Welfare Properties of Profit Maximizing Recommender Systems: Theory and Results from a Randomized Experiment
Open accessAbstract
Recommender systems have been introduced to help consumers navigate large sets of alternatives. They usually lead to more sales, which may increase consumer surplus and firm profit. In this paper, we ask whether the firms’ choice of recommender system might hurt consumers. We use data from a large-scale field experiment in video-on-demand to measure the price elasticity of demand for movies placed in salient and non-salient slots on the TV screen. During this experiment, the firm randomized the prices and slots in which movies were recommended to consumers. This setting readily allows for identifying the effects of price and slot on demand, and thus computes consumer surplus. We find that consumers are less price-elastic toward movies placed in salient slots. Using the outcomes of this experiment, we simulate how consumer surplus and welfare change when the firm implements several types of recommender systems, namely one that maximizes profit. We show that this system hurts consumer surplus and welfare relative to a system that maximizes welfare. We also show that, in our setting, the system that maximizes profit does not generate less consumer surplus than several recommender systems frequently used in practice. Yet, the amount of extra rent the firm can extract from strategically placing movies in salient slots is still a function of the popularity and quality of movies used to do so. Ultimately, our results question whether recommender systems embed mechanisms that extract excessive surplus from consumers, which may call for better scrutiny.
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In social networks, maximizing user engagement may be achieved by promoting content congruent with users' past engagement or ingroup attitudes, or content that humans inherently attend to, such as emotionally and morally charged content.
“In social networks, this may be achieved by promoting content congruent with users' past engagement or ingroup attitudes 134 , or content that humans inherently attend to, such as emotionally and morally charged content 135,136 .”
From Machine culture (2023) · cites this paper as [134]
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- Authors
- Zhang, X., Ferreira, P., de Matos, M. G., & Belo, R.
- Affiliations
- Carnegie Mellon University (US)
- Universidade Católica Portuguesa, Católica Lisbon School of Business and Economics, Palma de Cima, 1649-023 Lisboa Portugal
- Erasmus University Rotterdam (NL)
- Venue
- MIS Quarterly
- Publisher
- MIS Quarterly
- Published
- 2021-03-01
- Volume
- 45
- Issue
- 1
- Pages
- 1-43
- ISSN
- 0276-7783 (ISSN-L)
- 2162-9730
- OpenAlex
- W3137926414
- Cited by
- 29
- References
- 38
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 3 · 2023: 11 · 2022: 4 · 2021: 5 · 2020: 2
- FWCI
- 5.20
- Type
- journal article
- Language
- en
- Open access
- green
- pure.eur.nl
- Locations
- MIS Quarterly (publishedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion, other-oa)
- Journal of the Association for Information Systems (submittedVersion)
- Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, other-oa)
- Topics
- Physical Sciences › Computer Science › Information Systems › Recommender Systems and Techniques
- Social Sciences › Business, Management and Accounting › Strategy and Management › Digital Platforms and Economics
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Market Behavior and Pricing
- Keywords
- recommender systems, consumer surplus, welfare, price elasticity, video on demand, rent extraction, profit maximization, social welfare maximization, recommendation algorithms
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