Processes of Adaptivity in Decision Making

James R. Bettman, Duke University
[ to cite ]:
James R. Bettman (1988) ,"Processes of Adaptivity in Decision Making", in NA - Advances in Consumer Research Volume 15, eds. Micheal J. Houston, Provo, UT : Association for Consumer Research, Pages: 1-4.

Advances in Consumer Research Volume 15, 1988      Pages 1-4

PROCESSES OF ADAPTIVITY IN DECISION MAKING

James R. Bettman, Duke University

In my opinion, one of the most fascinating aspects of human behavior is individuals' ability to adapt to a wide variety of environmental conditions. At a macro level, such flexibility in early man (e.g., willingness to eat a variety of foods) may have played a major role in the survival of the species (Calvin, 1986). However, at a more micro level, individuals also learn to adapt. Individuals appear to fit their behavior to their environments almost effortlessly and with exquisite precision. Adaptivity is viewed as a mark of intelligence; in fact, failure to adapt often stands out as unusual. Despite the importance and prevalence of the phenomenon of adaptivity, the process of adaptation is not well understood or researched. Amazingly little is known about how adaptation occurs, yet how people adapt is a major issue of self-regulation of behavior (Mischel, 1973). Through what process do individuals assess the properties of environments, monitor their behavior, gauge the degree of fit, and ultimately adapt?

I wish to address this broad issue of the processes of adaptation, with particular emphasis on adaptivity in decision making. In doing so, I will attempt to examine both conceptual issues and needed areas of research. These ideas flow from work on adaptivity I have done jointly over the past several years with John Payne and Eric Johnson, and they have had an extensive influence on these notions.

I believe that further understanding of the process of adaptivity is very important for research on consumer decision making. For example, for more than ten years research on information overload (e.g., Jacoby, Speller, and Kohn 1974; Staelin and Payne 1976, Malhotra 1982; Keller and Staelin 1987) has attempted to document how consumers respond to differing amounts of information. There has been a great deal of disagreement as to the meaning of these data, however (c.g., Russo 1974; Wilkie 1974, Jacoby 1984). No one has directly tried to address the process by which consumers adapt to information load. It is my contention that examining this process could lead to important new insights into responses to information load and other areas of research on contingent consumer decision making.

AN ACCURACY/EFFORT APPROACH TO ADAPTIVITY

One approach to adaptivity in decision making is to frame the issue as how one decides to decide (Beach and Mitchell 1978; Russo and Dosher 1983; Johnson and Payne 1985; Payne, Bettman, and Johnson 1988). This approach has recently become of great interest to cognitive psychologists in general (e.g., Siegler 1986; Reder 1987). The basic approach taken is to argue that decision makers trade off accuracy and effort considerations. In deciding how to decide, a decision maker is thought to consider the costs of various strategies (mainly the effort involved in executing them) and the benefits of the strategies (how likely the strategy is to result in one's choosing the best alternative) for the particular environment. The most straightforward and simple conceptualization of such an approach is that decision makers have a repertoire of strategies whose accuracy and required effort can be ascertained or are known for a particular task environment. Then that strategy is selected which best meets the individual's desired trade-off between accuracy and effort. Adaptivity occurs because accuracy, effort, and the desired trade-off may vary over different decision environments.

In the course of our research on this general approach, it has become clear that this simple view is too confining. While we still espouse an accuracy/effort viewpoint and the idea of multiple strategy use, we have begun to consider several broader concerns which lead to a more complex view of that framework.

The essence of adaptivity, as noted above, is adjustment to environmental conditions (Payne 1982). Such adjustment involves several components, of which two will be the focus of further attention in this address: assessing the nature of the environment and evaluating how well one is doing. The accuracy/effort view presented above does not specify these more basic processes in any detail. How one determines the costs or benefits of a strategy is not specified, for example.

How sensitive individuals are to the nature of the environment and how well they can assess that environment are important questions. If one is to actively adjust to a particular set of circumstances, one must be able to notice both regularities and unusual circumstances in that setting. The simple accuracy/effort approach outlined above implies that individuals should be able to characterize the properties of different environments which might affect decision strategies, but how this is done is not considered. In addition, not all adaptivity may be active. Environments place constraints on behavior, so that some behaviors may simply not be possible under some conditions. For example, a complete examination of all available information may not be possible under time pressure. Hence, the role of the environment and individuals' sensitivity to it raises several broad and fascinating questions.

In order to adapt, individuals must determine, even if roughly, how well they are doing. The notion of adjustment via accuracy/effort tradeoffs implies that one must be able to generate some vague ideas about the degree of effort and accuracy characterizing one's decision process. Although current accuracy/effort approaches do not consider this process in any detail, several very interesting issues arise in considering how such information might be generated.

The focus of this address will be on the two areas of adaptive behavior raised briefly above: assessing the environment, and how one assesses how well one is doing. Following a discussion of these issues, the degree to which decision makers adapt successfully is considered.

THE ENVIRONMENT AND ADAPTIVITY

One process underlying adaptivity is assessing the properties of the task environment. The general question is what decision makers notice about decision environments. For example, whether decision makers perceive covariation, relationships among various alternatives, or other aspects of the choice setting could be considered. One approach to this broad issue is the notion of editing processes. The implications of a constructive approach (Bettman 1979) to editing will be developed.

Editing processes have been proposed as an important component of choice (Kahneman and Tversky 1979; Goldstein and Einhorn 1987), with individuals supposedly editing choice problems into simpler form before choosing. Editing could involve dropping outcomes which are identical across alternatives, eliminating some alternatives, or eliminating redundant attributes, for example. To the extent that editing can simplify choice, it is potentially a major component of adaptivity to different choice environments.

Whereas Kahneman and Tversky (1979) and Goldstein and Einhorn (1987) argue that editing processes come first, with alternatives edited and then simplified options evaluated, we argue instead that editing is opportunistic (Hayes-Roth and Hayes-Roth 1979). Editing may occur throughout a choice whenever individuals notice some structure in the choice environment that can be exploited. Hence, editing can be a bottom-up process, driven by the data, as well as a priori or top-down. Editing processes may be involved earlier in the decision process the more experience one has in a given choice environment (Johnson and Russo 1984).

Editing is probably also adaptive, in that the particular editing operations used may be a function of the immediately preceding processing. That is, different types of processing will leave different traces in short-term memory, and these traces will be more or less compatible with different editing operations. For example, processing a pair of alternatives one attribute at a time and noticing how one compares to the other OD each attribute would enable the detection of dominance, whereas processing each alternative in its entirety without direct comparison to the other would discourage such detection. Hence, different choice strategies enable different editing operations. Therefore, different choice environment properties will affect editing because they affect processing. This is likely to be particularly true for the effects of information display. Slovic (1972) has argued for a principle of concreteness, that individuals tend to use information in the form in which it is displayed. To the extent this is true, display should exert a strong influence on editing processes by encouraging or discouraging various types of processing.

This view of editing is quite flexible and implies a different conceptualization of strategy usage than the simple view outlined above. Rather than a priori selection from a repertoire of strategies, a very top-down approach, the opportunistic view of editing implies a more constructive view of choice (Bettman 1979; Bettman and Zins 1977). This view implies that people develop simplifications and strategies as they progress in a decision process, rather than invoking them a priori. In addition, the opportunistic view is much more general than the current depiction of phased processes, which argues that one strategy is used first (such as EBA to eliminate alternatives) and another (usually compensatory) is used on the remaining alternatives. Our view of editing includes this as a special case.

According to our view, editing is a crucial component of adaptivity, since which regularities (if any) are noted and exploited can profoundly affect the course of the decision process. If strategies are constructed instead of selected, the sequence of editing operations will have a major impact on the resultant process (Tversky, Sattath, and Slovic 1987).

Amazingly, however, almost nothing is known about editing processes. Such research topics as what features of a decision task are noticed and exploited and how this changes with display format would seem both natural and important. In general, studies of the determinants of focus of attention in decision problems could be extremely valuable.

The above discussion has focused on a decision maker actively noting and consciously adapting to an environment. However, adaptivity will not necessarily always be active. To the extent a choice environment is severely constrained, a very limited set of approaches may be possible. For example, under very severe time pressure, only strategies which look at a small subset of the available information may even be possible. In effect the environment selects out non-feasible approaches. Within the set of feasible strategies, the individual may still, of course, rely on accuracy/effort considerations in developing his or her preferred approach.

The individual's focus of attention may also be less actively controlled by the individual than implied above. Attention may be much more under the control of features of the choice environment in low involvement decisions, for example, with the decision maker exerting more control under high involvement.

ASSESSING HOW WELL ONE IS DOING

Individuals could make trade-offs involving accuracy and effort in several ways. In some situations, individuals might be given explicit feedback about accuracy and effort. Given such feedback, decision makers could then make conscious accuracy/effort tradeoffs. This view externalizes the problem of assessing how well one is doing by assuming that information about accuracy and effort is provided and hence need not be generated. While such a view might characterize some laboratory situations, it does not seem particularly generalizable.

Most common decision situations do not explicitly provide clear feedback to the decision maker (Einhorn 1980). Rather, individuals must somehow generate their own feedback about accuracy and effort. This process is not too difficult to imagine for effort. In the course of making a decision, individuals can generate process feedback (Anzai and Simon 1979). That is, a decision maker can probably ascertain fairly well how effortful a particular decision was. Such indicants as elapsed time and self-rated effort are readily available.

Self-generation of accuracy feedback is not quite so obvious. If the decision maker immediately experienced the outcome of the choice, some indication of the goodness of the decision would be available. Such self-generated accuracy feedback could then be used to modify one's behavior, if necessary, the next time a similar decision was made. However, there are other types of choices where feedback about outcomes is not readily available. In some situations, multiple choices must be made where experiencing the outcomes or receiving feedback about them is deferred (e.g., purchasing several types of wine for a dinner party or buying gifts). In other cases, one may not feel confident about judging the goodness of an outcome (e.g., what effects a particular health food is having). Finally, it may often be difficult for one to assess how relatively good an outcome is without some basis for comparison. Since there are a variety of such circumstances where feedback about outcomes is not available, it would seem that an additional process for self-generation of accuracy feedback is necessary.

We propose a process for assessing how well one is doing that seems generally applicable in most decision situations. We assume that individuals have general knowledge of the properties of a reasonable strategy. For example, decision makers might believe that in general one should first look at the most important information for all alternatives, and then look at other information as desired or as time allows. Then, during the course of making a decision, the individual could not only ascertain the effort required, but could also determine how closely their decision process resembled their notion of what a "good" strategy should entail. In the absence of environmental constraints, the match between the strategy used and notions of a "good" strategy should presumably be close and the accuracy assessment would be "high". However, if there were severe environmental constraint (e.g. great time pressure), the individual may feel that the strategy, either as executed or while executing, did not match their notion of a reasonable strategy. For example, important information may not have been examined because time ran out. The individual could then adjust his or her decision process to be more in line with their notion of strategy reasonableness. This adjustment could be made either on-line or the next time such a decision was faced. Hence, the decision maker potentially has access to a fairly rich data base about the course of his or her decision process, and such process feedback can lead to self-generated information about both effort and accuracy.

The decision maker could use such self-generated information in several ways. As noted above, an individual could adjust his or her process in the midst of a decision if things were not going well. Alternatively, the individual might decide to adjust his or her approach the next time the same or a related decision occurred. Note that there are two general processes of adjustment based on accuracy implied above: changes based upon the outcomes of particular decisions, and changes based upon goodness of the process. The latter kind of adjustment, that based upon process, may have broader effects on adaptivity across situations, since adjustments based upon notions of a "good" process may be easier to generalize.

Reder (1987) has also recently considered strategy changes without explicit feedback. She proposes a "feeling of knowing" process which is related to the ideas above. That is, she argues that people may develop strategies that are adaptive to different decision environments by trying to minimize effort while maintaining a feeling of knowing that a reasonable decision is being made.

These notions imply several potential areas for research. One such area is directly studying how properties of decision environments are related to individuals' ideas about reasonable strategies for those environments. A second area is to study self-reports of accuracy or feeling of knowing and see how well-calibrated such self-reports are and how they are affected by decision task properties.

DEGREE OF ADAPTIVITY

The discussions above imply several sorts of knowledge that decision makers might have that would foster adaptivity: (1) Knowing the characteristics of a "reasonable" decision strategy, both generally and with respect to specific decision environments; (2) Information about the relative effort required for various decisions; (3) Rules of thumb for editing operations to simplify choice; (4) Pieces or components of decision processes that could be put together constructively to form an overall approach to a decision. Such knowledge would presumably be more extensive the more experience one had in a decision domain. It is closely related to the notion of tacit knowledge developed by Wagner and Sternberg (1985), in that it is knowledge which is not usually formally taught but is extremely helpful in real-world pursuits. One implication, of course, is that such components of tacit knowledge relating to adaptivity might be very fruitful targets for consumer education. I would argue that investigations of such knowledge and the processes underlying adaptivity form an important agenda for research on consumer decision making. Adaptivity is a central process, and understanding how individuals adapt is crucial.

Finally, the issue of how well individuals can adapt is implicit in much of the above. The literature is replete with biases, errors, and other horrors to which decision makers seem surprisingly susceptible. One might be led to believe that discussing adaptivity is useless because people will "adapt" inefficiently in any case. In our research thus far, however, that has not been the case. In studies of adaptation to time pressure and dispersion in the probabilities of the possible outcomes, decision makers were quite adaptive in directions representing efficient accuracy/effort tradeoffs (Payne, Bettman, and Johnson 1988). Similar results have been found for covariation assessments (Bettman, John, and Scott 1986). Thus, our results suggest that individuals can adapt in ways which are appropriate given fairly subtle changes in the structure of the decision problems they face. Decision makers appear to be flexible and creative in coping with the variety of tasks they face. Individuals may not be optimal processors of information, but they are often intelligent processors.

REFERENCES

Anzai, Yuichiro and Herbert A. Simon (1979), "The Theory of Learning by Doing," Psychological Review, 86 (March), 124-140

Beach, Lee R. and Terence R. Mitchell (1978), "A Contingency Model for the Selection of Decision Strategies," Academy of Management Review, 3, 439-449.

Bettman, James R. (1979), An Information Processing Theory of Consumer Choice, Reading, MA: Addison-Wesley.

Bettman, James R., Deborah Roedder John, and Carol A. Scott (1986), "Covariation Assessment by Consumers," Journal of Consumer Research, 13 (December), 316-326.

Bettman, James R. and Michel A. Zins (1977), "Constructive Processes in Consumer Choice," Journal of Consumer Research, 4 (September), 75-85.

Calvin, William H. (1986), The River That Flows Uphill, New York: Macmillan.

Einhorn, Hillel J. (1980), "Learning from Experience and Suboptimal Rules in Decision Making," in Cognitive Processes in Choice and Decision Behavior, ed. Thomas S. Wallsten, Hillsdale, NJ: Lawrence Erlbaum.

Goldstein, William M. and Hillel J. Einhorn (1987) "Expression Theory and the Preference Reversal Phenomena," Psychological Review, 94 (April), 236-254.

Hayes-Roth, Barbara and Frederick Hayes-Roth (1979), "A Cognitive Model of Planning," Cognitive Science, 3, 275-310.

Jacoby, Jacob (1984), "Perspectives on Information Overload," Journal of Consumer Research, 10 (March), 432-435.

Jacoby, Jacob, Donald E. Speller, and Carol A. Kohn (1974), "Brand Choice Behavior as a Function of Information Load: Replication and Extension," Journal of Consumer Research, 1 (June), 3342.

Johnson, Eric J. and John W. Payne (1985), "Effort and Accuracy in Choice," Management Science, 31 (April) 395-414.

Johnson, Eric J. and J. Edward Russo (1984), "Product Familiarity and Learning New Information," Journal of Consumer Research, 11 (June), 542-550.

Kahneman, Daniel and Amos Tversky (1979), "Prospect Theory: An Analysis of Decision Making Under Risk, Econometrica, 47 (March), 263-291.

Keller, Kevin Lane and Richard Staelin (1987), "Effects of Quality and Quantity of Information on Decision Effectiveness," Journal of Consumer Research, 14 (September), 200-213.

Malhotra, Naresh K. (1982), "Information Load and Consumer Decision Making," Journal of Consumer Research, 8 (March), 419-430.

Mischel, Walter (1973), "Toward a Cognitive Social Learning Reconceptualization of Personality," Psychological Review, 80 (July), 252-285.

Payne, John W. (19823, "Contingent Decision Behavior," Psychological Bulletin, 92 (September), 382-402.

Payne, John W., James R. Bettman, and Eric 1. Johnson (1988), "Adaptive Strategy Selection in Decision Making," Journal of Experimental Psychology: Learning, Memory, and cognition, 14(July).

Reder, Lynne M. (1987), "Strategy Selection in Question Answering," Cognitive Psychology, 19 (January), 90-138.

Russo, J. Edward (1974), "More Information is Better A Reevaluation of Jacoby, Speller, and Kohn," Journal of consumer Research, 1 (December), 68-72.

Russo, J. Edward and Barbara Anne Dosher (1983), "Strategies for Multiattribute Binary Choice," Journal of Experimental Psychology: Learning, Memory, and Cognition, 9 (October), 676-696.

Slovic, Paul (1972), "From Shakespeare to Simon: Speculations and Some EvidenceCAbout Man's Ability to Process Information," Oregon Research Institute Monograph 12 (3).

Staelin, Richard and John W. Payne (1976), "Studies of Information Seeking Behavior of Consumers," in Cognition and Social Behavior, eds. John S. Carroll and John W. Payne, Hillsdale, NJ: Lawrence Erlbaum.

Tversky, Amos, Shmuel Sattath, and Paul Slovic (1987), "Contingent Weighting in Judgment and Choice," Office of Naval Research Technical Report.

Wagner, Richard K. and Robert J. Sternberg (1985), "Practical Intelligence in Real-World Pursuits: The Role of Tacit Knowledge," Journal of Personality and Social Psychology, 49 (August), 436-458.

Wilkie, William L (1974), "Analysis of Effects of Information Load," Journal of Marketing Research, 11 (November), 462-466.

----------------------------------------