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Risky weighting in discrete choice

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journal contribution
posted on 2017-05-26, 10:23 authored by Baibing LiBaibing Li, David A. Hensher
This paper presents a new approach to discrete choice analysis for risky prospects. Conventional discrete choice analysis focuses on riskless prospects and does not deal with the scenario where the alternatives that the decision-makers choose from are associated with risk. In this paper, we investigate decision-makers’ risk perception and choice behaviour in choice experiments when they are facing several risky prospects. We propose a broad class of cumulative risky weighting functions, upon which a unified cumulative risky weighting function is developed. We show that this unified cumulative risky weighting function includes several existing cumulative risky weighting functions as special cases. We then develop a multivariate method for choice analysis with risky prospects to account for decision-makers’ individual-specific risk perception and the impact of various factors on the value function respectively. We illustrate the developed method using an empirical study on road tolling in Australia.

History

School

  • Business and Economics

Department

  • Business

Published in

Transportation Research Part B: Methodological

Volume

102

Pages

1 - 21 (21)

Citation

LI, B. and HENSHER, D.A., 2017. Risky weighting in discrete choice. Transportation Research Part B: Methodological, 102, pp. 1-21.

Publisher

© Elsevier

Version

  • AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

2017-04-25

Publication date

2017-05-16

Copyright date

2017

Notes

This paper was published in the journal Transportation Research Part B: Methodological and the definitive published version is available at https://doi.org/10.1016/j.trb.2017.04.014.

ISSN

0191-2615

Language

  • en