Learning fair play in industrial symbiotic relationships

In this paper, we provide practical decision support to managers in firms involved in Industrial Symbiotic Relations (ISRs) in terms of strategy development and test the hypothesis that in the long-term, playing a fair strategy for sharing obtainable ISR-related benefits is dominant. We employ multi-agent-based simulations and model industrial decision-makers as interacting agents that observe their history of cooperation decisions in ISRs. The agents are able to: learn from their past, deviate from relations in which their partner plays unfair, and change their strategy to reach higher long-term benefits. Results show that in a long-run, industrial decision makers learn to play fair in ISRs. In addition to managerial support for developing long-lasting ISRs, our work introduces the concept of learning as a notion that links the micromotives in ISRs to their macrobehavior.