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Optimum design of electronic communities as economic entities

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  • Levent V. Orman

    (Cornell University)

Abstract

Electronic communities can be designed to organize consumers, to pool their purchasing power, and to guide their purchasing decisions. Such commercial electronic communities have the potential to facilitate the creation of novel marketplaces, and even radically change the buyer-seller interaction, as physical communities did throughout the history. Commercial electronic communities are groups of consumers that participate in the marketplace as a single unit. In addition to bargaining power gained from such bundling, such communities can expand markets by reducing market uncertainty, and they have the potential to drastically reduce consumers’ transaction costs, by facilitating group transactions and bulk purchasing. Communities are characterized by their size, their pricing strategy, and their membership characteristics. Analytical models and numeric analysis is utilized to compute the optimum size of a community for given market characteristics. Two major community pricing strategies are analyzed to improve the community design, and the conditions are derived where one dominates the other. Finally, market segmentation techniques are introduced to control the membership characteristics of the community to further improve the design.

Suggested Citation

  • Levent V. Orman, 2006. "Optimum design of electronic communities as economic entities," Information Systems Frontiers, Springer, vol. 8(3), pages 179-194, July.
  • Handle: RePEc:spr:infosf:v:8:y:2006:i:3:d:10.1007_s10796-006-8778-9
    DOI: 10.1007/s10796-006-8778-9
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    References listed on IDEAS

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    1. Yannis Bakos & Erik Brynjolfsson, 1999. "Bundling Information Goods: Pricing, Profits, and Efficiency," Management Science, INFORMS, vol. 45(12), pages 1613-1630, December.
    2. Yannis Bakos & Erik Brynjolfsson, 2000. "Bundling and Competition on the Internet," Marketing Science, INFORMS, vol. 19(1), pages 63-82, May.
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    Cited by:

    1. Chulhwan Chris Bang, 2015. "Information systems frontiers: Keyword analysis and classification," Information Systems Frontiers, Springer, vol. 17(1), pages 217-237, February.

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