Mitigating supply-demand mismatch: The relationship between inventory sharing and demand learning

扫码查看

原文链接

NETL
NSTL
Wiley

外文摘要：By mitigating supply-demand mismatch through advanced forecast technology, demand learning has attracted widespread attention and is increasingly adopted in conjunction with inventory sharing. However, this combination is not necessarily efficient given the unclear relationship between the two strategies. Therefore, crucially, this article investigates the strategic relationship between inventory sharing and demand learning, that is, when and whether they are substitutes or complements. We develop a theoretical game model consisting of two firms facing uncertain demand, and both of them need to determine their production quantity before demand is realized. Contrary to the intuition that demand learning is a substitute for inventory sharing, we find that these two strategies can be complements when the production cost is relatively low or high. Moreover, when forecast accuracy is relatively low, the substitutability will be weakened while the complementarity will be enhanced as forecast accuracy increases. Additionally, the substitutability first weakly decreases and then weakly increases, while the complementarity first weakly increases and then weakly decreases with the transfer price.

外文关键词：

demand learninginventory sharingsupply-demand mismatch

作者：

Liqun Wei、Wanying Wei、Yunchuan Liu、Jianxiong Zhang、Xuanhua Xu

展开 >

作者单位：

School of Business,Central South University,Changsha,China

College of Systems Engineering,National University of Defense Technology,Changsha,China

College of Business,University of Illinois at Urbana-Champaign,Champaign,Illinois

College of Management and Economics,Tianjin University,Tianjin,China

展开 >

出版年：

2024

DOI：

10.1111/deci.12611

Decision sciences: The journal for the American Institute for Decision Sciences

ISSN：0011-7315

年,卷(期)：2024.55(6)

参考文献量43