Behavioural Choice Group
The BCG will focus on the integration of process and outcome choice analysis, which is central to the development of the next generation of discrete choice models using both revealed preference and stated choice data. The theoretical and econometric research developments will be tested in a number of disciplinary contexts, beginning with transport, accounting and finance.
The fast pace at which discrete choice models have been developing since open-form simulation methods became widely available has left some of the fundamental behavioural building blocks somewhat lagging behind. One area of growing interest is the manner in which we assume individual's process information that is subsequently included in a choice model. Despite a growing number of studies focusing on these issues (see for example Cantillo et al. 2006, Hensher 1983, Swait 2001), the entire domain of every attribute and alternative is treated as relevant to some degree and included in the utility expressions for every individual. While acknowledging the extensive study of nonlinearity in attribute specification which permits varying marginal (dis)utility over an attribute's range, including account for asymmetric preferences under conditions of gain and loss, this is not the same as establishing ex ante the extent to which a specific attribute might be totally excluded from consideration for all manner of reasons, including the impost of the design of a choice experiment when stated choice data is being used.
The impetus to set up a behavioural choice group (BCG) to focus on process rules, treated endogenously, that individuals adopt in assessing a choice experiment and making a choice, is consistent with the contribution that prospect theory has made to understanding behavioural response since Kahneman and Tversky's 1979 pioneering research. Most psychological theories of choice assume a dual-phase model of the decision-making process (Houston et al.1989, Kahneman and Tversky, 1979, Thaler, 1999). The first phase relates to the editing of the problem. The second phase relates to the evaluation of the edited problem. The main function of the editing operations is "to organize and reformulate the options so as to simplify subsequent evaluation and choice" (Kahneman and Tversky, 1979, p. 274). The main function of the evaluation operations is to select the preferred alternative. Similarly, in other behavioural paradigms such as the 'Cancellation and Focus Model of Choice' (Houston et al., 1989, Bonini et al. 2004), it is assumed that people cancel features shared by the alternatives (within bounds that allow for just noticeable difference), and focus evaluation on the remaining attributes.
References
Arentze, T., Borgers, A., Timmermans, H. and DelMistro, R. (2003): 'Transport Stated Choice Responses: Effects of Task Complexity, Presentation Format & Literacy', Transportation Research, 39E, 229-244.
Bonini, N., Tentori, K. and Rumiati, R. (2004): 'Contingent Application of The Cancellation Editing Operation: The Role of Semantic Relatedness Between Risky Outcomes', Journal of Behavioral Decision Making, 17, 139-152.
Cantillo, V., Heydecker, B. and Ortuzar, J. de Dios (2006): 'A Discrete Choice Model Incorporating Thresholds for Perception in Attribute Values', Transportation Research B, 40 (9), 807-825.
Hallahan, K. (1999): 'Seven Models of Framing: Implications for Public Relations', Journal of Public Relations Research, 11(3), 205-242.
Hensher, D.A. (2006a): 'How Do Respondents Handle Stated Choice Experiments? - Attribute Processing Strategies under Varying Information Load', Journal of Applied Econometrics, 21, 861-878
Hess, S., Rose, J. M. and Hensher, D.A. (2008) Asymmetrical preference formation in Willingness to Pay Estimates in Discrete Choice Models (presented only at ETC2006 Strasbourg and TRB 2007), Transportation Research E.
Houston, D. A., Sherman, S. J. and Baker, S. M. (1989): 'The Influence of Unique Features and Direction of Comparison on Preferences', Journal of Experimental Social Psychology, 25, 121-141.
Kahneman, D. and Tversky, A. (1979) Intuitive prediction: biases and corrective procedures. In S. Makridakis and S. C. Wheelwright, Eds., Studies in the Management Sciences: Forecasting, 12 (Amsterdam: North Holland).
Prelec, D. (1998): 'The Probability Weighting Function', Econometrica, 66, 497-527.
Swait, J. (2001): 'A Non-Compensatory Choice Model Incorporating Attribute Cut-Offs', Transportation Research B, 35(10), 903-928.
Swait, J. and Adamowicz, W. (2001): 'The Influence of Task Complexity on Consumer Choice: A Latent Class Model of Decision Strategy Switching', Journal of Consumer Research, 28, 135-148.
Thaler, R. (1999): 'Mental Accounting Matters'. Journal of Behavioral Decision Making, 12, 183-206.