Pricing Power in the Context of Competition Between Platform Sales and Live Streaming Sales

The rapid growth of live-streaming commerce and the diversification of e-commerce channels have created significant debate regarding product pricing power. This paper focuses on the price competition between online dual channels, a complex interplay of supply-side pricing dilemmas and multi-channel price competition. The authors highlight a specific incident involving JD and Li Jiaqi, a prominent live-streamer, where a dispute over pricing highlighted the conflict over pricing power between live-streaming and traditional e-commerce platforms. The research aims to address the lack of modelling research in this area and to explore the ideal state for brands, streamers, and platforms, as well as the conditions influencing this state and how strategic choices impact equilibrium. The study employs a three-party evolutionary game model, incorporating brands, streamers, and traditional e-commerce platforms, and utilizes the "people-goods-scene" perspective to analyze the supply chain dynamics.

The existing literature is categorized into three areas: dual-channel supply chains, live-streaming e-commerce, and the "people-goods-scene" perspective. Research on dual-channel supply chains extensively covers channel competition, pricing strategies, and consumer behavior in online and offline settings, including price discrimination and reference price effects. Live-streaming e-commerce research focuses on pricing decisions, cooperation models with streamers/platforms, consumer purchase intention, and the perceived value of live-streaming. The "people-goods-scene" perspective, originating from Alibaba's new retail theory, emphasizes the interplay between people, goods, and the shopping scene in the context of new retail and live-streaming e-commerce. However, the current literature lacks in-depth analysis of the price game phenomenon between live-streaming and traditional e-commerce platforms from the "people-goods-scene" perspective. This research aims to bridge this gap.

The study constructs a three-party evolutionary game model involving a brand, a streamer, and a traditional e-commerce platform. The model incorporates several key assumptions and parameters, including fixed pit fees, commission proportions for the streamer, platform expenses (drainage costs, commissions, sales expenses, fixed costs), brand wholesale prices, platform subsidies, probabilities of vicious competition, and the effects of healthy and vicious competition on each party. The model analyzes the strategies of each party: the brand (accepting/rejecting low-price negotiations), the streamer (bargaining/not bargaining), and the platform (providing/not providing subsidies). Replication dynamic equations are used to analyze the stability of equilibrium points. Numerical simulations, using Matlab, are conducted to analyze the impact of various parameters (streamer and platform compensation, loss caused by vicious competition, and positive effects of healthy competition) on the system's evolution. The model considers the loss of customers due to brand competition and the probability of product diversion to competitive products. The stability of the equilibrium points is analyzed by examining the eigenvalues of the Jacobian matrix derived from the replication dynamic equations.

The analysis reveals two evolutionary stable strategies (ESS): 1. Brands resist low-price negotiations, streamers avoid bargaining, and platforms avoid subsidies. 2. Brands negotiate low prices, streamers bargain, and platforms provide subsidies. The study shows that, in most cases, brands tend to avoid explicitly stating their opposition to low-price negotiations. However, if a brand shifts towards rejecting low-price negotiations, the negative implications of price wars become crucial. Conversely, a more concessive pricing strategy requires consideration of the potential positive impacts of low-price competition. The stability analysis shows that the system's evolution can lead to either a situation where none of the parties engages in price competition or where they all do. Numerical simulations confirm the analytical findings and further illustrate the influence of various parameters on the system's evolution. The simulations show that the compensation given to the brand by the streamer and the platform under vicious competition influences the brand's willingness to accept low-price negotiations. Similarly, the positive effects of healthy competition and the negative impacts of vicious competition influence the strategies of all three parties. The initial strategies of the parties influence the speed of evolution towards the equilibrium points, but not the equilibrium points themselves.

The findings address the research question by identifying the conditions under which different pricing strategies are adopted by brands, streamers, and platforms. The significance of the results lies in their contribution to understanding the complex interplay of incentives and strategies in a rapidly evolving e-commerce environment. The "people-goods-scene" perspective provides a valuable framework for interpreting the findings, highlighting the importance of consumer behavior, streamer influence, and platform capabilities in shaping the pricing dynamics. The results have implications for supply chain management, marketing strategies, and regulatory policies in the live-streaming e-commerce sector.

This study contributes to the literature by developing a three-party evolutionary game model to analyze pricing power dynamics in the dual-channel e-commerce environment. The model incorporates the "people-goods-scene" perspective, providing a comprehensive framework for understanding the interplay between brands, streamers, and platforms. Future research could incorporate consumer behavior, governmental regulation, and the role of blockchain technology to enhance the model's realism and provide more nuanced insights into this dynamic market.

The study primarily focuses on the interactions between brands, streamers, and platforms, neglecting the direct influence of consumers and regulatory bodies. The model relies on several simplifying assumptions, such as perfect information and rational actors. Future research could explore the impact of information asymmetry, consumer behavior, and regulatory interventions on the pricing power dynamics.