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Optimal Design on Customized Bundling Strategy of Information Goods for Customers with Two-Dimensional Heterogeneity

Author

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  • Xiaoxiao Luo

    (College of Management and Economics, Tianjin University, Tianjin 300072, P. R. China)

  • Minqiang Li

    (College of Management and Economics, Tianjin University, Tianjin 300072, P. R. China)

  • Nan Feng

    (College of Management and Economics, Tianjin University, Tianjin 300072, P. R. China)

  • Fuzan Chen

    (College of Management and Economics, Tianjin University, Tianjin 300072, P. R. China)

Abstract

Customized bundling is a pricing strategy that allows consumers to choose a certain quantity of products at a fixed price. In the reality, a customer usually has a specific rank on information goods based on their valuations, or information goods can be ranked into a list of products with decreasing valuations for a customer. Thus, we characterize customers in two dimensions for constructing the customized bundles of ranked information goods: (i) the valuation that a customer sets for his/her most favorite information good; and (ii) the total quantity of information goods with positive valuations that a customer requires. We derive the optimal customized bundling strategies in two typical scenarios and examine the impact of customer heterogeneity in terms of each dimension on the optimal pricing schemes of customized bundles. Analytical results indicate that the two features have similar effects on optimal bundle price, market penetration, and maximal profit, but impact differently on optimal bundle size. Larger customer heterogeneity leads to a lower or identical optimal bundle price, market penetration, and maximal profit. However, optimal bundle size shrinks or remains unchanged with increased customer heterogeneity on the total quantities of information goods with positive valuations, but it grows or stays the same when customers have larger heterogeneity on the valuations of their most favorite information goods. Our results provide explanations to the marketing practices of digital product firms, and also support the optimal decision of customized bundling of information goods for heterogeneous customers.

Suggested Citation

  • Xiaoxiao Luo & Minqiang Li & Nan Feng & Fuzan Chen, 2017. "Optimal Design on Customized Bundling Strategy of Information Goods for Customers with Two-Dimensional Heterogeneity," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(02), pages 1-32, April.
  • Handle: RePEc:wsi:apjorx:v:34:y:2017:i:02:n:s0217595917500075
    DOI: 10.1142/S0217595917500075
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    References listed on IDEAS

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    1. Amiya Basu & Padmal Vitharana, 2009. "—Impact of Customer Knowledge Heterogeneity on Bundling Strategy," Marketing Science, INFORMS, vol. 28(4), pages 792-801, 07-08.
    2. Xuemei Zhang & Yao Wei & Jiqiong Liu & Gang Chen, 2015. "Product Design Strategy with Commonality by Considering Customer-Choice Behavior in Supply Chain," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 32(05), pages 1-22.
    3. Jianbin Li & Qifei Wang & Hong Yan & Stuart X. Zhu, 2016. "Optimal Remanufacturing and Pricing Strategies Under Name-Your-Own-Price Auctions and Stochastic Demand," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 33(01), pages 1-22, February.
    4. Ward Hanson & R. Kipp Martin, 1990. "Optimal Bundle Pricing," Management Science, INFORMS, vol. 36(2), pages 155-174, February.
    5. Chenghuan Sean Chu & Phillip Leslie & Alan Sorensen, 2011. "Bundle-Size Pricing as an Approximation to Mixed Bundling," American Economic Review, American Economic Association, vol. 101(1), pages 263-303, February.
    6. Shin-yi Wu & Lorin M. Hitt & Pei-yu Chen & G. Anandalingam, 2008. "Customized Bundle Pricing for Information Goods: A Nonlinear Mixed-Integer Programming Approach," Management Science, INFORMS, vol. 54(3), pages 608-622, March.
    7. Yong Chao & Timothy Derdenger, 2013. "Mixed Bundling in Two-Sided Markets in the Presence of Installed Base Effects," Management Science, INFORMS, vol. 59(8), pages 1904-1926, August.
    8. Chuang, John Chung-I & Sirbu, Marvin A., 1999. "Optimal bundling strategy for digital information goods: network delivery of articles and subscriptions," Information Economics and Policy, Elsevier, vol. 11(2), pages 147-176, July.
    9. Prasad, Ashutosh & Venkatesh, R. & Mahajan, Vijay, 2015. "Product bundling or reserved product pricing? Price discrimination with myopic and strategic consumers," International Journal of Research in Marketing, Elsevier, vol. 32(1), pages 1-8.
    10. Lorin M. Hitt & Pei-yu Chen, 2005. "Bundling with Customer Self-Selection: A Simple Approach to Bundling Low-Marginal-Cost Goods," Management Science, INFORMS, vol. 51(10), pages 1481-1493, October.
    11. Yannis Bakos & Erik Brynjolfsson, 1999. "Bundling Information Goods: Pricing, Profits, and Efficiency," Management Science, INFORMS, vol. 45(12), pages 1613-1630, December.
    12. Ashutosh Prasad & R. Venkatesh & Vijay Mahajan, 2010. "Optimal Bundling of Technological Products with Network Externality," Management Science, INFORMS, vol. 56(12), pages 2224-2236, December.
    13. Kim Huat Goh & Jesse C. Bockstedt, 2013. "The Framing Effects of Multipart Pricing on Consumer Purchasing Behavior of Customized Information Good Bundles," Information Systems Research, INFORMS, vol. 24(2), pages 334-351, June.
    14. R. Venkatesh & Wagner Kamakura, 2003. "Optimal Bundling and Pricing under a Monopoly: Contrasting Complements and Substitutes from Independently Valued Products," The Journal of Business, University of Chicago Press, vol. 76(2), pages 211-232, April.
    15. Xianjun Geng & Maxwell B. Stinchcombe & Andrew B. Whinston, 2005. "Bundling Information Goods of Decreasing Value," Management Science, INFORMS, vol. 51(4), pages 662-667, April.
    16. Rustam Ibragimov & Johan Walden, 2010. "Optimal Bundling Strategies Under Heavy-Tailed Valuations," Management Science, INFORMS, vol. 56(11), pages 1963-1976, November.
    17. William James Adams & Janet L. Yellen, 1976. "Commodity Bundling and the Burden of Monopoly," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 90(3), pages 475-498.
    18. Li, Minqiang & Feng, Haiyang & Chen, Fuzan & Kou, Jisong, 2013. "Numerical investigation on mixed bundling and pricing of information products," International Journal of Production Economics, Elsevier, vol. 144(2), pages 560-571.
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