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Integrating latent variables in discrete choice models: How higher-order values and attitudes determine consumer choice

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  • Temme, Dirk
  • Paulssen, Marcel
  • Dannewald, Till

Abstract

Integrated choice and latent variable (ICLV) models represent a promising new class of models which merge classic choice models with the structural equation approach (SEM) for latent variables. Despite their conceptual appeal, to date applications of ICLV models in marketing are still rare. The present study on travel mode choice clearly demonstrates the value of ICLV models to enhance understanding of choice processes. In addition to the usually studied directly observable variables such as travel time, we show how abstract motivations such as power and hedonisms as well as attitudes such as a desire for flexibility impact on travel mode choice. Further, we can show that it is possible to estimate ICLV models with the widely available structural equation modeling package Mplus. This finding is likely to encourage wider usage of this appealing model class in the marketing field.

Suggested Citation

  • Temme, Dirk & Paulssen, Marcel & Dannewald, Till, 2007. "Integrating latent variables in discrete choice models: How higher-order values and attitudes determine consumer choice," SFB 649 Discussion Papers 2007-065, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  • Handle: RePEc:zbw:sfb649:sfb649dp2007-065
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    References listed on IDEAS

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    Cited by:

    1. Bouscasse, Hélène & de Lapparent, Matthieu, 2019. "Perceived comfort and values of travel time savings in the Rhône-Alpes Region," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 370-387.
    2. Olaru, Doina & Smith, Brett & Taplin, John H.E., 2011. "Residential location and transit-oriented development in a new rail corridor," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(3), pages 219-237, March.
    3. Tran, Yen & Yamamoto, Toshiyuki & Sato, Hitomi, 2020. "The influences of environmentalism and attitude towards physical activity on mode choice: The new evidences," Transportation Research Part A: Policy and Practice, Elsevier, vol. 134(C), pages 211-226.
    4. Luis Márquez & Víctor Cantillo & Julián Arellana, 2020. "Assessing the influence of indicators’ complexity on hybrid discrete choice model estimates," Transportation, Springer, vol. 47(1), pages 373-396, February.
    5. Bouscasse, H., 2018. "Integrated choice and latent variable models: A literature review on mode choice," Working Papers 2018-07, Grenoble Applied Economics Laboratory (GAEL).
    6. Hélène Bouscasse, 2018. "Integrated choice and latent variable models: A literature review on mode choice," Working Papers hal-01795630, HAL.

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    More about this item

    Keywords

    Hybrid choice models; Mode choice; Values; Value-attitude hierarchy; Mplus;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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