Adaptive supply chains in industrial districts: A complexity science approach focused on learning

Abstract

This paper investigates the relationship between learning and adaptation in supply chains located within industrial districts, with the aim of identifying the best adaptive supply chain. It is motivated by the increasing attention that the design of adaptive supply chains has been receiving in recent years, as it is considered one of the most important critical factors in gaining sustainable competitive advantage in the current hypercompetitive environment. Focusing on two learning processes (i.e., by imitation and by interacting), diverse types of adaptive supply chains recognizable within industrial districts are compared by means of an agent-based simulation on the basis of their adaptive performance in environments characterized by different level of complexity and turbulence. The results confirm that the supply chain type influences the relationship between learning and adaptation and that both the product complexity and the turbulence of the environment moderate this effect. Finally, the best adaptive supply chain in each type of context is identified.