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Representation of unlearning in the innovation systems: A proposal from agent-based modeling

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Listed:
  • Santiago Quintero Ramírez
  • Walter Lugo Ruiz Castañeda
  • Jorge Robledo Velásquez

Abstract

In the present work it is understood the unlearning as the voluntary effort made by firms to abandon the capacities that are not necessary to compete in an innovation system. Modeling and simulating unlearning makes it possible to know emerging behaviors resulting not only from learning, but also from agents unlearning who try to adapt to other agents and the competitive environment. The objective of this work is to represent and analyze the unlearning from the agent-based methodology. As conclusion, a model representing unlearning as a negative variation in capacities accumulation was obtained, which according to its speed, has a different impact on the performance of the innovation system.

Suggested Citation

  • Santiago Quintero Ramírez & Walter Lugo Ruiz Castañeda & Jorge Robledo Velásquez, 2017. "Representation of unlearning in the innovation systems: A proposal from agent-based modeling," Estudios Gerenciales, Universidad Icesi, vol. 33(145), pages 366-376, November.
    • Handle: RePEc:col:000129:015944
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    as
    1. Jensen, Morten Berg & Johnson, Bjorn & Lorenz, Edward & Lundvall, Bengt Ake, 2007. "Forms of knowledge and modes of innovation," Research Policy, Elsevier, vol. 36(5), pages 680-693, June.
    2. G. Fagiolo & C. Birchenhall & P. Windrum, 2007. "Empirical Validation in Agent-based Models: Introduction to the Special Issue," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 189-194, October.
    3. Leal-Rodríguez, Antonio Luis & Eldridge, Stephen & Roldán, José Luis & Leal-Millán, Antonio Genaro & Ortega-Gutiérrez, Jaime, 2015. "Organizational unlearning, innovation outcomes, and performance: The moderating effect of firm size," Journal of Business Research, Elsevier, vol. 68(4), pages 803-809.
    4. Paul Windrum & Giorgio Fagiolo & Alessio Moneta, 2007. "Empirical Validation of Agent-Based Models: Alternatives and Prospects," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(2), pages 1-8.
    5. Triulzi, Giorgio & Scholz, Ramon & Pyka, Andreas, 2011. "R&D and knowledge dynamics in university-industry relationships in biotech and pharmaceuticals: An agent-based model," FZID Discussion Papers 33-2011, University of Hohenheim, Center for Research on Innovation and Services (FZID).
    6. Hafeez, Khalid & Zhang, YanBing & Malak, Naila, 2002. "Determining key capabilities of a firm using analytic hierarchy process," International Journal of Production Economics, Elsevier, vol. 76(1), pages 39-51, March.
    7. Paul S. Adler & Kim B. Clark, 1991. "Behind the Learning Curve: A Sketch of the Learning Process," Management Science, INFORMS, vol. 37(3), pages 267-281, March.
    8. Bengt-Åke Lundvall, 2007. "National Innovation Systems—Analytical Concept and Development Tool," Industry and Innovation, Taylor & Francis Journals, vol. 14(1), pages 95-119.
    9. Elvira Uyarra & Kieron Flanagan, 2010. "From Regional Systems of Innovation to Regions as Innovation Policy Spaces," Environment and Planning C, , vol. 28(4), pages 681-695, August.
    10. Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 2, number 2.
    11. Richard A. Bettis & C. K. Prahalad, 1995. "The dominant logic: Retrospective and extension," Strategic Management Journal, Wiley Blackwell, vol. 16(1), pages 5-14.
    12. Lall, Sanjaya, 1992. "Technological capabilities and industrialization," World Development, Elsevier, vol. 20(2), pages 165-186, February.
    13. Danny Miller, 1994. "What Happens After Success: The Perils Of Excellence," Journal of Management Studies, Wiley Blackwell, vol. 31(3), pages 325-358, May.
    14. K. J. Arrow, 1971. "The Economic Implications of Learning by Doing," Palgrave Macmillan Books, in: F. H. Hahn (ed.), Readings in the Theory of Growth, chapter 11, pages 131-149, Palgrave Macmillan.
    15. Daniel A. Levinthal, 1997. "Adaptation on Rugged Landscapes," Management Science, INFORMS, vol. 43(7), pages 934-950, July.
    16. Eric D. Darr & Linda Argote & Dennis Epple, 1995. "The Acquisition, Transfer, and Depreciation of Knowledge in Service Organizations: Productivity in Franchises," Management Science, INFORMS, vol. 41(11), pages 1750-1762, November.
    17. Hazhir Rahmandad & John Sterman, 2008. "Heterogeneity and Network Structure in the Dynamics of Diffusion: Comparing Agent-Based and Differential Equation Models," Management Science, INFORMS, vol. 54(5), pages 998-1014, May.
    18. 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.
    19. Michael Hobday, 1995. "Innovation In East Asia," Books, Edward Elgar Publishing, number 226.
    20. John D. Sterman & Nelson P. Repenning & Fred Kofman, 1997. "Unanticipated Side Effects of Successful Quality Programs: Exploring a Paradox of Organizational Improvement," Management Science, INFORMS, vol. 43(4), pages 503-521, April.
    21. Simona Iammarino, 2005. "An evolutionary integrated view of Regional Systems of Innovation: Concepts, measures and historical perspectives," European Planning Studies, Taylor & Francis Journals, vol. 13(4), pages 497-519, June.
    22. Linda Argote & Sara L. Beckman & Dennis Epple, 1990. "The Persistence and Transfer of Learning in Industrial Settings," Management Science, INFORMS, vol. 36(2), pages 140-154, February.
    23. Axelrod, Robert & Tesfatsion, Leigh, 2006. "A Guide for Newcomers to Agent-Based Modeling in the Social Sciences," Staff General Research Papers Archive 12515, Iowa State University, Department of Economics.
    24. de Holan Pablo Martin & Nelson Phillips, 2004. "Organizational forgetting as Strategy," Post-Print hal-02312934, HAL.
    25. Elvira Uyarra, 2010. "What is evolutionary about ‘regional systems of innovation’? Implications for regional policy," Journal of Evolutionary Economics, Springer, vol. 20(1), pages 115-137, January.
    26. Francesca Borrelli & Cristina Ponsiglione & Luca Iandoli & Giuseppe Zollo, 2005. "Inter-Organizational Learning and Collective Memory in Small Firms Clusters: an Agent-Based Approach," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 8(3), pages 1-4.
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    More about this item

    Keywords

    Unlearning; Learning; Capabilities; Agent-based model; Performance;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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