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300786 4238
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LIBRARY
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This is to certify that the
dissertation entitled

INCENTIVE PLANS AND
MULTI-AGENT INFORMATION SHARING

presented by

Susan Pickard Ravenscroft

has been accepted towards fulfillment
of the requirements for

Ph . D . degree in Accounting

 

ILA“: #asék

Major professor
Susan F. Haka

DateM

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MSU le An Alfimdlve Action/Equal Opportunity Inetltulon
QWM'

 

 

INCENTIVE PLANS AND MULTI-AGENT INFORMATION SHARING

BY

Susan Pickard Ravenscroft

A DISSERTATION

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

DOCTOR OF PHILOSOPHY

Department of Accounting

ABSTRACT
INCENTIVE PLANS AND MULII-AGENT INFORMATION SHARING

BY

Susan Pickard Ravenscroft

Managerial control systems have effects on behavior beyond those
predicted within micro—economic models. Incentive plans, which are one
aspect of management controls -- are the focus of this study. Several
conditions typical of actual work environments were manipulated across
two incentive plans in a laboratory experiment to explore the
interactive effects on employee performance and employee attitudes.

Expectancy theory provided the general framework for hypotheses
formulation. In addition, the theory of contests (a multi-agent
approach to agency theory) and organizational theory were valuable
sources of prior relevant research and served to enrich and refine the
research hypotheses. This study examined the effects of incentive
plans, the opportunity for direct inter-agent communication, and
feedback upon performance levels, information exchange among workers,
self assessments of abilities, and beliefs regarding the relationship
between performance and payoffs. The two incentive plans were a
cooperative group pooling and a rank ordering, or contest.

Generally, the hypothesized results were obtained. While prior

research comparing performance under cooperative versus competitive

Susan Pickard Ravenscroft

incentive plans has yielded mixed results, in this study communication
clearly interacted with the incentive plan. Performance was
significantly higher under the cooperative reward with communication
than in any other condition. Feedback positively affected workers'
expected performance in all conditions, which was contrary to
expectations. Information sharing and beliefs regarding the
performance-payoff relationship were significantly affected by the
incentive plan. Finally, the latter two attitudes were significantly
related to performance, which supports validity of expectancy theory.
The performance results also suggest that a single agent, single
principal model may be inadequate in studies comparing the effectiveness

of various incentive programs.

ACKNOWLEDGEMENTS

At this phase of my education I have many more debts of gratitude
than space or time allows me to enumerate. Those mentioned below are
the most pressing and must be acknowledged, though certainly not
settled, with a sincere thank you.

First, I wish to thank my committee - Susan Haka, Ron Marshall,
and Frank Boster - for their insights, their patience, and their
guidance. They were a diverse trio and I believe that their differences
served to enrich my readings and my thinking about the issues herein. I
am grateful also to Deloitte, Haskin and Sells for providing financial
support. I wish to express my particular admiration for my chairman,
Susan Haka. She wears many hats well, and I feel fortunate to have
worked with an academic who is able to fill so many roles so
successfully.

I also would like to express my gratitude to my fellow doctoral
students at Michigan State University. Because of the large number of
subjects required in this study, I relied frequently on my fellow
students for assistance in conducting experimental sessions. My student
colleagues were unfailingly helpful and obliging and met my importunate
requests with good humor and competence. Without them, the study would
not have been successful. My special thanks go to Annemarie Keinath,
who was not only my most constant assistant, but whose research

interests overlapped mine, affording us many fruitful, enjoyable hours

of discussion. I also am particularly grateful to Yong Sik Hong, K.
Ramesh, Robin Clement, Jan Trewin, Sanjay Gupta, and Geoff Gurka, all of
whom ably assisted me several times and in several ways. Last, but not
least, I express my appreciation to Frank Buckless, who provided
personalized computer consulting on demand, and was and continues to be
an inexhaustible source of good counsel on statistical matters.

On a more personal level, I wish to thank my sisters, Jan Bow and
Mary Bentley, for their unflagging encouragement, and two special
friends -- Sandy McFarland and Gretta Grimala -- whose cards and
letters continued all through graduate school. Finally, I wish to thank
my husband, Al. While we did not meet until I was in the dissertation
stage of the doctoral program, he has been a source of great joy. His
attention to our quotidian affairs freed me from distractions and his

humor provided much needed comic relief.

Introduction .

Literature Review
Motivation .
Prior Research .

Cooperative vs.

Expectancy Theory .
Theory of Contests .
Theory Linking Independent Variables .

TABLE OF CONTENTS

Hypotheses and Research Methods
Research Design
Administration .
Hypotheses .

Performance . .
Performance Variance

Information Transfer

Expectancy .
Instrumentality .

Results and
Results
Results
Results
Results
Results

Discussion .

and Discussion
and Discussion
and Discussion
and Discussion
and Discussion

Overview of Results

Conclusions

Research Findings .
Contributions of the Research
Limitations of the Research

Future Research

of Hypothesis
of Hypothesis
of Hypothesis
of Hypothesis
of Hypothesis

vi

Competitive Rewards .

One .
Two .

Three .

Four.
Five.

10
10
12
13
22
30
36

41
42
44
50
50
54
56
56
58

59
60
74
80
91
96

. 100

. 102
. 102
. 104
. 106
. 109

Appendices

- Informed Consent Declaration .
- First Expectancy Measure .

- Later Expectancy Measure .

- Final Questionnaire.

Single Item Instrumentality

- Pre- test for Non- Experts .

- Instructions for Experts .

menstruation»
I

References .

vii

- Experimental Task - Progressive Matrices .

114

. 115
. 116

117

. 122
. 123

126

Z 131

. 149

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LIST OF TABLES

11.912

Experimental Design .

Cell Means - Performance
Contrast Coding Coefficients.
ANOVA - Performance .
Contrast Coding Results .
Sub—hypothesis A

,Sub-hypothesis B

Sub- -hypothesis C . . . . . .
Sub- -hypothesis D and E. . . . .
ANOVA - Performance Change Score
Cell Means - Performance Change Score .
Omega Squared Results . . .
ANOVA - Variance in Performance .

Mean Scores - Six Round Variance in Performance .

ANOVA - Six Round Performance Variance
Means of Variance - Six Rounds

Brown Forsythe Test .

Question One Responses

Frequencies: Reward X Information Sharing
Frequencies: Reward X Work Style .

Frequencies: Work Style X Receiving Information.

Frequencies: Work Style X Information Sharing.
Frequencies: Expertise X Information Sharing .
Frequencies: Reward X Information Sharing
Frequencies: Reward X Information Sharing
ANOVA - Initial Expectancy .
Computation of Expectancy - an Example

Cell Means - Expectancy .

ANOVA - Change in Expectancy

Cell Means - Change in Expectancy .

ANOVA - Single Item Instrumentality .

Cell Means - Single Item Instrumentality
ANOVA - Fisher 2 Scores . . .
Instrumentality - Fisher 2 Scores .

ANOVA - Instrumentality Correlations

Summary of Research Findings

viii

100
101

Item

2.1
2.2
3.1

4.1

LIST OF FIGURES

Iitle

Diagram of Instrumentality .
Linkage of Theoretical Variables .
Research Design

Graph of Performance Results .

ix

.38

.40

.42

.73

INTRODUCTION

In a recent review of research on managerial control systems
Birnberg and Sadhu [1986] point out that a "model of the process by
which accounting budgets and reports are utilized in organizations," [p.
124] is emerging. The general objective of such research is "to
understand better the effects of accounting information and techniques
on behavior beyond those predicted by micro-economics in order to
identify the functional and dysfunctional effects of managerial
accounting systems" [p. 123]. In this study, several theoretical
sources are relied upon to formulate and test hypotheses regarding the
behavioral effects of incentive plans, which are one facet of management
control systems. According to Hopwood, "One of the principal means by
which senior managers attempt to motivate their managers and employees
towards effective performance is by linking organizational rewards to
the level of their performance" [1975, p. 95]. While that linkage can
take many forms the most obvious one is employee incentive plans.

The elements of any incentive plan include:

1. an agent(s) or employee(s) who provides effort or goods,
2. a principal or employer who provides a reward for the effort or
goods,

3. an agreement between the parties such that rewards are allocated to

2

the agent in accordance with certain defined levels of output,

4. a management accounting system which provides information that is
used in designing and implementing the plan.

This study explores the effect of incentive plans, feedback and the
opportunity for communication among employees on performance,
information exchange among workers, self assessments of ability, and on
beliefs regarding the performance-reward relationship. The questions
addressed in this study are significant because "information from the
management accounting system provides the basis for determining and
enforcing contracts among economic agents” [Kaplan, 1982, p. 4]. This
study differs from most prior accounting research on incentives in that
direct communication among workers is manipulated. In many studies,
"communication" is severely restricted both in format and content [e. g.
Waller and Payes, 1988]. The results of this study indicate that the
ability to communicate interacts significantly with incentives.

Incentive plans can differ along several dimensions. First, the
locus of the reward can differ, i.e., whether incentive plans are
distributed based on group or individual output. A second major
distinction among incentive schemes is whether rewards are structured
cooperatively or competitively. A reward scheme is cooperative if
attainment of one’s goals is positively correlated with other workers'
goal attainment. A reward scheme is competitive if attainment of one's
goal is negatively correlated with other individuals’ attainment of
their goals. For instance, a reward scheme which rewards group members
equally on the basis of total group output would be defined as

cooperative. On the other hand, a reward scheme which rewards group

3
members on a rank-order basis and results in differential payment is a
competitive scheme. A third criterion which distinguishes incentive
programs is the relationship between output (or performance) and reward.
The most common plan in practice is a piece-rate approach, which
involves a one-to-one relationship between output and reward. For
instance, a tax preparer might be paid $25.00 for each tax form
completed. However, many variants exist in practice.

Groups often play a role in incentive plans. The most obvious
instance is a competitive or rank order scheme in which an agent's rank
within a group determines his compensation or bonus. The question of
how group behavior is affected by incentive plans is unresolved. In
addition, the possible interactive effects of the incentive plans and
feedback or communication among group members have not been examined.
In designing incentive plans management accountants should consider both
the effect that the plan may have on the efficacy of feedback and the
effect that inter-agent communication may have under varying incentive
structures. The more general question of the relative efficacy of
various types of incentive plans has been explored under several
distinct theoretical approaches. Lines of research relevant to the
current study are the experimental approach in the psychological
literature comparing c00perative and competitive rewards, the work done
on expectancy theory, which includes both laboratory studies and field
studies, and, finally, the analytic approach of agency theory.

Within psychology and organizational behavior, a great deal of
research has been conducted on the question of whether cooperative or

competitive rewards result in higher performance or output levels. A

A
meta-analysis of over 100 studies [Johnson et al., 1981] emphasizes the
inconclusive results that can be inferred from this body of work. The
failure to reach definitive conclusions indicates that intervening or
mediating variables must be included in future studies. Possible
mediating variables include individual differences such as skills and
goals, as well as social behaviors leading to differential performance
levels. Inconclusive results may also indicate that the dependent
measure being studied is not sufficiently refined. Instead of looking
simply at the effect of incentive plans on performance, researchers
should study the effect of incentive plans on motivation, beliefs and/or
attitudes that correlate to performance.

Expectancy theory allows for that refinement by providing a general
model of motivation as a function of three theoretical constructs:
valence -- defined as the subjective utility of an outcome;
expectancy -- the subjective probability of attaining a certain level of

performance given a certain level of effort;
instrumentality -- the subjective probability of receiving a particular

reward given a certain level of performance.
According to expectancy theory, motivation and performance levels
increase when the subjective likelihoods of highly valued outcomes
increase. A major premise of this study is that both inter-agent
behavior and instrumentality are affected by incentive plans. Under a
cooperative incentive plan an increase in performance leads to an
increase in reward. Under a competitive incentive plan, an increase in
performance leads to an increase in reward only if one's rank in the

group changes. Thus, the connection between performance and reward

S
(instrumentality) is lower under a competitive reward. A second premise
is that feedback and incentive plans interactively affect expectancy.
To the extent negative feedback impairs performance, a decrease in the
expectancies of those subjects who are doing poorly relative to others
in the competitive condition is predicted. In summary, expectancy
theory variables provide a more refined measure of incentive plan
effects than simple performance comparisons by examining some of the
factors that drive performance.

A third line of research on the question of the relative efficacy
of incentive schemes appears within agency theory. In this paradigm,
organizations are defined as a nexus of contracts among the factors of
production. Relying on strict assumptions of rationality and utility
maximization, these theorists construct an analytic model which provides
the framework for the rational choice of compensation alternatives.
Within a line of agency research called the theory of contests,
researchers are investigating what theoretical circumstances render
competitive incentive plans superior to individual incentive plans.
While this approach has yielded some fruitful insights, it has
explicitly excluded consideration of the non-pecuniary aspects of
motivation [Demski and Feltham, 1978]. In addition, because this field
is fairly new, complexities which are common in the work world, but are
not easily modelled, are explicitly excluded. Thus, the agency model
has tended to focus on single period, single agent settings. The result
is that the possible incentive plan effects on behavior, such as
information exchange among agents, has not yet been addressed by the

theory of contests. Although agency research is not explicitly relied

6
upon to formulate hypotheses in this study, it does enrich the empirical
work and provides useful insights into the problems.

Two additional aspects of employment are controlled and studied in
this research - feedback and the effect of allowing inter-agent
communication. Feedback has been generally shown to have a positive
effect on performance, but the overall feedback effect differs depending
upon the context and content of the feedback. In this study, feedback
in a competitive reward scheme is predicted to have a negative effect on
the expectancy of those subjects who are performing poorly relative to
their group.

The second additional aspect of employment studied is that of
inter-agent communication. This manipulation proved to be very
significant in driving the obtained results. If these results prove to
be generalizable they have significant implications for management
control systems. Usually, employees do not work in isolation. While
the focus of agency work has been on the communication of privileged
information from the agent to the principal, another potentially more
important form of information is that of task-related expertise
exchanged among agents. When agents are rewarded cooperatively their
reward increases directly with increases in group performance. In the
competitive condition, agents are paid on a rank-order basis and receive
a greater reward only if their performance exceeds that of the other
group members. Thus information sharing among agents is expected to be
much more frequent under the cooperative reward plan than the
competitive reward. In this study information sharing proved to be an

important determinant of performance.

7

Over 300 students participated in this study by performing the same
task -- six sets of progressive matrices -- under varying incentive,
feedback, and communication conditions. The research design was a 2‘
factorial with one repeated measure. Four dependent variables were
directly measured and one was constructed statistically.

Briefly, the results of this study indicate that cooperative
incentive schemes result in significantly higher performance levels if
communication is allowed. If communication is not allowed, performance
under the cooperative incentive plan does not differ significantly from
performance levels under the competitive incentive plan. The expected
negative effect of feedback in the competitive condition did not occur.
Because predictability of performance can be an important factor in
management planning and control, the variance of performance was tested
and found to be significantly lower in the cooperative reward with
communication than in any other experimental condition. Both the
performance and performance variance results were highly significant and
suggest that incentive schemes should be designed to foster and,
perhaps, even reward information sharing among workers. If these
results are shown to be generalizable over a wide range of tasks and
settings, communication may be beneficial in the process of collecting
data as input to the management accounting system. Information compiled
by workers or managers who share ideas, cooperate in the gathering of
data, and provide feedback to one another at the input stage may be
superior to data gathered by managers who are not rewarded for such
cooperative behaviors.

Expectancy was hypothesized to improve with feedback in the

8
cooperative reward and to decrease in the competitive reward condition.
Instead, it improved with feedback in both incentive conditions, but the
improvement was greatest in the cooperative reward with communication
condition. These results parallel those found in analyzing the
performance measure. Information exchange was found to be significantly
higher in the cooperative incentive condition. Finally, the subjects'
perception of the relationship of their performance to reward
(instrumentality) was significantly affected by the reward condition.
The instrumentality of subjects paid under the cooperative incentive
scheme was significantly higher than the instrumentality of subjects
paid under the competitive incentive plan. In general, the results
were supportive of expectancy theory and also of the assertion that
comparisons of incentive plans must include consideration of possible
mediating environmental factors.

This study improves upon past research in several ways. First, it
explicitly includes the measure of a social process -- information
exchange -- that is affected by incentives and in turn affects
performance levels. Research based on a single agent working in
isolation provides a beginning to model development, but social
interaction is a reality in most work settings and the effects of
incentives on that interaction must be researched. Second, it applies
expectancy theory to the comparison of two incentive plans. Most prior
research on expectancy theory has compared hourly pay, which is not
performance based, to piece-rate or other performance-based plans.
These earlier results relate to the general question of the efficacy of

any performance related incentive and yield little insight into the more

9
difficult problem of which incentive plan to apply in a given work
setting. Third, it explores the application of expectancy theory in a
group setting. Fourth, in the statistical analysis the method of
contrast coding, a more powerful method of analysis than the traditional
ANOVA, is described and applied. Fifth, a multi-period setting is used
because single-period results are not always generalizable to multi-
period applications [e.g. Axelrod, 1984] and social processes may not
develop in a single period.

In the next chapter, previous literature relevant to this study is
reviewed. The following chapter describes the research hypotheses and
the adminiStration of the experiment. This is followed by the results
chapter. Finally, the concluding chapter presents the implications,
limitations, and strengths of this study, as well as suggestions for

future research.

LITERATURE REVIEW

Motivation

Managerial accounting systems generate much of the information used
in executing both the control system and the planning function of firms.
”Control system design encompasses choosing both the performance
standard and compensation scheme" [Chow, 1983, p. 667]. Belkaoui [1980]
asserts that the behavioral challenge facing management accountants is
the matching of the internal reporting system to those factors such as
the individual worker's perception of the firm's objective function, the
decision-making models used by the individual, and environmental
conditions that motivate the individual. In a similar vein, Dopuch et
al. [1974] observe that control systems may have dysfunctional
behavioral effects and that these effects comprise one of the criteria
by which such control systems should be evaluated. Experimental
evidence shows that subjects are highly responsive to differences in
reward systems [Luzi and Mackenzie, 1982] and that these responses are
not always predictable [Farr, 1976; Bull et al., 1987].

An important behavioral question then emerges. How can incentive or
compensation schemes be structured so as to promote goal congruence

between the firm and the agent?1 Particular emphasis is placed on the

 

1 In the literature the terms "incentive scheme" and "compensation

scheme" are not clearly distinguished. In general usage, "compensation
scheme" tends to be a generic term for any pay schedule, while incentive
plans tend to indicate a link between pay and performance. This rather
loose distinction is relied upon herein. E.g. straight hourly pay would
not be an incentive scheme. Both of the pay schedules used in this

11

problems of moral hazard and adverse selection, both of which arise
because of information asymmetry between workers and employers.
Employees possess superior information regarding their own abilities,
the state of nature, and the effort they must expend to perform at
certain levels. Since agents are not expected to voluntarily provide
this information to principals, a key element in designing incentive
schemes is the inducement of either information from agents (e.g., for
reducing slack in budgets or for allocating resources between divisions)
or actions by agents from which principals can infer information
[O'Keeffe et al., 1984; Green & Stokey, 1983; Holmstrom, 1982].

Another important type of information, but one which has received
little attention, is task related information that can be transferred
among agents. In agency theory the parties considered significant in
the exchange of information have traditionally been a single principal
and a single agent [Baiman, 1982]. A basic premise of this paper is
that task-related information exchange among agents is an important
factor in the performance of work groups. Examples of such information
include the suggestions of a production seamstress on how to most
quickly set a sleeve, to loan officers sharing financial information
about a loan applicant or a program to predict bankruptcies. Within
audit firms such information sharing could prove beneficial by
increasing productivity. In many firms audit staff are currently rank
ordered in annual ratings meetings, where promotions and raises are

determined. It is not clear that such ratings foster appropriate

 

study link pay and performance and are therefore, incentive schemes.
Finally, it should be noted that the following terms are used
interchangeably: incentive scheme, incentive plan, and reward structure.

12
behaviors. Despite high academic achievement, many junior auditors
would benefit from sharing basic information that could least
threateningly be conveyed by peers. The inclusion of a well-designed
peer rating on relevant information sharing behaviors could be
incorporated into performance appraisals. (Ilgen and Feldman [1983]
describe the effectiveness of peer review.) The benefits of information
sharing would have to be compared to the value of the performance
information derivable in existing evaluation systems to see whether such
a shift would be profitable. The extent to which incentive plans.
determine group processes, such as information exchange, has not been
thoroughly studied. To the extent such group processes affect

performance, the relationship warrants investigation.

Prior Research

Incentive plans can be differentiated along several dimensions. A
major dimension is the locus of rewards [Chow & Shields, 1986] where
locus is defined as the unit (usually an individual, a group, or a team)
whose output is being evaluated for purposes of reward distribution.
The effect of incentive plan locus has not been rigorously studied.
Instead, the comparison of group versus individual incentive plans is
usually discussed in field studies of incentive programs, in which many
variables are altered simultaneously, creating confounded variables and
allowing researchers to draw few conclusions.

Another dimension of incentive plans is whether rewards are
structured cooperatively or competitively. Cooperative plans are

defined as those in which attainment of reward is positively related

13
among workers; an example is paying group members equally based on the
entire group's output. Competitive plans are defined as those in which
the attainment of rewards by one person is negatively correlated to the
attainment of rewards by another person, as it is in a rank order
contest [Rosenbaum, 1980].

A third dimension which distinguishes plans is the relationship
between performance and reward. The most commonly used piece-rate
approach involves a one-to-one relationship between performance and
reward. In rank-order tournaments performance and rewards are not
directly related because one's reward is contingent on output or
performance relative to that of others who are being ranked [Nalebuff &
Stiglitz, 1983]. The perception of the relationship of performance and
reward is addressed in the section on expectancy theory research. While
very little research has been done on the social processes invoked by
various incentive schemes, the comparison of performance levels under
various incentive plans -- notably the contrast of cooperative versus
competitive rewards -- has been extensive. That research is discussed

in the next section.

0 a ve v Com etitive Reward
A major line of research relating to payoff patterns or reward
structures is the comparison of performance under cooperative and
competitive reward conditions. This includes studies in which rewards
are manipulated and others in which groups are encouraged or structured
so as to have cooperative or competitive working relations but are not

necessarily rewarded on those bases. It is only the former line of

14
research that has bearing on the issue being investigated herein and the
following literature review shall be mainly restricted to that category.

A major purpose of the current study is to examine the effect of
different reward structures on the group process of sharing task-related
information. In this study designated experts were subjects randomly
selected to receive information on how to complete the task which other
subjects did not receive. The experimental task was chosen to
facilitate monitoring of the relative frequency of information sharing
under the different incentive plans. Information sharing by the experts
was expected to be demonstrated by improvement in performance and was
probed directly in a final questionnaire.

Deutsch [1949] did the seminal work on performance differences under
varying reward schemes. He hypothesized and found support for greater
productivity when cooperative incentive plans were in force. Blau
[1954] obtained similar results in a field study. Employees in a public
employment agency were divided into two groups -- a cooperative one in
which employees were encouraged to share information and to help one
another place job applicants, and a competitive group in which workers
were evaluated based on individual performance relative to their co-
workers. In the competitive group the employees tended to hoard
information and consequently, productivity declined. The productivity
difference observed by Blau lends support to the hypothesis that for
those subjects allowed to communicate in this study, productivity will
be greater under the cooperative incentive plan.

Miller and Hamblin [1963] reviewed 24 studies comparing productivity

under cooperative and competitive conditions and found that the results

15

were fairly evenly divided. Miller and Hamblin hypothesized that task
interdependence was an orthogonally related trait that could account for
the divergent results. Task interdependence is the degree to which a
task can or cannot be executed without contact, assistance, or
information provided by others. They manipulated task interdependence
and found that in the high interdependence condition competitive rewards
were inversely related to productivity. In the low task interdependence
(hence called independent) condition the reward structure had no effect.

Weinstein and Holzbach [1972] argued that Miller and Hamblin's
independent group members may have felt so remotely connected that they
were simply individuals working on similar tasks, rather than
identifying as group members. They devised a task in which it was clear
that the output was a group output, even though individuals were
assigned different steps in the process. Groups were rewarded on a rank
order basis (one-half, one-third, and one-sixth of the total based on
group output) or on a cooperative basis - an equal share of a total
based on a group output. They found that productivity was greater when
the task was structured independently and was greater under the rank
order reward. Weinstein and Holzbach used a rank order scheme which had
the interesting feature that the group's total pay was a linear function
of the group productivity. This is not the competitive reward scheme
used by experimenters. In fact, for less productive employees this
particular reward structure could possibly counteract the disincentive
of a fixed total bonus plan. The effectiveness of the Weinstein and
Holzbach incentive plan should be further investigated.

Scott and Cherrington [1974] repeated the independent portion of the

16

Weinstein and Holzbach experiment, and added an individual reward
condition. Productivity was again found to be greatest in the
competitive condition. In another extension of Weinstein and Holzbach,
Farr [1976] used an independent task, the sorting of computer cards. He
had two time-periods and manipulated the existence of a performance
based incentive plan and the locus of the reward scheme (either group or
individual). Output was greatest in the contest, lowest in the hourly
pay and equal in the group and individual piece-rate conditions. Thus,
the very existence of an incentive plan increased productivity.
Contrary to Farr's hypotheses, however, the subjects considered the rank
order contest significantly less equitable than the other incentive
schemes. The subjects' perception of unfairness suggests that workers
paid under such a plan might try to subvert the plan. As is the norm in
studies of incentives, subjects in Farr's research did not communicate
with one another; instead the groups existed only as comparison units
for computing rewards. Thus, the effect of the pay schemes on group
interaction was not addressed.

In French et al. [1977] children built towers out of building blocks,
a highly interdependent task. French found that productivity was
inversely related to the extent of differentiation in rewards, i.e.
cooperative rewards yielded the greatest productivity. Rosenbaum et a1.
[1977] had adult subjects perform the same task and added an independent
task condition in which individuals worked alone. In that condition
productivity was not affected by reward structures. However, with an
interdependent task, productivity was highest in the cooperative reward

condition and lowest in the competitive condition. In addition, a

17
measure of efficiency of work procedures showed that the competitive
condition was less efficient than the other two conditions.

In a replication of that study Rosenbaum et a1. [1980] measured turn-
taking and found that it was significantly higher in the cooperative
condition than in the other two conditions, thus indicating that
subjects may use efficient production strategies when they serve the
group's interest. These last two studies are exceptional because they
did address issues of group process. Their results lend support to the
hypothesis that information sharing can increase productivity and.will
occur more frequently in cooperative reward conditions.

Johnson et a1. [1981] did a meta-analysis of 122 studies on the
effect of reward structure on performance. The results of three
different meta-analytic procedures showed that cooperative rewards
promote achievement more than competitive rewards or individualistic
rewards. In addition, competitive and individualistic rewards did not
correlate with significantly different levels of productivity. Johnson
et a1. [1982] responded to criticisms of their approach by providing
additional analyses, iterating their position that the number of studies
in which the same mediating variables are manipulated is generally too
small to allow for interpretable results. They concurred with their
critics on the importance of mediating circumstances and processes, but
said that "the social interaction processes mediating or moderating the
relation between cooperation and productivity have yet to be clarified
and consistently demonstrated" [p. 191-192].

Since interdependent tasks require cooperation it is not surprising

that cooperative reward structures generally lead to higher performance

18
levels on such tasks. Because the matrix task used in the current study
can be done individually, it is an independent task. However, the
results of a pilot study indicated that when subjects were provided a
brief, written explanation of the task, their performance improved
significantly. To some extent, therefore, the progressive matrix task
has characteristics of an interdependent task. All but the very
simplest independent tasks are also interdependent to some extent. In
this study the cooperative reward was expected to increase information
sharing, so higher performance was predicted in the cooperative
incentive than in the competitive condition.

As Rosenbaum [1980] points out, in studies of incentive plans the
usual dependent variable is productivity, with occasional measures of
error rates. Research does not usually address the effect of group
processes on productivity or the effects of incentive schemes on group
processes. Some research has been conducted, however, that relates
indirectly to the information sharing hypothesis.

Hackman et a1. [1976] manipulated the extent to which groups
interacted to discuss strategy for completing a task. In the strategy
condition groups were told to take about five minutes to discuss methods
for completing the task. By contrast, in the non-strategy condition
subjects were told to not waste time talking about the task. This
condition was crossed with a manipulation of task interdependence.
Using a performance rate calculated by dividing the value of
nondefective output by the time actually spent assembling, the results
for the high interdependence task were that the strategy group

significantly outperformed the non-strategy group and the results for

19
the independent task group were insignificant. In other words, with an
interdependent task the group process improved performance; in the
independent task, it had no effect.

Rosenbaum [1980] reports on an unpublished study in which subjects
collated parts of a booklet. An intermediate process required each
subject to complete a data card before proceeding to collate the next
set of pages. Subjects were told that they could process the data card
for the next person on the assembly line if they chose to. Even though
subjects were prohibited from communicating, the number of cards
processed for others in the cooperative reward condition was over twice
that in the individualistic and competitive conditions. This led to
significantly higher productivity. When the experiment was repeated
with the data card step removed, there was no reward effect on
productivity. Thus, the increase in productivity resulted from the
adoption of facilitative procedures by the cooperatively rewarded
subjects when such procedures were allowed.

Thomas [1957] had subjects construct cardboard houses. In some
groups each subject completed entire houses, while in other groups each
person did a portion of the house. This manipulation was crossed with a
reward manipulation, subjects were rewarded on either an individual or a
group condition. The groups which worked on sub-tasks and were scored
as groups performed better than the groups in which each individual
completed the entire task. However, the difference was not
statistically significant. Subjects working on subtasks reported
greater feelings of responsibility to other group members; and subjects

rewarded as a group were more willing to help others. Thomas's results

20
indicate that cooperative incentives motivate facilitative group
processes which can improve productivity. One of the purposes of the
current study is to test the possibility that reward structures affect
information sharing, which is one such behavior.

The possible effect of incentive structures on group processes has
significance because frequently individual employees in a group have
higher skills or more experience than other members of the group. Such
relative expertise enables them to work more efficiently or to produce
fewer errors than their colleagues. If these employees could be
motivated through incentive structures to share that information, higher
performance levels should result. Using the managerial problem of
negotiating transfer prices as their experimental task, Ackelsberg and
Yukl [1979] found that communication arose spontaneously among subjects
assigned the role of division managers who were paid on a corporate wide
basis but not among those paid on a divisional basis. In this study,
the corporate reward scheme corresponds to a cooperative plan, while the
divisional reward scheme correlates to a competitive plan.

Waller [1988] discusses the possibility of cases in which it is
desirable for production levels to be at or near those budgeted or
predicted. Problems could arise, for instance, if an intermediate
product was overproduced and created an excessive work-in-process
inventory. To the extent it is desirable to be able to predict work
levels or to be able to obtain approximately equal work output, variance
in output may be problematic. Bull et a1. [1987] described variance in
output as a cost to the principal in that it reduces the principal's

certainty regarding the agents' responses to a compensation plan.

21
Gruneberg and Oborne [1981] describe an incentive plan in an industrial
setting that was overly successful; parts were produced and loaded onto
a conveyor belt so quickly that they could not be used by the other
departments and caused storage and warehousing problems. Thus, it is
useful to look at the effect of the experimental variables upon
performance variance.

Predictability and consistency in productivity levels are important
management concerns, particularly in settings where standard costs are
used. Rambo et a1. [1982] studied consistency of output levels over
time. In a study of several work settings, Rothe [1978] found that
consistency was higher when an incentive system was in effect than when
pay was hourly. He says that "consistency of output, as measured by
week-to-week correlations, permits a statement about the effectiveness
of incentives," [p. 44]. An additional aspect of predictability is
important in setting standards -- uniformity of performance among
workers. Work standards will be perceived as more feasible if
individual output levels cover a narrower range, since smaller variances
imply that there would be fewer outliers, people producing much higher
or much lower than the standard. Varying levels of output can be
detrimental to motivation, depending upon the pay scheme or incentives
in place. Also, in some settings high variance of output causes
problems such as disruption in work flow, storage problems, and so
forth-

Consistent with Bull et a1. [1987] this writer considers consistency
a between subject variable. Other researchers such as Brewer and Kascer

[1963] and Rothe [1978] discuss consistency as an intra-individual

22
behavior over time. This is in line with attribution theory, where an
individual's performance history determines consistency and invariance
across individuals is called consensus. Rothe argues that consistency
over time is a necessary condition for an effective incentive plan.

It should be noted that the distinction between cooperative and
competitive rewards is not absolute, and is, in fact, dependent upon the
identification of a relevant group. For instance, while individual
professional baseball players may compete for the Most Valuable Player
award, they are rewarded cooperatively (as a team) for winning their
league playoffs. However, as a team they form a unit that is rewarded
competitively vis a vis other teams in the league. Thus, the
identification of the appropriate group is an important element of
determining whether incentive schemes are competitive or cooperative.

Overall, research results comparing cooperative to competitive
incentive schemes have been mixed. If tasks are interdependent, then
cooperative reward structures result in higher performance levels; while
if tasks are independent, competitive reward structures yield higher
performance. A weakness of this line of research is that a general
theoretical framework has not been formulated. Both Rosenbaum et a1.
[1980] and Johnson et a1. [1981] point out the lack of research on the
effect of incentive schemes when tasks are independent. Therefore, the

task used in this study is one which can be completed independently.

Expectancy Theory

G ne a1 back round. Expectancy theory provides a model of individual

motivation which accounting researchers have used to investigate a wide

23
range of work-related behavior, including job choice, selection of
method of pay, goal setting, and effort levels. According to expectancy
theory, behavioral choices are based on outcome attractiveness and the
perceived likelihood that a given act will lead to desired outcomes.
Within this framework some hypotheses about incentive structures emerge
[Ronen and Livingstone, 1975]. Incentive plans are expected to affect
instrumentality (defined below) and feedback is expected to affect
expectancy (also defined below). These two constructs, in turn, have
been shown to correlate to performance. Expectancy theory enables
researchers to begin to study the process by which incentive plans cause
differing performance levels.

The theoretical model in the seminal work on expectancy theory
[Vroom, 1964] includes three basic elements. Valences are the expected
utility of a particular outcome or event.2 Expectancy is the subjective
belief concerning the likelihood that effort will result in a certain
level of performance [Mitchell, 1982]. Instrumentality is the
subjective belief that a certain level of performance will lead to a
particular reward. In general terms the model has been presented as:
Force to perform - f[E - E (I . V)]

where E - Expectancy - Subjective Pr(Performance I Effort)

1 - Instrumentality - Subjective Pr(Reward I Performance)
V - Valence - Subjective expected utility of Reward

[Vroom, 1964]. More complex formulations have been introduced [Ronen &

 

2 Vroom also defines valence as the anticipated satisfaction of an
outcome (1964).

24
Livingstone, 1975; Ferris, 1977], but Schwab et a1. [1979] raise
concerns that elaborate formulae may "overintellectualize" the cognitive
processes people carry out in making choices.

In his discussion of expectancy theories, Belkaoui [1980] enumerates
some implications this theory has for management accounting. He said
that expectancy theory variables should be considered by managers in
determining how extrinsic rewards should be related to work performance,
in using feedback to increase the individual's expectancy, and in
rewarding individual effort in order to influence instrumentalities [p.
68]. Research on expectancy theory has shown that within the employment
setting workers select effort levels or engage in activities that
maximize their expected benefit. Jiambalvo [1979] successfully applied
the expectancy model to predict which job responsibilities auditors
would direct the greatest effort toward, contingent upon their
perception of the duties most highly valued by their superiors. Magee
and Dickhaut [1978] found that subjects used different decision rules
when faced with different compensation plans, as was predicted within
the expectancy paradigm. Dillard [1979] found that expectancy model
variables predicted junior auditors' occupational and position goals.

Incentives and Instrumentality. While the concept of instrumentality
has received less attention than either valence or expectancy, it is
recognized as a key link in the employee motivation- performance link.
Sims et a1. [1976] say, "The prevailing opinion is that perceptions of
performance-reward probabilities are an important factor in motivating
employees to improved performance" [p. 556]. Several studies have been

done on instrumentality and its relationship to performance. Wofford

25
[1971] found a biserial correlation between performance and expectancy-
instrumentality of .433. Harrell and Stahl [1984] provide evidence that
the weight given to the combined valence—instrumentality variable is
approximately four times that given to the expectancy variable,
indicating the importance attached to extrinsic rewards for performance.

Since incentive plans link performance levels to rewards, they are
expected to affect instrumentality. Schwab [1973] found that pay
schemes accounted for approximately 40% of the variance in
instrumentality ratings. Ilgen et a1. [1981] found that instrumentality
was highly dependent upon the pay structure in effect. It should be
stressed that the usual comparison in the studies cited is between
instrumentality in hourly or flat-rate incentives versus piece-rate
plans. Because there is virtually no connection between performance and
reward in a flat-rate pay scheme it is not surprising that
instrumentality is lower under such a scheme than it is in a piece-rate
plan. In the present study, the comparison will be between
instrumentality in two performance based plans -- one cooperative and
one competitive. This is a more subtle distinction and therefore
provides a more powerful test of the concept of instrumentality.

The strong link between instrumentality and performance has been
demonstrated. Campbell [1984] found that the instrumentality of the pay
scheme significantly affected performance. Cammann and Lawler [1973]
describe an incentive plan which failed because the relationship between
performance and rewards (instrumentality) was extremely complex and was
not understood by the employees. In that case a low instrumentality was

related to a low level of performance. These results reinforce the

26
conjecture made by Davis [1969] regarding the importance of reward
schemes in social settings.

It should be noted that Davis was commenting on group effort; while
expectancy theory is a theory of individual motivation. The effect of
aggregating expectancy theory concepts in a group setting is not
entirely clear. However, the general model is expected to apply in the
group setting of this experiment. The voluminous prisoner dilemma
literature, and other research [e.g., Becker, 1978; Chung & Vickery,
1976], provide strong support for the importance of extrinsic rewards.
In addition, Ronen and Livingston [1975] argue that groups enhance the
extrinsic valences of a worker and that workers are highly motivated to
comply with group norms. In summary, the group setting is expected to
enhance the validity of expectancy theory, which predicts that incentive
plans significantly determine instrumentality, which, in turn, affects
performance3 and/or effort.

Feedback and Expectancy. The beneficial effect of the knowledge of
results (one form of feedback) upon performance is one of the best
established findings in organizational behavior [Becker, 1978; Kim and
Hamner, 1976]. Within expectancy theory “feedback should play a vital
role in establishing a recipient's belief in the effort-performance

relationships (expectancies), which in turn should influence his or her

 

3In many experiments, including this one, performance is used as a
surrogate for effort. While this is far from ideal, it has proven
extremely difficult to construct meaningful tasks which do not involve
some measures of abilities. Researchers have been forced to use fairly
trivial tasks such as pushing a button or blowing air into a bellows in
order to eliminate the effect of ability.

27
desire to respond to the feedback” [Ilgen et al., 1979, p. 362].‘ The
same researchers indicate, however, that there are many mediating
factors which affect the positive connection between feedback and
performance. Chung and Vickery [1976] provide some evidence that
feedback and incentive plans affect performance interactively. The
relationship between feedback and incentive plans is being explored in
this study.

Feedback has two basic functions: it can "direct action by offering
informational cues...and/or it can influence motivational state” [Strang
et a1. 1978, p. 446]. In their research Strang et a1. provide evidence
that feedback may be necessary to the efficacy of assigned goals. Chung
and Vickery [1976] explored the possible interaction of the effect of
feedback and incentives schemes (either piece-rate or an hourly rate)
and obtained marginally significant results, indicating that feedback
provided under a piece-rate incentive plan had a positive effect on
performance. Chung and Vickery’s findings suggest the need for
additional study of how other incentive structures might interact with
feedback.

One response to feedback is a change in effort level, which is a
main variable of interest in expectancy theory. The sign of feedback
(i.e. whether it is positive or negative) can be significant. In an
early study negative feedback caused performance to worsen [Meyer et

al., 1965]. The favorability of feedback has been found to affect

 

‘The same researchers assert that feedback plays, "a major role in
the establishment and maintenance of beliefs about behavior-reward
contingencies," i. e. instrumentalities [Ilgen et al., 1979, p. 363].
They do not explicitly test this assertion, however.

28
subjects' perceived task competence, which is related to expectancy
[Stone & Stone, 1985]. Consistent with that result, Earley [1986]
showed that the sign of feedback has a significant effect on self-
efficacy or expectancy, which in turn, operates on performance. He
says, ”The importance of sign is to provide an individual with
information relevant to the estimations of capacity to perform.”
Because the agent's pay is based on relative performance in the
competitive incentive plan, some agents will receive negative messages
that they are the low performer in their group. If negative feedback
impairs performance, this effect is expected in the competitive
condition but not in the cooperative condition. In the contest, a low
performer receives feedback indicating that he is the worst in the group
and this is hypothesized to carry negative connotations. In the
cooperative condition a low performer receives a low score, but is not
told additionally that he is doing worse than the other people in his
group.

Bandura [1982] discusses the concept of self-efficacy, which is a
more general sense of abilities than expectancies, but which can be
measured in specific instances and is considered analogous to
expectancy. He found that past performance was the key determinant of
self-efficacy. Similarly, Locke et al. [1984] found that self-efficacy
had a significant, positive effect on performance. Self-efficacy is
measured more directly than the conditional probabilities involved in
expectancy measures. For instance, Locke et a1. asked subjects whether
they could perform at various levels and how certain they were of that

prediction, as opposed to asking what performance levels people would

29
expect if they expended differing levels of effort. (See Appendix C).
Locke et a1. [1984] showed the tie between self-efficacy and expectancy
theory. Self-efficacy was shown to be strongly linked to goal level,
task performance, and goal commitment, even when controlling for ability
and past performance. Locke et a1. [1984] argue that their scale, which
is based on confidence ratings rather than the usual estimates of the
probability of success, is more valid than most other scales used in
this type of research.

While a change in effort is one response to feedback, an alternative
reaction is suggested within the theory of contests, which is discussed
more fully in the next section.‘ According to the theory of contests, a
Stackelberg equilibrium is likely to emerge when feedback is provided
and abilities are widely variant. Such equilibria emerge in settings or
industries with a limited number of players, who are aware of each
other's power or abilities (Nicholson, 1978]. In a rank-ordering,
feedback will indicate to a low performer that he is not likely to
excel, so he will not work to his full abilities. At the same time a
high performer will assume that a low performer is reasoning precisely
that way, and will consequently also expend low effort [Dye, 1984;
O'Keeffe et al., 1984]. This result is predicated upon an assumption of
agents' effort aversion. In this scenario, the effect of feedback upon
performance is negative due to reduced effort by all group members.

In summary, prior research and expectancy theory would predict
generally beneficial effects from feedback. However, to the extent the
lowest performers in the competitive condition consider their feedback

negative, their performance is expected to decrease. This contrasts

30
with the theory of contests, which suggests that if abilities are
unequal the effect of feedback on all agents may be negative. The
resulting Stackelberg solution results in low effort levels by all
agents in a rank order incentive scheme. The interactive relationship

of feedback and incentives will be explicitly tested in this study.

Theory of Contests

The main analytic research approach investigating incentive schemes
is agency theory, in which an analytic model provides the framework for
the rational choice of compensation alternatives. In contrast to the
standard neoclassical position which models the firm as a production
function responding to market demands, the agency theorists focus on the
contractual relations among economic actors and view the firm as a nexus
of contracts among the factors of production. As Fama [1980] has
pointed out the agency theory literature has moved away from the
neoclassical model while it still includes the basic assumptions of the
model. Although it was not the original intention of the neoclassical
economists to derive a descriptive or normative theory of individual
managerial behavior, some managerial accounting researchers use this
theory to describe optimal individual behavior [Namazi, 1985].

An additional limitation of this line of research is that due to the
intractability of the model in multi-period and multi-agent settings,
researchers have generally focussed on single period, single principal,
and single agent settings [Namazi, 1985, Baiman, 1982]. Recently,
however, some researchers have explored the single principal, multiple-

agent setting. This line of research is called the theory of contests.

31
The purpose is to compare rank-order contests to other incentive plans,
usually piece-rate plans. Results are generally supportive of the use
of rank order contests. This theory is very recent and not fully
developed. Several of the researchers informally address some of the
consequences of agent interaction and communication; no formal model
allows for such interaction. However, the existing results shed some
light on the relative merits of the two types of incentive schemes and
are reviewed briefly below.

Lazear and Rosen [1981] assume a single period, two players (agents)
of identical skills, and no communication between agents. Output is
dependent on both individual characteristics such as worker effort or
skill, and on a random environmental shock. If agents are risk averse,
the superiority of an incentive depends on the relative variance of the
common shock and the individual random element of output. As the common
shock increases in importance, rank order tournaments become superior to
individual incentive plans.

Holmstrom [1982] urges the use of rank order incentive schemes, not
because of any benefit from competition per se, but because the effort
or performance level of one agent providesthe principal with
information regarding other agents. Holmstrom says that rank order
tournaments do not necessarily imply an efficient use of information and
suggests using an aggregate statistic, such as the mean of the agents'
performance to measure individual agent's output. In the absence of a
random shock, the theory predicts tournaments will be less productive
than individual incentive plans.. One should note that Holmstrom's model

does not allow for communication between agents.

32

Green and Stokey [1983] conclude that in the absence of a common
shock, independent contracts dominate tournaments. However, if the
diffusion of the environmental shock is sufficient then the tournament
is more productive. O'Keeffe et a1. consider the problems of
differential abilities and concede that "for many distributions of
workers' abilities, there may be no contest that induces efficient
effort." Despite these limitations to tournaments O'Keeffe et a1.
[1984] conclude that contests are an ingenious solution to market
imperfections such as indivisible rewards and asymmetric information.

It is important to note that the above researchers do not address the
issue of worker communication.

By way of contrast, Dye [1984] points out several weaknesses of
tournaments, including the possible consequences for inter-agent
communication. He discusses the potential for collusion,
counterproductive behavior, and the motivational problems which arise if
the abilities of the agents are unequal and are known by the agents. He
feels the most likely of these is the Stackelberg strategy or
equilibrium, which he describes as follows. Assume that two workers are
paid on their relative rank and that both worker A and worker 8 know
that A is twice as productive as B.

...Then B might reason as follows: regardless of what effort level

I select, if A selects the same effort level then I will be very

unlikely to win the tournament, so the best I can do (given that

effort is distasteful) is to apply no effort. A would in turn

exert no effort if he believed that B reasons as above, with the

net undesirable effect (from the principal's point of view) that no

effort would be exerted by either participant [Dye, 1984, p. 147].

The occurrence of collusion or actively counterproductive behavior is

not studied in the current research. However, the possible consequences

33
of negative feedback are explicitly hypothesized and tested in the
current study.

Nalebuff and Stiglitz [1983] also address some of the possible
effects of contests on agent behavior. In an informal discussion of
some of the limitations of contests, they suggest that eliciting
cooperative behavior among agents may significantly affect productivity.

In situations where contests are frequently observed, such as a

patent race, there may be technological returns to cooperation, as in

sharing information. In the competitive system, there are no
incentives for cooperation. There are even rewards from engaging in
destructive activity if it can hurt one's rival more than oneself.

The piece rate system will encourage agents to cooperate when it is
mutually beneficial, and this potentially may be very important.

[P-40]

The effect of information sharing is being investigated in this study
because, for this task, information transfer can lead to increased
productivity.

Very little empirical work has been done in support of the theory of
contests. In Bull et a1. [1987] subjects were involved in a tournament,
with payoffs determined partly randomly and partly by subjects' effort
level. Bull et al. found that whether subjects were rewarded on a
piece-rate plan or a rank-ordering, they reached the same equilibrium
effort level. However, the contest condition resulted in significantly
greater variance of effort than did the piece-rate plan. This result
was not predicted by the theory and has serious practical implications.
Bull et a1. conclude, "It appears that a cost to choosing a tournament
system over a piece rate system is that the principal must bear
uncertainty as to how the agents will react to the tournament" [1983, p.

29]. The researchers conjecture that the cause of this variance might

34
be a result of the game nature of tournaments, rather than the
information structure. Because predictability of performance is
sometimes desirable in management planning, the effect of incentive
plans on variance in performance is explicitly tested in the current
study. Bull et al. also manipulated abilities and found that the theory
of contests yielded better predictions when abilities were equal than
when abilities were divergent.

Greenberg [1986] addressed some of the issues in the theory of
contests. Greenberg's independent variables were the incentive plan and
the environment; the environment manipulation was an operationalization
of the random shock in HolmstrOm's model. Half the subjects faced a
common random shock and the other half operated in environments separate
from the other subjects. In half the groups the bonus pool was
distributed cooperatively (equally). In the other half the pool was
distributed competitively such that the agent choosing the highest
effort level received the greatest percentage of the bonus pool.
Greenberg found that the competitive compensation scheme was most
beneficial to the owner in both environments. In addition, for either
incentive scheme, the owner's payoff was higher when agents operated in
a separate environment. These results conflict with Holmstrom's
hypothesis that competition is useful only if it provides information
about common environments. Greenberg gives no indication that subjects
communicated with one another, so the possibility of cooperative
processes was not explored.

In summary, analytic research provides arguments and a limited amount

of empirical evidence which demonstrate that competitive rewards

35
dominate piece-rate incentives plans when environmental shock is great
and the abilities of workers are equal. Rank-order incentives schemes
may be problematic for some as yet unspecified distributions of ability,
in the absence of environmental shock, and, most importantly, if agents
can communicate. Researchers in the theory of contests contrast a rank-
order pay scheme (which has a group as its locus) and individual piece-
rate incentives plans. Thus, two variables are being manipulated and
compared -- the cooperative or competitive aspect of the incentive plan
and the group or individual locus of the plan.

In this study a rank-order incentive scheme is compared instead to a
group-based piece-rate incentive plan. This avoids the confounding
effect of changing two dimensions of incentive plans. While the theory
of contests assumes multiple agents it does not specify or allow for
inter-agent interaction, thus precluding consideration of the behavioral
consequences arising from working in groups and from group norms [Young,
1985, 1983]. Because the focus of this research is on non-mechanistic
responses that incentive plans may invoke, and because the existence of
a group does affect behavior, it is important to maintain a group locus
when comparing cooperative and competitive reward plans. Therefore, the
theory of contests is not explicitly tested in this study, but is relied
upon because of the insights it offers to certain relevant aspects of
the comparative study of incentive plans.

Furthermore, while the agency model has yielded many valuable
insights, its applicability to questions of individual behavior has been
questioned. Scapens and Arnold [1986] argue that agency theory is not

suitable for the study of individual behavior because it is founded in

36
neoclassical economics. Two basic assumptions of that branch of
economics are the economic rationality of economic agents, and the
economic allocation of resources through a market reflecting marginalist
utilities. When applied to individuals rather than to firms, both of

those assumptions have been questioned.

Theory Linking Independent Variables

According to Mitchell [1982] expectancy theory suggests "that
reward contingencies would be a major determinant of expectancies and
instrumentalities” [p. 308]. However, this hypothesized relationship
has not been thoroughly researched. Since incentive plans indicate the
objective relationship between performance and reward, they are used to
affect instrumentality, the perceived connection between performance and
reward. According to expectancy theory, incentive plans which are
perceived as directly relating a given output level to a certain reward
have higher instrumentalities and are expected to result in higher
effort or performance than incentive plans which connect performance and
reward less directly. The cooperative incentive scheme used in this
research consists of a variable bonus pool which is based on total group
production and is shared equally among group members.

Because the reward is determined using a piece rate, pay is a simple
linear function of the group's output. In other words, the relationship
of reward and output is a monotonic function. For any subject an
increase in his output will lead to an increase in payoff, regardless of
what other members of his group do. Since his output is pooled, he

receives only 1/3 of the $ .25 paid for each correct response. Of

37
course, he shares equally in the output of his group members' production
as well. The crucial point is that he is aware that if he has more
correct responses, he receives a higher level of pay. Figure 2.1
illustrates the connection between the group performance and the amount
an individual would be paid for a single problem set. As the
performance of the group increases, the individual's compensation
increases.

By contrast, the competitive incentive scheme will consist of a fixed
bonus pool which is to be split unequally among group members depending
upon their relative ranking within the group. Thus, the reward received
is not linearly related to performance; instead, the reward function is
a step function. In addition, pay is not a function of absolute level
of performance, but of one's performance level telative to that of other
group members. Green and Stokey [1983, p.351] say that, "Competing in a
tournament is like being judged against a standard that is a random
variable (the opponent's output)". (See Figure 2.1.) As Bull et a1.
[1987] point out, piece-rate schemes present workers with a simple
maximization problem, while tournaments present workers with the less
easily solved situation of a game. An individual cannot assume that if
his performance improves he will necessarily receive higher
compensation. The key to higher rewards is surpassing the performance
of another group member. The absolute level necessary to do so is not
known in advance of performing the task. That is why question marks
appear on the X-axis of the lower panel of Figure 2.1. These
characteristics of contests imply that the instrumentality of a contest

is lower than that of a piece-rate incentive.

38

INSTRUMENTALITY: THE LINK BETWEEN PERFORMANCE AND REWARD
Coo r v ew

As the pooled performance of the group improves, the compensation
received by each member of the group increases.

$2.50

COMPENSATION
RECEIVED

 

 

q 30

GROUP PERFORMANCE

Com t t ve ew
As an individual's performance improves, his compensation increases IF
and ONLY IF his performance exceeds that of someone else in the group.

The individual performer does not know what level he must attain in
order to receive a higher level of compensation.

$2.50 -————-

COMPENSATION $1.50 -——-————o
RECEIVED

$.50 -——-——o

 

 

0 ? 7
INDIVIDUAL PERFORMANCE

Figure 2.1
Diagram of Instrumentality

39

A graphic representation of the expected relationships among the
dependent and independent variables is presented in Figure 2.2. The
independent variables are shown in the left column outlined with double
scoring and the dependent variables are outlined in single scoring.
According to the model, feedback affects expectancy, which, in turn,
affects performance. The presence of an expert is manipulated primarily
to provide the experimenter with some controls on information sharing.
That variable is predicted to interact with incentives to affect
information sharing. In addition, the presence of an expert in a group
is expected to have some effect on expectancy. Incentives are the
primary independent variable and are expected to have an impact on
expectancy, instrumentality, and information sharing. By definition,
the opportunity to communicate is a necessary, though not sufficient,
condition for information sharing. It is hypothesized that information
sharing will be more frequent in the cooperative condition and in cells
in which "experts" have been given additional information on how to
perform the task. Expectancy, instrumentality and information sharing
all, in turn, affect performance. The research hypotheses are developed

and explained in the next chapter.

40'

 

 

" FEEDBACK H
-‘_‘_“_‘.‘_““-——€> EXPECTANCY

,,,,—”"’/””””7

INSTRUMENTALITY \

/’

INFORMATION SHARING

 

 

 

INCENTIVES

 

L___J

     
 

 

 

 

[—COMMUNICATION I

ll EXPERT IN GROUP "/

   

 

 

 

 

 

 

Figure 2.2
Linkage of Theoretical Variables

 

 

PERFORMANCE

 

 

HYPOTHESES AND RESEARCH METHODS

The purpose of this study is to explore the effects of performance
incentive plans, the opportunity of workers to communicate, feedback,
and expertise, on performance, information sharing, and on two
expectancy theory constructs -- expectancy and instrumentality. The
hypothesized relationships are tested in a laboratory study. This
experiment is a 2‘ factorial with three between subject variables and
one within subject variable as follows:

Betweeg subject variables;

1) reward structure - cooperative versus contest

2) presence of an expert in the group - yes or no

3) opportunity to communicate - yes or no

Wi sub ect variab e'

4) feedback given to the subjects - no for the first three periods
and yes for the second three periods.

A brief narrative form of the hypotheses is presented below (the
dependent variables are underscored). The full development of the
hypotheses in explicit, testable form is provided in the following
section of this chapter.

Hypothesis 1: Performance will generally be higher in the

cooperative reward and when communication is allowed. In the

41

42

competitive reward only, feedback is expected to have a negative effect

on petfotmance.

Hypothesis 2: The variance of performance in work groups will be

higher in the competitive reward.

Hypothesis 3: Among subjects allowed to communicate, those working
under the cooperative reward will have higher rates of information
shating than those rewarded competitively.

Hypothesis 4: Reward and feedback will have an interactive effect on
expectancy. Feedback will increase expectancy in the cooperative reward
condition and decrease expectancy in the competitive condition.

Hypothesis 5: Instrumentality will be higher in the cooperative

reward condition than in the competitive reward.

Reseatch Design

The design of the experiment is presented in Figure 3.1.

Reward Structure

 

 

 

 

 

 

 

 

 

 

 

 

Cooperative Competitive
Communication Allowedz
Yes No Yes No
WITHOUT FEEDBACK
Expert in Yes 1 2 3 4
Gtoppz No 5 6 7 8
a
WITH FEEDBACK
Expert in Yes 1F 2F 3F 4F
Group? No 5F 6F 7F 8F
Figure 3.1

Research Design

43

In later discussions of the hypotheses, experimental cells are referred
to by the numbers assigned in Figure 3.1. For instance, ”1F" represents
the following experimental condition: cooperative reward scheme, with
communication allowed, an expert in the group and with feedback
provided. This cell represents the last three periods of the
experimental session that corresponds to cell 1, and has the identical
manipulations except that feedback is provided in cell 1F and not in
cell 1.

The reward structures to be used are a cooperative group piece-rate
scheme and a rank-order contest. In the cooperative plan each member
receives an equal share of a total determined linearly on the total
number of correct responses by the three group members. In the contest
the most productive member of the group receives one-half of the total
fixed "bonus," the second most productive member gets one-third, while
the least productive member receives one-sixth of the bonus.

The second manipulated factor is the existence of an expert, i.e. one
member who is given a brief introduction to the construction and logic
of the experimental task, and some heuristics on how to quickly perform
the task. Half of the groups will not have expert members, i.e. all the
subjects in those groups will be naive. This factor is introduced to
allow some independent evidence of the extent of communication within
groups.

The third manipulated variable is the opportunity for group members
to communicate with one another. The hypothesized effect on

productivity is based on an interaction of communication and reward

44

structures. While it may seem perverse to manipulate the possibility of
communication in a study focussing on information transfer, it is
necessary to have the full factorial experiment in order to test the
interactive effects of cooperative versus competitive rewards with and

without communication.

Administration

Before any work could be initiated and in accordance with university
procedures governing the use of human subjects, an application was made
and approved by the University Committee on the Use of Research
Involving Human Subjects.‘

The research was conducted using volunteer, student subjects at the
facilities of Michigan State University. Volunteers were solicited in
beginning and intermediate accounting classes, and in introductory
management classes. The management students received course credit as
well as being excused from writing a paper in return for their
participation in an experiment. The group size at various experimental
sessions varied because some intact classes were used, while at other
sessions, the experiment was conducted outside of the normal classroom
meeting time. The size varied from nine subjects to forty-five
subjects.

The experiment began with the distribution of an informed consent
form to the subjects. See Appendix A. Subjects were asked to refrain
from discussing the experiment with other subjects outside of the
experimental setting. They were also told they were free to leave at

any time during the experiment with the only penalty being forfeiture of

45
the right to any payment. At that time subjects were also given a card
with their subject number on it and asked to use this number on all
forms they received and subsequently completed. This provided anonymity
and eased the job of identifying subjects in data compilation and
analysis.

The next step in the experiment was to describe the subjects'
incentive plan for reimbursement. The cooperative incentive plan was
based on pooled group effort. A work group consisted of three people,
and subjects were paid $.25 for each problem correctly solved in three
randomly selected problem sets. That amount was put into a group pool
and the three group members were each paid one-third of the group pool.
In the competitive condition, students were paid on a rank-order basis.
The highest performer received $2.50 for that set, the middle performer
received $1.50 and the lowest scorer received $ .50. In both conditions
subjects were told they would be asked to complete more than three sets,
but that they would not know which three sets were reimbursable until a
lottery was conducted at the end of the experimental session.

For the expert cells (cells 1 - 4) the subjects were told that a pre-
test would be administered, and that there were three different pre-
tests. They were divided into three groups based on the last digit of
their subject number. Subjects were told that because of scheduling
problems, we had access to only two rooms. Expert subjects were taken
to the second room. The remaining two groups were separated but stayed
in the test room. Non-experts were given a test containing various
story problems and I.Q. test type problems (See Appendix F), none of

which were the type used in the experimental instrument. Although the

 

46

tests were the same for all subjects, they were printed on different
color paper and passed out separately and subjects were told that the
tests were different.

Experts were given a written explanation of progressive matrices, the
type of problem used in the experiment. The logic used in designing
such matrices was explained; and examples of the two types of matrices
in the actual test were provided. In addition, a heuristic for solving
them quickly was provided. See Appendix G. Questions were solicited and
answered. Two subjects were asked to explain the examples to the
experimenter to verify their comprehension.

Experts were told they were the only members of their group receiving
task information and that other subjects were completing unrelated
problems. In the communication condition, emphasis was placed on the
subjects' freedom to share information with other members of their group
at any time during the experiment. When subjects had no further
questions about the task, they were moved back to the original room. At
that time communication cell subjects were seated in close proximity.

If communication was not allowed, group members were seated apart from
each other.

Subjects were informed of their communication condition. When
communication was allowed, the experimenter stressed the possibility of
communicating at any time throughout the experiment. Subjects were
asked to talk -- if at all -- only with their own group. After
returning the experts to the original classroom, the experimenter left
the room temporarily in the communication cells. Leaving the room

provided subjects time to freely discuss task procedures with their

 

47

group and to lessen the possibility of demand characteristics regarding
sharing or hoarding of information. It was crucial to allow subjects
unconstrained decisions regarding information sharing.

The subjects were told they would be working for several periods, but
the exact number of periods was not specified in order to avoid end-game
strategies. Informed subjects could decide to share information for one
period only, or at a certain point in the sequence if they knew in
advance exactly how long the experiment would continue.

Subjects used a standardized test answer sheet to indicate responses.
They were also given a brief explanation of the nature of the problem.
The experimenter explained that they were to complete a multiple-choice
task involving the completion of a visual matrix of abstract symbols.
The sample matrix used had no particular pattern or method, and was not
an example of the sort of matrix used in the actual instrument. No
explanation of matrix logic or heuristic for solving matrices was
provided. This task was described as one drawing on visual skills such
as those involved in reading graphs, maps, three-dimensional schematics.
Subjects then indicated their initial expectancy on the expectancy form
(See Appendix B). This was a simple measure of how adept they felt they
were at such tasks as compared to the average person.

Once the consent and expectancy forms were collected, the actual task
began. The experimental session comprised six problem sets of ten
problems each. Set One was distributed face down. Each set lasted
three minutes. When time was called the test booklet was collected and
the second set was distributed. See Appendix H for test instrument.

After Set Two, subjects were asked to indicate their expectancy, i.e.

48
expected level of performance. See Appendix C.

The experiment continued with the administration of Set Three.
Starting with the third problem set, the researcher provided outcome
feedback (the number correct) to all subjects. This was simple outcome
feedback; no instructions or advice on how to solve the problems was
given. Only Set Three was evaluated; no information was given on Sets
One or Two. For all subjects the experimenter wrote the number correct
on the subject's number card which was turned in at the end of the
experiment. Additionally, in the competitive condition the subject's
relative rank in the group was provided since this was the sole basis on
which pay was determined. The ranking was not given in the cooperative
condition as that had less effect on an individual's pay. The
researcher gave only that feedback necessary to establish the link
between performance and compensation.

The researcher had a deck of cards and if there was a tie in the
competitive condition, subjects drew cards to determine who would
receive the higher pay. The experimenter did not formalize or discuss
the possibility of any side payments. While these may have occurred
after subjects were paid, no such arrangements were ever discussed in
the presence of the experimenters. It was stressed that a drawing at
the end of the experiment would determine exactly which problem sets
would be paid. In the cooperative condition the experimenters stressed
that a subject's pay would be pooled with his group members and then
divided equally. Thus, the amount on the card represented the amount
the person was earning for the group pool. After receiving feedback for

the first time, subjects were again asked to provide their expectancy.

49

This was done to determine whether feedback affected expectancy.

Set Four was distributed, completed, and evaluated. The same process
was followed for Set Five. After Set Five, however, expectancy was
measured again. Finally, Set Six was administered, with no additional
measures and no feedback. Students at that time completed a final
questionnaire. See Appendix D and E. The purpose of the questionnaire
was to gather data on information sharing behavior and instrumentality.
At that time, a lottery was held to determine which three of the six
problem sets were to be used to determine reimbursement. The
experimenter and her assistants calculated reimbursement while subjects
completed the questionnaire.

A second smaller set of subjects in the four cells of the
communication condition did the same experiment but completed a final
questionnaire which included a much more extensive instrumentality
measure. See Appendix D. This second administration of the experiment
was necessary because the instrument used in the first round was not
appropriately designed and had not been properly tested. The more
complete instrument was more time-consuming and an initial concern had
been to avoid taking more than 90 minutes because of the difficulty of
enlisting subjects.

The task items were taken from Ravens Progressive Mattices, problems
requiring the completion of a visual sequence of abstract shapes or
symbols. Such items are found in typical intelligence tests, including
the Stanford-Binet. See Appendix H. This particular type of problem
was chosen because while it can be done adequately without any

instruction, the pilot test showed that provision of some rudimentary

50
explanations of the matrices significantly improved performance. This
sort of problem is also a convenient one since it is a pencil and paper
task, lending itself to some privacy in a classroom setting. If
learning occurs, it should result from information provided by a
subject's own group members, not from observing the action of other
groups. A major purpose of the current study was to examine the effect
of different reward structures on a group process —- the sharing of
task-related information. The matrix task was chosen to facilitate the
determination that "experts” were more likely to share that information
with other subjects under one reward plan than they were under another
plan. Experts were the subjects who were briefed on how to complete the
matrices. The experiment was terminated when the subjects turned in the

final questionnaire and were reimbursed by the experimenter.

fiypotheset

The hypotheses will be presented according to which dependent
variable is being discussed. In all cases the alternative, or research,
hypothesis is presented without the null hypothesis, which is simply

that no differences exist among the relevant cells.

22; fptpance

The first hypothesis summarizes the interactive effect of
communication, incentive scheme, and feedback on performance. Since the
predicted model is complex, it is presented in two steps. First, the

reasoning underlying the relationships among sub-sets of cells is

51
presented. Then these sub-hypotheses are combined into a single model.

The first sub-hypothesis relates to the effect of communication. The
cooperative incentive plan is expected to induce information sharing;
therefore subjects with the opportunity to communicate are expected to
have higher output than subjects in the cooperative incentive without
communication. This would imply the following relationship for
performance:

Cells 1, 1F, 5, SF > 2, 2F, 6, 6F.

In the contest, however, communication -- if it occurs at all -- is
expected to have a negative effect. The possibility that group members
are not equally talented suggests that a Stackelberg equilibrium would
emerge [Nicholson, 1978] due to differential abilities. Such equilibria
arise in oligopolistic situations in which one firm is a clear price
leader and other firms are clear price followers. The Stackelberg
equilibrium in this study would occur if one group member is clearly
more capable of performing this task than other group members. The less
talented group members realize this and consequently do not strive to
outperform the high achiever. The following relationship is then
predicted:

Cells 4, 4F, 8, 8F > 3, BF, 7, 7F.

Because the results on previous research comparing cooperative and
competitive rewards have been mixed, researchers must consider the
effect of intervening or additional variables in formulating hypotheses.
The major prediction of this research is that in conjunction with the
opportunity to communicate, cooperative rewards will result in

significantly higher performance than competitive rewards do. In terms

52

of cell means this is represented as follows:
Cells 1, 1F, 5, SF > 3, 3F, 7, 7F

Prior results have been mixed, but generally, for independent tasks
without feedback and without communication output in contests has been
equal to or greater than output in cooperative rewards.

Cells 4, 8 > 2, 6

Despite general support for the positive effect of feedback on
output, the theory of contests predicts a negative effect of feedback in
the competitive incentive plan. Thus, the expected effect of feedback
is to reverse the pattern of the preceeding sub-hypothesis. In the
competitive incentive plan learning one's rank through feedback is
expected to be discouraging to the low producers and to indicate to the
high producers that with relatively low output levels they can be the
highest performer, which is the Stackelberg scenario. The resulting
relationship follows:

Cells 2F, 6F > 4F, 8F

When multiple comparisons of means are performed the likelihood of an
inappropriate finding of significance increases [Keppe1, 1982].
Therefore, the above relationships are combined into a single model,
based on the method of contrast coding.1 The advantages of this method

are threefold. First, the model does not use as many degrees of freedom

 

1 This method is also called orthogonal polynomials or trend
analysis [Keppel, 1982]. However, since all the independent variables in
this study are dichotomous, the only pattern possible is a linear one.
Therefore, it seems more appropriate to use "contrast coding,” the
phrase that Cohen and Cohen [1975] use for this type of coding, as it
avoids the implication of quadratic or higher powered interactions,
which do not apply in this study.

53

so the statistical power of the test is not decreased as it is when
multiple tests are performed. Secondly, power, the likelihood of
finding a significant effect when it does exist, is increased. Thirdly,
this method enables the researcher to test for interactive relationships
other than the crossover interaction, which is the interaction that the
traditional ANOVA detects most powerfully. Using contrast coding, the
relationships shown above are aggregated into a single hypothesis, which
models the expected patterns of performance level among subjects in all
sixteen experimental cells. Again, the numbers below refer to
experimental cells:
HYPOTHESIS l: Pettormance is the dependent variable.

1, IF, 5, SF > 2F, 4, 6F, 8 > 2, 4F, 6, 8F > 3, 3F, 7, 7F
This prediction says that generally performance is higher in cooperative
rewards and the effect is increased by the opportunity to communicate.
In addition, if subjects are not allowed to communicate, the effect of
feedback is expected to be positive only in the cooperative condition.
Under the competitive incentive plan, feedback is expected to impair
performance.

The above hypothesis provides a tentative empirical test of one of
the conclusions within the theory of contests. In this experiment there
were six problem sets. However, subjects were monitored and paid for
only three of those problem sets. Since these were randomly determined
at the end of the experiment, subjects did not know which sets they
would be paid for until after they have completed all six rounds. This
random choice of problem sets is, according to O'Keeffe et a1. [1984], a

type of random environmental shock in the monitoring system. O'Keeffe

54

et al. describe various ways to increase randomness in the monitoring
process -- the timing of spot checks, the use of more impressionistic
evaluations, or paying differing amounts of attention to performance [p.
32-33]. In the current experiment the random shock is uncertainty about
the monitoring system and it is present in all experimental conditions.

By contrast the expert member is an individual abilities manipulation
and is present in only half the groups. This allows a preliminary test
of the two incentives' relative effectiveness when the individual
element dominates and when the environmental element dominates.
According to the theory of contests, when the environmental shock
dominates, contests are superior, which would imply that performance in
cells 7 and 8 is higher than in cells 5 and 6, which is contrary to the
model above. Alternatively, in those groups with an expert it is
hypothesized that the individual differences will outweigh the
environmental shock and, cells 1 and 2 would have higher performance
than cells 3 and 4. If the data indicate that cells 7 and 8 exceed
cells 5 and 6 app cells 1 and 2 exceed cells 3 and 4, the theory of
contests could provide an alternative explanation. If the data do not
indicate this pattern, then they provide some empirical results in
conflict with the theory of contests. However, any results related to
the theory of contests are at best suggestive, since the strict

assumptions of the models are not met in this experiment.

e o a c Va iance
In addition to performance levels, managerial accountants must also

consider the incentive plan's effect on the variability in performance

55

levels. Variation in performance is explored here both because it can
cause practical problems and because research has shown that it may
increase under certain types of incentive plans [Bull et al., 1987].
Consistent with the evidence found by Bull et a1. [1987] performance
variance is expected to be higher in the competitive condition than in
the cooperative condition. Bull et a1. did not have an explanation for
the effect they found, but conjectured that it was due to the game
nature of contests. The unit of analysis for this hypothesis is the
three person work group. Variance is defined as the variance across the
three group members as opposed to variance over time. While both types
of performance variance are important management concerns, the
consistency over time approach to variance is not being pursued here
because a change over time is expected due to learning and to the
provision of feedback during the last half of the experiment.

In this study, the piece—rate or cooperative scheme is expected to
induce information transfer when communication is allowed and thus yield
fairly consistent output across subjects in groups. Even in those cells
in which communication is not allowed the hypothesized effect is
expected because of the likelihood of a Stackelberg pattern in the
competitive condition. So the hypothesis is across feedback and
communication conditions, and is simply a prediction that variance of
performance will be higher under the competitive incentive than under
the cooperative incentive.

HYPOTHESIS 2: Variance of Performance

 

With or without feedback: 3, 4, 7, 8 > 1, 2, 5, 6

56

W
Information transfer or sharing among subjects is the group process

expected to drive the above results. The occurrence of such transfer
will be measured in two ways. Subjects' output levels will provide
indirect evidence of whether the expert subject shared information with
his group members. In addition, subjects will be asked about that
process in a final questionnaire. It is expected that information
sharing will be greater in the cooperative condition than in the contest
with communication. The reasoning is straightforward and is based on
the notion of maximizing utility. Because the individuals in the
cooperative incentive benefit if others in their group perform better,
they will be motivated to share information and to work to develop rules
for performing the task. Conversely, in the competitive condition, a
group member earns less if other members perform better so there is a
disincentive to share information.
HYPOTHESIS 3: Infotmation Transfer 1, 5, 1F, 5F > 3, 7, 3F, 7F

Hypothesis 3 says that information sharing will be more frequent in

the cooperative incentive than under the competitive incentive.

Expectancy

The two elements of expectancy theory which are measured in this
study are expectancy and instrumentality. Expectancy is measured at
four times during the experiment. At the beginning, a very general
question is asked regarding the subjects' assessment of their ability on
spatial tasks involving pattern recognition. During the actual problem

sets expectancy is assessed at three separate times. The self-efficacy

57

measure is administered after the second set, the third set, and the
fifth set. Subjects are asked to estimate what they believe their
performance on the next set will be and to give the certainty with which
they hold these expectations. This provides a measure of self-efficacy,
a more relevant measure of expectancy in this situation, [Locke et a1.
1984]. In this setting subjects are not allowed to decide how much time
they wish to expend completing the project, which means their effort
choices are severely restricted. Thus, it is difficult for subjects to
hypothesize about different effort levels. See Appendix C for a.copy of
the instruments used. Subjects received feedback information on sets
three, four, and five. So, the first general self-assessment of skill
and the first self-efficacy measure are completed in the absence of
feedback, while the second and third measure of self-efficacy are
completed after receiving feedback.

Subjects are expected to have essentially equal expectancies on the
general assessment and the first self-efficacy measure. Once feedback
is provided to them, however, the effect of feedback and incentive
scheme is expected to be interactive. Thus, in the competitive
condition, feedback is expected to reduce expectancy, while in the
cooperative condition, feedback is expected to have a positive effect on
expectancy. Generally, in prior feedback experimentation the
difficulty of goals was manipulated rather than the incentives or reward
structures.

HYPOTHESIS 4.A: Expectancy Cells 1F, 2F, 5F, 6F > 1, 2, 5, 6

Hypothesis 4.A says that in the cooperative incentive feedback is

expected to increase expectancy.

58

HYPOTHESIS 4.8: Expectancy Cells 3, 4, 7, 8 > 3F, 4F, 7F, 8F
Hypothesis 4.8. says that in the competitive incentive condition

feedback is expected to lower expectancy.

Infi tttgpentality

In the final questionnaire subjects were asked for information on
their perceived instrumentality of the reward structures. It was
expected that generally the instrumentality would be greater for the
cooperative reward scheme than for the contest. The relationship of
performance to reward is presented graphically in Figure 2.1. It is
anticipated that subjects' perceptions will reflect the objective
relationship and that instrumentality will be higher under the
cooperative incentive than under the competitive incentive.

HYPOTHESIS 5: Instrumentality Cells 1, 2, 5, 6 > 3, 4, 7, 8

e - Summa o Researc H otheses
Dtpendent Variable Expected Relationship
1. Performance: 1, 1F, 5, SF > 2F, 4, GP, 8 > 2, 4F, 6, 8F >
3, 3F, 7, 7F

2. Performance Variance: 3, 4, 7, 8 > 1, 2, 5, 6

3. Information Transfer: 1, 1F, 5, SF > 3, 3F, 7, 7F
4.A. Expectancy: 1F, 2P, 5P, 6P > 1, 2, 5, 6

4.8. Expectancy: 3, 4, 7, 8 > 3F, 4F, 7F, 8F

5. Instrumentality: l, 2, 5, 6, > 3, 4, 7, 8

RESULTS AND DISCUSSION

The purpose of this chapter is to present the experimental results of
the study. Each hypothesis is restated and followed by a description of
the statistics used for testing that hypothesis, the results and the
implications of the results. Statistical analysis was performed using
the SAS program [SAS Institute, 1987].

To begin, a brief review of the experimental design is presented for
expository clarity. The independent variables and their levels are:

1) Type of reward - a) Cooperative

b) Competitive
2) Communication - a) Allowed

b) Not allowed
3) Expert in group a) Present

b) Not present
4) Outcome feedback a) Provided

b) Not provided.
The first three variables are between subject variables, while the
fourth independent variable is a within subject variable. For ease of
reference the experimental design is graphically displayed below with
numerical referents for experimental cells. The three between subject
variables are included below. The within subject variable -- feedback -
- is not displayed graphically. Each of the eight cells shown has a

related cell number with an F suffix indicating that feedback was

59

60

provided. Thus, there are sixteen experimental cells in total.

Table 4,0 - Experimental Design

Incentive Plan

 

 

 

Cooperattve Qompetittve
Communtcationz
Yes No Yes No
Yes 1 2 3 4
Expert in Group?
No 5 6 7 8

 

 

 

 

 

 

Results and Discussion of Hypothesis One

Petformancs l, 1F, 5, SF > 2F, 4, 6F, 8 > 2, 4F, 6, 8F > 3, BF, 7, 7F

The prediction was that performance is higher in the cooperative
reward with communication. In the competitive reward condition,
feedback and communication are expected to have a negative effect. This
hypothesis was tested using orthogonal contrasts [Keppel, 1982], a
statistical method which is also called contrast coding [Cohen & Cohen,
1975]. This technique is particularly appropriate when research
hypotheses involve interactions. Contrast coding allows a researcher to
specify in advance the exact nature of the expected interactions and
avoids the usual difficulties of increased Type 1 error caused by
multiple planned comparisons. The specification of an overall model
relating all the cells uses only one degree of freedom and results in a
very powerful and efficient test. The procedure requires only cell

means, the determination of suitable coefficients, and an overall mean

61
squared error term from a traditional analysis of variance. Because of
the complexity of a model with sixteen cells the analysis is given first
for the overall model, followed by the results for the important sub-
hypotheses developed in chapter III.
The general formula for computing the sum of squares of a contrast

coding model is:

s(¢)2
SSComperison
z (c,)2
Where 5 - number of subjects in a cell

c - coefficient
i - a particular treatment, or cell
<X> - 2 (c1) . (A1)
A - treatment mean for cell i.

Keppel [1982, pp. 134-142] outlines the procedures necessary to obtain
orthogonality in one's model, which is achieved by using the appropriate
coefficients. Table 4.1.1 displays the performance cell means of the

experimental design of Table 4.0.

62

st1s 4,1,1 - Cel; Means - Performance

Incentive Plan

 

 

Cooperative Competitive
Without Feedback Communication?
Yes No Yes No

 

Yes 18.617 16.333 16.217 16.200

 

Expert in Group?

 

 

 

 

 

 

No 20.127 15.545 15.431 16.045
With Feedback Communitattonz
Yes No Yes No

 

Yes 21.900 19.056 17.600 18.700

 

Expert in Group?
No 19.857 17.909 16.902 17.614

 

 

 

 

 

 

Table 4.1.2 includes the cell means, the appropriate coefficients for

the contrast coding computation, and the cell sizes.

Table 4.1L2 - Contrast Coding Coefficients

Cell fl Cell Means Coeff N Coef Mean
1 18.617 3 60 55.851
1F 21.900 3 60 65.700
2 16.333 -1 36 -l6.333
2F 19.056 1 36 19.056
3 16.217 -3 60 -48.999
3F 17.600 -3 60 -52.800
4 16.200 1 30 16.200
4F 18.700 -1 30 ~18.700
5 20.127 3 63 60.381
5F 19.857 3 63 59.571
6 15.545 -1 33 ~15.545
6F 17.909 1 33 17.909
7 15.431 -3 51 -46.293
7F 16.902 -3 51 -50.706
8 16.045 1 44 16.045
8F 17.614 -1 44 ~ 2,614

63

An examination of the cell size (N) column in Table 4.1.2 reveals
that cell sizes are not equal. This arose from two causes. In some
cases intact classroom groups were used as subjects. Also, a second
instrument was designed to test instrumentality, as will be discussed in
the section on Hypothesis Five. This instrument was used on an
additional, smaller group of subjects in the odd-numbered cells only.
The resulting disparity in cell sizes requires the use of a harmonic
mean [Keppel, 1982, p. 347-350]. When using contrast coding a mean
square term is calculated according to the formula above and compared to
the mean square error term of a traditional ANOVA to obtain an F
statistic. The traditional ANOVA is presented in Table 4.1.3. Since
this is a repeated measures design, performance for each subject is
measured both with and without feedback. The traditional ANOVA
indicates a significant four-way interaction. However, it does not
provide any evidence on the pattern of the interaction, which renders
interpretation difficult. When the hypothesized model is tested using

contrast coding, the results are altered as shown in Table 4.1.4.

64

4 - 0 - o a

Source DF Sum of Squares Mean Square F Value Pr > F

e een ects
Reward 1 1005.82 1005.82 43.48 .0001
Comm 1 248.62 248.62 10.75 .0011
Expert 1 40.45 40.45 1.75 .1868
Rew * Comm 1 540.77 540.77 23.38 .0001
Comm * Expert 1 3.93 3.93 .17 .6804
Rew * Expert 1 1.28 1.28 .06 .8137
Rew * Comm * Expert 1 7.38 7.38 .32 .5723
Error (Between) 369 8535.80 23.13
Wi S b ct
Feedback 1 574.22 574.22 74.76 .0001
Feed * Reward l 2.31 2.31 .30 .5833
Feed * Comm 1 28.66 28.66 3.73 .0542
Feed * Expert 1 92.27 92.27 12.01 .0006
Feed * Rew * Comm 1 1.20 1.20 .16 .6930
Feed * Comm * Expert 1 15.28 15.28 1.99 .1593
Feed * Rew * Expert 1 49.21 49.21 6.41 .0118
Feed * Rew * Comm* Exp 1 48.52 48.22 6.32 .0124
Error (Within) 369 2834.32 7.68

Isth 4,;,4 - Contrast Qoding Resplts

Source DF Sum of Squares Mean Square F Value Pr > F
Model 1 1045.96 1045.96 67.89 .0001
Unexplained by Model 14 1613.96 115.28 7.48 .0001
Error 738 11370.12 15.41

Thus, the null hypothesis is rejected, and the model is seen to be
significant. The total of the treatment sums of squares in Table 4.1.3
is 2659.92, and the model explains approximately 39% of that treatment
variance, which is a significant proportion of the between-groups

variation. However, while the model is highly significant, it provides

65
only marginally more explanatory power than the main effect of reward in
the traditional ANOVA. Furthermore, the variance that is not explained
by the model is also significant, which indicates that the hypothesized
model does not maximize explained variance. As explained in chapter
two, the original hypothesis subsumed several sub-hypotheses. A further
analysis of the sub-hypotheses indicates that the model was not
successful because the expected negative effect of feedback and
communication in the competitive reward condition did not occur. The
purpose of the following additional tests is to diagnose the error in
the model, to probe which relationships implied in the model actually
occurred and which did not. Since these tests are not being relied upon
for hypothesis testing and since the results of the original model are
highly significant, the simplest adjustment --the modified Bonferroni
test [Keppe1, 1982] -- is being made for the possible increase in the
alpha rate due to multiple, non-independent comparisons. Using a
familywise error rate of .05, and a total of sixteen cell means, the
required significance level for any particular test is .003.

The following analysis is organized by sub-hypothesis. After the
sub-hypothesis is stated, the t-test results comparing the means of the
two groups, and the group means are presented. Since the presence of
feedback was provided for only half of the problem sets, there are two
sets of means involved -- performance without feedback and performance
with feedback.

Sup-hypothssts A; l, 1F, 5, SF > 2, 2F, 6, 6F
This hypothesis predicts that given a cooperative reward,

communication will result in improved performance. The t-test results

66
for performance with and performance without feedback were significant
(p < .0001). The means are presented in Table 4.1.5; the numbers in

parentheses following the means are the cell numbers.

Table 4.1.5 - Sub-Hypothesis A
Without Feedback With Feedback

 

With Communication 19.39 (1,5) 20.85 (1F,5F)

 

Without Communication 15.96 (2,6) 18.51 (2F,6F)

 

 

 

 

Sub-Hypothesis B; 4, 4F, 8, 8F > 3, 3F, 7, 7F

Given a competitive reward scheme, performance will be higher without
communication than with communication. While the cell means are in the
hypothesized direction, this sub-hypothesis was not supported. Results
of the t-test were p < .7064 for performance without feedback and p <
.1631 for performance with feedback. Thus, while the hypothesized
beneficial effects of communication with a cooperative reward did occur
(sub—hypothesis A), the hypothesized negative effects of communication
in the competitive scheme did not. The actual means are shown in Table

4.1.6:

Tab e 4 6 - Sub-h othesis 8

Without Feedback With Feedback

 

With Communication 15.86 (3,7) 17.28 (3F,7F)

 

Without Communication 16.11 (4,8) 18.05 (4F,8F)

 

 

 

 

67
Sup-Hypothesis g: 1, 1F, 5, SF > 3, 3F, 7, 7F
The premise of this hypothesis is that given the ability to
communicate, performance will be higher in the cooperative reward than
in the competitive reward. This is essentially a comparison of the top
row of each of the two tables above. The results are highly
significant; for both dependent variables the t-test results are p <

.0001. The data appear in Table 4.1.7.

Ta 1 4 7 - Sub-h othesis C

Without Feedback With Feedback

 

Cooperative reward 19.39 (1,5) 20.85 (1F,5F)

 

Competitive reward 15.86 (3,7) 17.28 (3F,7F)

 

 

 

 

Sub-flypothests D: 4, 8 > 2, 6

The prediction was that if subjects were not allowed to communicate,
performance with feedback would be higher in the competitive reward
condition than in the cooperative reward. This expectation was based on
the mixed results of prior research, which indicated a weak advantage
for competitive rewards in independent tasks. The relevant cell means
are presented in Table 4.1.8 (the cells included are shown
parenthetically in the matrix). The t-test results were not
significant ( p < .85).

Sup-Hypothesis E: 2F, 6F > 4F, 8F

The expectation was that without the ability to communicate,

performance with feedback would be higher in the cooperative reward

condition, since subjects who were ranked low within the competitive

68

group would be discouraged by their status and would decrease their
expectancy. The t-test results were not significant ( p < .416). The
expected strong differential effect of feedback, such that performance
would decline in cells 4F and 8F did not occur. Table 4.1.8 contains
the cell means of performance. Further discussion of the effect of

feedback follows Table 4.1.8.

b 4 8 - ub- othese and

Without Feedback With Feedback

 

Cooperative reward 15.95 (2,6) 18.51 (2F,6F)

 

 

 

 

Competitive reward 16.11 (4,8) 18.05 (4F,8F)

 

Generally, the analyses of the sub-hypotheses reveal that the
strongest effect was the interaction of the cooperative reward and the
communication condition. The hypothesized interaction due to feedback
did not appear, with the result that the model tested using contrast
coding did not add significant explanatory power over a traditional
ANOVA.

Further analysis of the role of feedback is warranted since the
observed effects differed from predictions. Feedback was expected to
cause a change in subjects' performance, to increase performance under
cooperation and to impair it under the competitive incentive plan. It
is helpful, therefore, to examine the patterns of change scores. A
change score can be calculated by subtracting a subject's performance in

the last three problem sets from his performance in the first three

69

problem sets. The results of a traditional ANOVA using a change score

as the dependent variable are presented in Table 4.1.9.

Tabls 4.1.9 -4ANOVA - Perfotmante Change Scote

 

Source DF Sum of Squares Mean Square F Value Pr >F
Reward 1 4.63 4.63 .30 .5833
Comm 1 57.32 57.32 3.73 .0542
Expert 1 184.55 184.55 12.01 .0006
Rew * Comm 1 2.40 2.40 .16 .6930
Comm * Expert 1 30.56 30.56 1.99 .1593
Rew * Expert 1 98.42 98.42 6.41 .0118
Rew*Comm*Expert 1 97.05 97.05 6.32 .0124

Error 369 5668.639 15.362

The three way interaction arose because of an unusual pattern in the
cell means, shown in Table 4.1.10. This table reflects the experimental

design shown in Table 4.0, so cell indicators are not included.

Tabls 411.10 - Cell Means - Performapce Change Scote

Incentive Plan

 

 

Cooperative Competitive

W
Yes No Yes No

 

Yes 3.283 2.722 1.383 2.50

 

Expert in Group?
No -.270 2.364 1.470 1.568

 

 

 

 

 

 

The very small decline in performance in cell 5 was unexpected and gave
rise to the three-way interaction. The performance in cell 5 without

feedback was the highest of the eight cells, and the performance with

70

feedback was the second highest. Thus, it appears that subjects in this
cell attained their maximum performance level during the first three
rounds and feedback had virtually no effect. The decline is not
significant in absolute terms, nor does it indicate that feedback caused
performance to be at low levels compared to those in other cells. Cell
5 included a group of students who were the most communicative of all
the subjects during the early rounds. Since all other cells had a
positive change, cell 5 is anomalous and causes a significant four way
interaction in the ANOVA. These results should not, therefore, lead to
conclusions that the effect of feedback is negative in this one
experimental condition, and positive in all others. Instead, the more
appropriate inference is that if subjects share information effectively,
as they did in cell 5, feedback provided by an experimenter does not aid
performance.

Because the sample size was very large and the number of
comparisons in the ANOVA was high, significant findings may have
occurred by chance [Keppel, 1982]. The possibility that the unusual
pattern of cell 5 gave rise to the significant four-way interaction was
investigated using omega squared, a statistic which indicates the
proportional amount of the total population variance explained by the
experimental treatments. Omega squared is not affected by sample size.
Table 4.1.11 presents the value of Omega squared for the significant

interactions from the ANOVA results of Table 4.1.3.

71

Isble 4.1.11 — Omega Sguared Results

 

Source

ANOVA Omega
Between Subjects Er > F Sguared
Reward*Communication .0001 .060
Within Subjects
Feedback*Expert .0006 .030
Feedback*Reward*Expert .0118 .015
Feedback*Rew*Expert*Comm .0124 .014

The interpretation of Omega squared is somewhat difficult, but generally
in the social sciences an Omega squared of .15 or more is considered a
large effect, a medium effect is approximately .06 and a small effect is
.01 [Keppel, 1982]. The Omega squared results in Table 4.1.11 imply
that the interactive effect that explained the greatest proportion of
variance was the reward - communication interaction. Despite a
significant main effect for feedback, no interactions involving feedback
were significant in the Omega squared computation.

Graphically the pattern of performance is presented in Figure 4.1.
The graph demonstrates that for all conditions except the no expert—
communication line (cells 5 and 7) the slope increased in Panel B, i.e.
the difference in performance across reward conditions was greater with
feedback than without feedback. This gives further evidence of the
impact that the atypical pattern of cell 5 exerted.

The performance pattern in cell 5 raises the possibility that
communication with other group members can be a very effective form of
feedback. The general research approach on feedback has been to treat
only information provided by the experimenter or teacher as feedback.

However, in this study group members of the most cohesive cell provided

72

sufficient information to one another to render the experimenter's
feedback otiose. This suggests that feedback and communication were
partially confounded and should be manipulated separately in future
research. These results suggest further that in some settings the costs
of providing feedback can be reduced by structuring incentive plans to
encourage communication among workers.

An informal test of the theory of contests was also carried out.
According to the theory of contests, a random shock -- the rewarding of
three problem sets which were not specified in advance -would cause
competitive schemes to dominate individual, piece-rate schemes. On the

other hand, an individual difference, such as ability, could mitigate
the environmental effect and result in higher performance in the
individual schemes. The implication was that for performance, cells 1
and 2 would exceed cells 3 and 4, and that cells 7 and 8 would exceed 5
and 6. Instead, performance in cells 1 and 2 exceeded that in cells 3
and 4, and cells 5 and 6 exceeded cells 7 and 8. In both cases the t-
tests results had p > .0001. In this study, the cooperative piece-rate
reward dominated the competitive reward scheme regardless of whether the
individual difference was present or absent. In summary, the
incentive plan was shown to have a significant effect on performance and
to interact with communication. The results support the work done on
cooperation versus competition showing that cooperative plans are more
productive than competitive incentive plans when communication is
allowed. Earlier mixed results indicated that additional variables were
important when determining the incentive schemes' productivity. The

present results demonstrate that communication among workers is an

Performance

Legend:

73

Panel A
No Feedback

22
21
20
19
18

17

 

l6

 

 

15

 

 

Comp. Coop.

Incentive Plan

Panel B
Feedback

 

u n
Comp. Coop.

Incentive Plan

Expert present, Communication allowed - Cells 1 and 3

No Expert, Communication allowed - Cells 5 and 7

Expert present, No Communication - Cells 2 and 4

No Expert, No Communication - Cells 6 and 8

mm

Graph of Performance Results

74
important variable which may cause increased productivity even when the
task is not an interdependent one. Feedback generally had a positive
effect on performance, with the exception of cell 5 in which performance

did not improve with feedback.

Results and Discussion of Hypothesis Two
Vattance of Performance Cells 3, 4, 7, 8 > 1, 2, 5, 6

Hypothesis Two predicts that variance of performance will be
greater in the competitive incentive conditions than in the cooperative
incentive conditions. In order to statistically test the variance of
performance levels in this study a procedure suggested by Games et al.
[1972 and 1979] was followed. Games et al. [1979] reviewed several
tests for homogeneity of variance in factorial studies. Usually, such
tests are comparisons of the variance between cells, with a single
variance calculated for each cell. In this study, however, the
hypothesis predicts that variances within work groups of a given cell
will differ from variances of work groups in other cells. In the Box-
Scheffe method recommended by Games, each cell is broken into I random
subsamples of M subjects each. The natural log of the variance of the
subsamples is computed; and these values are used as data points in an
ANOVA with I data points per cell. This transformation alters the test
to one of location, which allows "a great increase in the type of
hypotheses that may be tested,” [Games, 1979, p. 981]. The Box-Scheffe
test is robust to violations of normality assumptions. Although it is
not as powerful as some alternatives Games et a1. [1972] demonstrated

that a group size of three is optimal in terms of statistical power, up

75
to a total of 36 groups. For more subsamples than 36, power is little
affected by group size if it falls in the range of 3 to 6. In this
study, the experimental design determined the only possible selection of
subsamples which is of interest, which was the three person work group.
Because performance was a repeated measure, the variance was
computed on performance with and without feedback. The results of the

ANOVA using the Box-Scheffe procedure are presented in Table 4.2.1:

Table 4.2.1 - ANOVA - Variance in Performance

 

 

Source DF Sum of Squares Mean Square F Value Pr > F
Reward 1 94.659 94.659 39.35 .0001
Communication 1 28.721 28.721 11.94 .0008
Expert 1 .292 .292 .12 .7279
Comm * Reward 1 70.274 70.274 29.22 .0001
Comm * Expert 1 .038 .038 .02 .9006
Expert * Rew l .009 .009 .00 .9519
Comm*Expert*Rew 1 1.555 1.555 .65 .4230
Error 118 283.823 2.405

The results of the ANOVA show a significant effect for reward. They
also, though, indicate a significant effect for communication and for
the interaction of communication and reward.

The data in Table 4.2.2 indicate the pattern of the dependent
variable -- group variance -- at the two levels of reward and
communication. Visual inspection of the mean scores indicates that for
both dependent variables the reward - communication interaction arises
because of the significantly lower score in the cooperative reward with
communication cell. The typical analysis at this juncture is to compute

t-tests to determine any simple effects, i.e., one tests across

76

IabLe 4.2.2 - Mean Scores - Six Round Variance in Performance

 

 

 

 

 

Without Feedback With Feedbstk

Comm. No Comm. Comm. No Comm.
Cooperative -l.2819 2.0452 -2.3663 1.9368
Competitive 2.2122 1.9993 1.6768 1.673

 

 

 

 

 

 

 

 

communication conditions while holding the reward constant. In the
cooperative condition, the communication manipulation resulted in a
significant difference in performance variance (p > .0001). However, in
the competitive condition, the communication manipulation caused no
statistical difference (p > .615 for variance without feedback and p >
.9975 for variance with feedback).
This result is consistent with the reasoning underlying Hypothesis

One. Performance variance can be reduced only when subjects are allowed
to communicate. Given this necessary condition, communication will have
positive effects only when the incentive plan rewards the sharing of
information. In the cooperative condition it is in subjects' interest
to share their task knowledge in order to maximize group output. In the
competitive condition, conversely, it is not in the subjects' interest
to improve the performance of others in their work group. Thus, in the
competitive reward condition the opportunity to communicate did not
reduce observed variance in performance.

In the above analysis, variances were computed on the performance
scores. It was considered possible that the pattern of performance

variance over all six problem sets combined could differ from the

77

pattern of the two variances computed separately with and without
feedback. Thus, a second analysis was done using a single variance for
all six problem sets, in order to provide assurance that the above
results were not due to splitting the performance into two categories.
Again, the Box Scheffe procedure was used to obtain the data points for
the ANOVA. The results are displayed in Table 4.2.3, which reveals the
same pattern as that in the earlier results. Thus, computing the

variances separately with and without feedback did not influence the

results.
e 4 3 - OV - Six Round erfo ance Var an e
Source DF Sum of Squares Mean Square F Value Pr > F
Reward 1 199.759 199.759 37.65 .0001
Communication 1 50.247 50.247 9.47 .0026
Expert 1 .331 .331 .06 .8031
Comm * Reward 1 59.061 50.061 11.24 .0011
Comm * Expert 1 8.695 8.695 1.64 .2030
Reward * Expert 1 2.404 2.404 .45 .5023
Reward * Comm * Expert 1 19.061 19.061 3.59 .0605
Error 118 626.265 5.306

The performance variance means presented in Table 4.2.4 reveal the
familiar pattern of a significantly lower variance in one cell of the

four cells in the two-way interaction.

Table 4.2.4 - Means of Variance - Six Rounds

 

Communication No Communication

 

Cooperative Reward -.353 (l,5*) 2.380 (2,6)

 

Competitive Reward 3.192 (3,7) 3.081 (4,8)

 

 

 

 

* Since these means are for all six problem sets, the feedback and
non-feedback cells are combined.

78

Finally, although the alternatives to the Box-Scheffe procedure used
above avoid the problem of the arbitrary selection of sub-samples, such
tests are not theoretically appropriate in this study since they rely
explicitly or implicitly on an overall cell measure (such as mean or
median) rather than on the variance of the unit of interest -- the work
group. For the sake of completeness, one alternative test was
conducted. It is the Brown-Forsythe test which uses XL,-[Yij - cell
medianJ] as a test of variance, where ijis the Observed score for the
ith subject in the jth cell. The results of this test, which is less
powerful than the Box Scheffe for this particular hypothesis, appear in
Table 4.2.5. Although the Brown Forsythe test is less powerful than the
Box Scheffe, the reward effect is still significant. For this test,
neither the effect of communication nor the interaction of reward and

communication is significant, however.

Tab e 4 2.5 - ro ors e test

Source DF Sum of Squares Mean Square F Value Pr > F
Reward 1 31.864 31.846 4.12 .0431
Communication 1 12.371 12.371 1.60 .2068
Expert 1 .081 .081 .01 .9183
Reward*Comm 1 1.345 1.345 .17 .6769
Comm * Expert 1 3.143 3.143 .41 .5242
Reward*Expert 1 .000 .000 .00 .9988
Reward*Comm*Expert 1 7.318 7.318 .95 .3313
Error 369 2853.640 7.733

In order to provide more evidence that variance of performance in

this setting affects performance negatively, the correlation between

79

variance and performance was calculated. This overall calculation
precluded any comparisons of the two feedback conditions, the two reward
conditions, or the communication conditions. The correlation analysis
was conducted to provide further support for the hypothesized inverse
relationship between performance level and variance of performance.
Using the variance calculated on all six rounds and performance for all
six rounds the correlation between the two variables was -.4377 (p >
..0001). Therefore, a strong negative relationship between performance
and variance of performance was observed.

In summary, the results of the original analysis and the two
supplementary analyses indicate that reward and communication
significantly interact in their effect on variance of performance. The
research hypothesis was that reward would have an effect on performance
variance; no interaction was predicted. The results indicated that
while communication has little effect in the competitive condition, the
possibility of communication was significantly related to lowered
variances in the cooperation condition. These results are consistent
with those of Hypothesis One and again provide evidence that in the
debate over the relative merits of competitive versus cooperative
schemes, an important factor to consider is not only the nature of the
task, but the nature of the work process -- i.e. whether or not subjects
are allowed to communicate with one another about how to perform their

tasks.

80

Rssults and hiscussion at Hypothesis Thtes
o i n e l, 1F, 5, SF > 3, 3F, 7, 7F
It was hypothesized that given the opportunity to communicate,

subjects in the cooperative reward condition would do so with greater
frequency than subjects in the competitive reward condition. In this
case the dependent variable is a categorical variable and the analysis
was done on the frequency of information sharing among group members.
With frequency data, the Chi-squared test is the preferred statistical
test [Siegel, 1956, pp. 175-180].

A copy of the final questionnaire used to gather the data for this
hypothesis is presented in Appendix A. The first question asked "Did
you receive any information from the experimenter on how to perform the
task?" If the subject answered yes, he or she was instructed to go to a
series of questions asking about sharing the information. If the
subject answered no, then he or she was directed to questions about _
receiving information from group members. All subjects were asked how
they had gone about solving the problems and a general instrumentality
question. The purpose of the initial question on receiving information
was to segregate those subjects who were the ”experts", i.e. those who
had received detailed instructions, from those subjects who had not
received such instructions. The effectiveness of this identifying
question is shown in Table 4.3.1. Before subjects actually began the
task, it was necessary to explain progressive matrices in very general
terms and that the task was to select the appropriate symbol from a
choice of four or five alternatives. In this introduction to the

problem pp information was provided on how the matrices were designed.

81

A sample matrix with a random pattern was used as an illustration and
was erased before the actual task began. By contrast, the "experts"
were provided a set of written instructions describing the two types of
matrices they would see, the logic underlying the construction of the
matrices, and heuristic rules on how to quickly select the correct
choice. A verbal explanation was provided, the examples in the
instructions were reviewed, and questions were solicited and answered.
In the discussion of Hypotheses One and Two, "expert” referred to groups
which included an expert member. In discussing information sharing,
”expert" is used to refer to the individual subjects given task
information.

Only half the cells (1 through 4) included experts. Since there was
one expert per group the actual number of experts was 62. In Table
4.3.1 the responses by all subjects to question one of the final
questionnaire are summarized and reveal that while the experts responded
correctly, many of the non-experts felt that they too had received

information.

Table 4.3.1 - Ousstion One Responses

 

Did you receive information on the task?

 

 

Yes No
Expert 59 l
Non-expert 109 202

 

 

 

 

Table 4.3.1 indicates that over one-third of the non-experts responded

inappropriately to first question. While this renders the results less

82

clear, it does not negate them. The point of Hypothesis Three is that
the reward scheme under which a subject works will affect information

sharing behavior. Whether the shared communication is the information
provided by the experimenter is not crucial. The research question is
whether subjects shared task information, regardless of the source of

that information.

In the second phase of the experiment when the longer
instrumentality scale was used, this problem was circumvented by asking
subjects if they had received a ”pre-test" of a certain color. Since
the expert instructions were printed on green paper, and the irrelevant
pre-tests given to non-experts were printed on other colors, the
experimenter had a mechanism for "forcing” subjects to correctly
identify themselves as expert or non-experts. In both phases of the
experiment an independent identification was maintained by using
identifying subject number for experts. A positive implication of the
subjects' apparent confusion is that while the true experts knew they
had been given private information, the non-experts did not realize that
someone in their group had received such information. This reduces the
likelihood that information was shared because of group pressure on the
expert and increases the likelihood that information was shared because
it was in the individual's interest to do so.

The purpose of the expert manipulation was to enable the
experimenter to independently trace, through an increase in performance,
the sharing of that information. As the results of Hypothesis One
indicate, however, the expert manipulation did not affect performance,

while communication did. If subjects shared their understanding,

83

regardless of whether it was based on information provided by the
experimenter, group performance improved. The crucial behavioral
question is whether, believing he or she had information that could be
helpful, the subject shared it with others in the work group more
frequently under one reward scheme than under another. Evidence

relevant to that thesis is provided in Table 4.3.2.

Iabls 443.2,— Freguenties; Reward X lnformatloh Shatlng

Shared Info. Did not share Info.
(Communication Cells only)

 

 

 

Mrs .
Cooperative 46 12 |
Competitive 8 36 l

 

 

 

Chi-square is 37.5 with degrees of freedom of l (p < .0001). Table
4.3.2 includes only subjects in cells in which communication was
allowed, since they were the only subjects who were allowed to act on
their decision to share information. Thus, the hypothesized main effect
for reward was not rejected. As predicted, subjects in the cooperative
reward condition were significantly more likely to report sharing
information than subjects in the competitive condition. Table 4.3.2
includes only subjects who indicated they had received information from
the experimenter. Because some subjects did not respond to all of the
questions, there were more missing data points relating to this
hypothesis than to other hypotheses. However, several more tests were
completed to investigate the accuracy and consistency of responses.

One consistency test was a point-biserial correlation of member

84

responses in each group. The correlation was .71, with a probability >
.0001. Of the fifty-five groups with no missing data, forty—eight
showed agreement among all three group members. For instance, if the
expert said he shared information, both of the other group members said
that they received information from other group members. Seven groups
gave inconsistent responses. This manipulation check gives some comfort
that responses were accurate.

An additional accuracy check was provided by question eight, which
asked subjects if they had worked out a rule to solve problems alone or
with a group. This check has the disadvantage of possibly precluding
subjects who communicated but failed to develop a problem solving
heuristic. It has the advantage, though, of permitting non-experts to
indicate whether information was shared in their group. The cross-
tabulation of responses to question eight with the incentive condition

appears in Table 4.3.3:

 

Table 4.3.3 - Frequencies; Reward X Work Style

 

 

Worked as Group Worked Alone
Rewatd (Communication Cells Only)
Cooperative 59 29
Competitive 9 61

 

 

 

 

Chi squared is 46.698 for one degree of freedom, p < .0001, for 158
responses of a total of 232. The Chi squared results indicate that the
frequency of work style was not independent of the reward or incentive

plan.

85
Another question regarding information sharing behavior asked if
subjects had received information from anyone in their group. Responses
to that question were tested against responses to the question regarding

developing a problem solving rule together or with other group members.

The data are shown in Table 4.3.4.

Tab e 4 4 - e uencieS' Wo t l e e v n 0
Received info. from Did not receive
others in group info. from others

(Communication Cells Only)

 

Worked alone 18 26

 

Worked together. 48 15

 

 

 

 

Chi squared is 13.64, degrees of freedom - one, p < .0001. The final
questionnaire was not precise and that imprecision is indicated by the
responses. It is feasible that subjects did receive some advice from
others but still felt that they developed a rule or heuristic for
solving the problems by themselves.

A final consistency check was performed by cross-tabulating the
responses to question two and question eight in Table 4.3.5. The former
question asked whether subjects had shared information, while the latter
question asked whether they had worked out a rule to solve the problems
by themselves or in a group. Chi square is 20.38, one degree of
freedom, p < .0001. Although these additional analyses indicate some
imprecision in the final questionnaire, this weakness does not vitiate

the obtained results showing that reward scheme results in differential

86

frequencies of information sharing.

Ishlsi4.3.5 - Frequencies; Wpth Style 3 Informatioh Sharlng

 

Reported Sharing Did not Share
(Communication Cells Only)

 

Worked Alone 8 l9

 

Worked Together 25 3

 

 

 

 

An open-ended question on subjects' motivation for sharing or
withholding information was provided. Only subjects who responded that
they had received information from the experimenter were directed to
this question. Responses regarding the motivation to share (or not
share) information tended to fall into seven categories and were coded
numerically. Typical responses in the categories are listed in Table
4.3.6. The frequency of each response is shown in parentheses with the
frequency in the cooperative reward condition followed by the frequency

in the competitive condition:

Ta e 4 3 6 - Reaso s for Informat'o Sharin Behav o
0 - I had no information the others did not have as well (1,11)
l - to earn more money (5,21)
2 - fairness (9,0)

3 - I was told not to talk with others, or I did not know the others
did not have the same information (26,14)

4 - not enough time, didn't understand the information (6,8)
5 - to maximize group profits, to get the most correct (30,10)

6 - others did not appear to need my help (5,7).

87

There were no hypotheses made regarding subjects' responses, but the
results confirm intuitions that different incentive conditions result in
different motivations for behavior.

For the sake of brevity the following discussion will be narrative
only, without the inclusion of tables. The summary statistics will be
provided, however. When the responses to question two (did you share
information) were crossed with question four (the reason for sharing or
withholding information) these subjects who shared information were
significantly more likely to give fairness and maximizing group profits
(2 and 5 above) as their reasons. Those who did not report sharing
information were significantly more likely to give selections 0, l, 4,
or 6 as their reasons. That is, they felt the others did not need the
information, or already had the information, or they wanted to earn more
money, or felt time constraints. A Chi squared was done on the reasons
given by the two groups and the results were 81.72, degrees of freedom
of 5, p < .0001. When reward was crossed with motivation subjects in
the cooperative condition gave fairness and maximizing group profit as
reasons significantly more than subjects in the competitive condition.
Subjects in the competitive condition more often gave the following
reasons - the others had the same information, to earn more money, or
the others did not appear to need. Again a Chi-square was done on the
distribution with results of 40.819, degrees of freedom - 6, with p <
.001. Although no hypotheses were made regarding the reasons people
would give for information sharing, these results support the thesis

that reward schemes and reasons given for behavior are related. IThis

88
study does not resolve the question of whether the reward scheme affects
the reasons people give for their behavior or whether the reward scheme
directly affects behavior and subjects chose reasons which support or
rationalize their behavior.

One anomalous pattern did emerge from the various Chi square tests
performed. It was expected that the experts in the cooperative
condition would be highly motivated to share information, while the
experts in the competitive condition would not be likely to share
information. A Chi square crossing the actual ”expertise” with reported
information sharing yielded some surprising results. The data in Table
4.3.7 include all those subjects in communication cells who responded to
question two, indicating whether or not they had shared the information

they had received.

 

 

b e 4. .7 - r en ies: x er 1 nf ti h 1
Shared info. Did not share
Expert 9 29
Non-expert 45 19

 

 

 

 

The Chi squared is 20.91, one degree of freedom, p < .001. Contrary to
expectations, the subjects with expert information were not
significantly more likely to share that information; in fact they were
less likely to do so. The significant Chi squared results are based on
the high level of information sharing by non-experts combined with the

low incidence of sharing by the experts. Given the significant effect

89
of reward scheme on reported information sharing, a further breakdown of
Table 4.3.7 by reward scheme was completed. The cross tabulation of

reward by information sharing by the thirty-eight expert subjects (the

top row of Table 4.3.7) is shown in Table 4.3.8.

Table 4.3,8 - Freguencies: Reward X Information Sharing

 

 

Shared info. Did not share
(Experts - Communication Cells)
Cooperative reward 7 ll
Competitive reward 2 18

 

 

 

 

Chi square is 4.374 with one degree of freedom, p < .036. This
indicates that there was a greater percentage of information sharing in
the cooperative reward than in the competitive reward and that the
proportions were significantly different in the two reward conditions.
However, Tables 4.3.7 and 4.3.8 indicate that regardless of the
reward scheme, the informed subjects were not as likely to share
information as they were to withhold it, an unexpected finding. The
research hypothesis was accepted, however, because of the high rate of
information sharing by non-experts in the cooperative incentive
condition. The results of only the non-expert subjects (the bottom row
of Table 4.3.7) appear in Table 4.3.9. Chi square is 37.77, one degree
of freedom, and p < .0001. Table 4.3.9 parallels Table 4.3.2 and
indicates that non-expert behavior caused the strong results for

Hypothesis Three.

90

Iahle 413.9 - Frsguencies; Rewatd X Information Sharing
Shared info. Did not share

(Non-experts - Communication cells)

 

 

Cooperative reward 39 l

 

 

 

 

Competitive reward 6 18

 

The low level of information sharing by experts in the cooperative
condition is surprising. All experts were told that they were the only
member in their group receiving specific task-related information and
that during the "pre-test" other subjects were completing problems
unrelated to the-experimental task. The nature of the incentive was
reviewed with all subjects at the beginning of each session. Outcome
feedback indicating the number correct and - in the competitive
condition - the rank within the group was provided. This feedback was
expected to clarify and reinforce the nature of the incentive plan.
Since the experts were chosen at random and had not earned their
privileged knowledge, equity theory implies they would be likely to
share this information. Sharing of information was predicted to be more
frequent in the cooperative condition because it was in the expert's
interest to increase the performance of his group. The researcher does
not have an explanation for the low incidence of information sharing by
the experts. The observed results could be due to a small sample; there
were only 62 experts in total and 38 who were allowed to communicate.
The lower rate of information sharing by experts indicates that
differential ability or expertise should be considered in research on

group information sharing and on reward effects. Possibly, the expert

91

manipulation was not successful; i.e. the experts did not believe they
were more proficient than the non experts were. Finally, the experts
may have felt the others did not deserve to make more money because of
the experts' knowledge, regardless of how that knowledge had been

obtained.

R s u s o of t es on

We! (4.A) 11*, 2P, 5P, 6F > 1, 2, 5, 6
gypsttspty (4.8) 3, 4, 7, 8, > 3F, 4F, 7F, 8F

In general, the predicted effect of,outcome feedback was to increase
expectancy (Hypothesis 4.A). However, that effect was expected to
interact with the reward scheme, such that in the competitive reward
condition, feedback would decrease expectancies (Hypothesis 4.8). The
first measure was a very general measure based on a five-point Likert
type scale of estimated ability relative to other people. It was used
at the beginning of the experiment, just after the researcher provided a
general explanation of the task. At this point, subjects were expected
to have statistically equal expectancies regarding their abilities.
Expectancies were measured after round two, which was prior to feedback,
and again after rounds three and five, after subjects received feedback
on their performance. The scale used for the last three measures is
based on Locke et a1. [1984] and is actually a measure of self-efficacy,
which provides better predictions of performance in this type of
setting. An example of the form used is provided in Appendix C.

After round two subjects were again expected to have basically equal

expectancies. Once feedback was supplied, however, the expectancies

92

were predicted to diverge. In the cooperative condition, particularly
with communication, it was posited that subjects would work together,
thereby improving performance, and increasing expectancy. In the
competitive condition, feedback was expected to have a negative effect
on those subjects who were not ranked highest in the group. While the
predicted effect of feedback on the best performer in the group was
positive, it was expected to be outweighed by the negative effect on the
other two group members.

Several analyses were conducted on the data. The first was an ANOVA

based on the initial expectancy, presented in Table 4.4.1.

Iahle 4.4.1 - ANOVA - Initial Expectancy

Source DF Type I SS Mean Square F Value Pr > F
Reward 1 .090 .090 .16 .6872
Communication 1 .303 .303 .54 .4618
Expert 1 .891 .891 1.60 .2074
Reward*Comm 1 1.535 1.535 2.75 .0984
Reward*Expert 1 3.753 3.753 6.72 .0100
Comm* Expert 1 .055 .055 .10 .7518
Reward*Comm*Expert l .560 .560 1.00 .3172
Error 335 187.210 .558

Although no significant differences in means were expected, the
reward * expert interaction was significant. However, the cells means
were examined and were not substantively different. Therefore, no
conclusions are drawn regarding the initial expectancies.

On the form used to elicit expectancies (Appendix C) subjects
indicated their expectations regarding certain levels of performance and

the certainty of their expectations. A summary expectancy figure was

93
obtained by multiplying the increment of the score (which was two, in
all cases) by the likelihood of obtaining that score level in decimal
form. An example is presented in Table 4.4.2. The number correct

column was pre-printed on the form. Subjects filled the middle two

columns.
a e 4 4 — Com utation of Ex ectanc - an xam 1e
At Least Degree of Expectancy
o ect Yes 0; No Certainty (0 to 1002) Contributlph

2 Y 90 2 x .90 - 1.80
4 Y 80 2 x .80 - 1.60
6 Y 75 2 x .75 - 1.50
8 Y 60 2 x .60 - 1.20
10 N 100 2 x 0 - ,QQ

Total Expectancy - 6.10
Using the total expectancy as calculated in Table 4.4.2, the hypotheses
were examined with simple t-tests. The cell means of expectancy for the

feedback and the reward conditions are shown in Table 4.4.3.

I§Dl£.4-413 - C eans - Ex ectan

Without Feedback With Feedback

 

Cooperative 5.7827 6.6589

 

Competitive 5.3385 5.6975

 

 

 

 

Test results of means in the cooperative condition were significant, t -
5.087, p < .001, in the direction predicted. In the competitive
condition the t-test results were also significant, t - 1.9468, pi< .05,
in the opposite direction of that predicted. Feedback did not have a

negative effect on expectancy in the competitive reward condition.

94

Instead, expectancy increased with feedback in both reward conditions
which indicates that at least in this type of competitive reward the
Stackelberg equilibrium did not emerge. It is not clear what the effect
of negative feedback in a more prolonged work setting would be.

Hypothesis Four makes the strong claim that feedback will increase
expectancy in one incentive condition and decrease it in the other
incentive condition. The focus of Hypothesis Four is on the change in
expectancy across the two levels of the feedback manipulation.
Therefore, an explicit test of the change in expectancy was also.
performed. Cohen and Cohen [1975] caution against the over-use of
change scores because they are less reliable measures than direct
measures, which themselves, include measurement error. The following
analysis is not serving as a basis for hypothesis testing, however, but
simply to explore the data. Difference scores were computed by
subtracting the expectancy obtained after round two from the expectancy
obtained after round five. The results of the ANOVA are shown in Table
4.4.4 and the related cell means are presented in Table 4.4.5. The
expectancy change means presented in Table 4.4.5 demonstrate the now
familiar pattern we have seen in the analysis of performance and
variance of performance. When reward and communication are crossed, the
dependent variable (change in expectancy) is significantly higher in the
cooperation-communication cell and approximately equal in the other
three cells.

In summary, expectancy increased in all cells with the addition of
feedback. Since expectancy is closely correlated to performance, and

performance increased in all cells except cell 5, this supports

95

Ishlsg4.4.4 - ANOVA - Chan e n Ex ectanc

Source DF Type III 831 Mean Square F Value Pr > F
Reward 1 10.907 10.907 3.74 .0539
Communication 1 8.460 8.460 2.90 .0894
Expert 1 1.742 1.742 .60 .4399
Reward*Comm 1 13.021 13.021 4.47 .0353
Reward*Expert l .218 .218 .08 .7843
Comm* Expert 1 .345 .345 .12 .7310
Reward*Comm*Expert 1 6.482 6.48 0 2.22 .1368
Error 7 340 991.065 2.914

Ishlsl4l4.5 - Cell Means - Change ip Expectancy

 

 

 

. Communication No Communication
'Cooperative 1.1739 .4313
Competitive .3955 .4923

 

 

 

 

expectancy theory. The predicted deleterious effect of feedback on

expectancy in the competitive reward condition did not occur, although

 

1 Prior to this particular ANOVA all Sums of Squares displayed have
been Type 1 Sum of Squares, which is the typical computation taught in
experimental design textbooks (see, for example, Keppel [1982]). In Type
I Sum of Squares, the order in which effects are entered does not affect
the computation. By contrast, the Type III Sum of squares is computed
as if each effect were the last to be entered into the equation, i.e.
after all other effects have been accounted for. Generally, this will
result in lower significance levels than in Type I analyses. Because of
the highly significant results obtained in results reported to this
point, there has been no difference between the two methods in which
effects were found to be significant. In this analysis, however, there
was a difference, and so the more restrictive Type III results are being
shown. Using an alpha level of .05, the one effect which would be
reported differently using the Type I Sum of Squares is reward, which
had an F of 6.84 and pr. > F of .0093.

 

96
the increase in expectancy under the competitive incentive plan was
lower than under the cooperative incentive plan. The incentive plan
interacted with communication to generate the largest expectancy
increase in the cooperation - communication cells.
u s a cus o o H ot sis ive

Instrumentality 1, 2, 5, 6 > 3, 4, 7, 8 (with or without feedback)

Hypothesis Five predicts that instrumentality will be higher in the
cooperative reward than in the competitive reward. Instrumentality was
measured in two ways. For the first phase of the experiment,
instrumentality was measured in the final questionnaire with one
question, based on Ilgen et a1. [1981], who found the average test-
retest reliability of such a scale to be .58. Subjects were asked, "If
you had an average of five items correct per set and then began to do
substantially better, your average pay per set would:” and were given a
nine point verbally anchored Likert scale. Level 7 was designated
"Increase Moderately" while level 5, as the mid-point, was labelled
”Stay About the Same." The ANOVA for this single-item measure is

displayed in Table 4.5.1.

b e 4 . - V - l ite ns enta t
Source DF Type I SS Mean Square F Value Pr > F
Reward l .673 .673 .66 .4157
Communication 1 5.543 5.543 5.47 .0200
Expert 1 .185 .185 .18 .6695
Reward*Comm 1 1.357 1.357 1.34 .2482
Reward*Expert 1 2.082 2.082 2.05 .1529
Comm* Expert 1 3.244 3.244 3.20 .0746
Reward*Comm*Expert l .066 .066 .07 .7975

Error 284 287.843 1.013

97

There was an unanticipated main effect for communication, with the mean
response of subjects allowed to communicate being 6.635 and the mean
response of subjects who were not allowed to communicate being 6.354.

The cell means are presented in Table 4.5.2.

4 2 - Cel eans - Sin 1e item Instrumentalit

Communication No Communication

 

Expert in Group 6.711 6.212

 

 

 

 

No Expert in Group 6.556 6.474

 

Further examination of cell means reveals that communication had no
effect in the non-expert condition and a positive effect in the expert
condition, which is an interactive relationship (p < .0746). The result
that instrumentality was lowest in cell 4 (expert in group, no
communication, competitive reward) is not surprising. Subjects in this
category who were not doing well and could not communicate with other
group members to obtain information on the task or on others'
performances were expected to have lower instrumentalities. That is,
they were expected to perceive a lower correlation between performance
and increases in pay because they had the least information with which
to estimate that relationship. This simple, single question regarding
instrumentality was based on the measure used by Ilgen et a1. [1981] in
their comparative study of scales to measure expectancy theory
variables. While all four scales for instrumentality used in that study

were found to have high validity, the reliabilities ranged from the mid

98

.40's to the mid .70's. The single question measure has the virtue of
being a relatively simple and very brief instrument. This gross measure
was not expected to differentiate between incentive conditions as
effectively as the longer scale based on probabilities. The results in
Tables 4.5.2 and 4.5.4 confirmed this expectation.

For the second phase of the experiment the longer scale based on
probability assessments was used (Appendix D). Ilgen et a1. [1981]
stress the need for further exploration of scales used to measure
expectancy theory variables. By using two measures in the current study
provides additional data on their relative sensitivity. The scale used
in the second phase of this experiment had .78 test-retest reliability
in the Ilgen et a1. [1981] study, as well as high validity.

Because pay and performance are related in a monotonic pattern in
both incentive plans, their perceived correlation was expected to be
high under both incentive plans. However, the cooperative incentive
plan provides a simple, linear relationship between pay and performance,
while the competitive incentive scheme represents a step relationship.
The hypothesis was that the step relationship would result in lower
instrumentality (perceived correlation between performance and reward)
than the linear pattern. Instrumentality was computed by correlating
performance with expected pay for five levels of performance. The
correlation scores were transformed using Fisher's Z transformation.

The ANOVA results using the Z transformed correlation scores appear in
Table 4.5.3. Because this instrument was used in a second phase which
included only communication cells, the model is a two-factor model

including reward and expert only.

99

Table 4.5.3 - ANOVA - Fisher 2 Scores

Source DF Type I SS Mean Square F Value Pr > F
Reward 1 95.957 95.957 57.21 .0001
Expert 1 .003 .003 .00 .9690
Reward*Expert 1 .920 .920 .55 .4612
Error 75 125.788 1.677

The cells means of the Fisher Z Scores are presented in Table 4.5.4.

Table 4.5.4 - Instrumentality - Fisher Z Scores

 

 

 

Expert No Expert
Cooperative Reward 4.1029 4.3389
Competitive Reward 2.1093 1.9131

 

 

 

 

The hypothesized results were strongly supported, with the reward effect
accounting for more than 991 of the non-error variance. In addition,
two Student-Newman-Keuls tests were performed. The reward variable was
significant and the expert variable resulted in no statistical
difference among means.

Because the z score is a natural logarithm, it could exaggerate
differences in raw correlations. Therefore a test done directly on the
correlation scores was also performed. The results of that analysis are
shown in Table 4.5.5. The results using the untransformed correlation
scores replicate those obtained by using 2 scores, providing added

assurance that the results are not caused by manipulation of the data.

100

 

Igblg 4.5.5 - ANOVA: Instrumentality Correlations

Source DF Type I SS Mean Square F Value Pr > F
Reward 1 .042 .042 9.11 .0035
Expert 1 .000 .000 .09 .7622
Reward*Expert l .000 .000 .08 .7787
Error 75 .346 .005

In summary, the results of this section provide further support for
expectancy theory. Instrumentality varied in the direction predicted
and most of the non-error variance was explained by the incentive plan
effect. As a final test of expectancy theory, total performance on all
six problem sets was regressed on expectancy and instrumentality. The
residuals were symmetrically distributed and kurtosis was low ( -.l6),
indicating that the data are suitable for regression analysis. The
results showed that both instrumentality and expectancy were significant
in explaining the variance in performance ( p > .0028 and .0001)
respectively. This provides additional support for the explanatory

value of the two expectancy theory variables tested in this study.

Overvlew of Results

Table 4.6.1 summarizes the test of hypotheses results presented in
this chapter. In sum, Hypotheses 1, 2, 3, 4A, 5 were supported; while
Hypothesis 4B was rejected. Generally, performance in the cooperative
reward combined with the communication condition was highest and
variance of performance was lowest in that condition. Variance of
performance was inversely related to performance and was highest in the

competitive incentive plan. Information sharing was affected by

101

incentive plan, although those subjects who had been given individual
expertise did not share information to the same extent as the non-
experts did. Expectancy was affected by reward, but increased with the
provision of outcome feedback in all conditions. Feedback did not prove
to be a negative factor in the competitive condition, as was predicted
in Hypothesis 4B. Finally, instrumentality was significantly higher in
the cooperative incentive plan. Further discussion and implications of

the results are presented in Chapter Five.

.4 6 - Summa of Researc Findin s
Hypothesis Conclusion Re; Null Malg Table
1 Reject the null 4.1.4
2 Reject the null 4.2.1
3 Reject the null 4.3.2
4A Reject the null 4.4.4
4B Fail to reject the null 4.4.4

5 Reject the null 4.5.3

CONCLUSIONS

The purpose of this chapter is to summarize the results of this
research, discuss the limitations of the study, and indicate some

further research which could be carried out.

Research Eindlngs

Research results on the question of productivity under cooperative
versus competitive incentives have been mixed. The nature of the task
was shown to be an important, orthogonal variable. The results of the
current research indicate that the opportunity of agents to communicate
is another important variable, which can significantly affect results.
Performance was enhanced and the variance of performance levels was
reduced when subjects could communicate and were rewarded under a
cooperative incentive plan. The expectations regarding feedback effects
were that it would positively affect performance in the cooperative
reward and negatively affect it under the competitive incentive plan.
Instead, feedback was found to positively affect performance regardless
of reward structure, although the improvement in performance was
somewhat larger in the cooperative reward.

Information sharing was affected by reward structure. The results on
information sharing support the conclusion that managerial accountants

must consider not only the effect a reward scheme will have on an

102

103
individual's motivation to expend effort, but also on that individual's
behavior towards other individuals. If agents can be motivated via
incentive structures to share information with others, the principal
will generally be better off. Information exchange among workers was
shown to be an important form of feedback. Managerial accountants
should consider group interaction as a form of feedback when designing
incentive plans. In addition, the reasons people cited for sharing or
withholding information were different under the cooperative and
competitive reward structures. The information sharing results suggest
that economic models of worker behavior which assume a single agent and
a single principal should be enlarged to include the possibility of
inter-agent communication. An important aspect of this study is that
subjects were allowed to communicate face-to-face, rather than through
restricted mechanisms such as notes [De Jong, et al., Waller and Payes,
1989]. Given the significance of the communication variable on
performance, expectancy, and variance of performance, the effects of
direct, unrestricted communication deserve further study.

Expectancy theory provided the framework for measuring motivational
variables. Two of the three theoretical variables suggested by
expectancy theory -- instrumentality and expectancy -- were shown to be
significantly affected by reward structure. Expectancy was hypothesized
to increase in the cooperative reward and to decline in the competitive
reward because of an interactive effect of reward and feedback.
Instead, expectancy increased in both reward conditions. The resulrs
parallel those of performance in that expectancy increased the most in

the communication-cooperation cell, while the increase was approximately

104
equal in the other three cells. Instrumentality was significantly
affected by reward, as predicted. The results on instrumentality are
important because prior studies have compared instrumentalities of
grossly different pay structures -- a piece rate which is performance
based versus hourly or straight pay, which is not performance based. By
contrast, this study compared two structures which were both performance
based. Finally, the variance of instrumentality was not significantly

different across any of the experimental manipulations.

Contributions of the Research

The results of this research demonstrate the importance of
considering additional factors in testing the relative efficacy of
incentive plans. It was already known that the nature of the task and
the existence of goals were important variables in the comparison of
cooperative and competitive incentive plans. This study has shown that
the opportunity to communicate directly with other workers is an
important factor affecting performance levels differently under varying
incentive plans.

This study offers another, closely related contribution in that it
suggests that workers provide heuristic feedback to one another when
they are appropriately rewarded for doing so. Given the strong effect
of communication on performance, this research provides evidence that
the single-agent, single-principal model needs to be expanded to a
multi-agent model. Results showing the superiority of competitive
rewards may be significantly altered in the presence of direct

communication among agents.

105

This study also provided a more rigorous application of
instrumentality and expectancy scales used in earlier research. The
instrumentality scale distinguished between two performance based
incentive plans, which is a more subtle comparison than that tested in
prior research. While the expectancy results were not entirely as
predicted, the expectancies obtained reflected actual performance
patterns, which supports the validity of the scale and supports
expectancy theory.

The use of contrast coding was demonstrated, although the particular
model hypothesized contributed only marginally to the total variance
explained.

An informal, tentative test of the theory of contests was conducted.
The results relating to the effect of individual and environmental
differences did not support the theory. Results relating to the
variance of performance also did not support the theory, but did
replicate prior empirical findings.

The unexpected results showing that designated "experts" were less
willing than non-experts to share information, regardless of the
incentive plan they were working under, indicates that differential
abilities may be problematic. Theory of contest researchers [0'Keeffe,
et a1. 1984] speculated that abilities that this would be the case. In
this study, the information provided to experts was a surrogate for
ability. However, because the expert effect was not significant, the
surrogation was not successful. It is possible, therefore, that two
separate issues are involved here -- the use of privileged information

and the effect of individual ability.

106

Limitations of thelResearch

 

Constraints on generalizing the results of this research generally
relate to the experimental methods used in testing the hypotheses. The
limitations of the experiment are described below.

The Progressive Matrix problems were chosen because subjects'
performance in pilot tests improved significantly with a short
description and explanation. However, the matrix problems are not so
difficult that only the designated experts could complete them. While a
very difficult task could have made tracing the effect of experimenter
provided expertise easier, an extremely difficult task could have caused
motivational problems and resulted in inappropriate rewards. The
results could be generalized more if other types of tasks were used. In
addition, the role of expertise could be clarified if more different
types of task were studied.

The manipulation of expertise was not entirely successful. Although
the experts were given a written explanation, a verbal description, a
chance to ask questions, and even -- in the second round -- some samples
to work on, not all experts were the highest performer in their group.
Subjects' visual ability was an important variable in their performance
and that skill was not measured by a pre-test. However, given the large
sample sizes used, it is probably safe to assume that the ability
required for solving progressive matrices was randomly distributed among
the experimental cells. If this assumption is correct, ability should

not have caused any significant differences in cell means. In this

107
study the group process of research interest was information sharing.
The experimenter's intent was to supply the experts with the information
that could be shared or hoarded. During the actual experiment, however,
many non-experts shared their skills and insight into the nature of the
experimental task. That the information shared was not always the
information supplied by the experimenter is not crucial. The important
point is that the amount of sharing was shown to depend significantly
upon the reward structure used. The obtained results raise some
interesting questions as to why non-experts were, in fact, more willing
to share information than experts.

Another limitation was the relatively short time involved. The
number of problem sets was six, each one lasting three minutes. The
entire experiment took from 70 to 100 minutes. While subjects had time
to communicate if they chose to, in a more dynamic and extended setting
different behaviors may have emerged. The possibility of such outcomes
is discussed more fully in the following section of the paper. An
additional benefit of using an extended time period [Ilgen et al., 1981]
is that test-retest reliabilities could be determined for various
scales. The advantage of the relatively short time required for the
experiment was that it increased the likelihood of obtaining subjects.

Two instrumentality scales were used in the analysis. One was a
single item used by Ilgen et a1. [1981] and all subjects in the first
phase of the experiment responded to it. An additional five item scale
was used, but the questions were poorly designed, and the results were
indicative of subjects' confusion. Further testing was carried out to

emulate the longer scales used by Ilgen et al., modifying them as

108
appropriate for this study. That modification consisted of some
simplification of the presentation. Had the longer questionnaire been
used for all of the subjects the results on instrumentality might be
more powerful because of the larger sample size.

In the communication condition, subjects often told each other their
performance levels. It is possible that fuller disclosure of the other
group members' scores in both conditions would have had some impact on
performance.

An additional limitation is based on the particular incentive plans
tested in this research. Within the broad categories of cooperative and
competitive rewards, there are many individual methods of relating pay
to performance. The two plans used here were chosen because they
emphasized the group nature of the incentive plan. A competitive scheme
in which pay differential was greater could result in different
behaviors.

Finally, many questions still exist about the most appropriate form
of feedback and the differing effects of feedback under various
incentive plans. In this research a very minimal form of outcome
feedback was tested. Because this research is a study on incentive
plans, which link performance and reward, it was essential to include at
least minimal feedback. By definition incentive plans must include a
feedback mechanism. If pay is not linked to performance, then employees
do not have to know their performance levels. However, if pay is linked
to performance, then employees must be told their performance levels.
Because an additional purpose of the study was to explore the effect of

incentive plans on intra-group information sharing, it was essential

109
that the feedback provided by the experimenter be limited. Outcome
feedback indicates only the level of past performance. In the
competitive condition, subjects were told their rank as well as the
number they had correct. In the cooperative condition, subjects were
told only the number they had correct. Their rank did not have a direct
relationship to their pay so this information was not supplied.
However, it would have been possible to tell them their total group
productivity and their pay based on that. The appropriate feedback is
determined by the nature of the incentive plan. It is difficultpto
structure an experiment with different incentive structures and
identical feedback.

Other forms of feedback are primarily motivational, consisting of
exhortations to work harder and not be discouraged. Feedback can also
be more heuristic and individualized. One can examine how an employee
is approaching the problem and provide guidance and directions for
working more efficiently or effectively. None of that was done in this
study since the focus was not on the efficacy of feedback, but rather on
how incentive plans would alter group behavior. By sharing information
on their performance and on how to perform the task, the group members
were providing heuristic feedback to one another. Many questions are
still unanswered about the most appropriate type and amount of feedback

in various work settings.

Future Research

Future research on incentive plans and their effect on inter-agent

behavior could be developed along several distinct directions. Other

110
types of tasks should be tested -- particularly those involving complex
decision making. Generalizability is limited until numerous
replications over a wide range of tasks and subjects have been
completed. In future research ability should be a covariate, measured
at the beginning of the experiment in order to see how performance or
output changes over time. The theory of contest researchers suggest
that differential abilities may play a significant role in agent
behavior. It may prove fruitful to control for this variable and to
purposely manipulate it in order to determine its impact. This could be
done, for instance, by using more difficult or specialized tasks, such
that expert knowledge is necessary for successful completion. Such a
manipulation must be handled carefully, however, since an increase in
difficulty could lead to the confounding of task difficulty with task
interdependence.

The unexpected results in which the experts were relatively reluctant
to share information support the conjectures of the theory of contest
researchers and emphasize the importance of differential ability. In
this study the experts were given some information which ostensibly
affected their ability to perform the task. They were less willing to
share this information than subjects who had not received any privileged
information. Did the experts feel they had earned the right to benefit
from this privileged information? Did they genuinely misunderstand
their instructions? Did the experts in the cooperative reward fail to
see that sharing information was in their own interest? These questions
are rendered more significant when considering the fact that information

sharing by non-experts was significantly affected by the reward

111
structure. The non-experts apparently realized they could exchange
information to their benefit. Why were they more willing to share their
ability with other group members?

The experiment should be run over longer time periods or over more
periods, if possible. This would increase the possibility of either a
Stackelberg equilibrium or collusion arising. An additional,

methodological benefit to extending the time would be the possibility of
.measuring test-retest reliabilities of various scales. Ilgen et a1.

[1981] have stressed the need for such testing of expectancy theory

variables.
The possibility of collusion -- an intentional and coordinated level
of production below a level that could be reasonably achieved -- is an

interesting avenue for future research. The existence of such behavior
has been documented [Roy, 1952; Hickson, 1961; Coch & French, 1948;
Marriott, 1971]. Furthermore, the possibility that workers may collude
is widely recognized [Dye, 1984; Holmstrom, 1982; Lawler, 1981; Hopwood,
1976]. Nonetheless, the effect of various incentive plans on collusion
has not received much attention.1 In this study collusion would have
been most likely in the competitive setting. Since subjects were paid a
flat minimum wage ($ .50) for every period and a bonus for higher
performance relative to the others in their group, effort averse

subjects would be expected to communicate with other group members and

 

1 The studies mentioned above focussed on the social processes

that are involved in maintaining a restricted output level among group
members, rather than looking at whether such behavior is affected by
reward structures.

112
agree to do the minimum necessary to allow the principal to
differentiate among the group members. Successful collusion would
require side-payments, or other means of assuring pay equity. For
instance, the group members could agree to take turns being the most
productive member of the group. Both the restricted time-span and the
educational setting contributed to the fact that collusion did not arise
in the current experiment. Future experiments would strive for greater
realism in terms of length of study or could be done in the field.

Another suggestion for future research is to separately test the
effect of feedback and inter—agent communication by manipulating only
one at a time instead of using a factorial experiment. Since feedback
has been widely researched, the greater need is to study the effect of
inter-agent communication. Much of what was communicated among group
members was obviously feedback on the nature of the task and how to do
it correctly. If the appropriate technology is available, it would be
very interesting to monitor the exchanges among workers to see what
information is exchanged and what -- if any -- means are used to
encourage or discourage such sharing of information. Different
variations of cooperative and competitive incentive plans could be
tested using a similar research design. In particular, the differential
of pay in the competitive reward could be manipulated.

A final, difficult and profound issue underlying this research is the
question of the definition of rational self-interest. In the current
study fairness and self-interest were united in the cooperative reward
scheme, but were at odds in the competitive reward scheme. Ethical

motives were not the subject of this research. The study of the force

113
of ethical values in shaping economic decisions has not yet developed in
the accounting and economics literature. Kahneman et a1. [1986] say,
"The absence of considerations of fairness and loyalty from standard
economic theory is one of the most striking contrasts between this body
of theory and other social sciences...." They suggest that the standard
economic model would be enriched by the inclusion of fairness in agents'
motivation. Noreen [1988] argues that economic markets would be
eliminated without the assumption of ethical behavior. He quotes
Kenneth Arrow, ”It can be argued that the presence of what are in a
slightly old-fashioned terminology called virtues in fact plays a
significant role in the operation of the economic system...” Arrow
includes truth, trust, loyalty and justice in future dealings as
examples of such virtues. The importance and value of cooperative
behavior have been emphasized in recent psychology research. The
benefits of altruistic behavior have been shown to include the
unexpected result of positive biochemical changes in the agent [Luks,
1988]. By contrast, competition is shown to have many negative
psychological consequences. These include decreased motivation and
enjoyment and increased anxiety. See Kohn [1986] for a thorough review
of the literature in this area. One of Noreen's [1988] stated purposes
is to stimulate the inclusion of ethical considerations in discussions
of accounting. Future research on reward structures could be done
focussing on the force of ethical considerations both separately and in

conjunction with more traditional economic incentives.

APPENDIX A

INFORMED CONSENT DECLARATION

APPENDIX A
INFORMED CONSENT DECLARATION

The purpose of this research is to explore the effectiveness of various
incentive plans. In order to comply with University rules, it is
necessary that you read and sign this form.

This research requires you to participate in several sets of problems
called progressive matrices. In addition, you will be asked to answer
some questions about your performance and how your performance relates
to your pay. All the information you supply will be kept confidential
by the researcher, Sue Pickard, and will be seen only by her. She
assumes all responsibility for maintaining the confidentiality of all
results. You will be given a subject number to use on all forms.

Your pay for this experiment will depend upon your performance. As
there are different types of sessions, details of this will be explained
at the beginning of the session you participate in.

You may stop at any time, but if you choose to do so, you will not be
eligible for any compensation.

At the end of the study, a written description of the study and the
findings will be available from Sue Pickard.

Along with these rights, you incur some responsibilities by being a
subject. The primary responsibility is that you provide reliable
answers to the questions asked. We also ask that you do not discuss
this experiment with students outside this group; since the project is
still in progress other sessions will be conducted.

I certify that I have read and understand the rights and
responsibilities I have incurred as a subject in this research. Given
this understanding, I voluntarily agree to participate.

 

Print your name

 

 

Signature Date

114

APPENDIX B

FIRST EXPECTANCY MEASURE

APPENDIX B

FIRST EXPECTANCY MEASURE

SUBJECT NUMBER

 

The task you are about to perform and for which you will be paid
involves seeing relationships among abstract, visual symbols. Some
people are better at this srot of task than others are. Please indicate
below on a scale off one to five how you rate your general ability in
this area by circling the appropriate number. Examples of similar
skills are map-reading and interpreting graphs.

My skills at this sort of task are:

Worse than Somewhat About Somewhat Better than
most other lower than Average better than most other
people's average average people's

1 2 3 4 5

115

APPENDIX C

LATER EXPECTANCY MEASURE

APPENDIX C

LATER EXPECTANCY MEASURE

SUBJECT NUMBER

 

Test Set

 

Please indicate what you believe your performance will be on this set by
indicating whether you believe you can get the scores below and how
certain you are of getting that score:

Y - Can do Degree of
N - Cannot do Certainty:
0 to 1002

At least 2 right

At least 4 right

At least 6 right

At least 8 right

All 10 correct

116

APPENDIX D

FINAL QUESTIONNAIRE

APPENDIX D
FINAL QUESTIONNAIRE

Subject Number

 

Please answer the following questions as accurately as possible.

1. Did you receive a green test during the pre-test portion of the
experiment?

Yes Please go to Question 2.

No Please go to Question 5.

2. If you answer yes to question 1, did you share the information you
received from the experimenter with your fellow group members? Yes
No

3. If you answered no, please go to Question 4.

If you answered yes, at what point in the experiment did you share
the ' information? For example, did you share it before you started
working on the tasks? After two rounds?

 

 

4. What was the reason you decided to share or to not share the
information?

 

 

GO TO QUESTION 9

 

5. Did any group members give you information on how to perform the
task?

Yes No

 

6. If you answered yes, was the information helpful? Yes No

 

117

118

7. If you answered no to #5, did you figure out a rule to use in
ansering the questions? Yes No

If you did figure out a rule, could you please describe it:

 

 

 

8. Did you work this rule out alone or as a group?
Alone As a group

9. In this part of the questionnaire I am trying to get at what you
feel are the consequences or effects of how much work you do at this
task. The questions are in a somewhat unusual format. I will be asking
you to imagine that something happened 10 times and asking you to
indicate the number of times inn 10 that specific consequences would
follow. This can be a difficult idea to grasp, so I will start with an
example.
EXAMPLE: Suppose that on 10 different days you went to Hamburger Heaven
and each day you ate two Giganto-Burgers, one shake and an order of
fries. How many times in 10 would you .............
Still be hungry Feel Comfortably full Feel Stuffed

+ 3 + Z - 1Q

In this example, the person has indicated that he or she would feel

 

 

comfortably full 3 of the 10 times but on 7 of the 10 visits would have
been too full. This person also indicated that he or she would never
have felt hungry on any of the 10 days. Note that the answers total up

to 10.

119
Here is a second example. Assume that a person was offered a ride to
school on 10 different occasions and was asked the following:
How many times did you ride in a ..........

Red car White car Green car Blue car Silver car

2 + 2 + 2 + 2 + 2 - 10

 

 

 

 

 

 

This person has indicated that it is equally likely that he or she has
ridden in cars of the colors indicated by the five choices.

NOW I WOULD LIKE YOU TO ANSWER SOME QUESTIONS ABOUT THE RELATIONSHIP OF
YOUR PERFORMANCE TO YOUR PAY. PLEASE ANSWER EACH LINE AS A SEPARATE
QUESTION AND ASK IF YOU ARE CONFUSED.

Based on the method of payment you are receiving and the experience you

had doing these problems, indicate your chances in ten of being paid at
each of the following levels if you get the following number correct:

IF I GET THE
FOLLOWING # MY CHANCES IN 10 OF BEING PAID AT EACH LEVEL IS:
CORRECT:
.25 .50 .75 1-00 1.25 1.50 1.75 2100 2.25 2.50

 

 

 

 

2 Correct:

NOW ANSWER THE SAME SET OF QUESTIONS ASSUMING THAT YOU HAD 4
CORRECT, ETC.
.25 .50 .75 1.00 1J25 1.50 1.75 2.00 2.25 2.50

 

 

 

 

4 Correct:

 

 

 

 

6 Correct:

 

 

 

 

8 Correct:

 

 

 

 

10 Correct:

120
10. Now, please indicate what amount you would expect to be paid if you

have the following number correct in a single problem set. Notice that
this is another way of answering the same questions you answered above:

fl Correct Expected Pay
2

3

9

10

 

11. Could you please indicate:

 

a. Your sex M F

b. C. P.A.

c. Major

d. Age

e. Have you ever worked under an incentive plan? Yes No

f. If yes, could you please describe the plan?

 

 

121
THANK YOU FOR YOUR PARTICIPATION.

Please turn in your questionnaire and pick up your compensation. Please
remember that the research project is not completed and it is immportant
that you do not discuss the project with anyone outside this classroom.

A summary of the research results will be available spring quarter from
Sue Pickard, in the Accounting Department, if you are interested. If
you would like to discuss the project with Sue before then, feel free to
contact her at 355-7486.

APPENDIX F

PRE—TEST FOR NON-EXPERTS

123

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125

What Will 3e:rge Do TonightT
George has a problem about what to do with his
spare time this evening. There's a pro football
game on TV. friends have invited him to a party,
he has free tickets to see the ballet. and the
cinema near his apartment is showing a movie he
has been looking forward to seeing. To make his
dilemma even more acute he has just reached the
last chapter of a gripping novel and is about to
discover the murderer. What will George do tonight
given that he...

Likes parties less than movies.

Dislikes reading less than sports.

Doesn't like the ballet as much as parties.

Dislikes reading more than the ballet.

When you have found out what he will choose. find
out what he is least likely to have chosen.

The Nukkeldowne Elementary School believes in good old-fashioned
discipline; its educational philosophy allows for only moderate
use of positive stroking.

In fact, Ms. Rapp, Ms. Ruhl, and Mr. Palmer - each a specialist in
either reading, writing, or arithmetic (though not necessarily in

that order) - are the only teachers at the Nukkeldowne School who

regularly reward their students for good work.

From the following clues, can you determine which teacher is in
charge of each class, and offers each reward?

1. Ms. Ruhl, who doesn't teach the arithmetic class, gives her
best students brownie points.

2. Mr. Palmer and the teacher who gives her students gold stars for
excellence work in adjacent classrooms.

3. The writing teacher rewards the neatest, most legible, work with
red letters.

A A G N N O T R U

How many names of animals can you form using any or all of the nine
letters above? For each word, you may repeat only those letters that
appear more than once. Our list includes 13 animals, one using all
nine letters.

APPENDIX C

INSTRUCTIONS FOR EXPERTS

126

INSTRUCTIONS 0N RESEARCH TASK

Please note that you It. ch! only member of your work group to get this
information. You are under no obligation to share this information with
anyon. and should follow your own self-interest.

You will be given some matrix problems which only look difficult. Once you
know the ways to solve them you will be able to do so quickly and easily.
There are several different types of matrices that you will see. A majority
of the matrices you will see are based on the principle that each symbol
appears only once in each row (Horizontal) and once in each column (vertical).

See the example below:

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You are to pick which of the three choices belongs in the empty square in the
lower right corner of the matrix.

If you study the pattern you see that each symbol. the cross, the circle. and the
square,appears three times in the matrix. Each one appears once in each row and
once in each column. You have probably guessed by now that the circle is the
correct choice.

There are two approaches to this problem. You can look at the first row to see
what the three symbols are and then look at the bottom row and see which symbol
is missing. A speedier approach when the symbols are more complex is
called the diagonal method. To do this you look at the diagonal going from the
upper left to the lower right. If the two symbols are the same then the missing
symbol is also the same. If the two symbols are different then you look at the
middle square of the highest row and that is your miqsing symbol.

 

127

Here the two symbols in the Here the two symbols on the
diagonal are the same and so the missing diagonal are different so you look
symbol must be the same also. at the middle square of the first

row to see what the missing symbol is

 

 

 

 

 

 

 

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Things can become more complex by having several parts to the symbols. In the
following example you beve to treat the outside symbol. the square or circle or
triangle,seperately from the lines and dots in the middle of the symbol. Going
down the diagonal. you see a square and a triangle. so you move up to themiddle
square in the first row and see a circle. That means the correct answer is either
choice a or b. How you look at the symbol in the middle of the squares and
triangles and see that both items on the diagonal are short horizontal lines and
you know that the correct answer is b. which has a short horizontal line in the
circle.

 

 

 

 

 

 

 

 

There are other types of matrices you will see as well. These are called
change matrices and they tend to fall into three categories. An example

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APPENDIX H

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LI ST OF REFERENCES

REFERENCES

Ackelsberg, R. and G. Yukl. "Negotiated transfer pricing and conflict

resolution in organizations." ecision Sciencep, lg, 1979,
pp. 387-398.

Axelrod, R. Ihp Evolution of Cooperation, Basic Books: New York, 1984.

Baiman, S. "Agency research in managerial accounting: A survey."
Journal of Accounting Literature, l, 1982, pp. 154-213.

Bandura, A. "Self-efficacy mechanism in human agency." American
Psychologist, 37, 1982, pp. 122-147.

Becker, L. J. "Joint effect of feedback and goal setting on
performance: A field study of residential energy conservation."

Journal of Applied Psychology, hi, pp. 428-433.

Belkaoui, A. Conceptugl Foundations of Management Accounting. Addison-
Weslsy: Reading, Mass, 1980.

Birnberg, J. and K. K. Sadhu. "The contribution of psychological and
cognitive research to managerial accounting." In Research and

Current Issues in Management Accounting, ed. M. Bromwich and A.
Hopwood, Pitman Press, 1986, pp. 116-142.

Blau, P. "Cooperation and competition in a bureaucracy." American
Journal of Sociology, pg, 1954, pp. 530-535.

Brewer E. and P. Kacser. "A comparative analysis of incentive plans."
Journal of Industrial Economics, ll, 1963, pp. 183-198.

Bull C., A. Schotter, and K. Weigelt. "Tournaments and piece rates: An

experimental study." Journal of Political Economy, 2§(1), 1987,
pp. 1-33.

Cammann, C. and E. E. Lawler, III. "Employee reactions to a pay
incentive plan." Journal of Applied Psychology, pg, 1973,
pp. 163-72.

Campbell, D. J. "The effects of goal-contingent payment on the
performance of a complex task.” Personnel Psychology, fil, 1984,

149

150
pp. 23-40.

Chow, C. "The effects of job standard tightness and compensation scheme
on performance: An exploration of linkages." The Accounting
Review, October, 1983, pp. 667-685.

Chow, C. and M. D. Shields. ”Participation versus imposition of
standards and the trade-off between performance and truthful
subordinate communication." Unpublished working paper, San Diego
State University, September, 1986.

Chung, K. H., and W. D. Vickery. "Relative effectiveness and joint
effects of three selected reinforcements in a repetitive task

situation." Organizational Behavior and Human Performance, lg,
1976, 114-142.

Coch, L. J. and J. R. P. French, Jr. ”Overcoming resistance to change."
Human Relations, 1 1948, pp. 512-532.

-,

Cohen, J. and P. Cohen, Applied Multiple RegressithCorpelation Analysis
for th§,Beh§viora1 Sciences, John Wiley and Sons, 1975.

Davis, J. Group Performance, Addison Wesley: Reading, Ma., 1969.

Demski, J. and G. Feltham. "Economic incentives in budgetary control
systems.” The Accounting Review. April, 1978, pp. 336-359.

Deutsch, M. "An experimental study of the effects of cooperation and
competition upon group process." Human Relations, 2, 1949,
pp. 199-231.

Dillard, J. F. "Applicability of an occupational goal-expectancy model
in professional accounting organizations." Declsioh Sciences,
1979, pp. 161-176.

Dopuch, N., J. Birnberg, and J. Demski. Cost Accounting; Accounting
Data for Management Decisiong- 2nd edition. Harcourt Brace
Javonovich: New York, 1974.

Dye, R. "The trouble with tournaments.” Economic Inguipy, 1984, pp.
147-149.

Earley, P. C. "An examination of the mechanisms underlying the relation

of feedback to performance." Academy of Management Proceedings.
1986, pp. 214-220.

Fama, E. "Agency problems and the theory of the firm." Journal of

Political Ecppomy, §§(2), 1980, pp. 288-307.

Farr, J. L. "Incentive schedules, productivity, and satisfaction in

work groups." Organizational Behavior and Human Performance,
1976, ll, pp. 159 -170.

151

Ferris, K. R. "A test of the expectancy theory of motivation in an
accounting environment.” The Accounting Review, 1977, pp. 605-
615.

French, D., C. Brownell, W. Graziano, W. Hartup. "Effects of
cooperative, competitive, and individualistic sets on performance

in children's groups." Journal of Experimental Child Psychology,
23, 1977, pp. 1-10.

Games, P. A., H. J. Keselman, and J. J. Clinch. ”Tests for homogeneity
of variance in factorial designs." Psychological Bulletin, §§J
1979, 978-984.

Games, P. A., H. B. Winkler, and D. A. Probert. "Robust tests for

homogeneity of variance.” Educational and Psychologlcal
heasuremehg, PP, 1972, 887-909.

Green, J. R. and N. L. Stokey. "A comparison of tournaments and
contracts." Journgl of Political Economy, 1983, pp. 349-364.

Greenberg, P. S. "Incentive characteristics of bonus pools: Evidence
from laboratory experiments in a multi-agent setting." Working
paper, University of Illinois, 1986.

Gruneberg, M. M.and D. J. Oborne. Psychology and Industrial
Pgoductivity; A Reader, 1981, MacMillan: London.

Hackman, J. R., K. Brousseau, and J. A. Weiss. ”The interaction of task
design and group performance strategies in determining group
effectiveness." Or anizational ehavior nd Huma er 0 ance,
lg, August, 1976, pp. 350-365.

Harrell, A. M. and M. J. Stahl. ”Modeling managers' effort-level
decisions for a within-persons examination of expectancy theory in
a budget setting." Deci§ion Scienceg, lé, 1984, pp. 52-73.

Hickson, D. J. "Motives of work people who restrict output.”
Occupgtiongl Psychology, 1961, pp. 111-121.

Holmstrom, B. "Moral hazard in teams.” Bell Journal of Economics, l1,
Autumn, 1982, pp. 324-340.

Hopwood, A. Accounting and Human Behavior. Prentice Hall: Englewood
Cliffs, 1976.

Ilgen D. R. and J. M. Feldman. "Performance appraisal: A process

focus." Research in Organizational Behavior, h, 1983, pp. 141-
197.

Ilgen, D. R., C. D. Fisher and M. S. Taylor. ”Consequences of
individual feedback on behavior in organizations." Journal of

152

Applied Psychology, hi, 1979, pp. 349-371.

Ilgen, D. R., D. M. Nebeker, R. D. Pritchard. "Expectancy theory
measures: An empirical comparison in an experimental simulation."

Organizational Behavior and human Performance, PP, 1981, pp. 189-
223.

Jiambalvo, J. 1979. "Performance Evaluation and directed job effort:
Model development and analysis in a C.P.A. firm setting.” Journal

of Accounting Research, ll(2), Autumn, 1979, pp. 436-455.

Johnson, D. W., G. Maruyama, R. T. Johnson. ”Separating idology from
currently available data: A reply to Cotton and Cook and

McGlynn." ngchological Bulletin, 22, July, 1982, pp. 186-192.

Johnson, D. W., G. Maruyama, R. T. Johnson, D. Nelson, L. Skon. "Effects
of cooperative, competitive, and individualistic structures on

achievement: A meta analysis." sycholpgical Pullegln, g2,
January, 1981, pp. 47-62.

Kahneman, D., J. L. Knetsch, R. H. Thaler. ”Fairness and the
assumptions of economics." Printed in Rational Choice, ed. R.
Hogarth and M. W. Reder, University of Chicago, 1986, pp. 101-
110.

Kaplan, R. S. Advpnced Management Accounting, Prentice-Hall: Englewood
Cliffs, 1982.

Keppel, G. Design and Analysis; A Researcher's Handbook, second
edition. Prentice-Hall: Englewood Cliffs, 1982.

Kim, J. S. and W. C. Hamner. "Effect of performance feedback and goal
setting on productivity and satisfaction in an organizational

setting." Journal of Applied Psychology, hl, 1976, pp. 48-57.

Kohn, A. No contegt; The Case Against Competition. Houghton Mifflin:
Boston, 1986.

Lawler, E. E. III. Pay gnd Organization Development. Addison Wesley:
Reading, 1981.

Lazear, E. P. and S. Rosen. ”Rank-order tournaments as optimum labor
contracts.” Journgl of Politigpl Economy, §2(5), 1981, pp. 841-
864.

Locke, E., E. Frederick, C. Lee and P. Bobko. "Effect of self-efficacy,
goals and task strategies on task performance." Journal of

Applied Psychology, 92, 1984, pp. 241-251.
Luks, A. ”Helper's high." Psychology Today, 22(10), 1988, pp. 39-42.

Luzi, A. D. and K. D. MacKenzie. "An experimental study of performance

153
information systems." Management Science, gg, 1982, 243-259.

Magee, R. and J. Dickhaut. "Effects of compensation plans on heuristics

in cost variance investigations.” Journal of Accountipg Research,
Autumn, 1978, pp. 294-314.

Marriott, R. Incentive Payhent Systems, 4th edition. Staples: London,
1971.

Meyer, H. H., E. Kay, and J. R. P. French. "Split roles in performance
appraisal." Harvard Business Review, 3;, 1965, pp. 123-129.

Miller, L. and R. Hamblin. "Interdependence, differential rewarding and

productivity." American Sociologlcal Review, ;§, 1963, pp.
768-778.

Mitchell, T. R. "Expectancy-value models in organizational psychology."
In Expectations and Actions; Expectancy-Value Modelg in
P§ychology, ed. N. T. Feather. Erlbaum Associates: Hillsdale, N.
J., 1982.

Nalebuff, B. J. and J. E. Stiglitz. ”Prizes and incentives: Towards a
general theory of compensation and competition.” Bell Journal of
Economics, l3, Spring, 1983, pp. 21-43.

Namazi, M. "Theoretical developments of principal-agent employment
contract in accounting: The state of the art." gourpal pf

Accounting hlterature, A, 1985, pp. 113-163.

Nicholson, W. Microeconomic Theory, second edition. Dryden Press:
Hinsdale, 1978.

Noreen, E. "The economics of ethics: A new perspective on agency
theory." Accounting, Organizations and Society, l§(4), 1988,
pp. 359-370.

O'Keeffe, M. W. K. Viscusi, R. J. Zeckhauser. ”Economic contests:

Comparative reward schemes.” Journpl of Lgbor Economics, 2(1),
1984, pp. 27-56.

 

Rambo, W. W., A.M. Chomiak, and J. M. Price. "Consistency of
performance under stable conditions of work.” Jpp;ppl_p§_hppllpg
Psychology, §§(1), 1983, pp. 78-87.

Ronen, J. and J. Livingstone. "An expectancy theory approach to the
motivational impacts of budgets." The Accounting Review, October,
1975, pp. 671-685.

Rosenbaum, M. E. "Cooperation and competition." In Psychology pf Gyoup
Influence. Ed. P. B. Paulus. Erlbaum Associates: Hillsdale, N.
J., 1980.

 

154

Rosenbaum, M. E., D. Moore, J. Cotton, M. Cook, R. Heiser, M. Shovar, M.
Gray. ”Group productivity and process: Pure and mixed reward
structures and task interdependence.” Journal 0 Fe sonalit and

Social Psychology, lg, 1980, pp. 626-642.

Rothe, H. F. "Outputrates among industrial employees." Jo a of
Applied Psychology, 9;, 1978, pp. 40-46.

Roy, D. F. "Quota restriction and goldbricking in a machine shop.
"Aperican Journal of Sociology, 1952, pp. 427-442.

Scapens, R. W. and J. Arnold. "Economics and management accounting
research." In Research and Currpnt Issues in Management
Accounting, ed. M. Bromwich and A. Hopwood, Pitman Press, 1986,
pp. 78-102.

Schwab, D. P. ”Impact of alternative compensation systems on pay
valence and instrumentality perceptions.” Journal 0 ied

Psychology, 1973, pp. 308-312.

Schwab, D. P., J. D. Olain-Gottlieb, H. G. Heneman. ”Between subjects
expectancy theory research: A statistical review of studies
predicting effort and performance." Psychological Bulletin, 1979,
pp. 139-147.

Scott, W. E., Jr. and D. J. Cherrington. "Effects of competitive,
cooperative, and individualistic reinforcement contingencies."

Journal of Personality and Social Psychology, 39, 1974, pp. 748-
758.

Sims, H. P. Jr., A. D. Szilagyi, and D. R. McKemey. ”Antecedents of

work related expectancies." Academy of Managemeht Journal, lg,
1976, pp. 547-559.

Stone, D. L. and E. F. Stone. "The effects of feedback consistency and
feedback favorability on self-perceived task competence and

perceived feedback accuracy." Organizational Behavlo; and Human
Decision Processes 36 1985, pp. 167-185.

Strang, H. R., E. C. Lawrence, and P. C. Fowler. ”Effects of assigned
goal level and knowledge of results on arithmetic computation: A

laboratory study." Joupnal of Applied Psychology, 9;, 1978,
pp. 446-450.

Thomas, E. J. "Effects of facilitative role interdependence on group
functioning." human Relations, lg, 1957, pp. 347-366.

Vroom, H. Work and Motivation. John Wiley & Sons: New York, 1964.

Waller, W. S. "Slack in participative budgeting: The joint effect of a
truth-inducing pay scheme and risk preferences.” Accounting,

Qrganlzatiohs and Society, l;(1), 1988, pp. 87-100.

155

Waller, W. S. and R. B. Payes. "An experimental study of incentive pay
schemes, communication, and intrafirm resource allocation.”
Working paper, University of Arizona, 1989.

Weinstein, A. G. and R. L. Holzbach. "Effects of financial inducements
on performance under two task structures." Proceedings of the

80th Annual Convention, American Psychological Association, 1972,
pp. 217-218.

Wofford, J. C. ”The motivational basis of job satisfaction and job
performance." Personnel Psychology, 1971, pp. 501-519.

Young, S. M. Ihp Effectp of Subordinate's Private Information and
Participation on Budgetary Slack and Worker Satisfaction in a
Simulated Production. Unpublished doctoral dissertation,
University of Pittsburgh, 1983.

 

Young, S. M. ”Participative budgeting: The effects of risk aversion
and asymmetric information on budgetary slack.” Journal of

Accounting Research, 2;, Autumn, 1985, pp. 829-842.

GENERAL REFERENCES

Babchuk, N., and W. J. Goode. ”Work incentives in a self-determined
group." American Sociological Review, lg, 1951, pp. 679-687.

Bobko, P. "A solution to some dilemmas when testing hypotheses about

ordinal interactions.” Journal of Applied Psychology, ll, 1986,
pp. 323-326.

Brownell, P. "The role of accounting data in performance evaluation,
budgetary participation, and organizational effectiveness."

Journal of Accounting Research, 29(1), 1982, pp. 12-27.

Brownell, P. and M. McInness. ”Budgetary participation, motivation and

managerial performance." The Accounting Review, Lgl(4), October,
1986, pp. 587-600.

Chalos, P. and 8. Bake. ”Transfer pricing optima under bilateral
bargaining." Working paper, 1987.

Chow, C., J. Cooper and W. Waller. "Participative budgeting: Effects
of a truth-inducing pay scheme and information asymmetry on slack
and performance." Unpublished working paper, May, 1986.

Cooper, J. Compensation Contract Self Selection, Partlcipaplvp Spandard
setting and Job Performance. Unpublished doctoral dissertation,

University of North Carolina at Chapel Hill, 1985.

Demski, J. 8. "(Theoretical) research in (managerial) accounting.” In
Agcounting and Culture, ed. B. E. Cushing. American Accounting
Association, 1987.

Dillard, J. F. and J. Fisher. "Incentive compensation and worker
performance." Unpublished working paper, 1986.

Pain, M. ”Financial motivation.” Handbook of Industrial Engineerlng,
ed. G. Salvendy. John Wiley: New York, 1982.

Guyer, M. J. and A. Rapoport. ”2 X 2 games played once." Journal of
Conflict Resolution, 1972, pp. 409-432.

Harrell, A. and M. Stahl. ”Additive information processing and the
relationship between expectancy of success and motivational

force." Academy of Management Journal, 1986, pp. 424-433.
156

 

 

157

Hughes, E. C. "The knitting of racial groups in industry." American
Sociological Review, 1946, pp. 512-519.

Jorgenson, D. 0., M. D. Dunnette, and R. D. Pritchard. ”Effects of the
manipulation of a performance-reward contingency on behavior in a

simulated work setting." Journal of Applied Psychology, 1973, pp.
271-280.

Kaplan, R. S. ”The role for empirical research in management

accounting." Accounting, Organizations and Society, 1986, pp.
429-452.

Patten, R. Jr. Pay; Employee Compensation and Incentivp Planp, The
Free Press: New York, 1977.

 

 

Paulus, P. ”Group influence on individual task performance.” In
Sasic Group Processes, ed. P. Paulus. Springer-Verlag: New York,
1983.

Peters, L. H. ”Cognitive models of motivation, expectancy theory and
effort: An analysis and empirical test." Organizational Behavior
and Human Performance, 1977, pp. 129-148.

Pritchard, R. D. and P. J. DeLeo. "Experimental test of the valence-
instrumentality relationship in job performance.” Jougnal of

Applied Psychology, 1973, pp. 264-270.

Pritchard, R. D., P. J. DeLeo, and C. W. VonBergen, Jr. ”A field
experimental test of expectancy-valence incentive motivation

techniques." Organizational Behavior and Humgn Perfophance, 1976,
pp. 355-406.

Pritchard, R. D. and M. S. Sanders. "The influence of valence,
instrumentality, and expectancy on effort and performance.”

Journal of Applied Psychology, 1973, pp. 55-60.

Rosenbaum, M. E., D. Moore, J. Cotton, M. Cook, R. Heiser, M.Shovar, M.
Gray. "Group productivity and process: Pure and mixed reward
structures and task interdependence.” Journal of Pegsohality and

Social Psychology, ;2, 1980, pp. 626-642.

Roy, D. F. ”Banana time: Job satisfaction and informal interaction."
Human Organization, 1960, pp. 158-168.

Schoemaker, P. J. H. "The expected utility model: Its variants,
purposes, evidence and limitations." In The Quest fog Optimality,
ed. J. H. P. Paelinck and P. H. Vossen. Gower Publishing:
Hampshire, England, 1984.

Schwab, D. P. and L. Dyer. "The motivational impact of a compensation
system on employee performance." Or aniza iona ehavior and

158

hppah Performance, 1973, pp. 215-225.

Sweiringa, R. and K. Weick. "An assessment of laboratory experiments in

accounting.” Joupnal of Accounting Research, 1982 Supplement, pp.
56-101.

Terborg, J. R. and H. E. Miller. "Motivation, behavior, and
performance: A closer look at goal setting and monetary
incentives." Journgl of Applied Psychology, 1978, pp. 29-39.

Waller, W. S. "Slack in participative budgeting: The joint effect of a
truth-inducing pay scheme and risk preferences." Accounting,

Organizations and Society, l;(l), 1988, pp. 87-100.

Waller, W. S., and C. W. Chow. "The Self-Selection and effort effects
of standard-based employment contracts: A framework and some
empirical evidence." The Accounting Review, gQ(3), 1985.

Wilner, N. "SFAS and information inductance.” Accounting,
Organizations, and Society, 1(1), 1982, pp. 43-52.

Yetton, P. W. ”The interaction between a standard time incentive
payment scheme and a simple accounting information system."

Accounting, Organizations, and Society, l, 1976, pp. 81-87.

 

 

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