe are
likely to affect group performance, they do have some aspects in
common. Specifically, most all of them contain some notion that the
composition of the group and certain other factors (i.e. task,
motivation) influence group performance.

While these variables represent only two types of variables
commonly associated with models of group performance, the
consistency with which they appear in various discussions would-
seem to indicate their importance as influences of group
performance. As a result of this importance, any attempt at
developing a more specific model of group performance, as suggested
by Goodman et a1. (1986, 1987), should include these two types of
variables at a minimum. Theoretically, these variables are appealing
as potential influencers of group performance, in that at the
individual level, performance has often been defined simply as some
function of ability and motivation (Locke & Latham, 1990). Thus, it
would seem reasonable to expect similar relationships at the group
level, with the incentive serving as the motivation component and
group composition, in terms of member abilities, serving as the group
ability component.

One of the aims of developing a model of group performance is
to aid organizations in increasing productivity, satisfaction, etc (Dyer,
1984). Because of this, variables which are included in such a model

should be variables which are relevant to, and controllable by

8
organizations. Clearly, the incentive system is one such variable
which could be easily manipulated by organizations. In addition, the
composition of work groups within an organization is also under that
organization's control. Member abilities, however evaluated, are
known by the organization and could easily be used to establish
work groups comprised of varying ability levels.

As a result of the above discussion of the current state of group
performance research, it should be apparent that there exists little in
the way of well established and tested models of performance. Also,
it is clear that attempts at developing newer theories of this type-
would be most likely beneficial if they adopted a relatively narrow
focus. Thus, the purpose of this research proposal is to present and
test a relatively simple model of group performance using variables,
group composition and incentive system, which are expected to be
important from both past research and theory. Further knowledge of
the effects of these variables may be practically useful to
organizations as they can be controlled or manipulated by these
organizations.

The next two sections of this paper provide the empirical
research and theoretical arguments supporting the position that
incentives and group composition are major determinants of group

performance.

Incentives
The Empirical Law of Effect states that "...the consequence of a

response is an important determiner of whether the response will be

9

learned" (Wilcoxon, 1969, p. 28). In other words, people tend to do
those things that they find positive and they tend not to do those
things that they find negative (Pinder, 1984). This is the primary
proposition on which reward and incentive systems are based. At
the individual level, there is abundant literature suggesting that
when the incentive system is properly designed, individual
performance can indeed be increased (Campbell & Pritchard, 1976;
Guzzo, 1979; Guzzo, Jette, & Katzell, 1985; Pinder, 1984; Steers &
Porter, 1987). Understanding how the incentive system affects
individual performance is crucial in determining how to pay
individuals working on independent tasks. However, given that
much of the work in today's organizations is accomplished by task
groups (Austin & Bobko, 1985), it becomes important to understand
how the incentive system influences the performance of groups.

More than thirty years ago, March and Simon (1958) suggested
that the issue of group incentives was important in that so much of
the work that is accomplished in many organizations results from the
efforts of several individuals, often working at separate but highly
interdependent jobs. Parceling out rewards among members of a
work group, all of whom have something to do with the successful
accomplishment of the group's goals, is often a sticky problem
(Pinder, 1984). As Hackman (1987) suggests, when rewards .are
given to individuals on the basis of managers' judgments about who
has contributed most to a group product, dissension, low
productivity, and conflict often develop within the group. It is a

problem routinely faced by managers where the reward system has

10
traditionally focused on the identification and recognition of excellent
individual performers.

Recent research on incentives has offered two contradictory
suggestions concerning the effect of group-based reward systems on
performance. Pritchard, Jones, Roth, Stuebing, & Ekeberg (1988)
examined the effects of feedback, goal setting, and group-based
incentive interventions on group performance. A three stage
intervention was implemented in which task groups were first given
feedback using the Productivity Measurement and Enhancement
System (ProMES), which was based on the theory of organizational
behavior presented by Naylor, Pritchard, and Ilgen (1980). Goal
setting was then added to feedback. And, finally incentives, in the
form of time off, were added to feedback and goal setting. Results
indicated that feedback produced a gain in productivity over
baseline of 50%; feedback plus goal setting, 75%; and feedback plus
goal setting and incentives, 76%. From these results, Pritchard, et al.
concluded that incentives added nothing beyond feedback and goal
_ setting.

Although, based on the design and results of the study, these
conclusions may be warranted, they are, nonetheless, problematic.
For example, it may be that incentives added nothing to performance
due to an order effect in the interventions. That is, there may have
been a ceiling effect operating, such that because units were already
working under two other interventions, further increases in

performance were not really possible. Pritchard, et a1. discount this

l 1
possibility by arguing that if productivity can be increased to its
maximum without incentives, they may not be necessary.

However, there are other alternative interpretations of the
results that make the assumption that incentives do not serve to
increase group performance a bit premature. For example, these
results were obtained from one specific situation in which incentives
were not found to be effective. One must proceed with caution when
generalizing these results to all situations in which incentive systems
may influence performance. To illustrate, it may be that time off is
not an incentive which is offered in all situations, or moreso, even'
feasible in all settings. Also, there is nothing to suggest that time off
is an equivalent motivator to monetary incentives. It may be that
although time off seemed to be something that the participants in the
Pritchard, et a1. study valued, in other settings, other incentives (i.e.
monetary incentives) may be valued more.

This contention has support in research that has been
conducted comparing the effectiveness. of group incentive systems
with individual incentive systems, as they impact performance
(London & Oldham, 1977; Milkovich & Newman, 1987). One of the
problems with group incentive research which these researchers
note may have led others to erroneously conclude that group
incentives may not be effective, is that prior studies have often
failed to include one important factor: In comparisons of group
versus individual incentive plans it is typical to contrast one group
plan against multiple individual incentive plans. Thus, a specific

group plan may not be as effective as an individual one, but that

12
does not necessarily mean that m group plans are as effective as
individual plans. As London and Oldham suggest, "before the
conclusion is reached that group incentive systems are less effective
than individual incentive systems in enhancing employee work
performance, several types of group incentive schemes should be
examined".

London & Oldham (1977) proceeded to test this proposition by
comparing multiple group plans versus multiple individual incentive
plans. The group plans were (1) incentives based on the average
performance of the entire group, (2) incentives based on the highest
performer in the group, and (3) incentives based on the lowest
performer in the group. Productivity under these group plans was
compared against results using an individual piece-rate system and a
fixed-rate system. Performance was about equal under the high-
performance group incentive system and the individual piece-rate
system, with both plans resulting in significantly higher performance
than any of the other plans.

While London and Oldham acknowledge that these results need
to be replicated before any firm conclusions can be reached about
the effectiveness of group incentive plans, they do suggest that group
plans gen be structured to approximate the productivity results
obtained under individual plans. In fact, many of the field studies
reporting results from group incentive plans, which were primarily A
Scanlon- or Rucker-type plans, indicated productivity increases in
the range of 4.5 percent to 23.7 percent for periods of time between

1 and 17 years (Milkovich & Newman, 1987; Puckett, 1978), From

-

13
these results it seems that it is reasonable to believe that group plans
in general can be effective motivators of performance. And, given
that groups are completing much of the work in organizations,
finding incentive plans which increase performance in these settings
seems to be of increasing importance.

Given that the study of group incentive plans is important, the
next issue is what types of plans are effective and feasible in what
settings. Although the results expressed by Milkovich and Newman
(1987) and Puckett (1978) suggest that group plans may be
effective, they reflect somewhat dated research and do not employ
group incentive systems which may or may not be effective in
today's work settings. For instance, Scanlon plans, which were one of
the primary group incentive systems studied, are generally applied
at an organizational level. As a result, these types of plans may not
be effective as a motivator of 11ng group performance. In
comparison, the type of incentive systems that London and Oldham
(1978) employed in their study allowed rewards to be distributed to
individuals within a task group based more directly on individuals'
performance within the group than does a Scanlon-type plan.

However, even the incentive systems used by London and
Oldham (1978) may be subject to problems when applied in other
settings. For instance, while being effective in a non-interdependent
work group, pay based on the highest performing individual may not
be so effective when the setting is an interdependent one. This is
possible since the performance of any individual on an

interdependent group task is, to some degree, constrained by the

14
performance of all other members. This could result in the
performance of the best individual, and subsequently the group
performance being determined by the lowest performing member.
Thus, the reward system, as manipulated by London and Oldham,
may actually be based on the lowest performer, and not the highest
performer. This inconsistency may result in low group performance
and dissatisfaction, as a result of the perceived inequity of the

reward system.

Organizational Justiee.

A related line of research has been concerned with individuals'
perceptions (of fairness of organizational rewards (Kanfer, 1989). In
this literature a distinction is made between two distinct perceptions
of fairness: procedural justice and distributive justice (Greenberg,
1987). Procedgral justice refers to the degree to which individuals
feel that the we in which they are rewarded is fair.
Alternatively, gistribgtive justiee addresses the individuals'
perceptions of fairness related to the allocation of rewards across
persons (i.e. fairness of outcomes). While procedural justice concerns
are relevant in many real world settings, within a particular situation
(i.e. controlling for procedural justice perceptions) issues of
distributive justice would be a primary component in an individual's
perceptions of fairness of a reward system.

Research across several areas (Karambayya & Brett, 1989;
Organ, 1990; Pfeffer & Langton, 1988) has examined the impact of

perceptions of distributive justice fairness using a number of

15
outcome variables. In general, this research has suggested that "in
cooperative relations within which economic productivity is a
primary goal, equity rather than equality tends to be the chief
principle of distributive justice" (Kabanoff, 1991). In contrast, when
fostering or maintaining an enjoyable social relationship is the goal,
equality tends to be the dominant distributive principle. Thus, in a
cooperative situation (i.e. one which requires high interdependence)
in which individuals are working toward a common production goal,
it would be expected that individuals would feel more fairly treated
when rewards are distributed relative to individual inputs, rather
than equal rewards based on total team performance..

Some research related to this suggestion has been conducted in
the area of incentive research. Lawler (1981) suggested that when
pay is based on level of aggregated individual performance,
cooperation is normally increased dramatically. Moreover, as Organ
and Konovsky (1989) point out, research in the area of incentives
with respect to cooperative behaviors indicates that reward systems
that cause sharp differences in member outcomes may inhibit
cooperation. Thus, from this study it would appear that group
incentive systems in which individuals receive equal outcomes based
on the performance of the group would lead to high levels of
cooperation. However, given the above discussion, it may be that
what appears to be a principle of equality may in fact be equity.
That is, in teams where individuals contribute the same amount to
the team's performance, one would expect that greater satisfaction

would result from equal rewards to all members from both an

16
equality and equity perspective. Alternatively, when individuals
contribute different amounts to task performance, one would expect
that greater satisfaction, and thus greater cooperation, would result if
member outcomes were distributed in an equitable manner. If the
task is interdependent, this increased cooperation should translate

into increased performance.

 

Groups versus hams

An issue that arises whenever one does research with groups,
and one that deserves attention before undertaking a review of the
group composition literature, is that of defining the terms team and
group (Dyer, 1984). This distinction is difficult to draw in that since
few researchers have explained why they have called the groups
they studied "teams", ambiguity exists as to the precise meaning of
the two terms. Indeed, as the presentation of Work Learn: by
Sundstrom, De Meuse, and Futrell (1990) highlights, the terms ml;
team and werk green are used interchangeably to suggest the same
. concept. Sundstrom et a1. (1990) suggest that a work team (or

group) is an ...interdependent collection of individuals who share
responsibility for specific outcomes for their organizations." Similar
discussions Of this type by other authors (e.g. Komaki, Desselles, &
Bowman, 1989; McGrath & Kravitz, 1982) also indicate a lack of clear
distinction between the two terms.

Given this ambiguity with respect to the difference between
work groups and work teams, an examination of the global

definitions of group and team may prove illuminating. Forsyth

 

17
(1987) provides a clear, succinct definition of groups by suggesting
that a group may be defined as any setting in which two or more
individuals interact. While this definition may, at first, seem overly
broad, it should provide a basis for comparison with one potential
definition of team. Dyer (1984) proposed the following as an
integration of some of the previous attempts: "A team consists of (a)
at least two people, who (b) are working towards a common
goal/objective/mission, where (c) each person has been assigned
specific roles or functions to perform, and where (d) completion of
the mission requires some form of dependency among the group ,
members". From these two definitions it would appear that the
concept of team is encompassed under the rubric of group. That is,
teams are specific instances of groups. Further evidence for this
conceptualization is provided by McGrath and Kravitz (1982), where
they point out that "...one major thrust of gm [italics added]
research has been a concern with the task performance effectiveness
of groups". This suggests that the research on work teams or work
groups is a subset of the research on groups in general.

While this information may provide a distinction between the
concepts of groups and teams, there remains the problem of
distinguishing between the use of the specific concepts of wk
teams and groups. The inconsistency would appear to be that while
at a macro level, groups and teams are different concepts, when the
term well; is added to both they are often operationally equivalent.
As Dyer (1984) suggests such definitional issues are not trivial. How

does one decide if researchers are really studying the same entity?

1 8
Perhaps the difference between the use of the terms work group
versus work team arises out of the differences between the
disciplines of social psychology and industrial/organizational (I/O)
psychology. That is, in social psychology literature, the term group is
predominantly used (e.g. Levine & Moreland, 1990; McGrath &
Kravitz, 1982), while in HQ the term team may be the preferred
term (e.g. Sundstrom et al., 1990).

While the differences, if any, between these terms deserve
attention from researchers, the present study is not that large in
scope. Instead, the previous discussion was undertaken to provide a
background of the issues that were considered in choosing the term
that will be used in the present study to describe the unit of analysis.
Because of the constraints of the definition of team as provided by
Dyer (1984), as well as others (e.g. Komaki, Desselles, & Bowman,
1989), the term which will be adopted in the present study is 191k
teem. This term reflects the notion that the unit of analysis of
interest in this study is a collection of individuals working on an
interdependent task. This conceptualization of work teams is
consistent with that offered by Dyer (1984) in that these groups (a)
are comprised of three individuals, (b) require individuals to pursue
a common goal, and (0) require interdependency of actions of the

group members.

Task Interdependence

Given the above discussion of work teams, the next issue that

must be addressed is that of task interdependence. Task

 

19
interdependence has been defined as a situation in which "...the
members of a group must actually work together to accomplish a
task" (Mitchell & Silver, 1990). Mitchell and Silver suggest that
several conditions define a task as interdependent: Team members
may exchange information and/or resources (Thompson, 1967), they
have roles that require a coordinated division of labor (Thomas,
1957), or they use behaviors that contribute to their own
performance plus the performance _of the other members, and vice
versa (Van de Ven, Delbecq, & Koenig, 1976). Thus, there is some
latitude in distinguishing situations that can be considered examples
of interdependent tasks.

Another issue is that of individual task interdependence and
team task interdependence. The difference is that individuals can
work alone at a task yet be interdependent with people performing
other tasks or jobs (individual interdependence) or a team can work
on the same task and be interdependent in carrying it out (team
interdependence) (Mitchell & Silver, 1990). It is the latter type of
interdependence that is of interest here. Examples of this type of
team include strategic planning committees, semiautonomous work

teams, symphonies, and surgical teams (Mitchell & Silver, 1990).

Team m iion

Team composition can be defined as the mix of characteristics
and attributes of the members of the team. Because members of a
team are its most important resource, team composition should lead

to the subsequent outcomes realized by the team (Levine &

 

 

20
Moreland, 1990). Because of the importance of understanding the
factors which affect team performance, there has been considerable
research which has focused on team composition issues. However,
within the area of team composition, there has been considerable
diversity with respect to what characteristics of the members, and
also the team as a whole, are important. Research has examined
issues of team size (Kerr, 1989; Markham, Dansereau, & Alutto, 1982;
Gooding, & Wagner, 1985), team demographics (Wagner, Pfeffer, &
O'Reilly, 1984; Wood, 1985), member personalities (DeBiasio, 1986),
and member opinions.

Because team size is a variable which naturally acts as a
constraint on other team variables, it is a matter which deserves to
be addressed at this point. Size has several consequences for the
functioning of a team (Mannix, Thompson, & Bazerman, 1989). For
instance, size impacts on the range of knowledge, skills, and abilities
that are available to the team (i.e. the resources of the team). It is
possible then, that larger teams, have access to more resources
within the team. However, as Levine & Moreland (1990) point out,
as a team grows larger, it generally changes for the worse. People
who are members of larger teams are normally less likely to
cooperate with other members. And, although larger teams are
potentially more productive, coordination problems and motivation
losses often hinder the achievement of this potential (Gooding &
Wagner, 1985). Also, as Mannix, Thompson, & Bazerman (1989)
suggest, as the size of the team increases, so do the problems

associated with explaining what occurs within the team. Given that

21
team size influences the potential problems associated with
researching team phenomena (Mannix, Thompson, & Bazerman,
1989), it is desirable to clearly specify the size of the team when
testing the impact of variables, interpreting the results, or when
giving procedural advice. _

With that in mind, at this point it would be useful to define the
team size that will be assessed in the proposed research. Because the
focus of this study is interdependent work teams in organizations,
and also the aforementioned problems associated with conducting
research using large teams, small teams will be the unit of analysis.
In the literature, a small team is defined as having fewer than 20
members, although most research on small teams has focused on
teams with fewer than five members (Shaw, 1981). As a result of
these considerations and the task which will be used in this study,
team will be defined as, and hereafter referred to, as a three- '
member team of individuals working on an interdependent task.

It should be noted that defining team size in this manner may
restrict the generalizability of results. For this reason, it is important
to recognize that any conclusions which may be drawn must take this
fact into account and recognize that three person teams do not
encompass the spectrum of possible team sizes. Although it would
be optimal to use teams of varying sizes to allow conclusions about
small teams in general, it was not feasible in the current study. Also,
given that the area of team performance has received such little
attention, any results obtained would prove beneficial for stimulating

further research in this area. However, the impact of the

 

22
manipulated variables must be assessed keeping in mind the specific
size of the team under examination.

As Foushee (1984) and Hill (1982) suggest, individual member
abilities are a major determiner of the ultimate performance of the
team. Given that team performance is the outcome of interest here,
the other composition factor which becomes important is that of
member abilities. And, although there have been many studies of
team performance, Tziner and Eden (1985) point out that very little
is known about how composition factors affect performance on
interdependent tasks.

The abilities of team members have been the focus of some
studies on team composition (Bantel & Jackson, 1989; Tziner & Eden,
1985). Specifically, Tziner and Eden proceeded to examine the effects
of the ability and motivation distribution of team members using
three person tank crews. Each crew contained three soldiers who
were either high or low in general abilities. Results indicated that
the more high-ability soldiers a crew contained, the better the crew

performed. However, the abilities of different members of the team
I produce interactive effects on performance. For instance, crews with
all high ability members performed better than expected, while
those crews ‘ with all low ability members performed more poorly
than expected. These results would seem to support the suggestion
of Hill (1982) that member abilities are a critical factor in
determining the team's performance.

Another issue involved in dealing with team composition as a

variable of interest is whether it is considered an outcome of other

23
situational factors or whether it is a determinant of team
performance (Levine & Moreland, 1990). The examination of team
composition as a consequent variable has primarily focused on
naturally occurring teams, where composition can vary freely. The
primary finding of this line of research is that people strongly prefer
smaller teams (Levine & Moreland, 1990). Also, most naturally
occurring teams contain members who strongly resemble each other
in terms of certain key characteristics (e.g. age, interests). These
results would seem to suggest that in teams which are not naturally
occurring (i.e. work teams), member satisfaction would be highest-in
small homogeneous teams.

Other researchers see composition as a variable which, if
changed, results in the change of a target (dependent) variable.
Research cited previously (i.e. Foushee, 1984; Tziner & Eden, 1985)
viewed composition as just such a variable. Given that the purpose
of this study is to examine the effects of composition and incentives
on team performance, composition will be similarly viewed as a
causal variable. Following the work of Tziner and Eden (1985), it is
proposed that teams which contain uniformly high ability individuals
will perform much better than those teams which are mixed, and
those teams which contain all members of low ability will perform

much worse than those teams with members of mixed abilities.

24

Pr M 1

Given the above discussion of the literature on incentive
systems and team composition effects on team performance, it is
proposed that both incentive system and team composition will
directly influence team performance. In addition, given the research
on the effects of team incentive systems on the degree of cooperation
that is exhibited by team members, it is proposed that cooperation
will be a function of the type of incentive system under which a
team is operating. Specifically, it is expected that individuals
receiving equal allocation in teams will engage in more cooperative
behaviors than those in the individual incentive condition. Also,
because cooperation leads to greater performance on interdependent
tasks (Mitchell & Silver, 1990), it is expected that the degree of
cooperation will serve to mediate the relationship between
incentives and performance. The hypotheses briefly described here

and implicitly in Figure 1 are explicitly stated below.

Hypotheses

The first hypothesis relates to the expected effect of team
composition, manipulated with respect to individual ability on the

task, on team performance.

Hypothesis 1: The performance of three person teams on an
interdependent task will be positively
correlated with the average ability level of the
team members (See Figure 2).

25

Figure 1

Proposed Model of the Relationships Among Key Variables

 

 

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26

Figure 2

Proposed Effect of Team Ability on Team Performance

 

 

 

 

High -— 4.
Performance
+
Low ——
' l :
-A11 Al“ 1 High All
Low Mod. 1 Mod. High
1 Low.

Group Composition (Ability)

27
Intereetien Effeets en the Endegeneps Variables. The following set of
hypotheses deals with the expected effect of the interaction between
team composition and incentive system on the three endogenous
variables: perceptions of fairness, degree of cooperation, and team
performance. These hypotheses are stated below along with a
rationale for each.

As suggested by the distributive justice literature (e.g.
Greenberg, 1987), individuals make judgments regarding the fairness
of the allocation of outcomes. Expectations regarding distributive
fairness are met when there exists an equitable distribution of
rewards across individuals relative to their inputs. Thus, perceptions
of fairness are based primarily on individuals' expectations of
congruence between what a person puts into and gets out of a task.
That is, if inputs are congruent with outcomes (i.e. equitable), then
the individual will perceive a situation of fairness. If they are not
congruent, then an unfair situation will be perceived. In this
experiment, these inputs are likely to be most heavily influenced by
an individual's ability, while the outcome is the money they receive.

The specific hypothesis is stated below and depicted in Figure 3.

Hypothesis 2: In three person teams working on an
interdependent task, team composition will
interact with the incentive system in such a

way that in:
(a) heteregeneeps ability teams in which team

members are paid for their individual
performance, perceptions of fairness will be
greater than in teams in which members
receive equal pay based on team performance,
while in

28

Figure 3

Proposed Interaction of Pay and Composition on Fairness Perceptions

 

 

W
ngh _— x--x Individual
o--o Group
x
Perceptions 0—0 , 0
. x x x
of
Fairness
0
Low
| | I I

 

 

I I I I
Low Mod Mix High

Composition

29
(b) hempgenepps ability teams, method of pay

will not influence individual perceptions of
fairness.

Katz and Kahn (1978) suggested that reward systems that
result in sharp differences in member outcomes would result in less
cooperation among team members. The implicit assumptions of this
position are (1) that individuals contribute equally to the task and
(2) that equality is the overriding concern of team members.
However, these assumption may not always be tenable (Adams,
1964). For instance, when the task is interdependent and individual
members contribute differentially to the task, equal rewards may,
result in less cooperation due to feelings of inequity, as the previous
review of the fairness literature illustrates. Thus, the nature of the
task (i.e., the degree to which task completion requires
interdependent effort) and the relative inputs of each team member
must be taken into account when examining the effect of the
incentive system on the degree of cooperation exhibited by team
members.

Hypothesis 3: In three person teams working on an

interdependent task, team composition will

interact with the incentive system in such a
way that in:
(a) MW in which team
members are paid for their individual
performance, members will exhibit a higher
degree of cooperation than members in those
teams paid equally based on team

, performance, while in
(b) homegeneeps ability teams, method of pay
will not influence the degree of cooperation
exhibited by team members (See Figure 4).

30

Figure 4
Proposed Interaction of Pay and Composition on Degree of

Cooperation Exhibited

 

Bay Cpnditjen
ngh —— x--x Individual
o--o Group
x
Degree 0—0 9
x x x
of
Cooperation
0
Low ——

 

| l l I
l l l l
Low Mod Mix High

Composition

31

As previously stated, ability and motivation are the two

primary influencers of task performance. The fourth hypothesis

addresses the expected effect of these two variables, at the team

level, on team performance. It is briefly stated below and

graphically presented

Hypothesis 4:

in Figure 5.

In three person teams working on an
interdependent task, method of pay will
interact with team composition such that:

(a) in heterpgeneeps ability teams, team
performance in conditions where persons are
paid based on individual performance will be
greater than teams in which individuals are .
paid equally based on team performance, while

(b) in homegeneops ability teams, method of

pay will have no influence on performance.

The next two hypotheses address the expected relationships

among the variables in Figure 1 which have not previously been

discussed.

Hypothesis 5:

Hypothesis 6a:

Hypothesis 6b:

The three endogenous variables, perceived
fairness, degree of cooperation, and team
performance, will be positively correlated.

As depicted in Figure 1, it is hypothesized that
perceptions of fairness will mediate the
relationship between the interaction of team
composition and incentive system and degree
of cooperation.

As similarly depicted in Figure 1, degree of
cooperation is expected to mediate the
relationship between perceptions of fairness
and team performance.

While not central to the present experiment, the data also allow

for the examination of a final hypothesis. This hypothesis is related

32

Figure 5

Proposed Interaction of Pay and Composition on Team Performance

High --
o
x
x
Team 24mg
0
Performance x x--x Individual
0 o--o Group
0
x
Low ——
I I I I

 

 

Low Mod Mix High

Composition

33
to the expected effect of the interaction of team composition and
incentives on the performance of all homogeneous teams versus all
heterogeneous teams. Because the average ability level of these two
types of teams is equivalent, this question of how to best divide up a
set of individuals with different abilities can be addressed. That is,
should a team consist of individuals whose abilities are similar, or
should teams be comprised of individuals with a mix of ability levels
to maximize performance.

Practically, this issue is dealt with most dramatically in the
professional sports venue. Managers and coaches regularly are
required to make the decision of how to best combine. the team's
talent in order to achieve maximum performance. For example, in
hockey, this issue might be manifested in the following scenario.
Given that a team has several "all-stars", several average players,
and several lower ability players, how should lines be formed from
this team of individuals. That is, is it better to use all the "all-stars"
on the same line, or is it better to distribute them across several
lines? One might reasonably suggest that the answer to this question
could be answered by saying that in some situations (e.g. who is the
opposing team, are there injuries, etc.) one combination scheme
would be best and in others, the other approach might be most
beneficial. Certainly, other types of organizations are confronted
with similar. problems with how best to distribute employees'
abilities. In these settings one of the key situational variables would
be the pay system which the employees are being rewarded under.

Thus, operating under some pay systems it may be more productive

34
to assemble people with similar talents, while with other systems it
might be more useful to team peOple together who vary on their task
proficiency. The following hypothesis is proposed as what might be

expected in two such instances.

Hypothesis 7: Team composition will interact with the
incentive system such that the mean
performance of all homogeneous ability teams
will be higher than heterogeneous teams under
conditions of equal pay based on team
performance, while heterogeneous teams are
expected 'to perform better than homogeneous
teams in the individual pay condition (See
Figure 6).

35

Figure 6
Proposed Effect of Pay on Team Performance with Homogeneous or

Heterogeneous Teams

 

 

High -—
x x--x Individual Pay
o--o Group Pay
Performance

x 0
Low -—

I - I

Homogeneous Heterogeneous

Composition

 

METHOD

Partieipants

Participants were 126 undergraduate students from
introductory psychology and management courses at Michigan State
University. These individuals were combined to form 42 three-
person teams. A power analysis conducted assuming a medium
effect size suggested that this sample size provided statistical power
at the .60 level (Cohen, 1988) . Due to the nature of the ability
manipulation, complete random assignment of persons to teams was
not possible. As a result, after trichotomizing individuals relative to
ability level, within ability level individuals were randomly assigned
to the resulting 42 teams.
Design

The design was a 2 (team incentive) x 4 (team composition) x
15 (Trials) mixed model. Incentives and team composition were
manipulated as between-subjects facets, while trials was a within-
subjects facet.
figuration—Task

A computer simulation of a navy "command and control" team '
developed by Hollenbeck, Sego, Ilgen, and Major (1991) was chosen

for use in this study. This team is comprised of persons who assume

36

37
the roles of Commanding Officer (C0) of a Carrier, an AWACs
reconnaissance plane, a Coastal Air Defense (CAD) unit, and a Cruiser
unit. Each individual is seated in front of a computer which
corresponds to her/his role. These computers are then networked
such that individuals can communicate with each other. Slight
modifications to the original task were made to allow for the use of
three-person teams. The team's mission is to monitor aircraft (i.e.
targets) that come through the "airspace" surrounding the carrier
group and to make team decisions about how to respond to the
aircraft. Instructions stress the importance of correct decisions by
asking team members to make certain that decisions be made which
minimize loss of life resulting from attacks on ships in the task force,
while at the same time making sure that no friendly military or
civilian aircraft are shot down.

Simulation Rules. There were four roles in this simulation,
corresponding to each of the four members of the Carrier Group. The
leader was the C0 of the Carrier. Within the context of the current
experiment this role was played by a confederate. The other roles
included the C0 of the AWACs unit, the C0 of the Cruiser unit, and the
C0 of the CAD unit. Each of these persons could measure a certain
number of characteristics of the incoming aircraft entering the
airspace. Based on these measured attributes, each team member
was asked to decide on one of seven alternatives for each incoming
aircraft (i.e. target). These alternatives ranged from ignore (least
aggressive) to defend (most aggressive). See page two of Appendix A

for a complete description of each of the alternatives. After

3 8
measuring and communicating with one another regarding the
incoming target, individual members were asked to send their
recommendation to the C0 of the Carrier. The Carrier then simply
averaged these recommendations to arrive at the team decision for
that target.

Attributes ef Taggets. The incoming targets could be measured
on nine attributes. These attributes included speed, altitude, size,
angle, IFF, direction, corridor status, radar type, and range. Page
three of Appendix A provides a list of these attributes with the
ranges of possible values for each. The level of threat of each target
could be determined by its standing on these attributes. Five
combination. rules determined the danger associated with any target.
These rules are summarized on page four of Appendix A along with
an example of how they might be combined.

Webs. As previously stated, each team member
had the ability to measure four attributes related to the incoming
target. This resulted in individual members having access to two
unique pieces of information related to the aircraft (i.e. neither of the
other members has access to these attributes) and two redundant
pieces of information (i.e. one of the other members also has
information on that attribute). In addition to being able to measure
these pieces of information, individuals were trained to know exactly
how raw data on these attributes can be translated into terms of
"non-threatening," "somewhat threatening," and "very threatening."
With respect to determining the level of threat, individuals were

trained on several combination rules. Thus, while all individuals

 

 

3 9
knew how the information should be combined, they were not able
to measure all of the necessary information.

Sharing of information among the team members was
accomplished through the use of several available functions. In
addition to being able to measuse certain characteristics of the target,
individuals also had the options of querying, receiving, and sending
information from other team members. The my command allowed
any team member to ask any other team member for information
regarding a given characteristic of the target. Receiving allowed a
team member to look at a query from another member, while the-
seue command transmitted the response to a query. Another
function which was available to team members was a transmit
command. This allowed individuals to send text messages to each
other. However, it was stressed to participants that this function
potentially required more time than the other communication
sequence and they would be making their decisions in a relatively
short amount of time. Through the utilization of these commands,
team members can exchange information with each other and gain
characteristics of the target which alone they could not measure.

By way of example of a completed sequence using the above
commands is the communication between the Cruiser and the CAD.
If the Cruiser needs the speed of the target and knows that the CAD
can measure .this attribute, the Cruiser would query the CAD as to
this attribute. The CAD would receive this query and then send the
speed information to the Cruiser. The communication sequence

would be completed by the Cruiser receiving this information from

 

 

40
the CAD. It is important to note that, at any point in this sequence,
the communication could break down. For example, the CAD could
choose not to respond to, or even to look at, the query sent by the
Cruiser. Also, assuming the CAD actually responded to the Cruiser's
request for speed, the Cruiser may not look at the CAD's response.
Thus, while opportunity exists for individuals to cooperate with each
other, this process may not always lead to a successful coordination
of effort.

Patrel Sessien. Patrol sessions refer to the time that the team
is responsible for monitoring the airspace. During this time, each
individual team members’ monitor had four icons representing the
four stations of the carrier group. Also included on this screen was a
blinking red dot indicating that an aircraft was in the team's
airspace. During each of these sessions the team had a certain
amount of time, which also appeared on the screen, in which to make
a recommendation regarding this target. When there was 30 seconds
left in the session the red dot began to blink and beep at an
increasing rate. Because the leader had to make a final decision
' before time ran out, each of the other team members were required
to send their recommendations before this point. As the leader (i.e.
the Carrier) was a confederate in this experiment, the team's
judgment was the average of the three recommendations made by
the other members. If any individual failed to make a
recommendation regarding the target, their response was treated as

an ignere recommendation.

 

 

 

41

Feedback. When a trial (i.e. a patrol session) was over, all team
members received both a computer and an oral report as to how well
the team performed. The computer report appeared on the
computer screen after the trial and gave them information on what
their individual decisions were, what the team's decision was, and
what the correct response should have been. The oral feedback
presented by the experimenter closely resembled that presented by
the computer except that it presented a cumulative total of the
responses made by individuals, the team, and the correct decisions.
This feedback was designed to allow participants to monitor their
own, as well as other members and the team's, performance over the
fifteen trials.

As previously described, there were seven potential
recommendations individuals and teams could make (see Appendix
A). From these seven decisions, there were five potential outcomes
from a trial ranging from a but, which indicated that the team's or
individual's recommendation was exactly correct, to a disasses, which
indicated that the recommendation was off by four places in terms of
their aggressiveness level. Team and individual effectiveness was
then expressed in terms of points associated with each outcome.
More detailed descriptions and point values of all possible outcomes
are provided on page six of Appendix A.

Proeedures
The need to classify individuals in terms. of task ability

required participants to attend two sessions of the experiment.

42

Sessien 1. Participants were asked to read and study a packet
of information which provided them with a brief description of the
simulation, the ranges of the attributes which characterized each
target, and the various rules for combining the attributes of the
targets (See Appendix A). Following this, individuals were asked to
take a test on the materials they just read. The test was designed to
assess their knowledge of the various levels of the attributes and the
combination rules. After completion of this test, individuals were
informed that they were to be notified as to the time and place of the
second session of the experiment.

Cempesitieu Manipulatien. Ability in this experiment was
defined as the amount of job knowledge relative to this task
displayed by the participants on the test in Session 1. Scores on this
test were trichotomized. Teams were then randomly formed
comprised of either members with homogeneous ability or members
with heterogeneous abilities. Specifically, an equal number of three
person homogeneous teams were formed for three ability levels:
high, moderate, and low. Alternatively, heterogeneous teams were
composed of one high, one moderate, and one low ability person.

SeasieLZ. When participants arrived for the second session,
they were first seated in a room equipped with a television and VCR.
When all members arrived, individuals were given a handbook
similar to the one they received at the first session. The only
difference was that . this handbook provided them with a description
of their specific role, what attributes they could measure, and a

review of the various combination rules. The tape was started ten

413
minutes after they were given the handbook and they received video
instructions on how the simulation functioned.

After watching the tape and reading through this handbook,
participants were taken to their computer terminals and taken
through two practice trial targets by the experimenter. At this point,
any questions they had regarding the functioning of the simulation
were answered. They were then told that they had the opportunity
to go through five more practice trials before the experiment actually
began.

Ineentive Manipulatien. Incentives were manipulated based
on past research. As such, two incentive systems were used in this
study: (1) individuals within the team were rewarded based on their
individual performance (i.e. the accuracy of their recommended
decision), irrespective of team performance, (individual condition)
and (2) individuals received equal rewards based on the
performance of the team (i.e. the accuracy of the team decision),
irrespective of individual performance, (team condition). In the
individual incentive condition, individuals received $1.00 for a hit,
$0.50 for a near miss, and $0.25 for a miss. Decisions which resulted
in outcomes worse than a miss resulted in the individual receiving no
money for that trial. In the team condition, teams whose average
recommendation resulted in a decision which was a hit earned $3.00
($1.00 per person), a near miss earned $1.50 ($0.50 per person), and
a miss earned the team $0.75 ($0.25 per person). Any decisions
worse than a miss resulted in the team receiving no money for the

trial.

44

After the fifth trial, participants were informed of their
incentive condition (See Appendix D), that the next fifteen trials were
going to be scored, and that their performance on these trials was to
be used to determine their pay for the session.

After the final trial, participants were given a brief
questionnaire to complete. They were then debriefed as to the actual
nature of the experiment, paid their money, and allowed to leave.

M ni 1 ion h k

The questionnaire included an item concerning the individual's
knowledge of the incentive system (See Appendix C, Item 1). Also.
included in this questionnaire were items assessing certain
demographic variables (See Appendix C, Items 10-14).

D en n M r

Dependent variables came from both the questionnaire
distributed to participants after the team task and summary
statistics based on actual behavior on the task. These measures
included team and individual performance, perceived equity of pay,
and degree of cooperation.

Pertjermanee. The amount of money earned over the fifteen
trials served as an indicator of both team and individual
performance. The use of pay as a dependent variable resulted in a
criteria with four levels, rather than the five which would have
resulted if points earned had been used as the indicator. This use of
pay as a proxy measure of performance was acceptable given the
high correlation between the two measures (L = .96) and the fact that

team members were informed of their performance in dollar terms.

 

45

P r ' i . Included on the questionnaire were items
assessing individuals' feelings about the fairness of the incentive
system they were working under (See Appendix E, Items 2 through
9). These items were rated on 5-point scales and combined to form a
Fairness of Pay Scale (alpha = .83) and a Fairness of Pay System Scale
(alpha = .83).

Ceeperatien. As previously stated, cooperation was defined in
terms of the communication sequence detailed in Appendix E. While
several indices were generated from this sequence, several of them
were not deemed measures of cooperation. As a result, only those
indices which indicated either individuals not attending to the
requests of team members or not responding to those requests were
used in the operationalization of cooperation. More specifically,
cooperation was defined as the extent to which teams minimized the
occurrence of "slights" and "unresponsives". These two indices were
summed across the fifteen trials for each team yielding a measure of
cooperation. Thus, those teams which were acting cooperatively
would receive lower scores on this variable than those teams with

uncooperative members.

RESULTS

Mani l i n h k

Manipulation checks were collected with a questionnaire that
was administered following the simulation. One manipulation check
which was used in this experiment was related to the participants'
ability to correctly identify which pay condition they were operating
under and was obtained via an item on the questionnaire. Of the '142
individuals completing the questionnaire, 131 (92%) correctly
identified their pay condition.
Adequacy ef the Individual Ability Variable

Analyses of individual level data were conducted in order to
determine if the initial classification of individuals as high, moderate,
or low ability was supported by individuals' actual task performance
as well as perceptions of ability by self and others. The first step
- was to conduct an ANOVA using individual performance as the
dependent variable (DV), initial classification of ability as the
between-subjects factor (high, moderate, and low), and trials (15) as
the within-subjects factor. Results showed no significant interaction
(p_ > .05) between ability and trial suggesting that computing a
performance measure by summing across the trials was acceptable.

Subsequently, 'a one-way ANOVA was then performed comparing

46

47
mean total performance, expressed in dollars earned, across the
three teams. Results indicated a significant main effect for ability
(£12,123) = 5.80, p < .05) with the following observed means and
standard deviations: Lilow = $6.77 (1.81), Mmod = $7.06 (1.25), and
M11131; = $7.90 (1.55). Post hoc tests indicated that the means for low
and moderate ability individuals significantly differed from the high
team (p < .05), but not each other (p > .05).

While differences in performance at the individual level are
crucial in establishing the foundation for assessing the group-level
data, they are not sufficient. As the relationships between the
exogenous and endogenous variables rely on perceptions of the
fairness of pay among individuals, it should be true that individuals
of varying abilities should be perceived as having differences in
abilities. To assess this, individuals rated each other, as well as
themselves on a five-point scale (1 = Well below average ability to 5
= Well above average ability). This led to each individual receiving
three ratings of their performance. A one-way ANOVA, with ratings
as the DV, was conducted to assess perceived differences in ability
across ability levels. Results indicated no significant differences
between the three means (p > .05). However, while not significant,
the means were in the expected direction (Mlow = 3.35 (.78), Mmod =
3.40 (.70), and Ming}, = 3.68 (.64)). Further, the correlation between
ratings and performance was significant (1 = .66, p < .05), suggesting
that the individuals‘ perceptions were congruent with team
members' actual task performance. These results of the individual-

level data were taken as support that the initial classification of

48

individuals as low, moderate, or high ability was adequate in the
development of the three-person teams.
Analyses ef Primary Hypotbeses

Hypethesis 1: The first hypothesis was concerned with the
relationship between team composition, as stated in the introduction,
and team performance, measured in dollars earned. Specifically, it
was predicted that there would be a positive correlation between the
two. An ANOVA with team performance as the DV, trials (15) as a
within-subjects factor, and team composition (4 levels) as a between-
subjects factor indicated that there was no significant trial by ability
interaction (p > .05). As a result, performance was summed across
the fifteen trials to produce an index of team performance. Across
the teams, performance measured in dollars earned per team ranged
from $6.00 to $10.50 with a grand mean of $8.44. The correlation
between team ability and performance (I = .40, p < .05) provided
support for the first hypothesis. This relationship is depicted in
Figure 7. Post hoc tests for differences between the means indicated
that the means for teams comprised of all low ability performers
($7.15, SD = .89) and all moderate ability performers ($8.34, SD = .98)
differed from those teams composed of all high ability performers
($9.15, SD = 1.28) (p< .05). The mean for the mixed-ability team
(8.59, SD = 1.21) did not differ significantly from any of the other
means. While the difference between the moderate teams and the
mixed ability teams was not significant, it is worth noting that while
these teams had essentially the same total ability (3 moderate ability

equal 1 high, 1 moderate, and 1 low ability), those teams that

49

Figure 7

Effect of Team Ability on Team Performance

 

10.00 #
9.75 '
9.50 :
9.25 -:
9.00 ':
8.75 1
8.50 :
8.25 :
8.00 '1
7.75 g
7.50 "
7.25 '3

Team Performance ($)

9.15

8.59
8.34

7.15

 

7.00

 

fl
Low Mod Mix High

Team Ability

 

50
included a high ability performer performed somewhat better than
those with all moderate ability individuals.

Hypethesis 2. The second hypothesis was concerned with the
expected interaction of team ability and team pay on team members'
perceptions of the fairness of their pay. Observed means and
standard deviations for the fairness variable by condition are
presented in Table 1. A 2 (pay system) x 4 (team ability) ANOVA
with perceptions of pay as the DV revealed no significant main
effects for either variable (F's < 1.00) (see Table 2), nor was the
interaction significant (E (3,34) = 1.25, p = .31). Figure 8 presents ‘a
graph of the observed means and standard deviations (SD's) for this
interaction.

Of particular interest in the examination of these means is the
difference in the high ability condition as a function of pay. Those
teams composed of all high ability performers and paid equally
based on the team's performance expressed higher (more than 2
standard deviations) perceptions of fairness than their individually
paid counterparts. In no other condition were these perceptions so
divergent. A potential explanation for this finding has to do with the
performance of individuals versus teams. Generally speaking, team
performance was higher than the performance of any one individual
in the team. Thus, in those cases where there were three high ability
members and team performance was high, being paid individually.
would most likely result in earning less money than would have
been the case had pay been based on the team's performance.

Because performance tended not to be as high in the other teams,

 

51

Table 1

Means and Standard Deviations for the Endogenous Variables

 

Fairness Cooperation Performance

Condition N M (SD) M LSD) M (SD)
Group Pay:

Low 2 57.50 (6.36) 37.00 (1.41) 7.00 (1.41)

Mod 4 62.25 (12.82) 70.75 (26.03) 8.19 (1.03)

Mix 12 64.33 (11.66) 47.92 (14.92)‘ 8.33 (1.24)

High 2 71.00 (7.07) 46.00 (8.49) 8.50 (2.12)
Individual Pay:

Low 3 58.33 (12.42) 36.67 (21.22) 7.25 (0.75)

Mod 4 62.50 (8.89) 41.00 (17.11) 8.50 (1.06)

Mix 12 64.58 (8.89) 47.33 (15.87) 8.85 (1.16)

High 3 51.67 (10.97) 53.33 (7.51) 9.58 (0.58)

 

 

52

Table 2

Analysis of Variance Summary for Endogenous Variables

 

 

FAIR COOP PERF
Independent Variable df F F F
Ability (A) 3 .68 1.40 2.87*
Team Pay (P) 1 .36 1.09 2.00
A x P 3 1.25 1.96 .14
Within 34 (109.80) £263.28) (1.37)

 

Nete; FAIR = Perceptions of Fairness, COOP = Degree of Cooperation,
and PERF = Team Performance. Values in parentheses represent

mean square terms. * p < .05

53

Figure 8

Interaction Between Pay and Team Ability on Perceptions of Fairness

Perceptions of Fairness

 

 

 

 

 

80
75 -
70 -
65 -
' 58.33
60 ‘ (12.42)
55 . 57.50
(6.36)
50 I I l 1
Low Mod MIX High

Team Ability

—9— Group Pay
—v- Individual Pay

54
this difference between team and individual outcomes would not
have been so large.

Also of interest is the fact that this difference was not
significant. Most likely, this was due to the problem of low power as
a function of small sample size. Given a larger sample and no change
in the pattern of means, this difference would probably have
resulted in a significant interaction.

Hypethesis 3. Hypothesis 3 focused on the expected effect of
the interaction between pay and ability on the degree of cooperation
exhibited by team members. The index of cooperation used in this
set of analyses was computed through the process described in the
Methods section as well as Appendix E. Means and standard
deviations are presented in Table 1. As with the other analyses
which were examining a variable assessed at each of the fifteen
trials, an ANOVA was conducted using cooperation (COOP) as the DV.
No significant interaction was observed (p > .05). As a result,
cooperation across trials was collapsed to produce a single index for
each team with a minimum value of zero (indicating perfect
cooperation). A subsequent ANOVA using this measure of
cooperation as the DV yielded neither a significant main effect for
ability, nor pay (p's > .05). The interaction of these two variables was
also non-significant (see Figure 9).

Hypethesis 4. The effect of the interaction between pay and ,
ability on team performance was the focus of the fourth hypothesis.
An ANOVA, using performance as the DV, indicated no significant

interaction between trials and the between-subjects variables (p >

 

Cooperativeness

55

Figure 9

Interaction of Ability and Pay on Cooperation

 

 

    
   

  

 

 

80
70.75
(26.03)
70 -
60 - 53.33
(7.51)
50 -
‘ 37.00 47.33 45,00
40 _ (141) (15.87) (349)
41.00
36.67 (17.11)
(21.22)
30 I I 1 .l
Low Mod Mix High

Team Ability

+ Group Pay
—0— Individual Pay

 

 

5 6

.05). As a result, performance over the trials was summed to yield
an index of team performance. A 2 x 2 ANOVA revealed a significant
main effect for ability (F (3,34) = 2.87, p < .05). However, there were
no significant effects for either the main effect of pay or for the I
interaction (p‘s > .05). Figure 10 shows the pattern of means (SD's)
for the interaction of team ability and pay on team performance.

Hypethesis 5.. Hypothesis 5 suggested that all three dependent
variables would be intercorrelated. Table 3 includes the correlation
matrix for these, as well as all'other relevant, variables. As indicated
in this table, none of the intercorrelations is significant (p's > .05).
Due to this fact, the analyses for Hypotheses 6a and 6b were not
conducted, as the basic criterion for testing mediation was not met.
Figure 11 does display the path coefficients of the hypothesized
model; the only significant relationship being that between ability
and performance. I

Hypethesis jZ. Hypothesis 7 discussed the expected effect of the
interaction on team performance when teams were categorized as
.either homogeneous or heterogeneous (i.e. ability was equal in these
teams). No significant main effects were found (p‘s > .05). Similarly,
no interaction effect was demonstrated using the 2 x 2 ANOVA with
team performance as the DV (p > .05). However, while not
significant, results were consistent with earlier analyses in that
individual pay resulted in higher performance (M = 8.67) than did
group pay (M‘ = 8.19) for both homogeneous and heterogeneous

teams (see Figure 12).

Performance (3)

Team

57

Figure 10

Interaction of Ability and Pay on Team Performance

 

 

  

 

 

10.0
9.58

9.5 " (0.58)

" 8.85
9.0 "' 3.50 (1-16)
8.5 "

. 8.50

_ 8.33 (2.12)
8.0 (1.24)

‘ 7.25
7.5 " (0.75)
7.0 '

. 7.00
6.5 _ (1.41)
6.0 I r r 1

Low Mod Mix High

Team Ability

—-II— Group Pay
—0— Individual Pay

58

Table 3

Intercorrelations Among Key Variables

 

 

(I) (2) (3) (4) (5)
Teamab(l) 1.00
Teampay(2) -.01 1.00
Fairness(3) .09 -.11 1.00 -
Cooperation(4) .11 -.16 -.20 1.00
Teamperf(5) .41** .20 .11 -.01 1.00

 

 

11019: ** (p < -01)

5 9
Figure 11

Observed Relationships Among Key Variables

 

 

58:30
MESS

 

 

 

 

0.8.6
0036830:
3355

 

 

 

 

FEEQELW
$807.8

man—5%
cm .03.

 

-.No

 

 

.38..

 

Uomuem
c».
08838:

 

:8
IT

 

 

H88
women—3:8

 

 

 

** (p < .01)

Nete:

Team Performance (3)

60

Figure 12
Relationship Between Pay and Homogeneous versus Heterogeneous

Teams and Performance

 

 

 

 

 

8.85

8.80 - (1.16)
8.55 -

. 8.45

(1.22) 8.33 —9— Group Pay

8.30 - (1.24) —'0— Ind1v1dual Pay
8.05 ~

. 7.97

‘ (1.33)
7.80 r l

Homogeneous Heterogeneous

Team Composition

 

DISCUSSION

This discussion will be divided into three sections. The first
will provide a brief review of the strengths of the current procedure
for studying team performance, what the interesting findings were

and where these findings fit into current literature on team

 

performance. Following that, the second section will be devoted to a
discussion of possible limitations of the study and their potential
impacts on the obtained results. Finally, a discussion of potential
directions for future research will be presented.
Rviwf lnnrin'h rrnirr

This study had several strengths associated with it which
should be incorporated in the design of future research on team
performance. First, and most importantly, the operationalization of
ability proved useful and provided some support for the importance
of ability as a determinant of performance in this task. The ability
measure allowed for the pre-classification of individuals as high,
moderate, or low performers. Further, this task allowed for these
individual differences to be manifested both at the individual and
team level. That is, not only did high ability persons perform better

than low ability persons, but also these individual differences were

realized in the team's performance. A task which allows for the

61

62
simultaneous collection and examination of both individual and team
level variables is certainly an asset to the team performance
literature.

In addition to the strengths associated with the task itself, the
results of this study also add to the literature. For example,
consistent with previous research in the area of team performance
(cf. Tziner & Eden, 1985), results from this study supported the

position that the higher the ability level of the team, the better the

 

team's performance. All else being equal, it would appear that the
intuitive position that "more is better," is supported by these results.
Teams with three high ability persons performed better than those
with three moderate ability persons which, in turn, performed better
than those with three low ability people. Further, these results seem
to suggest that high ability individuals aid team performance more
than low ability individuals detract from team performance. This
was demonstrated by the fact that teams with three moderate and
teams with one high, one moderate, and one low ability person both
. had an equal pool of ability to draw from, but did not have equal
subsequent performance. On average, though not significantly so, the
mixed ability teams performed better than teams with all moderate
ability individuals. This evidence suggests that when combining
individuals into teams, performance will be more influenced by the
number of high ability people in the team than the average talent
within the team.

Also of potential interest was the effect of pay on team

performance. Results indicated that those teams whose members

63
were paid based on their individual performance tended to perform
better than teams whose members were paid equal amounts based
on team performance. That is, even on a "team" task, teams may
tend to perform better when individuals are rewarded for their
individual performance. While the main effect for pay was not
significant, the results nonetheless suggest that this may be an
important variable and warrants further investigation.

Results indicated that the best performing teams under the
group pay condition (3 high ability members) performed only as well
as the teams comprised of three moderate ability members in the
individual pay condition. This finding is interesting in that it
suggests that the reward system can make up for ability deficits in
the team context. Further, this is consistent with the notion that, at
the individual level, motivation can make up for ability deficiencies.

Another interesting finding with respect to the effect of both
the incentive system and team ability level on performance was that
associated with the final hypothesis. Specifically this hypothesis was
concerned with the question of how to best divide up a fixed set of
talent. Teams which are composed of members with varying ability
levels tend to outperform those teams which are comprised of
members with similar abilities. Drawing back on the analogy used in
the introduction, it would be better to put together a "line" of hockey
players who had varying ability levels, rather. than putting the best
players together, then the next best, and so- on. Thus, the old saying
that you "should not put all your eggs in one basket" seems to have

found some support, albeit weak, in the current study.

64

Limitations

Several problems may have detracted from my ability to
adequately test the hypotheses presented above. The first, and
possibly the most critical, is the problem of low power. With a
sample size of only 42 teams and the types of interactions being
examined, it is clear why many of the observed results were not
significant. Given that when looking at individual level data

manipulations appeared to be working (manipulation checks were, in

 

fact, significant) it is highly likely that more significant results would
have been observed with the group-level data had more teams been
examined.

Another problem which almost certainly affected the
nonsignificant results observed with respect to the proposed model
was the operationalization of both the cooperation and fairness
variables. To begin with, the cooperation measure which was
adopted from Hollenbeck et a1. (1991) did not appear to adequately
capture the construct of interest. This was evidenced by apparent
unsystematic differences across teams. It may be that for this
particular task cooperation may be better. measured using another
set of indices. Whatever the problem may have been, clearly the
cooperation measure used in this study should be redeveloped and
refined. In addition to the objective measures, perhaps a
questionnaire item, or set of items, assessing the participants'
perceptions of the degree of cooperation would prove valuable in

attempting to measure this construct.

65

The measure of fairness was also a potential cause for concern
in this study. Perceptions of fairness were gathered following the
last trial, while the other measures (i.e. cooperation and
performance) were gathered after each of the fifteen trials. It may
have been that fairness perceptions changed from the first to the last
trial as a result of team and/or individual performance outcomes.
Given that it was measured at one point in time, it was impossible to
assess whether this occurred. While it may have been cumbersome
to gather these perceptions after each of the trials, and the
participants may have been reactive, perhaps it may have been
worthwhile to collect them after every fifth trial or so.

One other issue that may have reduced the observation of
significant results that deserves to be addressed at this point is the
fact that participants received betb course credit and money for
participating in this experiment. Given that participants knew that
they were going to be getting something for their time (i.e. credit),
the monetary incentive may have been reduced in importance. To
truly test the model that was presented in the introduction,
incentives should be the QDIJL reward used.

Dir i n f r F r h

In addition to being aware of the problems which plagued the
current study, future research in the area of team performance
should also try to get the teams to perform for a longer period of
time. Such a longitudinal approach would allow for team members to
develop a sense of team identity. Variables such as pay and ability

would be manipulated in an environment which would further allow

 

66
for their influence on team performance. While such an approach to
the study of team performance would certainly provide many
benefits over the current study,' other problems would likely arise.
For example, time may create a situation in which other processes
could influence performance over and above those being
manipulated. For this reason, while future research should be
directed more towards examining teams in a dynamic environment,
control over key variables remains a critical issue.

While the current study did not find support for the proposed
model, future researchers should continue to rely on careful theory
development in this area. As Goodman and his colleagues (1986,
1987) suggest, it makes sense to attempt to understand the
phenomena of team performance by taking a simple approach to
model development. That is, begin with a few testable variables.
Team performance is far too complex a process to develop and test a
comprehensive model in a single experiment. Although the model
presented was not supported, future research should continue to
examine the influences of both team composition and incentives as
potentially important determinants of team performance.

Finally, given the ubiquity of teams in the current work
environment, more research is clearly needed so that we can more
fully understand how teams should be formed, how they operate,
and how we can make them more effective. Researchers should not
only look to the industrial/organizational psychology literature as a
potential source for developing models of team performance, but

they should also examine the research on teams in social psychology,

67
case study information detailing teams from the business literature,
and perhaps most importantly the factors which are at work in

today's work settings.

 

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APPENDICES

 

APPENDIX A

76

HANDBOOK FOR TEAM MEMBERS
TEAM PERFORMANCE EXPERIMENT
COMMAND AND CONTROL SIMULATION

Michigan State University

Summer, 1991

 

7 7
COMMAND AND CONTROL TEAM SIMULATION

INTRODUCTION:

The year is 1994 and you are part of a US. naval carrier group's command and
control team stationed in the Middle East. A regional conflict between two nations in this
area has recently broken out, and your mission is to protect seagoing commercial traffic in
the area from accidental or intentional attacks. As history indicates, this is a highly
sensitive task. For example, in 1987, an Iraqi jet accidentally fired two Exocet missiles
into the Frigate U.S.S. Stark, killing 37 American servicemen and crippling the vessel.
One year later, the USS. Cruiser Vincennes accidentally shot down an Iranian passenger
plane killing 290 innocent civilians. Any repeat of mistakes of this kind will probably lead
to a withdrawal of American forces from the area. Such a withdrawal would have
disastrous economic and political ramifications that would spread well beyond this region.

THE TASK FORCE:

 

A naval carrier battle group team is an awesome array of ships and support units. It
has a concentric ring of missile firing warships which protect the aircraft carrier at its
center. The aircraft carrier in return provides an overall umbrella of air protecu'on for the
entire task force. The carrier's 9O planes can unleash air strikes against targets at land, sea,
and even under water. A carrier group can dominate up to 196,000 square miles of Ocean.
A standard carrier group consists of six ships; the Carrier itself, two Ticonderoga class
Aegis Cruisers, two anti-air Destroyers, and a submarine.

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

TEAM MISSION:

 

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

 

7 8
OVERVIEW OF ROLES:

There are four roles in this simulation, one for each member of a four person team.
The leader is the Commanding Officer (C0) of the Aircraft Carrier. The other team
members include the C0 of an AWACs air reconnaissance plane, the 00 of an Aegis
Cruiser, and the C0 of a Coastal Air Defense (CAD) unit located on the mainland. The
team's task is to decide what response the carrier group should make toward incoming air
targets. These decisions are based on data they collect by measuring characteristics of
aircraft that enter the group's airspace. These measures are obtained from sophisticated
radar equipment. Aircraft that are being tracked on radar are called tatgets. There are seven
possible choices to make for each incoming target. These responses are graded in terms of
their aggressiveness. Each of these is described below, moving fiom least to most

aggressive:

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

 

(2) REVIEW: This means to leave this target momentarily, so that the team can
monitor other targets, but to return to this target after a short period of time to update its
status. A carrier group can review a large number of targets, but not an infinite number of
targets.

(3) MONITOR: This means that the carrier group should continuously track the
target on radar. A carrier group can monitor fewer targets than it can review, and thus,
monitoring diminishes the group's overall capacity.

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

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

(6) LOCK-ON: This synchronizes the ship's radar and attack weapons so that the
weapons fix themselves on the target. A ship at Lock-On position can take offensive action
at a moments norice. However, a ship's capacity to track other targets in severely
constrained once it has Locked-On a single target. Thus, this should be reserved for targets
that are almost certain to be threatening.

(7) DEFEND: This is "weapons away" and means to attack the target with
Tomahawk cruise missiles. A defend decision cannot be aborted once initiated and thus
must only be used when the group feels attack is imminent.

7 9
CHARACTERISTICS OF TARGETS:

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

(1) Speed: 150 to 800 mph.

(2) Altitude: 5,000 to 35,000 ft.

(3) Size: 15 meters to 50 meters

(4) Angle: -15 Degrees (rapid descent) to +15 Degrees

(rapid ascent). .

 

(5) IFF: stands for "Identification Friend or Foe," this
is a radio signal that identifies whether an
aircraft is civilian, para-military or military
which ranges from 0.2 Mhz (an airliner) to
1.6 Mhz (a fighter).

(6) Direction: from +40 Degrees (passing far to the east or
west of the carrier) to 00 Degrees (coming

straight in to the canier).
(7) Corridor: a conidor is a 20 mile lane open to
Status commercial air traffic, and this is expressed

in terms of miles hour the center of the
corridor, ranging from 1 mile (in the middle
of it) to 50 miles (way out of it).

(8) Radar Type: the kind of radar possessed by the aircraft
range from Class 1 (weather radar only) to
Class 9 (weapons radar).

(9) Range: distance of the aircraft from the carrier
ranging from anywhere from 20 to 200
miles.

 

8 0
DETERMINING THE LEVEL OF THREAT:

In general, the degree to which an incoming target is threatening depends on its
standing on the previous nine attributes. There are five simple rules to remember 1n
determining the danger associated with any target:

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

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

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

(d) ALTITUDE and CORRIDOR STATUS go together, so that 191
We: are CSPccially
threatening (see #2 & #7 above). Altitude alone and conidor status alone
mean nothing. There 1s nothing to fear from high targets flying well outside
the corridor or low flying targets in the middle of the corridor.

(e) SIZE and RADAR go together, so that Weeds
meat; are especially threatening (see #3 & #8 above). There 1s nothing to
fear from small targets with weather radar or from large targets with
weapons radar.

HOW RULES COMBINE TO DETERMINE JUDGMENTS:

 

 

The five rules combine to determine the overall threat represented by the target. So
for example, if the team detected an (a) military aircraft that is (b) flying in straight and fast,
(c) was close and descending, (d) was flying low and way outside the corridor and (e) was
small and had weapons radar, the ship is being attacked and should DEFEND.

If the team detected (a) a civilian aircraft, (b) passing slow at an angle, (c) was far
away and ascending, (d) was flying high and in the middle of the conidor and (e) was large
and had weather radar; this is a passenger plane that should be IGNORED.

Intermediate responses like MONITOR, WARN, or READY are to be used when
the target is threatening according to some of the rules, butnetali. For example, a military
aircraft that is close and descending (see Rule c), small and with weapons radar (see
Rule e), but is travelling slowly at an angle to the group (see Rule b), and is high and in
the middle of the corridor (see Rule (1) might need to be WARNED. You would not want
to ignore it, but you would not want to shoot it down either.

 

 

8 l
AREAS OF EXPERTISE:

The C0 of the Carrier is the leader of the team and the person to whom each of the
other COS must make their recommendation for each target. Each team member, other than
the C0 of the Canier, has expertise that is unique to his or her role. That expertise comes
in the form of the person's (a) ability to measure attributes and translate raw data
into judgments regarding threat, and (b) the person's knowledge of the rules.

For example, although all team members know that military aircraft are more
threatening than non-military aircraft, only two people in the team can actually measure this
characteristic of the target. In addition, only these two players will be trained to know
exactly how raw data on IFF (i.e. radio signal Mhz.) can be translated into terms of "non-
threatening," "somewhat threatening," and "very threatening."

Each member of the team will have to memerizeali of the four combination rules.
Thus, while all members will know how the various attributes combine to determine threat,
they will only be able to measure and interpret a subset of the raw information.

PATROL SESSIONS:

W. Patrol session refer to the time that you and your teammates are
responsible for monitoring air traffic in your designated area. While you are monitoring
traffic, you will be stationed at a computer monitor. When this screen has four icons on it
(i.e. the canier, plane, ship, and land mass), you are in the "Sea Screen" mode. This
means that there is a target (i.e. a red dot) in your airspace that needs to be assessed. The
target will begin to blink and beep at an increasing rate when there is less than 30 seconds
to respond. If the leader (C0 of the Carrier) fails to make any decision with respect to the
target, this will be treated as if the team decided to IGNORE it. In making the team
decision, the leader will simply average the three recommendations made by each of the
other COS. If there are less than 10 seconds to go in a session and one, or all, of the other
three members haven't made their recommendations to the Carrier, it will also be treated as
an IGNORE when determining the average response.

Ibejlieedbaekjemnfl. When the trial is over, all team members will receive an
immediate report telling them how well the team, and they as individuals, performed. This
will be presented both on the computer and on a chart in the room. The computer feedback
will inform them of the team decision, each individuals recommendation, and the correct
decision. The chart will present cumulative information of this type after each trial. There
are five possible outcomes from an encounter, and the team's, and individual's, total
effectiveness will be expressed in terms of points associated with each outcome:

 

 

82

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

NEAR MISS -- A near miss means that the team was off by one place in terms of their
aggressiveness level. For example, if the team decision was WARN, when it
should have been MONITOR, this would be a near miss (a little too aggressive).
It would also be a near miss if the decision was WARN when it should have been
READY (a little too passive). A near miss is a pretty good outcome, however,
since the ships will be able to adjust to the target if the initial stance is this close. A
near miss is worth 1 point. The color bars at the top and bottom of the screen will
be aquamarine when this occurs.

 

MISS -- A miss means that the team decision was off by two places. For example, if the
team decision was WARN when it should have been REVIEW the team was too
aggressive. Similarly, if the decision was WARN when it should have been
LOCK-ON, the team was too passive. The ships will usually be able to adjust if
the initial stance is this far off, but this is not guaranteed. Thus, this outcome is
worth 0 points. The color bars will be purple when this occurs.

INCIDENT -- An incident means that the team was off by three places in their response
to the target. An incident means that the team just narrowly avoided disaster (i.e.,
being hit itself or mistakenly shooting down a fiiendly target). This outcome
results in the less of 1 point. The color bars will be red when this occurs.

DISASTER -- A disaster means that the team decision was off by four places. That is,
the team said to IGNORE or REVIEW when they should have said LOCK-ON
or DEFEND or, the team said LOCK-ON or DEFEND when they should have
responded IGNORE or REVIEW. This means that one of the ships was struck
by a missile (if overly passive), or that one of the ships shot down a friendly target
(if overly aggressive). Remember that the ship set to READY or LOCK-ON will
have activated automatic weapons. So, you can shoot down targets by mistake,
even when you are not explicitly "defending." .This outcome results in a less of 2
points. The color bars will be black in this case.

 

83

RANGE OF ATTRIBUTES AND COMBINATION RULES:

EirsLSessien. Presented below is a brief review of the combination rules for determining
the threat level associated with any target along with the ranges for all nine attributes and
the threat level associated with these ranges. For this session, it is important that you learn
the various threat levels associated with each corresponding attribute and range.

Degree of Threat
Non-mmm—SmmW—MW—

 

Speed 100-275 mph 325-500 mph 600-800 mph
Altitude 35,000-27,000 ft 23,000-17,000 ft 13,000-5,000 ft
Size 65-43 mtr 37-23 mtr 17-10 mtr
Angle +15 to +8 dgs ' . +3 to -3 dgs -8 to -15 dgs
IFF .2 to .6 Mhz .9 to 1.1 Mhz 1.4 to 1.8 Mhz
Direction 30 to 22 dgs 18 to 12 dgs 8 to O dgs
Corridor St. 0 to 8 mi 12 to 18 mi 22 to 30 mi
Radar Type Class 1 & 2 Class 5 Class 8 & 9
Range 200t0110mi 90to60mi 40tolmi

 

Summary of How to Determine Threat Levels

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

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

(c) ANGLE and RANGE go together, so that WEI.
areelese are especially threatening (see #4 & #9 above). Angle alone
and range alone mean nothing. Descending targets that are far away,or

close targets that are on the way up are not threatening.

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

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

 

 

APPENDIX B

84

Task Knowledge Test

Individual Session

 

Summer, 1991

85

600 miles per hour represents which of the following?

(a)
(b)
(o)
(d)
(o)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.
A target that is out of the possible range of values.

05 degrees of direction represents which of the following?

(a)
(b)
(C)
(d)
(o)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.
A target that is out of the possible range of values.

50 meters represents which of the following?

(a)
(b)
(o)
(d)
(o)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.
A target that is out of the possible range of values.

Class 2 radar type represents which of the following?

(a)
(b)
(o)
(d)
(e)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.
A target that is out of the possible range of values.

1.5 Mhz represents which of the following?

(a)
(b)
(o)
(d)
(c)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.
A target that is out of the possible range of values.

 

 

 

(a)
(b)
(o)
(d)
(e)

(a)
(b)
(C)
(d)
(c)

(a)
(b)
(o)
(d)
(o)

(a)
(b)
(o)
(d)
(e)

86

+20 degrees of angle represents which of the following?

A non—threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.
A target that is out of the possible range of values.

250 miles for range represents which of the following?

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.
A target that is out of the possible range of values.

30,000 foot altitude represents which of the following?

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.
A target that is out of the possible range of values.

5 miles outside the corridor represents which of the following?

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.
A target that is out of the possible range of values.

10. 20 meters represents which of the following?

(a)
(b)
(o)
(d)
(c)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.
A target that is out of the possible range of values.

 

87

11. Class 7 radar type represents which of the following?

12

l3

14

15

(a)
(b)
(o)
(d)
(e)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.
A target that is out of the possible range of values.

. .5 Mhz represents which of the following?

(a)
(b)
(o)
(d)
(c)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.
A target that is out of the possible range of values.

. 850 miles per hour represents which of the folloWing?

(a)
(b)
(o)
(d)
(o)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.
A target that is out of the possible range of values.

. 35 degrees of direction represents which of the following?

(a)
(b)
(o)
(d)
(e)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.
A target that is out of the possible range of values.

. 0 degrees of angle represents which of the following?

(a)
(b)
(o)
(d)
(e)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.
A target that is out of the possible range of values.

 

 

8 8
16. 80 miles for range represents which of the following?

(a) A non-threatening target.

(b) A somewhat threatening target.

(0) A very threatening target.

((1) A target on the border between two threat levels.
(e) A target that is out of the possible range of values.

17. 7,500 foot altitude represents which of the following?

(a) A non-threatening target.

(b) A somewhat threatening target.

(0) A very threatening target.

((1) A target on the border between two threat levels.
(e) A target that is out of the possible range of values.

 

18. 25 miles outside the corridor represents which of the following?

(a) A non-threatening target.

(b) A somewhat threatening target.

(0) A very threatening target.

(d) A target on the border between two threat levels.
(e) A target that is out of the possible range of values.

19. .7 Mhz represents which of the following?

(a) A non-threatening target.

(b) A somewhat threatening target.

(c) A very threatening target.

((1) A target on the border between two threat levels.
(e) A target that is out of the possible range of values.

20. 200 miles per hour represents which of the following?

(a) A non-threatening target.

(b) A somewhat threatening target.

(0) A very threatening target.

((1) A target on the border between two threat levels.
(e) A target that is out of the possible range of values.

 

 

21.

22.

23.

24.

25.

8 9
25 degrees of direction represents which of the following?

(a) A non-threatening target.

(b) A somewhat threatening target.

(c) A very threatening target.

(d) A target on the border between two threat levels.
(e) A target that is out of the possible range of values.

15 meters represents which of the following?

(a) A non-threatening target.

(b) A somewhat threatening target.

(c) A very threatening target.

((1) A target on the border between two threat levels.
(e) A target that is out of the possible range of values.

 

Class 8 radar type represents which of the following?

(a) A non-threatening target.

(b) A somewhat threatening target.

(c) A very threatening target.

((1) A target on the border between two threat levels.
(e) A target that is out of the possible range of values.

15,000 foot altitude represents which of the following?

(a) A non-threatening target.

(b) A somewhat threatening target.

(0) A very threatening target.

((1) A target on the border between two threat levels.
(e) A target that is out of the possible range of values.

20 miles outside the corridor represents which of the following?

(a) A non-threatening target.

(b) A somewhat threatening target.

(0) Avery threatening target.

(d) A target on the border between two threat levels.
(e) A target that is out of the possible range of values.

 

26.

27.

28.

29.

30.

90

+10 degrees of angle represents which of the following?

(a)
(b)
(C)
(d)
(C)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.
A target that is out of the possible range of values.

120 miles for range represents which of the following?

(a)
(b)
(C)
(d)
(C)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.
A target that is out of the possible range of values.

300 miles per hour represents which of the following?

(a)
(b)
(C)
(d)
(C)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.
A target that is out of the possible range of values.

10 degrees of direction represents which of the following?

(a)
(b)
(C)
(d)
(C)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.
A target that is out of the possible range of values.

2.0 Mhz represents which of the following?

(a)
(b)
(C)
(d)
(C)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A' target on the border between two threat levels.
A target that is out of the possible range of values.

 

 

 

 

 

31.

32.

33.

34.

35.

91

25 meters represents which of the following?

(a)
(b)
(C)
(d)
(C)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.
A target that is out of the possible range of values.

Class 5 radar type represents which of the following?

(a)
(b)
(C)
(d)
(C)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.
A target that is out of the possible range of values.

-5 degrees of angle represents which of the following?

(a)
(b)
(C)
(d)
(C)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.
A target that is out of the possible range of values.

50 miles for range represents which of the following?

(a)
(b)
(C)
(d)
(C)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.
A target that is out of the possible range of values.

40,000 foot altitude represents which of the following?

(a)
(b)
(C)
(d)
(C)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.
A target that is out of the possible range of values.

 

36.

37.

38.

39.

40.

92

40 miles outside the corridor represents which of the following?

(a)
(b)
(C)
(d)
(C)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.
A target that is out of the possible range of values.

70 meters represents which of the following?

(a)
(b)
(C)
(d)
(C)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.
A target that is out of the possible range of values.

Class 10 radar type represents which of the following?

(a)
(b)
(C)
(d)
(C)

non-threatening target.

somewhat threatening target.

very threatening target.

target on the border between two threat levels.
target that is out of the possible range of values.

>>>>>

400 miles per hour represents which of the following?

(a)
(b)
(C)
(d)
(C)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.
A target that is out of the possible range of values.

15 degrees of direction represents which of the following?

(a)
(b)
(C)
(d)
(C)

A non-threatening target.

A somewhat threatening target.

A very threatening target.

A target on the border between two threat levels.
A target that is out of the possible range of values.

 

 

41.

42.

43.

44.

45.

93
1.2 Mhz represents which of the following?

(a) A non-threatening target.

(b) A somewhat threatening target.

(c) A very threatening target.

(d) A target on the border between two threat levels.
(e) A target that is out of the possible range of values.

-12 degrees of angle represents which of the following?

(a) A non-threatening target.

(b) A somewhat threatening target.

(0) A very threatening target.

(d) A target on the border between two threat levels.
(e) A target that is out of the possible range of values.

 

35 miles for range represents which of the following?

(a) A non-threatening target.

(b) A somewhat threatening target.

(c) A very threatening target.

(d) A target on the border between two threat levels.
(e) A target that is out of the possible range of values.

22,000 foot altitude represents which of the following?

(a) A non-threatening target.

(b) A somewhat threatening target.

(c) A very threatening target.

((1) A target on the border between two threat levels.
(e) A target that is out of the possible range of values.

13 miles outside the corridor represents which of the following?

(a) A non-threatening target.

(b) A somewhat threatening target.

(c) A very threatening target.

((1) A target on the border between two threat levels.
(e) A target that is out of the possible range of values.

94

46. All else equal, which of the following is/are characteristic(s) of a
threatening target? "

(a) Low flying targets.

(b) Military targets.

(c) Targets with weather radar

(d) 2 of the above are characteristics of a threatening
target.

(e) 3 of the above are characteristics of a threatening
target.

47. All else equal, which of the following is/are characteristic(s) of a
threatening target? '

 

(a) Targets that are high flying.

(b) Targets with weapons radar.

(c) Targets that are fast and inside the traffic corridor.
((1) Targets that are descending and close.

(e) Targets that are large and descending.

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

(a) Targets that are large.

(b) Targets with weather radar.

(c) Targets that are fast and coming straight in.

(d) Targets that are small and inside the traffic
corridor.

(e) Targets that are ascending and close.

49. Which of the following combinations represents a more
threatening target?

(a) Weapons radar and small targets.

(b) High flying and inside the traffic corridor.

(c) Fast and straight on targets.

(d) Close and land radar targets.

(e) Outside the traffic corridor and descending targets.

 

95

50. Which of the following combinations represents a more
threatening target?

(a)
(b)
(C)
(d)
(C)

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

 

 

 

APPENDIX C

 

96

lneentive Manipulations

r In niv niin

"That concludes the learning trials. For each of the next fifteen
trials you will be scored on this task as a team, based on the accuracy
of the team's decision. If the team's decision is a 'hit', each of you
will receive one dollar, if the decision is a 'near miss', each of you will
receive fifty cents, and if the team's decision is a 'miss', each of you
will get twenty-five cents. Anything worse than a 'miss' will result
in each of you earning nothing for that trial. I will keep track of
your performance on this board so that you can see how you are
doing."

Inivi lIn niv niin

"That concludes the learning trials. For each of the next fifteen
trials you will be scored on this task individually, based on the
accuracy of your individual decisions, irrespective of the team's
decision accuracy. If your decision were to be a 'hit' you will earn
one dollar, if it is a 'near miss', you get fifty cents, and if it is a 'miss',
you get twenty-five cents. Anything worse than a 'miss' will result
in you earning nothing for that particular trial. I will keep track of
your performance on this board so that you can see how you are
doing."

 

 

APPENDIX D

 

9 7
Questionnaire

Name (Print) ID#

1. Please circle the method by which you and the members in your
team were paid?

A. We were paid equal amounts depending on the accuracy
of our team's decisions regarding targets.

OR

B. Each team member was paid based on her/his individual
accuracy regarding targets.

Please indicate your responses to items 2 to 9 using the scale below:

5-Strongly Agree

4-Agree

3-Neither Agree nor Disagree
2-Disagree

l-Strongly Disagree

2. My pay was fair, considering what other group members were
paid.

 

3. I was dissatisfied with the amount of my pay.

 

4. Considering the skill and effort I put into this task, I was
satisfied with my pay.

 

5. I didn't make the kind of money I wanted to on this task.

 

6. All in all, my pay was about what I wanted on this task.

 

7. The way I was paid was fair.

 

 

 

10.

11.

12.

13.

- 14.

15.

9 8
The method of paying people was as fair as it could be.

 

The amount of pay that I received was fair.

 

Using the following scale, please rate the ability level of yourself
and the other two members of your team in the spaces provided:

High Ability

Slightly Above Average Ability
Average Ability

Slightly Below Average Ability
Low Ability

idiom-ISM

CAD Rating

 

AWACs Rating

 

Cruiser Rating

 

Sex: M or F (Circle one)

Age:

 

Year in school: Fr. So. Jr. Sr. (Circle one)

Major:

 

Current GPA:

 

 

APPENDIX E

99

Communication Measures Used in the Calculation of the Cooperation

Index
"Perfeet Cemmunieatien Segueuee"
(a) (b) (C) (d)

QUERY -------- > RECEIVE -------- > TRAN SMIT -------- > RECEIVE
(Air to Land) (Land from Air) (Land to Air) (Air from Land)
(Re: Speed) (Speed)
R w In i rm n D ri i n

N iv i n

"Slight" - - a, but no b

"Unresponsive" - - a and b, but no 0

"Forget" - - a, b, and c, but no d

Pesitive Aetiens

"Learn" - - a, b, c, and d

"Lecture" - - c and d, but no a or b
Qeeperatien Index

"Cooperation" = "Slights" + "Unresponsives"

 

' IHIIIIIIIIIHIIIIIII/IIIIIHIHIIHIIIII