Using eye tracking methods to understand decision-making heuristics in discrete choice experiments
Modern societies are characterised by an abundance of choices. In everyday life, people face many decision problems. Am I going to the office by car, bus, or on foot? Which brand of fruit juice do I need to buy? The complexity of these decision problems increases with the options available, and the number of features of each option. In applied economics, individuals’ choices are commonly used to elicit preferences for the attributes of the product/service under investigation. In health, preferences for health-related topics, such as medical treatments or jobs, are usually not readily observable. Stated preference methods, such as Discrete Choice Experiments (DCEs), can be used to overcome this limitation. Crucially the link between individuals’ choices and preferences is defined by an economic theory which makes assumptions about how individuals make decisions. This theory postulates that individuals (i) have a full understanding of the decision problem and (ii) adopt an optimising behaviour to make their decisions. Based on these assumptions it is possible to break down the choice of a particular product/service into the influence of its specific features (What is the role of price, quantity, or quality in my decisions?). However research on bounded rationality and information processing has questioned the validity of these assumptions. For example, previous studies show that people do not pay attention to all the available information when comparing products, suggesting that people only have a partial understanding of the decision problem. So far this literature has been largely ignored the analysis of individuals’ choices, especially in DCEs. Discrete choice models mainly focused on the outcomes of the decision making, i.e. observed choices, and paid little attention to the processes by which individuals make their decisions. This research project explores how individuals make choices and the implications of decision making processes for choice data analysis. We use neuro-psychological data collected with an eye-tracking machine. An eye-tracker is a process-tracking method, providing information about individuals’ (visual) attention while they complete DCE tasks. Eye movements, such as gaze duration, correspond to measures of the decisions making processes, and can be used in complement to choices which are measures of the decision making outcomes. New choice models describing both processes and outcomes of decision making are expected to provide a better account of individuals’ preferences.HERU researchers involved in this research project: Nicolas Krucien and Mandy Ryan
External Collaborator: Frouke Hermens (School of Psychology, University of Aberdeen)
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