Price Optimization of Closed-loop Supply Chain With Uncertain Demand Under Multi-channel Cross Influence

Abstract

Face ubiquitous demand uncertainty and channel cross-influence, how to make price decision to improve profits has become an issue faced by decision makers. This paper concerns multichannel price optimization for a closed-loop supply chain and constructs the deterministic and uncertain models. Taking a real closed-loop clothing supply chain as an example, we carry out parameter assumptions and numerical experiments and analyze the simulation results. Our analysis reveals: (1) The supply chain is more profitable under centralized policy. The company can maximize profits by expanding upstream and downstream. (2) When experienced experts give more accurate error terms, the companies can accurately predict the demand and make price decisions. (3) Raising wholesale price will not maintain manufacturer’s profits growing. Beyond the threshold, the manufacturer’s profit will decrease. (4) The channel cross-influence is beneficial to the supply chain. When other factors remain unchanged, the greater the cross price-demand sensitivity coefficient in a channel, the higher the retailing price and the total profit of the supply chain will be. Decision makers can adjust pricing in time to adapt to changes of cross-influence and uncertain demand. The findings provide theoretical guidance for each player in the closed-loop supply chain.