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

Available online at www.rajournals.in International Journal of Management and Economics Invention ISSN: 2395-7220 DOI: 10.47191/ijmei/v11i10.10 Volume: 11 Issue: 10 October 2025 International Open Access Impact Factor: 8.518 (SJIF) Page no. 4778-4789 4778 Xinghua WANG1, IJMEI Volume 11 Issue 10 October 2025 The Path and Countermeasures for Cultivating New Quality Productive Forces Driven by High-quality Supply of Agricultural Data Elements in Shanxi Province, China Xinghua WANG1, Shunchen WU2, Xiaoli GUO1, Xiaoqiang ZHAO1, Caixia WANG1, Yingying SUN1 1Shanxi Agricultural University, Taiyuan, China, 030031 2Chinese Academy of Social Sciences, Institute of Rural Development, Beijing, China, 100008 ARTICLE INFO ABSTRACT Published Online: 28 October 2025 Corresponding Author: Wang Xinghua 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. KEYWORDS: Data elements; New quality productive forces; High-quality supply; Agriculture 1. INTRODUCTION Currently, a new round of technological revolution and industrial transformation is deeply evolving globally. The new generation of information technology, represented by big data, artificial intelligence, and the Internet of Things, is integrating into various fields of economic and social development with unprecedented breadth, depth, and speed, giving rise to profound restructuring of production factors, production methods, and industrial structures. Against this grand backdrop, the significant theoretical innovation of new-quality productive forces has emerged, with its core essence lying in breaking away from traditional economic growth paths and productivity development paradigms, and giving birth to an advanced productive force quality state driven by revolutionary technological breakthroughs, innovative allocation of production factors, and deep transformation and upgrading of industries. Data, as a new type of production factor, is a fundamental resource for digital, networked, and intelligent development, and has been listed alongside traditional factors such as land, labor, capital, and technology as a core engine driving modern economic development. Shanxi Province, as an important energy and heavy chemical industry base and a region with advantages in characteristic agricultural products in China, is in a critical period of promoting the transformation of resource-based economy and achieving high-quality development. Shanxi Province attaches great importance to the deep integration of the digital economy and the real economy, and has clearly proposed to accelerate the development of new-quality productive forces, empower the transformation and upgrading of traditional industries, and cultivate and expand emerging industries. However, it must be soberly recognized that the value release of agricultural data elements still faces numerous bottlenecks and difficulties in Shanxi Province and even nationwide. On the supply side, there are issues such as inconsistent data collection standards, varying quality of underlying data, prominent isolated phenomena of agricultural-related data, and impeded mechanisms for data integration and sharing. On the application side, it manifests as insufficient data mining and analysis capabilities, a shortage of effective supply of data products and “The Path and Countermeasures for Cultivating New Quality Productive Forces Driven by High-quality Supply of Agricultural Data Elements in Shanxi Province, China” 4779 Xinghua WANG1, IJMEI Volume 11 Issue 10 October 2025 services, an underdeveloped mechanism for data value assessment and benefit distribution, and severe challenges in data security and privacy protection. These factors collectively constrain the full transformation of the potential value of agricultural data elements, making it difficult to effectively empower the systematic cultivation and large-scale development of new agricultural productive forces. In view of this, this study is based on serving the major strategic needs of the country and local economic and social development practices, closely focusing on the two core issues of high-quality supply of agricultural data elements and the cultivation of new quality productive forces. Taking Shanxi Province as the specific research object, it aims to systematically explore the following key issues: How to scientifically define and assess the connotation and level of high-quality supply of agricultural data elements? Through what transmission mechanism do agricultural data elements drive the formation and development of new agricultural productive forces in Shanxi? What structural contradictions and institutional obstacles exist in the current supply system of agricultural data elements in Shanxi? How should we plan a clear and feasible implementation path in the future and build an effective policy support system? This study strives to clarify the internal logic, diagnose the practical dilemmas, and propose forward-looking and operational countermeasures through in-depth theoretical analysis and empirical research. It aims to provide high-level theoretical support and decision-making reference for maximizing the value of agricultural data elements in Shanxi Province, accelerating the leapfrog development of new agricultural productive forces, and embarking on a path of high-quality agricultural development with Shanxi characteristics. 2. LITERATURE REVIEW 2.1 Review of Foreign Literature 2.1.1 Research on the connotation, value creation, and property rights definition of agricultural data elements Research on agricultural data elements in academia abroad has extended from the technical level to the fields of economics and law. Early studies often regarded agricultural data as auxiliary information for enhancing production efficiency. With the development of technologies such as big data and the Internet of Things, data has become a new type of key production factor. Its connotation has surpassed traditional meteorological, soil, and market information, encompassing massive, multi-source, heterogeneous datasets generated throughout the entire chain from production to consumption, as well as through machine and human interactions. In terms of value creation, data profoundly reshapes the agricultural value chain by optimizing decision-making, predicting markets, strengthening supply chain collaboration, and facilitating innovative services such as personalized insurance. The realization of its value relies on the integration, analysis, and application capabilities of data. However, the unclear definition of data property rights is seen as a key bottleneck restricting the release of its value. Scholars in Europe and the United States have focused their debates on the ownership of data, including ownership, usage rights, and profit rights, as well as how to balance the rights of data subjects and the development incentives of data controllers. Related research has promoted the exploration of governance models such as data cooperatives and data trusts, aiming to establish a fair, transparent, and credible mechanism for data circulation and benefit distribution. This provides an important reference for China to regulate the agricultural data element market. 2.1.2 The theoretical origins of new quality productive forces and their manifestations in the agricultural sector The term "new quality productive forces" has no direct equivalent in foreign literature, but its core concept aligns closely with categories such as disruptive innovation, technological-economic paradigm shifts, smart agriculture, and "Agriculture 4.0" in Western economics. Its theoretical origins can be traced back to Schumpeter's innovation theory, which emphasizes achieving a qualitative leap in economic growth through creative destruction. In terms of specific manifestations in the agricultural sector, international research generally focuses on the development of smart agriculture driven by data: firstly, it manifests as the intelligence of labor resources, with widespread application of autonomous agricultural machinery, agricultural robots, and drone inspection systems; secondly, it manifests as the upgrading of labor skills, placing new demands on practitioners' digital literacy and data analysis capabilities; thirdly, it manifests as the expansion of labor objects, utilizing data to tap into genetic potential and develop new agricultural products; fourthly, it manifests as the integration of industrial forms, promoting deep integration between agriculture and industries such as information services and cultural tourism, forming new business forms and models. These studies reveal how data, through penetration and integration, triggers systemic changes in agricultural productivity. 2.1.3 International practices and policy implications of data-driven agricultural modernization Developed countries have accumulated rich practical experience in utilizing data elements to drive agricultural modernization. Relying on its strong private sector and regulations such as the Agricultural Data Act, the United States has formed a market-oriented data service model led by large agricultural technology enterprises, emphasizing the commercial application of data products. The European Union places greater emphasis on data sovereignty and privacy protection. Under the framework of the General Data Protection Regulation, it promotes the establishment of an agricultural data space to facilitate data sharing and interoperability under strict rules. Countries such as Japan and the Netherlands focus on leveraging the role of organizations such as agricultural cooperatives to build bridges connecting small farmers with big data, and have achieved efficient utilization of data in fields such as precision agriculture and smart greenhouses. These experiences provide valuable references and warnings for China, “The Path and Countermeasures for Cultivating New Quality Productive Forces Driven by High-quality Supply of Agricultural Data Elements in Shanxi Province, China” 4780 Xinghua WANG1, IJMEI Volume 11 Issue 10 October 2025 especially Shanxi Province, in advancing related work at the regional level. 2.2 Review of Domestic Literature 2.2.1 Research on the market-based allocation of agricultural data elements and supply-side structural reform Domestic research closely revolves around the strategic deployment of market-oriented allocation reform of data elements and agricultural supply-side structural reform. Currently, agricultural data elements in China face issues such as low supply quality, poor circulation mechanisms, and insufficient application depth, which restrict the realization of their potential value. Promoting the market-oriented allocation of agricultural data elements is regarded as an important lever for deepening agricultural supply-side structural reform. Relevant research emphasizes the need to focus on the supply side, by establishing and improving the data property rights system, data classification and grading confirmation and authorization mechanisms, and perfecting data circulation and trading rules and market systems, to stimulate the enthusiasm of various entities to provide high-quality data. At the same time, the research advocates integrating data elements into the entire process of agricultural production, operation, and management, using data flow to lead technology flow, capital flow, and talent flow, optimizing the efficiency of agricultural resource allocation, and enhancing the quality, efficiency, and resilience of the agricultural product supply system, thereby better adapting to changes in market demand and achieving a leap from quantitative change to qualitative change in the agricultural supply system. 2.2.2 Explanation of the theory of new-quality productive forces and research on its adaptability to agriculture Domestic scholars have delved into the Marxist theory of productive forces, offering in-depth interpretations that emphasize its characteristics of high technology, high efficiency, and high quality. The core lies in the leapfrog development of laborers, labor materials, labor objects, and their optimized combination. In the research on adaptability in the agricultural sector, the cultivation of new agricultural productive forces hinges on the dominance of technological innovation, particularly digital technology and biotechnology, replacing traditional growth methods reliant on resource consumption. This is specifically manifested in promoting the transformation of agricultural technological progress from following and paralleling to leading, developing biological breeding, intelligent agricultural machinery and equipment, etc.; promoting the upgrading of agricultural industrial structure towards high-end, intelligent, and green development; and building a new workforce that meets the requirements of modern agricultural development. It is widely believed that data elements, as the key to connecting and activating other elements, are the core engine that drives the emergence of new agricultural productive forces. They can effectively help agriculture break away from traditional path dependence and achieve connotative growth. 2.2.3 Empirical research on data-enabled high-quality development of regional agriculture and relevant discussion on Shanxi province Research on regions with advanced digital economies indicates that the digital transformation of agriculture has a significant positive effect on enhancing total factor productivity and promoting green development. These studies often utilize econometric models to verify the causal relationship between data infrastructure investment, the level of digital technology application, and agricultural economic and ecological benefits. Specifically, preliminary discussions have been initiated in Shanxi Province. Some studies have analyzed the opportunities and challenges faced by Shanxi's characteristic agriculture during the digital transformation process, pointing out that although Shanxi possesses certain advantages in characteristic agricultural product resources, it has significant shortcomings in agricultural data perception capabilities, platform integration levels, and talent reserves. Scholars suggest that Shanxi should align with its strategic positioning as a pilot zone for comprehensive reform in resource-based economic transformation, focus on the development strategy of "specialized and high-quality" agriculture, and explore differentiated paths such as utilizing data elements to transform and enhance traditional agriculture, develop smart agricultural services, and strengthen brand traceability. 2.3 Research Review In summary, domestic and international research has laid a solid theoretical foundation for this topic and provided rich practical insights. Overall, existing research exhibits the following characteristics and trends: Firstly, the academic community has generally recognized the strategic position of data as a new production factor in the process of agricultural modernization, and the understanding of its value creation mechanism is continuously deepening. Secondly, research on new-quality productive forces is in its ascendant phase, and its specific manifestations, measurement methods, and cultivation pathways in the agricultural field are becoming new academic growth points. Thirdly, the market-based allocation of data elements and the construction of property rights systems are global challenges that are being addressed through practical exploration and institutional design, rather than mere theoretical debates. However, existing research still has several areas that require further exploration: Firstly, most studies focus on theoretical elaboration or technical route descriptions at the macro level, and there is still a lack of in-depth, systematic, and mechanism-based research on connecting the prerequisite condition of high-quality supply of data elements with the ultimate goal of cultivating new-quality productive forces, especially regarding the detailed analysis of the transmission pathways through which supply quality specifically affects the qualitative transition of productive forces. Secondly, at the “The Path and Countermeasures for Cultivating New Quality Productive Forces Driven by High-quality Supply of Agricultural Data Elements in Shanxi Province, China” 4781 Xinghua WANG1, IJMEI Volume 11 Issue 10 October 2025 regional level, especially for provinces like Shanxi with unique resource endowments, industrial structures, and development stages, existing research has not delved deeply into how to closely integrate universal theories, experiences, and local realities to propose targeted solutions that are both forward-looking and operable. There is a lack of systematic evaluation of the current situation, bottlenecks, and matching degree with the cultivation needs of new-quality productive forces in the agricultural data element supply of Shanxi Province. Therefore, this study aims to fill the research gaps mentioned above, focusing on the key aspect of high-quality supply, deeply analyzing the internal logic and implementation pathways of agricultural data elements driving the cultivation of new-quality productive forces, and taking Shanxi Province as a specific research object to propose practical countermeasures and suggestions, with the hope of providing theoretical support and decision-making references for achieving high-quality regional agricultural development. 3. CURRENT STATUS OF HIGH-QUALITY SUPPLY OF AGRICULTURAL DATA ELEMENTS AND CULTIVATION OF NEW PRODUCTIVITY IN SHANXI PROVINCE 3.1 The Realistic Foundation and Main Achievements of High-quality Supply of Agricultural Data Elements in Shanxi Province 3.1.1 Take multiple measures to strengthen the agricultural data system. Based on the national big data strategy and digital rural development deployment, Shanxi Province has established a relatively solid foundation for development by prioritizing the construction of the agricultural data element supply system as a leading project for promoting agricultural modernization transformation. At the infrastructure level, through the implementation of special projects such as "Broadband Shanxi", the network coverage and access capabilities in rural areas have been significantly improved, providing underlying support for data collection and transmission. Technologies such as the Internet of Things and remote sensing monitoring have been preliminarily deployed in key agricultural product production areas and modern agricultural industrial parks, establishing an integrated sky-ground data perception network. At the data resource level, the construction of a provincial agricultural and rural big data platform has taken shape, initially aggregating and integrating multi-source heterogeneous data from agricultural production, operation, management, service, and other aspects. This covers core dimensions such as farmland quality, meteorological environment, market conditions, and information on new agricultural business entities, forming a sizable and valuable agricultural data resource pool. At the institutional and regulatory level, the provincial government and relevant departments have successively issued policy documents on promoting the sharing and openness of government data and regulating the application of agricultural information technology. These documents have initially clarified the responsible parties and basic principles of data governance, providing preliminary institutional guarantees for the orderly circulation and safe utilization of data elements. These series of measures collectively constitute the preliminary framework system for the collection, aggregation, management, and application of agricultural data elements in Shanxi Province. 3.1.2 Both the quality and efficiency of agricultural data supply have been enhanced. The quality and efficiency of agricultural data element supply in Shanxi Province have been steadily improved. Firstly, the precision and timeliness of data supply have been enhanced. Relying on the continuously improving perception terminals and transmission networks, the dynamic monitoring capabilities for major crops such as wheat, corn, and minor grains, as well as key industries such as fruits and vegetables, and animal husbandry, have been continuously strengthened. This has enabled near real-time acquisition and precise control of key production information such as seedling conditions, soil moisture, and disaster situations, providing unprecedented data insights for scientific decision-making. Secondly, the breadth and depth of data fusion applications have been expanded. In practice, agricultural data has not only served traditional production statistics but has also been deeply integrated into specific scenarios such as smart breeding, precision irrigation, intelligent feeding, intelligent pest and disease diagnosis, and intelligent scheduling of agricultural machinery, effectively enhancing total factor productivity. In the Jinzhong National Agricultural High-tech Industrial Development Zone (Shanxi Agricultural Valley), the smart farm model based on multi-source data fusion analysis has significantly reduced water, fertilizer, and pesticide inputs while improving crop yield and quality. Thirdly, data-driven service model innovations have emerged. Service models such as agricultural product production and marketing docking, precision pricing of agricultural insurance, and inclusive financial credit based on data analysis have been piloted and promoted, effectively addressing the issue of information asymmetry and reducing market risks and financing costs for agricultural business entities. Overall, agricultural data elements are gradually transitioning from auxiliary resources to core driving forces, injecting strong momentum into the cultivation of new agricultural productive forces. 3.2 Evaluation of the Application Effectiveness of Agricultural Data Elements in Driving the Cultivation of New Quality Productive Forces 3.2.1 Data empowers the entire agricultural chain, driving industrial transformation and upgrading. Agricultural data elements have exerted a preliminary yet positive influence on the efficiency and dynamic changes inherent in the new quality productive forces, by permeating the entire process of agricultural production and management. In “The Path and Countermeasures for Cultivating New Quality Productive Forces Driven by High-quality Supply of Agricultural Data Elements in Shanxi Province, China” 4782 Xinghua WANG1, IJMEI Volume 11 Issue 10 October 2025 the production phase, their effectiveness is primarily manifested in cost reduction, efficiency enhancement, and quality improvement. The application of precision agriculture technology has optimized resource allocation, effectively reduced the unreasonable input of production materials such as fertilizers and pesticides, and achieved a reduction in resource consumption per unit of output and a decrease in negative environmental impacts. Simultaneously, automated and intelligent equipment operates efficiently under data instructions, directly enhancing labor productivity. In the management phase, their effectiveness is highlighted in decision optimization and risk mitigation. Big data analysis assists producers in predicting market trends, guiding planting structures and market timing, and reducing the risk of price fluctuations caused by blindly following trends. A data-based supply chain management system enhances the circulation efficiency of agricultural products from the field to the dining table, reducing losses. Overall, the application of data elements has begun to break the traditional agricultural model reliant on experience and extensive management, driving the transformation of agricultural development towards a more connotative growth model that relies on technological progress and the enhancement of total factor productivity. This is the core manifestation of the replacement of traditional productive forces by new quality productive forces. 3.2.2 Data activates new forms of agricultural business and shapes a new paradigm of development. The value of data elements lies not only in optimizing existing resources but also in creating new ones. They exhibit immense potential in stimulating new forms and models of agriculture, constituting a new growth point for innovative productive forces. On the one hand, data elements have given rise to new forms of "agriculture plus". By combining geographic information data with consumer behavior data, the planning and marketing of rural leisure tourism projects become more targeted; traceable data in the production process endows agricultural products with higher brand premiums and market trust, promoting the development of green and organic agriculture. On the other hand, data elements have facilitated the innovation of industrial organizational forms. The model of the platform economy has begun to extend into the agricultural sector, giving rise to comprehensive data service platforms that integrate production services, technical services, financial services, and market services, thereby facilitating effective connections between small farmers and modern large markets. However, it is also necessary to objectively recognize that such emerging forms and models are still in the exploratory and pilot stages. Their scale and industrialization levels need to be improved, and their contribution to the economic growth of the province's agriculture still requires further nurturing and quantitative assessment. Although the multiplier and amplification effects of data-driven innovation have begun to emerge, they have not yet been fully unleashed. This represents both the current efficiency status and a direction for future breakthroughs. 3.3 The Main Problems and Deep Constraints Faced Currently 3.3.1 Agricultural data supply faces challenges such as isolated islands, poor quality, and weak security. The high-quality supply of agricultural data elements in Shanxi Province still faces a series of urgent practical problems that need to be solved. Firstly, the phenomenon of data silos still exists, and the sharing and circulation are not smooth. Agricultural data is scattered across multiple departments such as agriculture and rural areas, meteorology, water conservancy, and market supervision, as well as various market entities. Due to the lack of unified and mandatory standards and efficient sharing and coordination mechanisms, it is common for multiple data sources to be disconnected from each other, making it difficult to maximize the value of data through aggregation mining. Secondly, the data quality varies greatly, and the level of standardization and normalization is not high. A large amount of data has problems such as inconsistent formats, different calibers, untimely updates, and even missing data. Especially in the grassroots collection process, relying on manual filling can easily introduce errors, affecting the accuracy, completeness, and usability of the data, and restricting subsequent analysis applications. Once again, the data security protection system is not yet sound. The vague definition of data ownership, usage rights, and revenue rights, as well as the relatively weak ability to protect data privacy and network security, have led to concerns among all parties when participating in data sharing and transactions, suppressing the vitality of the data element market. 3.3.2 The transformation of data elements is hindered by the triple structural contradiction. Behind the surface problems lies a deep-seated structural contradiction that constrains the full transformation of the potential of data elements into new and high-quality productive forces. One is institutional barriers. The cross departmental, cross level, and cross regional agricultural data governance architecture has not been fully streamlined, and there is a lack of a clear and well coordinated top-level coordination mechanism, resulting in institutional resistance to data integration and application promotion. The reform process of market-oriented allocation of data elements is relatively lagging behind, and the exploration of key mechanisms such as property rights confirmation, pricing, and trading is insufficient. The second shortcoming is the integration of technology and talent support. Transforming raw data into valuable knowledge and decision support capabilities relies on the deep integration of cutting-edge technologies such as big data and artificial intelligence with agricultural knowledge. However, there is currently a severe shortage of versatile talents who understand both agriculture and data science. The majority of traditional farmers and some new business entities lack digital literacy, resulting in a digital divide. Thirdly, there is a lack of sustainable investment and business models. The construction “The Path and Countermeasures for Cultivating New Quality Productive Forces Driven by High-quality Supply of Agricultural Data Elements in Shanxi Province, China” 4783 Xinghua WANG1, IJMEI Volume 11 Issue 10 October 2025 and operation maintenance costs of agricultural data infrastructure are high, and relying solely on government financial investment is difficult to sustain. At the same time, commercial application scenarios that can clearly demonstrate data investment returns and have strong profitability are still limited, making it difficult to attract large-scale social capital, which affects the sustainability and innovation vitality of the supply system. 4. PATHWAY INNOVATION FOR HIGH-QUALITY AGRICULTURAL DATA FACTOR SUPPLY DRIVING THE CULTIVATION OF NEW QUALITY PRODUCTIVE FORCES IN SHANXI PROVINCE 4.1 Theoretical Framework Promoting the leap of agricultural data factors from a basic resource to a high-quality supply, and using this as a key driving force to cultivate New Quality Productive Forces (NQPF), urgently requires the construction of a rigorous and systematic theoretical analytical framework. The theoretical foundation of this study is rooted in the cross-integration and deepening extension of New Structural Economics, Innovation Ecosystem Theory, and Data Value Chain Theory. New Structural Economics emphasizes that economic development is a dynamic process of structural change, where the upgrading of the factor endowment structure is the fundamental internal driver for optimizing the industrial and technological structures. From this perspective, agricultural data factors, as a new type of advanced production factor, will—through their high-quality supply—induce the reallocation and efficiency multiplication of traditional factors in Shanxi's agricultural sector. This alters the region's comparative advantages and fosters new industrial forms and business models, which embodies the essential characteristics of NQPF: "high-tech, high-efficiency, and high-quality." Innovation Ecosystem Theory extends the perspective to multi-agent interactions and the cultivation of an innovation environment. It posits that the emergence and growth of NQPF in agriculture are not isolated actions of a single technology or enterprise. Rather, they result from the symbiotic evolution of diverse nodes—including government, enterprises, research institutions, and new agricultural business entities—within an ecological field constituted by specific institutions, culture, and infrastructure, achieved through complex non-linear interactions. Within this ecosystem, agricultural data factors play a dual role as both ecological nutrients and connective tissue. The efficiency of their flow, sharing, and value release directly determines the vitality and resilience of the entire ecosystem. Data Value Chain Theory provides an analytical tool at the micro-operational level by deconstructing the process through which data creates value—from collection, storage, and processing to analysis and final application. High-quality supply of agricultural data factors signifies significant enhancement in the accuracy, speed, breadth, and depth of each link in this chain. This enables effective embedding into the entire process of agricultural production, operation, management, and service, thereby achieving value addition. Together, these three theories form the cornerstone of this study, revealing the core logic whereby data factors drive NQPF by altering factor endowments, optimizing the innovation ecology, and reshaping the value chain. Building upon this theoretical foundation, this study constructs a trinity theoretical analytical framework of "Factor–Ecology–Value" to systematically explain the internal mechanism through which high-quality supply of agricultural data factors drives the cultivation of NQPF. This framework comprises three interrelated and progressively advancing logical levels. The first level is the Core Factor Enablement Layer, focusing on the inherent attributes of agricultural data factors and their transformative impact on traditional production factors. Data supplied with high quality possesses characteristics such as high precision, comprehensive coverage, real-time capability, and standardization. As a direct input, combined with advanced technologies like the Internet of Things (IoT), Artificial Intelligence (AI), and blockchain, it enables precise perception, intelligent decision-making, and automated control of agricultural production processes, directly enhancing land productivity, resource utilization efficiency, and labor productivity. Concurrently, acting as a lubricant and magnifier, it optimizes capital allocation efficiency and upgrades human capital skills—thus inducing a multiplier effect through the enablement of traditional factors. The second level is the Innovation Ecology Catalysis Layer, emphasizing the platform and nexus role of data factors in stimulating regional agricultural innovation vitality. High-quality data supply breaks down information barriers, facilitates knowledge sharing, technology spillover, and collaborative R&D among government, enterprises, universities, research institutes, and farmers, thereby reducing innovation costs and risks and accelerating the transformation and application of scientific and technological achievements. This catalyzes the emergence of new market entities such as data service providers, algorithm model suppliers, and smart agriculture solution providers, enriching the "species" within the innovation ecosystem. By fostering an open, collaborative, and co-governed ecology for data resource sharing and application, it provides fertile ground for the emergence of new technologies, business formats, and models. The third level is the Value Network Restructuring Layer, focusing on the profound transformation profound transformation of the industrial system induced by data factors. The high-quality supply of agricultural data factors not only optimizes various segments of the existing industrial chain but also, through convergence with other industries, spawns new business formats such as "Agriculture + Internet," "Agriculture + Finance," and "Agriculture + Culture and Tourism." This extends industrial boundaries and reshapes the modes of value creation and distribution, ultimately promoting the transformation and upgrading of Shanxi's agricultural industrial “The Path and Countermeasures for Cultivating New Quality Productive Forces Driven by High-quality Supply of Agricultural Data Elements in Shanxi Province, China” 4784 Xinghua WANG1, IJMEI Volume 11 Issue 10 October 2025 system towards digitalization, intellectualization, servitization, and greening. The final outcome is the formation of NQPF characterized by data-driven dynamics. This framework clearly delineates the complete transmission chain from data supply to productive forces transition, providing clear theoretical guidance for subsequent pathway design. 4.2 Pathway I: Strengthening Top-Level Design and Institutional Supply to Build a New Pattern of Holistic Collaborative Governance Within the theoretical framework, this pathway primarily relies on the core mechanism of the innovation ecosystem catalytic layer. It aims to address critical bottlenecks in the agricultural data domain—such as data silos, inconsistent standards, ambiguous ownership, and security concerns—through robust top-level design and systematic institutional supply. This approach clears obstacles for the free flow and value realization of data factors, thereby establishing a holistic collaborative governance framework capable of effectively supporting the incubation and development of new quality productive forces. The specific operational mechanism is as follows: First, by formulating unified provincial-level agricultural data development strategies and medium-to-long-term plans, it clarifies the rights, responsibilities, and interests of governments at all levels, market entities, and social forces in data collection, integration, sharing, application, and security assurance. This establishes a guidance mechanism with aligned objectives and coordinated actions, preventing redundant investments and resource waste from the outset, while ensuring strategic orientation and overall efficiency in the allocation of data factors. Second, efforts are focused on constructing and refining a comprehensive institutional rule system covering the entire data lifecycle. Key priorities include accelerating the introduction of guidelines for agricultural data classification and grading, methods for rights confirmation and authorization, rules for circulation and trading, standards for security and privacy protection, and performance evaluation incentive policies in Shanxi Province. These institutional arrangements function like laying tracks and traffic rules for the data factor market: they delineate data property rights, standardize procedures for data sharing and openness, ensure secure and trustworthy data transactions, and stimulate stakeholder enthusiasm for data provision and application through equitable benefit distribution mechanisms. A mandatory public data sharing system, operating outside a "negative list," will be established to promote the orderly opening of agriculture-related public data—such as meteorological, soil, hydrological, and market data—to society. Additionally, an agricultural data asset certification system based on blockchain technology will be explored to clearly define the rights of data contributors, allowing them to trade, pledge, or convert data into equity within regulatory frameworks, thereby capitalizing data assets. Finally, a cross-departmental, cross-level, and inter-regional collaborative governance mechanism for agricultural data will be established and strengthened. This includes setting up a provincial-level Agricultural Big Data Coordination Leading Group and an operational Agricultural Data Management Center to coordinate the integration, aggregation, standardization, and platform-based servicing of data resources. Through regular consultations, information briefings, joint law enforcement, and other means, communication and collaboration among departments such as agriculture and rural affairs, development and reform, industry and information technology, science and technology, and finance will be enhanced. This fosters policy synergy to collectively address challenges and bottlenecks in data sharing and application. Essentially, this series of combined measures in top-level design and institutional supply creates a stable, transparent, and predictable institutional environment for the high-quality supply of agricultural data factors. By significantly reducing transaction costs and uncertainties, it effectively activates the innovation ecosystem catalytic layer, promotes trust and cooperation among diverse stakeholders, accelerates knowledge spillover and collaborative innovation, and ultimately provides solid and reliable institutional safeguards and endogenous momentum for cultivating new quality productive forces. 4.3 Pathway Ⅱ: Deepening Scenario Empowerment and Business Convergence to Forge a Digital-Driven Industrial Ecosystem This pathway closely aligns with the core mechanism of the value network reconstruction layer. It focuses on deeply integrating high-quality agricultural data elements as production factors into specific industrial practices. By precisely targeting typical application scenarios and promoting cross-sector convergence, this approach fully unleashes the multiplier effect of data as a new type of production factor, thereby fostering and expanding a modern agricultural industrial ecosystem that is driven by data and embodies the characteristics of new quality productive forces. The key mechanisms are as follows: On one hand, it is oriented toward addressing the pain points, challenges, and bottlenecks in the development of Shanxi’s distinctive and advantageous agriculture. A series of smart agricultural application scenarios with demonstrative and leading effects are systematically planned and implemented. In the Yanmen Pass agro-pastoral ecotone, emphasis is placed on deploying dynamic analysis of grass-livestock balance and precision feeding management systems based on remote sensing monitoring, drone field patrols, and sensor networks, achieving optimal matching between forage resources and breeding scale. In the southern Shanxi fruit advantage zone, efforts are made to promote digital orchard management scenarios that integrate IoT environmental monitoring, smart irrigation with integrated water-fertilizer systems, AI-based pest and disease image recognition and early warning, and non-destructive fruit quality testing technologies, “The Path and Countermeasures for Cultivating New Quality Productive Forces Driven by High-quality Supply of Agricultural Data Elements in Shanxi Province, China” 4785 Xinghua WANG1, IJMEI Volume 11 Issue 10 October 2025 enabling precision and green production processes. In the northern Shanxia minor grain production area, end-to-end traceability scenarios from farm to table to table are established, utilizing blockchain technology to record critical information such as origin environment, planting and processing, storage, and logistics, thereby enhancing product credibility and added value. These deeply applied scenarios transform abstract data into tangible tools for productivity improvement, directly acting on the core element empowerment layer and revolutionizing the precision allocation and efficiency of traditional production factors. On the other hand, a more profound impact lies in promoting the deep integration of industrial formats and the systematic reconstruction of value networks based on data connectivity. The high-quality supply of agricultural data elements breaks down information barriers between agriculture and secondary/tertiary industries, serving as both an adhesive and catalyst for industrial coupling. This enables agricultural producers to respond more accurately to changes in consumer market demand, driving the development of contract farming and customized agriculture. It allows financial service institutions to provide targeted credit, insurance, and other inclusive financial services to new agricultural business entities based on authentic production and operational data. It enables logistics enterprises to optimize warehouse layouts and distribution routes using big data on production and sales. Furthermore, it facilitates the innovative integration of industries such as rural tourism and cultural creativity with resources like specialty agricultural products and pastoral landscapes, giving rise to new formats such as experiential consumption and cloud-based farms. Such cross-boundary integration continuously extends the agricultural industrial chain, enhances the value chain, and refines the supply chain, ultimately forming a digital-driven industrial ecosystem where data flow guides the flow of technology, capital, talent, and materials, ensuring efficient coordination among various elements and the vibrant emergence of value-creating activities. This represents the concentrated manifestation of new quality productive forces at the industrial level. 4.4 Pathway Ⅲ: Strengthening the Technical Foundation and Infrastructure to Build a New Base for Data Supply Capacity This pathway directly corresponds to the foundational support role of the Core Element Enablement Layer and provides an indispensable material and technical prerequisite for the vitality of both the Innovation Ecosystem Catalyzation Layer and the Value Network Restructuring Layer. It focuses on fundamentally enhancing the capabilities for generating, collecting, transmitting, storing, computing, and securing agricultural data factors. By continuously reinforcing and upgrading the technical systems and hardware facilities that support the entire data workflow, this pathway lays a solid and reliable physical foundation for achieving high-quality supply of agricultural data factors. Its core mechanism of action is manifested at three levels: First, striving to break through the technical bottlenecks in the data collection and perception layer. In response to Shanxi's complex and diverse topography and agricultural production types, an integrated "space-air-ground" agricultural data stereoscopic perception network will be constructed by comprehensively utilizing various means such as high-throughput satellite remote sensing, low-altitude UAV aerial photography, field IoT sensor arrays, and mobile intelligent terminals. Emphasis will be placed on developing and promoting low-cost, highly reliable, long-endurance intelligent sensing equipment suitable for specific environments in Shanxi, such as hilly and mountainous areas, facility greenhouses, and large-scale breeding farms. This aims to solve the "last mile" problem of data acquisition and achieve real-time, precise, and large-scale collection of key information including crop growth status, soil moisture, pest and disease occurrence, livestock and poultry/aquatic behavior, and environmental parameters, thereby ensuring the comprehensiveness and accuracy of data supply from the source. Second, making every effort to construct an efficient and collaborative data transmission and computing power support system. Efforts will be accelerated to deepen the coverage and improve the service quality of 5G networks and the BeiDou Ground-Based Enhancement System in vast rural areas, while also optimizing rural broadband networks to provide an information highway for the real-time, stable, and low-latency transmission of massive agricultural data. Concurrently, a coordinated layout and intensive construction of cloud computing centers and edge computing nodes for the agricultural sector will be pursued, alongside active exploration of integration into the national "East Data West Computing" project. This will provide sufficient computing power assurance for complex agricultural AI model training, big data analysis, and digital twin construction, ensuring the efficiency and intelligence of data processing and analysis. Finally, systematically building a secure and trustworthy data management and service platform. Leveraging provincial and municipal government cloud resources, a provincially unified and interconnected agricultural big data center with a unified architecture will be established. A unified data standard and specification system will be formulated to clean, integrate, desensitize, and label the aggregated multi-source heterogeneous data, forming a high-quality, reusable data asset pool. Based on this, an agricultural data sharing and exchange platform with open APIs for various users—including government decision-making, production operations, and public services—will be developed, providing convenient data retrieval, access, and application development services. Simultaneously, data security protection capabilities protection capabilities will be strengthened by establishing a security management mechanism that spans the entire data lifecycle. “The Path and Countermeasures for Cultivating New Quality Productive Forces Driven by High-quality Supply of Agricultural Data Elements in Shanxi Province, China” 4786 Xinghua WANG1, IJMEI Volume 11 Issue 10 October 2025 Technologies such as encryption, desensitization, access control, and security auditing will be employed to strictly prevent data leakage, tampering, and misuse, ensuring the security, controllability, and compliance of data factors during circulation and use. Through the systematic strengthening of the aforementioned technical foundation and infrastructure, this pathway essentially ensures, at the physical level, that agricultural data factors can be produced and circulated smoothly with lower cost, higher efficiency, better quality, and stronger security assurance. Thereby, it provides the most fundamental fuel and engine for the effective implementation of the first two pathways and the smooth operation of the entire theoretical framework. 5. STRATEGIES AND RECOMMENDATIONS FOR DRIVING THE CULTIVATION OF NEW QUALITY PRODUCTIVE FORCES IN SHANXI PROVINCE THROUGH HIGH-QUALITY AGRICULTURAL DATA FACTOR SUPPLY 5.1 Improving the Management System for Agricultural Data Property Rights and Classification In the process of advancing high-quality agricultural data factor supply, perfecting the management system for agricultural data property rights and classification/grading is a crucial measure to solidify the institutional foundation. Currently, ambiguous definition of agricultural data property rights and unclear allocation of responsibilities and powers have become core bottlenecks restricting data circulation and value release. There is an urgent need to establish a framework for the agricultural data property rights system based on the Civil Code and the Data Security Law, clarifying the rights subjects and responsibility boundaries at each stage of data production, collection, processing, and use. Particular attention should be paid to refining the distribution mechanisms for ownership, usage rights, and profit rights, so as to protect the legitimate interests of farmers, new types of business entities, and data processors. Simultaneously, drawing on the national data classification and grading protection system and considering the characteristics of Shanxi's agricultural industry, data classification standards covering the entire chain of agricultural production, operation, management, and services should be formulated. Based on data sensitivity, public attributes, and economic value, agricultural data should be categorized into core data, important data, and general data, with differentiated security management strategies implemented. Strict control should be enforced for core data involving national food security and biological genetic resources; authorized use should be promoted for important data such as market supply and demand, meteorology, and soil; and open sharing should be encouraged for general agricultural technical data. By establishing a property rights system with clearly defined rights and responsibilities and a scientific, standardized classification/grading system, the dilemma of "unwillingness to supply and share data" can be effectively resolved, providing institutional guarantees for the compliant circulation and efficient utilization of agricultural data factors, thereby stimulating the endogenous motivation for new quality productive forces. 5.2 Enhancing the Regulatory System for Market-Based Allocation of Agricultural Data Factors Perfecting the regulatory system for the market-based allocation of agricultural data factors is essential for dismantling institutional barriers and invigorating data transaction activities. Currently, the agricultural data factor market faces issues such as a lack of transaction rules, lagging regulation, and insufficient protection of rights and interests, which severely constrain the optimal allocation of data resources. To this end, efforts should be accelerated to formulate and promulgate the "Shanxi Provincial Regulations on the Management of Market-Based Allocation of Agricultural Data Factors," defining legal norms for key links including data confirmation of rights, pricing, transactions, and supervision. The focus should be on constructing a revenue distribution mechanism that evaluates contribution based on market principles and determines remuneration accordingly, and exploring the formation of a government-guided, market-led data pricing model. Concurrently, the regulatory framework for the data transaction market should be improved, specifying the responsibilities of regulatory authorities and establishing monitoring establishing monitoring, early warning, and risk disposal mechanisms covering the entire data transaction process, while strictly cracking down on data monopoly, unfair competition, and abuse. Regarding data security and compliance, it is necessary to strictly implement overarching laws such as the Cybersecurity Law and the Personal Information Protection Law, and formulate detailed implementation rules for cross-border data flow, privacy protection, and security reviews in the agricultural sector. By building a systematic, complete, and efficiently operating regulatory system, the behavior of data market entities can be effectively standardized, transaction costs and compliance risks reduced, and a fair, transparent, trustworthy, and controllable market environment fostered. This will fully unleash the potential value of agricultural data factors and inject strong momentum into cultivating new quality productive forces. 5.3 Promoting the Integration and Orderly Opening of Agricultural Public Data Resources Promoting the integration and orderly opening of agricultural public data resources is a vital pathway to achieving data inclusivity and enhancing government governance efficiency. Various agricultural-related departments at all levels in Shanxi Province have accumulated substantial amounts of high-value public data resources. However, long-standing issues such as data silos, inconsistent standards, and poor sharing persist. The immediate priority is to establish and improve a unified provincial agricultural public data resource system. Leveraging the provincial government data sharing and exchange platform,