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This is to certify that the

thesis entitled

Substitutability and Dependency
Threat as Moderators of the relationship Between
COping with Uncertainty and Intraorganizational
Power

presented by
Jose Manuel Cortina

has been accepted towards fulfillment
of the requirements for

Master of Arts Psychology

degree in

 

 

 

Major professor

January 13, 1992
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TO AVOID FINES return on or before date due.

 

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MSU Is An Affirmative Action/Equal Opportunity Institution
cfblchunHi

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

M 7

 

SUBSTITUTABILITY AND DEPENDENCY THREAT AS MODERATORS
OF THE RELATIONSHIP BETWEEN COPING WITH UNCERTAINTY
AND INTRAORGANIZATIONAL POWER

BY

Jose M. Cortina

A THESIS

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

MASTER OF ARTS

Department of Psychology

1991

ABSTRACT
SUBSTITUTABILITY AND DEPENDENCY THREAT AS MODERATORS

OF THE RELATIONSHIP BETWEEN COPING WITH UNCERTAINTY
AND INTRAORGANIZATIONAL POWER

BY

Jose M. Cortina

The relationships among coping with uncertainty,
substitutability of home run hitters, dependency threat, and
intraorganizational power were examined in a sample of
college baseball teams. Previous studies suggesting that
substitutability accounted for little variance in power used
questionable operationalizations of relevant variables and
failed to test important interactions. Previous studies
investigating dependency threat have failed to examine the
various components of dependence. It was found that
substitutability, dependency threat, and the coping with
uncertainty by dependency threat interaction contributed
significantly to the prediction of power. It is suggested
that managers see their players as occupying roles which
require players to cope with specific types of uncertainty.
The type of uncertainty depends on the role that the player
is supposed to fill. Implications of these findings are

discussed.

ACKNOWLEDGEMENTS

Although there were many people who played a role in
the completion of this motley, rambling piece of work, the
true hero is Neal Schmitt. So I would like to give my
thanks to Neal. Thank you for beginning all of your
comments with encouraging words. Thank you for taking the
time to talk even when it wasn't convenient for you. Thank
you for getting the drafts of this thing back to me even
faster than I may have wanted them. I wouldn't have wanted

to tackle this project without you.

iii

TABLE

LIST OF TABLES . . . . . .
LIST OF FIGURES . . . . .
INTRODUCTION . . . . . . .

The Nature of Power .

OF CONTENTS

Coping as a Mean to Power . . . . . . .

Another Source of Power: Substitutability

A Third Antecedent to
Dependency Threat . .

Models of Power . . .

Power:

Objectives of the Present Study . . . .

Study Hypotheses . .
METHO D O O O O O O O O 0
Sample and Design . .

Objective Measures of

Coping with

Uncertainty and Substitutability . . .

Subjective Measures of Coping,

Substitutability, and
Dependent Variables .
Data Analysis . . . .

RESULTS 0 O O I O O O O O

Dependency Threat

Development of Measures of Dependent

Variables . . . . . .

Independent Variables: Coping,

iv

Page
vi

viii

11
12'
17
20
22

22

23

25

25

30

31

31

Substitutability, and Dependency Threat
Objective offensive and defensive
statistics . . . . . . . . . . . .
Subjective Measures . . . . . . .

Relationships Among Subjective and

Objective Measures . . . . . . . . . .

Tests of Hypotheses . . . . . . . . . .
Correlations between dependent and
independent variables . . . . . .
Hierarchical regressions . . . . .

DISCUSSION . . . . . . . . . . . . . . . . .

Hypotheses . . . . . . . . . . . . . .

Limitations . . . . . . . . . . . . . .

Future Directions . . . . . . . . . . .

LIST OF REFERENCES . . . . . . . . . . . . .
APPENDIX A . . . . . . . . . . . . . . . . .
APPENDIX B . . . . . . . . . . . . . . . . .

APPENDIX C . . . . . . . . . . . . . . . . .

44

44

48

51

54

54

56

62

62

66

67

70

73

82

89

TABLE

TABLE

TABLE

TABLE

TABLE

TABLE

TABLE

TABLE

LIST OF TABLES

Questionnaire Items and the Clusters

to Which They Belong . . . . . . . . . .
Means, Standard Deviations, and
Intercorrelations for the Seven Items
Representing the Defensive Cluster . . .
Means, Standard Deviations, and '
Intercorrelations for the Ten Items
Representing the Offensive Cluster . . .
Means, Standard Deviations, and
Intercorrelations for the Five Items
Representing the Quality of Practice
Cluster . . . . . . . . . . . . . . . .
Intercorrelations of the T-Scores for
the Final Set of Items and the
Reliabilities for the Final Clusters . .
LISREL Estimates for the Lambda X and
Phi Matrices for a Three-Factor

Model . . . . . . . . . . . . . . . . .
LISREL Estimates for the Lambda X Matrix
for a One-Factor Model . . . . . . . .
Means, Standard Deviations, and
Intercorrelations for Objective

Offensive and Defensive Statistics . .

vi

Page

28

32

33

35

38

41

42

45

TABLE 9

TABLE 10

TABLE 11

TABLE 12

Means, Standard Deviations, and
Intercorrelations Among the Subjective

Measures of the Three Independent

Variables . .

Means, Standard Deviation, and

Intercorrelations Between Objective

and Subjective Questionnaire Items .

Correlations of Measures of the Three
Independent Variables with Measures of
the Three Dependent Variables
Hierarchical Regressions of the Three

Dependent Variables on Coping with

Uncertainty, Substitutability,

Dependency Threat, and their

Interactions .

vii

49

52

55

58

LIST OF FIGURES

Page

FIGURE 1 A Conceptual Model of Power . . . . . . 16
FIGURE 2 Plot of the Effects of the Interaction

Between Coping with Uncertainty and

Dependency Threat on Offensive

Decisions . . . . . . . . . . . . I . . 60
FIGURE 3 Plot of the Effects of the Interaction

Between Coping with Uncertainty and

Dependency Threat on Defensive

Decisions . . . . . . . . . . . . . . . 61

viii

INTRODUCTION

The concept of power has existed in the social/
organizational psychology literature for decades. It is an
important concept because it exists anywhere there are two
or more people interacting with one another (Hickson et al.,
1971). While power has received a fair amount of attention
in the literature, very few models explaining the nature of
power have been formulated. Of those authors who have
sought to explain the use of power, only a handful (e.g.,
Pfeffer and Salancik, 1974: Salancik and Pfeffer, 1974:
Hinings et al., 1974) present empirical data to support
their models. For this reason, while many antecedents to
and outcomes of power have been postulated, the exact nature
of their relationships to one another have not been firmly
established. The goal of the research described in this
paper is to clarify the relationships among some proposed
antecedents to power and power itself.

WW2]:

Power is often conceptualized as an attribute of an
individual. However, this attribute cannot be measured
directly. Instead, power is inferred from the supposed
results of power, such as salary, influence, etc. For this
reason, the unit of analysis can be unclear in a power
study. For example, a person's power may, theoretically, be
an attribute of that person, but that person's power may be

measured in terms of its effects on a department. So, it

1

2
seems that power can be conceptualized at one level of
analysis and operationalized at a different level. If this
is the case, then individual power, for example, can be
studied at the group level. This sounds strange if not
logically impossible. It may also seem that this is what
the present study is attempting to do in that the measures
of one person's power are based on the behavior of another.
However, Salancik (1990) has suggested a way out of this
problem or, to be more precise, that the problem doesn't
even exist.

Salancik has argued that power is not an attribute of
any one entity, be it person or group. Instead, he suggests
that power is a social relationship. Power exists where one
entity, A, is dependent upon another entity, B, for some
valued resource. Power cannot be an individual attribute
because more than one person must be involved in order for
power to exist. A person does not simply have power. A
person has power over something else. One can say that
dependence has an effect on resource allocation and that
this relationship is one of power. One cannot say that
dependence has an effect on power because dependence is a
component of the power relationship. This seems like a
useful, logical way of thinking about power. The present
study adopts this view of power with the hope that it will
address any level of analysis problems. In the present
study, I sometimes refer to power as though it were an

individual attribute. This is done merely for the sake of

simplicity.

Mechanic (1962) defines power as any force, be it
personal or normative, that results in behavior that would
not have occurred had the force not been present. The power
literature suggests that this means power results in some
form of bonus. Fossum & Fitch (1985) and Bartol & Martin
(1989) looked at the effects of dependence on pay increases.
Hinings et al. (1974) looked at differences across subunits
which were on similar organizational levels in terms of
participation in decisions, formal authority, and perceived
power. This is important because it clarifies the
conceptual nature of power. Power is not simply doing work
and getting paid for it in some way. Instead, power results
in behavior that would not have occurred had the force not
been present, whether it be a pay increase, influence in
decisions, or any other form of bonus.

Mechanic also makes a distinction between formal and
informal power. Formal power is power that results from the
formal structure of an organization. An example of this
would be the power that results from holding a high-ranking
position in an organization. The present paper, however,
focusses on informal power, which can be roughly defined as
that power which results from the ability to cope with
uncertainty. This is a vague definition and is, therefore,
dealt with in more detail in the section below titled,
”Coping as a means to power".

The present study incorporates previous

4
conceptualizations of power in viewing it as the influence
of a subordinate over managerial decisions relating to that
subordinate. For example, Bartol & Martin (1989) examined
power of a subordinate over pay allocation (i.e., raises) to
that subordinate. This captures both the "influence over
decisions" aspect of power as well as the ”bonus" aspect of
power. The present study, for reasons that are explained
below, examines the power of a baseball player over
decisions of the team manager relating to the number of
games the player starts and the position in the batting
order in which the player starts given certain levels of
performance in defense, offense, and quality of practice
time. For example, a player with power over managerial
decisions would be allowed to start a game in spite of his
committing fielding errors or slacking off during practice.
Again, this captures both the "influence over decisions"
aspect (i.e., starting a game) as well as the "bonus" aspect
(i.e., starting in spite of poor performance). One way to
acquire such power is by coping with uncertainty.
W

In 1967, Thompson asked us to "...conceive of the
organization as an open system, indeterminate and faced with
uncertainty, but subject to criteria of rationality and
hence needing certainty.” Uncertainty, in this sense, is
the result of any event or situation which can have an
impact on an organization. Organizations strive to reduce

this uncertainty by coping with it. Therefore, any member

5
of an organization who can cope with an event or situation
that could have a significant impact on that organization
and that can't be coped with by a superior has power over
that organization. For example, if a machine breaks down on
an assembly line and Person A can cope with that uncertainty
(i.e., fix the machine), then A has power over the
organization. That person possesses a resource for which
the organization has a use. Hinings et a1. (1974) described
three different types of coping behavior. Coping by
prevention involves reducing the probability of variations
occurring in the inputs of the organization. Coping by
information involves providing forewarning of probable
variations in the inputs of the organization. Coping by
absorption involves offsetting the effects of variations in
the inputs of the organization. In the above example,
uncertainty is coped with by absorption. An important
machine breaks down, and Person A offsets the effects of
this event by fixing the machine. Absorption is generally
considered to be the most important type of coping (Crozier,
1964; Hinings et al., 1974). It alone comes after a
variation has already occurred and is causing problems. At
such a point, something has to be done immediately. The
benefits of coping by prevention and information are
”...more speculative and less obvious to [those] who might
thereby be protected..." (Hinings et al., 1974). The
operationalization of coping in the present study,

nevertheless, captures both coping by absorption and coping

by prevention.

The ability to prevent or absorb uncertainty gives one
informal power. In the above example as well as in the
present study, the power is upward power: power subordinates
possess to influence decisions of superiors. This is in
contrast to the downward power referenced by the work of
such authors as French & Raven (1959). As Blackburn (1981)
suggested, power and dependence exist on both ends of a
manager-subordinate relationship. This conceptualization
fits perfectly within the framework presented by Salancik
above. Subordinates simply wield a different kind of power.
The ability to cope with important uncertainty is a
component of this upward power. Nevertheless, ability to
cope with uncertainty, no matter how important the
uncertainty, is not the only determinant of power.

u ow ° ti tab' '

Several contemporary theories of power acknowledge the
existence of other determinants of power. Mechanic (1962)
calls one of these replaceability. Fossum and Fitch (1985)
call it marketability. Hickson et al. (1971) call it
substitutability. The idea is that coping leads to power
only insofar as that coping is monopolized. If more than
one person has the ability to cope with a given uncertainty,
then the relationship between coping and power is
diminished. In the assembly line example, A had the ability
to fix the machine and, because of that ability, A had a

necessary ingredient for reducing uncertainty. Person A,

7
therefore, had some potential for power. If, however, B and
C hays the same ability, then the power of A is lessened.

In the latter case, the organization would not have to rely
upon A to fix the machine and, therefore, should have been
under less pressure to respond to the influence attempts of
A.

Although the concept of substitutability as a component
of power relationships is pervasive in models of power, its
role has only been investigated empirically on a few
occasions (e.g, Hinings et al., 1974: Fossum & Fitch, 1985).
In what may be the most extensive look to date at the
relationship between substitutability and power, Hinings et
al.(1974) examined the correlations between their measure of
substitutability and their nine measures of power which
covered perceived power, participation power, and position
power. Perceived power was simply the extent to which a
subunit was perceived to wield influence. Participation
power was the extent to which subunits were allowed to
participate in various organizational decisions. Position
power was simply formal authority. The correlations of
substitutabilty with these nine measures of power (three
measures of perceived power, four measures of participation
power, and two measures of position power) ranged from .11
to .61, suggesting a moderate to strong relationship between
substitutability and power. However, the correlation
between coping and perceived power (perceived power was used

because it was the measure that was best predicted by the

8
independent variables) was .81 while the correlation with
substitutability partialled out was .74, suggesting that
substitutability adds little to coping in the prediction of
power. Nevertheless, those units found to be high in power
were generally high in nonsubstitutability. The low partial
correlation seemed to come from the fact that
substitutability didn't appear to matter when coping was
low. They concluded that substitutability was related to
power, but that there was no clear idea of how it was
related. There were, however, some potentially serious
problems with this study.

The first problem stems from the operationalizations of
substitutability. In their principal analyses, Hinings et
al. used five indirect measures of substitutability such as
level of formal education required, experience required, and
training required, and one direct, perceptual measure.
Substitutability can only be inferred from items such as job
requirements, and the only direct measure was perceptual.
Hickson et al. (1971) described such substitutability
measures as job requirements to be secondary. Primary
measures would seek to discover if alternative means of
performing activities do exist, and if they do, whether it
would be feasible to use them (Hickson et al., 1971). The
main problem with such measures is that they are often
difficult, if not impossible, to obtain. In the Hinings et
'al. (1974) study, no direct, objective measures were used,

thus possibly casting doubt on the inferences that were

made.

The second problem with the Hinings et al. study lies
in their data analyses. In concluding their 1974 study,
Hinings et al. suggested that substitutability might
interact with coping to affect power:

"...nonsubstitutability is of little consequence if the
nonsubstitutable activities absorb little uncertainty...".
Despite this intuitively reasonable statement, the
interaction term was not tested. The reason for this may
have been that coping with uncertainty and substitutability
were highly correlated. This multicolinearity could cause a
substantial decrease in statistical power with respect to
the interaction term, thus limiting the chances of
statistical significance. For this reason, it is important
to obtain valid measures of coping and substitutability with
as little unnecessary overlap as possible. While this may
be much more difficult than it sounds, it may also be
critical if one is to evaluate this hypothesized interaction
empirically.

Ability to cope with uncertainty seems to reference
that person (subunit, unit, etc.) who possesses the ability.
In the example of the broken machine, the person who could
fix the machine had this ability. Substitutability,
however, is not an individual attribute. Just as one person
cannot have power without another person over which he or
she might have power, so it is with substitutability. It is

not a characteristic of a person, but of a situation. An

10

organization has a certain amount of substitutability with
respect to e certain person. While a person's ability to
cope with uncertainty probably has an effect on the
organization's substitutability with respect to that person,
this effect may be exaggerated when substitutability is
operationalized as it was by Hinings et al. (1974).
Training and experience required for a position are
essentially individual characteristics. These measures do
not seem to encompass all of the factors which make up the
organization's ability to substitute. This would explain
why Hinings et al. found coping with uncertainty to account
for so much more of the variance in power than did
substitutability. Their operationalization of
substitutability may only have tapped into that part of
substitutability which stems from a person's ability to cope
with uncertainty. It would be no wonder if ability to cope
with uncertainty were highly related to training and
experience. Perhaps a measure of substitutability which
directly assesses an organization's capacity to compensate
for the loss of a certain performer would show this
correlation to be relatively small, hence allowing a better
test of the coping-substitutability relationship.

A final note about the Hinings et al. (1974) study is
that it failed to measure what has turned out to be another

important antecedent to power: dependency threat.

11
w ° ea

Dependency threat is a construct which has received a
growing amount of attention over the last two or three
years. Dependency threat is the extent to which a member of
a subordinate/superior relationship perceives the
relationship to be in danger of dissolution (Bartol &
Martin, 1988). Bartol & Martin (1989) examined the effects
of dependency threat, dependence, and pay secrecy on pay
allocations. These authors found: 1) a significant main
effect for dependency threat, 2) a significant dependency
threat by dependence interaction such that, under conditions
of high dependence, dependency threat led to pay increases
whereas, under conditions of low dependence, dependency
threat did not lead to pay increases, and 3) a significant
three-way interaction such that high dependence and high
dependency threat led to pay increases only when pay
decision information was available to the entire staff
(i.e., pay openness). What is important about the Bartol &
Martin paper for the present study (besides the fact that
dependency threat was found to affect pay allocations) is
the way they operationalized dependence. A superior was
considered to be dependent upon a subordinate if the unique
talents of the subordinate (i.e., asset-based lending) were
required to carry out the directives of the executive vice-
president. If asset-based lending was not important to the
directives of the executive vice-president, then dependence

was said to be low. To put it in terms of the present

12

study, coping with uncertainty (knowledge of asset-based
lending) and substitutability (other members of the staff
with knowledge of asset-based lending) were held constant.
The subordinate was always the only member of the staff with
knowledge of asset-based lending. It was the importance of
this knowledge (and thus, dependence) and dependency threat
that were varied. The present study expands on this.
Ability to cope with uncertainty and substitutability are
measured along with importance. What remains to be seen is
whether dependency threat plays the same role in the
dependence/ allocation relationship when coping,
substitutability, and importance change as when only
importance varies while coping and substitutability are held
constant (i.e., Bartol & Martin, 1989). Specific
operationalizations are discussed in more detail below.
W

In an attempt to clarify some of the ideas and
relationships that have been put forth in the previous
sections, this section is devoted to describing in detail
past models of power and relating these to the present
study. The present study examines the relationships among
coping with uncertainty, substitutability, dependency
threat, and managerial decisions. The literature suggests
several possible conceptual models of the relationships
among the variables examined in the present study. One of
these is the Resource Allocation Model of Salancik & Pfeffer

(1974). These authors, in a study of university

l3
departmental power, found that those departments that
acquired outside grants controlled more positions on more
important committees and were perceived by various faculty
members to have more power than departments that did not
acquire outside grants. In turn, these two outcomes led to
greater graduate support for the departments. In other
words, provision of valued resources led to power which, in
turn, led to acquisition of different valued resources.

This conceptual model is very simple. It leaves
several questions unanswered. For example, How would the
relationships change if the effect on power of the number of
departments that provided valuable resources (i.e.,
substitutability) were assessed? Hinings et al. (1974)
attempted to answer this question by examining the effects
of coping with uncertainty (roughly analogous to grant
acquisition) and substitutability on power. As was
mentioned previously, these authors found coping correlated
highly with power while their measure of substitutability
with the effects of coping partialled out did not. In
concluding, they suggested two plausible models of routes to
power. Although these were not causal models, the causal
relationships that are assumed by the models can be
described. .

The first model suggests that the principal
determinants of power are coping with important uncertainty
and number of others dependent upon the person that can cope

with the important uncertainty. Substitutability is

14
mentioned as something to be avoided, but it is not endowed
with any direct links to power.

The second model ascribes even less importance to
substitutability. Substitutability, or in this case,
nonsubstitutability, is merely an incidental effect of
coping with uncertainty with no further links in the model.

Both of these models explain in more detail the ways in
which power is affected by provision of valued resources.
They do, however, leave two important questions unanswered.
First, how do all of these factors combine to affect the
outcomes of power (i.e., graduate support)? Second, what
would be the effect on power and its outcomes of a threat to
the provision of valued resources such as grants (Salancik &
Pfeffer, 1974) or specialized skills (Hinings et al., 1974)?
For example, in the case of Salancik & Pfeffer, how would
power and its outcomes be affected by the chairperson of a
department who acquires copious grants receiving an
attractive job offer from another school? Bartol & Martin
(1989) addressed these questions and found that managers
were most likely to approve a raise for a subordinate when
that subordinate provided important, unique skills and was
considering applying for another job. According to Bartol &
Martin (1989), the relationship between dependency threat
and pay allocation is moderated by dependence such that
dependency threat leads to increased pay only if the
allocator is dependent upon the recipient for some important

resource. While this model shores up some of the weaknesses

15
of the Hinings et al. (1974) model, it also suffers from
some of the same problems that were found in the Salancik &
Pfeffer (1974) study and that were dealt with by Hinings et
al. (1974). Hinings et al. (1974) broke down what Salancik
& Pfeffer (1974) call provision of valued resources and what
Bartol & Martin (1989) call dependence into some of its
constituent parts such as coping with uncertainty and
substitutability. The present study attempts to combine the
strengths of all three of these studies within the overall
framework suggested by Salancik (1990) that was mentioned
earlier. I propose that something similar to the model
presented in Figure 1 best describes the relationships among
coping with uncertainty, substitutability, dependency

threat, and managerial reward allocations.

16

 

 

 

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17

The first point to be made with regard to this model is
that "power" is not proposed as a variable. In accordance
with the suggestions of Salancik (1990), the entire set of
antecedents and outcomes make up a power relationship or
power situation. The second point is that coping,
substitutability, and dependency threat all have direct
effects on allocations. This is in line with the findings
of Hinings et a1. (1974) and Bartol & Martin (1989). The
third point is that substitutability moderates the
relationship between coping and allocations. This follows
from the hypotheses of the present study and is in line with
the suggestions of Hinings et al. (1974). The final point
to be made is that dependency threat moderates the
relationships between power and coping with uncertainty, and
power and substitutability. These moderator effects are
hypothesized because Bartol & Martin (1989) found a
significant dependence by dependency threat interaction.
Unlike the Bartol & Martin study, however, the present study
will examine various levels of coping with uncertainty and
substitutability. If, as is hypothesized, coping with
uncertainty and substitutability, as components of
dependence, all lead to power, then dependency threat should
moderate both of these relationships.

e s e Pres Stud

The present study attempts to clarify the relationships

of substitutability, coping, and dependency threat to power.

This is be accomplished in several ways. First, the

18
operationalizations of coping and substitutability used by
Hinings et al.(1974) are improved upon by using direct
measures of coping and substitutability, both objective and
perceptual. Second, the role of substitutability in the
coping-power relationship is specified. Hinings et al.
(1974) did not test for the interaction of coping and
substitutability. In the present study, measures of coping
and substitutability that are relatively independent are
developed and used to allow a meaningful test of the
interaction that is consistent with prior theoretical
statements about power (Hickson et al., 1971; Hinings et
al., 1974). Third, the Bartol & Martin (1989) study is
replicated and expanded upon with respect to dependency
threat. Specifically, the role of dependency threat in
power relationships is examined in a setting where coping
with uncertainty and substitutability vary. In this way,
the effects of dependency threat on the different components
of dependence are examined. It is hypothesized that, above
and beyond main effects, substitutability interacts with
coping ability to affect power such that coping ability has
less of an effect on power when substitutability is high
than when substitutability is low.

The failure of Hinings et al. (1974) to use direct
measures of substitutability may have resulted from
unavailability of such measures in their sample of
manufacturing subunits. If this was the case, then they

would have had no way of knowing whether or not one unit was

l9
performing or coping to such an extent as to be a legitimate
substitute for another unit. The present study attempts to
overcome this problem by using college baseball teams as the
sample. College baseball teams keep extensive records of
objective performance data (e.g., home runs, errors,
assists, etc.) which make possible accurate assessments of
coping with uncertainty and substitutability. For example,
if a team has one player that hits 35 home runs in a season
(a large number of home runs, which are an important
component of team success), then that player can be said to
have the ability to cope well with the uncertainty of
generating runs (or not generating runs). Just as a car
manufacturer needs someone to cope with the uncertainty of
machine-down time, so does a baseball manager need someone
to cope with the uncertainty of not driving in runs. Also,
if the team as a whole only hit 50 home runs, then it can be
said that the team is low on substitutability with respect
to that player on that characteristic. If, however, the
same team hits 300 home runs, then the team is high on
substitutability with respect to that player. College
baseball also offers some advantages over other types of
organized baseball. Intramural baseball, for instance,
tends to be less organized, with few, if any, practices held
and few, if any, records kept. Also, teams will often
differ greatly with respect to talent, motivation to win,

etc.

20

The use of professional baseball, like college
baseball, would avoid all of these problems. They are both
highly organized, and such items as individual talent and
motivation to win are relatively constant across teams. The
problem with using professional baseball comes with the
measurement of substitutability. If a professional who is
vital to a team slacks off, he can be traded for a player of
similar abilities. If a college player who is a vital part
of a team misses practice or slacks off somehow, there is
little the coaching staff can do (i.e., he can't be traded).
A transfer student in college must sit out a year before
playing a varsity sport. A professional is necessarily
substitutable. A college player is not necessarily
substitutable.
W

Following Hinings et al.(1974), power is the dependent
variable to be explained. Power, in this case, will be
upward power. The question to be addressed is, When does
the performance of subordinates influence the decisions of
superiors? It is expected that a.) subjects high in coping
with uncertainty have more power over managerial decisions
concerning starts and batting order than subjects low in
coping ability, b.) subjects high in substitutability have
less power over such managerial decisions than do subjects
low in substitutability, c.) substitutability interacts with
coping to affect power such that coping has less of an

effect on power when substitutability is high than when it

21
is low and d.) subjects high in dependency threat have more
power over such managerial decisions than will subjects low
in dependency threat, and e.) dependency threat moderates
the relationships hypothesized in a.) and b.) above such
that coping and substitutability will not be related to
power when dependency threat is low. In other words, it is
hypothesized that both substitutability and dependency
threat moderate the relationship between coping with
uncertainty and power and that dependency threat also
moderates the relationship between substitutability and

power.

Method

W

320 Division 1 and Division 2 NCAA baseball coaches
were mailed the 41 item questionnaire (Appendix A) in which
they were asked about the value of their best home run
hitter (specifics are described below). As low returns can
affect the validity and reliability of a study (Roeher,
1963), several measures were taken to ensure an adequate
return rate. Heberlein & Baumgartner (1978) found that
questionnaires with content salient to the respondent had an
average return rate 35% higher than those with non-salient
content. As this questionnaire deals with decisions that
baseball managers have to make everyday, its salience is
assumed to be high. A second factor affecting return rate
is number of contacts (e.g., Linsky, 1975; Dillman et al.,
1974). For this reason, 198 of the managers were sent a
postcard "warning" them of the questionnaire to come. Two
weeks after the questionnaires were sent to these 198
coaches, they were mailed a second postcard thanking those
who had returned them already and asking those who had not
to please do so. Also, those coaches of the 198 who had not
returned their questionnaires within a month of mailing were
sent a second copy. Because of low return rate,
questionnaires were sent to an additional 122 coaches. No
additional contacts were made with this supplemental set of

122 coaches.

22

23

A third factor influencing return rate is the presence
of a personally signed letter of introduction on letterhead
paper (Longworth, 1953). The managers were sent a cover
letter briefly describing the study and displaying the
support of the study by the head baseball coach of Michigan
State University and the assistant baseball coach of Tulane
University (Appendix B). A fourth factor is the use of
multi-colored, small-denomination stamps (Longworth, 1953).
This, too, was employed. Finally, in accordance with the
findings of Ferriss (1951), self-addressed, stamped return
envelopes were used. Of the 320 coaches who were polled,

108 returned the questionnaire completed, for a return rate

of 34%.

Objective Measures of Coping with Uncertainty and
E l I'lu! J'J't

Coping ability was operationalized as the number of
home runs hit by the team member with the most home runs
divided by his number of at bats, thus providing an index of
coping with uncertainty that is comparable across different
teams. Number of home runs was used because it is crucial,
objective, and relatively independent of other factors such
as batting average, quality of teammates, etc. It is a
function of little more than the ability to hit the ball
hard. This operationalization encompasses both coping by
prevention and coping by absorption. The uncertainty in
this case is a lack of runs. A home run prevents this

uncertainty if it doesn't already exist and absorbs it if it

24
does. "Substitutability" was operationalized in three ways.
The first two operationalizations were very similar. They
were the number of home runs hit by the team and the number
of home runs hit by the team minus the number of home runs
hit by the best home run hitter. For example, if a certain
player hits 40 home runs and his team, as a whole, hits only
60, then there is no reasonable substitute for that player's
home run hitting. If, on the other hand, a certain player
hits 40 home runs and his team hits 400, then that player's
home runs are only a small part of the home runs hit by the
team and, therefore, that player is more substitutable with
respect to home run hitting. By using team home runs, the
team's overall substitutability with respect to its best
home run hitter can be measured. While the number of home
runs hit by the team leader in home runs is certainly
related to the number of home runs hit by the team, it is
only one small component of team home runs and should not be
prohibitively correlated with it. The third measure of
substitutability was the number of home runs hit by the
second best home run hitter on the team. .This provides an
index of substitutability that differs conceptually from the
first two. Unlike the first two indices, which better
reflect the conceptualization of substitutability as a team-
level construct, the number of home runs hit by the second
best home run hitter measures the extent to which there is
one person who could step in and take the place of the best

home run hitter with respect to home run hitting.

25
Subjeetiye Meeegzes ef seeing, Subsgitutability, and
W

Subjective questionnaire items were used as alternate
measures of the coping with uncertainty and substitutability
variables. Item 4 in the questionnaire (se Appendix A),
which asks the coach to rate his best home run hitter with
respect to home run hitting ability, was used as the sole
subjective measure of coping with uncertainty: Item 13,
which asks the coach to estimate the number of players on
his team who could do a reasonable job of substituting for
the team's best home run hitter with respect to home run
hitting, was used as the sole subjective measure of
substitutability. As there were no objective measures of
dependency threat available, only subjective measures of
this construct were used. Items 40 and 41, which asked
coaches to estimate the probability that his best home run
hitter could get a minor league contract immediately and the
probability that he could play in the major leagues some
day, provided these measures.

e Va ' es

Clusters of questionnaire items relating to three
aspects of baseball performance and of managerial decision-
making were used. The three clusters were offensive play,
defensive play, and quality of practice time. Power was
measured by asking the managers questions such as, How low
would the subject's assist output have to go before he would

be removed from the starting lineup (Defense)?, How high

26
would the subject's number of strikeouts have to go before
he would be moved down in the batting order (Offense), and
How many practices would the subject have to be late for
before he would be removed from a lineup (Quality of
practice time)?

Managers were also asked questions such as, How many
times did the subject strike out?, Rate the subject with
respect to the strength of his throwing arm, and Rate the
subject on the extent to which he works hard on his hitting.
These performance items were used merely as a frame of
reference for the coaches filling out the questionnaire so
that they would have a foundation on which to base their
responses to the managerial decision items. These reference
items were used in data analysis only insofar as they were
partialled out of their respective regressions before
coping, substitutability, dependency threat, and their
interactions were entered into equations. This was done to
remove any possible priming effects of the reference items.
The item numbers and their corresponding clusters can be
found in the Table 1. Appendix B lists the questionnaire
items by cluster (i.e., offensive, defensive, or quality of
practice time) and by category (i.e., frame of reference or
measure).

In addition, one questionnaire item was used to get an
overall measure of each of the clusters for each category.
For example, item 17 asks the coach to rate the player with

respect to his overall defensive ability, and item 18 asks

27
the coach to estimate how low this overall defensive ability
would have to go before he would sit the player out for a
game. Item 17 is a frame of reference item for item 18.
Items 21 and 22, and 32 and 33 do the same for offensive
ability and quality of practice time. These were intended

as additional measures of their respective constructs.

28

Table 1
01:: °!!'. ‘ ‘1'. :10. t!‘ - ‘, - 1°Ch he Belon

 

11£u_ggne§3 CLUSTER NUMBEB'
5-8 18
10-11
17
20-21
26-28b

4 2
9

12

14-15 .
26

28

33-34

37-38

18-19 3
24-25
29-32
35-36

 

'*1=Offensive Cluster, 2=Defensive Cluster,

3=Practice Cluster

'-Items 14, 18, 20, 24, 26, 29, 31, 33, 35, and 37 are frame
of reference items.

b-Items 26 and 28 can be used for both the offensive and
defensive clusters.

29

At this point, it should be made clear that the present
study does not hypothesize, for instance, that a player who
hits more home runs will have more errors, fewer assists,
etc. The hypothesis is that he would be allowed to play in
spite of these faults because of his home run hitting
ability. This operationalization of power is analogous to
those referenced by Bartol & Martin (1988,1989) in that it
tests for changes in influence over managerial decisions as
a function of coping ability. In the case of Bartol &
Martin (1989), dependence on subordinates (coping with
uncertainty being a component of this dependence) gives
subordinates influence over managerial decisions concerning
pay allocations. In college baseball, there are no
salaries. Instead, coping ability buys one rewards of a
slightly different nature; it buys a player chances to play
in games in spite of deficiencies that the player might
have. Specifically, home run hitting buys a player game
time even if that player is less than proficient in other
areas of coping ability. This is in line with the present
conceptualization of power. For example,.a player who makes
more than his share of errors would not normally be a
starter. If, however, this same player is uniquely able to
cope with the uncertainty of a lack of runs by hitting home
runs, then he will receive the "bonus" of appearing in the
starting lineup. As an example from the offensive and
practice clusters, a player who bats .220 or a player who

never takes batting practice seriously would not normally be

30
a starter. Home runs, however, might influence managerial
decisions concerning playing time.

As indicated above, coaches were asked to provide
statistics such as the number of home runs hit by the team's
best home run hitter so that, when filling out the
questionnaire, they would have the actual statistics in
mind.

DQEA.AD§1¥§1§

Data analyses were conducted in three stages. First,
convergent validity of the various measures of coping with
uncertainty and substitutability were examined by
correlating the objective measures of coping with
uncertainty and substitutability with the subjective
measures of each.

Second, the viability of the formation of the three
dependent variable clusters (offensive, defensive, and
leadership-based decisions) was assessed with measures of
internal consistency, item intercorrelations, and
confirmatory factor analysis (LISREL VII, Joreskog & Sorbom,
1991).

Third, hierarchical regressions were conducted. Each
of the power measures was regressed on coping with
uncertainty, substitutability, dependency threat, the three
first-order interactions, and the second-order interaction.
Due to power considerations resulting from relatively small
sample size, hypotheses were tested at p<.10 significance

level.

Results

!1- - 0911‘! - . .e .-~_--.d-.
Means, standard deviations, and intercorrelations for

the seven items representing the defensive cluster, the ten

items representing the offensive cluster, and the five items

representing the practice quality cluster are presented in

Tables 2, 3, and 4 respectively.

31

32

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Table 4

Meene, Stengerg Deviations, and Intercorrelations for the
Five Items Represegting EDS Quality of Practice Cluster
1335? H Mean SD 1 2 3 i 5
SERREM 105 2.71 1.54 1.00

SHAPREM 103 2.64 1.33 .34‘ 1.00

LATEREM 100 3.66 2.00 .06 —.05 1.00 .

PRACREM 99 2.86 1.36 .35" .55*—.17 1.00
HELPREM 101 2.08 1.40 .25‘ .42‘ -.04 .47‘1.oo
'p<.05

' SERREM=Seriousness in batting practice before removal;

SHAPREM=Extent to which he tries to stay in shape before

removal: LATEREM=Extent to which he comes to practice late

or leaves early before removal; PRACREM=Seriousness in

practice in general before removal; HELPREM=Extent to which

he was willing to help other team members before removal.

36

Four points should be made about these tables. First,
number of putouts before removal (PUTREM, Table 2), number
of assists before removal (ASSREM, Table 2), number of times
hit into a double play before moving down in the batting
order (HDPDOWN, Table 3), and number of times hit into a
double play before removal (HDPREM, Table 3) have standard
deviations that are larger than their means. This is caused
by the fact that most of the coaches who returned
questionnaires responded to these items with zeros,
suggesting that putouts, assists, and number of times
hitting into double plays alone would not be reason enough
to remove their best home run hitters from the lineup or
move them down in the batting order. For this reason, these
items were not used in subsequent analyses.

The second point to be made about these tables is that
number of errors before removal (ERRREM, Table 2), batting
average before removal (AVGREM, Table 3), batting average
before moving down in the batting order (AVGDOWN, Table 3),
frequency with which he was allowed to swing with a three-
ball count (COUNT, Table 3), and extent to which he was
allowed to arrive to practice late before removal (LATEREM,
Table 4) have relatively low intercorrelations with the rest
of the items in their respective clusters. For this reason,
these items were not used in subsequent cluster development
analyses.

Third, because of their negative correlations with

other items in their respective clusters, defensive

37

performance before removal (DEFREM), the two items involving
strikeouts (KSDOWN and KSREM) and ability to get to balls
hit in his direction before removal (BALLREM) were
negatively scored for all subsequent analyses. The final
point to be made about these tables is that the various
items have substantially different means and standard
deviations. For this reason, items were standardized and
transformed to items with means of 50 and standard
deviations of 10 so that all items would have unit weights
when combined to form scales.

Table 5 presents the intercorrelations among the final
set of twelve items (four offensive, four defensive, and
four leadership) and coefficient alphas for each of the

three clusters. These correlations were computed after the

transformations to standard scores described above.

38

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40

Two points should be made about Table 5. First, given
the number of items in each of the clusters, coefficient
alphas are moderate, suggesting that communalities are
reasonable, but not outstanding (Cortina, in preparation).
Second, the intercorrelations within clusters are larger
than those outside the three clusters. These data offer
some support for the discriminant validity of the three
clusters. In an attempt to further investigate the
discriminant validity of these measures, LISREL VII
(Joreskog 8 Sorbom, 1991) was used to test one-factor and

three-factor models.

41
Table 6
Lierel Regimegee fie; Lemee 3 egg Ehi Matgices for a
Threezfaeter_uedel

 

glueters
Items effenee Defense Leederehin
KSREM .722
xsoowu .846
OFFREM .515
spsnowu .513
SPEDREM .611
DEFREM .499
BALLREM .746
ARMREM .679
SERREM .410
SHAPREM .667
PRACREM .878
HELPREM .519
DEFENSE' .669
LEADERSHIP.532 .631

 

' The DEFENSE and LEADERSHIP rows contain the Lisrel
estimates of the Phi matrix; that is, the relationships

between the three latent constructs.

42
Table 7
LISBEL Eetimetee fie: the Lemtda M Matrix for a One-Factor
Mel

 

ltete ral ac o
KSREM .480
KSDOWN .611
OFFREM .627
SPEDOWN .598
SPEDREM .597
DEFREM .514
BALLREM .660
ARMREM .610
SERREM .459
SHAPREM .513
PRACREM .656

HELPREM .414

 

43

Tables 6 and 7 present the LISREL estimates for the two
models. Table 6 shows that the estimated loadings of the 12
items on their respective e_ptie;i factors range from .410
to .878 with a mean loading of .634. Table 7 shows that the
estimated loadings of the 12 items on one overall factor
range from .414 to .660 with a mean loading of .561. This
suggests that the a etiori factors represent the data better
than a single factor explanation. However, the Phi Matrix
presented at the bottom of Table 6 suggests that the three
clusters are highly intercorrelated. In addition to these
data, adjusted goodness of fit indices and root mean square
residuals for the two models are similar, with the adjusted
goodness of fit index being slightly larger for the three-
factor model (.75 vs. .72) and root mean square residual
being slightly smaller (i.e., more supportive) for the one-
factor model (.10 vs. .09). Because the one-factor model is
nested within the three-factor model, a test of the
difference in Chi-squared was performed (Widaman, 1985).
This difference (34.07, 3 degrees of freedom) was found to
be significant (p<.05), and because Chi-squared was more
supportive of the three-factor model (95.30 for the three-
factor model vs. 129.37 for the one-factor model) than of
the one-factor model, it was concluded that the a priori
clusters of the dependent variable items better represent
the items. As a result, all subsequent analyses were
conducted for each of the three a priori clusters, which

were formed by summing the four items constituting each

44

cluster.

e : s bst'tutab'lit and
W
'v a s've tat'stics
Means, standard deviations, and intercorrelations among

the objective statistics are presented in Table 8.

 

45

 

 

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47

Three points should be made about this table. First,
the three possible substitutability measures; number of home
runs hit by the team (TEAMHR), number of home runs hit by
the second best home run hitter (SECNDHR), and the number of
home runs hit by the team minus the number of home runs hit
by the best home run hitter (OTHERS) are very highly
correlated. Because the OTHERS variable best fits the
conceptual definition of substitutability as.a team-level
construct (as opposed to SECNDHR), and because it is
somewhat independent of coping with uncertainty (as opposed
to TEAMHR, which includes the home runs hit by the best home
run hitter), only the OTHERS variable is used in subsequent
analyses.

The second point to be made about Table 8 is that the
OTHERS variable has substantial positive skew. For this
reason, all subsequent analyses involving this variable are
performed with the square root of OTHERS (ROOTOTH).

The final point to be made about this table is that
HRRATIO (Coping with Uncertainty) has a correlation of .38
with ROOTOTH (Substitutability). While this correlation is
statistically significant, it is considerably smaller than
the relationship between these two variables reported by
Hinings et al. (1974), suggesting that substitutability may
not be as dependent upon coping with uncertainty as was

suggested by Hinings et al. (1971).

It!)

48
Wares
Table 9 contains means, standard deviations, and
intercorrelations for the subjective measures of coping with

uncertainty, substitutability and dependency threat.

 

49

 

 

Table 9

v o s a n e co elations Among the
finnjeetiye Meesntee of the Three Independent Variables
Items N USED 52 1 2 3 i
RATEHR 103 5.00 1.16
(Coping)
SUBS 105 0.44 0.50 -.13 ‘
(Substitutability)
MINORS 102 59.31 29.58 .34* .oo

(Dependency Threat)
MAJORS 104 31.59 27.68 .21 .05 .74'

(Dependency Threat)

 

RATEHR=Coaches' rating of home run hitting ability;
SUBS=Coaches' estimation of number of substitutes for the
home run hitting of the best home run hitter;
MINORS=Coaches' estimation of the probability that the
player could get a minor league contract immediately;
MAJORS=Coaches' estimation of the probability that the

player could get a major league contract someday.

50

Three observations can be made about the data presented
in Table 9. First, the item asking coaches to estimate the
number of players on his team that could substitute for the
home run hitting of the best home run hitter (SUBS, the
subjective measure of substitutability) does not correlate
significantly with any of the variables in Table 9. Also,
although it is not shown in this table, this subjective
measure of substitutability does not correlate with the
three objective measures of substitutability. These
correlations range from -.05 to .05. Possible reasons for
these low correlations are suggested in the discussion
section of this paper. Because of its lack of convergence
with the onjective measures, the subjective substitutability
measure is not used in subsequent analyses.

Second, Table 9 shows that probability of getting a
minor league contract (MINORS) and probability of going to
the major leagues (MAJORS) are highly correlated (.74). For
this reason, these two items were combined to form a single
measure of dependency threat.

Finally, the subjective measure of coping with
uncertainty (RATEHR) is significantly correlated with the
two items measuring dependency threat (MINORS and MAJORS),
suggesting that the better able a subordinate is to cope
with uncertainty, the more likely it is that the person will

have alternative career options.

51
s ' s u e 've an ob ective measuree
Table 10 contains means, standard deviations, and
intercorrelations among the subjective and objective

measures of the three independent variables.

52

 

Table 10
ev' 'o e cor elations Between
aneetive eng Snbjeetiye Questionnaite Itens
N MEAN §D l 2 3 A 5
1.RATEHR 103 5.00 1.16

(Subjective Coping)
2.HRRATIO 102 0.06 0.03 .53

(Objective Coping)

3.ROOTOTH 102 4.82 1.48 .46* .38‘
(Objective Substitutability)

4.SUBS 105 0.44 0.50 -.13 .02 -.03
(Subjective Substitutability)

5.THREAT 102 91.03 51.65 .30 .26 .25 .03

(Subjective Dependency Threat)

 

.Note: Only subjective measures of dependency threat were
available, and the subjective measure of substitutability
was dropped from further analyses previously.

' p<.05

BULJORS=Chances of the best home run hitter going to the
major leagues; MINORS=Chances of the best home run hitter
being offered a minor league contract; RATEHR=Rating of the
home run hitting of the best home run hitter; HRRATIO= Ratio

0f.home runs to at bats for the best home run hitter;

R00TOTH=Square root of home runs hit by the rest of the team

 

th

tt

35

P'fl

53

There are two points to be made about Table 10. First,
the objective (HRRATIO) and subjective (RATEHR) measures of
coping with uncertainty are highly correlated, suggesting
that baseball managers are, in fact, able to make accurate
assessments of the ability of a subordinate to cope with an
important uncertainty.

Second, the objective measure of coping with
uncertainty (HRRATIO) is significantly correlated with the
measure of dependency threat, thus providing further support
for the notion that the better able a subordinate is to cope
with uncertainty, the more likely it is that the person will
have alternative career options.

To summarize the results up to this point,
investigations of the intercorrelations and dimensionality
of the various dependent measures suggested that the three e
prieti clusters are discriminable though correlated and that
each cluster is measured with four items. Investigations of
Izhe intercorrelations between and among the various measures
<>f the three independent variables suggested that these
‘variables are, to some extent, correlated with each other,
Inst that they aren't as interdependent as has been suggested
by previous studies (Hinings et al., 1974; Bartol 8 Martin,
19 89) . Results of the present study have also shown that
Iflle subjective and objective measures of coping with
lancertainty are highly correlated with each other while the
sukajective and objective measures of substitutability are

n01:. In the next section, tests of the various hypotheses

 

54
are presented.
W
e w d e endent
xeriebles
Table 11 presents the correlations between the
objective and subjective measures of the three independent

variables and the three dependent variables.

Table 11

Getteiations 0; Measures of the Three Independent Variables

55

 

gitn Meeentee e: tne Three Dependent Veriables
Objective Dependent
Measures Va '21 es

Coping
Substitute

Subjective
M2§§EI§§
Coping
Substitute
Dependency

Threat

Offensive

.06

-.09

-010
.08

-.04

Defensive

.11

-.12

-007
.14

.19

-.05

.00

.12

Quality of
Practice
.09

.10

 

' p<.10

 

 

 

56

The correlations presented in Table 11 are relatively
low and, with one exception (Dependency Threat/Defense),
nonsignificant, suggesting that dependency threat has more
of an impact on managerial decisions than either coping or
substitutability. Also, all of the correlations involving
the objective measures are in the anticipated direction,
with the correlations involving substitutability being
negative and the correlations involving coping and
dependency threat being positive. Because correlations
between the subjective measures of coping and
substitutability and the dependent variables are negative,
and because this is inconsistent with the hypotheses of the
present study, only the objective measures of these
variables are used in subsequent analyses. Finally, these
correlations suggest that this set of data do not provide
support for hypotheses A. and B. of the present study. All
of the hypotheses will be further investigated using
hierarchical regression.

Mietatcnicai tegtessions

Hierarchical regressions were used to investigate 1.)
the relationships between power and coping,
substitutability, and dependency threat, 2.) the incremental
validity of the three first-order interactions over their
main effects, and 3.) the incremental validity of the
second-order interaction. These regressions were performed
using only the objective measures of coping and

substitutability as the correlations in Table 11 indicated

57
that relationshps with subjective measures were in a
direction opposite to that hypothesized. Table 12 displays

the results of this examination.

58
Table 12
Miezezenieei Begteeeiene e: Intee erendent Variables on
' st't abi it De endenc

Threst1_snd_1heir_Interaetiens

 

pependent Variabies

 

Objective Qfifienee Deienee Btactice

Measures 82 Beta 83 Beta 3? Beta

Step 1

COPING .004 .06 .011 .11 .009 .09

THREAT .001 -.04 .038‘ .21 .016 .13

SUBST. .014 -.13 .032* -.19 .021 -.16
.019 .081* .046

Step 2

1 x 2 .030‘ .66 .036* .72 .002 .15

1 x 3 .007 -.33 .000 .08 .006 .30

2 x 3 .013 .59 .000 -.07 .002 -.25
.050 .036 .010

Step 3

1.x 2 x 3 .024 1.01 .002 .28 ..003 .35

 

p<.10

59

Table 12 contains changes in R2 and Beta-weights for
each of three steps in the three hierarchical regressions.
The results in this table provide support for the effects of
substitutability (Hypothesis B), dependency threat
(Hypothesis D), and the interaction between coping with
uncertainty and dependency threat (Hypothesis E) on power.
These findings are discussed in more detail below. Further
analyses were performed to determine the nature of the
dependency threat/coping interaction. In the group of
subjects above the mean on dependency threat, the rz‘between
the objective measure of coping (HRRATIO) and the Offensive
dependent variable was .048, and the :3 between the
objective measure of coping and the Defensive dependent
variable was .072. In the group below the mean on dependency
threat, the relationships for the same variables were .015
and .029 respectively, suggesting that coping with
Iincertainty leads to playing time in spite of offensive and
ciefensive deficiencies only when dependency threat is high
(Hypothesis E). Plots of these interactions (Figures 2 and
:3), however, were inconsistent with the a.priori hypothesis
Iregarding this interaction (Cohen 8 Cohen, 1983).
Specifically, while the relationships between coping with
inacertainty and power for the high dependency threat group
were positive as expected, the same relationships for the
low dependency threat group were negative, not zero as
expected. Possible explanations of these findings are

discussed below.

 

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Discussion
masses

The first three hypotheses of the present study were
that there would be significant main effects for coping with
uncertainty, substitutability, and dependency threat. The
main effect for coping with uncertainty was not significant
for any of the three dependent variables, suggesting that
coping with uncertainty alone does not lead t0 influence
over managerial decisions. This finding is in contrast to
the findings of Hinings et al. (1974) and to the hypotheses
of the present study, but is in line with comments made by
several of the coaches that participated in this study,
specifically, that number of home runs seldom if ever
provides enough information to make judgments about starting
lineups.

The main effect for substitutability was significant
for the Defensive dependent variable. This finding was in
line with the findings of Hinings et al. (1974) and suggests
‘that a player who has a monopoly on the ability to hit home
runs will be allowed to play in spite of defensive
deficiencies. The main effect for dependency threat was
also significant for the Defensive dependent variable. This
finding was in line with the findings of Bartol 8 Martin
(14989) and suggests that a player with other career options

will be allowed to play in spite of defensive deficiencies.

Neither substitutability nor dependency threat had a

62

63
significant effect on the Offensive or Practice quality
dependent variables.

The fourth hypothesis of the present study was that
substitutability would moderate the relationship between
coping with uncertainty and power. This interaction term
was not significant for any of the dependent variables,
suggesting that the effect of coping with uncertainty does
not depend on the extent to which there are other team
members who can cope with the same uncertainty. It would
appear, instead, that the effect of coping with uncertainty
depends upon the level of dependency threat.

The fifth hypothesis of the present study was that
dependency threat would moderate the relationship between
coping with uncertainty and power. This interaction term
was significant for both the Offensive and Defensive
dependent variables, suggesting that the effect of coping
with uncertainty depends on the extent to which a player has
other career options. Specifically, a player who hits home
:runs and has alternative career options would be allowed to
start in spite of deficiencies in defensive and offensive
Play. This finding also sheds light on the mechanisms
through which the relationships found by Bartol 8 Martin
( 1989) work. Specifically, dependency threat affects the
dePendence-power relationship by affecting components of

dependence such as coping with uncertainty. The plots of
these interactions, however, were not in the form predicted

in the hypotheses of the present study. For those coaches

64
whose best home run hitter was below the mean on dependency

threat, the relationship between coping with uncertainty and

power was negative. In other words, within this group of

subjects, as the number of home runs increased, influence
over managerial decisions decreased. Initially, this

finding is counterintuitive, but there is a possible

explanation. These negative correlations could reflect a
halo effect for home run hitters. But this halo effect may
sometimes be overshadowed by other considerations.

As was mentioned in the introduction section of this
paper, a baseball team has many of the same characteristics
as any other work situation. There are managers who

supervise subordinates who perform work that the managers

cannot perform themselves. As such, baseball managers make

the same kinds of rating errors that any other manager can

be expected to make. One of these potential errors is halo

error. With regard to home run hitters, a baseball manager
may form a general impression about a player from one of the
:more salient aspects of his performance: home run hitting.
So, the manager may see a player hit many-home runs and
exPect that player to be talented in all aspects of the

game. As the number of home runs increases, so would

expectations. This, in turn, should lead to higher

Standards for the player in question. So, as the number of

home runs increases, the extent to which a manager would
e"‘Dect and allow deficiencies in other areas should

de<21'ease. This would explain the negative correlation

65
between coping and managerial decisions for the low
dependency threat group. As I suggested above, however,
this might change when there are other considerations. When
an external threat to the very existence of the relationship
between a manager and a player appears (in this case, the
possibility of becoming a professional baseball player), the
dynamics of the superior-subordinate relationship can be
expected to change. Specifically, an external threat might
force a manager to be more lenient with a player who copes
with an important uncertainty in an attempt to counteract
the lure of the threat. As the ability of the player to
cope with uncertainty increases, the manager could be
expected to be more lenient (i.e., to allow the player to
start in spite of deficiencies). Future research might
examine changes in the relationship between coping with
uncertainty and influence over managerial decisions as
dependency threat changes. It may be that this relationship
would be negative before dependency threat exists, but as
dependency threat increases, the relationship would become
positive.

Finally, although no hypotheses were made with respect
t£> the second-order interaction term were presented, this
term was tested and found to be nonsignificant for all three
dependent measures.

Overall, these results suggest that coaches see their

players as occupying roles and that these roles, in order to

be fulfilled, demand certain types of behavior. These

66
results suggest that players who monopolize the ability to
hit home runs, and players who hit a large number of home
runs and have alternative career options are not expected to
contribute as much defensively as are those who hit fewer
home runs. Anyone who is reasonably familiar with baseball

can think of many players who fit this description.

tio

There are several possible limitations to this study
that should be discussed. First, poor return rate (34%)
from a relatively small pool of subjects (approximately 340
Division 1 and 2 baseball programs) resulted in small sample
size which, in turn, led to the use of p<.10 in the
regressions. These regressions did, however, provide
support for several a prioti hypotheses and replicated some
previous research results. Nevertheless, a larger sample
size would have been desirable.

Second, the subjective measure of substitutability
(SUBS) did not correlate significantly with either the
objective measure of substitutability (ROOTOTH) or the
dependent variables, thus failing to provide a useful
alternative measure of substitutability. This item,
however, may be conceptually different from the objective
Measure in that the subjective measure asks for the number
of 11% who could replace the home run hitting of the

best home run hitter while the objective measure, number of

home runs hit by the rest of the team, is more in line with

the conceptualization of substitutability as a team-level

67
construct that was adopted the present study. Coaches may
not be able to conceptualize of substitutability of home run
hitters as an individual-level construct.

Another potential limitation is that hypothetical
decision items were used. However, the types of decisions
used in the present study are decisions that a manager must
make every day, i.e., weighing the importance of various
factors and comparing players with respect to these factors.
Also, pilot testing of the questionnaire showed that high
school and college coaches were able to understand and
relate to the questions that were asked, and survey
respondents reported no difficulty in completing the
questionnaire.

The final possible objection is that the measures of
dependency threat may have been perceived simply as measures
of overall ability or performance. This is possible,
however, there is no logical reason for overall performance
to moderate the relationship between coping with uncertainty
and power, while the a ptiori hypothesis that dependency
threat would moderate this relationship is based on the
findings of previous research (e.g., Bartol 8 Martin, 1988,
1989) .

Wises

Future research should attempt to further examine the
dYnamics of the interactions between managers and
subordinates and how these dynamics might change over time.

Specifically, the interaction effects found in the present

68
study suggest that external influences such as dependency
threat can literally turn manager/subordinate relationships
upside down. Instead of the usual situation in which
downward power is dominant (i.e., subordinates feeling the
impact of and reacting to the power of managers), a new
situation created by dependency threat emerges in which
managers must react to the upward power of subordinates.
Longitudinal research which examines changes in the
relationships between managers and subordinates as
dependency threat changes would be most useful in achieving
this end. One possible source for such data is professional
sports.

Extensive statistics for players and teams have been
kept by most major professional athletic associations in
this country and around the world for decades. This means
that changes in objective statistics are available over
periods of many years. This could be useful for the type of
longitudinal research mentioned above. For example, the
upward power of a home run hitter could be operationalized
as the strength of the relationship between the defensive
and offensive statistics (other than home runs), and number
of innings played over the course of a season. A player

would be high in power to the extent that offensive and

 

defensive statistics fail to predict playing time.
Dependency threat could be operationalized as the amount of
time before a player becomes a free agent (a free agent in

IDImofessional baseball is allowed to sign a contract with any

tear
thal
rel;
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69
team he chooses). Using this data, it might be predicted
that coping with uncertainty (Home runs) would be negatively
related to power (the defense/playing time relationship) in
the period of time immediately following the signing of a
contract (Low dependency threat). This would be due to the
high expectations that the manager has for the player that
result from halo error. However, this relationship would
become positive over time as the end of the contract
approaches and a manager feels pressure to appease a player
whose career options are about to expand. In this way,
archival data from athletic teams would provide the data
necessary to the investigation of variables that are

instrumental to theories of power.

References

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W. 14. 105-113 .

Blackburn, R.S. (1981). Lower participant power:
Toward a conceptual integration. Academy of
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Crozier, M. (1964). The bureaucratic phenomenon.

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Pfeffer, J. 8 Salancik, G.R. (1974). Organizational

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York: McGraw-Hill.

 

APPENDIX A

In your opinion, which region of the United States do you
think produces the best baseball players?

A. Midwest
B. East

C. South
D. West

Please give a few examples and explain why you think this
is? ‘

1. Please fill in the following stats for the peet_nene_;nn
e o o . The defensive position should
refer to the position he occupied most often.

 

 

 

 

BONERS .AT BATS BATTING STRIXEOUTS SPOT IN
AVG. ORDER
ASSISTS ERRORS PUTOUTS HIT INTO DEFENSIVE

DOUBLE PLAY POS. (DH?)

 

 

 

 

 

 

 

 

2. Please indicate the number of home runs hit by your team
overall. ans

3. Please indicate the number of home runs hit by your
second best home run hitter. ERs

t t t or e to o
m tt .

73

74

4. On the scale below, please rate your best ER hitter with
respect to his home run hitting performance.

1.0.0.020.0I03..00.4.00005000006000007

Very Poor Fair Excellent
Performance Performance Performance

5. Please estimate how high the player's number of errors
would have to have been before he would be removed from the
starting lineup for the start of the "second half" of the

season (Position viii De teten into neeount to; £11
gegeneiye_gneetienet An example is in the instructions, and
remember, Mp_Dfl). '

( e made 1 o d la

the "second half" f the season t made 0
Isn1se2ldn1t1_s2.122:.snsser_seuld_bs_29-i 51:22:

 

6. Please estimate how low the player's number of putouts
would have to have been before he would be removed from the
starting lineup for the start of the "second half" of the
season. If putouts don't matter, put 0. Putouts

7. Please indicate how low the player's batting average
would have to have been before he would be removed from the
starting lineup for the start of the "second half" of the
season (In other words, all other things being equal, what
is the lowest average you would let him start with)

AVG.

8. Please indicate how high the player's number of
strikeouts would have to have been before you would move him
to or below the fifth spot in the batting order for the
start of the "second half" of the season . If he already is
below the fifth spot, How high would his strikeouts have to
have been before you would move him down lower in the
batting order

e t on t v
where he t he struck out 50 t s u we
do 0 o 0 Rs.

75

9. Please indicate how high the player's number of
strikeouts would have to have been before you would remove
him from the starting lineup for the start of the "second
half" of the season

e e c 0 es o wo et
la t e o he
AW
5;) re.

10. Please indicate how high the number of times the player

hit into double plays would have to have been‘before you

would move him to or below the fifth spot in the batting

order for the start of the "second half" of the season . If

he already is in or below the fifth spot, How high would the

number of times he hit into double plays have to have been 1
before you would move him down even lower in the batting

order. If it doesn't matter, put 0.

t t 6 doub wo
iegze ti; where De is. but i; he tit inte 1;. yon wonig Deep

9:1 HDPS.

     

11. Please indicate how high the number of times the player
hit into double plays would have to have been before he
would be removed from the starting lineup for the start of
the "second half" of the season. HDPs.

12. Please indicate how low the player's batting average
would have to have been before he would be moved to or
below the fifth spot in the batting order for the start of
the "second half" of the season. If he already is in or
below the fifth spot, now low would his average have to go
before he would be moved lower in the order? AVG

13. Please estimate how many players there were on the team
that could do a good job of substituting for the player with
respect to home run hitting.

 

76

14. Please indicate how low the player's number of assists
would have to have been before you would remove him from the
starting lineup for the start of the I'second half" of the
season (If assists don't matter, put 0.)

W

t e "s ond ' o e t o d
32r_12n_!9E1QELEs__£21.!!!I_§n!!!£_!9!1§_h!
gel, Assists.

 

15. Please indicate how low the player's number of home runs
would have to have been before you would move‘him to or
below the fifth spot in the batting order for the start of
the "second half" of the season . If he already is in or
below the fifth spot, now low would his home runs have to
have been before you would move him down even lower in the
batting order? HRs

16. Please indicate how low the player's number of home runs
would have to have been before he would be removed from the
starting lineup for the start of the "second half" of the
season. HRs

12: the remaining items. gate yep; best ER Ditto; with
e ect to he characte tic entioned n each tam
o tin an here a on th c rov ded or each t
ex Is on e t low o wou rate

W

17. His overall defensive performance.

10.....20.C.03.0.0.4.00005000006000007

Very Poor Fair Excellent
Performance Performance Performance

77

18. Please estimate how low the player's defensive
performance would have to have been before he would be
removed from the starting lineup for the start of the
"second half" of the season.

-?_- |°1'— , 31. -'~ '- °1~11°11.;11°— w - , .7 then-o1
et ormanc

WW
0 ' eco s o ou woul

' e If- -14 e) A ‘ ‘ oLeA __ 01—. _.’

222.11

10.0.002000003..000‘000005000006000007 ‘

Very Poor Fair Excellent

Performance Performance Performance

19. The extent to which he took his batting practice
seriously (as seriously as he takes it in his games.)

1.0.0.02000003000.0‘000005000006000007

Not very Fairly As serious
serious serious as games

20. Please estimate how low the player's seriousness in
batting practice would have to have been before he would be
removed from the starting lineup for the start of the
"second half" of the season. If it doesn't matter, put 1.

gnnnpleg it Me hag teen 'Pairly;8erione'. you wonig leave
0 a but f he ad "not V6 So one" he wo
emov m.t e start linen o the tart of the
' econd N o e season. on so u

WW

1.0.0.020...03..0.0‘00000500000‘000007

Not very Fairly As serious
serious serious as games

21. His overall offensive performance.

1.0.0.0200000300000‘...0.5.0.006000001

Very Poor Fair Excellent
Performance Performance Performance

78

22. Please estimate how low the player's overall offensive
performance would have to have been before he would be
removed from the starting lineup for the start of the
"second half" of the season.

1.0.0.020....3000004000005000006.0.0.7

Very Poor Pair Excellent
Performance Performance Performance

23. The number of times he was allowed to swing at a pitch
with a 3-0 or 3-1 count relative to the rest of the team.

 

1.0.0.020000030000040000.5.00.06000007
Less than Average More than
anyone else anyone else

24. How important the player's home run hitting was to the
team.

1.0.0.020...03.0.004000005000006.0.0.7

not very Fairly _ Extremely
important important important

25. The extent to which he tries to keep in shape.

1.0.0.020.00.3.0000‘00000500.0.6.0000,

Doesn't Try Tries Tries Very,
very Bard Fairly Hard Hard

26. Please estimate how low the player's efforts to keep in
shape would have to have been before he would be removed
from the starting lineup for the start of the "second half"
of the season. If it doesn't matter, put 1.

1.0.0.020....3.0.00‘000005000006000007

Doesn't Try Tries Tries Very
Very Eard Fairly Eard Eard

 

79

27. Please rate the player with respect to his speed.

1......2.....30....‘OIOOOSOO...‘OOO..7
not Very Fairly Very
Fast 'Fast Fast

28. Estimate how low the player's speed would have to have
been before you would move him to or below the fifth spot in
the batting order for the start of the "second half" of the
season . If he already is in or below the fifth spot, now
low would the player's speed have to have been before you
would move him down even lower in the batting order? If it
doesn't matter, put 1.

10.000020.00.30....‘00000500.0.6.0000?
not Very Fairly Very
Fast Fast Fast

29. Please estimate how low the player's speed would have to
have been before before he would be removed from the
starting lineup for the start of the "second half" of the
season. If it doesn't matter, put 1.

1.0.0.020...03.....‘000005000.060.000?
Not Very Fairly Very
Fast Fast Fast

30. The extent to which he came to practice late or left
early.

1eeeeee2eeeee3eeeee‘eeeee5eeeee‘eeeee7

Almost Sometimes Almost
never always

31. Please estimate how often the player would have to have
come to practice late or leave early before he would be
removed from the starting lineup for the start of the
"second half" of the season.

1......2.....3...0.‘00.0.5.....‘.00.07

Almost Sometimes Almost
never always

 

 

32. The extent to which he took practice in general
seriously. (as seriously as games)"

10000002.....3.00.0‘0.00050000.‘00.007

not very Fairly As serious
serious serious as games

33. Please estimate how low the player's seriousness in
practice in general would have to have been before he would
be removed from the starting lineup for the start of the
"second half" of the season.

1eeeee2eeeee3eeeee‘eeeeeSeeeee‘eeeee?

not very Fairly As serious
serious serious as games

34. The extent to which he got to balls hit in his
direction.

1.000002000003....0‘00...s..00.‘000.07

Only Balls Gets To Gets To
Hit At Him. Gome Almost All

35. Please estimate how low the player's ability to get to
balls would have to have been before he would be removed
from the starting lineup for the start of the "second half"
of the season. If it doesn't matter, put 1.

10.00.02000.03..0.0‘.00005.....‘...0.7

Only Balls Gets To Gets To
Hit At Him. Bone Almost All

36. The extent to which the player was willing to take time
to help his teammates.

1eeeeee2eeeee3eeeee‘eeeeeSeeeee‘eeeee7

Almost Sometimos Almost
Never Always

 

 

81

37. Please estimate how low the player's willingness to help
would have to have been before he would be removed from the
starting lineup for the start of the "second half" of the
season. If it doesn't matter, put 1.

1eeeeee2eeeee3eeeee‘eeeeeSeeeee‘eeeee?

Almost Sometimes Almost
Never Always

38. Please rate the player on the extent to which he has a

good arm. “
1.00.0020...03..0.04.00.05.00006000007
not Very Fairly Very
Strong Strong Strong

39. Please estimate how had his arm would have to have been
before he would be removed from the starting lineup for the
start of the "second half" of the season. If it doesn't
matter, put 1.

1.0.0.020...03.000.400.005...0.6.00.0?
Not Very Fairly Very
Strong Strong Strong

40. The probability that the player could get a minor league
contract right now. keep in mind that there is still the
"second half" of the season to go.

o...1o....2°....3o....‘o....so.0..‘o....7o....ao....9°...1°o
No Chance Of About a 50/50 ne Could Definitely
Getting A Contract Chance Get A Contract

41. The probability that the player could make it to the
major leagues someday.

Oeee10eeee2°eeee3°eeee‘OeeeeSOeeee‘Oeeee7°eeee8°eeee9°eee1°°

No Chance About a 50/50 Be Could Definitely
of Raking It Chance Make It

In!!! ‘00 FOR IOUI.EBLP. I! IS GRIIILI IPPflBCILIBD!

 

 

Appendix E

 

20. On the scale below, please rate the player with respect
to overall offensive performance.

10000002000003.000040000050....‘.00007

Very Poor Fair Excellent
Performance Performance Performance

26. Please rate the player with respect to his speed.

1.0.0.020.0.030....‘0000050000.6.0000?
Not Very Fairly Very
Fast Fast Fast

m. o s
5. Please indicate how low the player's batting average
would have to go before he would be moved below the fourth
spot in the batting order for the start of the ''second half"
of the season. If he already is below the fourth spot, now
low would his average have to go before he would be moved
lower in the order? (Example: If he was in the fourth spot
and batted .250, you would leave him there, but if he had
been below .240, you would move him down in the batting
order. So, your answer would be .239. .

6. Please indicate how low the player's batting average
would have to have been before he would be removed from the
starting lineup for the start of the "second half" of the
season (In other words, all other things being equal, what
is the lowest average you would let him start with)

 

7. Please indicate how high the player's number of
strikeouts would have to have been before you would move him
below the fourth spot in the batting order for the start of
the "second half" of the season . If he already is below
the fourth spot, How high would his strikeouts have to have
been before you would move him down lower in the batting
order (Example, If he struck out 30 times, you would leave
him where he is, but if he struck out 50 times, you would
bump him down. So your answer would be 50.) .

 

82

 

 

 

83

9. Please indicate how high the player's number of
strikeouts would have to have been before you would remove
him from the starting lineup for the start of the "second
half" of the season (Example, If he struck out 40 times, you
would let him start the "second half" of the season, but if
he struck out 45 times, you wouldn't. So, you would answer
would be 45) .

10. Please indicate how high the number of times the player
hit into double plays would have to have been before you
would move him below the fourth spot in the batting order
for the start of the "second half" of the season . If he
already is below the fourth spot, How high would the number
of times he hit into double plays have to have been before
you would move him down even lower in the batting order
(Example, If he hit into 6 double plays, you would leave him
where he is, but if he bit into 15, you would bump him down.
So, your answer would be 15.)

 

11. Please indicate how high the number of times the player
hit into double plays would have to have been before he
would be removed from the starting lineup for the start of
the "second half" of the season.

 

17. On the scale below, please rate the player with respect
to the number of times he was allowed to swing at a pitch
with a three ball count relative to the rest of the team.

Example: He was allowed to swing at more three-ball pitches
than anyone else.

10....020.00.30.00040000050000.60.0007
Less than Average nore than
anyone else anyone else

21. On the scale below, please estimate how low the player's
overall offensive performance would have to have been before
he would be removed from the starting lineup for the start
of the "second half" of the season.

Example: If his overall offense was "Excellent" then you
would leave him alone, but if his offense was only "Fair",
he would be removed from the starting lineup for the start
of the "second half" of the season. So you would put a mark
somewhere near the 4.

10.....2.....3.....‘.....5.....‘0....7

Very Poor Fair Excellent
Performance Performance Performance

 

84

27. Please estimate how low the player's speed would have to
have been before you would move him below the fourth spot in
the batting order for the start of the "second half" of the
season . If he already is below the fourth spot, How high
would the number of times he bit into double plays have to
have been before you would move him down even lower in the
batting order?

Example: If he were a little less than "Very Fast" (about a
6), you would leave him where he is, but if he were a little
less than "Fairly Fast", you would move him down. So, you
would put a mark somewhere near 3.

1.0.00.2000.03..00.40.00.5000006000007 '
not Very Fairly Very
Fast Fast Fast

28. Please estimate how low the player's speed would have to
have been before before he would be removed from the
starting lineup for the start of the "second half" of the
season.

Example: If he were "Fairly Fast", you would leave him in
the starting lineup, but if he were "not Very Fast", he
would be removed from the starting lineup for the start of
the "second half" of the season. So, you would put a mark
somewhere near 1.

1.0...0200..0300...‘.00.05.....‘...0.7

Not Very Fairly Very
Fast Fast Fast
ence t def d an ant v as

14. On the scale below, please rate the player referred to
in question 1 with respect to his overall defensive
performance. Mark your rating anywhere along the line.

1......2..0..3.0...‘.....s.....‘.....7
Very Poor Fair Excellent
Performance Performance Performance

26. Please rate the player with respect to his speed.

1...0.02.....3.....‘.....s...0.6....07
Not Very Fairly Very
Fast Fast Fast

 

 

85

33. Please rate the player with respect to his ability to
get to balls hit in his direction.

1.0.0.020....3.0000‘..0005.....‘00.007

Only Balls Gets To Gets To
Sit At Eim Some Almost All

37. Please rate the player on the extent to which he has a
good arm.

1.00.0020...030.00.400.005000.06.0000?
Not Very Fairly Very
Strong Strong Strong

D2E2IQQIE..§S§!I££.IQI.§2I£B§!

4. Please estimate how high the player's number of errors
would have to have been before he would be removed from the
starting lineup for the start of the "second half" of the
season (An example is in the instructions).

 

9. Please indicate how low the player's number of assists
would have to have been before you would remove him from the
starting lineup for the start of the "second half" of the
season (Example, If he made 40 assists, you would let him
start the "second half" of the season, but if he only made
20, you wouldn't. So, your answer would be 20)

 

12. Please estimate how low the player's number of putouts
would have to have been before he would be removed from the
starting lineup for the start of the "second half" of the
season.

 

15. On the scale below, please estimate how low the player's
defensive performance would have to have been before he
would be removed from the starting lineup for the start of
the "second half" of the season.

Example: If his defensive performance were "Fair", then you
would let him start, but if he had "Very Poor Performance",
then he would be removed from the starting lineup for the
start of the "second half" of the season. So, you would put
your mark somewhere near the 1.

1.0.00.20...03.00.040.00050000.60.0007
Very Poor Fair Excellent
Performance Performance Performance

 

 

28. Please estimate how low the player's speed would have to
have been before before he would be removed from the
starting lineup for the start of the ”second half" of the
season.

Example: If he were "Fairly Fast", you would leave him in
the starting lineup, but if he were "not Very Fast", he
would be removed from the starting lineup for the start of
the "second half" of the season. So, you would put a mark
somewhere near 1.

1......2.....3.....‘.....5.00..‘.O...7
Not Very Fairly Very
Fast Fast Fast -

34. Please estimate how low the player's ability to get to
balls would have to have been before he would be removed
from the starting lineup for the start of the "second half"
of the season.

 

Example: If he got to some balls, then you would let him
start, but if he only got to balls hit at him, then you
wouldn't let him start. So, you would put a mark somewhere
near 1.

1eeeeee2eeeee3eeeee‘eeeee5eeeee‘eeeee7

Only Balls Gets To Gets To
Sit At Eim Some Almost All

38. Please estimate how bad his arm would have to have been
before he would be removed from the starting lineup for the
start of the "second half" of the season.

Example: If his arm were "Fairly Strong", you would let him
start, but if his arm were "Not Very Strong", then you
wouldn't let him start. So, you would put a mark somewhere
near 1.

1eeeeee2eeeee3eeeee‘eeeee5eeeee‘eeeee7

Not Very Fairly Very
Strong Strong Strong

 

MW

18. Please rate the player on the extent to which he took
his batting practice seriously (as seriously as he takes it
in his games.)

1......2.....3..0..‘.0...s..0..‘..00.7 ’

Not very Fairly As serious
serious serious as games

O7

24. Please rate the player on the extent to which he tried
to keep in shape.

1.00.0.2.0.0.3....0‘.....5.....‘....07

Doesn't Try Tries Tries Very
Very Eard Fairly Eard hard

29. Please rate the player on the extent to which he came to
practice late or left early.

1eeeeee2eeeee3eeeee‘eeeeeSeeeee‘eeeee?

Almost Sometimes Almost
never always

31. On the scale below, please rate the player referred to

in question 1 on the extent to which he took practice in
general seriously. (as seriously as games)

10.0.0020....3.....‘.....50.000‘...007

not very Fairly As serious
serious serious as games
t e o

19. Please estimate how low the player's seriousness in
batting practice would have to have been before he would be
removed from the starting lineup for the start of the
"second half" of the season.

Example: If he had been "Fairly Serious", you would leave
him alone, but if he had been "Not Very Serious", he would
be removed from the starting lineup for the start of the
"second half" of the season. So, you would put your mark
somewhere near 1.

1......2.....3.....‘.....s.....‘.....7
not very Fairly As serious
serious serious as games

25. Please estimate how low the player's efforts to keep in
shape would have to have been before he would be removed
from the starting lineup for the start of the "second half"
of the season.

Example: If he tried a little harder than "Fairly Hard" to
keep in shape (about a 5), you would leave him alone, but if
he didn't try very hard, he would be removed from the
starting lineup for the start of the "second half" of the
season. So, you would put a mark somewhere near 1.

1......2.....3.....‘.....5.....‘.....7
Doesn't Try Tries Tries Very
Very Eard Fairly Eard hard

A
I‘m

 

 

30. Please estimate how often the player would have to have
come to practice late or leave early before he would be
removed from the starting lineup for the start of the
"second half" of the season.

Example: If he left early or came late "Sometimes", then you
would leave him alone, but if he "Almost Always" came late
or left early, then you would remove him. So, you put a
mark somewhere near 7.

10.000.20.000300.00‘0000.s....0‘000007

Almost Sometimes Almost

never always

32. On the scale below, please indicate how low the player's
seriousness in practice in general would have to have been
before he would be removed from the starting lineup for the
start of the "second half" of the season.

Example: If he was "As Serious as Games", you would let him
start, but if he was only "Fairly Serious", you wouldn't let
him start. So, you put a mark somewhere near 4.

leeeee2eeeee3eeeee‘eeeeeSeeeee‘eeeee?

not very Fairly As serious
serious serious as games

.‘g

F?

 

 

APPENDIX C

MW
(Read Carefully!)

The purpose of this study is to discover how important home
runs are to you. Kore specifically, to what extent will a
player's ability to hit home runs make up for deficiencies
in other areas? I am not claiming that home run hitters are
necessarily bad defensive players or slackers in practice.
I'm just saying that, all other things being equal, a player
that hits home runs can be a starter even if, for example,
he isn't a great defensive player.

All of the following questions except for questions 2 and 3
refer to the player on your team who hit the most homers
during the season that just ended. If your season is not
yet over, then use the person who has the most homers up to
this point. If there is a tie for the most homers, then
take your pick.

Some of the 41 questions are simply performance questions
while others are hypothetical questions like, How high would
the player's number of errors have to have been before he
would be removed from the lineup? These questions should be
answered as if the baseball season that just ended were only
the first half of the season and you were making lineup
decisions for the second half. They should also be answered
as if there were no DE rule (You can't make a bad defensive
player DE, you either bench him or not). For example, if
your best home run hitter was the left fielder and you
answered the question, "Please rate the player on the extent
he took batting practice seriously" with a rating of 6, and
you would pull him from the lineup now if he had been a 2
with respect to his seriousness in batting practice, then
you would mark 2 on the question that asks you how low the
player's seriousness in batting practice would have to have
been before you would remove him from the starting lineup
for the "second half" of the season.

If your best home run hitter was the Designated Eitter most
of the time, then please indicate this in question #1 and
leave questions 4, 9, 12, 14, 15, 33, 34, 37, and 38 blank.

If any of this is unclear, there are examples for many of

the questions. Mun—tw- I do not

want to suggest what your answer should be. I only want to
know what 129 think.

 

Finally, it may be that some of the questions don't really
apply to you. For example, you may not be terribly
concerned with how seriously a player takes batting
practice. If this were the case, then you would answer the
question "Please estimate how low the player's seriousness
in batting practice would have to go before you would sit

him out for at least one game" with the lowest possible
rating.

   

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