Supply chain ethics and transparency: An agent‐based model approach with Q‐learning agents

Abstract

This study examines suppliers' decision making regarding supply chain ethics and transparency using an agent‐based model with Q‐learning agents. A supplier may not accurately identify the demand for its product because the impact of supply chain ethics on the market is opaque. Thus, we define each supplier as a Q‐learning agent that learns via an iterative game process. Our simulation results show that suppliers maintain low levels of ethics and transparency, which is a collusion behavior. Several suppliers deviate from collusion, but most of the suppliers collude to manage the supply chain unethically and opaquely.

Searching for and evaluating outsourced chief investment officers

“…Learning within the multi‐armed bandit problem is considered the simplest version of reinforcement learning. Reinforcement learning typically requires three elements—specifically, action, reward, and state (Park & Ryu, 2022). When an agent selects an action, a reward is provided and the subsequent state is determined.…”

Supply chain transparency as a signal of ethical production

“…We assume that two distinct firms compete on R&D for supply chain transparency and that consumers prefer ethical production methods. Modifying the consumer utility function of Park and Ryu (2022), we derive stochastic demand based on consumers' preference for an ethical supply chain. Our model confirms that peach firms raise their transparency level and lemon firms lower their transparency level, as the probability that the rival is a peach firm and the efficiency of technology for supply chain transparency is higher 1 .…”