Establishing the relevance of non-compensatory choice algorithms from stated choice surveys – an exploration

Abstract

In applied sciences large-scale surveys are a popular means to acquire insights in the choices that people make in different contexts. In transportation research, for example, tens of thousands stated their choices between alternatives characterized by cost and time attributes. In this study I explore the extent to which the data acquired in such studies may exhibit the co-occurrence of different choice algorithms within such survey populations. For that purpose I propose a novel version of the outcome-oriented approach. It is applied to the outcomes of two Dutch value-of-time surveys. If the recorded choice patterns are viewed apart, most could be the result of several different algorithms, in line with the main criticism of the outcome-oriented approach. The novel version considers the causal relationships between an individual’s personal circumstances, his use of a particular algorithm and the resulting choice pattern. It employs inferential statistics for analyses of the frequencies of the expected and actually recorded choice patterns within groups of respondents. Applied to the Dutch survey results this allowed disentangling, at the aggregate level, the overlap in explaining compensatory and non-compensatory algorithms to a large extent. It revealed that weighted additive (WADD) algorithms incorporating different degrees of loss aversion could explain most recorded choice behaviour while none of the many non-compensatory algorithms that were considered yielded a more than marginal explanation. Replications of this study, preferably by re-analysing other large-scale surveys with more complicated choice sets, is recommended to find out whether or not these findings are incidental.

Keywords

• outcome-oriented approach
• non-compensatory decision rule
• lexicographic rule
• Elimination-by-Aspects
• random choice
• human error
• value of time
• loss aversion