IDEAS home Printed from https://ideas.repec.org/a/oup/indcch/v28y2019i3p589-611..html

Replicator dynamics in value chains: explaining some puzzles of market selection

Author

Listed:
  • Uwe Cantner
  • Ivan Savin
  • Simone Vannuccini

Abstract

The pure model of replicator dynamics provides important insights in the evolution of markets but has not met with much empirical support. This article extends the model to the case of firms vertically integrated into value chains (VCs). Through an extended analytical model and numerical simulations, we show that (i) by taking VCs into account, the replicator dynamics may reverse its effect. In these ”regressive developments” of market selection, firms with low fitness expand because of being integrated with highly fit partners, and the other way around; (ii) allowing a partner’s switching re-introduces selection forces into the upper layers of VCs; and (iii) periods of instability in the early stage of the industry life cycle may be the result of an optimization’ of partners within a value chain, thus providing a novel and simple explanation of the evidence discussed earlier in the literature.

Suggested Citation

  • Uwe Cantner & Ivan Savin & Simone Vannuccini, 2019. "Replicator dynamics in value chains: explaining some puzzles of market selection," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 28(3), pages 589-611.
    • Handle: RePEc:oup:indcch:v:28:y:2019:i:3:p:589-611.
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/icc/dty060
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or

    for a different version of it.

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ivan Savin & Maria Novitskaya, 2023. "Data-driven definitions of gazelle companies that rule out chance: application for Russia and Spain," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 13(3), pages 507-542, September.
    2. Ivan Savin & Kristina Chukavina & Andrey Pushkarev, 2023. "Topic-based classification and identification of global trends for startup companies," Small Business Economics, Springer, vol. 60(2), pages 659-689, February.
    3. Grodzicki, Maciej J. & Skrzypek, Jurand, 2020. "Cost-competitiveness and structural change in value chains – vertically-integrated analysis of the European automotive sector," Structural Change and Economic Dynamics, Elsevier, vol. 55(C), pages 276-287.
    4. Eric Kemp-Benedict, 2022. "A classical-evolutionary model of technological change," Journal of Evolutionary Economics, Springer, vol. 32(4), pages 1303-1343, September.
    5. Uwe Cantner & Holger Graf & Ekaterina Prytkova & Simone Vannuccini, 2018. "The Compositional Nature of Productivity and Innovation Slowdown," Jena Economics Research Papers 2018-006, Friedrich-Schiller-University Jena.
    6. Jan Schulz & Daniel M. Mayerhoffer, 2021. "Equal chances, unequal outcomes? Network-based evolutionary learning and the industrial dynamics of superstar firms," Journal of Business Economics, Springer, vol. 91(9), pages 1357-1385, November.
    7. Shungo Sakaki, 2019. "Equality in Income and Sustainability in Economic Growth: Agent-Based Simulations on OECD Data," Sustainability, MDPI, vol. 11(20), pages 1-32, October.
    8. Luca Fontanelli, 2023. "Theories of market selection: a survey," LEM Papers Series 2023/22, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    9. Savin, Ivan & Mundt, Philipp, 2022. "Drivers of productivity change in global value chains: Reallocation vs. innovation," Economics Letters, Elsevier, vol. 220(C).
    10. Shungo Sakaki, 2017. "Income distribution management to sustain long-term economic growth: does the equalization of income distribution contribute to long-term economic growth?," Evolutionary and Institutional Economics Review, Springer, vol. 14(2), pages 363-395, December.
    11. Savin, I., 2020. "Studying market selection in Russia and abroad: Measurement problems, national specificity and stimulating methods," Journal of the New Economic Association, New Economic Association, vol. 48(4), pages 197-204.
    12. Diego d’Andria, 2025. "Insider imitation with product differentiation," Journal of Evolutionary Economics, Springer, vol. 35(1), pages 95-122, January.
    13. Uwe Cantner & Simone Vannuccini, 2017. "Innovation and lock-in," Chapters, in: Harald Bathelt & Patrick Cohendet & Sebastian Henn & Laurent Simon (ed.), The Elgar Companion to Innovation and Knowledge Creation, chapter 11, pages 165-181, Edward Elgar Publishing.
    14. Shungo Sakaki, 2023. "The rationality of adaptive decision-making and the feasibility of optimal growth planning," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 10(1), pages 1-12, December.
    15. Shungo Sakaki, 2018. "A method of building simulation model for organizational decision-making and inter-organizational control," Evolutionary and Institutional Economics Review, Springer, vol. 15(2), pages 289-313, December.
    16. Cantner, Uwe & Vannuccini, Simone, 2021. "Pervasive technologies and industrial linkages: Modeling acquired purposes," Structural Change and Economic Dynamics, Elsevier, vol. 56(C), pages 386-399.

    More about this item

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:oup:indcch:v:28:y:2019:i:3:p:589-611.. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Oxford University Press (email available below). General contact details of provider: https://academic.oup.com/icc .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.