人工智能技术对网络外部性产业的影响——以电商平台为例

The Impact of Artificial Intelligence on Network Externalities Industries—A Case Study of E-Commerce Platforms

摘要: 随着数字经济的蓬勃发展，人工智能技术正深刻重构网络外部性产业的运行逻辑与组织形态。目前广泛探讨了数字技术对平台经济的赋能作用，但多将人工智能视为单一的技术变量，缺乏对“技术–网络效应”深层互动机理的系统性解构，尤其忽视了其对网络外部性强度的非线性强化效应。鉴于此，本研究以电商平台为切入点，深入剖析人工智能技术对网络外部性作用机制的微观基础与实际效益。理论分析表明，人工智能通过优化推荐算法、提升供需匹配效率及改善用户体验三重路径，显著放大了平台的网络外部性特征。具体而言，个性化推荐有效压缩了用户信息搜寻成本，智能客服弥合了交易双方的信任鸿沟，而基于大数据的动态定价则实现了平台资源配置的帕累托改进。在效益维度，技术的应用不仅通过增强用户粘性扩大了交易规模，更借助精准营销与智能风控重塑了平台的盈利结构。研究进一步证实，人工智能与网络外部性之间存在正向协同机制，这种“智能增强型”网络效应为平台可持续发展注入了新动能。未来研究应进一步关注算法权力在平衡平台竞争与垄断中的双重角色，以及数据滥用引发的隐私伦理边界问题。

Abstract: With the booming development of the digital economy, artificial intelligence (AI) technology is profoundly reconstructing the operational logic and organizational forms of industries characterized by network externalities. Although existing literature extensively explores the enabling role of digital technology in the platform economy, most treat AI as a singular technical variable, lacking a systematic deconstruction of the deep interaction mechanism between “technology and network effects”, and particularly overlooking its nonlinear reinforcement effect on the intensity of network externalities. In view of this, this study takes e-commerce platforms as the entry point to deeply analyze the micro-foundations and actual benefits of the impact of AI technology on network externality mechanisms. Theoretical analysis indicates that AI significantly amplifies the network externality characteristics of platforms through three pathways: optimizing recommendation algorithms, enhancing supply-demand matching efficiency, and improving user experience. Specifically, personalized recommendations effectively reduce users’ information search costs, intelligent customer service bridges the trust gap between transacting parties, and big data-based dynamic pricing achieves a Pareto improvement in platform resource allocation. In terms of benefits, the application of AI not only expands transaction scale by enhancing user stickiness but also reshapes the platform’s profit structure through precise marketing and intelligent risk control. The study further confirms a positive synergy between AI and network externalities; this “intelligence-augmented” network effect injects new momentum into the sustainable development of platforms. Future research should further focus on the dual role of algorithmic power in balancing platform competition and monopoly, as well as the ethical boundaries of privacy arising from data abuse.