An econometric model for estimating decision rules, choice of rules and influence of consistency

The hypothesis that people use different decision rules to adapt to decision problems has been well supported. However, most studies were carried out through experiments where decision rules were a priori given to the subjects, while the rules used by the decision makers are unobservable to the researcher from choice behavior in real environments. This paper first proposes an econometric modeling approach which estimates the probability distributions of decision rules from response patterns of choice. The approach assumes that the subject constructs a mental representation of the decision problem, which is constructed using threshold-based mechanism and used as the template for guiding information search and decision making. It is shown that, depending on the variation of the decision standard that discriminates two alternatives with certain amount of value, a spectrum of non-compensatory decision rules can be deduced from the representation, such as the conjunctive, disjunctive, and lexicographic rule. Then, the choice pattern is approached by the choice probability which is derived by assuming that the subject chooses a rule probabilistically and uses this rule for making the decision. Second, the paper focuses on explaining the distribution of the use of rules. A popular explanation is that people choose rules by trading off effort and accuracy (e.g., Payne, et al., 1988). With regard to accuracy, however, many decisions do not allow people to have feedbacks about the decision quality, in which people have to use a rule based on subjective feeling of its appropriateness (e.g., Karelaia, 2006). Consistency is an important component of such appropriateness. Two types of consistency are defined and hypothesized as the factors influencing the choice of rules. The first is called information consistency which is defined as the probability that the decision outcome based on collected attributes is the same as the outcome based on all attributes. If the trade-off between information consistency and effort is larger than some threshold value, the search for more attributes stops. Hence, the stopping rule directly relates to the evaluation of the expected effort of a rule. The second type of consistency is called defensibility consistency which is defined as the probability that using the same amount of information will generate the same outcome under all other decision standards, based on the consideration that a good decision should be robust against attacks from different views. The last factor is whether the rule leads to a definitive answer or random choice, hypothesizing that people prefer definitive choice due to a sense of control. It is assumed that the subject derives the utilities of the rules composed of the four factors and chooses the rules probabilistically based on the utilities. Finally, the model is illustrated on three real-world cases about pedestrians deciding to end shopping in shopping streets. Consistent results are derived, showing that pedestrians seek high information consistency in forming decision rules, and definiteness is the most important factor influencing rule choice.