Quality-Variety Tradeoffs in Recommendation Systems on Content Platforms

References

• Aggarwal CC (2016) Recommender Systems (Springer, Cham, Switzerland).Crossref, Google Scholar
• Aguiar L, Waldfogel J (2018) Quality predictability and the welfare benefits from new products: Evidence from the digitization of recorded music. J. Political Econom. 126(2):492–524.Crossref, Google Scholar
• Amaldoss W, He C (2010) Product variety, informative advertising, and price competition. J. Marketing Res. 47(1):146–156.Crossref, Google Scholar
• Amaldoss W, He C (2013) Pricing prototypical products. Marketing Sci. 32(5):733–752.Link, Google Scholar
• Amaldoss W, He C (2018) Reference-dependent utility, product variety, and price competition. Management Sci. 64(9):4302–4316.Link, Google Scholar
• Amaldoss W, He C (2019) The charm of behavior-based pricing: When consumers’ taste is diverse and the consideration set is limited. J. Marketing Res. 56(5):767–790.Crossref, Google Scholar
• Amaldoss W, Shin W (2025) Content provision on UGC platforms. Management Sci., ePub ahead of print June 18, https://doi.org/10.1287/mnsc.2022.01066.Google Scholar
• Anderson C (2006) The Long Tail: Why the Future of Business is Selling Less of More (Hyperion, New York). Google Scholar
• Ansari A, Mela CF (2003) E-customization. J. Marketing Res. 40(2):131–145.Crossref, Google Scholar
• Ansari A, Essegaier S, Kohli R (2000) Internet recommendation systems. J. Marketing Res. 37(3):363–375.Crossref, Google Scholar
• Berman R, Katona Z (2020) Curation algorithms and filter bubbles in social networks. Marketing Sci. 39(2):296–316.Link, Google Scholar
• Bernile G, Bhagwat V, Yonker S (2018) Board diversity, firm risk, and corporate policies. J. Financial Econom. 127(3):588–612.Crossref, Google Scholar
• Cao HH, Ma L, Ning ZE, Sun B (2024) How does competition affect exploration vs. exploitation? A tale of two recommendation algorithms. Management Sci. 70(2):1029–1051.Link, Google Scholar
• Chen Y, Riordan MH (2007) Price and variety in the spokes model. Econom. J. 117(522):897–921.Google Scholar
• Chen G, Chan T, Zhang D (2025) The effects of recommendations on social engagement and user-generated content creation. Working paper, University of Southern California, California.Google Scholar
• Chen G, Chan T, Zhang D, Liu S, Wu Y (2024) The effects of diversity in algorithmic recommendations on digital content consumption: A field experiment. Preprint, submitted on May 13, https://doi.org/10.2139/ssrn.4365121.Google Scholar
• Covington P, Adams J, Sargin E (2016) Deep neural networks for YouTube recommendations. Sen S, Geyer W, Freyne J, Castells P, eds. Proc. 10th ACM Conf. Recommender Systems (ACM, New York), 191–198.Google Scholar
• Das AS, Datar M, Garg A, Rajaram S (2007) Google news personalization: Scalable online collaborative filtering. Williamson CL, Zurko ME, Patel-Schneider PF, Shenoy PJ, eds. Proc. 16th Internat. Conf. World Wide Web (ACM, New York), 271–280.Google Scholar
• Feng F, Hu M (2024) Market entry and competition under network effects. Oper. Res. 72(6):2467–2487.Link, Google Scholar
• Fleder D, Hosanagar K (2009) Blockbuster culture’s next rise or fall: The impact of recommender systems on sales diversity. Management Sci. 55(5):697–712.Link, Google Scholar
• Goldman W (1983) Adventures in the Screen Trade: A Personal View of Hollywood and Screenwriting (Warner Books, New York).Google Scholar
• Holtz D, Carterette B, Chandar P, Nazari Z, Cramer H, Aral S (2020) The engagement-diversity connection: Evidence from a field experiment on Spotify. Biró P, Hartline JD, Ostrovsky M, Procaccia AD, eds. Proc. 21st ACM Conf. Econom. Comput. (ACM, New York), 75–76.Google Scholar
• Hosanagar K, Fleder D, Lee D, Buja A (2014) Will the global village fracture into tribes? Recommender systems and their effects on consumer fragmentation. Management Sci. 60(4):805–823.Link, Google Scholar
• Hunt V, Layton D, Prince S (2015) Diversity matters. McKinsey Company 1(1):15–29. Google Scholar
• Iyer G, Katona Z (2016) Competing for attention in social communication markets. Management Sci. 62(8):2304–2320.Link, Google Scholar
• Jamieson KH, Cappella JN (2008) Echo Chamber: Rush Limbaugh and the Conservative Media Establishment (Oxford University Press, Oxford, UK).Google Scholar
• Jiang B, Zou T (2020) Consumer search and filtering on online retail platforms. J. Marketing Res. 57(5):900–916.Crossref, Google Scholar
• Latzer M, Hollnbuchner K, Just N, Saurwein F (2016) The economics of algorithmic selection on the internet. Handbook on the Economics of the Internet (Edward Elgar Publishing, Cheltenham, UK), 395–425.Crossref, Google Scholar
• Li L, Chen J, Raghunathan S (2018) Recommender system rethink: Implications for an electronic marketplace with competing manufacturers. Inform. Systems Res. 29(4):1003–1023.Link, Google Scholar
• Li L, Chen J, Raghunathan S (2020) Informative role of recommender systems in electronic marketplaces: A boon or a bane for competing sellers. MIS Quart. 44(4):1957–1986.Crossref, Google Scholar
• Long F, Amaldoss W (2024) Self-preferencing in e-commerce marketplaces: The role of sponsored advertising and private labels. Marketing Sci. 43(5):925–952.Link, Google Scholar
• Pariser E (2011) The Filter Bubble: How the New Personalized Web Is Changing What We Read and How We Think (Penguin, London).Google Scholar
• Qian K, Jain S (2024) Digital content creation: An analysis of the impact of recommendation systems. Management Sci. 70(12):8668–8684.Link, Google Scholar
• Ren Q (2024) Advertising and content creation on digital content platforms. Marketing Sci. 43(4):734–750.Link, Google Scholar
• Schnidman ME (2024) Playing to the algorithm: How Spotify’s recommendations shape music production. Working paper, Microsoft, Seattle, Washington.Google Scholar
• Van Alstyne M, Brynjolfsson E (2005) Global village or cyber-Balkans? Modeling and measuring the integration of electronic communities. Management Sci. 51(6):851–868.Link, Google Scholar
• Wang Y, Tao L, Zhang XX (2024) Recommending for a multi-sided marketplace: A multi-objective hierarchical approach. Marketing Sci. 44(1):1–29.Link, Google Scholar
• Wu Y (2024) Creation, consumption, and control of sensitive content. Marketing Sci. 43(4):885–902.Link, Google Scholar
• Xia T (2025) Supporting content creators on two-sided markets: Experimental evidence from a short-form video platform. Preprint, submitted February 19, https://doi.org/10.2139/ssrn.5118719.Google Scholar
• Zeng Z, Zhang Z, Zhang D, Chan T (2025) The impact of recommender systems on content consumption and production: Evidence from field experiments and structural modeling. Preprint, submitted May 20, https://doi.org/10.2139/ssrn.4915562.Google Scholar
• Zhou B, Zou T (2023) Competing for recommendations: The strategic impact of personalized product recommendations in online marketplaces. Marketing Sci. 42(2):360–376.Link, Google Scholar
• Zou T, Shi Z, Wu Y (2025) Welfare implications of democratization in content creation. Preprint, submitted October 3, https://doi.org/10.2139/ssrn.4662282.Google Scholar