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Explaining consumer choice through neural networks: The stacked generalization approach

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  • Hu, Michael Y.
  • Tsoukalas, Christos

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  • Hu, Michael Y. & Tsoukalas, Christos, 2003. "Explaining consumer choice through neural networks: The stacked generalization approach," European Journal of Operational Research, Elsevier, vol. 146(3), pages 650-660, May.
    • Handle: RePEc:eee:ejores:v:146:y:2003:i:3:p:650-660
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    References listed on IDEAS

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    1. Dasgupta, Chanda Ghose & Dispensa, Gary S. & Ghose, Sanjoy, 1994. "Comparing the predictive performance of a neural network model with some traditional market response models," International Journal of Forecasting, Elsevier, vol. 10(2), pages 235-244, September.
    2. Patricia M. West & Patrick L. Brockett & Linda L. Golden, 1997. "A Comparative Analysis of Neural Networks and Statistical Methods for Predicting Consumer Choice," Marketing Science, INFORMS, vol. 16(4), pages 370-391.
    3. Min, Chung-ki & Zellner, Arnold, 1993. "Bayesian and non-Bayesian methods for combining models and forecasts with applications to forecasting international growth rates," Journal of Econometrics, Elsevier, vol. 56(1-2), pages 89-118, March.
    4. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
    5. Hui, Michael K & Bateson, John E G, 1991. "Perceived Control and the Effects of Crowding and Consumer Choice on the Service Experience," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 18(2), pages 174-184, September.
    6. Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March.
    7. Simonson, Itamar & Winer, Russell S, 1992. "The Influence of Purchase Quantity and Display Format on Consumer Preference for Variety," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 19(1), pages 133-138, June.
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    Cited by:

    1. Lu, Jing & Meng, Yucan & Timmermans, Harry & Zhang, Anming, 2021. "Modeling hesitancy in airport choice: A comparison of discrete choice and machine learning methods," Transportation Research Part A: Policy and Practice, Elsevier, vol. 147(C), pages 230-250.
    2. Xudong Hu & Hongbo Mei & Han Zhang & Yuanyuan Li & Mengdi Li, 2021. "Performance evaluation of ensemble learning techniques for landslide susceptibility mapping at the Jinping county, Southwest China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 105(2), pages 1663-1689, January.
    3. Gholamhossein Mahdavi & Mohammad Sadeghzadeh Maharluie & Ahmad Shokrolahi, 2017. "The Use of Artificial Neural Networks for Quantifying the Relative Importance of the Firms' Performance Determinants," International Journal of Economics and Financial Issues, Econjournals, vol. 7(3), pages 119-127.
    4. Potharst, R. & van Rijthoven, M. & van Wezel, M.C., 2005. "Modeling brand choice using boosted and stacked neural networks," Econometric Institute Research Papers EI 2005-05, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. van Wezel, Michiel & Potharst, Rob, 2007. "Improved customer choice predictions using ensemble methods," European Journal of Operational Research, Elsevier, vol. 181(1), pages 436-452, August.
    6. van Wezel, M.C. & Potharst, R., 2005. "Improved customer choice predictions using ensemble methods," Econometric Institute Research Papers EI 2005-08, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

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