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Towards a Taxonomy of Multi-Agent Simulation Models to Determine Disruptive Technology Adoption Behaviour in the Wine Industry

Michael Paul Kramer (), Joe Viana, Rolf A. E. Mueller (), Claus-Hennig Hanf and Jon H. Hanf ()
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Michael Paul Kramer: Hochschule Geisenheim University
Joe Viana: BI Norwegian Business School
Rolf A. E. Mueller: Christian-Albrechts-Universität zu Kiel
Claus-Hennig Hanf: Christian-Albrechts-Universität zu Kiel
Jon H. Hanf: Hochschule Geisenheim University

Chapter 5 in Agribusiness Innovation and Contextual Evolution, Volume II, 2024, pp 103-130 from Palgrave Macmillan

Abstract: Abstract Multi-agent modelling and simulation (MAMS) is an emerging field in agricultural economics. The models consist of multiple interacting agents representing real-world entities including stakeholders or organizations. They provide better understanding of the behaviour and decision-making processes in complex adaptive systems such as agri-food supply networks. We provide a taxonomy of multi-agent models in the agri-food sector based on their attributes, including agent types, degree of interaction, feedback, and learning. The article provides insights in their use in the wine supply network. We conducted a literature review and found a lack of research in the realms of stakeholder collaboration, technology adoption, and supply network efficiency. The results suggest that MAMS is used primarily in land use exploration and decision making for potential policy changes.

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:pal:pinchp:978-3-031-45742-5_5

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DOI: 10.1007/978-3-031-45742-5_5

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