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Investment and Market Structure in Industries with Congestion

Author

Listed:
  • Ramesh Johari

    (Department of Management Science and Engineering, Stanford University, Stanford, California 94305)

  • Gabriel Y. Weintraub

    (Columbia Business School, New York, New York 10027)

  • Benjamin Van Roy

    (Department of Management Science and Engineering, Department of Electrical Engineering, Stanford University, Stanford, California 94305)

Abstract

We analyze investment incentives and market structure under oligopoly competition in industries with congestion effects. Our results are particularly focused on models inspired by modern technology-based services such as telecommunications and computing services. We consider situations where firms compete by simultaneously choosing prices and investments; increasing investment reduces the congestion disutility experienced by consumers. We define a notion of returns to investment, according to which congestion models inspired by delay exhibit increasing returns, whereas loss models exhibit nonincreasing returns. For a broad range of models with nonincreasing returns to investment, we characterize and establish uniqueness of pure-strategy Nash equilibrium. We also provide conditions for existence of pure-strategy Nash equilibrium. We extend our analysis to a model in which firms must additionally decide whether to enter the industry. Our theoretical results contribute to the basic understanding of competition in service industries and yield insight into business and policy considerations.

Suggested Citation

  • Ramesh Johari & Gabriel Y. Weintraub & Benjamin Van Roy, 2010. "Investment and Market Structure in Industries with Congestion," Operations Research, INFORMS, vol. 58(5), pages 1303-1317, October.
  • Handle: RePEc:inm:oropre:v:58:y:2010:i:5:p:1303-1317
    DOI: 10.1287/opre.1100.0827
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    References listed on IDEAS

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    2. Patrick Maillé & Peter Reichl & Bruno Tuffin, 2011. "Interplay between security providers, consumers, and attackers: a weighted congestion game approach," Post-Print inria-00560807, HAL.
    3. Georgia Perakis & Wei Sun, 2014. "Efficiency Analysis of Cournot Competition in Service Industries with Congestion," Management Science, INFORMS, vol. 60(11), pages 2684-2700, November.
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    6. Jacob, Jagan, 2020. "Should competing firms cooperate to reduce congestion?," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    7. Xinyi Hu & George Kesidis & Behdad Heidarpour & Zbigniew Dziong, 2020. "Media delivery competition with edge cloud, remote cloud and networking," Netnomics, Springer, vol. 21(1), pages 17-36, December.
    8. Thành Nguyen & Hang Zhou & Randall A. Berry & Michael L. Honig & Rakesh Vohra, 2016. "The Cost of Free Spectrum," Operations Research, INFORMS, vol. 64(6), pages 1217-1229, December.
    9. Refael Hassin & Yair Y. Shaki & Uri Yovel, 2015. "Optimal service‐capacity allocation in a loss system," Naval Research Logistics (NRL), John Wiley & Sons, vol. 62(2), pages 81-97, March.
    10. Melo, Emerson, 2014. "Price competition, free entry, and welfare in congested markets," Games and Economic Behavior, Elsevier, vol. 83(C), pages 53-72.
    11. Harks, Tobias & Schröder, Marc & Vermeulen, Dries, 2019. "Toll caps in privatized road networks," European Journal of Operational Research, Elsevier, vol. 276(3), pages 947-956.
    12. Key, Peter & Steinberg, Richard, 2020. "Pricing, competition and content for internet service providers," LSE Research Online Documents on Economics 107008, London School of Economics and Political Science, LSE Library.
    13. Lhost Jonathan & Pinto Brijesh & Sibley David, 2015. "Effects of Spectrum Holdings on Equilibrium in the Wireless Industry," Review of Network Economics, De Gruyter, vol. 14(2), pages 111-155, June.

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