摘要

Because supply chains are complex systems of interdependent subsystems, decisions by one partner can cause large and unpredictable system-wide effects, including the so-called "bullwhip" effect. The predominant approach to mitigating the bullwhip effect has been to provide additional information to supply chain members. However, recent research suggests that even the most information rich conditions lead decision makers to create the bullwhip effect. We propose an adaptive, learning perspective on supply chain decision making. Our model recognizes the key role of meta-decisions whereby decision makers decide whether or not to incorporate additional information into their decision making process based on the extent to which they understand cause and effect relationships. An experiment in which participants made orders in a simulated supply chain confirms that decision makers that felt they understood cause and effect relationships were more likely to incorporate relevant information into their decision processes, and thereby made better ordering decisions.

  • 出版日期2017-2