[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/net/wpaper/0741.html
   My bibliography  Save this paper

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

Author

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
    as

    Download full text from publisher

    File URL: http://www.netinst.org/Hervas_07-41.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Claussen, Jörg & Kretschmer, Tobias & Mayrhofer, Philip, 2010. "Private Regulation by Platform Operators – Implications for Usage Intensity," Discussion Papers in Business Administration 11374, University of Munich, Munich School of Management.
    2. Gal OEstreicher-Singer & Barak Libai, 2011. "Assessing Value in Product Networks," Working Papers 11-29, NET Institute, revised Sep 2011.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gaenssle Sophia & Budzinski Oliver & Astakhova Daria, 2018. "Conquering the Box Office: Factors Influencing Success of International Movies in Russia," Review of Network Economics, De Gruyter, vol. 17(4), pages 245-266, December.
    2. Budzinski, Oliver & Kohlschreiber, Marie & Kuchinke, Björn & Pannicke, Julia, 2019. "Does music quality matter for audience voters in a music contest?," Ilmenau Economics Discussion Papers 122, Ilmenau University of Technology, Institute of Economics.
    3. Aloys Prinz, 2017. "Rankings as coordination games: the Dutch Top 2000 pop song ranking," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 41(4), pages 379-401, November.
    4. Sudip Bhattacharjee & Ram D. Gopal & Kaveepan Lertwachara & James R. Marsden & Rahul Telang, 2005. "The Effect of P2P File Sharing on Music Markets: A Survival Analysis of Albums on Ranking Charts," Working Papers 05-26, NET Institute, revised Oct 2005.
    5. Julianne Treme & Samuel K. Allen, 2011. "Press Pass: Payoffs to Media Exposure Among National Football League (NFL) Wide Receivers," Journal of Sports Economics, , vol. 12(3), pages 370-390, June.
    6. Marc Bourreau & François Moreau & Patrik Wikström, 2022. "Does digitization lead to the homogenization of cultural content?," Economic Inquiry, Western Economic Association International, vol. 60(1), pages 427-453, January.
    7. Michael R. Ward & Alexander D. Harmon, 2019. "ESport Superstars," Journal of Sports Economics, , vol. 20(8), pages 987-1013, December.
    8. Budzinski, Oliver & Gaenssle, Sophia, 2018. "The economics of social media stars: An empirical investigation of stardom, popularity, and success on YouTube," Ilmenau Economics Discussion Papers 112, Ilmenau University of Technology, Institute of Economics.
    9. Fei Peng & Lili Kang & Sajid Anwar & Xue Li, 2019. "Star power and box office revenues: evidence from China," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 43(2), pages 247-278, June.
    10. Angela (Xia) Liu & Tridib Mazumdar & Bo Li, 2015. "Counterfactual Decomposition of Movie Star Effects with Star Selection," Management Science, INFORMS, vol. 61(7), pages 1704-1721, July.
    11. Heski Bar-Isaac & Guillermo Caruana & Vicente Cunat, 2012. "Search, Design, and Market Structure," American Economic Review, American Economic Association, vol. 102(2), pages 1140-1160, April.
    12. Andrej Srakar, 2017. "Prevalence of Diseases and Health Care Utilization ofthe Self-Employed Artists and TheirEmpirical Determinants: Evidence From a Slovenian Survey," ACEI Working Paper Series AWP-08-2017, Association for Cultural Economics International, revised Sep 2017.
    13. O. Loginova & A. Mantovani, 2015. "Information and Online Reviews," Working Papers wp996, Dipartimento Scienze Economiche, Universita' di Bologna.
    14. Shu Han & S. Abraham Ravid, 2020. "Star Turnover and the Value of Human Capital—Evidence from Broadway Shows," Management Science, INFORMS, vol. 66(2), pages 958-978, February.
    15. Kotrba, Vojtěch, 2019. "Direct preferences of sports fans: Is there a superstar effect in the fantasy league?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 78(C), pages 89-97.
    16. Egon Franck & Stephan Nüesch, 2006. "Superstars versus Celebrities - Big Man or Big Name?," Working Papers 0010, University of Zurich, Center for Research in Sports Administration (CRSA).
    17. Zhang, Xubing & Jiang, Bo, 2014. "Increasing Price Transparency: Implications of Consumer Price Posting for Consumers' Haggling Behavior and a Seller's Pricing Strategies," Journal of Interactive Marketing, Elsevier, vol. 28(1), pages 68-85.
    18. Andrés González-Moralejo, S & Compés López, R, 2009. "Problemas contractuales y acuerdos de subcontratación: El caso de la logística frigorífica en la industria alimentaria valenciana/," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 27, pages 279(30á)-27, Abril.
    19. Daniel Högele & Sascha L. Schmidt & Benno Torgler, 2012. "The Influence of Superstars on Organizational Identification of External Stakeholders: Empirical Findings from Professional Soccer," CREMA Working Paper Series 2012-18, Center for Research in Economics, Management and the Arts (CREMA).
    20. Egon Franck & Stephan Nüesch, 2005. "Talent, Past Consumption and/or Popularity - Are German Soccer Celebrities Rosen or Adler Stars?," Working Papers 0005, University of Zurich, Center for Research in Sports Administration (CRSA), revised 2006.

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:net:wpaper:0741. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Nicholas Economides (email available below). General contact details of provider: http://www.NETinst.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.