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A Forecast Simulation Analysis of the Next-Generation DVD Market Based on Consumer Preference Data

Author

Listed:
  • Jongsu Lee
  • Jae Young Choi

  • Youngsang Cho

    (Technology Management, Economics, and Policy Program (TEMEP); Seoul National University)

Abstract

Just as standards wars over formats had characterized VCRs upon introduction to the market, the next-generation DVD standards war between Blu-Ray and HD-DVD lasted six years before Blu-Ray won the contest. Beginning with stated preference data drawn from a structured conjoint survey conducted before Blu-Ray became the de facto standard of the next-generation DVD format, we estimated consumer preferences on digital video players. A Bayesian mixed-logit model was used and market share simulations were conducted under various scenarios based on estimated parameters to surmise the future South Korean digital video-player market. Results indicate that consumers feel that network size and title availability are more important than hardware-related facets of the product, such as definition and storage capacity. The level of title availability and price of the Blu-Ray player for Blu-Ray¡¯s dominance over DVD will vary by the penetration rate of DVD players.

Suggested Citation

  • Jongsu Lee & Jae Young Choi & Youngsang Cho, 2009. "A Forecast Simulation Analysis of the Next-Generation DVD Market Based on Consumer Preference Data," TEMEP Discussion Papers 200933, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Nov 2009.
    • Handle: RePEc:snv:dp2009:200933
    as

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    File URL: http://temep-repec.my-groups.de/DP-33.pdf
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    References listed on IDEAS

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    1. Huber, Joel & Train, Kenneth, 2000. "On the Similarity of Classical and Bayesian Estimates of Individual Mean Partworths," Department of Economics, Working Paper Series qt7zm4f51b, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    2. Farrell, Joseph & Saloner, Garth, 1987. "Coordination Through Committees and Markets," Department of Economics, Working Paper Series qt5sn4b6v4, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    3. Sangin Park, 2004. "Quantitative Analysis of Network Externalities in Competing Technologies: The VCR Case," The Review of Economics and Statistics, MIT Press, vol. 86(4), pages 937-945, November.
    4. Roe, Brian & Boyle, Kevin J. & Teisl, Mario F., 1996. "Using Conjoint Analysis to Derive Estimates of Compensating Variation," Journal of Environmental Economics and Management, Elsevier, vol. 31(2), pages 145-159, September.
    5. Layton, David F., 2000. "Random Coefficient Models for Stated Preference Surveys," Journal of Environmental Economics and Management, Elsevier, vol. 40(1), pages 21-36, July.
    6. Batt, Carl E & Katz, James E, 1997. "A conjoint model of enhanced voice mail services. Implications for new service development and forecasting," Telecommunications Policy, Elsevier, vol. 21(8), pages 743-760, October.
    7. Yeonbae Kim & Yuri Park & Jeong-Dong Lee & Jongsu Lee, 2006. "Using stated-preference data to measure the inconvenience cost of spam among Korean E-mail users," Applied Economics Letters, Taylor & Francis Journals, vol. 13(12), pages 795-800.
    8. Joel Huber and Kenneth Train., 2000. "On the Similarity of Classical and Bayesian Estimates of Individual Mean Partworths," Economics Working Papers E00-289, University of California at Berkeley.
    9. Farrell, Joseph & Saloner, Garth, 1988. "Coordination Through Committees and Markets," Department of Economics, Working Paper Series qt08w115vq, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    10. Venkatesh Shankar & Barry L. Bayus, 2003. "Network effects and competition: an empirical analysis of the home video game industry," Strategic Management Journal, Wiley Blackwell, vol. 24(4), pages 375-384, April.
    11. Joseph Farrell & Garth Saloner, 1988. "Coordination through Committees and Markets," RAND Journal of Economics, The RAND Corporation, vol. 19(2), pages 235-252, Summer.
    12. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, November.
    13. Neil Gandal & Michael Kende & Rafael Rob, 2000. "The Dynamics of Technological Adoption in Hardware/Software Systems: The Case of Compact Disc Players," RAND Journal of Economics, The RAND Corporation, vol. 31(1), pages 43-61, Spring.
    14. David Hensher, 2001. "The valuation of commuter travel time savings for car drivers: evaluating alternative model specifications," Transportation, Springer, vol. 28(2), pages 101-118, May.
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    Keywords

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    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality
    • L82 - Industrial Organization - - Industry Studies: Services - - - Entertainment; Media

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