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Model for Studying Commodity Bundling with a Focus on Consumer Preference


  • Yuri Park
  • Hyunnam Kim
  • Jongsu Lee

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


As various mobile contents can be delivered over mobile platform, mobile contents have been considered as new profit opportunities, Choices of mobile contents and mobile terminals are not independent but closely related. Accordingly, this paper analyses consumer preferences and correlations between the adoption of mobile phones and mobile contents. Based on survey data, multinomial logit and multivariate probit models with a Bayesian approach are used for understanding structures of consumer preferences. The results show not only consumer preferences for specific features of mobile phones and complementary relations between various types of mobile contents but also significant correlations between the adoption of phones and of contents. The results identify necessities of releasing phones with full web browsers in specific forms as well as providing product and services with an integrated view for both mobile phones and mobile contents. Also, the study presents information and new business opportunities for the telecommunication market.

Suggested Citation

  • Yuri Park & Hyunnam Kim & Jongsu Lee, 2009. "Model for Studying Commodity Bundling with a Focus on Consumer Preference," TEMEP Discussion Papers 200935, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Nov 2009.
  • Handle: RePEc:snv:dp2009:200935

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    References listed on IDEAS

    1. Baourakis, G. & Matsatsinis, N. F. & Siskos, Y., 1996. "Agricultural product development using multidimensional and multicriteria analyses: The case of wine," European Journal of Operational Research, Elsevier, vol. 94(2), pages 321-334, October.
    2. Yeonbae Kim & Jeong-Dong Lee & Daeyoung Koh, 2005. "Effects of consumer preferences on the convergence of mobile telecommunications devices," Applied Economics, Taylor & Francis Journals, vol. 37(7), pages 817-826.
    3. Baltas, George, 2004. "A model for multiple brand choice," European Journal of Operational Research, Elsevier, vol. 154(1), pages 144-149, April.
    4. Hsu, Chin-Lung & Lu, Hsi-Peng & Hsu, Huei-Hsia, 2007. "Adoption of the mobile Internet: An empirical study of multimedia message service (MMS)," Omega, Elsevier, vol. 35(6), pages 715-726, December.
    5. Ishii, Kenichi, 2004. "Internet use via mobile phone in Japan," Telecommunications Policy, Elsevier, vol. 28(1), pages 43-58, February.
    6. McCulloch, Robert & Rossi, Peter E., 1994. "An exact likelihood analysis of the multinomial probit model," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 207-240.
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    Cited by:

    1. Castro, Marisol & Bhat, Chandra R. & Pendyala, Ram M. & Jara-Díaz, Sergio R., 2012. "Accommodating multiple constraints in the multiple discrete–continuous extreme value (MDCEV) choice model," Transportation Research Part B: Methodological, Elsevier, vol. 46(6), pages 729-743.

    More about this item


    mobile phone; mobile contents; consumer preferences; discrete choice model; bayesian approach;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • M21 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - Business Economics
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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