Title: Structuring socio-technical complexity in infrastructure systems: an agent-based model
Authors: Reinier Verhoog; Amineh Ghorbani; Esther E. Hardi; Gerard P.J. Dijkema; Margot P.C. Weijnen
Addresses: College of Management of Technology, Swiss Federal Institute of Technology in Lausanne (EPFL), Station 5, CH-1015 Lausanne, Switzerland ' Faculty of Technology, Policy and Management, Delft University of Technology, Jaffalaan 5, 2628 BX Delft, The Netherlands ' Department of Strategy, Alliander N.V., Utrechtseweg 68, 6812 AH Arnhem, The Netherlands ' Faculty of Mathematics and Natural Sciences, University of Groningen, Nijenborgh 4, 9747 AG Groningen, The Netherlands ' Faculty of Technology, Policy and Management, Delft University of Technology, Jaffalaan 5, 2628 BX Delft, The Netherlands
Abstract: In this paper we demonstrate how agent-based modelling can be used to understand the emergence of a new infrastructure system, more specifically, a biogas infrastructure in the Netherlands. The innovative element in our modelling approach is the use of MAIA (modelling agent systems using institutional analysis), a meta-model for agent-based modelling of socio-technical systems, to conceptualise and gain insights into the complexity of infrastructure systems. Through our agent-based simulation model we were able to see how the BioNet infrastructure might evolve over three decades, under various conditions of social norms and institutions. We found that current social norms and institutions allow agricultural biogas production to be economically feasible without any subsidies. The simulations also reveal low expected returns on investment and significant risks for farmers in biogas projects.
Keywords: agent-based modelling; socio-technical complexity; conceptualisation; social simulation; biogas infrastructure; institutional analysis; infrastructure systems; agent-based systems; multi-agent systems; MAS; Netherlands; metamodels; socio-technical systems; STS; agent-based simulation; social norms; agricultural biogas; biogas production; return on investment; RoI; risk assessment; farmers.
DOI: 10.1504/IJCAST.2016.081292
International Journal of Complexity in Applied Science and Technology, 2016 Vol.1 No.1, pp.5 - 21
Received: 30 Apr 2015
Accepted: 10 Nov 2015
Published online: 03 Jan 2017 *