Building on lecture notes from his course at Stanford University, James G. March provides an introduction to decision making, a central human activity, fundamental to individual, group, organizational, and societal life. March draws on research from all the disciplines of social and behavioural science to show decision making in its broadest context. By emphasizing how decisions are actually made - as opposed to how they should be made - he enables those involved in the process to understand it both as observers and as participants. In addition, March explains key concepts of vital importance to decision makers, such as limited rationality, history-dependent rules, and ambiguity, and weaves these ideas into a full depiction of decision making.
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James G. March is the Jack Steele Parker Professor of International Management and a professor of political science and sociology at Stanford University. Professor March is the author and co-author of numerous books and hundreds of journal articles on organizations, decision making, and leadership. He lives in Stanford, California.Excerpt. © Reprinted by permission. All rights reserved.:
By far the most common portrayal of decision making is one that interprets action as rational choice. The idea is as old as thought about human behavior, and its durability attests not only to its usefulness but also to its consistency with human aspirations. Theories of rational choice, although often elaborated in formal and mathematical ways, draw on everyday language used in understanding and communicating about choices. In fact, the embedding of formal theories of rationality in ordinary language is one of their distinctive features. Among other things, it makes them deceptively comprehensible and self-evident. This chapter examines the idea of rational choice and some ways in which theories of limited rationality have made that idea more consistent with observations of how decisions actually happen.
1.1 The Idea of Rational Choice
Like many other commonly used words, "rationality" has come to mean many things. In many of its uses, "rational" is approximately equivalent to "intelligent" or "successful." It is used to describe actions that have desirable outcomes. In other uses, "rational" means "coldly materialistic," referring to the spirit or values in terms of which an action is taken. In still other uses, "rational" means "sane," reflecting a judgment about the mental health displayed by an action or a procedure for taking action. Heterogeneous meanings of rationality are also characteristic of the literature on decision making. The term is used rather loosely or inconsistently.
In this book, "rationality" has a narrow and fairly precise meaning linked to processes of choice. Rationality is defined as a particular and very familiar class of procedures for making choices. In this procedural meaning of "rational," a rational procedure may or may not lead to good outcomes. The possibility of a link between the rationality of a process (sometimes called "procedural rationality") and the intelligence of its outcomes (sometimes called "substantive rationality") is treated as a result to be demonstrated rather than an axiom.
1.1.1 The Logic of Consequence
Rational theories of choice assume decision processes that are consequential and preference-based. They are consequential in the sense that action depends on anticipations of the future effects of current actions. Alternatives are interpreted in terms of their expected consequences. They are preference-based in the sense that consequences are evaluated in terms of personal preferences. Alternatives are compared in terms of the extent to which their expected consequences are thought to serve the preferences of the decision maker.
A rational procedure is one that pursues a logic of consequence. It makes a choice conditional on the answers to four basic questions:
1. The question of alternatives: What actions are possible?
2. The question of expectations: What future consequences might follow from each alternative? How likely is each possible consequence, assuming that alternative is chosen?
3. The question of preferences: How valuable (to the decision maker) are the consequences associated with each of the alternatives?
4. The question of the decision rule: How is a choice to be made among the alternatives in terms of the values of their consequences?
When decision making is studied within this framework, each of these questions is explored: What determines which alternatives are considered? What determines the expectations about consequences? How are decision maker preferences created and evoked? What is the decision rule that is used?
This general framework is the basis for standard explanations of behavior. When asked to explain behavior, most people "rationalize" it. That is, they explain their own actions in terms of their alternatives and the consequences of those alternatives for their preferences. Similarly, they explain the actions of others by imagining a set of expectations and preferences that would make the action rational.
A rational framework is also endemic to theories of human behavior. It is used to understand the actions of firms, marriage partners, and criminals. It underlies many theories of bargaining, exchange, and voting, as well as theories of language and social structure. Rational choice processes are the fundamentals of microeconomic models of resource allocation, political theories of coalition formation, statistical decision theories, and many other theories and models throughout the social sciences.
1.1.2 Rational Theories of Choice
Within rational processes, choice depends on what alternatives are considered and on two guesses about the future: The first guess is a guess about future states of the world, conditional on the choice. The second guess is a guess about how the decision maker will feel about that future world when it is experienced.
PURE THEORIES OF RATIONAL CHOICE
Some versions of rational choice theory assume that all decision makers share a common set of (basic) preferences, that alternatives and their consequences are defined by the environment, and that decision makers have perfect knowledge of those alternatives and their consequences. Other versions recognize greater inter-actor subjectivity but nevertheless assume perfect knowledge for any particular decision -- that all alternatives are known, that all consequences of all alternatives are known with certainty, and that all preferences relevant to the choice are known, precise, consistent, and stable.
These pure versions of rational choice have well-established positions in the prediction of aggregate behavior, where they are sometimes able to capture a rational "signal" within the subjective "noise" of individual choice. They are sources of predictions of considerable generality, for example the prediction that an increase in price will lead (usually) to an aggregate decrease in demand (although some individuals may be willing to buy more at a higher price than at a lower one).
In spite of their utility for these qualitative aggregate predictions, pure versions of rational choice are hard to accept as credible portraits of actual individual or organizational actors. Consider the problem of assigning people to jobs in an organization. If it were to satisfy the expectations of pure rationality, this decision would start by specifying an array of tasks to be performed and characterizing each by the skills and knowledge required to perform them, taking into account the effects of their interrelationships. The decision maker would consider all possible individuals, characterized by relevant attributes (their skills, attitudes, and price). Finally the decision maker would consider each possible assignment of individuals to tasks, evaluating each possible array of assignments with respect to the preferences of the organization.
Preferences would be defined to include such things as (1) profits, sales, and stock value (tomorrow, next year, and ten years from now); (2) contributions to social policy goals (e.g. affirmative action, quality of life goals, and the impact of the assignment on the family); and (3) contributions to the reputation of the organization among all possible stakeholders -- shareholders, potential shareholders, the employees themselves, customers, and citizens in the community. The tradeoffs among these various objectives would have to be known and specified in advance, and all possible task definitions, all possible sets of employees, and all possible assignments of people to jobs would have to be considered. In the end, the decision maker would be expected to choose the one combination that maximizes expected return.
A considerably less glorious version of rationality -- but still heroic -- would assume that a structure of tasks and a wage structure are given, and that the decision maker assigns persons to jobs in a way that maximizes the return to the organization. Another version would assume that a decision maker calculates the benefits to be obtained by gathering any of these kinds of data, and their costs.
Virtually no one believes that anything approximating such a procedure is observed in any individual or organization, either for the job assignment task or for any number of other decision tasks that confront them. Although some people have speculated that competition forces the outcomes of actual decision processes to converge to the outcomes predicted from a purely rational process, even that speculation has been found to be severely restricted in its applicability. Pure rationality strains credulity as a description of how decisions actually happen. As a result, there have been numerous efforts to modify theories of rational choice, keeping the basic structure but revising the key assumptions to reflect observed behavior more adequately.
RATIONAL DECISION MAKING AND UNCERTAINTY ABOUT CONSEQUENCES
The most common and best-established elaboration of pure theories of rational choice is one that recognizes the uncertainty surrounding future consequences of present action. Decision makers are assumed to choose among alternatives on the basis of their expected consequences, but those consequences are not known with certainty. Rather, decision makers know the likelihoods of various possible outcomes, conditional on the actions taken.
Uncertainty may be imagined to exist either because some processes are uncertain at their most fundamental levels or because decision makers' ignorance about the mechanisms driving the process make outcomes look uncertain to them. The food vendor at a football game, for example, knows that the return from various alternative food-stocking strategies depends on the weather, something that cannot be predicted with certainty at the time a decision must be made.
Since a decision maker does not know with certainty what will happen if a particular action is chosen, it is unlikely that the results of an action will confirm expectations about it. Post-decision surprise, sometimes pleasant sometimes unpleasant, is characteristic of decision making. So also is postdecision regret. It is almost certain that after the consequences are known (no matter how favorable they are) a decision maker will suffer regret -- awareness that a better choice could have been made if the outcomes could have been predicted precisely in advance. In such a spirit, investors occasionally rue the gains they could have realized in the stock market with perfect foresight of the market.
The most commonly considered situations involving uncertainty are those of decision making under "risk," where the precise consequences are uncertain but their probabilities are known. In such situations, the most conventional approach to predicting decision making is to assume a decision maker will choose the alternative that maximizes expected value, that is, the alternative that would, on average, produce the best outcome if this particular choice were to be made many times. The analog is gambling and the choice of the best gamble. An expected-value analysis of choice involves imagining a decision tree in which each branch represents either a choice to be made or an "act of nature" that cannot be predicted with certainty. Procedures for constructing and analyzing such trees constitute a large fraction of modern decision science.
In more elaborate rational theories of choice in the face of risk, an alternative is assessed not only by its expected value but also by its uncertainty. The value attached to a potential alternative depends not only on the average expected return but also on the degree of uncertainty, or risk, involved. For risk-averse decision makers, riskiness decreases the value of a particular alternative. For risk-seeking decision makers, riskiness increases the value.
The riskiness of an alternative is defined in different ways in different theories, but most definitions are intended to reflect a measure of the variation in potential outcomes. This variation has a natural intuitive measure in the variance of the probability distribution over outcome values. For various technical reasons, such a measure is not always used in studies of choice, but for our purposes it will suffice. When risk is taken into account, a decision is seen as a joint function of the expected value (or mean) and the riskiness (or variance) of the probability distribution over outcomes conditional on choice of a particular alternative.
MODIFYING THE ASSUMPTIONS
The introduction of risk and the development of ways to deal with it were major contributions to understanding and improving decision making within a rational framework. Such developments were, however, just the first step in modifying the knowledge assumptions of rational choice. Most modern theories of rational choice involve additional modifications of the pure theory. They can be distinguished by their assumptions with respect to four dimensions:
1. Knowledge: What is assumed about the information decision makers have about the state of the world and about other actors?
2. Actors: What is assumed about the number of decision makers?
3. Preferences: What is assumed about the preferences by which consequences (and therefore alternatives) are evaluated?
4. Decision rule: What is assumed to be the decision rule by which decision makers choose an alternative?
Although most theories "relax" the assumptions of the pure theory on at least one of these dimensions, they tend to be conservative in their deviations from the assumptions underlying a pure conception of rationality. For example, most theories of limited knowledge are not simultaneously theories of multiple actors; most theories of multiple actors (for example, microeconomic versions of game theory) are not simultaneously theories of limited knowledge; and virtually none of the limited knowledge or multiple-actor theories introduce conceptions of ambiguous or unstable preferences. In that sense at least, the pure model still permeates the field -- by providing an overall structure and significant (though different) parts for various different theories.
1.1.3 Enthusiasts and Skeptics
Enthusiasts for rational models of decision making notice the widespread use of assumptions of rationality and the successes of such models in predictions of aggregates of human actors. They easily see these symptoms of acceptance and usefulness as impressive support for the models. Skeptics, on the other hand, are less inclined to give credence to models based on their popularity, noting the historical fact that many currently rejected theories have enjoyed long periods of popularity. They are also less inclined to find the models particularly powerful, often emphasizing their less than perfect success in predicting individual behavior. They easily see these symptoms of conventionality and imperfection as making the models unattractive.
Both enthusiasts and skeptics endorse limited rationality, the former seeing limited rationality as a modest, natural extension of theories of pure rationality, and the latter seeing limited rationality as a f...
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