The Path and Countermeasures for Cultivating New Quality Productive Forces Driven by High-quality Supply of Agricultural Data Elements in Shanxi Province, China

ABSTRACT : In the context of the digital era, agricultural data, as a new type of production factor, holds significant practical importance in promoting the intelligentization of agricultural production, optimizing resource allocation, and innovating industrial forms. This paper analyzes the realistic foundation and achievements of agricultural data factor supply in Shanxi Province, and points out the key bottlenecks existing at both the supply and application ends. Based on this, a theoretical framework integrating "factor-ecology-value" is constructed, and three implementation paths are proposed: strengthening top-level institutional design, deepening scenario application and business format integration, and enhancing technical infrastructure. Furthermore, forward-looking and actionable countermeasures and suggestions are put forward from six aspects: property rights system, regulatory system, data integration, quality standards, scenario demonstration, and market entity cultivation. The aim is to provide theoretical support and practical reference for Shanxi Province to maximize the value of agricultural data, accelerate the leapfrog development of new quality productive forces, and embark on a path of high-quality development for characteristic agriculture.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-10-28
DOI
https://doi.org/10.5281/zenodo.17464394
Primary Topic
Smart Agriculture and AI
Type
article
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article

The Path and Countermeasures for Cultivating New Quality Productive Forces Driven by High-quality Supply of Agricultural Data Elements in Shanxi Province, China

Zenodo (CERN European Organization for Nuclear Research)
Smart Agriculture and AI
article

The Path and Countermeasures for Cultivating New Quality Productive Forces Driven by High-quality Supply of Agricultural Data Elements in Shanxi Province, China

article en

Abstract

ABSTRACT : In the context of the digital era, agricultural data, as a new type of production factor, holds significant practical importance in promoting the intelligentization of agricultural production, optimizing resource allocation, and innovating industrial forms. This paper analyzes the realistic foundation and achievements of agricultural data factor supply in Shanxi Province, and points out the key bottlenecks existing at both the supply and application ends. Based on this, a theoretical framework integrating "factor-ecology-value" is constructed, and three implementation paths are proposed: strengthening top-level institutional design, deepening scenario application and business format integration, and enhancing technical infrastructure. Furthermore, forward-looking and actionable countermeasures and suggestions are put forward from six aspects: property rights system, regulatory system, data integration, quality standards, scenario demonstration, and market entity cultivation. The aim is to provide theoretical support and practical reference for Shanxi Province to maximize the value of agricultural data, accelerate the leapfrog development of new quality productive forces, and embark on a path of high-quality development for characteristic agriculture.

Zenodo (CERN European Organization for Nuclear Research)
Shanxi Agricultural University (CN), Rural Development Institute (CN)
Openalex Percentile: Top 30%
Smart Agriculture and AI
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