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Using Neural Networks to Identify Competitive Market Structures from Aggregate Market Response Data

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  • Gruca, TS
  • Klemz, BR

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  • Gruca, TS & Klemz, BR, 1998. "Using Neural Networks to Identify Competitive Market Structures from Aggregate Market Response Data," Omega, Elsevier, vol. 26(1), pages 49-62, February.
    • Handle: RePEc:eee:jomega:v:26:y:1998:i:1:p:49-62
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    1. Nakanishi, Masao & Cooper, Lee G & Kassarjian, Harold H, 1974. "Voting for a Political Candidate under Conditions of Minimal Information," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 1(2), pages 36-43, Se.
    2. Gorr, Wilpen L. & Nagin, Daniel & Szczypula, Janusz, 1994. "Comparative study of artificial neural network and statistical models for predicting student grade point averages," International Journal of Forecasting, Elsevier, vol. 10(1), pages 17-34, June.
    3. Hruschka, Harald, 1993. "Determining market response functions by neural network modeling: A comparison to econometric techniques," European Journal of Operational Research, Elsevier, vol. 66(1), pages 27-35, April.
    4. Gregory S. Carpenter & Lee G. Cooper & Dominique M. Hanssens & David F. Midgley, 1988. "Modeling Asymmetric Competition," Marketing Science, INFORMS, vol. 7(4), pages 393-412.
    5. V. Kumar & Timothy B. Heath, 1990. "A comparative study of market share models using disaggregate data," Post-Print hal-00670544, HAL.
    6. Tam, KY, 1991. "Neural network models and the prediction of bank bankruptcy," Omega, Elsevier, vol. 19(5), pages 429-445.
    7. Theil, Henri, 1969. "A Multinomial Extension of the Linear Logit Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 10(3), pages 251-259, October.
    8. Kar Yan Tam & Melody Y. Kiang, 1992. "Managerial Applications of Neural Networks: The Case of Bank Failure Predictions," Management Science, INFORMS, vol. 38(7), pages 926-947, July.
    9. Kumar, V. & Heath, Timothy B., 1990. "A comparative study of market share models using disaggregate data," International Journal of Forecasting, Elsevier, vol. 6(2), pages 163-174, July.
    10. Gorr, Wilpen L., 1994. "Editorial: Research prospective on neural network forecasting," International Journal of Forecasting, Elsevier, vol. 10(1), pages 1-4, June.
    11. Chatfield, Chris, 1993. "Neural networks: Forecasting breakthrough or passing fad?," International Journal of Forecasting, Elsevier, vol. 9(1), pages 1-3, April.
    12. Chiang, W. -C. & Urban, T. L. & Baldridge, G. W., 1996. "A neural network approach to mutual fund net asset value forecasting," Omega, Elsevier, vol. 24(2), pages 205-215, April.
    13. Windal, Pierre M & Weiss, Doyle L, 1980. "An Iterative GLS Procedure for Estimating the Parameters of Models with Autocorrelated Errors Using Data Aggregated over Time," The Journal of Business, University of Chicago Press, vol. 53(4), pages 415-424, October.
    14. Makridakis, Spyros, 1993. "Accuracy measures: theoretical and practical concerns," International Journal of Forecasting, Elsevier, vol. 9(4), pages 527-529, December.
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    Cited by:

    1. Kanellos, Nikolaos & Katsianis, Dimitrios & Varoutas, Dimitrios, 2022. "Forecasting a telecommunications provider's market share," 31st European Regional ITS Conference, Gothenburg 2022: Reining in Digital Platforms? Challenging monopolies, promoting competition and developing regulatory regimes 265639, International Telecommunications Society (ITS).
    2. Sally Mckechnie, 2006. "Integrating intelligent systems into marketing to support market segmentation decisions," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 14(3), pages 117-127, July.
    3. Klemz, Bruce R., 1999. "Using genetic algorithms to assess the impact of pricing activity timing," Omega, Elsevier, vol. 27(3), pages 363-372, June.
    4. Fang, Xiao & Rachamadugu, Ram, 2009. "Policies for knowledge refreshing in databases," Omega, Elsevier, vol. 37(1), pages 16-28, February.
    5. Marusia Ivanova, 2007. "Genesis and Evolution of Market Share Predictive Models," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 2, pages 117-148.

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