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Dynamic decision-making analysis of Netflix's decision to not provide ad-supported subscriptions

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  • Zhou, Yufei
  • Wang, Sihan
  • Zhang, Nuo

Abstract

Netflix is a leading digital streaming platform that provides a variety of content to users. Netflix charges a fixed amount from its users for its services. Unlike other digital streaming platforms, Netflix does not support subscriptions supported by ads; consequently, Netflix's subscriptions are decreasing. However, Netflix does not offer ad-supported subscriptions. In this context, we aimed to explain why Netflix does not provide them by modelling a monopolist's decision-making using asymmetric information. We compared a shutdown policy with other strategies using the first-best contract with complete information as the benchmark. The results indicate a close relationship between the customer base and the efficiency of the shutdown policy. This outcome at least partly explains Netflix's choice of strategy, its past success, and its current dilemma.

Suggested Citation

  • Zhou, Yufei & Wang, Sihan & Zhang, Nuo, 2023. "Dynamic decision-making analysis of Netflix's decision to not provide ad-supported subscriptions," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    • Handle: RePEc:eee:tefoso:v:187:y:2023:i:c:s0040162522007399
    DOI: 10.1016/j.techfore.2022.122218
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    References listed on IDEAS

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    1. Pierre‐André Chiappori & Bruno Jullien & Bernard Salanié & François Salanié, 2006. "Asymmetric information in insurance: general testable implications," RAND Journal of Economics, RAND Corporation, vol. 37(4), pages 783-798, December.
    2. Shahul Chettali Hameed, 2022. "Stock Market E-Assistance on Platform-as-a-Service (PaaS)," International Journal of Cloud Applications and Computing (IJCAC), IGI Global Scientific Publishing, vol. 12(2), pages 1-11, April.
    3. Urmila Shrawankar & Chetan Ashokrao Dhule, 2022. "Resource-Efficient Pareto-Optimal Green Scheduler Architecture," International Journal of Cloud Applications and Computing (IJCAC), IGI Global Scientific Publishing, vol. 12(2), pages 1-14, April.
    4. Madhumala R. B. & Harshvardhan Tiwari & Devaraj Verma C., 2022. "Resource Optimization in Cloud Data Centers Using Particle Swarm Optimization," International Journal of Cloud Applications and Computing (IJCAC), IGI Global Scientific Publishing, vol. 12(2), pages 1-12, April.
    5. Yu Hao & Lingzhe Wang & Ying Liu & Jiulun Fan, 2022. "Information Entropy Augmented High Density Crowd Counting Network," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global Scientific Publishing, vol. 18(1), pages 1-15, January.
    6. Elisabetta Iossa & David Martimort, 2011. "The Theory of Incentives Applied to the Transport Sector," Chapters, in: André de Palma & Robin Lindsey & Emile Quinet & Roger Vickerman (ed.), A Handbook of Transport Economics, chapter 29, Edward Elgar Publishing.
    7. Pierre‐André Chiappori & Bruno Jullien & Bernard Salanié & François Salanié, 2006. "Asymmetric information in insurance: general testable implications," RAND Journal of Economics, The RAND Corporation, vol. 37(4), pages 783-798, December.
    8. Saravanan Krishnan & Rajalakshmi N. R., 2022. "A Cost-Optimized Data Parallel Task Scheduling in Multi-Core Resources Under Deadline and Budget Constraints," International Journal of Cloud Applications and Computing (IJCAC), IGI Global Scientific Publishing, vol. 12(2), pages 1-16, April.
    9. Kavita Sharma & B. B. Gupta, 2019. "Towards Privacy Risk Analysis in Android Applications Using Machine Learning Approaches," International Journal of E-Services and Mobile Applications (IJESMA), IGI Global Scientific Publishing, vol. 11(2), pages 1-21, April.
    10. Zhang Ling & Zhang Jia Hao, 2022. "An Intrusion Detection System Based on Normalized Mutual Information Antibodies Feature Selection and Adaptive Quantum Artificial Immune System," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global Scientific Publishing, vol. 18(1), pages 1-25, January.
    11. Armando Barbosa & Ig I. Bittencourt & Sean W. Siqueira & Diego Dermeval & Nicholas J. T. Cruz, 2022. "A Context-Independent Ontological Linked Data Alignment Approach to Instance Matching," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global Scientific Publishing, vol. 18(1), pages 1-29, January.
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