【摘要】 数据要素的价值化是数据要素市场发展的核心命题，也是学术界关注的理论焦点和难点。论文立足于马克思主义政治经济学的理论视角，以“如何实现数据要素价值化”这一根本性问题为起点，通过构建一个“价值创造—价值实现—价值分配”的整合性分析框架，系统梳理和解构数据要素价值化的完整过程。研究首先厘清了数据要素价值化的内涵特征，比较并融合不同学派对数据要素价值来源和实现路径的理论争鸣；其次，重点聚焦生产过程与流通交易过程实现数据要素价值的内在机制，深入剖析数据要素非竞争性属性如何影响实现价值增值的独特规律，从而对现有理论形成拓展；最后，进一步分析了数据要素价值测算的主流方法及其拓展方向，并探讨了当前数据要素价值化面临的挑战与可能的研究展望。论文旨在为理解数据要素价值运动规律提供一个系统性和整合性的理论分析框架，为数据要素价值化相关理论研究的系统深入提供一个理论视角。更多还原

【Abstract】 The market-based allocation and valorization of data as a factor of production serve as both a core engine driving the digital economy and a fundamental proposition in developing data factor markets. These topics have also emerged as key theoretical foci and challenges in academic research. Given the current lack of a scientific and systematic research paradigm in this field,existing studies on the internal logic of data valorization remain fragmented and predominantly focused on isolated aspects. There is a notable absence of a unified analytical framework that integrates the “production” and “circulation” phases of value movement, as well as “creation” and “realization” processes,within a coherent structure capable of encompassing the entire value movement process. From the theoretical perspective of Marxist political economy,this paper addresses the fundamental question of “how to achieve the valorization of data elements” by constructing an integrated “value creation-value realization-value distribution” analytical framework to systematically examine and deconstruct the complete process of data valorization,while offering insights for future research.Initially,the paper clarifies the conceptual characteristics of data valorization,comparing and synthesizing theoretical debates among different schools regarding the source of data value and its realization pathways. It posits that data valorization constitutes a dynamic value movement process spanning value creation,value realization,value augmentation,and value distribution. While adhering to general value laws,this process demonstrates a dialectical unity of sequential progression in time and parallel existence in space,profoundly reflecting the dynamic,cyclical,and expansive characteristics manifested in the contradictory movement between the objectification of value subjects and the subjectification of value objects.Subsequently,the paper defines value realization as the “leap” whereby data products,having completed value creation,convert their intrinsic value into measurable economic outcomes either through market transactions or productive integration into industrial processes—this being the ultimate criterion for successful value realization. The paper identifies two key pathways:the embedding of data as a means of production in industrial processes,and its circulation as a final product in market transactions. Based on this,an analytical framework for data value realization is developed to explore its underlying mechanisms. The research further investigates how the non-rivalrous nature of data facilitates its unique pattern of value augmentation,thereby extending existing theoretical systems.Furthermore,the paper reviews research progress in data value measurement and distribution. Mainstream valuation methods include output elasticity approaches,input-output analysis,and valuation models. To extend this framework,the paper proposes specific directions:for production-side measurement,it suggests developing econometric estimation methods for multi-layer nested CES production functions,introducing dynamic modeling perspectives,and promoting mutual verification and integration of macro-micro measurement results;for circulation-side measurement,it advocates a foundational logic of “scenario classification-entitlement clarification-cost-benefit quantification-pricing modeling-asset incorporation”,which can be extended to include cross-entity derivative value measurement. Additionally,regarding value distribution,the paper examines three dimensions:entitlement allocation,contribution recognition,and benefit sharing,characterized by multi-stakeholder involvement,contribution-oriented principles,and equitable outcomes. By integrating the resource-based view and stakeholder bargaining theory, the paper deconstructs the data value distribution process into three stages:initial endowment,process bargaining,and outcome adjustment.In conclusion,the paper outlines current challenges and future research prospects in data valorization. Although progress has been made across various aspects,multiple practical challenges persist,including technological capacity constraints in value creation,market mechanism and institutional barriers in value realization,deep-seated contradictions in entitlement allocation and ethical governance in value distribution,and the lack of standardized valuation criteria and systematic regulatory frameworks in value measurement. There is an urgent need to advance data valorization through multiple dimensions,such as constructing an interdisciplinary theoretical system,exploring practical pathways,innovating valuation methodologies,and deepening research on value distribution theories and institutional mechanisms.更多还原