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Philosophy and Multiple Criteria Decision Analysis
David L. Olson, Texas A&M University
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ABSTRACT
This paper considers multiple criteria decision making in light of philosophy. It is a working draft, considering a
number of issues. The concept of rationality is reviewed, concluding that rationality varies by perspective.
Philosophical comments on expected utility are identified. The continuum between objective and subjective is
examined, concluding that subjective views are a fact of life. The influence of philosophical work on modern
business is reviewed, including the influence of rational-deductive philosophy on theory, and normative versus real
philosophical approaches. Critiques of the rational normative view are given. The complications to normative
theory arising from group aspects of decision making are discussed. Three alternative multiple criteria methods
(image theory, verbal decision analysis, and recognition-primed decision) are demonstrated as possible means of
overcoming some of the limitations of analytic-deductive approaches.
INTRODUCTION
Multiple criteria decision analysis has evolved from economic theory, applying mathematical modeling in attempts
to support decision-making involving tradeoffs. This approach has had many successes, but deals with a very
difficult problem area. It is hard to analyze many tradeoffs involved in decision making, especially in times with so
many uncertainties presented by environmental considerations, by the need to be more inclusive and consider the
desires of more groups, and when the complex systemic features of interrelated economies and businesses are
involved.
RATIONALITY
Rationality has been used as an approach applying the analytic-deductive approach of Descartes and Leibniz
(Churchman, 1971), based on the contention that there is an objective truth common to us all (Henig and Buchanan,
1996), and that therefore all truths can be deduced a priori. Rational by this strict definition would mean that
decisions were consistent with proven truths. Actually real life involves few proven truths. But analytic-deductive
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philosophy was shared by many in the developing fields of science. Modeling decision making usually begins with
a mathematical expression of the preference function of the decision-maker, a formal approach. Rational economic
decision makers are assumed to follow certain behavior patterns: they are value maximizers, always preferring more
to less, but sometimes at least at a diminishing rate on a continuous scale of value (Debreu, 1959). However, later
philosophical systems (such as pragmatism in the late 19 th century) contended that rational decisions can be reached
without definitive arguments for or against. Nozick (1993) traced an evolutionary account of rationality from
Wittgenstein through Dewey, Heidegger, and Polanyi, with the conclusion that people are not born rational. For
rational behavior is basically other people doing what we expected. And in competitive environments, this
characteristic of rationality would be fatal. Rational is a relative term. If everyone in a group (such as a conference
of academics sharing a narrow interest field) share the same Gestalt, they can talk to each other and convince
themselves that a rather complex set of assumptions reflects the real world. Those outside the group probably view
rationality quite differently. Flanagan (1984) listed the formal ideals in logic (impartiality, consistency, and
objectivity) as standards for all rationality. However, the more outside views that are allowed into the group, the
less likelihood that these formal ideals are shared.
Work in disciplines interested in human behavior can provide additional understanding of what it is that
multiple criteria decision analysis is seeking to model. Nozick (1993) held that what was rational depended on the
reasons for holding a position. DeSousa (1987) stated that scientists commonly tend to look for justifications of
beliefs already held. Belief is tied to context, and so is rationality. Only when we enlarge the context to include
other beliefs and wants can the charge of irrationality be made to stick. DeSousa also contended that rationality is
neither necessary nor sufficient for attainment of success.
Amatra Sen (1982) has been one of many economists to point out limitations of the assumption of
rationality. For instance, economic decision-makers are assumed to be honest to the extent of economic incentive.
If some poor sucker is honest in spite of his or her economic interests, they can be labeled as a fool in order to
preserve the economic theory of rationality. But this view is not shared by all of us. Sen concluded that a purely
economic man is close to being a social moron. DeSousa (1987) accused moral philosophy of trying to find a selfish
motive for any altruistic behavior. Moore (1994) demonstrated the importance of altruism, supporting Sen‟s view of
the need for a broader basis for decision making than is provided by pure economic models.
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Two broad approaches can be taken to reconciling the formal ideal model to observed reality. The first is
to assume that the formal ideal model is right. Nozick stated that economists and statisticians have developed
elaborate rational theories in order to preserve theories in light of observed reality. An opposing approach is to call
for a better model. Goldman (1986) cited Tversky‟s (1969) work about systematic and predictable economic
intransitivities, and MacCrimmon's (1968) reports of violations of most of Savage's postulates. Nozick (1993) noted
that we tend to discount the future and to discount probabilistic information. Discounting can be used to rationalize
any result. Yet if it were not for discounting in both time and space, DeSousa contends that we would be literally
care-buried.
DeSousa (1987) cited the Concorde fallacy as an example of irrational decision making with respect to
sunk costs, using the formal logical ideal. Because a great deal had been invested, the cooperative effort to build a
supersonic passenger aircraft proceeded after rational economic cost/benefit analysis indicated that it was irrational.
Yet the plane is a technological achievement, as well as an achievement for Franco-Anglo cooperation. How many
great cultural works would have been built based upon rational decision making? In addition to the seven wonders
of the ancient world, the cathedrals of medieval Europe, the Great Wall of China, the Taj Mahal, St. Petersburg,
Mayan pyramids, the Alhambra, and the Palace at Versailles might all have fallen to the axe of cost/benefit analysis.
Possibly from some perspectives they were counterproductive. But we would all be cheated had they not been built.
The post-modernist Feyerabend (1993) presented a convincing argument that scientific discovery happens
when the bounds of dogmatic theory are discarded, and the cause of rationality abandoned. Rosenau (1992)
proposed the even more radical position that rational minds should not be trusted, holding that conclusions based on
formal logical ideals often do more harm than good.
Nozick (1993) held that rationality depended on the reasons for holding a position, and that it was natural to
think of rationality as a goal-directed action. Goals are different from preferences. They involve standards of
attainment that may not be optimal (at least if they are attainable). Nozick proposed that goals can be used to filter,
providing humans the ability to cope with decision problems involving the complexity of large numbers of (or in
mathematical programming, infinite) alternatives. That is the approach used in screening discrete sets of
alternatives, and in preemptive goal programming models. These methods have been quite effectively applied,
although many would argue for seeking true optimality. Kersten and Noronha (1996) discussed a number of
alternative rationalities, and processes to support them.
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Making mathematical assumptions makes it possible to develop theorems about how people would be
expected to behave. Rationality is often a concept used to justify convenient mathematical assumptions. I propose
that these methodologically convenient assumptions include the concepts of Pareto optimality, seeking to minimize
distance to the ideal point, and unsaturated desire for some good. Pareto optimality (inferred from always preferring
more to less of a good) is valid in many contexts, but of questionable value in dynamic problems if used to eliminate
alternatives where new criteria might be added. Minimizing the distance to an ideal point is often used if no
preference information is available, but there seems no compelling reason to expect a decision maker‟s preference to
point in that direction. Saturated desire for some good is often empirically observed, even by people who seem
otherwise rational. In the words of Nozick (1993), economists assume wealth-maximization. I contend that this
assumption is made for mathematical tractability, not because it is truly useful.
EXPECTED UTILITY
The concept of expected utility is a key tool of multiple criteria decision analysis. Probability and statistics is a
fascinating field of practical mathematics to many. Those who try to teach these concepts to undergraduates
understand quite well that it is not a simple, natural conception. In fact, even those who teach graduate students,
who are motivated by the need to use the tools of probability and statistics in their work, understand that probability
and statistics involve concepts that are hard for humans to grasp. Yet probability and statistics work. Many natural
events follow normally distributed behavior.
Expected utility is an extension of probability and statistics into rational human decision making. It is
complicated by human behavior. While risk neutral behavior will maximize payoff in the long run, most humans
follow skewed response to risk neutral decision making, most opting for risk averse behavior so that they have less
probability of losing what they have gained in the past. DeSousa (1987) cited the Dutch book - a set of simultaneous
bets guaranteed to lose in the aggregate. By the formal ideal logic of economic wealth maximization, this is
irrational. However, big losses are avoided at the cost of a smaller loss. Adopting a Dutch book would therefore be
rational from some perspective.
Expected utility has had its critics. Einstein denied the role of chance in physics, claiming that God does
not play at dice. Popper (1972) said that the theory of corroboration showed that every probabilistic theory of
preference was absurd. He explained the continued support received by probability theory by pointing out that
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probability statements can never strictly be contradicted by experience, which many scientists (including Popper)
contended was a requirement for a true scientific hypothesis.
While expected utility has its limitations, it does provide useful analysis for those who adopt its inherent set
of assumptions. Expected utility theory operates by decomposing problems in a divide-and-conquer approach,
isolating preference and utility. Yet Nozick (1993) stated that utility can be complex, reflecting not simple
probability but rather the complex combination of probabilities and payoffs. This complex combination is not
wholly captured by causal expected utility. While it may be hard to measure all of these complexities, efforts
continue to more accurately capture the preferences of humans when uncertainty is present (as it almost always is).
THE OBJECTIVE/SUBJECTIVE CONTINUUM
A key part of philosophy is man's search for truth. As youths, we realize that we have our inherent biases, and we
try to overcome these tendencies to believe what we want to believe. Webster's dictionary defines objective as
having reality independent of the mind (Daellenbach, 1996). De Sousa (1987) referred to objectivity as explaining
by something real, other than by thoughts or propositions. This relates directly to philosophy, with one school (the
analytic-deductive school of Descartes and Leibniz in Churchman‟s 1971 framework) seeking to develop knowledge
through rigorous proof, and another school (Hume, Locke) believing only what could be sensed. Kant considered
the objective to involve universal and necessary conclusions (analytic), and the subjective to involve particular and
sensed observations (empirical). Objective is a word we all believe in, truth unblemished by human intervention for
ulterior motives (such as those used in marketing, politics, or negotiation).
The quest for objectivity is, however, usually thwarted. Polanyi (1958) contended that we use apparent
objectivity as a crutch, trusting that we can be relieved of all personal responsibility for our beliefs through objective
criteria of validity. Polanyi argued that our own critical powers have shattered this trust. To avoid subjective
believing, objectivity requires a “specifiably functioning mindless knower.” One is reminded of U.S. courtrooms,
where a set of rules and precedences are used to shelter raw truth from juries in the name of justice. Nozick (1993)
noted the attempts to eliminate the personal preferences, prejudices, moods, and partiality of judges in order to attain
objectivity. To the contrary, Polanyi takes the position that personal knowledge is worth more than strict
objectivity.
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The prevailing conception of science is elimination of the personal and subjective, and the attainment of the
objective. But attempts at perfect objectivity in the name of science have been thwarted. Polanyi (1958) cites the
case of the 18th century British Astronomer Royal, Nicholas Maskeleyne, who dismissed his assistant for persistent
recordings of star passages that were over half a second longer than Maskeleyne‟s own measures. Twenty years
later Bessel confirmed that the assistant was simply systematically measuring in a different manner. Individual
variations in perceptive faculties are now widely recognized. Theoretical objectivity assumes that we all measure the
same way. Both the researcher and the laboratory assistant were perfectly objective and consistent, but in their own
manner.
Subjectivity is defined by my dictionary as feelings, ideas, and thought. De Sousa (1987) listed
phenomenology, projection, relativity, and perspective as different forms of subjectivity. Popper (1972) called the
subjective behaviorist, psychological, sociological, and causal. Subjective concepts include words, meaningfulness,
definitions, and undefined concepts. Things that are in the mind of a human, but not precisely expressed so that
another human would necessarily interpret described concepts in the same way. Popper's primary philosophical
point was the critical method, relying upon elimination of error in an attempt to obtain objective growth of
knowledge. Popper decried probability theory as subjectivist epistemology at its strongest.
In the context of multiple criteria decision analysis, the ideal of MAUT is total objectivity. The method
uses precise lottery tradeoffs expressed in terms sufficiently abstract so humans can't see precisely what the impact
of their selections would be (so that they don't bias the measures of their personal preference by their personal
beliefs). This is combined with totally objective measures of the utility scales of attainment on each criterion.
Howard (1992) referred to those who would change the underpinnings of decision analysis as heretics, and referred
to those who allow the decision-maker to avoid the dictates of logic as members of cults. Subjective scales can be
used, but MAUT purists avoid them as much as possible, even if it adds years to the analysis.
At the other extreme, AHP is designed to quantify the subjective - providing a subjective scale of measure
in the words equal, moderately more, substantially more, and so forth. This is the essential difference to me between
MAUT and AHP. The technical issues of measures leading to rank-reversal probably ensue from this difference, but
that is for others to establish. (They probably have.)
Many in operations research seek to be as objective as possible (see Henig and Buchanan, 1996 in the
MCDA field). While total objectivity would be convenient, it is not always attainable to a sufficient degree to
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enable required decision making. Attempts to obtain objectivity are often thwarted by measurement difficulties, by
problem complexity, and by time limitations. It is the lot of humans to have to cope with subjectivity. I share
Kersten and Noronha‟s (1996) view that other approaches are needed, for at least some decision contexts.
PHILOSOPHICAL INFLUENCE ON BUSINESS THINKING
The rationalization of business administration has been a great cultural breakthrough. Max Weber (1978) argued for
the implementation of a trained and objective bureaucracy to replace the arbitrary decisions subjectively made by
prior systems. These arbitrary decisions were subjective in that they were a function of the individual decision
makers. While we all have grown to dislike bureaucratic red tape, the idea of consistent and rational administration
has been truly valuable. Ideal approaches to understanding decision problems are based on a rational normative
philosophy (Leibnizian, in Churchman 1971). The rational, objective views of Descartes and Leibniz are a natural
consequence of mathematics. Once the system of the world is understood, all outcomes of the system can be
calculated. If accurate measures are not available, the mathematical view of rationality is to expend the effort to
obtain an accurate and objective measure.
These rational, objective concepts are widely adopted in business theory today, especially in the form of
agency theory and transaction cost analysis. In the field of finance and accounting, agency theory (Jensen and
Meckling, 1976) proposes that shareholders incur losses due to divergence of interest between managers and their
agents. To rationally control organizations with different goals arising from different self-interests, controls and
governing structures need to be imposed. These can be financial penalties, or they can be more positive (such as
golden parachutes and profit sharing). Transaction cost analysis assumes that organizations function as perfectly
competitive, profit seeking markets (Williamson, 1975, 1981, 1985, 1987). Transaction costs are reduced through
internal control of resources and markets for products. The salient economic feature is that theoretically, the most
efficient will survive (Spencer, 1972 – social Darwinism). Therefore, those that survive must have been (and
continue to be) efficient.
There are other philosophies appropriate for specific decision contexts. Churchman identified empirical
(Lockean), multi-perspective frameworks (Kantian), dialectic (Hegelian), and cause-and-effect (Singerian) inquiring
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systems as alternatives to the rational system. Empirical approaches emphasize objective measures, relying upon
induction for development of theories. The Kantian model emphasizes using multiple views, which shared decision-
making would provide. For issues of particular importance, Hegelian approaches pitting one advocate against
another may be a useful way to quickly consider the important factors involved in a decision. The Singerian model‟s
focus on measurement would be useful in monitoring the impact of actions taken, thus enabling more accurate
development of system understanding.
The work of Habermas from the Frankfurt Institute of Social Research has been widely used in the field of
accounting. Laughlin (1987) argued that the scientific approach, seeking the objective path, was insufficient to
understand the nature and content of accounting practice. Habermas provided a basis for a methodological approach
for analysis, based upon critical theory. The development of language skill was credited with leading to social
progress, through which ideal states could be discovered. Habermas provided moral argumentation by which
consensus based on justice or right could be reached by decision-makers (Collier, 1998). Habermas also provided a
normative framework of discourse ethics (Flyvbjerg, 1998). Habermas‟s critical theory as applied to accounting, a
technical, organizationally independent activity, makes the need to consider social context apparent (Laughlin,
1987). It also has been used as the basis for the radical concept of applying ethical notions to marketing (Van
Toledo, 1986).
While Habermas was normative, Michel Foucault focused on the real, emphasizing the analysis of power
and the role of ethics (Flyvbjerg, 1998). The work of Foucault applied to accounting exposed the social roots behind
accounting systems design (Laughlin, 1987). Foucault's work has been traced in four phases (Miller and Leary,
1987), with different interpretations of historical processes.
Foucault's work on geneology involved tracing the emergence of frequently unquestioned contemporary
rationales. Contemporary beliefs were viewed by reference to the structure and events that led to their development.
This work involved diagnosis focusing on power, knowledge, and their interrelationships (Burrell, 1988).
Traditional authority systems (characterized by European social structure prior to 1800) was arbitrarily imposed. A
more disciplinary imposition of authority followed the French revolution (with varying times of transition in
different locations).
Foucault (1972) also had a body of work labeled archaeology, viewing the ways people have of doing
things influenced by institutional and legal criteria, pedagogical norms, and influenced by discourse (Miller and
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Leary, 1987). Archaeology was interested in the preconditions for change, the process of change, and the
organizational consequences of change (Hopwood, 1987). It provides a method of analysis by experts, who through
their communication can establish truth (Burrell, 1988). Theory arises from understanding the archives of diverse
discourses. If rules can be uncovered, accepted truth can be identified.
Knowledge and power were viewed by Foucault as a web of regulations and administrative tools applied in
a calculated manner to manage social life. If there is no truth, no objective means exists to distinguish between right
and wrong views. Power then remains as the only means of deciding whose perspective will prevail. This thinking
has been applied in appraisal (Townley, 1993a, 1993b), the general study of management (Knights, 1992), and many
other business studies.
Habermas represents a critical approach that is useful in multiple criteria analysis. This could be viewed as
focusing on the structure of a decision problem, the traditional route applied in MAUT (as objectively as possible),
AHP (allowing subjective input), and all of the other widely accepted methods. Foucault provides more emphasis
on process. This view is compatible with Roy's (1974) concept of decision maker construction of an outranking
relationship. Rather than simply reporting numbers reflecting measures (or subjective estimates), a constructivist
process would render the crucial aspects of the decision context visible (tracing geneology, or uncovering in an
archaeological sense).
CRITIQUE OF THE RATIONAL NORMATIVE VIEW
There have been many criticisms of the rational normative view. Within the field of economics, Morgenstern (1972)
cited thirteen problems that normative economic theory did not satisfactorily address in his opinion. Georgescu-
Roegen (1954) discussed things that real decision-makers do to cope with problems not addressed by normative
utility theory. Georgescu-Roegen argued that cardinalist utility relies on two unwarranted assumptions: the
irreducibility of wants, and perfect knowledge. Wildavsky (1997) noted the high levels of uncertainty that decision
making involves. We may not even be confident of our own preferences, as these depend on complete understanding
of the effects of our actions. Without complete knowledge, it is not possible to optimize. We use whatever
understanding we have, including that of the expected reactions of others to our actions. Wildavsky suggested
incrementalism (Lindblom, 1959; Lindblom and Braybrook, 1963) as the appropriate approach to dealing with
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environments with high levels of unknowns. Incremental change can be superior to system optimization, because
seeking rational, normative optimality requires assuming too much, leading to dangerous change.
Simon (1979) observed satisficing behavior on the part of many business decision-makers. While not
endorsing this behavior, Simon did suggest that rational, normative optimization was not appropriate in some
business decision-making contexts. Kahneman, et al. (1982) found that human decision-makers often rely upon
heuristics violating the rational utility procedure when faced with tradeoffs. MacCrimmon and Wehrung (1988)
published a detailed study of things that real executives do to cope with difficult tradeoffs, again at variance with the
rational normative view. Executives were found to have different aversion to risk, depending upon if gains or losses
were at stake. They modified risk through information gathering, bargaining, delay, and delegation. They also did
not settle for choices presented to them, but sought to reframe decision problems by creating superior alternatives.
Thus, real decision makers were found to operate in an environment settling for the best information they could get,
realizing that the cost of gathering complete information was too high, or time to gather it unavailable.
Zey (1992, 1998) also disputed rational choice contentions in a systematic manner. She identified ten
underlying assumptions, and discussed the implications of each. (1) Our own welfare also depends on the welfare of
those for whom we care. (2) Altruism holds clear value for many of us. (3) A broad definition of rationality is
tautological and irrefutable, in that an imaginative analyst can construct value-maximizing choice for any action.
Humans have been observed to react differently to risk when given the frame of expected gain as opposed to the
frame of expected loss. (4) Value is subjective in that it varies across individuals. Relationships of trust are difficult
if the parties involved are expected to be completely self-interested. (5) Objective measurement is often beyond
human understanding, due to complexity, or time limitations. (6) Utility is subjective, yet rational choice theorists
rationalize martyrdom by placing a value on sacrifice, leading to logical absurdity. (7) Myrdal (1979) pointed out
that rational choice models themselves have to use subjective values for efficiency, productivity, and growth. (8)
Group decision-making is growing in importance, making the idea of free will difficult to support. (9) What is
rational for one group is quite likely to be irrational for another group. (10) Market economies are not unitary
systems, but rather a collection of many subsystems consisting of many interacting groups.
The implications of this broader view of decision making within organizations is important to decision
support and group decision support. Management science and operations research focus on models, ideally on
optimal models, of organizational decision problems. However, models by their very nature leave things out. The
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idea of a model is to mathematically express the essential nature of the problem, assuming away inconsequential
aspects of the problem. The difficulty arises in that it is often convenient to assume away the complicating bits of
reality, or those parts of the system that are difficult to accurately measure.
If an aspect of a system is complicated or difficult to measure, that does not mean that it is not critically
important. The production aspects of an automobile manufacturing operation are usually precisely measured. The
marketing aspects of demand are critically important, but very complex and difficult to measure (they depend on the
response of people to changes in design features as well as price). Automobile producers that focus their decision-
making on the production aspects of their system are doomed to failure. Marketing is critical, and automobile firms
have spent great efforts in measuring aspects of marketing as well as they can. However, there still are many
subjective aspects important in marketing decisions.
GROUP RATIONALITY
Decision theory recommends performing the dominating action. Yet Nozick (1993) noted that evidence indicated
that more often the cooperative choice was taken. Kierkegaard (Barrett, 1958) held that social thinking was
determined by the law of large numbers - where the mass of opinion was, was truth. While we dispute that truth is
reliably identified by vote, acceptable group action often requires majority support. The American pragmatist Pierce
held that a person is not absolutely an individual, they must live in a society where the opinions of others impact
individual decision-making. Public decision making obviously involves the need to assure others, bending the
preference functions of individual decision-makers. The general rule is that the majority prevails. Yet none of us
want the will of the majority to impose undue hardship on minority groups. One attempt to overcome the
dictatorship of the majority was made by the Polish diet in medieval times. Unanimity was required for action. This
structure has generally been viewed as a failed approach. But it is hard to find a satisfactory balance between simple
majority and unanimity. In many contexts, a majority is not even available, and means of using various forms of
plurality to reach decisions have been attempted.
Group preference is problematic. Since every person may hold different beliefs, and there is only one truth,
group consensus clearly does not prove truth. The interest of all is clearly not the interest of each. Nor can
coordinated plans be expected from a totally democratic group. Marais in 1937 claimed that group wisdom results
from nothing other than the myriads of individual termites, specialized as several different castes, going about their
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individual business, influenced by each other, but uninfluenced by any master plan (Dennett, 1998). The only way
to operate in a group environment is through compromise, which Nozick (1993) points out is precisely what
objective principles are not supposed to do.
According to Hume (Nozick, 1993), a group of individual preferences could be expected to be irrational.
The economist Sen (1982) pointed to a number of limitations in attempts to identify a group preference (in addition
to the obvious problems of time). It is very difficult to obtain consistency in eliciting group preference. Individual
welfare is affected by the positions of others in the group. While individual votes can be aggregated, aggregation of
the weights of individual group members are problematic, as individuals begin to focus on their interests and apply
gaming strategies. Each person has a family of utility functions, explaining some of the difficulties involved in
accurate individual preference elicitation. Extending the idea to groups is unrealistic. Sen concluded that a group
welfare function is best approximated by the accepted value judgements of society. Rather than seeking to identify a
group preference function, Mitroff and Linstone (1993) proposed that the purpose of democracy is not polling, but
rather an open-ended discussion of key issues.
There are many well-established multiple criteria methods to support selection decisions, discussed above.
Almost all of these take the normative approach, based on an analytic-deductive philosophy. If most multiple criteria
methods are analytic-deductive, and analytic-deductive is insufficient, what are we to do? Without any promise of
satisfactory resolution, a representative analytic-deductive approach is compared to three other methods, where at
least parts of the problems uncovered might be more satisfactorily resolved.
ALTERNATIVE MULTIPLE CRITERIA METHODS
The methods are demonstrated with a scenario to select a nuclear dump site (Olson, 1996). Criteria considered include
cost, expected lives lost, risk of catastrophe, and civic improvement. The hierarchy of objectives is:
Overall
Cost Lives Lost Risk Civic Improvement
Cost is measured in net present value in billions. Expected lives lost reflects workers as well as expected local (civilian
bystander) lives lost. Lives lost are expected value calculations over the life of the project from both construction and
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operation. Risk is measured in the probability of a major catastrophe, such as an earthquake, tidal wave, flood, etc. that
would expose radiation. Civic improvement is measured objectively in an estimate of the number of families whose
housing would be upgraded from their current levels. The alternatives available are given below. Measures on each
criterion are given in objective measures to reflect best theoretical practice.
Cost Expected Lives Lost Risk Civic
(billions) probability Improvement
Nome AK 39.548 61 0.0165 312 upgrades
Newark NJ 98.467 143 0.0002 68,472 upgrades
Rock Springs WY 58.930 41 0.0036 4,138 upgrades
Duquesne PA 60.156 39 0.0069 20,653 upgrades
Gary IN 69.693 86 0.0027 56,847 upgrades
The initial problem solution is presented using SMART, using these objective measures based on anchor values, which
are considered in the development of weights.
Cost Expected Lives Lost Risk Civic
(billions) Improvement
weight .089 .556 .333 .022
Nome AK 0.991 0.564 0.175 0.003
Newark NJ 0.026 0.007 0.990 0.685
Rock Springs WY 0.685 0.707 0.820 0.041
Duquesne PA 0.664 0.721 0.655 0.207
Gary IN 0.505 0.386 0.865 0.568
The resultants are the products of weights time scores, used to rank order the alternatives based on SMART analysis.
Rock Sprgs 0.736
Duquesne 0.675
Gary 0.552
Nome 0.468
Newark 0.351
The MAUT model provides cardinal value scores that can be used to precisely rank each alternative (accurate as
long as all measures of importance are included, measurements are accurate, and preferences are independent and
accurately measured). The author‟s position is that this is dubious at best.
Image Theory
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Image Theory (Beach, 1990; 1993) utilizes framing of decisions to allow quick decision making necessary in
contexts where many options need to be considered, or where time is limited. It is well known that humans respond
differently to situations framed in different manners (Tversky and Kahneman, 1987). Image theory provides a
broader view of decision making, focusing on images of desired states, the actions needed to attain these desired
states, and the current status resulting from previous efforts to attain desired states (Beach and Lipshitz, 1993). This
approach would focus on identifying the context of the decision, and selecting alternatives that best matched views
of how they might be attained. Image theory would be highly compatible with the concepts of decision support
systems, seeking to provide decision-makers with key information and tools, relying upon human judgment for
decision choice. This concept may be related to Roy‟s (1974) outranking methods and their construction of
preference.
Image theory is probably most useful in the structuring phases of multiple criteria analysis. For instance,
the official analysis may have been based on the four measures provided in the data set above. But these were
selected from the official perspective. In nuclear siting problems, there are many parties who feel strongly about the
matter. For instance, local citizens may hold very strong opinions once they realize the site will be located near
them. They might want additional criteria to be considered, such as preservation of cultural artifacts endangered by
construction, or equity in that the interests of lowly populated areas should not be sacrificed to make more populated
areas more comfortable. Political progress has always had to consider a variety of perspectives. For instance, in
democratic legislative bodies, the support of at least 50 percent of the voting members need to be obtained, usually
through persuasion that a proposal is sufficiently in the interests of the voting member‟s constituents. Image theory
would utilize the perspectives of ALL voting members to identify concerns with a proposed site. A simplified
example for our nuclear dump site scenario could be:
Interest Group Criteria reflecting concerns
Government cost, lives lost, risk of catastrophe, civic improvement
Nuclear Industry permanent storage of nuclear waste, nuclear power demand
Local Citizens equity, cultural artifacts, employment
General Population nuclear power generation safety, transportation risk, low-cost electricity
Image theory in this context would thus make the analysis more complex, as it solicits the views of more
participants. Measures (objective or subjective) would be required for all of the criteria considered important. This
would mean more analysis would be required. It is also highly likely that the criteria of strong concern to one group
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would be directly conflicting with the concerns of other groups. This makes the decision more problematic than it
would be for a centralized decision-making authority.
Another aspect of image theory relates to the political process of obtaining support. Even those who hold
strong views in favor of objectivity have to sell their ideas. The way in which results are presented has clearly been
demonstrated to affect the result. While analysts should seek objective presentation, politicians are experts at
subjective framing of cases.
Within the multiple criteria field, Zeleny (1986) proposed de novo programming, which considers a
dynamic set of criteria that evolve through the analysis. This seems to be a concrete implementation of the framing
views arising from image theory.
Image theory is a process consideration, not necessarily affecting the numerical methodology used. It is
Singerian in Churchman‟s framework, providing a means to sweep in new perspectives of the decision problem.
Instead of providing numbers, it offers a means to obtain a broader base of support for a decision, and ideally
provided all a forum to express their concerns.
Verbal Decision Analysis
Verbal Decision Analysis (Larichev and Moshkovich, 1997) uses qualitative data for decision environments
involving high levels of uncertainty. This method utilizes controlled pairwise comparisons of tradeoffs among
conflicting criteria in order to identify the decision maker‟s preferred solution option (Berkeley, et al., 1991;
Andre‟eva, et al., 1995; Larichev, et al., 1995; Flanders, et al., 1998). This method is much less data intensive than
multiattribute utility theory, relying upon the subjective assessments of the decision maker at a strategic level.
Tradeoffs of robust data (Larichev, 1992) are used to elicit decision maker preference.
Verbal decision analysis vastly simplified the decision problem by stressing what is important. Precise but
meaningless measures are discarded to focus on broad concepts of importance. This means that lengthy and data-
intensive measures can be foregone if the relative tradeoffs can be identified with less precise input.
Cost Expected Lives Lost Risk Civic
(billions) probability Improvement
Nome AK moderate low very high low
Newark NJ very high very high very low very high
Rock Springs WY high very low low high
Duquesne PA high very low medium medium
Gary IN higher high low very high
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Screening can be used to eliminate all alternatives but two. For instance, expected lives lost should not be very high,
and expected risk of catastrophe should be less than high. This eliminates Nome and Newark, reducing the set to
three options. With the elimination of very minor measure advantages, Rock Springs now dominates Duquesne.
Therefore, the focus of the analysis is between the Rock Springs and Gary sites.
Cost Expected Lives Lost Risk Civic
(billions) probability Improvement
Rock Springs WY high very low low high
Gary IN higher high low very high
Rock Springs has relative advantages on cost and expected lives lost. Gary has a relative advantage on civic
improvement. Decision-makers would be faced with the following tradeoff:
Rock Spring relative advantages Gary relative advantages
Cost reduced from higher to high Civic improvement increased from high to very high
Expected lives lost reduced from high to very low
If decision-makers have enough information to clearly make a choice, the analysis will have been completed. Given
the weights on criteria, it seems quite probable that Rock Springs would be selected here. If, however, the tradeoff
is still difficult, one of the choices can be improved to match the other, with an estimated cost of improvement. For
instance, the Rock Springs site lacks the civic improvement offered by the Gary site. This is due primarily to the
number of families living in substandard housing. To match the Gary measure, more people would need to be
moved into Rock Springs, and provided with work. The estimated cost of doing this could be provided to give
decision-makers a basis for comparison.
Verbal decision analysis simplifies by focusing on important differences. It becomes subjective in that it
foregoes meaningless and inaccurate measures of the obvious. By focusing on comparisons of final candidate
alternatives, verbal decision analysis can be classified as Hegelian in Churchman‟s framework.
Recognition-Primed Decision
Recognition-primed decision involves preprogramming decision making to cope with rapidly moving environments
(Klein, et al., 1993). Recognition-primed decision making was developed from environments involving intensive
time pressure, such as fire fighting, the petroleum industry, and military operations (Flin, et al., 1996; Kaempf, et al.,
17
1996). This approach is what most organizations utilize: standard operating procedure to be implemented as specific
circumstances arise. Actions are triggered by recognizing the specific circumstances. In terms of multiple criteria
analysis, the tradeoffs would need to be analyzed ahead of time, and the resulting decisions mapped to the
circumstances calling for them, with this mapping communicated to those responsible for implementing these
policies. Recognition-primed decision provides a way to implement analysis conducted in repetitive environments,
such as hiring in compliance with nondiscrimination laws. As with expert system rule bases, consistency is obtained
if the system is thoroughly designed to cover all cases.
In the case of the example problem, RPD would only fit if the problem was repetitive, such as selecting
from a set of proposals periodically. An example set of rules that might be developed, to be applied by a screening
process, might be:
Do not accept a cost greater than 100 billion all pass
Do not accept expected lives lost greater than 100 Newark eliminated
Do not accept a risk of catastrophe greater than low Nome, Duquesne eliminated
If no proposals meet these screening minimum performances, further development of alternatives would be required.
If more than one satisfied these limits (here Rock Springs and Gary), a process such as preemptive goal
programming could be used (or any weighting scheme could also be applied).
Priority 1: Expected lives lost to be no greater than 90
Priority 2: Civic improvement to be at least medium
Priority 3: Risk of catastrophe to be no greater than very low
Priority 4: Expected lives lost to be no greater than 30
Priority 5: Expected cost to be no greater than 80 billion
Priority 6: Expected lives lost to be no greater than 20
Priority 7: Expected cost to be no greater than 50 billion
Priority 8 Expected lives lost to be minimized
In this case, both alternatives pass priority rules 1, 2, and 3. Neither pass the priority 4 rule, but Rock Springs is
closest, and the preemptive method would therefore select Rock Springs. With the preemptive approach, priorities 5
through 8 are not considered, because they are not required. Note that use of multiple attainment levels provides an
approximate implementation of a tradeoff function.
Recognition-primed decision provides a means to implement policies. These policies could have been
derived following thorough objective, analytic-deductive study, or more subjective study. The main benefit to
decision making is with respect to time.
18
SYSTEMS
The systems perspective recognizes collections of interacting components working toward the attainment of
common goals. Decision making within organizations may involve independent individuals, but organizations
include some decision making where coordination is required. The cooperative level varies a great deal.
The need to consider systems is highlighted by many mistakes. Asbestos was considered a miracle
substance in the 1940s, a way to drastically reduce the threat of fires. It did, but asbestos fibers turned out to be
highly toxic. Not everyone agrees about the magnitude of the problem, but asbestos is eliminated wherever
encountered in the U.S. Nuclear power was selected by many in the 1950s and 1960s on the basis of its cheap cost
and its lack of pollution. Things turned out drastically different on the cost dimension, and the fear of nuclear
radiation is considered far worse than coal pollution by most people. Aerosol cans were once considered a great
consumer convenience in the delivery of many products. It turned out that they released chemicals which absorbed
some of the ozone it the higher atmosphere. Whether or not this is leading to global warming (and paradoxically
enough, on to a subsequent ice age) is being studied and debated. But we have decided to forget about aerosol
containers.
The systems that we have created have made life very complex, with very few easy solutions. Wildavsky
(1997) related a number of cases where environmental concerns were raised, many times without scientific basis.
Verma (1998) relates a similar problem where a rational objective analysis failed to identify resistance of a
community‟s citizens to eminent domain condemnation of ground for a new automobile plant. Rational analysis can
rarely include all systemic components. There will always be some political aspects that need to be considered.
Mitroff and Linstone (1993) extended Churchman‟s (1971) framework of inquiring systems to consider
multiple perspectives. Systems exist in science, as well as historical, legal, and political contexts. According to
Singer, every act or action of humans is complex, and science must be conceived of and managed as a whole system.
If feedback is neglected, or systems become too complex, irrationality can easily arise as humans cope by
simplifying to the dimension (or few dimensions) that they can deal with in the easiest manner.
Mitroff and Linstone (1993) proposed viewing decision problems from three perspectives: technical,
organizational, and people. Tradeoffs support decision making in the technical perspective, but compromise and
bargaining are more effective in the organizational perspective, while beliefs and creativity prevail in the people
19
perspective. Uncertainty is anathema to those in the technical perspective, and uncertainty in decision problems
tends to be dismissed as unmanageable, or is replaced by probability estimates. However, humans aren‟t that good
at dealing with probability estimates. What-if exercises develop the capability of dealing with surprises, such as
hedging or crisis management. In the organizational perspective, reaction to problems typically begins with
stonewalling. From the people perspective, there is a tendency to ignore complex feedback loops, to discount the
future, and if no problem is immediately experienced, threats tend to be disregarded. Actions available to improve
systems performance include decoupling problems in the technical framework, transforming problems in the
organizational framework, and including all needed perspectives early in the planning stages of problems in the
people framework.
CONCLUSIONS
The scientific approach has been a major topic of interest of many in the fields of physics and philosophy. Polanyi
(1958) traced the denial of hypnotism by skeptical science for over a century despite the demonstrations by Mesmer.
This was due to an ingrained body of theory rejecting a phenomenon that didn't fit. We all remember the problems
encountered by Galileo when his theories of physics contradicted the dogma of the Roman church. Giordano Bruno
was in fact burned by the inquisition for similar views. There was a strong belief ingrained in human culture in
witchcraft and magic that dominated for three thousand years.
The concept of preference is as involved as the concepts of probability and statistics. Habermas (1984) held
that feelings and desires can only be expressed subjectively. Morgenstern (1972) felt that it was hard to accurately
identify preference (even revealed preference), and found indifference curve analysis to be inaccurate. Churchman
(1971) took the more radical position that preference orderings were absurd.
Judgment is at the heart of human decision making. Hegel (1873) considered judgment to be subjective. If
a decision were to be made objectively, one should simply adopt the alternative with the greatest calculated utility
value. Even the field of multiple criteria decision analysis has adopted the "decision support" view that human
decision-makers should be entrusted with the final decision. This is probably because funding sources would insist,
as well as a realization that responsibility for the decision belongs with the vested authority. But this is probably the
right decision for the wrong reason. Every model is imperfect. Models do not include all factors. Even the most
careful attempts at objective measurement will inevitably involve some inaccuracy. We accept much of the
20
information given out by leading centers of publicity, and rely on recognized authority for most of our judgments of
value. Polanyi (1958) stated that we must accredit our own judgment as the paramount arbiter. Some subjectivity is
required. This is the human condition.
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