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A Theoretical Framework for Analysing Technology Transfer Processes Using Agent-Based Modelling: A Case Study on Massive Technology Adoption (AMTEC) Program on Rice Production

Author

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  • William Orjuela-Garzon

    (School of Engineering, Universidad Pontificia Bolivariana, Medellín 050031, Colombia)

  • Santiago Quintero

    (School of Engineering, Universidad Pontificia Bolivariana, Medellín 050031, Colombia)

  • Diana P. Giraldo

    (School of Engineering, Universidad Pontificia Bolivariana, Medellín 050031, Colombia)

  • Laura Lotero

    (School of Engineering, Universidad Pontificia Bolivariana, Medellín 050031, Colombia)

  • César Nieto-Londoño

    (School of Engineering, Universidad Pontificia Bolivariana, Medellín 050031, Colombia)

Abstract

The technology transfer (TT) process has been studied from different approaches to improve productivity and competitiveness in agricultural chains. However, the process is not always presented successfully due to heterogeneity and inequality in the technological capacities (TC) of the agents that are part of the transfer process, in addition to the geographical context, the interaction networks and decision rules, which are key factors to understand the TT phenomenon. In this context and as a case study, the Colombian National Federation of rice growers promoted the development and adoption of technology that increased crop competitiveness and sustainability by implementing a technology transfer program known as the Massive Technology Adoption Program (AMTEC—Adopción Masiva de Tecnología) on rice. With the AMTEC program, average production costs were reduced by 26% (USD 119 per hectare), and it increased average yields by 23% (1.27 tonnes per hectare), which shows the importance of introducing technologies in productive chains in developing countries. This research provides a better understanding of the TT processes, based on the analysis of the interaction dynamics and behaviour patterns between the agents (i.e., generators, intermediaries, or users) in the TT processes. As an analysis tool, the agent-based modelling paradigm (ABM) was proposed to study the emergence at the macro-level of behaviour patterns of a system from the interactions of semi-intelligent agents at the micro-level, using experiments.

Suggested Citation

  • William Orjuela-Garzon & Santiago Quintero & Diana P. Giraldo & Laura Lotero & César Nieto-Londoño, 2021. "A Theoretical Framework for Analysing Technology Transfer Processes Using Agent-Based Modelling: A Case Study on Massive Technology Adoption (AMTEC) Program on Rice Production," Sustainability, MDPI, vol. 13(20), pages 1-23, October.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:20:p:11143-:d:652236
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    1. Koza, Mitchell & Lewin, Arie, 2000. "Managing partnerships and strategic alliances: raising the odds of success," European Management Journal, Elsevier, vol. 18(2), pages 146-151, April.
    2. Robinson, Scott A. & Rai, Varun, 2015. "Determinants of spatio-temporal patterns of energy technology adoption: An agent-based modeling approach," Applied Energy, Elsevier, vol. 151(C), pages 273-284.
    3. Lall, Sanjaya, 1992. "Technological capabilities and industrialization," World Development, Elsevier, vol. 20(2), pages 165-186, February.
    4. Simona Naspetti & Serena Mandolesi & Jeroen Buysse & Terhi Latvala & Philippa Nicholas & Susanne Padel & Ellen J. Van Loo & Raffaele Zanoli, 2017. "Determinants of the Acceptance of Sustainable Production Strategies among Dairy Farmers: Development and Testing of a Modified Technology Acceptance Model," Sustainability, MDPI, vol. 9(10), pages 1-16, October.
    5. F. Castro-Llanos & G. Hyman & J. Rubiano & J. Ramirez-Villegas & H. Achicanoy, 2019. "Climate change favors rice production at higher elevations in Colombia," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 24(8), pages 1401-1430, December.
    6. Hannah Muelder & Tatiana Filatova, 2018. "One Theory - Many Formalizations: Testing Different Code Implementations of the Theory of Planned Behaviour in Energy Agent-Based Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 21(4), pages 1-5.
    7. Michael Fritsch & Viktor Slavtchev, 2011. "Determinants of the Efficiency of Regional Innovation Systems," Regional Studies, Taylor & Francis Journals, vol. 45(7), pages 905-918.
    8. 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.
    9. Carlsson, B & Stankiewicz, R, 1991. "On the Nature, Function and Composition of Technological Systems," Journal of Evolutionary Economics, Springer, vol. 1(2), pages 93-118, April.
    10. Sanjaya Lall, 1998. "Technological capabilities in emerging Asia," Oxford Development Studies, Taylor & Francis Journals, vol. 26(2), pages 213-243.
    11. 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.
    12. A. Dinmohammadi & M. Shafiee, 2017. "Determination of the Most Suitable Technology Transfer Strategy for Wind Turbines Using an Integrated AHP-TOPSIS Decision Model," Energies, MDPI, vol. 10(5), pages 1-17, May.
    13. X Martin & R Salomon, 2003. "Knowledge transfer capacity and its implications for the theory of the multinational corporation," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 34(4), pages 356-373, July.
    14. Audretsch, David B & Feldman, Maryann P, 1996. "R&D Spillovers and the Geography of Innovation and Production," American Economic Review, American Economic Association, vol. 86(3), pages 630-640, June.
    15. Park, Byung Il, 2011. "Knowledge transfer capacity of multinational enterprises and technology acquisition in international joint ventures," International Business Review, Elsevier, vol. 20(1), pages 75-87, February.
    16. David J. Teece & Gary Pisano & Amy Shuen, 1997. "Dynamic capabilities and strategic management," Strategic Management Journal, Wiley Blackwell, vol. 18(7), pages 509-533, August.
    17. Verma, Pranay & Sinha, Neena, 2018. "Integrating perceived economic wellbeing to technology acceptance model: The case of mobile based agricultural extension service," Technological Forecasting and Social Change, Elsevier, vol. 126(C), pages 207-216.
    18. Happe, Kathrin, 2004. "Agricultural policies and farm structures: Agent-based modelling and application to EU-policy reform," Studies on the Agricultural and Food Sector in Transition Economies, Leibniz Institute of Agricultural Development in Transition Economies (IAMO), volume 30, number 14945.
    19. Kathrin Happe, 2005. "Agricultural policies and farm structures - agent-based simulation and application to EU-policy reform," Others 0504011, University Library of Munich, Germany.
    20. Carlsson, Bo & Jacobsson, Staffan, 1994. "Technological systems and economic policy: the diffusion of factory automation in Sweden," Research Policy, Elsevier, vol. 23(3), pages 235-248, May.
    21. Walrave, Bob & Raven, Rob, 2016. "Modelling the dynamics of technological innovation systems," Research Policy, Elsevier, vol. 45(9), pages 1833-1844.
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