Direct selling, agent selling, or dual-format selling: Electronic channel configuration considering channel competition and platform service

Flourishing e-commerce has prompted manufacturers to design different electronic channel structures for consumers' electronic shopping needs. As a result, the study of e-commerce channel configuration decision has become an important research topic. Toward this end, we establish three-stage sequential game models and investigate a manufacturer's electronic channel configuration strategy from the perspective of both the manufacturer and the whole supply chain. In addition to a traditional channel, the main innovation of this paper is the framework involving three different electronic channel structures: the first is direct selling, in which the manufacturer sells products directly to consumers; the second is agent selling, in which the manufacturer sells products through a third-party platform; and the third is dual-format selling, in which the manufacturer sells products through both direct selling and agent selling. In these frameworks, the manufacturer's selling price and the platform's transaction fee are obtained by backward induction. Another innovation is the simultaneous incorporation of key factors such as the cross-channel effect, channel competition and platform service into our discussion. Sensitivity analysis is carried out and numerical examples are given to reveal the impact of exogenous parameters on equilibrium outcomes and channel configuration strategies both theoretically and numerically. Our analysis shows that channel competition intensity and transaction fee impact factor are critical to determining channel configuration. When these two factors are both either large or small, dual-format selling is the optimal configuration; otherwise, agent selling is preferred. In addition, we find that an electronic channel consisting solely of direct selling will never be chosen. In the extended models, we also find that our main results are robust for cases of positive entry cost, endogenous pricing, and demand-driven data value.