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Recommended for you: The effect of word of mouth on sales concentration

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  • Hervas-Drane, Andres

Abstract

I examine the role of word of mouth in consumer's product discovery process and its implications for the firm. A monopolist supplies an assortment of horizontally differentiated products and consumers search for a product that matches their taste by sampling products from the assortment or by seeking product recommendations from other consumers. I analyze the underlying consumer interactions that lead to the emergence of word of mouth, examine the optimal pricing and assortment strategy of the firm, and explain the impact of word of mouth on the concentration of sales within the assortment. The model provides a rationale for the long tail phenomenon, explains recent empirical findings in online retail, and is well suited for product categories such as music, film, books, and video game entertainment.

Suggested Citation

  • Hervas-Drane, Andres, 2015. "Recommended for you: The effect of word of mouth on sales concentration," International Journal of Research in Marketing, Elsevier, vol. 32(2), pages 207-218.
    • Handle: RePEc:eee:ijrema:v:32:y:2015:i:2:p:207-218
    DOI: 10.1016/j.ijresmar.2015.02.005
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    References listed on IDEAS

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    Cited by:

    1. Tobias Kretschmer & Christian Peukert, 2020. "Video Killed the Radio Star? Online Music Videos and Recorded Music Sales," Information Systems Research, INFORMS, vol. 31(3), pages 776-800, September.
    2. Amir Ajorlou & Ali Jadbabaie & Ali Kakhbod, 2018. "Dynamic Pricing in Social Networks: The Word-of-Mouth Effect," Management Science, INFORMS, vol. 64(2), pages 971-979, February.
    3. Yongjin Park & Youngsok Bang & Jae-Hyeon Ahn, 2020. "How Does the Mobile Channel Reshape the Sales Distribution in E-Commerce?," Information Systems Research, INFORMS, vol. 31(4), pages 1164-1182, December.
    4. Gobinda Roy & Biplab Datta & Rituparna Basu, 2017. "Effect of eWOM Valence on Online Retail Sales," Global Business Review, International Management Institute, vol. 18(1), pages 198-209, February.
    5. Chen, Daqiang & Ignatius, Joshua & Sun, Danzhi & Zhan, Shalei & Zhou, Chenyu & Marra, Marianna & Demirbag, Mehmet, 2019. "Reverse logistics pricing strategy for a green supply chain: A view of customers' environmental awareness," International Journal of Production Economics, Elsevier, vol. 217(C), pages 197-210.
    6. Peluso, Alessandro M. & Bonezzi, Andrea & De Angelis, Matteo & Rucker, Derek D., 2017. "Compensatory word of mouth: Advice as a device to restore control," International Journal of Research in Marketing, Elsevier, vol. 34(2), pages 499-515.
    7. Sebastian Schneider, 2022. "Price-related consumer discussions in China and the United States: a cross-cultural study investigating price perceptions and word-of-mouth transmission," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(3), pages 274-290, June.
    8. Joan Calzada & Nestor Duch-Brown & Ricard Gil, 2021. "Do search engines increase concentration in media markets?," UB School of Economics Working Papers 2021/415, University of Barcelona School of Economics.
    9. Menon, Kalyani & Ranaweera, Chatura, 2018. "Beyond close vs. distant ties: Understanding post-service sharing of information with close, exchange, and hybrid ties," International Journal of Research in Marketing, Elsevier, vol. 35(1), pages 154-169.
    10. Sebastian Köhler & Thomas Wöhner & Ralf Peters, 2016. "The impact of consumer preferences on the accuracy of collaborative filtering recommender systems," Electronic Markets, Springer;IIM University of St. Gallen, vol. 26(4), pages 369-379, November.
    11. Sebastian Schneider & Frank Huber, 2022. "You paid what!? Understanding price-related word-of-mouth and price perception among opinion leaders and innovators," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(1), pages 64-80, February.
    12. Lusi Li & Jianqing Chen & Srinivasan Raghunathan, 2018. "Recommender System Rethink: Implications for an Electronic Marketplace with Competing Manufacturers," Information Systems Research, INFORMS, vol. 29(4), pages 1003-1023, December.
    13. Latzer, Michael & Festic, Noemi, 2019. "A guideline for understanding and measuring algorithmic governance in everyday life," Internet Policy Review: Journal on Internet Regulation, Alexander von Humboldt Institute for Internet and Society (HIIG), Berlin, vol. 8(2), pages 1-19.
    14. Paul Belleflamme & Martin Peitz, 2018. "Inside the Engine Room of Digital Platforms: Reviews, Ratings, and Recommendations," Working Papers halshs-01714549, HAL.
    15. Yanrong Li & Lai Wei & Wei Jiang, 2021. "A Two-stage Pricing Strategy Considering Learning Effects and Word-of-Mouth," Papers 2110.11581, arXiv.org.
    16. Silva, Ana Teresa & Moro, Sérgio & Rita, Paulo & Cortez, Paulo, 2018. "Unveiling the features of successful eBay smartphone sellers," Journal of Retailing and Consumer Services, Elsevier, vol. 43(C), pages 311-324.
    17. Roma, Paolo & Aloini, Davide, 2019. "How does brand-related user-generated content differ across social media? Evidence reloaded," Journal of Business Research, Elsevier, vol. 96(C), pages 322-339.

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    More about this item

    Keywords

    Search; Product discovery; Product recommendations; Recommender systems; Long tail;
    All these keywords.

    JEL classification:

    • 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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