Centralized Decision Making in an Omnichannel Supply Chain with Stochastic Demand

With retailers increasingly adopting the omnichannel retailing model as a core strategy in their daily operations, this study investigates the impact of random demand on the omnichannel supply chain that employs a combination of the online channel, retail channel, and buy online and pick up in store (BOPS) channel, in light of the more stochastic market after the occurrence of COVID-19. To enhance the sustainable profitability of the omnichannel supply chain, this study considers price and lead time dependent demand with both known and unknown distributions, and establishes mathematical models to maximize profit under centralized situations. The study analyzes the variations in demand with lead time in the three channels and examines the effects of price and lead time on profit. Additionally, it investigates the interactions between price and lead time. Through numerical examples, the study illustrates the effects of the mean and variance of random demand on decision variables and examines the influence of potential demand and the sensitivity of lead time. Overall, this analysis provides valuable insights into the impact of demand randomness on the profitability of an omnichannel supply chain, highlighting the importance of considering price and lead time in the decision-making process.

Automated summary

This study investigates the impact of random demand on the omnichannel supply chain, which employs a combination of online, retail, and buy online and pick up in-store channels. It considers price and lead time-dependent demand with known and unknown distributions and establishes mathematical models to maximize profit. The study analyzes the variations in demand with lead time and examines the effects of price and lead time on profit, as well as the interactions between them.