IDEAS home Printed from https://ideas.repec.org/a/inm/ororsc/v10y1999i3p322-341.html
   My bibliography  Save this article

Path Dependence, Competition, and Succession in the Dynamics of Scientific Revolution

Author

Listed:
  • John D. Sterman

    (Sloan School of Management, E53-351, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142)

  • Jason Wittenberg

    (Department of Political Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142)

Abstract

What is the relative importance of structural versus contextual forces in the birth and death of scientific theories? We describe a formal dynamic model of the birth, evolution, and death of scientific paradigms based on Kuhn's Structure of Scientific Revolutions . The model represents scientific activity as a changing set of coupled institutions; a simulated ecology of interacting paradigms in which the creation of new theories is stochastic and endogenous. The model captures the sociological dynamics of paradigms as they compete against one another for members, solve puzzles, and recognize anomalies. We use sensitivity tests and regression to examine the role of intrinsic versus contextual factors in determining paradigm success. We find that situational factors attending the birth of a paradigm largely determine its probability of rising to dominance, while the intrinsic explanatory power of a paradigm is only weakly related to the likelihood of success. For those paradigms surviving the emergence phase, greater explanatory power is significantly related to longevity. However, the relationship between a paradigm's “strength” and the duration of normal science is also contingent on the competitive environment during the emergence phase. Analysis of the model shows the dynamics of competition and succession among paradigms to be conditioned by many positive feedback loops. These self-reinforcing processes amplify intrinsically unobservable microlevel perturbations in the environment—the local conditions of science, society, and self faced by the creators of a new theory—until they reach macroscopic significance. Such path dependent dynamics are the hallmark of self-organizing evolutionary systems. We consider the implications of these results for the rise and fall of new ideas in contexts outside the natural sciences such as management fads.

Suggested Citation

  • John D. Sterman & Jason Wittenberg, 1999. "Path Dependence, Competition, and Succession in the Dynamics of Scientific Revolution," Organization Science, INFORMS, vol. 10(3), pages 322-341, June.
    • Handle: RePEc:inm:ororsc:v:10:y:1999:i:3:p:322-341
    DOI: 10.1287/orsc.10.3.322
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/orsc.10.3.322
    Download Restriction: no
    File URL: https://libkey.io/10.1287/orsc.10.3.322?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
    ---><---

    References listed on IDEAS

    as
    1. Arthur, W Brian, 1989. "Competing Technologies, Increasing Returns, and Lock-In by Historical Events," Economic Journal, Royal Economic Society, vol. 99(394), pages 116-131, March.
    2. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    3. Theresa K. Lant & Stephen J. Mezias, 1992. "An Organizational Learning Model of Convergence and Reorientation," Organization Science, INFORMS, vol. 3(1), pages 47-71, February.
    4. Bikhchandani, Sushil & Hirshleifer, David & Welch, Ivo, 1992. "A Theory of Fads, Fashion, Custom, and Cultural Change in Informational Cascades," Journal of Political Economy, University of Chicago Press, vol. 100(5), pages 992-1026, October.
    5. John D. W. Morecroft, 1985. "Rationality in the Analysis of Behavioral Simulation Models," Management Science, INFORMS, vol. 31(7), pages 900-916, July.
    6. Sterman, John D., 1989. "Deterministic chaos in an experimental economic system," Journal of Economic Behavior & Organization, Elsevier, vol. 12(1), pages 1-28, August.
    7. Wanda J. Orlikowski, 1996. "Improvising Organizational Transformation Over Time: A Situated Change Perspective," Information Systems Research, INFORMS, vol. 7(1), pages 63-92, March.
    Full references (including those not matched with items on IDEAS)

    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. Mercure, Jean-François, 2018. "Fashion, fads and the popularity of choices: Micro-foundations for diffusion consumer theory," Structural Change and Economic Dynamics, Elsevier, vol. 46(C), pages 194-207.
    2. Desmarchelier, Benoît & Fang, Eddy S., 2016. "National culture and innovation diffusion. Exploratory insights from agent-based modeling," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 121-128.
    3. John D. Sterman & Rebecca Henderson & Eric D. Beinhocker & Lee I. Newman, 2007. "Getting Big Too Fast: Strategic Dynamics with Increasing Returns and Bounded Rationality," Management Science, INFORMS, vol. 53(4), pages 683-696, April.
    4. Anita Elberse & Jehoshua Eliashberg, 2003. "Demand and Supply Dynamics for Sequentially Released Products in International Markets: The Case of Motion Pictures," Marketing Science, INFORMS, vol. 22(3), pages 329-354.
    5. R. Bentley & Michael O’Brien & Paul Ormerod, 2011. "Quality versus mere popularity: a conceptual map for understanding human behavior," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 10(2), pages 181-191, December.
    6. Sgrignoli, P. & Agliari, E. & Burioni, R. & Schianchi, A., 2015. "Instability and network effects in innovative markets," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 108(C), pages 260-271.
    7. Edouard Civel & Marc Baudry, 2018. "The Fate of Inventions. What can we learn from Bayesian learning in strategic options model of adoption ?," EconomiX Working Papers 2018-47, University of Paris Nanterre, EconomiX.
    8. Comin, Diego & Rode, Johannes, 2013. "From Green Users to Green Voters," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 63678, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    9. Robin Cowan & William Cowan & G.M. Peter Swann, 2004. "Waves in consumption with interdependence among consumers," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 37(1), pages 149-177, February.
    10. Alexandre Steyer & Jean-Benoît Zimmermann, 1998. "Étude empirique de l'influence sociale dans les phénomènes de diffusion : l'exemple du câble et du fax en France," Économie et Prévision, Programme National Persée, vol. 135(4), pages 109-119.
    11. Venkatesh Bala & Sanjeev Goyal, 1998. "Learning from Neighbours," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 595-621.
    12. den Hartigh, E. & Langerak, F. & Commandeur, H.R., 2002. "The Effects of Self-Reinforcing Mechanisms on Firm Performance," ERIM Report Series Research in Management ERS-2002-46-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    13. Chen, Huayi & Ma, Tieju, 2017. "Optimizing systematic technology adoption with heterogeneous agents," European Journal of Operational Research, Elsevier, vol. 257(1), pages 287-296.
    14. Bell, Ann Maria, 2002. "Locally interdependent preferences in a general equilibrium environment," Journal of Economic Behavior & Organization, Elsevier, vol. 47(3), pages 309-333, March.
    15. Henrich R. Greve & Marc-David L. Seidel, 2015. "The thin red line between success and failure: Path dependence in the diffusion of innovative production technologies," Strategic Management Journal, Wiley Blackwell, vol. 36(4), pages 475-496, April.
    16. Li, Francis G.N. & Trutnevyte, Evelina & Strachan, Neil, 2015. "A review of socio-technical energy transition (STET) models," Technological Forecasting and Social Change, Elsevier, vol. 100(C), pages 290-305.
    17. Cantono, Simona, 2012. "Unveiling diffusion dynamics: an autocatalytic percolation model of environmental innovation diffusion and the optimal dynamic path of adoption subsidies," Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio 201222, University of Turin.
    18. Sridhar Narayanan & Harikesh S. Nair, 2011. "Estimating Causal Installed-Base Effects: A Bias-Correction Approach," Working Papers 11-22, NET Institute.
    19. Bala, Venkatesh & Van Long, Ngo, 2005. "International trade and cultural diversity with preference selection," European Journal of Political Economy, Elsevier, vol. 21(1), pages 143-162, March.
    20. Brozynski, Max T. & Leibowicz, Benjamin D., 2022. "A multi-level optimization model of infrastructure-dependent technology adoption: Overcoming the chicken-and-egg problem," European Journal of Operational Research, Elsevier, vol. 300(2), pages 755-770.

    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:inm:ororsc:v:10:y:1999:i:3:p:322-341. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.