Abstract:

[Purpose/Significance] Against the backdrop of the accelerated development of the digital economy, data elements have become a core production factor, driving the optimization of resource allocation and the transformation and upgrading of of industry in China. A series of national policy documents, including the "Data Element ×" Three-Year Action Plan (2024-2026) and the Digital Agriculture and Rural Development Plan (2019-2025), have established systematic progresses for allocating data elements to the market and integrating them deeply into agricultural production, operations, circulation, and services. With the prominent characteristics of scattered data sources, spatiotemporal heterogeneity and multi-stakeholder coupling, the agricultural sector serves as a typical scenario for observing the whole process of data value evolution. Existing studies mostly focus on single dimensions such as technical empowerment or market transaction mechanisms, and fail to fully reveal the dynamic process of data element value release driven by multi-subject collaboration in specific industrial contexts. This research explores the internal logic and realization process of releasing value of data elements in agricultural scenarios from the perspective of value co-creation, so as to provide theoretical support and practical references for allocating data elements in a market-oriented manner. [Method/Process] Twenty-eight typical cases from the agricultural track of the national "Data Element ×" competition were selected as empirical materials, all of which meet three core screening criteria: a complete business closed loop covering the whole data value chain, participation of two or more types of stakeholders, and quantifiable value release effects. Procedural grounded theory was adopted as the core research method, following the standard three-level coding procedure including open coding, axial coding and selective coding. Double independent coding by two researchers with relevant professional backgrounds was applied to ensure coding reliability, and the inter-coder consistency coefficient reached 0.87. The 28 cases were divided into three groups for initial framework construction, category iteration and theoretical saturation test, respectively, to guarantee the rigor and saturation of the theoretical model. [Results/Conclusions] Through systematic coding analysis, 90 initial concepts, 22 basic categories, 8 main categories and 3 core categories were extracted, and a three-layer "driving-supporting-pathway" theoretical model of data element value release was constructed. The findings show that the value co-creation actor network acts as the driving premise, which breaks the dilemma of "unwilling to share and difficult to share" data through multi-stakeholder collaboration and mutual trust mechanism. The data resource integration and governance mechanism serves as the key support, transforming scattered heterogeneous raw data into high-quality usable data resources through multi-source fusion, full-life-cycle governance and trusted environment construction. The data element value transformation mechanism is a process by which data evolve from a resource to a factor and then to a value through algorithm empowerment, scenario-driven service innovation, and data productization. This study broadens the scope of value co-creation theory in the field of data element research, and provides practical, replicable references for the digital transformation of agriculture. Due to the limited sample selection of excellent cases, the research has a certain survivorship bias. Follow-up studies can include cases with unsatisfactory value release effects and perform cross-industry verification to further improve the model's generalizability.

Key words: data elements, value co-creation, value release, data governance, grounded theory