Abstract:

Practical data shows that the return freight insurance model has achieved great success in the field of e-commerce and has attracted widespread attention in the academic community， but few studies have examined the multi-agent decision-making interactions and the risk transfer function within this model. In order to further clarify the operation mechanism of the return freight insurance model， a Stackelberg game model involving an insurer， an online retailer， and risk-averse consumers is developed， analyzing the insurer's optimal pricing and the retailer's strategy of offering free return freight insurance. By solving the equilibrium via backward induction， it is found that the optimal insurance price increases monotonically with return freight costs， while its relationship with product matching rate， product cost， and consumer risk aversion depends on specific contexts. The retailer offers free insurance only when the price falls below a certain threshold. Furthermore， it is shown that when return costs are low， this model improves both retailer profit and consumer welfare. However， when return freight costs are high， the cost of providing free insurance becomes substantial for the retailer， who transfers this cost to consumers by setting higher product prices， ultimately harming both the retailer and the consumers. These conclusions are validated through extensive numerical analysis and model extensions， helping to reassess the true role of return freight insurance， establish boundary conditions for its implementation， and provide decision-making insights for e-commerce platform operations.

Key words: e-commerce, return freight insurance, pricing strategy, complimentary strategy