Modeling the effect of task complexity on stated choice behavior allowing for differential sensitivity: comparison between utility and regret models

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

The aim of this paper is to better understand the effect of task complexity in experimental design on individual choice behavior. Although the scale factor in discrete choice models is generally normalized, studies have consistently pointed out that the imposed randomness on individual choice behavior varies as a function of task complexity. Therefore, several researchers incorporated the effect of task complexity by parameterizing the scale factor as an exponential function of task complexity. Consequently, choice behavior becomes more random with increased task complexity. Moreover, sensitivity to task complexity increases at an exponential rate with decreasing task complexity. In this paper, to relax these rigorous assumptions, the authors propose an alternative function that can be viewed as a generalization of the commonly used exponential function. The newly suggested approach is examined for both conventional utility-maximization and regret-minimization models. To assess the empirical performance of the proposed methodology, they designed a stated preference survey with seven task scenarios, differing in their degree of complexity. Estimation results evidence that the generalized parameterization of the scale factor as a function of task complexity better represents individuals’ stated choices in both utility and regret models.
Original languageEnglish
Title of host publicationTransportation Research Board 98th Annual Meeting
Number of pages22
Publication statusPublished - Jan 2019
Event98th Annual Meeting of the Transportation Research Board - Walter E. Washington Convention Center, Washington, D.C., United States
Duration: 13 Jan 201917 Jan 2019
https://www.eltis.org/participate/events/transportation-research-board-98th-annual-meeting

Conference

Conference98th Annual Meeting of the Transportation Research Board
CountryUnited States
CityWashington, D.C.
Period13/01/1917/01/19
Internet address

Fingerprint

Exponential functions
Parameterization
Design of experiments

Cite this

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title = "Modeling the effect of task complexity on stated choice behavior allowing for differential sensitivity: comparison between utility and regret models",
abstract = "The aim of this paper is to better understand the effect of task complexity in experimental design on individual choice behavior. Although the scale factor in discrete choice models is generally normalized, studies have consistently pointed out that the imposed randomness on individual choice behavior varies as a function of task complexity. Therefore, several researchers incorporated the effect of task complexity by parameterizing the scale factor as an exponential function of task complexity. Consequently, choice behavior becomes more random with increased task complexity. Moreover, sensitivity to task complexity increases at an exponential rate with decreasing task complexity. In this paper, to relax these rigorous assumptions, the authors propose an alternative function that can be viewed as a generalization of the commonly used exponential function. The newly suggested approach is examined for both conventional utility-maximization and regret-minimization models. To assess the empirical performance of the proposed methodology, they designed a stated preference survey with seven task scenarios, differing in their degree of complexity. Estimation results evidence that the generalized parameterization of the scale factor as a function of task complexity better represents individuals’ stated choices in both utility and regret models.",
author = "Sunghoon Jang and Soora Rasouli and Harry Timmermans",
year = "2019",
month = "1",
language = "English",
booktitle = "Transportation Research Board 98th Annual Meeting",

}

Jang, S, Rasouli, S & Timmermans, H 2019, Modeling the effect of task complexity on stated choice behavior allowing for differential sensitivity: comparison between utility and regret models. in Transportation Research Board 98th Annual Meeting. 98th Annual Meeting of the Transportation Research Board, Washington, D.C., United States, 13/01/19.

Modeling the effect of task complexity on stated choice behavior allowing for differential sensitivity : comparison between utility and regret models. / Jang, Sunghoon; Rasouli, Soora; Timmermans, Harry.

Transportation Research Board 98th Annual Meeting. 2019.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

TY - GEN

T1 - Modeling the effect of task complexity on stated choice behavior allowing for differential sensitivity

T2 - comparison between utility and regret models

AU - Jang, Sunghoon

AU - Rasouli, Soora

AU - Timmermans, Harry

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N2 - The aim of this paper is to better understand the effect of task complexity in experimental design on individual choice behavior. Although the scale factor in discrete choice models is generally normalized, studies have consistently pointed out that the imposed randomness on individual choice behavior varies as a function of task complexity. Therefore, several researchers incorporated the effect of task complexity by parameterizing the scale factor as an exponential function of task complexity. Consequently, choice behavior becomes more random with increased task complexity. Moreover, sensitivity to task complexity increases at an exponential rate with decreasing task complexity. In this paper, to relax these rigorous assumptions, the authors propose an alternative function that can be viewed as a generalization of the commonly used exponential function. The newly suggested approach is examined for both conventional utility-maximization and regret-minimization models. To assess the empirical performance of the proposed methodology, they designed a stated preference survey with seven task scenarios, differing in their degree of complexity. Estimation results evidence that the generalized parameterization of the scale factor as a function of task complexity better represents individuals’ stated choices in both utility and regret models.

AB - The aim of this paper is to better understand the effect of task complexity in experimental design on individual choice behavior. Although the scale factor in discrete choice models is generally normalized, studies have consistently pointed out that the imposed randomness on individual choice behavior varies as a function of task complexity. Therefore, several researchers incorporated the effect of task complexity by parameterizing the scale factor as an exponential function of task complexity. Consequently, choice behavior becomes more random with increased task complexity. Moreover, sensitivity to task complexity increases at an exponential rate with decreasing task complexity. In this paper, to relax these rigorous assumptions, the authors propose an alternative function that can be viewed as a generalization of the commonly used exponential function. The newly suggested approach is examined for both conventional utility-maximization and regret-minimization models. To assess the empirical performance of the proposed methodology, they designed a stated preference survey with seven task scenarios, differing in their degree of complexity. Estimation results evidence that the generalized parameterization of the scale factor as a function of task complexity better represents individuals’ stated choices in both utility and regret models.

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