IDEAS home Printed from https://ideas.repec.org/a/spr/jknowl/v10y2019i1d10.1007_s13132-017-0446-4.html
   My bibliography  Save this article

Micro-Cultural Preferences and Macro-Percolation of New Ideas: A NetLogo Simulation

Author

Listed:
  • Annie TUBADJI

    (University of Bologna)

  • Vassilis ANGELIS

    (University of the Aegean)

  • Peter NIJKAMP

    (Tinbergen Institute
    A. Mickiewicz University)

Abstract

This paper provides an extension of the Schelling agent-based model (ABM) of segregation which is augmented here with a mechanism for the percolation of new ideas. The main objective of the paper is to demonstrate that individual segregation preferences affect not only the intensity of aggregate segregation, but also the aggregate efficiency from crucial decision-making processes, such as the decision to invest in new ideas. To perform our research, we implement a NetLogo simulation in two steps by (i) obtaining three sets, each composed of 500 random segregation patterns, generated through a one-step simulation of a Schelling ABM for three different levels of segregation preference: namely, 20, 25 and 30%; and (ii) using the obtained level of segregation, we set the porosity level in a model for the percolation of new ideas and record the observed speed of percolation of new ideas for the first 100 steps. We find that levels of segregation due to 20 and 25% individual preference for homophily produce a difference of 3.4% in their effect on the speed of the percolation of new ideas. The levels of segregation of 25 and 30% individual preference for homophily, however, produce a difference of 12.8% in their effect on the percolation of new ideas. This means that the increase of the individual preference for segregation increases the intensity with which segregation acts as a barrier for new ideas to percolate successfully in the world of R&D investment. The segregation-percolation model used can be extended with further dynamics and developed as a code to be added to the NetLogo library. The main implication of our findings is that small changes in segregation preferences as in the Schelling ABM model produces increasingly negative on aggregate level spillover effects on other socio-economic processes, such as percolation of new ideas, which depend on the connectivity between people in the local society.

Suggested Citation

  • Annie TUBADJI & Vassilis ANGELIS & Peter NIJKAMP, 2019. "Micro-Cultural Preferences and Macro-Percolation of New Ideas: A NetLogo Simulation," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 10(1), pages 168-185, March.
  • Handle: RePEc:spr:jknowl:v:10:y:2019:i:1:d:10.1007_s13132-017-0446-4
    DOI: 10.1007/s13132-017-0446-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13132-017-0446-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s13132-017-0446-4?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. Pietro Terna, 2009. "The epidemic of innovation - playing around with an agent-based model," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 18(7), pages 707-728.
    2. Autant-Bernard, Corinne & Fadairo, Muriel & Massard, Nadine, 2013. "Knowledge diffusion and innovation policies within the European regions: Challenges based on recent empirical evidence," Research Policy, Elsevier, vol. 42(1), pages 196-210.
    3. G. M.P. Swann, 2009. "The Economics of Innovation," Books, Edward Elgar Publishing, number 13211.
    4. Wilhite, Allen, 2014. "Network structure, games, and agent dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 47(C), pages 225-238.
    5. Dalmazzo, Alberto & Pin, Paolo & Scalise, Diego, 2014. "Communities and social inefficiency with heterogeneous groups," Journal of Economic Dynamics and Control, Elsevier, vol. 48(C), pages 410-427.
    6. Jacquemet, Nicolas & Yannelis, Constantine, 2012. "Indiscriminate discrimination: A correspondence test for ethnic homophily in the Chicago labor market," Labour Economics, Elsevier, vol. 19(6), pages 824-832.
    7. David Joyce & John Kennison & Owen Densmore & Stephen Guerin & Shawn Barr & Eric Charles & Nicholas S. Thompson, 2006. "My Way or the Highway: a More Naturalistic Model of Altruism Tested in an Iterative Prisoners' Dilemma," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 9(2), pages 1-4.
    8. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    9. Eveline S. Van Leeuwen, 2010. "The effects of future retail developments on the local economy: Combining micro and macro approaches," Papers in Regional Science, Wiley Blackwell, vol. 89(4), pages 691-710, November.
    10. Annie Tubadji & Peter Nijkamp, 2015. "Cultural Gravity Effects among Migrants: A Comparative Analysis of the EU15," Economic Geography, Taylor & Francis Journals, vol. 91(3), pages 343-380, July.
    11. Hong, Lu & Page, Scott E., 2001. "Problem Solving by Heterogeneous Agents," Journal of Economic Theory, Elsevier, vol. 97(1), pages 123-163, March.
    12. Aghion, Philippe & Howitt, Peter, 1992. "A Model of Growth through Creative Destruction," Econometrica, Econometric Society, vol. 60(2), pages 323-351, March.
    13. Daniel Arribas-Bel & Peter Nijkamp & Jacques Poot, 2014. "How Diverse can Spatial Measures of Cultural Diversity be? Results from Monte Carlo Simulations on an Agent-Based Model," Tinbergen Institute Discussion Papers 14-081/VIII, Tinbergen Institute.
    14. Peter Nijkamp & Jacques Poot & Jessie Bakens (ed.), 2015. "The Economics of Cultural Diversity," Books, Edward Elgar Publishing, number 15883.
    15. Charles M. Tiebout, 1956. "A Pure Theory of Local Expenditures," Journal of Political Economy, University of Chicago Press, vol. 64(5), pages 416-416.
    16. Jackson, Matthew O. & López-Pintado, Dunia, 2013. "Diffusion and contagion in networks with heterogeneous agents and homophily," Network Science, Cambridge University Press, vol. 1(1), pages 49-67, April.
    17. Timothy R. Gulden, 2013. "Agent-Based Modeling as a Tool for Trade and Development Theory," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 16(2), pages 1-1.
    18. Fabrizio, Kira R. & Hawn, Olga, 2013. "Enabling diffusion: How complementary inputs moderate the response to environmental policy," Research Policy, Elsevier, vol. 42(5), pages 1099-1111.
    19. repec:hal:pseose:hal-00745109 is not listed on IDEAS
    20. Fabrizio Iozzi, 2008. "A simple implementation of Schelling's segregation model in NetLogo," Working Papers 015, "Carlo F. Dondena" Centre for Research on Social Dynamics (DONDENA), Università Commerciale Luigi Bocconi.
    21. Talke, Katrin & Salomo, Sören & Rost, Katja, 2010. "How top management team diversity affects innovativeness and performance via the strategic choice to focus on innovation fields," Research Policy, Elsevier, vol. 39(7), pages 907-918, September.
    22. Carlos Lozares & Joan Verd & Irene Cruz & Oriol Barranco, 2014. "Homophily and heterophily in personal networks. From mutual acquaintance to relationship intensity," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(5), pages 2657-2670, September.
    23. Juan-Luis Suárez & Fernando Sancho, 2011. "A Virtual Laboratory for the Study of History and Cultural Dynamics," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 14(4), pages 1-19.
    24. Guillermo Montes, 2012. "Using Artificial Societies to Understand the Impact of Teacher Student Match on Academic Performance: The Case of Same Race Effects," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 15(4), pages 1-8.
    25. Chadha, Jagjit S. & Holly, Sean, 2010. "Macroeconomic models and the yield curve: An assessment of the fit," Journal of Economic Dynamics and Control, Elsevier, vol. 34(8), pages 1343-1358, August.
    26. Schelling, Thomas C, 1969. "Models of Segregation," American Economic Review, American Economic Association, vol. 59(2), pages 488-493, May.
    27. Boh, Wai Fong & Evaristo, Roberto & Ouderkirk, Andrew, 2014. "Balancing breadth and depth of expertise for innovation: A 3M story," Research Policy, Elsevier, vol. 43(2), pages 349-366.
    28. Annie Tubadji & Vassilis Angelis & Peter Nijkamp, 2016. "Endogenous intangible resources and their place in the institutional hierarchy," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 36(1), pages 1-28, February.
    29. Yang, Hongyan & Steensma, H. Kevin, 2014. "When do firms rely on their knowledge spillover recipients for guidance in exploring unfamiliar knowledge?," Research Policy, Elsevier, vol. 43(9), pages 1496-1507.
    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. Tubadji, Annie & Nijkamp, Peter & Santarelli, Enrico, 2017. "Shacklean Uncertainty and Cultural Embeddedness as Innovation Constraints in the UK," GLO Discussion Paper Series 111, Global Labor Organization (GLO).
    2. Annie Tubadji & Peter Nijkamp, 2016. "Six degrees of cultural diversity and R&D output efficiency," Letters in Spatial and Resource Sciences, Springer, vol. 9(3), pages 247-264, October.
    3. Tubadji, Annie & Nijkamp, Peter, 2017. "Green Online vs Green Offline preferences on local public goods trade-offs and house prices," Socio-Economic Planning Sciences, Elsevier, vol. 58(C), pages 72-86.
    4. Zhiling Wang & Thomas de Graaff & Peter Nijkamp, 2018. "Barriers of Culture, Networks, and Language in International Migration: A Review," REGION, European Regional Science Association, vol. 5, pages 73-89.
    5. Tubadji, Annie & Nijkamp, Peter, 2016. "Impact of Intangible Cultural Capital on Regional Economic Development: A Study on Culture-Based Development in Greece," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 46(1).
    6. Del Bo, Chiara F., 2016. "The rate of return to investment in R&D: The case of research infrastructures," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 26-37.
    7. Marcel Ausloos & Herbert Dawid & Ugo Merlone, 2015. "Spatial Interactions in Agent-Based Modeling," Dynamic Modeling and Econometrics in Economics and Finance, in: Pasquale Commendatore & Saime Kayam & Ingrid Kubin (ed.), Complexity and Geographical Economics, edition 127, pages 353-377, Springer.
    8. Annie Tubadji & Peter Nijkamp, 2015. "Cultural impact on regional development: application of a PLS-PM model to Greece," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 54(3), pages 687-720, May.
    9. Annie Tubadji & Valentina Montalto, 2021. "Geographies of Flowers and Geographies of Flower Power," Sustainability, MDPI, vol. 13(24), pages 1-23, December.
    10. Chiara F. DEL BO, 2014. "The rate of return to investment in R&D infrastructure: an overview," Departmental Working Papers 2014-11, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    11. Chu, Angus C. & Pan, Shiyuan, 2013. "The Escape-Infringement Effect Of Blocking Patents On Innovation And Economic Growth," Macroeconomic Dynamics, Cambridge University Press, vol. 17(4), pages 955-969, June.
    12. Pierpaolo Parrotta & Dario Pozzoli & Mariola Pytlikova, 2014. "The nexus between labor diversity and firm’s innovation," Journal of Population Economics, Springer;European Society for Population Economics, vol. 27(2), pages 303-364, April.
    13. Aghion, Philippe & Akcigit, Ufuk & Howitt, Peter, 2014. "What Do We Learn From Schumpeterian Growth Theory?," Handbook of Economic Growth, in: Philippe Aghion & Steven Durlauf (ed.), Handbook of Economic Growth, edition 1, volume 2, chapter 0, pages 515-563, Elsevier.
    14. Grimaud, André & Lafforgue, Gilles & Magné, Bertrand, 2011. "Climate change mitigation options and directed technical change: A decentralized equilibrium analysis," Resource and Energy Economics, Elsevier, vol. 33(4), pages 938-962.
    15. Da Rin, Marco & Di Giacomo, Marina & Sembenelli, Alessandro, 2011. "Entrepreneurship, firm entry, and the taxation of corporate income: Evidence from Europe," Journal of Public Economics, Elsevier, vol. 95(9), pages 1048-1066.
    16. Michael Noel & Mark Schankerman, 2013. "Strategic Patenting and Software Innovation," Journal of Industrial Economics, Wiley Blackwell, vol. 61(3), pages 481-520, September.
    17. Neij, Lena & Heiskanen, Eva & Strupeit, Lars, 2017. "The deployment of new energy technologies and the need for local learning," Energy Policy, Elsevier, vol. 101(C), pages 274-283.
    18. Åsa Johansson, 2016. "Public Finance, Economic Growth and Inequality: A Survey of the Evidence," OECD Economics Department Working Papers 1346, OECD Publishing.
    19. Caroline Roussy & Aude Ridier & Karim Chaïb, 2014. "Adoption d’innovations par les agriculteurs : rôle des perceptions et des préférences," Post-Print hal-01123427, HAL.
    20. André Torre, 2014. "Proximity relations at the heart of territorial development processes: from clusters, spatial conflicts and temporary geographical proximity to territorial governance," Chapters, in: André Torre & Frédéric Wallet (ed.), Regional Development and Proximity Relations, chapter 2, pages 94-134, Edward Elgar Publishing.

    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:spr:jknowl:v:10:y:2019:i:1:d:10.1007_s13132-017-0446-4. 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.