Agent-based model of self-organized industrial symbiosis

Authored by Mohamed Raouf Ghali, Jean-Marc Frayret, Chahid Ahabchane

Date Published: 2017

DOI: 10.1016/j.jclepro.2017.05.128

Sponsors: National Science and Engineering Research Council of Canada (NSERC)

Platforms: NetLogo

Model Documentation: Other Narrative Flow charts Mathematical description

Model Code URLs: Model code not found

Abstract

Industrial synergies are collaborative partnerships between companies resulting in the sharing of resources or the exchange of material or energy by-products, and leading to cleaner production processes and more efficient use of resources. They generally have both economic and environmental benefits. The creation of such innovative partnerships within a territory leads to the development of an industrial symbiosis (IS), which is a dynamic network of interconnected industrial actors. IS can develop in different manners, with different levels of planning and serendipity, in which the diffusion of trust and knowledge are generally thought to play a key role. This paper proposes and evaluates a simple agent based model of self-organized IS development capable of simulating and predicting the impacts of social factors (i.e., social structure and dynamics, trust, knowledge diffusion) on the creation of industrial synergies and the emergence of IS. This model was tested using NetLogo. Its consistency with the original design objectives was validated with a sensitivity analysis that considered several factors. Next, experiments were designed and carried out irx order to study the influence of the social structure (i.e., types of social network) and dynamics (i.e., creation of new social contacts between plants). Results revealed that both factors have an influence on synergy creation, and IS development is a function of both social dynamics and structure. However, more multidisciplinary analysis is required to better understand the limits of this model, to validate its assumptions, as well as to improve it. (C) 2017 Published by Elsevier Ltd.

Tags

Simulation Agent-based modeling networks Industrial symbiosis dynamics Social embeddedness