A Study on Channel Decisions of Online Retailers Considering Anticipated Regret

In the direct selling model, this study discusses how consumers' anticipated regret affect online retailers' decision to open offline experience stores in the dual-channel supply chain. By introducing the anticipated regret sensitivity coefficient, a Stackelberg game model is constructed for scenarios before and after opening offline experience stores, which is solved using the backward induction method. Using Matlab numerical simulation, this study compares and analyzes equilibrium price, demand, and profit under different conditions. The simulation results show that the anticipated regret sensitivity coefficient has a significant impact on the profit of offline experience stores and the prices of online and offline products. Opening offline experience stores can only increase the demand and profit of the whole supply chain under certain conditions, and the amount of demand and profit is also influenced by the pricing strategy of each agent in the supply chain. This study proposes a verifiable method system for online retailers to choose the optimal strategy for setting up offline experience stores and provides a reference for them.