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Word of Mouth and Taste Matching: A Theory of the Long Tail

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Abstract

I present a model to assess the impact of demand-side factors on the concentration of sales within large product assortments. Consumers face a search problem within an assortment of horizontally differentiated products supplied by a monopolist. They may search for a product match by drawing products from the assortment or by seeking word of mouth recommendations from other consumers. Product evaluations prior to purchase and word of mouth are shown to arise endogenously, and increase the concentration of sales. I show that taste matching mechanisms such as recommender systems, which allow consumers to obtain product recommendations from others with similar preferences, reduce sales concentration by generating a long tail effect, an increase in the tail of the sales distribution. Insights are derived on the mechanisms driving concentration in artistic markets and their strategic implications for the firm. The model is suited for experience good markets such as music, cinema, literature and video game entertainment.

Suggested Citation

  • Andres Hervas-Drane, 2007. "Word of Mouth and Taste Matching: A Theory of the Long Tail," Working Papers 07-41, NET Institute, revised Jan 2009.
  • Handle: RePEc:net:wpaper:0741
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    1. Tucker, Catherine & Zhang, Juanjuan, 2007. "Long Tail or Steep Tail? A Field Investigation into How Online Popularity Information Affects the Distribution of Customer Choices," Working papers 39811, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    2. Chrysanthos Dellarocas, 2006. "Strategic Manipulation of Internet Opinion Forums: Implications for Consumers and Firms," Management Science, INFORMS, vol. 52(10), pages 1577-1593, October.
    3. Adler, Moshe, 1985. "Stardom and Talent," American Economic Review, American Economic Association, vol. 75(1), pages 208-212, March.
    4. Chong Ju Choi & Carla C. J. M. Millar & Caroline Y. L. Wong, 2005. "Knowledge and the State," Palgrave Macmillan Books, in: Knowledge Entanglements, chapter 0, pages 19-38, Palgrave Macmillan.
    5. J. Yannis Bakos, 1997. "Reducing Buyer Search Costs: Implications for Electronic Marketplaces," Management Science, INFORMS, vol. 43(12), pages 1676-1692, December.
    6. MacDonald, Glenn M, 1988. "The Economics of Rising Stars," American Economic Review, American Economic Association, vol. 78(1), pages 155-166, March.
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    Cited by:

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    2. Gal OEstreicher-Singer & Barak Libai, 2011. "Assessing Value in Product Networks," Working Papers 11-29, NET Institute, revised Sep 2011.

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    More about this item

    Keywords

    Search; Word of Mouth; Sales Concentration; Long Tail;
    All these keywords.

    JEL classification:

    • C78 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Bargaining Theory; Matching Theory
    • D42 - Microeconomics - - Market Structure, Pricing, and Design - - - Monopoly
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

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