Attributes that are common, or overlapping, across alternatives in two-alternative forced preferential choice tasks are often non-diagnostic. In many settings, attending to and evaluating these attributes does not help the decision maker determine which of the available alternatives is the most desirable. For this reason, many existing behavioural theories propose that decision makers ignore common attributes while deliberating. Across six experiments, we find that decision makers do direct their attention selectively and ignore attributes that are not present in or associated with either of the available alternatives. However, they are as likely to attend to common attributes as they are to attend to attributes that are unique to a single alternative. These results suggest the need for novel theories of attention in preferential choice.This network project brings together economists, psychologists, computer and complexity scientists from three leading centres for behavioural social science at Nottingham, Warwick and UEA. This group will lead a research programme with two broad objectives: to develop and test cross-disciplinary models of human behaviour and behaviour change; to draw out their implications for the formulation and evaluation of public policy. Foundational research will focus on three inter-related themes: understanding individual behaviour and behaviour change; understanding social and interactive behaviour; rethinking the foundations of policy analysis. The project will explore implications of the basic science for policy via a series of applied projects connecting naturally with the three themes. These will include: the determinants of consumer credit behaviour; the formation of social values; strategies for evaluation of policies affecting health and safety. The research will integrate theoretical perspectives from multiple disciplines and utilise a wide range of complementary methodologies including: theoretical modeling of individuals, groups and complex systems; conceptual analysis; lab and field experiments; analysis of large data sets. The Network will promote high quality cross-disciplinary research and serve as a policy forum for understanding behaviour and behaviour change.
Experimental data. In Experiment 1 we offered participants choices between two alternatives, defined on a set of attributes. After decision makers had seen the alternatives and the attributes, we tested whether they were better at recalling the attributes that were common, unique, or absent in their choice set. One hundred participants were recruited through Amazon Mechanical Turk and performed the experiment online. All participants were English speakers living in the United States. The goal of Experiments 2 and 3 is to test the robustness of the results in Experiment 1. Experiment 2 utilizes a different choice domain and additionally modifies the presentation of the choice stimuli, so as to include an explicit symbol to indicate attribute absence. Experiment 3 considers settings with a higher number of unique and common attributes and correspondingly smaller number of absent attributes. The goal of Experiment 4 is to observe attention during the decision process itself.uses a Mouselab interface that allows us to observe information acquisition during deliberation. Experiment 5 presents choices similar to those used in Experiments 1, 3, and 4, but varies the number of common versus absent attributes in the choice. Additionally, it measures total decision time instead of attribute recall or click-based information acquisition. Fifty participants performed the experiment in a behavioural laboratory at a British university. Participants were recruited from the university’s experimental participant pool. In Experiment 6 we study both attention in forced choices and attention in free choices, using a design similar to that of Experiments 1–3.
