双边平台竞争下低端平台的高端市场入侵策略

With the rapid development of the Internet and information technology, an increasing number of industries, such as media, e-commerce, and securities trading, use bilateral platforms to allow consumers to access, purchase, and use products provided by third parties. Online shopping platforms, which serve as intermediaries connecting consumers and third-party merchants, represent a typical two-sided platform business model. In China, JD. com, Taobao, and Pinduoduo, as the three giant e-commerce platforms, have formed relatively stable consumer segments: JD. com focuses on high-end markets, while Taobao and Pinduoduo mainly target low-end brands. However, after accumulating a certain amount of traffic in the low-end market, the desire to expand their user base and penetrate high-end markets naturally arises. Typically, two strategic approaches are available for such market encroachment: one is to directly invite the high-end merchants to join the platform, and the other is to develop a new high-end App. Pinduoduo has adopted the first strategy to attract well-known high-end brands to directly settle in, such as Apple, to open flagship stores on its platform. Alibaba has adopted the second strategy. It has launched a new Tmall App targeting the high-end market to provide high-quality brands to compete with JD. com and cover more high-end users, which is different from the Taobao App. Therefore, determining which business model is more optimal for low-end platforms remains an open and important research question. Building on the network effects that shape competition between high-end and low-end platforms, this paper develops a game model between high-end and low-end platforms, assuming that there are two types of consumers with different consumption levels (high and low) in the market. Specifically, the following three issues are proposed to be studied for low-end platforms: The change of pricing strategy of high-end and low-end platforms when low-end platforms choose to directly invite the high-end merchants to join the platform or introduce a new high-end App to target the high-end consumers. Comparing and analyzing the impact of the two modes and indirect network effects on the profit of low-end platforms, exploring the optimal strategies for low-end platforms to invade high-end markets. Analyzing the impact of the low-end platform market encroachment strategy on the high-end platform pricing strategy and profit. The main results indicate that: 1) If the low-end platform chooses the strategy of inviting high-end merchants to join directly, an increase in indirect network effects leads both high and low-end platforms to shift from subsidizing merchants to charging them, while their pricing strategies toward consumers shift from charging to subsidizing. 2) If low-end platforms choose to introduce a new high-end App to target the high-end consumers, both high-end and low-end platforms will subsidize merchants when the indirect network effect on the merchant side is small, and charge merchants when the network effect is large. However, both platforms will always adopt a charging strategy towards consumers. These findings suggest that two-sided platforms should explicitly account for network effects when formulating pricing strategies. 3) Due to the significant indirect network effects that can compensate for the profit losses caused by competition, low-end platforms are more willing to choose the strategy of inviting high-end merchants to join the platform in most cases. However, when the indirect network effects are weak, the low-end platform tends to choose to introduce a new high-end App, which also benefits the high-end platform and achieves a win-win situation. 4) However, if consumers in the high-end market multihoming, the strategy of attracting high-end merchants to join the low-end platform will result in a win-win situation for both platforms, which is exactly opposite to the conclusion that consumers are single-homing. The conclusions of this study provide practical implications for platform enterprises seeking to expand their scale and offer valuable insights for optimizing platform pricing strategies. The conclusions drawn in this paper can help platform enterprises make decisions when expanding their scale and have certain reference value and inspirational significance for platform pricing. But this research also has certain shortcomings. In the future, the model structure can be optimized by introducing more realistic influencing factors, considering that high-end and low-end platforms are likely to exhibit more networked characteristics, with not only mutual invasion but also internal and external competition. Coupling the model with empirical data analysis is expected to provide more valuable management insights.