Trust based decisions in supply chains with an agent

• This paper focuses on trust mechanism in a two-tier supply chain.
• A trust updating model is built to evaluate agent's trust level.
• The strategy of recommended order quantity and credit standing will affect differently retailer's decision making.
• We propose a series of corresponding strategies according to the experiment results.

In this paper, we propose a quantitative method to study the trust relationship between a retailer (he) and an agent (she) in the supply chain. The retailer seeks private demand forecast information from the agent before procuring the optimal order quantity (OOQ) of a product from a supplier. To earn more profit, the agent has an incentive to inflate her forecast. However, the decisions of the agent has impact on her immediate gains as well as her future credibility as the retailer updates his trust in the agent at the end of each demand period. We study how the repeated interaction and updated trust influence decisions of the retailer and the agent and their impacts on the supply chain performance. We also investigate how social characteristics of the agent affect the decisions and supply chain performances. In particular, we consider two types of agents: a benevolent agent who seeks to maximize the retailer's profit and a selfish agent who cares only her own profit. The simulation results and analyses of this paper show, that trust updating model effectively embodies the idea of punishment for opportunism and maliciously recommended behavior which are brought about under the influence of the selfish commission agent; that trust value will decline rapidly when consecutive trading failure occurs or the commission agent begins to have opportunistic behavior, i.e. the retailer's predicted demand is more accurate than commission agent's; and that to restore trust value has to undergo a lengthy process which will take commission agent a long time and greater effort to earn trust back.