IDEAS home Printed from https://ideas.repec.org/a/jas/jasssj/2005-2-2.html
   My bibliography  Save this article

Inter-Organizational Learning and Collective Memory in Small Firms Clusters: an Agent-Based Approach

Author

Listed:
  • Francesca Borrelli
  • Cristina Ponsiglione
  • Luca Iandoli
  • Giuseppe Zollo

Abstract

Literature about Industrial Districts has largely emphasized the importance of both economic and social factors in determining the competitiveness of these particular firms' clusters. For thirty years, the Industrial District productive and organizational model represented an alternative to the integrated model of fordist enterprise. Nowadays, the district model suffers from competitive gaps, largely due to the increase of competitive pressure of globalization. This work aims to analyze, through an agent-based simulation model, the influence of informal socio-cognitive coordination mechanisms on district's performances, in relation to different competitive scenarios. The agent-based simulation approach is particularly fit for this purpose as it is able to represent the Industrial District's complexity. Furthermore, it permits to develop dynamic analysis of district's performances according to different types of environment evolution. The results of this work question the widespread opinion that cooperative districts can answer to environmental changes more effectively that non-cooperative ones. In fact, the results of simulations show that, in the presence of turbulent scenarios, the best performer districts are those in which cooperation and competition, trust and opportunism balance out.

Suggested Citation

  • 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.
    • Handle: RePEc:jas:jasssj:2005-2-2
    as

    Download full text from publisher

    File URL: https://www.jasss.org/8/3/4/4.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rosaria Conte, 1999. "Social Intelligence Among Autonomous Agents," Computational and Mathematical Organization Theory, Springer, vol. 5(3), pages 203-228, October.
    2. Brusco, Sebastiano, 1982. "The Emilian Model: Productive Decentralisation and Social Integration," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 6(2), pages 167-184, June.
    3. Troy J Strader & Fu-ren Lin & Michael J Shaw, 1998. "Simulation of Order Fulfillment in Divergent Assembly Supply Chains," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 1(2), pages 1-5.
    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. 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.
    2. Riccardo Boero & Flaminio Squazzoni, 2005. "Does Empirical Embeddedness Matter? Methodological Issues on Agent-Based Models for Analytical Social Science," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 8(4), pages 1-6.
    3. Prenkert, Frans & Følgesvold, Atle, 2014. "Relationship strength and network form: An agent-based simulation of interaction in a business network," Australasian marketing journal, Elsevier, vol. 22(1), pages 15-27.

    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. Luca Iandoli & Elio Marchione & Cristina Ponsiglione & Giuseppe Zollo, 2009. "Learning and Structural Properties in Small Firms’ Networks: A Computational Agent-Based Model," Research in Economics and Business: Central and Eastern Europe, Tallinn School of Economics and Business Administration, Tallinn University of Technology, vol. 1(1).
    2. Marta Gancarczyk, 2010. "Model schyłku i odrodzenia klastrów," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 3, pages 1-21.
    3. Cirer-Costa, Joan Carles, 2015. "The pressure of tourism on the Mediterranean coastline and beaches," MPRA Paper 62843, University Library of Munich, Germany.
    4. Carla Costa & Rui Baptista, 2012. "Agglomeration vs. Organizational Reproduction: The Molds Cluster in Portugal," Papers in Evolutionary Economic Geography (PEEG) 1222, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Nov 2012.
    5. Ariel Mendez & Elena Ragazzi, 2007. "Coopération et gouvernance dans deux districts en transition," CERIS Working Paper 200710, CNR-IRCrES Research Institute on Sustainable Economic Growth - Torino (TO) ITALY - former Institute for Economic Research on Firms and Growth - Moncalieri (TO) ITALY.
    6. Huasheng Zhu & Kelly Wanjing Chen & Juncheng Dai, 2016. "Beyond Apprenticeship: Knowledge Brokers and Sustainability of Apprentice-Based Clusters," Sustainability, MDPI, vol. 8(12), pages 1-17, December.
    7. Roy, Satyaki, 2012. "Spatial Organization Of Production In India: Contesting Themes And Conflicting Evidence," Journal of Regional Development and Planning, Rajarshi Majumder, vol. 1(1), pages 1-16.
    8. Marie-Laure Salles-Djelic & Michel Gutsatz, 2000. "Managerial Competencies for Organizational Flexibility: The Luxury Goods Industry between Tradition and Postmodernism," Post-Print hal-01892018, HAL.
    9. Mark Lazerson & Gianni Lorenzoni, 1999. "Resisting Organizational Inertia: The Evolution of Industrial Districts," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 3(4), pages 361-377, December.
    10. Hervas-Oliver, Jose-Luis & Lleo, María & Cervello, Roberto, 2017. "The dynamics of cluster entrepreneurship: Knowledge legacy from parents or agglomeration effects? The case of the Castellon ceramic tile district," Research Policy, Elsevier, vol. 46(1), pages 73-92.
    11. Francesco Quatraro, 2009. "Innovation, structural change and productivity growth: evidence from Italian regions, 1980--2003," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 33(5), pages 1001-1022, September.
    12. Di Matteo, Dante & Mariotti, Ilaria & Rossi, Federica, 2023. "Transport infrastructure and economic performance: An evaluation of the Milan-Bologna high-speed rail corridor," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    13. Andrea Morrison, 2018. "Spinoffs, parents, and institutions: Evidence from the Italian motorcycle industry," Papers in Evolutionary Economic Geography (PEEG) 1840, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Nov 2018.
    14. Molina Morales, F. Xavier, 2000. "Geographical Embeddedness Of The Firm. A Case Study Based On The Knowledge-Based View," ERSA conference papers ersa00p346, European Regional Science Association.
    15. Thomas Brenner, 2005. "Innovation and cooperation during the emergence of local industrial clusters: An empirical study in Germany," European Planning Studies, Taylor & Francis Journals, vol. 13(6), pages 921-938, September.
    16. Rosenfeld, Martin T. W. & Hornych, Christoph, 2021. "Wie vernetzt sind die privaten Firmen in Mitteldeutschland? Räumliche Muster der Kooperation im Rahmen "Formeller Unternehmensnetzwerke" (FUN)," Arbeitsberichte der ARL: Aufsätze, in: Rosenfeld, Martin T. W. & Stefansky, Andreas (ed.), "Metropolregion Mitteldeutschland" aus raumwissenschaftlicher Sicht, volume 30, pages 96-126, ARL – Akademie für Raumentwicklung in der Leibniz-Gemeinschaft.
    17. Rabellotti, Roberta, 1995. "Is there an "industrial district model"? Footwear districts in Italy and Mexico compared," World Development, Elsevier, vol. 23(1), pages 29-41, January.
    18. Boschma, Ron, 2000. "An Empirical Analysis Of The Industrial Rise Of The Third Italy," ERSA conference papers ersa00p114, European Regional Science Association.
    19. John N H Britton, 2003. "Network Structure of an Industrial Cluster: Electronics in Toronto," Environment and Planning A, , vol. 35(6), pages 983-1006, June.
    20. Kerstin Press, 2006. "Divide to conquer? The Silicon Valley - Boston 128 case revisited," Papers in Evolutionary Economic Geography (PEEG) 0610, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Dec 2006.

    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:jas:jasssj:2005-2-2. 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: Francesco Renzini (email available below). General contact details of provider: .

    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.