Philosophy and Multiple Criteria Decision Analysis by abstraks



Philosophy and Multiple Criteria Decision Analysis

David L. Olson, Texas A&M University

return to papers menu                return to Olson‟s home page


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.


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



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

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.

         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


         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.

         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.


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

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).


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


          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


          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

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.


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

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

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).


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

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

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.


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

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.


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:


               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

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

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


         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

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

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.,

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.


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


         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

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.


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

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.


Andre‟eva, Y., Larichev, O., Flanders, N. & Brown, R., Complexity and uncertainty in Arctic resource decision: The
   example of the Yamal pipeline. Polar Geography and Geology Vol. 19, 22-35, 1995.

Bacon, F., Novum Organum, trans. & ed. P. Urbach and J. Gibson, Chicago: Open Court Publishing Co., 1994,
   fourth printing 1996.

Barrett, W., Irrational Man: A Study in Existential Philosophy, New York: Anchor Books, 1958.

Beach, L.R., Image Theory: Decision Making in Personal and Organizational Contexts, London, Wiley, 1990.

Beach, L.R., Making the Right Decision, Englewood Cliffs, NJ: Prentice-Hall, 1993.

Beach, L.R. and Lipshitz, R., Why classical decision theory is an inappropriate standard for evaluating and aiding
    most human decision making, in Klein, G.A., Orasnu, J., Calderwood, R. and Zsambok, C.E. (Eds.) Decision
    Making in Action: Models and Methods Norwood, NJ: Ablex Press, 21-35, 1993.

Bennett, P. and Howard, N., Rationality, emotion and preference change: Drama-theoretic models of choice,
   European Journal of Operational Research 92, 603-614, 1996.

Berkeley, D., Humphreys, P., Larichev, O., and Moshkovich, H. Aiding strategic decision making: Derivation and
    development of ASTRIDA. In Y. Vecsenyi and H. Sol, eds., Environment for Supporting Decision Processes,
    North-Holland, Amsterdam, 1991.

Burrell, G. Modernism, postmodernism and organizational analysis 2: The contribution of Michel Foucault,
    Organization Studies 9:2, 221-235, 1988.

Churchman, C. W. (1971) The Designing of Inquiring Systems, New York: Basic Books.

Collier, J., Theorising the ethical organization, Business Ethics Quarterly 8:4, 621-654, 1998.

Daellenbach, H.G., Comments to „Solving MCDM problems: Process concepts‟ by Henig and Buchanan, Journal of
    Multi-Criteria Decision Analysis 5:1, 1996, 15-16.

DeBreu, G., Theory of Value: An Axiomatic Analysis of Economic Equilibrium, New Haven, CN: Yale University
   Press, 1959, sixth printing, 1975.

Dennett, D.C., Brainchildren: Essays on Designing Minds, Cambridge, MA: A Bradford Book, 1998.

De Sousa, R., The Rationality of Emotion, Cambridge, MA: The MIT Press, 1987, fifth printing,1997.

Feyerabend, P., Against Method, 3rd ed., London: Verso, 1993.

Flanagan, O., The Science of the Mind, second edition, Cambridge, MA: A Bradford Book, 1984, sixth

Flanders, N.E., Brown, R.V., Andre‟eva, Y. and Larichev, O. Justifying public decisions in Arctic oil and gas
    development: American and Russian approaches. Arctic 51:3, 262-279, 1998.

Flin, R., Slaven, G., and Stewart, K., Emergency decision making in the offshore oil and gas industry. Human
     Factors 38:2, 262-277, 1996.

Flyvberg, B. Habermas and Foucault: Thinkers for civil society? British Journal of Sociology 49:2, 210-233, 1998.

Foucault, M., The Archaeology of Knowledge & the Discourse on Language, trans. A.M. Sheridan Smith, New
    York: Pantheon Books, 1972.

Georgescu-Roegen, N., Choice, expectations, and measurability. Quarterly Journal of Economics 68(4), 503-534,

Goldman, A.I., Epistemology and Cognition, Cambridge, MA: Harvard University Press, 1986.

Habermas, J., The Theory of Communicative Action, Vol. 1: Reason and the Rationalization of Society, in German
   1981, T. McCarthy, trans., Boston: Beacon Press, 1984.

Hegel, G.W.F., The Science of Logic, trans. W. Wallace, Oxford: The Clarendon Press, orig. 1873, trans. 1975.

Henig, M.I. and Buchanan, J.T., Solving MCDM problems: Process concepts, Journal of Multi-Criteria Decision
    Analysis 5:1, 1996, 3-11.

Hopwood, A.G. The archaeology of accounting systems, Accounting, Organizations and Society 12:3, 207-234,

Howard, R.A., Heathens, heretics, and cults: The religious spectrum of decision aiding, Interfaces 22:6, 15-27, 1992.

Jensen, M. C. & Meckling, W. H. Theory of the firm: Managerial behavior, agency costs and ownership structure.
    Journal of Financial Economics 3, 305-360, 1976.

Kaempf, G.L., Klein, G., Thordsen, M.L., and Wolf, S., Decision making in complex naval command-and-control
   environments. Human Factors 38:2, 220-231, 1996.

Kahneman, D., Slovic, P., & Tversky, A., eds. Judgment under Uncertainty: Heuristics and Biases, Cambridge, UK:
   Cambridge University Press, 1982.

Kersten, G.E. and Noronha, S.J., Comments to „Solving MCDM problems: Process concepts‟ by Henig and
    Buchanan, Journal of Multi-Criteria Decision Analysis 5:1, 1996, 12-15.

Klein, G.A., A recognition-primed decision (RPD) model of rapid decision making, in Klein, G.A., Orasnu, J.,
    Calderwood, R. and Zsambok, C.E. (Eds.) Decision Making in Action: Models and Methods Norwood, NJ:
    Ablex Press, 138-147, 1993.

Knights, D., Changing spaces: The disruptive impact of a new epistemological location for the study of
    management, Academy of Management Review 17:3, 514-536, 1992.

Larichev, O., Cognitive validity in design of decision-aiding techniques, Journal of Multi-Criteria Decision Analysis
    1:3, 127-138, 1992.

Larichev, O., Brown, R., Andre‟eva, E. and Flanders, N. Categorical decision analysis for environmental
    management: A Siberian gas distributing case. In J.-P. Caverni, M. Bar-Hillel, F.H. Barron and H. Jungermann,
    eds., Contribution to Decision Making, North-Holland, Amsterdam, 255-286, 1995,

Larichev, O. and Moshkovich, H. Verbal Decision Analysis for Unstructured Problems, Kluwer Academic
    Publishers, Boston, 1997.

Laughlin, R.C. Accounting systems in organisational contexts: A case for critical theory, Accounting, Organizations
    and Society 12:5, 479-502,1987.

Lindblom, C., The science of muddling through. Public Administration Review 19, 79-88, 1959.

Lindblom, C. E. and Braybrook, D., A Strategy of Decision Policy Evaluation as a Social Process, Glencoe, IL: The
    Free Press, 1963.

MacCrimmon, K.R., Descriptive and normative implications of the decision-theory postulates, in K. Borch and J.
   Mossin, eds., Risk and Uncertainty, New York: St. Martin‟s, 1968.

MacCrimmon, K. R. and Wehrung, D. A., Taking Risks: The Management of Uncertainty, New York: The Free
   Press, 1988.

Miller, P. and O‟Leary, T., Accounting and the construction of the governable person, Accounting, Organizations
    and Society 12:3, 235-265,1987.

Mitroff, I.I. and Linstone, H.A., The Unbounded Mind: Breaking the Chains of Traditional Business Thinking, New
    York: Oxford University Press, 1993.

Moore, K.R., A fat lady in a corset: Altruism and social theory, American Journal of Political Science 38:4, 861-
   893, 1994.

Morgenstern, O. Thirteen critical points in contemporary economic theory: An interpretation. Journal of Economic
   Literature 10, 1163-1189, 1972.

Myrdal, G., Against the Stream: Critical Essays on Economics, New Yorkj: Pantheon, 1979.

Nozick, R., The Nature of Rationality, Princeton, NJ: Princeton University Press, 1993, paperback 1995.

Olson, D.L., Decision Aids for Selection Problems, New York: Springer, 1996.

Polanyi, M., Personal Knowledge: Towards a Post-Critical Philosophy, Chicago: The University of Chicago Press,
    1958, corrected edition 1974.

Popper, K.R. Objective Knowledge: An Evolutionary Approach, Oxford: Oxford University Press, 1972, revised
   edition 1979.

Rosenau, P.M., Post-Modernism and the Social Sciences: Insights, Inroads, and Intrusions, Princeton, NJ: Princeton
    University Press, 1992.

Roy, B., Critères multiples et modélisation des préférences: l‟apport des relations de surclassement, Review Econ.
    Politi. 1, 1974.

Sen, A., Choice, Welfare, and Measurement, Oxford: Blackwell, 1982; Cambridge, MA: Harvard University Press,

Simon, H., Rational decision making in business organizations. American Economic Review 69, 493-513, 1979.

Spencer, H., Herbert Spencer on Social Evolution: Selected Writings, Chicago: The University of Chicago Press,
    reprint, 1972.

Townlwy, B., Performance appraisal and the emergence of management, Journal of Management Studies 30:2, 221-
   238, 1993a.

Townlwy, B., Foucault, power/knowledge, and its relevance for human resource management, Academy of
   Management Review 18:3, 518-545, 1993b.

Tversky, A., Intransitivity of preferences, Psychological Review 76, 31-48, 1969.

Tversky, A. & Kahneman, D., Rational choice and the framing of decisions, in R. M. Hogarth & M. W. Reder, eds.,
    Rational Choice: The Contrast between Economics and Psychology, Chicago, University of Chicago Press, 67-
    94, 1987.

Van Toledo, K., Ethical notions about the general application of marketing-techniques, derived from Jürgen
    Habermas‟ theory of human action.

Verma, N., Similarities, Connections, and Systems, Lanham, MD: Lexington Books, 1998.

Weber, M. B.,. Economy and Society, G. Roth & C. Wittich, eds., University of California Press, 1968, second
   printing 1978.

Wildavsky, A., But Is It True? A Citizen's Guide to Environmental Health and Safety Issues, Cambridge, MA:
    Harvard University Press, third printing, 1997.

Williamson, O. E., Markets and Hierarchies: Analysis and Antitrust Implications, New York: Free Press, 1975.

Williamson, O. E., The economics of organization: The transaction cost approach. American Journal of Sociology
    87, 548-577, 1981.

Williamson, O. E., The Economic Institution of Capitalism, New York: Free Press, 1985.

Williamson, O. E., Antitrust Economics: Firms, Markets, Relational Contracting, New York: Basil Blackwell, 1987.

Zeleny, M., Optimal system design with multiple criteria: De novo programming approach, International Journal of
    Production Economics 10:2, 89-94, 1986.

Zey, M., Criticisms of rational choice models, in M. Zey, ed., Decision Making: Alternatives to Rational Choice
Models, Thousand Oaks, CA: Sage, 9-31, 1992.

Zey, M., Rational Choice Theory and Organization Theory: A Critique, Thousand Oaks, CA: Sage, 1998.

return to papers menu              return to Olson‟s home page

To top