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

Author

Listed:
  • Dirk Temme
  • Marcel Paulssen
  • Till Dannewald

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

  • Dirk Temme & Marcel Paulssen & Till Dannewald, 2007. "Integrating latent variables in discrete choice models – How higher-order values and attitudes determine consumer choice," SFB 649 Discussion Papers SFB649DP2007-065, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  • Handle: RePEc:hum:wpaper:sfb649dp2007-065
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    File URL: http://sfb649.wiwi.hu-berlin.de/papers/pdf/SFB649DP2007-065.pdf
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    References listed on IDEAS

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    1. Vredin Johansson, Maria & Heldt, Tobias & Johansson, Per, 2006. "The effects of attitudes and personality traits on mode choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(6), pages 507-525, July.
    2. Walker, Joan & Ben-Akiva, Moshe, 2002. "Generalized random utility model," Mathematical Social Sciences, Elsevier, vol. 43(3), pages 303-343, July.
    3. McFadden, Daniel, 1974. "The measurement of urban travel demand," Journal of Public Economics, Elsevier, vol. 3(4), pages 303-328, November.
    4. Vredin Johansson, Maria & Heldt, Tobias & Johansson, Per, 2005. "Latent Variables in a Travel Mode Choice Model: Attitudinal and Behavioural Indicator Variables," Working Paper Series 2005:5, Uppsala University, Department of Economics.
    5. Kenneth Train, 1980. "A Structured Logit Model of Auto Ownership and Mode Choice," Review of Economic Studies, Oxford University Press, vol. 47(2), pages 357-370.
    6. Ben-Akiva, Moshe & McFadden, Daniel & Train, Kenneth & Börsch-Supan, Axel, 2002. "Hybrid Choice Models: Progress and Challenges," Sonderforschungsbereich 504 Publications 02-29, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
    7. Bresson, Georges & Dargay, Joyce & Madre, Jean-Loup & Pirotte, Alain, 2004. "Economic and structural determinants of the demand for public transport: an analysis on a panel of French urban areas using shrinkage estimators," Transportation Research Part A: Policy and Practice, Elsevier, vol. 38(4), pages 269-285, May.
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    Cited by:

    1. 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.

    More about this item

    Keywords

    Hybrid choice models; Mode choice; Values; Value-attitude hierarchy; Mplus;

    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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