Retailers’ Order Timing Strategies under Competition and Demand Uncertainty

Ozgun Caliskan Demirag, Weili Xue, Jie Wang

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

We examine retailers’ timing of order placement relative to the realization of demand uncertainty. Retailers can commit to an order before demand realization (i.e., “early order commitment”), or they can postpone ordering until they observe the demand (i.e., “delayed order commitment”). In a supply chain with duopolistic retailers and a single supplier, we develop a multistage, non-cooperative game-theoretic model to study how retailers choose their order commitment strategies. We identify market conditions and explore mechanisms that result in the supply chain members’ equilibrium behaviors and preferences. Our results indicate that both retailers adopt delayed order commitment in equilibrium when the demand variability is sufficiently high or low; whereas, early order commitment arises as an equilibrium strategy for one or both retailers when the demand variability is moderate. In the absence of production lead time or capacity restrictions, key drivers for the observed equilibrium outcomes are the retailers’ price competition, flexibility of contingent ordering, and the supplier's responsive wholesale price decision. The configuration in which the retailers choose opposite order commitment strategies can be sustained in equilibrium for symmetric retailers when the competition is not too intense or the supplier's production cost is sufficiently low. We extend our analysis in several directions, including the scenarios with non-zero production lead time, wholesale price premium for delayed ordering, alternative decision sequence, heterogeneous retailers, and two ordering opportunities. Our findings provide useful insights for retailers regarding the development of their order commitment strategies in a competitive environment and for suppliers regarding the order placement options to offer the retailers.

Original languageEnglish (US)
Article number102256
JournalOmega (United Kingdom)
Volume101
DOIs
StatePublished - Jun 2021

All Science Journal Classification (ASJC) codes

  • Strategy and Management
  • Management Science and Operations Research
  • Information Systems and Management

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