摘要
基于对快手和咪咕的双案例分析,通过数据价值链理论的“生成—加工—交换”分析框架,探究了数据要素的劳动性与资产性价值生成机理。研究结果发现,劳动性价值生成包括原生性劳动、加工性劳动和经营性劳动3个环节,而资产性价值生成则涵盖协同性生成、复用性增值和融合性互联3个阶段。无论是劳动性还是资产性价值生成机理,均通过价值回溯分享机制,规范不同主体间的利益分配秩序。此外,数据要素的劳动性和资产性价值生成在时间上具有“共时性”,在空间上具有“共场性”,即数据要素的价值生成过程表现出劳动性与资产性双元混融的逻辑,两种价值生成机理交织融合,共同推动数据要素价值的持续生成。
Based on a dual-case analysis of Kuaishou and Migu,this study explores the labor-based and asset-based value generation mechanisms of data elements through the“generation—processing—exchange”analytical framework of the data value chain theory.The findings reveal that labor-based value generation consists of three key stages:primary labor,processing labor,and operational labor,whereas asset-based value generation encompasses synergistic generation,reutilization-driven enhancement,and integrative interconnection.Both mechanisms,whether labor-based or asset-based,operate through a value retrospection and sharing mechanism,which standardizes the distribution of benefits among different stakeholders.Moreover,labor-based and asset-based value generation exhibit“simultaneity”in time and“coexistence”in space,indicating that the data value generation process is characterized by a dual-fusion logic of labor-based and asset-based mechanisms.These two mechanisms are intricately intertwined and mutually reinforcing,jointly facilitating the sustained value generation of data elements.
作者
张志朋
唱小溪
周禹
张好雨
魏巍
ZHANG Zhipeng;CHANG Xiaoxi;ZHOU Yu;ZHANG Haoyu;WEI Wei(University of Science and Technology Beijing,Beijing,China;China University of Political Science and Law,Beijing,China;Renmin University of China,Beijing,China;Beijing Sport University,Beijing,China;Beijing Wuzi University,Beijing,China)
出处
《管理学报》
北大核心
2025年第7期1215-1226,共12页
Chinese Journal of Management
基金
北京市社会科学基金资助青年学术带头人项目(24DTR036)
国家自然科学基金资助项目(72202224)
国家社会科学基金资助项目(22BGL142)。
关键词
数据要素
劳动性价值
资产性价值
价值生成
data elements
data labor-based value
data asset-based value
value generation
