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Beyond Equilibrium: Revisiting Two-Sided Markets from an Agent-Based Modeling Perspective

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  • Heinrich, Torsten
  • Gräbner, Claudius

Abstract

Two-sided markets are an important aspect of today's economies. Yet, the attention they have received in economic theory is limited, mainly due to methodological constraints of conventional approaches: two-sided markets quickly lead to non-trivial dynamics that would require a computational approach, as analytical models quickly become intractable. One approach to this problem is to opt for models that operate on an aggregated level, abstracting from most of the (micro-level) causes of these non-trivial dynamics. Here we revisit a well known equilibrium model by Rochet and Tirole of two-sided markets that has taken this approach. Analyzing the model from an agent-based perspective, however, reveals several inconsistencies and implicit assumptions of the original model. This, together with the highly implausible assumptions that are required to make the model analytically tractable, limits its explanatory power significantly and motivates an alternative approach. The agent-based model we propose allows us to study the phenomenon of two-sided markets in a more realistic and adequate manner: Not only are we able to compare different decision making rules for the providers, we are also able to study situations with more than two providers.%We find that Thus, our model represents a first step towards a more realistic and policy-relevant study of two-sided markets.

Suggested Citation

  • Heinrich, Torsten & Gräbner, Claudius, 2015. "Beyond Equilibrium: Revisiting Two-Sided Markets from an Agent-Based Modeling Perspective," MPRA Paper 67860, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:67860
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    References listed on IDEAS

    as
    1. Oz Shy, 2011. "A Short Survey of Network Economics," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 38(2), pages 119-149, March.
    2. Jean-Charles Rochet & Jean Tirole, 2003. "Platform Competition in Two-Sided Markets," Journal of the European Economic Association, MIT Press, vol. 1(4), pages 990-1029, June.
    3. Herbert A. Simon, 1955. "A Behavioral Model of Rational Choice," The Quarterly Journal of Economics, Oxford University Press, vol. 69(1), pages 99-118.
    4. Martin Peitz & Sven Rady & Piers Trepper, 2017. "Experimentation in Two-Sided Markets," Journal of the European Economic Association, European Economic Association, vol. 15(1), pages 128-172.
    5. Katz, Michael L & Shapiro, Carl, 1985. "Network Externalities, Competition, and Compatibility," American Economic Review, American Economic Association, vol. 75(3), pages 424-440, June.
    6. Jean‐Charles Rochet & Jean Tirole, 2006. "Two‐sided markets: a progress report," RAND Journal of Economics, RAND Corporation, vol. 37(3), pages 645-667, September.
    7. Brian Arthur, W. & Ermoliev, Yu. M. & Kaniovski, Yu. M., 1987. "Path-dependent processes and the emergence of macro-structure," European Journal of Operational Research, Elsevier, vol. 30(3), pages 294-303, June.
    8. repec:rje:randje:v:37:y:2006:3:p:668-691 is not listed on IDEAS
    9. Bendor Jonathan & Mookherjee Dilip & Ray Debraj, 2001. "Reinforcement Learning in Repeated Interaction Games," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 1(1), pages 1-44, March.
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    Cited by:

    1. William Rand & Christian Stummer, 2021. "Agent‐based modeling of new product market diffusion: an overview of strengths and criticisms," Annals of Operations Research, Springer, vol. 305(1), pages 425-447, October.
    2. William Rand & Roland T. Rust & Min Kim, 2018. "Complex systems: marketing’s new frontier," AMS Review, Springer;Academy of Marketing Science, vol. 8(3), pages 111-127, December.

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    More about this item

    Keywords

    Two-sided markets; Network externalities; Agent-based modeling; Simulation; Heuristic decision making; Reinforcement learning; Satisficing; Differential evolution; Evolutionary economics; Market structure; IT economics; Equilibrium dynamics;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D4 - Microeconomics - - Market Structure, Pricing, and Design
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation
    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality

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