数据要素赋能传统消费生态重构的关键痛点与全链条治理路径研究

Research on Key Pain Points and Whole-Chain Governance Paths of Traditional Consumption Ecosystem Reconstruction Empowered by Data Elements

摘要: 数据要素的非竞争性、边际成本趋零、价值不确定性、场景依附性四重属性，通过技术赋能、模式创新与需求升级三重机制，推动消费生态从线性供给向全域协同重构。本文从产权界定与信息成本双重视角，分析数据要素驱动消费生态演变的内在机理，梳理渠道、决策、支付、体验四维重构表现，剖析消费关系转型逻辑，针对数字鸿沟、隐私风险、非理性消费等痛点，提出分级认证、隐私计算分层、财政金融激励的全链条治理路径。

Abstract: The four attributes of data elements: non-rivalry, near-zero marginal cost, value uncertainty, and scenario dependency, are driving the reconstruction of the consumption ecosystem from linear supply to holistic synergy through a triple mechanism of technological empowerment, model innovation, and demand upgrading. From the dual perspectives of property rights definition costs and information costs, this study analyzes the internal mechanisms of consumption ecosystem evolution under data element empowerment, outlines the manifestations of reconstruction across four dimensions—channels, decision-making, payment, and experience—and examines the logic of consumption relationship transformation. In response to key pain points including the digital divide, privacy risks, and irrational consumption, this paper proposes whole-chain governance paths encompassing tiered certification, stratified promotion of privacy-preserving computing, and fiscal-financial incentives.