Selling mode selection and AI service strategy in an E-commerce platform supply chain

Abstract

With the advancement and wide adoption of Artificial Intelligence (AI) technology, various industries have recognized its immense potential and significance, especially in the e-commerce sector. This study considers an E-commerce Platform Supply Chain (EPSC) consisting of a manufacturer and a platform that may provide AI service. The primary purpose of this research is to explore the strategic interaction between different customer service strategies (i.e., Manual or AI service) and different selling modes (i.e., Agency or reselling mode). The research results show that if the manual service sensitivity is relatively high, the manufacturer is more willing to set a higher wholesale price. When the service efficiency attenuation effect of the manual customer towards demand is stronger, AI service would bring about more demand. Additionally, when the service efficiency attenuation effect is stronger, or it is weaker but the AI service efficiency is higher, the EPSC could utilize AI service to obtain more profit under reselling mode. Under agency mode, AI service can benefit the EPSC more when the service effect attenuation coefficient is relatively larger. Last but not least, we find that when the AI service cost coefficient is relatively small, the reselling mode can benefit the EPSC more. Most importantly, compared with manual service, AI service provides the EPSC with a new opportunity to embrace the reselling mode more.