Agent-system co-development in supply chain research: Propositions and demonstrative findings

In this study, we develop an agent-system co-development (ASC) theoretical framework for behavioral research in supply chains. The ASC framework aims at explaining the dynamic agent-system relationships in supply chains whereby both action-influencing properties of human agents (e.g., beliefs, personalities, attitudes) and governance-influencing properties of supply chain systems (e.g., social norms, power-dependence, partnerial/adversarial relationship forms) mutually influence each other over time. Two empirical studies are conducted to illustrate how ASC can be a useful theoretical framework in supply chain research and to partially validate the central thesis of ASC in the contexts of partnerial/adversarial supply chain relationships and cooperative/competitive attitudes of human agents in supply chains. The results of both studies support the central thesis of ASC regarding the dynamic agent-system relationships. From two replicated experiments in Study 1, the results suggest that agents’ cooperative and competitive attitudes in business relationships are altered as they are exposed to different supply chain conditions of partnerial and adversarial relationships. In addition, from the multi-method research efforts in Study 2, the results from two survey studies and an experiment are largely consistent with one another, suggesting that personnel turnovers in existing supply chain systems can eventually lead to changes in supply-chain-system properties including the degrees of long-term commitment, information sharing, and joint problem-solving between supply chain partners, as well as the frequency of opportunism occurrences in the supply chains. Finally, we propound that the dynamic agent-system relationships proposed in the ASC framework can be a useful analytical lens in viewing various supply chain issues, such as supply chain evolutions and changes, supply chain designs and personnel decisions, and self-reinforcing feedback loops and decision tendencies in supply chains.