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The role of the reference alternative in the specification of asymmetric discrete choice models

Author

Listed:
  • Lorenzo Masiero

    (Institute for Economic Research (IRE), Faculty of Economics, University of Lugano, Switzerland)

  • John M. Rose

    (Institute of Transport and Logistics Studies (ITLS), Faculty of Economics and Business, The University of Sydney, Australia)

Abstract

Within the discrete choice modelling literature, there has been growing interest in including reference alternatives within stated choice survey tasks. Recent studies have investigated asymmetric utility specifications by estimating discrete choice models that include different parameters according to gains and losses relative to the values of the reference attributes. This paper analyses asymmetric discrete choice models by comparing specifications expressed as deviations from the reference point and specifications expressed in absolute values. The results suggest that the selection of the appropriate asymmetric model specification should be based on the type of the stated choice experiment.

Suggested Citation

  • Lorenzo Masiero & John M. Rose, 2011. "The role of the reference alternative in the specification of asymmetric discrete choice models," Quaderni della facoltà di Scienze economiche dell'Università di Lugano 1104, USI Università della Svizzera italiana.
    • Handle: RePEc:lug:wpaper:1104
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    Cited by:

    1. Ferrari, Paolo, 2014. "The dynamics of modal split for freight transport," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 163-176.
    2. Xueyan Li & Jing Li, 2021. "A freight transport price optimization model with multi bounded-rational customers," Transportation, Springer, vol. 48(1), pages 477-504, February.
    3. Haghani, Milad & Bliemer, Michiel C.J. & Rose, John M. & Oppewal, Harmen & Lancsar, Emily, 2021. "Hypothetical bias in stated choice experiments: Part II. Conceptualisation of external validity, sources and explanations of bias and effectiveness of mitigation methods," Journal of choice modelling, Elsevier, vol. 41(C).
    4. Sotirios Thanos & Maria Kamargianni & Andreas Schäfer, 2018. "Car Travel Demand: Spillovers and Asymmetric Price Effects in a Spatial Setting," Transportation Science, INFORMS, vol. 52(3), pages 621-636, June.
    5. Punel, Aymeric & Stathopoulos, Amanda, 2017. "Modeling the acceptability of crowdsourced goods deliveries: Role of context and experience effects," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 105(C), pages 18-38.
    6. Jang, Sunghoon & Hong, Doosun & Jung, Yeonwoo & Lee, Chungwon, 2024. "Exploring reference-dependency in route switching behavior on intercity travel: Endowment effect and disparities between willingness to pay and willingness to accept," Transport Policy, Elsevier, vol. 155(C), pages 224-233.
    7. Jawaher Binsuwadan & Gerard De Jong & Richard Batley & Phill Wheat, 2022. "The value of travel time savings in freight transport: a meta-analysis," Transportation, Springer, vol. 49(4), pages 1183-1209, August.
    8. Ferrari, Paolo, 2015. "Dynamic cost functions and freight transport modal split evolution," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 77(C), pages 115-134.
    9. Feo-Valero, María & Arencibia, Ana Isabel & Román, Concepción, 2016. "Analyzing discrepancies between willingness to pay and willingness to accept for freight transport attributes," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 89(C), pages 151-164.
    10. Ding, Hongxing & Yang, Hai & Xu, Hongli & Li, Ting, 2023. "Status quo-dependent user equilibrium model with adaptive value of time," Transportation Research Part B: Methodological, Elsevier, vol. 170(C), pages 77-90.
    11. Milad Haghani & Michiel C. J. Bliemer & John M. Rose & Harmen Oppewal & Emily Lancsar, 2021. "Hypothetical bias in stated choice experiments: Part II. Macro-scale analysis of literature and effectiveness of bias mitigation methods," Papers 2102.02945, arXiv.org.
    12. Mahmud, Asif & Gayah, Vikash V. & Paleti, Rajesh, 2022. "A latent choice model to analyze the role of preliminary preferences in shaping observed choices," Transportation Research Part B: Methodological, Elsevier, vol. 161(C), pages 95-108.
    13. Ferrari, Paolo, 2016. "Instability and dynamic cost elasticities in freight transport systems," Transport Policy, Elsevier, vol. 49(C), pages 226-233.
    14. Hongli Xu & Hai Yang & Jing Zhou & Yafeng Yin, 2017. "A Route Choice Model with Context-Dependent Value of Time," Transportation Science, INFORMS, vol. 51(2), pages 536-548, May.

    More about this item

    Keywords

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    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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