Can Providing Algorithmic Performance Information Facilitate Humans’ Inventory Ordering Behaviors?
通过现场实验，研究了向管理者提供算法决策系统的性能信息（尤其是负面信息）如何改善其库存订购决策，并发现对低绩效管理者及低销量、高不确定性产品帮助更大。
Over recent years, companies have been increasingly adopting algorithmic decision systems (ADS) to replace humans. In this paper, we focus on how ADS facilitates human managers’ decision making rather than replacing humans altogether in the context of inventory ordering decisions, specifically on the effect of providing ADS performance information to human managers. Using a pair of field experiments, our results suggest that providing ADS performance information can improve their inventory ordering decisions. Interestingly, providing both positive and negative ADS performance information enhances human managers’ inventory ordering decisions, with the latter proving even more effective. Our analyses reveal that compliance and deliberation are two mechanisms through which ADS performance transparency influences inventory ordering decisions. Furthermore, we explore the heterogeneous effect and find that disclosing ADS performance information is more helpful for human managers overseeing products with lower sales and higher uncertainty, thus solving the pain points where human managers rely on algorithmic recommendations the most. Our results also show that ADS performance information serves as an equalizer that benefits low-performing managers more. These results demonstrate the importance of algorithm performance transparency in the human adoption of ADS and shed light on the managerial implications of using ADS within corporations.