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Technological regimes and demand structure in the evolution of the pharmaceutical industry

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  • Christian Garavaglia
  • Franco Malerba
  • Luigi Orsenigo
  • Michele Pezzoni

Abstract

This paper examines how the nature of the technological regime governing innovative activities and the structure of demand interact in determining market structure, with specific reference to the pharmaceutical industry. The key question concerns the observation that—despite high degrees of R&D and marketing-intensity—concentration has been consistently low during the whole evolution of the industry. Standard explanations of this phenomenon refer to the random nature of the innovative process, the patterns of imitation, and the fragmented nature of the market into multiple, independent submarkets. We delve deeper into this issue by using an improved version of our previous “history-friendly” model of the evolution of pharmaceuticals. Thus, we explore the way in which changes in the technological regime and/or in the structure of demand may generate or not substantially higher degrees of concentration. The main results are that, while technological regimes remain fundamental determinants of the patterns of innovation, the demand structure plays a crucial role in preventing the emergence of concentration through a partially endogenous process of discovery of new submarkets. However, it is not simply market fragmentation as such that produces this result, but rather the entity of the “prize” that innovators can gain relative to the overall size of the market. Further, the model shows that emerging industry leaders are innovative early entrants in large submarkets. Copyright Springer-Verlag 2012

Suggested Citation

  • Christian Garavaglia & Franco Malerba & Luigi Orsenigo & Michele Pezzoni, 2012. "Technological regimes and demand structure in the evolution of the pharmaceutical industry," Journal of Evolutionary Economics, Springer, vol. 22(4), pages 677-709, September.
    • Handle: RePEc:spr:joevec:v:22:y:2012:i:4:p:677-709
    DOI: 10.1007/s00191-012-0285-1
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    Cited by:

    1. Garavaglia Christian & Malerba Franco & Orsenigo Luigi & Pezzoni Michele, 2014. "Innovation and Market Structure in Pharmaceuticals: An Econometric Analysis on Simulated Data," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 234(2-3), pages 274-298, April.
    2. R. Fontana & L. Zirulia, 2015. "then came Cisco, and the rest is history : a history friendly model of the Local Area Networking industry," Working Papers wp993, Dipartimento Scienze Economiche, Universita' di Bologna.
    3. Beniamino Callegari & Christophe Feder, 2022. "The long-term economic effects of pandemics: toward an evolutionary approach [Epidemics and trust: the case of the Spanish flu]," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 31(3), pages 715-735.
    4. Thakur-Wernz, Pooja & Bruyaka, Olga & Contractor, Farok, 2022. "Sourcing portfolio diversity in new product development: Antecedents and performance implications," Journal of Business Research, Elsevier, vol. 150(C), pages 179-193.
    5. Peili Yu & Junguo Shi & Bert M. Sadowski & Önder Nomaler, 2020. "Catching Up in the Face of Technological Discontinuity: Exploring the Role of Demand Structure and Technological Regimes in the Transition from 2G to 3G in China," Journal of Evolutionary Economics, Springer, vol. 30(3), pages 815-841, July.
    6. Roberto Fontana & Lorenzo Zirulia, 2015. "“…then came Cisco, and the rest is history”: a ‘history friendly’ model of the Local Area Networking industry," Journal of Evolutionary Economics, Springer, vol. 25(5), pages 875-899, November.
    7. Pierre Barbaroux & Victor Santos Paulino, 2022. "Why do motives matter? A demand-based view of the dynamics of a complex products and systems (CoPS) industry," Journal of Evolutionary Economics, Springer, vol. 32(4), pages 1175-1204, September.
    8. Li, Daitian & Malerba, Franco, 2024. "Technological change and the evolution of the links across sectoral systems: The case of mobile communications," Technovation, Elsevier, vol. 130(C).

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    More about this item

    Keywords

    Industrial dynamics; Innovation; Market structure; Pharmaceuticals; History-friendly model; C63; L10; L65; O30;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • L10 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - General
    • L65 - Industrial Organization - - Industry Studies: Manufacturing - - - Chemicals; Rubber; Drugs; Biotechnology; Plastics
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General

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