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Predicting Empirical Patterns in Viewing Japanese TV Dramas Using Case-Based Decision Theory

Author

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  • Kinjo Keita

    (Department of Economics, Okinawa International University, Ginowan, Japan)

  • Sugawara Shinya

    (Graduate School of Information Science and Technology, University of Tokyo, Tokyo, Japan)

Abstract

This article empirically analyzes consumer behavior of viewing TV dramas using case-based decision theory. The theory addresses an economic situation with structural ignorance, where states of the world are not naturally given nor simply formulated for a decision-maker. Under this theory, consumers make decisions based on subjective evaluations of previous purchases for similar goods. Our empirical analysis is concerned with viewing decisions on getsuku, the Japanese TV dramas broadcast at 9 pm Monday by the Fuji Television Network. The regularity of the schedule and the long-sustaining popularity of the program enable us to easily collect consumer data. Then, we conduct a web survey of individual audiences on subjective evaluations of previously watched dramas. For our empirical analysis, we utilize a simple linear model of the case-based model that allows the incorporation of flexible inference techniques. Our results demonstrate better performance of the case-based models than models based on traditional expected utility theory regarding both statistical model selection and one-step-ahead prediction. We also reveal that the successful performance of the case-based model in our analysis depends on the availability of individual subjective evaluations and that it is difficult to replace the individual-specific information using demographic information and aggregate data.

Suggested Citation

  • Kinjo Keita & Sugawara Shinya, 2016. "Predicting Empirical Patterns in Viewing Japanese TV Dramas Using Case-Based Decision Theory," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 16(2), pages 679-709, June.
  • Handle: RePEc:bpj:bejtec:v:16:y:2016:i:2:p:679-709:n:6
    DOI: 10.1515/bejte-2015-0014
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    References listed on IDEAS

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    6. Seaman, Bruce A, 2006. "Empirical Studies of Demand for the Performing Arts," Handbook of the Economics of Art and Culture, in: V.A. Ginsburgh & D. Throsby (ed.), Handbook of the Economics of Art and Culture, edition 1, volume 1, chapter 14, pages 415-472, Elsevier.
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    8. Offer Lieberman & Peter C. B. Phillips, 2014. "Norming Rates And Limit Theory For Some Time-Varying Coefficient Autoregressions," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(6), pages 592-623, November.
    9. Offer Lieberman, 2012. "A similarity‐based approach to time‐varying coefficient non‐stationary autoregression," Journal of Time Series Analysis, Wiley Blackwell, vol. 33(3), pages 484-502, May.
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    Cited by:

    1. Minjie Huang & Shunan Zhao & Andreas Pape, 2023. "Estimating Case‐based Individual and Social Learning in Corporate Tax Avoidance," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(2), pages 403-434, April.
    2. Todd Guilfoos & Andreas Duus Pape, 2020. "Estimating Case-Based Learning," Games, MDPI, vol. 11(3), pages 1-25, September.
    3. M. Huang & A. D. Pape, 2020. "The Impact of Online Consumer Reviews on Online Sales: The Case-Based Decision Theory Approach," Journal of Consumer Policy, Springer, vol. 43(3), pages 463-490, September.

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