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Will the Global Village Fracture Into Tribes? Recommender Systems and Their Effects on Consumer Fragmentation

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Cited by:

  1. Yipu Deng & Jinyang Zheng & Warut Khern-am-nuai & Karthik Kannan, 2022. "More than the Quantity: The Value of Editorial Reviews for a User-Generated Content Platform," Management Science, INFORMS, vol. 68(9), pages 6865-6888, September.
  2. Adithya Pattabhiramaiah & Eric Overby & Lizhen Xu, 2022. "Spillovers from Online Engagement: How a Newspaper Subscriber’s Activation of Digital Paywall Access Affects Her Retention and Subscription Revenue," Management Science, INFORMS, vol. 68(5), pages 3528-3548, May.
  3. Atom Sonoda & Yoshifumi Seki & Fujio Toriumi, 2022. "Analyzing user engagement in news application considering popularity diversity and content diversity," Journal of Computational Social Science, Springer, vol. 5(2), pages 1595-1614, November.
  4. Dongwon Lee & Anandasivam Gopal & Sung-Hyuk Park, 2020. "Different but Equal? A Field Experiment on the Impact of Recommendation Systems on Mobile and Personal Computer Channels in Retail," Information Systems Research, INFORMS, vol. 31(3), pages 892-912, September.
  5. Dokyun Lee & Kartik Hosanagar, 2019. "How Do Recommender Systems Affect Sales Diversity? A Cross-Category Investigation via Randomized Field Experiment," Service Science, INFORMS, vol. 30(1), pages 239-259, March.
  6. Xitong Li & Jörn Grahl & Oliver Hinz, 2022. "How Do Recommender Systems Lead to Consumer Purchases? A Causal Mediation Analysis of a Field Experiment," Information Systems Research, INFORMS, vol. 33(2), pages 620-637, June.
  7. 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.
  8. Hu, Xiaojian & Qiu, Ju & Zhao, Ju & Li, Yang, 2023. "Can in-store recommendations for online-substitutive products integrate online and offline channels?," Journal of Retailing and Consumer Services, Elsevier, vol. 70(C).
  9. Tom Fangyun Tan & Serguei Netessine & Lorin Hitt, 2017. "Is Tom Cruise Threatened? An Empirical Study of the Impact of Product Variety on Demand Concentration," Information Systems Research, INFORMS, vol. 28(3), pages 643-660, September.
  10. Xuan Bi & Mochen Yang & Gediminas Adomavicius, 2024. "Consumer Acquisition for Recommender Systems: A Theoretical Framework and Empirical Evaluations," Information Systems Research, INFORMS, vol. 35(1), pages 339-362, March.
  11. Alexander Cuntz & Carsten Fink & Hansueli Stamm, 2024. "Artificial Intelligence and Intellectual Property : An Economic Perspective," WIPO Economic Research Working Papers 77, World Intellectual Property Organization - Economics and Statistics Division.
  12. 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.
  13. 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.
  14. Molaie, Mir Majid & Lee, Wonjae, 2022. "Economic corollaries of personalized recommendations," Journal of Retailing and Consumer Services, Elsevier, vol. 68(C).
  15. Christian Peukert, 2019. "The next wave of digital technological change and the cultural industries," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 43(2), pages 189-210, June.
  16. Yi, Sangyoon & Kim, Dongyeon & Ju, Jaehyeon, 2022. "Recommendation technologies and consumption diversity: An experimental study on product recommendations, consumer search, and sales diversity," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
  17. Abhijeet Ghoshal & Subodha Kumar & Vijay Mookerjee, 2020. "Dilemma of Data Sharing Alliance: When Do Competing Personalizing and Non‐Personalizing Firms Share Data," Production and Operations Management, Production and Operations Management Society, vol. 29(8), pages 1918-1936, August.
  18. Xuan Bi & Gediminas Adomavicius & William Li & Annie Qu, 2022. "Improving Sales Forecasting Accuracy: A Tensor Factorization Approach with Demand Awareness," INFORMS Journal on Computing, INFORMS, vol. 34(3), pages 1644-1660, May.
  19. Abhijeet Ghoshal & Syam Menon & Sumit Sarkar, 2015. "Recommendations Using Information from Multiple Association Rules: A Probabilistic Approach," Information Systems Research, INFORMS, vol. 26(3), pages 532-551, September.
  20. Nathan M. Fong, 2017. "How Targeting Affects Customer Search: A Field Experiment," Management Science, INFORMS, vol. 63(7), pages 2353-2364, July.
  21. Konstantin Bauman & Alexander Tuzhilin, 2022. "Know Thy Context: Parsing Contextual Information from User Reviews for Recommendation Purposes," Information Systems Research, INFORMS, vol. 33(1), pages 179-202, March.
  22. Naveen Kumar & Liangfei Qiu & Subodha Kumar, 2018. "Exit, Voice, and Response on Digital Platforms: An Empirical Investigation of Online Management Response Strategies," Information Systems Research, INFORMS, vol. 29(4), pages 849-870, December.
  23. Elina H. Hwang & David Krackhardt, 2020. "Online Knowledge Communities: Breaking or Sustaining Knowledge Silos?," Production and Operations Management, Production and Operations Management Society, vol. 29(1), pages 138-155, January.
  24. Ruiqi Rich Zhu & Cheng He & Yu Jeffrey Hu, 2023. "The Effect of Product Recommendations on Online Investor Behaviors," Papers 2303.14263, arXiv.org, revised Nov 2023.
  25. Amelia Fletcher & Peter L Ormosi & Rahul Savani, 2023. "Recommender Systems and Supplier Competition on Platforms," Journal of Competition Law and Economics, Oxford University Press, vol. 19(3), pages 397-426.
  26. Jörg Claussen & Christian Peukert & Ananya Sen, 2019. "The Editor vs. the Algorithm: Returns to Data and Externalities in Online News," CESifo Working Paper Series 8012, CESifo.
  27. Liu, Weihua & Liang, Yanjie & Tang, Ou & Shi, Victor & Liu, Xinyun, 2021. "Cooperate or not? Strategic analysis of platform interactions considering market power and precision marketing," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 154(C).
  28. Hofmann, Jeanette, 2017. "Constellations of trust and distrust in internet governance," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, pages 85-98.
  29. Peukert, Christian & Claussen, Jörg & Kretschmer, Tobias, 2017. "Piracy and box office movie revenues: Evidence from Megaupload," International Journal of Industrial Organization, Elsevier, vol. 52(C), pages 188-215.
  30. Gediminas Adomavicius & Jesse C. Bockstedt & Shawn P. Curley & Jingjing Zhangc, 2018. "Effects of Online Recommendations on Consumers’ Willingness to Pay," Information Systems Research, INFORMS, vol. 29(1), pages 84-102, March.
  31. Giovanni Luca Ciampaglia, 2018. "Fighting fake news: a role for computational social science in the fight against digital misinformation," Journal of Computational Social Science, Springer, vol. 1(1), pages 147-153, January.
  32. Park, YoungSoo & Sim, Jeongeun & Kim, Bosung, 2022. "Online retail operations with “Try-Before-You-Buy”," European Journal of Operational Research, Elsevier, vol. 299(3), pages 987-1002.
  33. Jens Foerderer, 2023. "Should we trust web-scraped data?," Papers 2308.02231, arXiv.org.
  34. Dokyun Lee & Kartik Hosanagar, 2021. "How Do Product Attributes and Reviews Moderate the Impact of Recommender Systems Through Purchase Stages?," Management Science, INFORMS, vol. 67(1), pages 524-546, January.
  35. Chinchanachokchai, Sydney & Thontirawong, Pipat & Chinchanachokchai, Punjaporn, 2021. "A tale of two recommender systems: The moderating role of consumer expertise on artificial intelligence based product recommendations," Journal of Retailing and Consumer Services, Elsevier, vol. 61(C).
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