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Abstract

Decision making is a mental or behavioral commitment to a course of action. In a broader sense, the term ‘‘decision making’’ denotes an information-processing activity of a single decision maker, or of multiple decision makers, that begins with the recognition of a choice situation and ends with the implementation of the choice and the monitoring of its effects.

Outline

Introduction
Key Concepts
Features and Distinctions
Value/Utility
Uncertainty/Probability
Models and Modes of Decision Making
Methods
Areas of Application
Conclusion

1. Introduction

More than many other behaviors, individual decision making is a subject not only of psychological research in the laboratory but also of interest in a number of ‘‘real-world’’ domains where significant decisions are actually made and where psychological knowledge has been applied successfully. The study of decision making has its roots in economics and statistics, and this is still the most active field for decision researchers. Topics include how people choose among consumption goods, investment options, and/or retirement plans as well as how managers make production and marketing decisions and how they make organizational and employment decisions. Another important field involves health-related and medical decisions of both patients and physicians. For patients, topics include how people make their personal decisions about smoking, drinking, taking drugs, and/or sexual behaviors as well as how patients choose among treatment options (e.g., surgery or radiation) and how they can be helped in making such decisions. For physicians, topics include how they choose among diagnostic and treatment alternatives and how their individual or collective decision processes can be supported. A very different field is aviation, where the interest focuses on the decisions that pilots must make—often under extreme time pressure. Closely related are decision situations in high-risk facilities such as nuclear power and chemical plants. Knowledge about people’s decision-making behavior has also been used for designing counseling and advice-giving procedures. Examples include when patients are asked for their informed consent, when parents come to a genetic counselor, when people seek investment advice, and when adolescents need behavioral strategies against sexual assault.

2. Key Concepts

A decision is a mental or behavioral commitment to a course of action. An option to change the status quo may be brought to the attention of a person and is accepted or rejected, or one of several given options is preferred over the others. A decision can be expressed by verbal judgment (e.g., ‘‘Option X is the best one’’) or by behavioral choice (e.g., Option X is chosen). In a narrow sense, the term ‘‘decision’’ denotes only the moment in which the commitment is made. In a broader sense, the term denotes an information-processing activity, usually beginning with the recognition of a choice situation and ending with the monitoring of the outcomes of the chosen option. Research has looked at all phases of a decision-making process—how people identify, generate, screen, and modify options; how they mentally simulate courses of action; how they match actions to situations; how they frame, compare, and evaluate all or a subset of options; and how they process information after a choice has been made. Decisions can require different amounts of cognitive effort and be made on different levels of awareness, depending largely on the significance of the problem, the familiarity of the situation, and the experience of the decision maker. When people drive from their home to their office, or when surgeons perform appendectomies, their decision making is often nearly automatic and is experienced as performed routinely or intuitively. On the other hand, when people in a restaurant choose from a menu, they realize that they must make decisions and often ponder about the options and consider the various pros and cons. Typically, substantial cognitive effort is invested only if the problem is important, complex, or unfamiliar such as in the purchase of a house by a family, the choice of a cancer treatment by a patient, or the development of a new product by a company. Economists tend to consider a decision maker—the homo economicus—as a rational decision maker if he or she uses all available information, if preferences and beliefs are stable and consistent, and if a maximizing strategy is applied. Psychologists (and behavioral economists) favor the assumption that decision makers usually operate with bounded rationality (i.e., within the limits of their cognitive capacity) and that they apply the strategy that best matches their situational assessment and motivation.

3. Features And Distinctions

The dominant view is that people make their decisions as a result of anticipating and evaluating the potential outcomes and the uncertainties associated with them. This is called a consequentialist perspective. The major part of this research-paper focuses on research that takes this perspective, but nonconsequentialist approaches are also presented later. From the consequentialist perspective, decision problems differ formally in the following ways. First, the consequences of the decision are certain (e.g., the consequences of choosing Apartment A or Apartment B) or uncertain (e.g., the consequences of choosing chemical therapy or surgery). Second, the consequences are unidimensional (e.g., the consequences of gambling in a casino as either a gain or a loss of money) or multidimensional (e.g., the consequences of choosing a job in a company or at a university). Third, the decision process may have one stage (e.g., the decision to hire a person) or several stages (e.g., the decision to develop a new drug). Fourth, the decision may be unique (e.g., decisions among cancer treatments) or may be made repeatedly (e.g., decisions between job applicants). Fifth, another important distinction must be made between individual decision situations and social ones. In the former case, decisions are made by individuals, and individuals primarily must bear the consequences. This situation is the topic of cognitive psychology. In the latter case, decisions are also made by individuals, but the decisions are made in direct or indirect interaction among these individuals. This situation is the topic of social and organizational psychology.

4. Value/Utility

People are assumed to make their decisions depending on their preferences for the potential consequences (i.e., states or events) of the given options. Implicitly or explicitly, people evaluate these consequences, and the subjective values, called utilities, determine their decisions. However, the utility of outcomes is not simply a linear function of their quantity. In general, one finds a logarithmic function well known from psychophysics. In economics, this is called the decreasing marginal utility function: The second million causes less pleasure than the first million. The same holds for the negative part of the function: A dessert for $5 appears to be less expensive after a $70 dinner than after a $7 pizza. Advertising and marketing use the knowledge about the psychophysics of spending in many ways.

Evaluations are influenced by a number of factors, including the following prominent ones. First, people value an object more highly when they believe to have achieved it by their performance rather than by luck (i.e., source dependency). Second, people value an object more highly when they consider selling it than when they consider buying the same object (i.e., endowment effect); that is, a person would want a higher price for a painting he or she owns than the person would pay for the same painting. Third, the evaluation of an option is sometimes influenced by investment of money, time, or effort in the past (i.e., sunk cost effect); that is, a person does not leave a boring movie because he or she has paid for the admission ticket. Fourth, the evaluation also depends on the moment in time when the object will be received or when the state will occur (i.e., time preferences); that is, a person prefers to receive $100 sooner rather than later, and the person probably prefers to see the dentist later rather than sooner (unless he or she has pain).

Multi-attribute options (e.g., consumption goods, job applicants) require trade-offs between attributes. Consumer reports provide the relevant attributes of the goods and the values of the goods on these attributes. But consumers must make the trade-offs themselves.

Numerous studies have examined which attributes people use in such situations, how they weigh them, and how they integrate the information about the goods on all attributes. Sometimes, people use noncompensatory rules; that is, they eliminate all options that do not exceed certain cutoff points on one or several attributes or that do not share certain features, independent on their values on other attributes. For instance, a person looking for an apartment may first screen out those apartments that do not have a minimum size, then those whose rents exceed a certain limit, then those whose distance to the beach exceeds a certain distance, and so on until finally one acceptable apartment is left. Alternatively, people may use compensatory rules; that is, they accept that each value on an attribute, however low, can be compensated by high values on other attributes. For the person looking for an apartment, the small size of an apartment might not lead to its elimination because it can be compensated by a low rent. Consumer research has used the theoretical concepts, the research methods, and the empirical findings extensively.

5. Uncertainty/Probability

Decisions are always made under uncertainty because their consequences occur in the future and, thus, depend not only on the decision makers’ choice but also on events and states not under the decision makers’ control. In some situations, the consequences can be considered as nearly certain or the fundamental uncertainty is irrelevant for the choice. However, in most decision situations, the uncertainty cannot be ignored; therefore, research on how people deal with uncertainty is an important field of decision research.

For mathematicians, probability is the language of uncertainty; for decision researchers, subjective probability is the language of uncertainty. The subjective probability for an event may be based on the known or assumed relative frequency of that event (e.g., the subjective probability of rain tomorrow, the subjective probability of having a car accident), but in many situations the event is unique and there are no relative frequencies (e.g., the subjective probability of Brazil winning the soccer world championship, the subjective probability of an increase of the gold price by the end of the year). Research has studied the psychological variants of uncertainty, their cognitive characteristics and determinants, the ways in which people express uncertainty (e.g., numerically, verbally), and the ways in which people understand expressions of uncertainty (e.g., probabilities, percentages, frequencies). Intuitive judgments of probabilities have been shown, under certain conditions, to deviate considerably from our statistical knowledge and to violate the rules of probability theory systematically. These observations led Tversky and Kahneman to develop their heuristics and biases research program. The key assumption is that people intuitively apply mental heuristics rather than statistical algorithms, and although these heuristics are generally useful and efficient, they can produce judgmental errors, fallacies, or biases. Two heuristics are particularly important: representativeness and availability. Representativeness is when events are unique (e.g., the guilt of a defendant) or set in the future (e.g., the outcome of the next election) and people draw on their knowledge about the case and judge the probability by the closeness of the match between the event and the prediction derived from their knowledge. Availability is when events are grouped in categories or by features (e.g., percentages of road accidents in a year) and people judge the probability by the number of examples that come to mind or by the ease with which they come to mind. Many judgmental biases can be explained by the assumption that people use these heuristics, for instance, the base rate fallacy, sample size neglect, regression neglect, the unpacking effect, and the conjunction fallacy. Other prominent biases in subjective probability judgments, not directly related to the use of heuristics, are the hindsight effect, the overconfidence effect, conversion errors, the illusion of control, and unrealistic optimism.

6. Models And Modes Of Decision-Making

Prescriptive theories of decision making say how decisions should be made if the decision maker wants to follow certain principles of rationality (e.g., the principle of transitivity). These theories are part of management science. They provide formal rules and procedures for structuring and processing the relevant information and, thus, provide support in complex decision situations. Descriptive theories aim to show how people actually make decisions. Because the cognitive capacity is limited, or at least is not always used efficiently, actual decisions are often suboptimal compared with the decisions prescribed by formal theories.

The first descriptive model of decision making under uncertainty was proposed by Edwards in 1954. The subjective equivalent utility (SEU) model assumes that people try to maximize their subjectively expected utility. The SEU of an option is the sum of the utilities of its consequences, weighted by the subjective probabilities of their occurrence. The decision maker is assumed to choose the option with the highest SEU value. In 1979, Kahneman and Tversky proposed prospect theory (PT) as an updated version of the SEU model. The theory sticks to the assumption that decisions are determined by the values and probabilities of their consequences but takes into account the many observations of decision-making behaviors that do not concur with the SEU model. PT has become very influential, particularly in the economic and medical domain. In 2002, Kahneman was awarded the Nobel Prize in economics, primarily for this theory (Tversky had died in 1996). The essential elements of PT are the value function and the decision weight function. With respect to the value factor, PT assumes that people mentally code the potential outcomes of options in relation to a reference point, that is, the status quo or the aspiration level. Outcomes above the reference point are coded as gains and outcomes below the reference point are coded as losses. Gains and losses are evaluated according to a value function that has two properties. First, the function is concave over gains and convex over losses; that is, additional gains please less, and additional losses hurt less. Second, the function is steeper over losses than over gains; that is, a loss of $100 hurts more than a gain of $100 pleases. With respect to the probability factor, PT assumes that subjective probabilities of outcomes are transformed into weights that represent the significance of the occurrence of the outcome. For instance, many people weigh the transition from a 0.99 probability to certainty (1.00) as heavier than a transition from a 0.41 probability to a 0.42 probability. PT provides explanations for a number of empirical phenomena that often are considered as irrationalities or anomalies, particularly in economics. Examples include the finding that preferences are not invariant with respect to their verbal description (i.e., framing effect) and the finding that investors sell winner stocks too fast and hold loser stocks too long (i.e., disposition effect).

An alternative theory, image theory, was proposed in 1990 by Beach. Image theory has become very popular in management and business schools. Beach assumed that people apply an optimizing strategy like the one proposed in PT, only under very special conditions. More often, people examine whether a new option is compatible with their goals and plans (called images) and accept and implement the option if that is the case. If the option is not compatible and violates important features, other options are searched and explored. When people are confronted with a number of options, they first screen out the ones that are incompatible with goals and plans, and only if more than one option remains do they try to identify the optimal one.

Other researchers have also pointed out that in real life, optimizing decision making is the exception rather than the rule. Features of the problem and the situation are often more important than the potential consequences of a decision. For instance, the behavior of managers in organizations is strongly determined by rules. The decisions of consumers are often determined by affects. In ethical conflicts, decisions are primarily determined by basic values, such as honesty and ‘‘do not harm,’’ irrespective of the consequences.

Still another approach focuses on what is called naturalistic decision making, denoting the process by which people use their experience to make decisions in complex and dynamic environments, often under time pressure and involving high risks (e.g., pilot decisions on the flight deck). For such situations, in 1993, Klein proposed a recognition primed decision model that involves recognition of cue patterns that leads to retrieval of a response option. Serial evaluation of single options is considered typical, and the first option that matches the decision maker’s goals and the situational constraints is chosen.

Models of organizational decision making describe decision making by both single and multiple actors in an organizational context. The normative rational (classical) model assumes that the organization follows a computational value-maximizing decision-making strategy. The model’s usefulness is limited to a small set of situations with specific characteristics (e.g., goals can be described in quantitative terms); consequently, alternative models were developed based more on the actual behavior of decision makers in organizations. For instance, the (behavioral) organizational model focuses on the limited information-processing capacity of decision makers and postulates an outcome satisfying strategy. In addition, the garbage can model conceives of organizations as ‘‘organized anarchies’’ (e.g., having inconsistent goals). Universities are considered the prototype of such organizations that do not follow one specific decision-making strategy. Outcomes result from the variable participation of their various members and groups in continually changing tasks. All of these models differ in their capacity to cope with different degrees of uncertainty and conflict among interests.

7. Methods

Decision researchers use a variety of quantitative and qualitative methods to examine how people make decisions. Experimental studies in the lab usually ask participants to make judgments about values and importance as well as about uncertainties and risks, to make choices among given options, and to evaluate options, search for information about options, or distribute goods. Reaction times, eye movements, and other behavioral data (including verbal reports) are also used as measures of the information-processing activity of participants. Outside of the lab, the questionnaire is the dominant method, where either decision problems are presented by the researcher, and participants provide the required responses (e.g., students in a lecture) or decision situations arise and the researcher observes and records participants’ behavior (e.g., pilots in a cockpit).

8. Areas Of Application

The examples provided in this research-paper for illustrative purposes have indicated some of the areas where decision making has been studied and where concepts and findings of decision research have been applied. More systematically, one may distinguish the following major domains: (a) behavioral economics and finance (e.g., investment and savings decisions); (b) business, administration, and management (e.g., employment, organizational, and product decisions; strategic planning with scenarios; communication of decisions; distributed decision making; cultural differences in decision making); (c) marketing and consumer behavior (e.g., product advertising, labeling, and pricing decisions; consumers’ allocation of their scarce means over various commodities and services; consumers’ decisions to acquire, consume, and dispose of products, services, and time); (d) health and medicine (e.g., addictive behaviors such as smoking, drugs, and alcohol; cancer screening campaigns; physicians’ use of probabilistic information; diagnostic and treatment decisions; informed consent; shared decision making); (e) aviation, military command, and firefighting (e.g., pilot crew decisions and decision-aiding systems; battle commander decisions; general aviation safety decisions); (f) high-risk facilities (e.g., operator decisions in nuclear power and chemical plants; emergency and general safety-related organizational decisions); (g) environmental issues (e.g., individuals’ benign attitudes and destructive behaviors; governmental decisions and their implementation; communication between the public and the experts); (h) ethical and justice issues (e.g., organ transplantation decisions; business ethics; conflicts between self-interest and the other; dilemmas in risk communication); (i) advice, consulting, and counseling (e.g., decision advice in medical and financial problems; decision consulting for companies and agencies; genetic or abortion counseling for potential parents).

9. Conclusion

Approximately 50 years ago, the study of decision making started with lab experiments examining how people make choices among monetary gambles. Since then, the scope of studies has been extended immensely, reflecting the increasing importance of understanding and improving decision making in our society as well as the progress of methodology and model construction within the research community. However, the extension of the field has also eroded the idea of a general theory of decision making in favor of situation and domain-specific models and empirical research on the conditions under which the various modes and strategies are being applied.

References:

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