Resource-Allocation Behavior

244 Pages·2003·6.8 MB·English

by  Harvey J. Langholtz

RESOURCE-ALLOCATION
BEHAVIOR
RESOURCE-ALLOCATION
BEHAVIOR
by
Harvey J. Langholtz
Antoinette T. Marty
Christopher T. Ball
The College of William and Mary
Williamsburg, Virginia
Eric C. Nolan
University of California, Davis
Davis, California
SPRINGER SCIENCE+BUSINESS MEDIA, LLC
Library of Congress Cataloging-in-Publication Data
Resource-allocation behavior / by Harvey J. Langholtz [et al.]
Langholtz, Harvey J., 1948
p.cm.
Includes bibliographical references and indexes.
ISBN 978-1-4613-5408-6 ISBN 978-1-4615-1131-1 (eBook)
DOI 10.1007/978-1-4615-1131-1
I. Strategic planning, 2. Resource allocation. I. Langholtz. Harvey J..
II. Marty, Antoinette T. III. Ball, Christopher T.. IV. Nolan. Eric C.
s
HD30 .28 .R464 2002
153.8/3—dc21
2002030087
A C.I.P. Catalogue record for this book is available
from the Library of Congress.
Copyright © 2003 by Springer Science+Business Media New York
Originally published by Kluwer Academic Publishers in 2003
Softcover reprint of the hardcover 1st edition 2003
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Printed on acid-free paper.
Contents
Chapter 1 1
An Introduction to Resource-Allocation Behavior
Chapter 2 9
The Optimal Model: Linear Programming
Chapter 3 19
Resource-Allocation Behavior
with Time, Three Dimensions, and Minimums
Chapter 4 31
Previous Research:
Behavioral Models Follow Normative Models
Chapter 5 37
Resource-Allocation Behavior
with Various Levels of Information
Chapter 6 63
Resource-Allocation Behavior
in Harsh and Benign Environments
VI
Chapter 7 89
Resource-Allocation Behavior
when Gains and Losses are Possible
Chapter 8 107
Resource-Allocation Behavior
when the Objective Function Changes
Chapter 9 145
Resource-Allocation Behavior
in Commonplace but Complex Tasks
Chapter 1( ) 179
Cognitive Strategies for Resource-Allocation Behavior
Chapter 11 201
Distributive Justice in Resource-Allocation
Chapter 12 235
Conclusions and Future Areas to be Mapped
Index 243
Chapter 1
AN INTRODUCTION TO RESOURCE
ALLOCATION BEHAVIOR
How do people make decisions about the allocation of resources? How well
or how poorly can people make such decisions? How efficiently can people
allocate resources? What are some of the different situations under which people
make resource-allocation decisions, and will performance vary between
situations? What are some of the cognitive strategies people use to make
resource-allocation decisions? Is there a normative standard to which people's
performance can be compared in resource-allocation situations?
In the 12 chapters of this book we will attempt to address these questions
and see how people make resource-allocation decisions. Of course it must be
recognized at the outset that such an initial investigation of the topic of
resource-allocation behavior can only explore some of preliminary topics, and
the results of this preliminary investigation can only be a short list of answers
with a longer list of topics for further research. But it is our goal here to build
an initial foundation, answer some preliminary questions, propose some possible
models and approaches for the investigation of resource-allocation behavior,
and suggest what broad areas need to be investigated further.
What is Resource-Allocation Behavior, Really?
Resource-allocation decisions are ubiquitous, and resource-allocation
behavior is continuous. How will we divide our time between the various
activities of daily life? How much of today will be spent on working, e-mails,
phone calls, meetings, reading, writing, relaxing, exercising, eating, and
2 Chapter 1
sleeping? How much time will we allocate towards our own goals and how
much will we provide in service to causes we value? How much of our financial
budget will we allocate to food, clothing, shelter, education, recreation, travel,
savings, health, charity, and a long list of other priorities? And even within any
one of these broad categories, how much of the budgeted money will be
allocated to each individual item within that category? And will we consume
our resources evenly across time, will we hoard them for future use, or will we
squander them early in a time period?
Resource-allocation decisions are any decisions in which people make
judgments about how they will allocate resources. Resource-allocation behavior
is the outward, observable behavior in which people act upon their
resource-allocation decisions. While the most common resource-allocation
decisions are typically made about time and money, these two resources are in
no way the only resources about which we make resource-allocation decisions.
Often, the actual application in real-world situations will take forms other than
time and money (i.e., how to mix chemicals in an industrial setting, who to hire,
which meetings to attend, and where to eat). Chemicals, employees, meetings,
and food will be the specific resources to be allocated, but in many cases these
resource-allocation decisions are ultimately decisions about the allocation of
time or money, or both.
There is a normative model for calculating the optimal solution to
resource-allocation problems. This optimal solution can be calculated when the
costs of the resources are known, when it is understood how the resources may
be combined to reach an objective, and when it is possible to place a value on
reaching the objective. The method for calculating the optimal solution to such
resource-allocation problems is known in the literature of Operations Research
(or Management Science) as Linear Programming (LP), (Dantzig, 1963). LP
was developed in the late 1940's as a method for determining optimal solutions
to large-scale logistical or scheduling problems, and since Dantzig's seminal
book on the topic, there have been hundreds of other books and perhaps
thousands of joumal articles on the topic. Chapter 2 will provide an introduction
to LP, but for a more thorough discussion of the topic, the reader is referred to
any of the texts used to teach Operations Research or Management Science, and
typically available in any college bookstore for use management or math
classes.
While it may initially seem unusual to be conducting research on behavior
as compared to a model of Operations Research, it is not LP that is being
AN INTRODUCTION TO RESOURCE-ALLOCATION BEHAVIOR 3
studied here, but rather people's decision-making behavior as compared to LP.
This is no different from the predominance of current publications in the field
of decision theory that examine behavior in what are fundamentally Bayesian
environments of choice. In such Bayesian environments, the decision maker has
a choice of two or more alternatives. Often the decision is made with a
knowledge of the possible outcomes and associated probabilities. Decision
making in a Bayesian environment will typically be discussed in the same
Operations Research texts that teach LP, but Bayesian topics will be discussed
in the preliminary chapters and serve as an introduction to the more complicated
areas of Operations Research that include LP, Stochastic Processes, Markov
Chains, and other models.
This Book Is about Behavior, Not Math
In the chapters that follow, we examine people's resource-allocation
behavior in several different resource-allocation settings. In order to do this
properly and thoroughly, we have described the resource-allocation problems
using precise LP mathematical format. This may sometimes create the
impression that this is a book about LP or math. It is not. This is a book about
behavior. But in order to study rigorously, and in order to deconstruct how
people make resource-allocation decisions in a methodological way, we must
be clear on the normative mathematical model that provides both the optimal
solution, but perhaps more importantly, a way for us to view and understand the
resource-allocation problem. In order to introduce the concept and the details
of LP, this chapter will discuss LP in general conceptual terms. Chapter 2 will
introduce LP as a mathematical model. And in Chapter 3 we will examine
various types of resource-allocation problems, both static and dynamic. For
those already familiar with LP, this may seem like a long, slow, and indirect
approach to the topic. And of course if the topic of this book were LP as a
mathematical model, it would be a long, slow and indirect approach. But since
it is anticipated that most readers of this book will be interested in
resource-allocation behavior primarily, and LP only secondarily as an optimal
model to be used as a standard against which to compare behavior, this longer
approach of examining at resource-allocation behavior in various settings will
be taken. This book is about behavior, not math.
4 Chapter 1
Different Types of Resource-Allocation Situations
There are many different types of resource-allocation situations or
resource-allocation problems. At the most basic level, they can be separated into
two categories: maximization problems and minimization problems. In
maximization problems the resources are fixed. In minimization problems the
goal is fixed.
In a maximization problem the decision maker is attempting to reach the
maximum possible level of a goal while not consuming more than a fixed
amount of resources. For example, the dispatcher for a police department is
trying to determine how to obtain the maximum number of hours of police
officers on patrol within the fixed budget for salary. Or the planner for a large
commercial airline is attempting to schedule a fleet of a fixed size in order to
offer the most possible passenger-miles. For some maximization problems it
may be more difficult to quantify benefit. For example, the physician in the
emergency room is allocating his time between incoming patients. The model
for making this resource-allocation decision may be a complex one that involves
diagnosis, prioritization, treatment, etc. But even applying LP to determine the
optimal solution to such a decision might require numerous assumptions and
stipulations. Once those assumptions and stipulations have been accepted, the
optimal solution can be calculated.
In minimization problems, the decision maker is attempting to reach a fixed
goal while consuming a minimum amount of resources. The contractor
constructing a building will seek the most economical way to complete the task
within the design specifications, but the goal is not to build a smaller building
within a fixed budget, but rather to meet a specific task while minimizing costs.
Once the airline company planner has determined the best routes to maximize
passenger-miles it will be up to the pilot to operate the jet liner in such a way as
to minimize fuel consumption.
In this book we wiIl examine only maximization problems, not because
minimization problems are not important, but for a standard approach to the
research. Certainly, for every aspect of resource-allocation behavior that we
might study in a maximization situation, we could also examine the same aspect
in a minimization situation. For a discussion of resource-allocation in
AN INTRODUCTION TO RESOURCE-ALLOCATION BEHAVIOR 5
minimization situations the reader is referred to Gonzalez, Langholtz, and
Sopchak (in press).
Chapter 3 will begin with a discussion of simple one-time
resource-allocation problems. In such problems the decision maker is given a
fixed amount of resources and determines the method of allocation that will
provide the maximum result. This resource-allocation decision is made once and
is not ongoing. An example of such a situation would be an owner of a small
fleet of oceangoing commercial fishing vessels, each with different
characteristics in terms of size, nets, etc. The fleet owner must decide where to
allocate individual boats within an expanse of ocean to fish during a 24-hour
legal opening. He must have his vessels prepositioned at specific locations at the
start of the legal opening. Once the fishing period begins, they put out their nets,
and leave them out for 24 hours, and retrieve them at the end of the 24-hour
period. His goal is to harvest the maximum amount of fish but once the decision
is made of where each boat will fish, the decision is carried out without revision.
In many cases, resource-allocation decisions are made over time, with the
decision maker having the benefit of knowing what happened during earlier
resource-allocation decisions. These are multi-cycle problems, where each
allocation represents one cycle among a series. An example of this would
include decisions about how to allocate money from the food budget and where
to shop for food or at which restaurant to eat. The decision maker knows how
much money remains in the week's food budget; he knows about the local
restaurants; and he knows how much food he has at home in his refrigerator. He
makes a decision about the next meal based at least on these factors, especially
considering how much money remains in the week's food budget and how many
days remain until the next payday. Once that allocation cycle is complete, he
can wait until the next meal, consider again how much money is left, what his
choices are, and where to eat. These allocation cycles are repeated until receipt
of the next paycheck.
In those situations where the decision maker has the option of carrying over
unused resources from one time-frame to the next (or in some cases, borrowing
against the next time-frame) the resource-allocation problem is extended.
Because carry-over (or borrowing against the future) is possible, this case is
actually one ongoing resource-allocation problem, not a series of discrete
problems. However, this should be differentiated from those cases where the
decision maker will solve a series of identical resource-allocation problems
where carry-over (or borrowing) is not permitted. Such problems would include