IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v24y2005i4p321-355.html
   My bibliography  Save this article

Evaluating Market Attractiveness: Individual Incentives Versus Industry Profitability

Author

Listed:
  • Herbert Dawid
  • Marc Reimann

Abstract

In this paper, we employ an agent-based industry simulation model to study the effects of the interplay between individual firms’ market evaluation strategies on the extent of product innovations and overall industry development. In particular, we show that a homogenous industry consisting of companies with focus on historical profits yields high overall industry profits but is very unstable. The introduction of a single firm oriented towards market growth rather than profits is sufficient to trigger a severe drop in profits and a transformation towards an industry with strong market growth orientation and a large number of marketed product innovations. Furthermore, we show that the degree of horizontal differentiation of product innovations from existing products is of significant importance for the individual incentives to adopt market growth orientation and the effects of such a development on overall industry profits. Copyright Springer Science + Business Media, Inc. 2005

Suggested Citation

  • Herbert Dawid & Marc Reimann, 2005. "Evaluating Market Attractiveness: Individual Incentives Versus Industry Profitability," Computational Economics, Springer;Society for Computational Economics, vol. 24(4), pages 321-355, June.
    • Handle: RePEc:kap:compec:v:24:y:2005:i:4:p:321-355
    DOI: 10.1007/s10614-005-6158-z
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10614-005-6158-z
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10614-005-6158-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Simon, Herbert A, 1978. "Rationality as Process and as Product of Thought," American Economic Review, American Economic Association, vol. 68(2), pages 1-16, May.
    2. Winter, Sidney G., 1984. "Schumpeterian competition in alternative technological regimes," Journal of Economic Behavior & Organization, Elsevier, vol. 5(3-4), pages 287-320.
    3. Jovanovic, Boyan & MacDonald, Glenn M, 1994. "The Life Cycle of a Competitive Industry," Journal of Political Economy, University of Chicago Press, vol. 102(2), pages 322-347, April.
    4. Silverberg, Gerald & Verspagen, Bart, 1994. "Collective Learning, Innovation and Growth in a Boundedly Rational, Evolutionary World," Journal of Evolutionary Economics, Springer, vol. 4(3), pages 207-226, September.
    5. Tesfatsion, Leigh & Judd, Kenneth L., 2006. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers Archive 10368, Iowa State University, Department of Economics.
    6. Beardsley, George & Mansfield, Edwin, 1978. "A Note on the Accuracy of Industrial Forecasts of the Profitability of New Products and Processes," The Journal of Business, University of Chicago Press, vol. 51(1), pages 127-135, January.
    7. Jan Fagerberg, 2003. "Schumpeter and the revival of evolutionary economics: an appraisal of the literature," Journal of Evolutionary Economics, Springer, vol. 13(2), pages 125-159, April.
    8. Bottazzi, Giulio & Dosi, Giovanni & Lippi, Marco & Pammolli, Fabio & Riccaboni, Massimo, 2001. "Innovation and corporate growth in the evolution of the drug industry," International Journal of Industrial Organization, Elsevier, vol. 19(7), pages 1161-1187, July.
    9. Fagiolo, Giorgio & Dosi, Giovanni, 2003. "Exploitation, exploration and innovation in a model of endogenous growth with locally interacting agents," Structural Change and Economic Dynamics, Elsevier, vol. 14(3), pages 237-273, September.
    10. Armstrong, J. Scott & Brodie, Roderick J., 1994. "Effects of portfolio planning methods on decision making: experimental results," MPRA Paper 81684, University Library of Munich, Germany.
    11. Cantner, Uwe & Pyka, Andreas, 1998. "Absorbing Technological Spillovers: Simulations in an Evolutionary Framework," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 7(2), pages 369-397, June.
    12. Klepper, Steven, 1997. "Industry Life Cycles," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 6(1), pages 145-181.
    13. Dawid, Herbert, 2006. "Agent-based Models of Innovation and Technological Change," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 25, pages 1235-1272, Elsevier.
    14. Yildizoglu, Murat, 2002. "Competing R&D Strategies in an Evolutionary Industry Model," Computational Economics, Springer;Society for Computational Economics, vol. 19(1), pages 51-65, February.
    15. Malerba, Franco, 1992. "Learning by Firms and Incremental Technical Change," Economic Journal, Royal Economic Society, vol. 102(413), pages 845-859, July.
    16. Javier Pajares & Adolfo López-Paredes & Cesáreo Hernández-Iglesias, 2003. "Industry As an Organisation of Agents: Innovation and R&D Management," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 6(2), pages 1-7.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Klaus Wersching, 2007. "Agglomeration in an innovative and differentiated industry with heterogeneous knowledge spillovers," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 2(1), pages 1-25, June.
    2. Giorgio Fagiolo & Paul Windrum & Alessio Moneta, 2006. "Empirical Validation of Agent Based Models: A Critical Survey," LEM Papers Series 2006/14, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    3. Klaus Wersching, 2010. "Schumpeterian Competition, Technological Regimes and Learning through Knowledge Spillover," Post-Print hal-00849408, HAL.
    4. Herbert Dawid & Marc Reimann, 2011. "Diversification: a road to inefficiency in product innovations?," Journal of Evolutionary Economics, Springer, vol. 21(2), pages 191-229, May.
    5. Močnik Dijana & Širec Karin, 2015. "Determinants Of A Fast-Growing Firm’s Profits: Empirical Evidence For Slovenia," Scientific Annals of Economics and Business, Sciendo, vol. 62(1), pages 37-54, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dosi, Giovanni & Nelson, Richard R., 2010. "Technical Change and Industrial Dynamics as Evolutionary Processes," Handbook of the Economics of Innovation, in: Bronwyn H. Hall & Nathan Rosenberg (ed.), Handbook of the Economics of Innovation, edition 1, volume 1, chapter 0, pages 51-127, Elsevier.
    2. Murat YILDIZOGLU, 2009. "Evolutionary approaches of economic dynamics (In French)," Cahiers du GREThA (2007-2019) 2009-16, Groupe de Recherche en Economie Théorique et Appliquée (GREThA).
    3. Herbert Dawid & Marc Reimann, 2011. "Diversification: a road to inefficiency in product innovations?," Journal of Evolutionary Economics, Springer, vol. 21(2), pages 191-229, May.
    4. Malerba, Franco, 2007. "Innovation and the dynamics and evolution of industries: Progress and challenges," International Journal of Industrial Organization, Elsevier, vol. 25(4), pages 675-699, August.
    5. Hommes, Cars & Zeppini, Paolo, 2014. "Innovate or Imitate? Behavioural technological change," Journal of Economic Dynamics and Control, Elsevier, vol. 48(C), pages 308-324.
    6. Stefania Vitali & Gabriele Tedeschi & Mauro Gallegati, 2013. "The impact of classes of innovators on technology, financial fragility, and economic growth," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 22(4), pages 1069-1091, August.
    7. Alessandro Caiani, 2017. "Innovation Dynamics and Industry Structure Under Different Technological Spaces," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 3(3), pages 307-341, November.
    8. Giorgio Fagiolo & Paul Windrum & Alessio Moneta, 2006. "Empirical Validation of Agent Based Models: A Critical Survey," LEM Papers Series 2006/14, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    9. Frank Beckenbach & Maria Daskalakis & David Hofmann, 2012. "Agent-based modelling of novelty creating behavior and sectoral growth effects—Linking the creative and the destructive side of innovation," Journal of Evolutionary Economics, Springer, vol. 22(3), pages 513-542, July.
    10. Karolina Safarzyńska & Jeroen Bergh, 2010. "Evolutionary models in economics: a survey of methods and building blocks," Journal of Evolutionary Economics, Springer, vol. 20(3), pages 329-373, June.
    11. Alfred Haid & Markus Thomas Münter, 1999. "Neuere Entwicklungen in der industrieökonomischen Forschung und die aktuelle Berichterstattung über die technologische Leistungsfähigkeit Deutschlands," Discussion Papers of DIW Berlin 188, DIW Berlin, German Institute for Economic Research.
    12. Javier Garcia-Sanchez & Luiz F. Mesquita & Roberto S. Vassolo, 2014. "What doesn't kill you makes you stronger: The evolution of competition and entry-order advantages in economically turbulent contexts," Strategic Management Journal, Wiley Blackwell, vol. 35(13), pages 1972-1992, December.
    13. Coronese, Matteo & Occelli, Martina & Lamperti, Francesco & Roventini, Andrea, 2023. "AgriLOVE: Agriculture, land-use and technical change in an evolutionary, agent-based model," Ecological Economics, Elsevier, vol. 208(C).
    14. Kurt Dopfer, 2012. "The origins of meso economics," Journal of Evolutionary Economics, Springer, vol. 22(1), pages 133-160, January.
    15. Bos, Jaap W.B. & Economidou, Claire & Sanders, Mark W.J.L., 2013. "Innovation over the industry life-cycle: Evidence from EU manufacturing," Journal of Economic Behavior & Organization, Elsevier, vol. 86(C), pages 78-91.
    16. Christian Garavaglia & Franco Malerba & Luigi Orsenigo & Michele Pezzoni, 2013. "Technological Regimes and Demand Structure in the Evolution of the Pharmaceutical Industry," Economic Complexity and Evolution, in: Andreas Pyka & Esben Sloth Andersen (ed.), Long Term Economic Development, edition 127, pages 61-94, Springer.
    17. Franco Malerba & Maureen McKelvey, 2020. "Knowledge-intensive innovative entrepreneurship integrating Schumpeter, evolutionary economics, and innovation systems," Small Business Economics, Springer, vol. 54(2), pages 503-522, February.
    18. Elena Cefis & Franco Malerba & Orietta Marsili & Luigi Orsenigo, 2021. "Time to exit: “revolving door effect” or “Schumpeterian gale of creative destruction”?," Journal of Evolutionary Economics, Springer, vol. 31(5), pages 1465-1494, November.
    19. Werker, Claudia, 2000. "Market performance and competition: A product life cycle model," Wirtschaftswissenschaftliche Diskussionspapiere 10/2000, University of Greifswald, Faculty of Law and Economics.
    20. Zhangqi Zhong & Lingyun He, 2022. "Macro-Regional Economic Structural Change Driven by Micro-founded Technological Innovation Diffusion: An Agent-Based Computational Economic Modeling Approach," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 471-525, February.

    More about this item

    Keywords

    agent-based simulation; innovation dynamics; market attractiveness JEL codes: D83; L11; O32;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • 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:kap:compec:v:24:y:2005:i:4:p:321-355. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.