Research on Leading Agricultural Enterprises Guiding Farmers' Participation in Pre-Production Quality and Safety Control: Evidence from the Yangtze River Delta Region of China

Research on Leading Agricultural Enterprises Guiding Farmers' Participation in Pre-Production Quality and Safety Control: Evidence from the Yangtze River Delta Region of China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Research on Leading Agricultural Enterprises Guiding Farmers' Participation in Pre-Production Quality and Safety Control: Evidence from the Yangtze River Delta Region of China Chenying Liu, Wen Li, Yulan You, Qizhi Yang, Mingjuan Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6536489/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 14 You are reading this latest preprint version Abstract The leadership of agricultural enterprises in guiding farmers to participate in pre-production quality and safety control not only helps promote high-quality agricultural development and drives the industrialization process of agriculture, but also provides important support for achieving the goal of building a strong agricultural nation. This paper focuses on agricultural leading enterprises and farmers in the Yangtze River Delta region of China. The study does not limit itself to exploring the independent influence of enterprise-led actions in guiding farmers' participation in pre-production quality and safety control, but rather investigates how multiple factors work together to lead farmers' participation under various interacting elements. The research employs a grounded theory approach to conduct a multi-case study, following the general logic of " Motivations-Behaviors-Outcomes." Relevant data from case companies were extracted, analyzed, and coded to construct a theoretical interpretation, revealing the intrinsic mechanisms of agricultural leading enterprises in pre-production quality and safety control and identifying key influencing factors. Additionally, using fuzzy-set qualitative comparative analysis (fsQCA), the study explores how five enterprise control behaviors—village-enterprise cooperation, integration of primary, secondary, and tertiary industries, agricultural mechanization, agricultural digitalization, and agricultural technology promotion—collaborate to guide farmers’ involvement in pre-production quality and safety control from a configurational perspective. The results indicate that agricultural leading enterprises guide farmers’ participation in pre-production quality and safety control through organizational linkage mechanisms and new quality productive forces elements linkage mechanism, and based on this, six configurational paths are summarized, leading to the identification of three constructs: Industry Integration-driven, Digital Intelligence-driven, and Land Trusteeship-driven. Business and commerce/Business and management Social science/Business and management Social science/Economics Social science/Environmental studies Agricultural leading enterprises farmers agricultural product quality grounded theory qualitative comparative analysis Figures Figure 1 Figure 2 Figure 3 1. Introduction China has proposed accelerating the construction of a new development pattern and achieving the strategic goal of modernizing with high-quality development, with a particular emphasis on the priority development of agriculture and rural areas. High-quality agricultural development is not only the core path to promoting rural revitalization and building a strong agricultural nation but also an inevitable choice for realizing the goal of Chinese-style modernization. In this process, China has introduced the concept of “New quality productivity”, aiming to guide economic transformation and upgrading, promote the cultivation of strategic emerging industries and future industries, and foster the formation of new forms of productivity with new attributes, functions, and characteristics [ 1 – 3 ]. New quality productivity is essentially a form of productivity driven by innovation, distinct from traditional economic growth models. It emphasizes technological progress, optimized resource allocation, and highly efficient production methods. Specifically, New quality productivity is jointly fostered by technological breakthroughs, innovative allocation of production factors, and deep transformation and upgrading of industrial chains. The core feature of this concept is the optimized combination of labor, labor materials, and labor objects, which drives productivity improvement. A significant increase in total factor productivity becomes a core indicator of New quality productivity development, and its key driving force is innovation, fundamentally reflecting advanced productivity. In the context of Chinese-style modernization, agricultural productivity upgrading is not only the result of technological innovation but also a systematic improvement supported by multiple dimensions, including technology, factors, systems, and the environment [ 4 – 6 ]. New quality productivity emphasizes transforming agricultural productivity through technological innovation, especially in terms of increasing agricultural total factor productivity and achieving low-carbon, green, and sustainable development, which is of great significance. This process not only focuses on improving production efficiency but also aims to meet the growing demand for high-quality agricultural products, thereby enhancing the overall quality of life for the people [ 7 – 9 ]. In the context of agricultural industrialization, agricultural industrial organization models, based on industrial organization theory, play a vital role as institutional carriers in agricultural development, serving as bridges, links, and carriers in the agricultural industry. Therefore, promoting close connections between farmers and other entities in the industrial chain, establishing stable industrial organization models, may become an effective path for enterprise-led farmer participation in pre-production quality and safety control. Existing research suggests that the primary organizational model is "agricultural leading enterprises + cooperatives + farmers." This organizational model not only helps implement various quality control measures effectively in agricultural production but also enhances the production capacity and quality safety control efficiency of agricultural leading enterprises. Agricultural leading enterprises, with their modern production capabilities, refined management mechanisms, and extensive market channels, play a leading role in quality and safety control in the agricultural product supply chain. Since 2018, multiple departments, such as the Ministry of Commerce and the Ministry of Agriculture and Rural Affairs, have jointly promoted the "Supply Chain Innovation and Application Pilot" project, aiming to promote the deep integration of farmers and the agricultural industry chain, thereby forming a full industrial chain cooperation model centered on agricultural leading enterprises and benefiting farmers [ 10 – 13 ]. In this model, cooperatives serve as a bridge between enterprises and farmers, helping agricultural leading enterprises influence farmers' production behaviors, promoting green planting, and achieving carbon reduction in agriculture. Cooperatives also facilitate the organic connection of smallholder farmers with modern agriculture through organizational operations, standardized production, green production, financial credit, and the extension of the industrial chain. With the improvement of China's economic development level and agricultural labor productivity, as well as the diversification of agricultural industrial structure and rural employment structure, urbanization's absorption of rural population, and other factors, traditional farmers are being impacted from various angles and levels, leading to a diversity of economic perspectives and planting scales. This has resulted in a diversified classification of farmers, including individual farmers, contract farmers, mixed farmers, and large-scale farmers [ 14 – 18 ]. Previous research has recognized the importance of strengthening quality and safety control during the agricultural production phase. Liu Hongchao (2021) and others proposed using blockchain technology to supervise key data, such as production conditions, agricultural input usage, and processing materials, to achieve effective pre-production quality safety control of agricultural products [ 19 ]. Pan Siqi and Luo Feng (2021) suggested building an "Internet+" integrated monitoring platform to improve the current instability in agricultural product production quality [ 20 ]. Li et al. (2022) researched the impact of digital promotion services via smartphones on farmers' adoption of sustainable agricultural technologies, finding that farmers using these services could improve the effectiveness of quality and safety control actions, such as precision fertilization, technical learning, and soil testing [ 21 ]. Lu Quanzhi and Zhang Yifeng (2022), while exploring how cooperatives promote green production among farmers, indicated that cooperatives significantly boost farmers' adoption of green production behaviors, with an overall increase of 25.57% [ 22 ]. Chen Weiqiang and Ma Pengchao (2023) argued that cooperative support significantly enhances farmers' cognitive and behavioral abilities, serving as an important external factor in agricultural product quality and safety control [ 23 ]. Cai Rong et al. (2019) used the example of reduced fertilizer and pesticide use to illustrate the positive role cooperatives play in improving agricultural product quality and safety [ 24 ]. Zhang Fengyi et al. (2022) found that cooperatives could improve farmers' quality control behaviors, with cooperatives owning independent agricultural product brands placing more emphasis on product quality control [ 25 ]. Li Dan et al. (2021) suggested that brand premiums have a positive effect on pre-production quality safety control, particularly when brand-specific assets constrain farmers' production behaviors, maximizing the impact of brand premiums on enhancing product quality and safety [ 26 ]. Under the background of supply-side structural reform in agriculture, agricultural mechanization has not only promoted large-scale production but also facilitated the integration of primary, secondary, and tertiary industries, thereby contributing to improved agricultural product quality [ 27 ]. Liu Lingxiu (2024) proposed that chemical weeding has a negative impact on product quality, and the introduction of mechanized physical weeding robots provides technical support for the production of high-quality agricultural products [ 28 ]. Yin et al. (2022) developed a high-end equipment manufacturing system framework aimed at satisfying the green quality requirements of agricultural products, providing a technological path for high-quality agricultural development [ 29 ]. Yang and Li (2022) suggested that agricultural machinery services should be tailored to local conditions to better meet farmers' needs for producing high-quality agricultural products [ 30 ]. Yu Lianghong et al. (2022) found through heterogeneity analysis that farmers involved in managed economic crops achieve the highest ecological and economic benefits, with service organizations in land trusteeship using environmentally friendly agricultural technologies such as green pest control, integrated water and fertilizer management, and soil testing-based fertilization, significantly reducing pesticide and fertilizer application intensity and improving agricultural product quality and safety [ 31 ]. Based on the existing literature, current research primarily focuses on specific methods and technological pathways for agricultural product quality and safety control. However, there is relatively limited attention to the factors influencing farmers' proactive safety production behaviors under the guidance of leading enterprises in a multi-actor context. Therefore, this study aims to explore which agricultural product quality control measures are more effectively accepted and adopted by farmers in the context of agricultural leading enterprises taking the lead. At present, research on pre-production quality and safety control of agricultural products has covered various aspects, including cooperative participation, industrial integration, mechanization levels, and digital technologies. However, most studies tend to focus on the independent effects of single factors on quality control. As research methods continue to improve, the interactive effects among multiple factors and their complex impacts on quality control effectiveness have gradually emerged as a new research direction. Based on this, this paper uses data from agricultural leading enterprises and farmers in the Yangtze River Delta region of China, applying configurational theory to analyze the multidimensional combination of measures that guide farmer behavior and their multiple interactive effects on pre-production quality control of agricultural products. By exploring the mechanisms of multi-factor dynamic combinations in agricultural product quality and safety, this paper aims to provide a theoretical basis and empirical support for optimizing quality control strategies and practical pathways. 2. Identification of Mechanisms and Influencing Factors 2.1. Mechanisms Analysis This study selects four leading agricultural enterprises in the Yangtze River Delta region of China, which guide farmers in producing high-quality agricultural products, as research samples (see Table 1 ). A multiple-case study is conducted using the grounded theory method. Following the analytical logic of "motivation–behavior–outcome," interview data from these enterprises are systematically extracted, thoroughly analyzed, and coded at multiple levels. Ultimately, a theoretical interpretation is constructed to reveal the internal mechanism of agricultural leading enterprises in pre-production raw material quality control [ 51 ]. Table 1 Basic Information of the Four Case Enterprises Case Enterprises Company A Company B Company C Company D Core Business Mulberry Wine Pueraria (Kudzu) Agricultural and Sideline Products Rice Table Grapes and Wine Product Advantages Deep-processed High-end Health Agricultural Products High Nutritional and Health Value High Nutritional Value and Excellent Taste Wide Variety, Excellent Quality, and Superior Ecological Environment Customer Network Involves hundreds of distributors, group purchases, and online stores Group Purchases and Online Sales Acquired by COFCO (China National Cereals, Oils and Foodstuffs Corporation) Offline Stores, Online Sales, and Corporate Procurement Sales Scale 150 million RMB 300 million RMB 70 million RMB 300 million RMB Involved Farmers Approximately 500 households 200 Pluriactive Farmers Over 20,000 mu under contract 2,000 mu of grape fields, with a total of 1,927 growers This study employs open coding to systematically analyze the interview data of the four case enterprises, thoroughly reading and accurately understanding the text to identify the main mechanisms and key events related to the motivations, behaviors, and outcomes of agricultural leading enterprises guiding farmers in pre-production quality and safety control. During the coding process, the latest theoretical research advancements are incorporated to conceptualize and summarize the relevant content from the case materials. The motivation section focuses on the roles, functions, and effects of farmers in pre-production quality and safety control; the behavior section examines the response measures under different mechanisms; and the outcome section analyzes the changes and impacts on both farmers and pilot enterprises after implementing action strategies under different mechanisms. This process then distills secondary coding entries. Based on this, axial coding is applied to integrate and abstract the open coding concepts, further summarizing them into higher-level categories, ultimately forming the primary coding. Based on the aforementioned logical analysis and research design, a grounded theory analysis is conducted to explore the pathways and mechanisms through which leading agricultural enterprises engaged in high-quality agricultural product production guide farmers to participate in pre-production quality and safety control. The primary focus is to address the issue of linkage, specifically by examining the linkage establishment process and performing a processual analysis. This aims to elucidate the linkage mechanisms and pathways through which agricultural leading enterprises orchestrate farmer involvement in pre-production quality and safety control. Mechanism 1: Organizational Connection Mechanism Within the organizational linkage mechanism, labor force elements constitute the foundation for leading agricultural enterprises to implement pre-production quality and safety control. However, a primary challenge currently faced is the heterogeneity of farmer types, encompassing contract farmers, part-time farmers, large-scale farmers, and individual smallholders, each exhibiting significantly divergent demands. The inability of leading agricultural enterprises to effectively discern the specific roles and needs of these diverse farmer types in pre-production quality and safety control leads to a lack of targeted quality control measures, consequently resulting in agricultural product quality and safety issues. In response, case enterprises have adopted a series of countermeasures. Agricultural cooperatives play a pivotal intermediary role between leading agricultural enterprises and farmers. Utilizing village-enterprise collaboration as a bridge, leading agricultural enterprises, through contracting with cooperatives, enhance the awareness and behaviors of various farmer types regarding agricultural product quality and safety control. Cooperatives disseminate the economic and social value of quality control to farmers through policy dissemination and organized training, thereby reinforcing farmers' behavioral cognition of quality control. Simultaneously, a mechanism combining rewards and penalties is employed to ensure the equivalent conversion of agricultural product value, gradually shifting agricultural product prices from a pooling equilibrium to a separating equilibrium. This breaks the economic cycle of 'bad money driving out good,' thereby enhancing farmers' willingness to implement quality control. Building upon the cultivation and enhancement of farmers' quality control behavioral capabilities, leading agricultural enterprises provide support tools such as production factors, technical training, and low-interest loans. By promoting the establishment of industry-university-research groups and conducting targeted technical training, farmers' capacity to implement quality control is augmented. Leading agricultural enterprises, through promoting land trusteeship or transfer, improve the efficiency of idle resource element utilization and further stimulate farmers' enthusiasm for producing high-quality agricultural products. For part-time farmers facing household labor shortages or seasonal employment, idle land is entrusted or transferred to cooperatives, enterprises, or small farmers, forming a more efficient intensive management model. This production model not only facilitates specialized management and enhances production management efficiency but also integrates agricultural materials, technology, and human resources required for high-quality agricultural product production, enabling dynamic management of breeding, production management, and post-harvest storage processes. Concurrently, enterprises leverage big data, cloud computing, and Internet of Things technologies to predict extreme climate and natural disaster changes, enabling proactive scientific production decisions. Government subsidies for large-scale production of high-quality agricultural products further incentivize the contiguous production model of land trusteeship or transfer, allowing farmers to benefit from policy dividends and promoting the effective implementation of pro-farmer policies. Leading agricultural enterprises, through the deep integration of primary, secondary, and tertiary industries, enhance farmers' awareness of pre-production agricultural product quality and safety control. The extension of the industrial chain not only lengthens the agricultural product value chain but also propels farmers towards high-quality production transformation. In forward extension, the order contract model directly links farmers' production behaviors with market demands, unifying quality standards and brand requirements, thereby standardizing farmers' production behaviors. By enhancing industrial chain resilience and developing new products and brands, leading enterprises enable farmers to more directly perceive the premium benefits of high-quality agricultural products, thereby further enhancing their quality control awareness. The grounded theory analysis results and pathways of leading agricultural enterprises guiding farmers to participate in pre-production quality and safety control based on the organizational linkage mechanism are presented in Table 2 and Fig. 1 , respectively. Table 2 Grounded Theory Analysis Results of Leading Agricultural Enterprises Guiding Farmers' Participation in Pre-Production Quality and Safety Control Based on the Organizational Linkage Mechanism. (Selected Representative Evidence) Logical Foundation Level 1 Coding Level 2 Coding Representative Evidence Motivations Labor Factors Contract Farmers A: The company enters into contracts with cooperatives, stipulating annual quality standards and order volumes. B: The company establishes contracts with individual farmers for the procurement of kudzu root. C: The company engages in contractual land leases with farmers, employing them for rice cultivation. D: The company enters into contracts with farmers for the acquisition of fresh fruit. Pluriactive Farmers A: Farmers establish an employment relationship with the Xiajin Yellow River Old Course Ancient Mulberry Tree Cluster as employees, participating in the maintenance and harvesting of the ancient mulberry trees. B: Farmers are employed as temporary workers at the Maobao Kudzu Root Garden, engaging in production activities such as kudzu root harvesting and weeding. C: Farmers participate in rice cultivation as laborers. Small-scale Farmers A: Farmers sell their cultivated mulberries to the company. B: Local farmers harvest and sell wild kudzu root to the company. D: Farmers sell their self-cultivated grapes to the company. Large-scale Farmers A: Large-scale farmers cultivate tens of acres of mulberry trees. B: The company conducts on-site procurement of farmers' homemade kudzu root powder. D: Farmers contract large tracts of land for grape cultivation. Behaviors Integration of Primary, Secondary, and Tertiary Industries Industrial Chain Resilience A: The company develops the 'Purple Wine Town Project', aiming to radiate throughout Maoshan. A: The company registers the 'Worry-Free Mulberry' brand and develops new mulberry leaf tea products. B: The company actively develops specialty products such as kudzu root tea, kudzu root biscuits, kudzu root enzyme, and kudzu root farm cuisine. D: The company actively develops its wine business. Industrial Chain Extension A: The company hosts the 'Kunming May Day Most Beautiful Mulberry Orchard' event, featuring mulberry fruit picking and tourism. B: The company organically integrates the kudzu root industry with agricultural sightseeing tourism, establishing projects such as the Maobao Kudzu Garden, Kudzu Root Culture Museum, and Kudzu Root Demonstration Science Park. C: The company establishes industry-university-research bases and conducts various research activities with universities. D: The company develops summer vacation extension bases and establishes agritainment campsites. Village-Enterprise Cooperation Model Cooperatives A: The company directly interfaces with cooperatives, establishing guaranteed purchase agreements. B: The company establishes its own cooperative. C: The company establishes its own cooperative. D: The company establishes the 'Dingzhuang Grape Cooperative Alliance'. Land Trusteeship/Transfer A: The company leases tens of acres of land for the research and development of new varieties, technologies, and models. B: The company leases 250 mu of land for the demonstration and promotion of standardized kudzu root cultivation. C: The company manages land for the centralized cultivation of high-quality rice. D: The company manages land entrusted by farmers and re-employs those farmers for the standardized cultivation of grapes. Outcomes Organizational Linkage Mechanism Enhancement of Land Factor Value A: A 5,000-acre raw material base, driving the 'one village, one product' initiative, has become one of the first rural characteristic industry hundred-million-yuan villages. C: The signing of production and sales agreements has increased the value of nearly 20,000 acres of managed land. D: The company's influence has led to the appreciation of land value across 2,000 acres. Enhancement of Labor Factor Value A: The company recruits farmers for employment. B: Farmers participate in kudzu root harvesting, contributing to a household income increase of twenty to thirty thousand yuan. C: Farmers are responsible for field management. D: The company encourages farmers to engage in grape cultivation. Enhancement of Agricultural Product Quality A: The company increased the purchase price of mulberries. B: The company enhanced farmers' awareness of green and high-quality products, incentivizing them to harvest wild and natural kudzu root. C: "The 'Run Guo Jiu Du' rice was rated as a four-star 'Very Delicious Rice' on China's 'Good Rice List'. D: "The 'Dingzhuang Grapes' were designated as a geographical indication agricultural product. Mechanism 2: New Quality Productive Forces Elements Linkage Mechanism The current proposition of new quality productive forces elements highlights that producing high-quality agricultural products is pivotal, with advanced productivity being the essence. This entails focusing on new types of laborers, labor materials, and labor objects, along with their optimized combinations, and taking the substantial enhancement of total factor productivity as the core marker. Consequently, standardized and green planting have become new driving forces for leading agricultural enterprises to guide farmers in promoting pre-production agricultural product quality and safety control. To realize standardized and green planting, leading agricultural enterprises cultivate and develop new types of agricultural laborers, tools, and objects. Through agricultural technology extension and industry-university-research cooperation, leading agricultural enterprises enhance farmers' quality control capabilities. Enterprises invite agricultural experts to provide full-cycle production technical guidance to farmers in the fields and collaborate with research institutions to develop patented technologies and promote standardized planting models. New labor objects, centered on data elements, enable leading agricultural enterprises to establish digital platforms for digital and information-based monitoring of field management. By leveraging big data, cloud computing, and Internet of Things technologies, enterprises construct intelligent farmland management systems to achieve real-time monitoring of crop growth environments and optimize planting strategies through intelligent decision-making systems. In terms of financial credit, enterprises launch agricultural credit platforms to provide farmers with financial support such as agricultural material credit sales, reducing farmers' production input pressure and enhancing their enthusiasm for participating in high-quality planting. For quality traceability, enterprises establish a full-process traceability system from production to market, including product QR code traceability and government food safety electronic traceability systems, ensuring that the sources of agricultural products are traceable, destinations are trackable, and responsibilities are accountable, thereby enhancing consumer trust in product quality. New types of labor tools in agricultural mechanization are crucial for improving agricultural product quality. Addressing the issues of insufficient farm machinery and low mechanization levels among farmers, leading agricultural enterprises reduce farmers' production costs and improve mechanized operation efficiency through agricultural machinery outsourcing leasing and maintenance scheduling mechanisms. Enterprises or cooperatives provide farm machinery leasing services and conduct pilot demonstrations in areas suitable for farm machinery promotion to enhance farmers' awareness and application capabilities of mechanized planting. Furthermore, for complex terrains such as hills and mountains, enterprises establish farm machinery adaptation and scheduling systems to ensure that farmers can access suitable agricultural machinery and maintenance services, thereby improving the precision and stability of agricultural production. Leading agricultural enterprises, relying on the linkage mechanism of new quality productive forces elements, integrate key elements such as modern technology and industrial chain collaboration to promote the construction of innovative production models and facilitate deep synergy between enterprises and various types of farmers along the industrial chain, thereby improving the quality and yield of agricultural products. The grounded theory analysis results and pathways of leading agricultural enterprises guiding farmers in pre-production agricultural product quality and safety control based on the linkage mechanism of new quality productive forces elements are presented in Table 3 and Fig. 2 , respectively. Table 3 Grounded Theory Analysis Results of Leading Agricultural Enterprises Guiding Farmers' Participation in Pre-Production Quality and Safety Control Based on the Organizational Linkage Mechanism. (Selected Representative Evidence) Logical Foundation Level 1 Coding Level 2 Coding Representative Evidence Motivations Optimization of New Quality Productive Forces Elements Standardized Cultivation A: The company implements standardized maintenance protocols and adopts uniform quality standards for mulberry procurement. C: The company employs uniform varieties, fertilizers, and field management practices for cultivation. D: Through standardized cultivation, the company modifies farmers' traditional planting habits. Green Cultivation A: The company provides farmers with green planting guidance and encourages the use of organic fertilizers. B: The company encourages farmers to cultivate wild kudzu root and conducts monitoring of soil and water quality. C: The company prohibits the burning of straw and promotes straw composting. D: The company uniformly implements green management practices and organic cultivation. Behaviors Agricultural Mechanization Agricultural Machinery Outsourcing Leasing A: Due to the high cost of manual mulberry harvesting, the company needs to promote mechanized harvesting and sorting. C: The company provides agricultural machinery and implements. D: The cooperative provides agricultural machinery and implements. D: The company installs drip irrigation facilities. Agricultural Machinery Maintenance and Scheduling A: The cultivation site is hilly, necessitating the deployment of agricultural machinery suitable for hilly terrain. C: The company schedules agricultural machinery and provides maintenance services to farmers. D: The cooperative alliance provides agricultural machinery maintenance services. Agricultural Digitalization Digital Agriculture Platform A: The company utilizes integrated dashboards for order and production information. C: The company has established a 'Smart Farmland Patrol' digital management system for field operations. Financial Credit Platform A: The company has developed a 'one card per household' platform, offering farmers access to agricultural input credit sales services. Quality Traceability Platform A: Each bottle of wine is affixed with an agricultural product traceability code. B: The company regularly submits data to the Jiangsu Province Agricultural Product Traceability Platform and the Zhenjiang City Food Safety Electronic Traceability System. C: The company has developed a field monitoring and traceability function. Agricultural Standardization Agricultural Technology Extension A: The company engages experts to provide technical guidance to farmers and supplies them with agricultural materials. B: The company collaborates with universities on patented technologies. D: The company constructs grape greenhouses and collectively contracts them out. Outcomes New Quality Productive Forces Elements Linkage Mechanism Increase Raw Material Output A: "Following collaboration, the yield of a single mulberry tree exceeded 100 kilograms; the cultivation area expanded from 1,000 acres to over 3,000 acres. C: The yield per acre increased to 1,200-1,300 kilograms, representing a 9% improvement in per-acre productivity. D: Production increased to 420,000 tons, with monthly exports of 4–5 tons overseas. Improve Raw Material Quality A: Quality is reflected in the procurement price, which has steadily increased from 1.5 yuan to over 2 yuan. B: The company rigorously ensures the green and organic nature of raw materials. C: Water resource utilization has increased by 30%, fertilizer utilization by 15%, pesticide usage has decreased by over 20%, and per-acre benefits have risen by 20%. D:'Dingzhuang Grapes' have been designated as a national geographical indication agricultural product and have received multiple awards for 'Green and High-Quality Agricultural Products'. This study, taking four representative leading agricultural enterprises as examples, analyzes the cyclical mechanisms through which enterprises guide farmers to participate in pre-production quality and safety control. By exploring the inherent logic of 'motivations-behaviors-outcomes,' it is found that the linkage mechanisms involve two dimensions: organizational and new quality productive forces elements. These are multi-dimensional linkage mechanisms that collaboratively ensure and facilitate farmers' participation in the quality and safety control of the industrial chain. The organizational linkage mechanism serves as a necessary foundation for enterprises to guide farmers in pre-production quality and safety control. It addresses the effective integration of farmers' production factors, such as land and labor, into the agricultural industrial chain by organizing contract and large-scale farmers through cooperative organizational management and absorbing individual smallholders and part-time farmers through land transfer/trusteeship. This enables various types of farmers to become the first link in the agricultural industrial chain and a necessary component of vertical collaboration. The linkage mechanism of new quality productive forces elements acts as a catalyst for enterprises to guide farmers in pre-production quality and safety control. Starting from green and standardized planting, leading agricultural enterprises optimize the combination of technological innovation, labor materials, and labor objects, enabling farmers to participate in agricultural production activities conveniently and efficiently. This drives farmers to achieve self-accumulation cycles, innovation, and transformation, ensuring high-quality and high-yield outcomes. In the quality and safety control of the entire agricultural industrial chain, leading agricultural enterprises promote farmers' active participation in pre-production quality and safety control through the synergistic effect of organizational linkage mechanisms and new quality productive forces elements linkage mechanisms, thereby improving the quality and yield of agricultural products. This mechanism provides an effective path for deep cooperation between leading agricultural enterprises and farmers, promotes the modernization and high-quality development of agricultural production, and supports the innovation and sustainable development of the agricultural industrial chain. The mechanisms through which leading agricultural enterprises guide farmers in pre-production quality and safety control are illustrated in Fig. 3 . 2.2. Identification of Influencing Factors Through a grounded theory analysis based on literature review and field research, this study reveals that pre-production quality and safety control in agriculture is a multi-path, complex behavior of deep collaboration between leading agricultural enterprises and farmers. The integration of three industries, village-enterprise cooperation, agricultural mechanization, agricultural digitalization, and agricultural standardization have, to varying degrees, promoted farmers' participation in pre-production quality and safety control. However, the complexity of this combined pathway poses challenges to traditional regression analysis methods. Therefore, it is necessary to select key behavioral elements based on the actual needs of leading agricultural enterprises and farmers, and to explore the configurational structures under multiple behavioral interactions, in order to accurately identify the core and peripheral factors influencing farmers' participation in pre-production quality and safety control. In light of this, this paper selects five key elements—the integration of three industries, village-enterprise cooperation, agricultural mechanization, agricultural digitalization, and agricultural technology extension—as antecedent conditions for guiding farmers' deep participation in pre-production quality and safety control. The specifics are shown in Table 4 . Table 4 Names and Specific Details of Relevant Variables Antecedent Conditions Specific Contents Village-Enterprise Cooperation (EC) Recognition of Cooperative Role Integration of Three Industries (I) Willingness to Extend Industrial Chain Agricultural Mechanization (M) Acceptance of Machinery Leasing and Maintenance Scheduling Agricultural Digitalization (D) Acceptance of Digital Information Platform Agricultural Technology Extension (S) Agricultural Technology Extension Land Circulation/Trusteeship (LC) Willingness of Land Circulation/Trusteeship 3. Data and methods 3.1. Fuzzy Set Qualitative Comparative Analysis Method Fuzzy-set Qualitative Comparative Analysis (fsQCA) is a research method that combines qualitative and quantitative approaches. It builds upon the theory and methods of Qualitative Comparative Analysis (QCA), integrating Boolean algebra and set theory to provide a novel research perspective for addressing complex causal relationships. By leveraging the advantages of both quantitative and qualitative analysis, fsQCA analyzes and synthesizes concurrent causal relationships among different sets through the comparison of a certain number of cases. This means that various combinations of variables may influence multiple cases to produce the same phenomenon. From a holistic perspective, fsQCA explores the process of complex social problems arising from multiple concurrent causes [ 52 , 53 ]. Compared to crisp-set Qualitative Comparative Analysis (csQCA) and multi-value Qualitative Comparative Analysis (mvQCA), fsQCA better prevents information loss during data conversion and enhances data precision, thereby more accurately detecting the effects caused by changes in antecedent conditions [ 54 ]. Due to its ability to transform causal relationships into complex causalities characterized by fuzziness, asymmetry, and equivalence, fsQCA can address partial membership issues of sets, precisely capturing the impact of conditional variable changes on outcome variables [ 55 ]. This paper employs the fsQCA method, primarily considering that existing research indicates that exploring the pathways for leading agricultural enterprises to guide farmers in pre-production quality and safety control requires more than just analyzing the independent effects of individual behaviors. It necessitates a holistic approach to investigate the outcomes of multiple complex variables interacting with each other. By transforming fuzzy sets into truth tables, fsQCA retains the advantages of truth table analysis in processing qualitative data, limited diversity, and simplifying configurations, thereby endowing the research with dual attributes of qualitative and quantitative analysis [ 56 ]. Furthermore, this paper utilizes fsQCA 3.0 software to set qualitative anchors and employs program operations to finely calibrate the variable membership and outcome membership of cases within the sets. Necessity analysis of individual conditional variables is conducted, and truth tables are constructed to explore the impact of conditional variable combinations on outcome variables. Finally, the conditional configurations are analyzed to examine the sufficiency of different conditional variable configurations on the outcome variables [ 57 ]. 3.2. Data Source Given that the fsQCA method's sample size requirements differ from traditional quantitative analysis methods, this study selected 40 farmers from the Yangtze River Delta region of China as the research sample. According to the research needs, the sample selection criteria included: farmers must be within the industrial radiation range of enterprise A and cover four types: contract farmers, part-time farmers, individual smallholders, and large-scale farmers. The design of the questionnaire was closely aligned with behaviors related to organizational linkage mechanisms and new quality productive forces elements linkage mechanisms. A total of 40 questionnaires were distributed, and 33 valid questionnaires were returned, meeting the standards for medium-sized sample research. The basic characteristics of the sample are detailed in Table 5 . Table 5 Sample distribution. Characteristic Variables Type Sample Size Questionnaire Validity Rate Farmer Type Contract Farmers 18 45% Pluriactive Farmers 3 7.5% Small-scale Farmers 8 20% Large-scale Farmers 11 27.5% Planting Income Approximately 30,000–40,000 RMB 4 10% Approximately 60,000–70,000 RMB 9 22.5% Approximately 100,000 RMB 14 35% Approximately 200,000 Yuan 9 22.5% More 4 10% 4. Empirical Analysis and Results 4.1. Reliability and Validity Test This study utilizes SPSS 20.0 software to analyze the reliability and validity of the scales. The reliability of the scales is assessed using Cronbach's alpha coefficient and CR value. The closer the alpha and CR values are to 1, the better the reliability. Generally, a value above 0.7 indicates good reliability of the scale. Validity represents the degree to which results approximate the intended targets. The convergent validity of the scales is typically measured using the average variance extracted (AVE) of all variables. An AVE value above 0.5 indicates good convergent validity. The discriminant validity is optimal when the AVE is higher than the correlation coefficients of other variables. The test results are shown in Table 6 . Table 6 Reliability and validity test. Variable Crobach’s α CR AVE EC I M D S LC N EC 0.886 0.891 0.803 0.896 I 0.811 0.921 0.854 0.276 0.924 M 0.870 0.901 0.819 0.325 0.252 0.905 D 0.879 0.895 0.741 0.155 0.202 0.189 0.861 S 0.745 0.949 0.903 0.051 0.375 0.278 0.259 0.950 LC 0.840 0.898 0.815 -0.107 -0.417 0.108 -0.173 -0.306 0.903 N 0.768 0.940 0.887 0.572 0.069 0.181 0.347 0.304 -0.247 0.942 Note: Village-Enterprise Cooperation (EC); Integration of Three Industries (I); Agricultural Mechanization (M); Agricultural Digitalization (D); Agricultural Technology Extension (S); Land Circulation/Trusteeship (LC) 4.2. Data calibration Data calibration is the process of converting variables into sets and calculating membership scores. In fsQCA software, the membership relationships of each instance within the sets and the outcome membership relationships are calibrated. 1 indicates absolute membership, 0 indicates absolute non-membership, and 0.5 is the maximum ambiguity point for assessing whether an instance belongs to a set. Since the variables 'Village-Enterprise Cooperation,' 'Integration of Three Industries,' 'Agricultural Mechanization,' 'Agricultural Digitalization,' 'Agricultural Technology Extension,' and 'Pre-Production Quality and Safety Control Level' in this study were obtained through a four-point Likert scale, the original data must be transformed into values between 0 and 1 before fsQCA analysis. To calibrate the variables in each sample, this paper selects three anchor points: 4, 2.5, and 1. Consequently, the membership scores of each variable in the samples are shown in Table 7 . Table 7 Fuzzy set membership (partial). Sample EC1 I1 M1 D1 S1 LC1 N1 1 0.95 0.73 0.88 0.91 0.88 0.95 0.95 2 0.88 0.73 0.95 0.95 0.95 0.88 0.88 3 0.73 0.73 0.88 0.84 0.73 0.12 0.88 4 0.73 0.27 0.73 0.91 0.73 0.27 0.88 5 0.73 0.27 0.73 0.84 0.73 0.88 0.88 6 0.88 0.88 0.73 0.73 0.95 0.27 0.88 7 0.27 0.73 0.88 0.91 0.95 0.73 0.27 8 0.95 0.73 0.88 0.95 0.95 0.27 0.73 9 0.95 0.27 0.73 0.73 0.88 0.73 0.88 10 0.05 0.27 0.27 0.27 0.73 0.73 0.27 11 0.95 0.73 0.27 0.84 0.27 0.73 0.27 12 0.73 0.73 0.73 0.73 0.95 0.27 0.88 13 0.88 0.27 0.73 0.27 0.73 0.88 0.27 14 0.95 0.88 0.95 0.27 0.95 0.95 0.73 4.3. Single condition necessity analysis For the needs of fsQCA analysis, a necessity analysis must first be performed, where necessity refers to the explanatory power of a single conditional variable on the outcome variable. Before truth table analysis, a consistency threshold of 0.9 must be met for the conditional variable to be considered necessary. If the consistency is 1, this condition is essential, and the subset relationship between the conditional variable and the outcome variable is optimal. The analysis results are shown in Table 8 . Table 8 Results of Necessary Condition Analysis. Influence factors Consistency Coverage EC 0.935353 0.870791 ཞEC 0.283002 0.677489 I 0.817812 0.829056 ཞI 0.443038 0.876565 M 0.887432 0.828270 ཞM 0.337251 0.802150 D 0.917270 0.827150 ཞD 0.299729 0.782763 S 0.976490 0.790919 ཞS 0.215642 0.838313 LC 0.555606 0.731983 ཞLC 0.684901 0.934608 4.4. Results After conducting necessity analysis on individual conditional variables, this paper analyzes the sufficiency of configurations composed of different combinations of conditional variables on the outcome variable. Intermediate solutions are used to determine the number of configurations and the included conditions, and these are combined with parsimonious solutions to distinguish between core conditions and peripheral conditions. A solid circle indicates the presence of a conditional variable, a hollow circle indicates the absence of a conditional variable, a large circle represents a core condition, a small circle represents a peripheral condition, and a blank indicates that the conditional variable can be either present or absent. Standardized analysis is performed using fsQCA 4.0 software, and the configuration analysis results of the combinations of influencing factors for farmers' participation in vertical collaboration in the industrial chain are shown in Table 9 . Table 9. Combined Pathways of Conditional Variables. As shown in Table 9 , the overall consistency of the configurations in this study is 0.912, indicating that the six configurations explain 0.912 of the extent to which leading agricultural enterprises guide farmers to participate in pre-production quality and safety control. The overall coverage rate is 0.941, indicating that the research results ultimately cover 94.1% of the case scenarios. The consistency of all configurations in this paper is higher than the acceptance standard of 0.8. These configurations and the willingness of farmers to participate in vertical collaboration in the industrial chain have a good subset relationship, demonstrating that the antecedent conditions have a good explanatory power for the outcome variable (pre-production quality and safety control level of agricultural products). Based on the above research, this paper has derived a total of six configurations with high levels of pre-production quality and safety control for agricultural products. Configuration N1 (ཞM*D*S*LC) indicates that a low level of agricultural mechanization, a high level of agricultural digitalization, a strong agricultural technology extension effort, and a high willingness for land trusteeship can result in high control over pre-production quality of agricultural products. Configuration N2 (~ I*D*S*LC) indicates that a low level of integration of three industries, a high level of agricultural digitalization, adequate agricultural technology extension, and a high willingness for land trusteeship can result in a high level of control over pre-production quality of agricultural products. Configuration N3 (EC*I*M*S) indicates that participation in cooperatives, a high level of integration of three industries, agricultural mechanization, and a strong agricultural technology extension effort can result in high control over pre-production quality of agricultural products. Configuration N4 (EC*I*D*S) indicates that participation in cooperatives, a high level of integration of three industries, a high degree of digitalization, and a strong agricultural technology extension effort can result in high control over pre-production quality of agricultural products. This configuration has the highest consistency index and the strongest explanatory power. Configuration N5 (EC*M*D*S) indicates that participation in cooperatives, high levels of agricultural mechanization and digitalization, and a strong agricultural technology extension effort can result in high control over pre-production quality of agricultural products. Configuration N6 (EC*M*S*LC) indicates that participation in cooperatives, a high level of agricultural mechanization, a strong agricultural technology extension effort, and a high willingness for land trusteeship can result in high control over pre-production quality of agricultural products. Through the interpretation of the above six configurations, it can be seen that all six configurations significantly affect the level of pre-production quality and safety control of agricultural products. The explanatory power ranking is: N4 > N3 > N5 > N2 > N6 > N1. 4.5. Robustness Check Robustness checks are used to ensure that research findings are not accidental phenomena resulting from specific data or methodological choices. By altering certain parameters or conditions, if the results remain consistent, then these results can be considered reliable. Common robustness check methods include: adjusting calibration values, changing case frequency thresholds, varying consistency thresholds, and adding other conditions related to the outcome. This paper employs the method of changing case consistency thresholds to analyze whether the original results are robust by comparing the state of the set relationships and parameter differences before and after the change. By adjusting the case consistency threshold from 0.8 to 0.85, the generated configurations remain consistent with the original configurations, and the consistency and coverage of the solutions do not change. The robustness check shows that the configuration results are robust. 4.6. Result Discussion Based on the six configurations, three overarching configurational types can be summarized regarding how leading agricultural enterprises guide farmers to participate in pre-production quality and safety control. Configuration 1: Three-Industry Integration Driven This configuration includes configurations N3 and N4, characterized by the deep participation of cooperatives and the enhancement of three-industry integration levels, combined with the integrated application of agricultural mechanization, agricultural technology extension, and digital technologies. In configuration N3, the active involvement of cooperatives, high levels of three-industry integration, and the synergistic effect of agricultural mechanization and agricultural technology extension significantly enhance pre-production quality control capabilities of agricultural products. Configuration N4 further introduces higher levels of digital technology, strengthening the refined management of agricultural production, and demonstrating higher consistency indices and explanatory power in fsQCA analysis. This configuration is suitable for leading agricultural enterprises that promote industrial chain collaboration through modern agricultural production and deep industrial integration. By leading three-industry integration and modern technologies, these enterprises can stimulate farmers' willingness to participate and improve their behavioral performance in pre-production quality control. Therefore, the three-industry integration driven configuration not only helps to promote the coordinated development of agriculture, industry, and service sectors but also provides continuous momentum for high-quality agricultural production, enhancing the overall quality control level of the agricultural industrial chain by encouraging active farmer participation. Under this configuration, leading agricultural enterprises should collaborate with large-scale farmers to transfer and manage idle land to form large-scale planting, while also purchasing mechanized equipment and providing agricultural technology extension to part-time farmers and contract farmers to establish standardized production. Leading agricultural enterprises should further strengthen cooperation with cooperatives, promote the integrated development of agriculture with secondary and tertiary industries through the organized management of cooperatives, and facilitate the development of primary agricultural products towards processed agricultural products, branded products, and agricultural tourism, thereby upgrading products and increasing added value. Various types of farmers should participate in the integrated development of rural primary, secondary, and tertiary industries, forming a complete 'production-sales-tourism' industrial chain, which enhances farmers' subjective awareness of pre-production quality and safety control through industrial chain extension. Configuration 2: Digital Intelligence Driven This configuration encompasses configuration N5, emphasizing the core role of digital technologies and intelligent means in agricultural production, especially in the context of deep integration of agricultural mechanization and digital technologies. Configuration N5 indicates that, based on cooperative participation, the enhancement of agricultural mechanization levels, the widespread application of digital technologies, and the strengthening of agricultural technology extension jointly build an efficient pre-production quality control system. The digital intelligence driven configuration is particularly suitable for agricultural production environments with high digital technology penetration and advanced information levels. Under this configuration, relying on advanced digital and intelligent means can achieve precise monitoring and quality assurance of the entire agricultural production process, thereby promoting the transformation of agricultural production towards efficiency, greenness, and intelligence. This configuration emphasizes the leading role of agricultural enterprises in promoting and applying digital technologies to encourage farmers to actively participate in pre-production quality control, ensuring that agricultural products are produced more accurately and efficiently. The leading role of agricultural enterprises provides farmers with technical support and management tools to help them overcome the limitations of traditional production methods, thereby improving the overall quality control capabilities of the industrial chain. In this model, it is recommended that agricultural enterprises provide more comprehensive technical support to various types of farmers. For contract farmers and large-scale farmers, enterprises should use digital platforms and intelligent equipment to help farmers monitor the entire agricultural production process. Enterprises should improve information flow capabilities and socialized services such as agricultural machinery and technology for individual smallholders and part-time farmers, enhancing their initiative to participate in pre-production quality and safety control. Configuration 3: Land Trusteeship Driven This configuration includes configurations N1, N2, and N6, characterized by the high manifestation of land trusteeship willingness, supplemented by the support of agricultural mechanization and agricultural technology extension. The implementation of land trusteeship significantly reduces the presence of individual smallholders and promotes the increase of contract farmers, part-time farmers, and large-scale farmers, driving the intensive management model of farmers. In configurations N1 and N2, the combination of the strength of land trusteeship willingness, the level of agricultural digitalization, and effective agricultural technology extension plays a crucial role. Especially in the context of strong land trusteeship willingness, enterprises can improve farmers' willingness and ability to participate in pre-production quality control by optimizing land resource allocation and strengthening technical support. The land trusteeship model helps to reduce the dispersion among farmers, increase production scale, and thereby enhance their enthusiasm and efficiency in participating in quality control. In configuration N6, the synergistic application of land trusteeship and agricultural mechanization further enhances farmers' production capacity and quality control levels. The land trusteeship model helps farmers improve production efficiency and strengthen quality and safety control through centralized management, large-scale production, and technical support. The guidance and support of agricultural enterprises enable farmers, especially contract farmers, part-time farmers, and large-scale farmers, to better participate in the quality control process of agricultural products, thereby improving the quality and safety level of the entire industrial chain. The land trusteeship driven configuration highlights the positive role of land trusteeship in enhancing farmers' initiative to participate in pre-production quality control. This model is particularly suitable for areas where land trusteeship obligations and agricultural mechanization levels are at a medium to low stage. Agricultural enterprises should further improve land trusteeship and transfer mechanisms, optimize resource allocation, and strengthen cooperation with cooperatives. Through the organized management of cooperatives, they should promote the implementation of land trusteeship models and provide land trusteeship support for part-time farmers and individual smallholders. For contract farmers and large-scale farmers, enterprises should continuously promote the synergistic application of land trusteeship models and agricultural mechanization, improve farmers' production efficiency through advanced management systems, and strengthen quality monitoring to promote the quality improvement of the entire industrial chain. Through the summarization and analysis of the six configurations, it can be seen that under the combined effect of village-enterprise cooperation, three-industry integration, agricultural mechanization, digitalization, and agricultural technology extension, farmers show a strong willingness to participate in pre-production quality and safety control of agricultural products. These configurations not only effectively enhance the quality and safety control capabilities of agricultural product raw materials by leading agricultural enterprises but also reduce quality risks in the mid- and post-production stages, thereby improving the quality and safety control efficiency of the entire industrial chain. Furthermore, the research results indicate that the leading role of agricultural enterprises on farmers is the result of multi-factor synergy, which further verifies the complexity of the configurations and increases the credibility of problem analysis based on a configurational perspective. 5. Conclusions This study, focusing on leading agricultural enterprises and farmers in the Yangtze River Delta region of China, explores the configurational pathways of leading agricultural enterprises guiding farmers to participate in pre-production quality and safety control, combining grounded theory and fuzzy-set Qualitative Comparative Analysis (fsQCA). The research provides constructive suggestions for leading agricultural enterprises to guide farmers in participating in vertical collaboration within the industrial chain to a certain extent, but it still has some limitations. In the configuration analysis process, this paper selected five conditional variables—village-enterprise cooperation, integration of three industries, agricultural mechanization, agricultural digitalization, and agricultural technology extension—to study their configurational effects on farmers' participation in pre-production quality and safety control. Considering that enterprise quality control behaviors in grounded analysis can be further subdivided, future research could further refine the configurational effects of specific enterprise behaviors in quality control on guiding farmers' participation in pre-production quality control. 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Management World , 40(6) , 217–237 , (2024). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 07 Dec, 2025 Reviews received at journal 01 Oct, 2025 Reviewers agreed at journal 31 Aug, 2025 Reviews received at journal 15 Aug, 2025 Reviews received at journal 08 Aug, 2025 Reviewers agreed at journal 16 Jul, 2025 Reviewers agreed at journal 13 Jul, 2025 Reviewers agreed at journal 13 Jul, 2025 Reviewers agreed at journal 10 Jul, 2025 Reviewers invited by journal 10 Jul, 2025 Editor invited by journal 21 May, 2025 Editor assigned by journal 21 May, 2025 Submission checks completed at journal 21 May, 2025 First submitted to journal 26 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6536489","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":484796249,"identity":"612596d4-a6ac-4bde-95c3-7b3ab29d3859","order_by":0,"name":"Chenying Liu","email":"","orcid":"","institution":"Jiangsu University","correspondingAuthor":false,"prefix":"","firstName":"Chenying","middleName":"","lastName":"Liu","suffix":""},{"id":484796250,"identity":"e23d7e19-bfb9-42fa-aca3-cdbecd58fcef","order_by":1,"name":"Wen Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAp0lEQVRIiWNgGAWjYDACdsbGBww8IFYCsVqYGZsNSNXCwCYBYRGrxeAwc1s1j0wdAz97jgHDzx1EaWFsu83Dc5hBsueNAWPvGSK0mEG0HGAwuJFjwMzYRqSWYh6eOgZ7krQw8/AwMxhIEKvF/jBjs+QcnsM8EmeeFRzsJUaLZHv7ww9ve+rk+NuTNz74SYwWMGDsgUTmAWI1AMEPEtSOglEwCkbByAMA8vcug8RPzC8AAAAASUVORK5CYII=","orcid":"","institution":"Jiangsu University","correspondingAuthor":true,"prefix":"","firstName":"Wen","middleName":"","lastName":"Li","suffix":""},{"id":484796251,"identity":"4903d682-0d9f-4c2a-880c-3ae3cc2bf49b","order_by":2,"name":"Yulan You","email":"","orcid":"","institution":"Jiangsu University","correspondingAuthor":false,"prefix":"","firstName":"Yulan","middleName":"","lastName":"You","suffix":""},{"id":484796253,"identity":"90aea03a-a183-4141-b4be-1a120b61daf0","order_by":3,"name":"Qizhi Yang","email":"","orcid":"","institution":"Jiangsu University","correspondingAuthor":false,"prefix":"","firstName":"Qizhi","middleName":"","lastName":"Yang","suffix":""},{"id":484796255,"identity":"7d67348b-d441-4ba0-8e41-dcb8b2c2a7ef","order_by":4,"name":"Mingjuan Li","email":"","orcid":"","institution":"Jiangsu University","correspondingAuthor":false,"prefix":"","firstName":"Mingjuan","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2025-04-26 18:08:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6536489/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6536489/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86777078,"identity":"7a2a16e0-2a18-4b60-bce3-739855d92c9b","added_by":"auto","created_at":"2025-07-15 12:48:05","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":126593,"visible":true,"origin":"","legend":"\u003cp\u003ePathways for Leading Agricultural Enterprises to Guide Farmers in Pre-Production Quality and Safety Control Through the Organizational Linkage Mechanism\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6536489/v1/85440e6ea07e8c423a8d7378.png"},{"id":86777080,"identity":"ffe5a9b4-d9c7-4235-8de5-115466d31452","added_by":"auto","created_at":"2025-07-15 12:48:05","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":126728,"visible":true,"origin":"","legend":"\u003cp\u003ePathways for Leading Agricultural Enterprises to Guide Farmers in Pre-Production Quality and Safety Control Through the new quality productive forces elements linkage mechanism\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6536489/v1/7a60d69adf365043f69d0abd.png"},{"id":86777081,"identity":"f3c7c1d2-1675-4322-8e14-8b1b612e7c6a","added_by":"auto","created_at":"2025-07-15 12:48:05","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":72382,"visible":true,"origin":"","legend":"\u003cp\u003eThe Mechanism of Leading Agricultural Enterprises Guiding Farmers to Participate in Pre-Production Quality and Safety Control\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6536489/v1/8913c7125cbccfc118925357.png"},{"id":86778759,"identity":"39e0d481-de2a-4580-bba0-71331882b108","added_by":"auto","created_at":"2025-07-15 13:04:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1642253,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6536489/v1/2fdda7dd-7728-4c6c-9957-46749ef84cca.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Research on Leading Agricultural Enterprises Guiding Farmers' Participation in Pre-Production Quality and Safety Control: Evidence from the Yangtze River Delta Region of China","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eChina has proposed accelerating the construction of a new development pattern and achieving the strategic goal of modernizing with high-quality development, with a particular emphasis on the priority development of agriculture and rural areas. High-quality agricultural development is not only the core path to promoting rural revitalization and building a strong agricultural nation but also an inevitable choice for realizing the goal of Chinese-style modernization. In this process, China has introduced the concept of \u0026ldquo;New quality productivity\u0026rdquo;, aiming to guide economic transformation and upgrading, promote the cultivation of strategic emerging industries and future industries, and foster the formation of new forms of productivity with new attributes, functions, and characteristics [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eNew quality productivity is essentially a form of productivity driven by innovation, distinct from traditional economic growth models. It emphasizes technological progress, optimized resource allocation, and highly efficient production methods. Specifically, New quality productivity is jointly fostered by technological breakthroughs, innovative allocation of production factors, and deep transformation and upgrading of industrial chains. The core feature of this concept is the optimized combination of labor, labor materials, and labor objects, which drives productivity improvement. A significant increase in total factor productivity becomes a core indicator of New quality productivity development, and its key driving force is innovation, fundamentally reflecting advanced productivity. In the context of Chinese-style modernization, agricultural productivity upgrading is not only the result of technological innovation but also a systematic improvement supported by multiple dimensions, including technology, factors, systems, and the environment [\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. New quality productivity emphasizes transforming agricultural productivity through technological innovation, especially in terms of increasing agricultural total factor productivity and achieving low-carbon, green, and sustainable development, which is of great significance. This process not only focuses on improving production efficiency but also aims to meet the growing demand for high-quality agricultural products, thereby enhancing the overall quality of life for the people [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn the context of agricultural industrialization, agricultural industrial organization models, based on industrial organization theory, play a vital role as institutional carriers in agricultural development, serving as bridges, links, and carriers in the agricultural industry. Therefore, promoting close connections between farmers and other entities in the industrial chain, establishing stable industrial organization models, may become an effective path for enterprise-led farmer participation in pre-production quality and safety control. Existing research suggests that the primary organizational model is \"agricultural leading enterprises\u0026thinsp;+\u0026thinsp;cooperatives\u0026thinsp;+\u0026thinsp;farmers.\" This organizational model not only helps implement various quality control measures effectively in agricultural production but also enhances the production capacity and quality safety control efficiency of agricultural leading enterprises. Agricultural leading enterprises, with their modern production capabilities, refined management mechanisms, and extensive market channels, play a leading role in quality and safety control in the agricultural product supply chain. Since 2018, multiple departments, such as the Ministry of Commerce and the Ministry of Agriculture and Rural Affairs, have jointly promoted the \"Supply Chain Innovation and Application Pilot\" project, aiming to promote the deep integration of farmers and the agricultural industry chain, thereby forming a full industrial chain cooperation model centered on agricultural leading enterprises and benefiting farmers [\u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In this model, cooperatives serve as a bridge between enterprises and farmers, helping agricultural leading enterprises influence farmers' production behaviors, promoting green planting, and achieving carbon reduction in agriculture. Cooperatives also facilitate the organic connection of smallholder farmers with modern agriculture through organizational operations, standardized production, green production, financial credit, and the extension of the industrial chain.\u003c/p\u003e\u003cp\u003eWith the improvement of China's economic development level and agricultural labor productivity, as well as the diversification of agricultural industrial structure and rural employment structure, urbanization's absorption of rural population, and other factors, traditional farmers are being impacted from various angles and levels, leading to a diversity of economic perspectives and planting scales. This has resulted in a diversified classification of farmers, including individual farmers, contract farmers, mixed farmers, and large-scale farmers [\u003cspan additionalcitationids=\"CR15 CR16 CR17\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePrevious research has recognized the importance of strengthening quality and safety control during the agricultural production phase. Liu Hongchao (2021) and others proposed using blockchain technology to supervise key data, such as production conditions, agricultural input usage, and processing materials, to achieve effective pre-production quality safety control of agricultural products [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Pan Siqi and Luo Feng (2021) suggested building an \"Internet+\" integrated monitoring platform to improve the current instability in agricultural product production quality [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Li et al. (2022) researched the impact of digital promotion services via smartphones on farmers' adoption of sustainable agricultural technologies, finding that farmers using these services could improve the effectiveness of quality and safety control actions, such as precision fertilization, technical learning, and soil testing [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Lu Quanzhi and Zhang Yifeng (2022), while exploring how cooperatives promote green production among farmers, indicated that cooperatives significantly boost farmers' adoption of green production behaviors, with an overall increase of 25.57% [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Chen Weiqiang and Ma Pengchao (2023) argued that cooperative support significantly enhances farmers' cognitive and behavioral abilities, serving as an important external factor in agricultural product quality and safety control [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Cai Rong et al. (2019) used the example of reduced fertilizer and pesticide use to illustrate the positive role cooperatives play in improving agricultural product quality and safety [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Zhang Fengyi et al. (2022) found that cooperatives could improve farmers' quality control behaviors, with cooperatives owning independent agricultural product brands placing more emphasis on product quality control [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Li Dan et al. (2021) suggested that brand premiums have a positive effect on pre-production quality safety control, particularly when brand-specific assets constrain farmers' production behaviors, maximizing the impact of brand premiums on enhancing product quality and safety [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Under the background of supply-side structural reform in agriculture, agricultural mechanization has not only promoted large-scale production but also facilitated the integration of primary, secondary, and tertiary industries, thereby contributing to improved agricultural product quality [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Liu Lingxiu (2024) proposed that chemical weeding has a negative impact on product quality, and the introduction of mechanized physical weeding robots provides technical support for the production of high-quality agricultural products [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Yin et al. (2022) developed a high-end equipment manufacturing system framework aimed at satisfying the green quality requirements of agricultural products, providing a technological path for high-quality agricultural development [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Yang and Li (2022) suggested that agricultural machinery services should be tailored to local conditions to better meet farmers' needs for producing high-quality agricultural products [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Yu Lianghong et al. (2022) found through heterogeneity analysis that farmers involved in managed economic crops achieve the highest ecological and economic benefits, with service organizations in land trusteeship using environmentally friendly agricultural technologies such as green pest control, integrated water and fertilizer management, and soil testing-based fertilization, significantly reducing pesticide and fertilizer application intensity and improving agricultural product quality and safety [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eBased on the existing literature, current research primarily focuses on specific methods and technological pathways for agricultural product quality and safety control. However, there is relatively limited attention to the factors influencing farmers' proactive safety production behaviors under the guidance of leading enterprises in a multi-actor context. Therefore, this study aims to explore which agricultural product quality control measures are more effectively accepted and adopted by farmers in the context of agricultural leading enterprises taking the lead. At present, research on pre-production quality and safety control of agricultural products has covered various aspects, including cooperative participation, industrial integration, mechanization levels, and digital technologies. However, most studies tend to focus on the independent effects of single factors on quality control. As research methods continue to improve, the interactive effects among multiple factors and their complex impacts on quality control effectiveness have gradually emerged as a new research direction.\u003c/p\u003e\u003cp\u003eBased on this, this paper uses data from agricultural leading enterprises and farmers in the Yangtze River Delta region of China, applying configurational theory to analyze the multidimensional combination of measures that guide farmer behavior and their multiple interactive effects on pre-production quality control of agricultural products. By exploring the mechanisms of multi-factor dynamic combinations in agricultural product quality and safety, this paper aims to provide a theoretical basis and empirical support for optimizing quality control strategies and practical pathways.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"2. Identification of Mechanisms and Influencing Factors","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Mechanisms Analysis\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThis study selects four leading agricultural enterprises in the Yangtze River Delta region of China, which guide farmers in producing high-quality agricultural products, as research samples (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). A multiple-case study is conducted using the grounded theory method. Following the analytical logic of \"motivation\u0026ndash;behavior\u0026ndash;outcome,\" interview data from these enterprises are systematically extracted, thoroughly analyzed, and coded at multiple levels. Ultimately, a theoretical interpretation is constructed to reveal the internal mechanism of agricultural leading enterprises in pre-production raw material quality control [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBasic Information of the Four Case Enterprises\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003eCase Enterprises\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCompany A\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCompany B\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCompany C\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCompany D\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCore Business\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMulberry Wine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePueraria (Kudzu) Agricultural and Sideline Products\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRice\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTable Grapes and Wine\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProduct Advantages\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDeep-processed High-end Health Agricultural Products\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHigh Nutritional and Health Value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHigh Nutritional Value and Excellent Taste\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eWide Variety, Excellent Quality, and Superior Ecological Environment\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCustomer Network\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInvolves hundreds of distributors, group purchases, and online stores\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGroup Purchases and Online Sales\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAcquired by COFCO (China National Cereals, Oils and Foodstuffs Corporation)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eOffline Stores, Online Sales, and Corporate Procurement\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSales Scale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e150\u0026nbsp;million RMB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e300\u0026nbsp;million RMB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e70\u0026nbsp;million RMB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e300\u0026nbsp;million RMB\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInvolved Farmers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eApproximately 500 households\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e200 Pluriactive Farmers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eOver 20,000 mu under contract\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2,000 mu of grape fields, with a total of 1,927 growers\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThis study employs open coding to systematically analyze the interview data of the four case enterprises, thoroughly reading and accurately understanding the text to identify the main mechanisms and key events related to the motivations, behaviors, and outcomes of agricultural leading enterprises guiding farmers in pre-production quality and safety control. During the coding process, the latest theoretical research advancements are incorporated to conceptualize and summarize the relevant content from the case materials. The motivation section focuses on the roles, functions, and effects of farmers in pre-production quality and safety control; the behavior section examines the response measures under different mechanisms; and the outcome section analyzes the changes and impacts on both farmers and pilot enterprises after implementing action strategies under different mechanisms. This process then distills secondary coding entries. Based on this, axial coding is applied to integrate and abstract the open coding concepts, further summarizing them into higher-level categories, ultimately forming the primary coding.\u003c/p\u003e\u003cp\u003eBased on the aforementioned logical analysis and research design, a grounded theory analysis is conducted to explore the pathways and mechanisms through which leading agricultural enterprises engaged in high-quality agricultural product production guide farmers to participate in pre-production quality and safety control. The primary focus is to address the issue of linkage, specifically by examining the linkage establishment process and performing a processual analysis. This aims to elucidate the linkage mechanisms and pathways through which agricultural leading enterprises orchestrate farmer involvement in pre-production quality and safety control.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eMechanism 1: Organizational Connection Mechanism\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eWithin the organizational linkage mechanism, labor force elements constitute the foundation for leading agricultural enterprises to implement pre-production quality and safety control. However, a primary challenge currently faced is the heterogeneity of farmer types, encompassing contract farmers, part-time farmers, large-scale farmers, and individual smallholders, each exhibiting significantly divergent demands. The inability of leading agricultural enterprises to effectively discern the specific roles and needs of these diverse farmer types in pre-production quality and safety control leads to a lack of targeted quality control measures, consequently resulting in agricultural product quality and safety issues.\u003c/p\u003e\u003cp\u003eIn response, case enterprises have adopted a series of countermeasures. Agricultural cooperatives play a pivotal intermediary role between leading agricultural enterprises and farmers. Utilizing village-enterprise collaboration as a bridge, leading agricultural enterprises, through contracting with cooperatives, enhance the awareness and behaviors of various farmer types regarding agricultural product quality and safety control. Cooperatives disseminate the economic and social value of quality control to farmers through policy dissemination and organized training, thereby reinforcing farmers' behavioral cognition of quality control. Simultaneously, a mechanism combining rewards and penalties is employed to ensure the equivalent conversion of agricultural product value, gradually shifting agricultural product prices from a pooling equilibrium to a separating equilibrium. This breaks the economic cycle of 'bad money driving out good,' thereby enhancing farmers' willingness to implement quality control. Building upon the cultivation and enhancement of farmers' quality control behavioral capabilities, leading agricultural enterprises provide support tools such as production factors, technical training, and low-interest loans. By promoting the establishment of industry-university-research groups and conducting targeted technical training, farmers' capacity to implement quality control is augmented.\u003c/p\u003e\u003cp\u003eLeading agricultural enterprises, through promoting land trusteeship or transfer, improve the efficiency of idle resource element utilization and further stimulate farmers' enthusiasm for producing high-quality agricultural products. For part-time farmers facing household labor shortages or seasonal employment, idle land is entrusted or transferred to cooperatives, enterprises, or small farmers, forming a more efficient intensive management model. This production model not only facilitates specialized management and enhances production management efficiency but also integrates agricultural materials, technology, and human resources required for high-quality agricultural product production, enabling dynamic management of breeding, production management, and post-harvest storage processes. Concurrently, enterprises leverage big data, cloud computing, and Internet of Things technologies to predict extreme climate and natural disaster changes, enabling proactive scientific production decisions. Government subsidies for large-scale production of high-quality agricultural products further incentivize the contiguous production model of land trusteeship or transfer, allowing farmers to benefit from policy dividends and promoting the effective implementation of pro-farmer policies.\u003c/p\u003e\u003cp\u003eLeading agricultural enterprises, through the deep integration of primary, secondary, and tertiary industries, enhance farmers' awareness of pre-production agricultural product quality and safety control. The extension of the industrial chain not only lengthens the agricultural product value chain but also propels farmers towards high-quality production transformation. In forward extension, the order contract model directly links farmers' production behaviors with market demands, unifying quality standards and brand requirements, thereby standardizing farmers' production behaviors. By enhancing industrial chain resilience and developing new products and brands, leading enterprises enable farmers to more directly perceive the premium benefits of high-quality agricultural products, thereby further enhancing their quality control awareness. The grounded theory analysis results and pathways of leading agricultural enterprises guiding farmers to participate in pre-production quality and safety control based on the organizational linkage mechanism are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, respectively.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eGrounded Theory Analysis Results of Leading Agricultural Enterprises Guiding Farmers' Participation in Pre-Production Quality and Safety Control Based on the Organizational Linkage Mechanism. (Selected Representative Evidence)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLogical Foundation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLevel 1 Coding\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLevel 2 Coding\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRepresentative Evidence\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003eMotivations\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003eLabor Factors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eContract Farmers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eA: The company enters into contracts with cooperatives, stipulating annual quality standards and order volumes.\u003c/p\u003e\u003cp\u003eB: The company establishes contracts with individual farmers for the procurement of kudzu root.\u003c/p\u003e\u003cp\u003eC: The company engages in contractual land leases with farmers, employing them for rice cultivation.\u003c/p\u003e\u003cp\u003eD: The company enters into contracts with farmers for the acquisition of fresh fruit.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003ePluriactive Farmers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eA: Farmers establish an employment relationship with the Xiajin Yellow River Old Course Ancient Mulberry Tree Cluster as employees, participating in the maintenance and harvesting of the ancient mulberry trees.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eB: Farmers are employed as temporary workers at the Maobao Kudzu Root Garden, engaging in production activities such as kudzu root harvesting and weeding.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eC: Farmers participate in rice cultivation as laborers.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSmall-scale Farmers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eA: Farmers sell their cultivated mulberries to the company.\u003c/p\u003e\u003cp\u003eB: Local farmers harvest and sell wild kudzu root to the company.\u003c/p\u003e\u003cp\u003eD: Farmers sell their self-cultivated grapes to the company.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLarge-scale Farmers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eA: Large-scale farmers cultivate tens of acres of mulberry trees.\u003c/p\u003e\u003cp\u003eB: The company conducts on-site procurement of farmers' homemade kudzu root powder.\u003c/p\u003e\u003cp\u003eD: Farmers contract large tracts of land for grape cultivation.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eBehaviors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eIntegration of Primary, Secondary, and Tertiary Industries\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIndustrial Chain Resilience\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eA: The company develops the 'Purple Wine Town Project', aiming to radiate throughout Maoshan.\u003c/p\u003e\u003cp\u003eA: The company registers the 'Worry-Free Mulberry' brand and develops new mulberry leaf tea products.\u003c/p\u003e\u003cp\u003eB: The company actively develops specialty products such as kudzu root tea, kudzu root biscuits, kudzu root enzyme, and kudzu root farm cuisine.\u003c/p\u003e\u003cp\u003eD: The company actively develops its wine business.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIndustrial Chain Extension\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eA: The company hosts the 'Kunming May Day Most Beautiful Mulberry Orchard' event, featuring mulberry fruit picking and tourism.\u003c/p\u003e\u003cp\u003eB: The company organically integrates the kudzu root industry with agricultural sightseeing tourism, establishing projects such as the Maobao Kudzu Garden, Kudzu Root Culture Museum, and Kudzu Root Demonstration Science Park.\u003c/p\u003e\u003cp\u003eC: The company establishes industry-university-research bases and conducts various research activities with universities.\u003c/p\u003e\u003cp\u003eD: The company develops summer vacation extension bases and establishes agritainment campsites.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVillage-Enterprise Cooperation Model\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCooperatives\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eA: The company directly interfaces with cooperatives, establishing guaranteed purchase agreements.\u003c/p\u003e\u003cp\u003eB: The company establishes its own cooperative.\u003c/p\u003e\u003cp\u003eC: The company establishes its own cooperative.\u003c/p\u003e\u003cp\u003eD: The company establishes the 'Dingzhuang Grape Cooperative Alliance'.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLand Trusteeship/Transfer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eA: The company leases tens of acres of land for the research and development of new varieties, technologies, and models.\u003c/p\u003e\u003cp\u003eB: The company leases 250 mu of land for the demonstration and promotion of standardized kudzu root cultivation.\u003c/p\u003e\u003cp\u003eC: The company manages land for the centralized cultivation of high-quality rice.\u003c/p\u003e\u003cp\u003eD: The company manages land entrusted by farmers and re-employs those farmers for the standardized cultivation of grapes.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eOutcomes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eOrganizational Linkage Mechanism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEnhancement of Land Factor Value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eA: A 5,000-acre raw material base, driving the 'one village, one product' initiative, has become one of the first rural characteristic industry hundred-million-yuan villages.\u003c/p\u003e\u003cp\u003eC: The signing of production and sales agreements has increased the value of nearly 20,000 acres of managed land.\u003c/p\u003e\u003cp\u003eD: The company's influence has led to the appreciation of land value across 2,000 acres.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEnhancement of Labor Factor Value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eA: The company recruits farmers for employment.\u003c/p\u003e\u003cp\u003eB: Farmers participate in kudzu root harvesting, contributing to a household income increase of twenty to thirty thousand yuan.\u003c/p\u003e\u003cp\u003eC: Farmers are responsible for field management.\u003c/p\u003e\u003cp\u003eD: The company encourages farmers to engage in grape cultivation.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEnhancement of Agricultural Product Quality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eA: The company increased the purchase price of mulberries.\u003c/p\u003e\u003cp\u003eB: The company enhanced farmers' awareness of green and high-quality products, incentivizing them to harvest wild and natural kudzu root.\u003c/p\u003e\u003cp\u003eC: \"The 'Run Guo Jiu Du' rice was rated as a four-star 'Very Delicious Rice' on China's 'Good Rice List'.\u003c/p\u003e\u003cp\u003eD: \"The 'Dingzhuang Grapes' were designated as a geographical indication agricultural product.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eMechanism 2: New Quality Productive Forces Elements Linkage Mechanism\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe current proposition of new quality productive forces elements highlights that producing high-quality agricultural products is pivotal, with advanced productivity being the essence. This entails focusing on new types of laborers, labor materials, and labor objects, along with their optimized combinations, and taking the substantial enhancement of total factor productivity as the core marker. Consequently, standardized and green planting have become new driving forces for leading agricultural enterprises to guide farmers in promoting pre-production agricultural product quality and safety control.\u003c/p\u003e\u003cp\u003eTo realize standardized and green planting, leading agricultural enterprises cultivate and develop new types of agricultural laborers, tools, and objects. Through agricultural technology extension and industry-university-research cooperation, leading agricultural enterprises enhance farmers' quality control capabilities. Enterprises invite agricultural experts to provide full-cycle production technical guidance to farmers in the fields and collaborate with research institutions to develop patented technologies and promote standardized planting models. New labor objects, centered on data elements, enable leading agricultural enterprises to establish digital platforms for digital and information-based monitoring of field management. By leveraging big data, cloud computing, and Internet of Things technologies, enterprises construct intelligent farmland management systems to achieve real-time monitoring of crop growth environments and optimize planting strategies through intelligent decision-making systems. In terms of financial credit, enterprises launch agricultural credit platforms to provide farmers with financial support such as agricultural material credit sales, reducing farmers' production input pressure and enhancing their enthusiasm for participating in high-quality planting. For quality traceability, enterprises establish a full-process traceability system from production to market, including product QR code traceability and government food safety electronic traceability systems, ensuring that the sources of agricultural products are traceable, destinations are trackable, and responsibilities are accountable, thereby enhancing consumer trust in product quality. New types of labor tools in agricultural mechanization are crucial for improving agricultural product quality. Addressing the issues of insufficient farm machinery and low mechanization levels among farmers, leading agricultural enterprises reduce farmers' production costs and improve mechanized operation efficiency through agricultural machinery outsourcing leasing and maintenance scheduling mechanisms. Enterprises or cooperatives provide farm machinery leasing services and conduct pilot demonstrations in areas suitable for farm machinery promotion to enhance farmers' awareness and application capabilities of mechanized planting. Furthermore, for complex terrains such as hills and mountains, enterprises establish farm machinery adaptation and scheduling systems to ensure that farmers can access suitable agricultural machinery and maintenance services, thereby improving the precision and stability of agricultural production.\u003c/p\u003e\u003cp\u003eLeading agricultural enterprises, relying on the linkage mechanism of new quality productive forces elements, integrate key elements such as modern technology and industrial chain collaboration to promote the construction of innovative production models and facilitate deep synergy between enterprises and various types of farmers along the industrial chain, thereby improving the quality and yield of agricultural products. The grounded theory analysis results and pathways of leading agricultural enterprises guiding farmers in pre-production agricultural product quality and safety control based on the linkage mechanism of new quality productive forces elements are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, respectively.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eGrounded Theory Analysis Results of Leading Agricultural Enterprises Guiding Farmers' Participation in Pre-Production Quality and Safety Control Based on the Organizational Linkage Mechanism. (Selected Representative Evidence)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLogical Foundation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLevel 1 Coding\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLevel 2 Coding\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRepresentative Evidence\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eMotivations\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eOptimization of New Quality Productive Forces Elements\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStandardized Cultivation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eA: The company implements standardized maintenance protocols and adopts uniform quality standards for mulberry procurement.\u003c/p\u003e\u003cp\u003eC: The company employs uniform varieties, fertilizers, and field management practices for cultivation.\u003c/p\u003e\u003cp\u003eD: Through standardized cultivation, the company modifies farmers' traditional planting habits.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGreen Cultivation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eA: The company provides farmers with green planting guidance and encourages the use of organic fertilizers.\u003c/p\u003e\u003cp\u003eB: The company encourages farmers to cultivate wild kudzu root and conducts monitoring of soil and water quality.\u003c/p\u003e\u003cp\u003eC: The company prohibits the burning of straw and promotes straw composting.\u003c/p\u003e\u003cp\u003eD: The company uniformly implements green management practices and organic cultivation.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eBehaviors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eAgricultural Mechanization\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAgricultural Machinery Outsourcing Leasing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eA: Due to the high cost of manual mulberry harvesting, the company needs to promote mechanized harvesting and sorting.\u003c/p\u003e\u003cp\u003eC: The company provides agricultural machinery and implements.\u003c/p\u003e\u003cp\u003eD: The cooperative provides agricultural machinery and implements.\u003c/p\u003e\u003cp\u003eD: The company installs drip irrigation facilities.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAgricultural Machinery Maintenance and Scheduling\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eA: The cultivation site is hilly, necessitating the deployment of agricultural machinery suitable for hilly terrain.\u003c/p\u003e\u003cp\u003eC: The company schedules agricultural machinery and provides maintenance services to farmers.\u003c/p\u003e\u003cp\u003eD: The cooperative alliance provides agricultural machinery maintenance services.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eAgricultural Digitalization\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDigital Agriculture Platform\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eA: The company utilizes integrated dashboards for order and production information.\u003c/p\u003e\u003cp\u003eC: The company has established a 'Smart Farmland Patrol' digital management system for field operations.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFinancial Credit Platform\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eA: The company has developed a 'one card per household' platform, offering farmers access to agricultural input credit sales services.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eQuality Traceability Platform\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eA: Each bottle of wine is affixed with an agricultural product traceability code.\u003c/p\u003e\u003cp\u003eB: The company regularly submits data to the Jiangsu Province Agricultural Product Traceability Platform and the Zhenjiang City Food Safety Electronic Traceability System.\u003c/p\u003e\u003cp\u003eC: The company has developed a field monitoring and traceability function.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAgricultural Standardization\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAgricultural Technology Extension\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eA: The company engages experts to provide technical guidance to farmers and supplies them with agricultural materials.\u003c/p\u003e\u003cp\u003eB: The company collaborates with universities on patented technologies.\u003c/p\u003e\u003cp\u003eD: The company constructs grape greenhouses and collectively contracts them out.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eOutcomes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eNew Quality Productive Forces Elements Linkage Mechanism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIncrease Raw Material Output\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eA: \"Following collaboration, the yield of a single mulberry tree exceeded 100 kilograms; the cultivation area expanded from 1,000 acres to over 3,000 acres.\u003c/p\u003e\u003cp\u003eC: The yield per acre increased to 1,200-1,300 kilograms, representing a 9% improvement in per-acre productivity.\u003c/p\u003e\u003cp\u003eD: Production increased to 420,000 tons, with monthly exports of 4\u0026ndash;5 tons overseas.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eImprove Raw Material Quality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eA: Quality is reflected in the procurement price, which has steadily increased from 1.5 yuan to over 2 yuan.\u003c/p\u003e\u003cp\u003eB: The company rigorously ensures the green and organic nature of raw materials.\u003c/p\u003e\u003cp\u003eC: Water resource utilization has increased by 30%, fertilizer utilization by 15%, pesticide usage has decreased by over 20%, and per-acre benefits have risen by 20%.\u003c/p\u003e\u003cp\u003eD:'Dingzhuang Grapes' have been designated as a national geographical indication agricultural product and have received multiple awards for 'Green and High-Quality Agricultural Products'.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThis study, taking four representative leading agricultural enterprises as examples, analyzes the cyclical mechanisms through which enterprises guide farmers to participate in pre-production quality and safety control. By exploring the inherent logic of 'motivations-behaviors-outcomes,' it is found that the linkage mechanisms involve two dimensions: organizational and new quality productive forces elements. These are multi-dimensional linkage mechanisms that collaboratively ensure and facilitate farmers' participation in the quality and safety control of the industrial chain. The organizational linkage mechanism serves as a necessary foundation for enterprises to guide farmers in pre-production quality and safety control. It addresses the effective integration of farmers' production factors, such as land and labor, into the agricultural industrial chain by organizing contract and large-scale farmers through cooperative organizational management and absorbing individual smallholders and part-time farmers through land transfer/trusteeship. This enables various types of farmers to become the first link in the agricultural industrial chain and a necessary component of vertical collaboration. The linkage mechanism of new quality productive forces elements acts as a catalyst for enterprises to guide farmers in pre-production quality and safety control. Starting from green and standardized planting, leading agricultural enterprises optimize the combination of technological innovation, labor materials, and labor objects, enabling farmers to participate in agricultural production activities conveniently and efficiently. This drives farmers to achieve self-accumulation cycles, innovation, and transformation, ensuring high-quality and high-yield outcomes.\u003c/p\u003e\u003cp\u003eIn the quality and safety control of the entire agricultural industrial chain, leading agricultural enterprises promote farmers' active participation in pre-production quality and safety control through the synergistic effect of organizational linkage mechanisms and new quality productive forces elements linkage mechanisms, thereby improving the quality and yield of agricultural products. This mechanism provides an effective path for deep cooperation between leading agricultural enterprises and farmers, promotes the modernization and high-quality development of agricultural production, and supports the innovation and sustainable development of the agricultural industrial chain. The mechanisms through which leading agricultural enterprises guide farmers in pre-production quality and safety control are illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Identification of Influencing Factors\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThrough a grounded theory analysis based on literature review and field research, this study reveals that pre-production quality and safety control in agriculture is a multi-path, complex behavior of deep collaboration between leading agricultural enterprises and farmers. The integration of three industries, village-enterprise cooperation, agricultural mechanization, agricultural digitalization, and agricultural standardization have, to varying degrees, promoted farmers' participation in pre-production quality and safety control. However, the complexity of this combined pathway poses challenges to traditional regression analysis methods. Therefore, it is necessary to select key behavioral elements based on the actual needs of leading agricultural enterprises and farmers, and to explore the configurational structures under multiple behavioral interactions, in order to accurately identify the core and peripheral factors influencing farmers' participation in pre-production quality and safety control. In light of this, this paper selects five key elements\u0026mdash;the integration of three industries, village-enterprise cooperation, agricultural mechanization, agricultural digitalization, and agricultural technology extension\u0026mdash;as antecedent conditions for guiding farmers' deep participation in pre-production quality and safety control. The specifics are shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eNames and Specific Details of Relevant Variables\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAntecedent Conditions\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSpecific Contents\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVillage-Enterprise Cooperation (EC)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRecognition of Cooperative Role\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntegration of Three Industries (I)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWillingness to Extend Industrial Chain\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAgricultural Mechanization (M)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAcceptance of Machinery Leasing and Maintenance Scheduling\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAgricultural Digitalization (D)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAcceptance of Digital Information Platform\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAgricultural Technology Extension (S)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAgricultural Technology Extension\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLand Circulation/Trusteeship (LC)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWillingness of Land Circulation/Trusteeship\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Data and methods","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Fuzzy Set Qualitative Comparative Analysis Method\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eFuzzy-set Qualitative Comparative Analysis (fsQCA) is a research method that combines qualitative and quantitative approaches. It builds upon the theory and methods of Qualitative Comparative Analysis (QCA), integrating Boolean algebra and set theory to provide a novel research perspective for addressing complex causal relationships. By leveraging the advantages of both quantitative and qualitative analysis, fsQCA analyzes and synthesizes concurrent causal relationships among different sets through the comparison of a certain number of cases. This means that various combinations of variables may influence multiple cases to produce the same phenomenon. From a holistic perspective, fsQCA explores the process of complex social problems arising from multiple concurrent causes [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Compared to crisp-set Qualitative Comparative Analysis (csQCA) and multi-value Qualitative Comparative Analysis (mvQCA), fsQCA better prevents information loss during data conversion and enhances data precision, thereby more accurately detecting the effects caused by changes in antecedent conditions [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Due to its ability to transform causal relationships into complex causalities characterized by fuzziness, asymmetry, and equivalence, fsQCA can address partial membership issues of sets, precisely capturing the impact of conditional variable changes on outcome variables [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis paper employs the fsQCA method, primarily considering that existing research indicates that exploring the pathways for leading agricultural enterprises to guide farmers in pre-production quality and safety control requires more than just analyzing the independent effects of individual behaviors. It necessitates a holistic approach to investigate the outcomes of multiple complex variables interacting with each other. By transforming fuzzy sets into truth tables, fsQCA retains the advantages of truth table analysis in processing qualitative data, limited diversity, and simplifying configurations, thereby endowing the research with dual attributes of qualitative and quantitative analysis [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Furthermore, this paper utilizes fsQCA 3.0 software to set qualitative anchors and employs program operations to finely calibrate the variable membership and outcome membership of cases within the sets. Necessity analysis of individual conditional variables is conducted, and truth tables are constructed to explore the impact of conditional variable combinations on outcome variables. Finally, the conditional configurations are analyzed to examine the sufficiency of different conditional variable configurations on the outcome variables [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Data Source\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eGiven that the fsQCA method's sample size requirements differ from traditional quantitative analysis methods, this study selected 40 farmers from the Yangtze River Delta region of China as the research sample. According to the research needs, the sample selection criteria included: farmers must be within the industrial radiation range of enterprise A and cover four types: contract farmers, part-time farmers, individual smallholders, and large-scale farmers. The design of the questionnaire was closely aligned with behaviors related to organizational linkage mechanisms and new quality productive forces elements linkage mechanisms. A total of 40 questionnaires were distributed, and 33 valid questionnaires were returned, meeting the standards for medium-sized sample research. The basic characteristics of the sample are detailed in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSample distribution.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristic Variables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eType\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSample Size\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eQuestionnaire Validity Rate\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eFarmer Type\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eContract Farmers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e45%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePluriactive Farmers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.5%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSmall-scale Farmers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLarge-scale Farmers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27.5%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003ePlanting Income\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eApproximately 30,000\u0026ndash;40,000 RMB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eApproximately 60,000\u0026ndash;70,000 RMB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22.5%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eApproximately 100,000 RMB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eApproximately 200,000 Yuan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22.5%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMore\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Empirical Analysis and Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e4.1. Reliability and Validity Test\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThis study utilizes SPSS 20.0 software to analyze the reliability and validity of the scales. The reliability of the scales is assessed using Cronbach's alpha coefficient and CR value. The closer the alpha and CR values are to 1, the better the reliability. Generally, a value above 0.7 indicates good reliability of the scale. Validity represents the degree to which results approximate the intended targets. The convergent validity of the scales is typically measured using the average variance extracted (AVE) of all variables. An AVE value above 0.5 indicates good convergent validity. The discriminant validity is optimal when the AVE is higher than the correlation coefficients of other variables. The test results are shown in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eReliability and validity test.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"11\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCrobach\u0026rsquo;s α\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAVE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eEC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eLC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.886\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.891\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.803\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.896\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.811\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.921\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.854\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.276\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.924\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.870\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.901\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.819\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.325\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.252\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.905\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.879\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.895\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.741\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.202\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.189\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.861\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.745\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.949\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.903\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.051\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.375\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.278\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.259\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.950\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.840\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.898\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.815\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.417\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.108\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.173\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e-0.306\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.903\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.768\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.940\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.887\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.572\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.069\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.181\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.347\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.304\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e-0.247\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.942\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"11\"\u003eNote: Village-Enterprise Cooperation (EC); Integration of Three Industries (I); Agricultural Mechanization (M); Agricultural Digitalization (D); Agricultural Technology Extension (S); Land Circulation/Trusteeship (LC)\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e4.2. Data calibration\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eData calibration is the process of converting variables into sets and calculating membership scores. In fsQCA software, the membership relationships of each instance within the sets and the outcome membership relationships are calibrated. 1 indicates absolute membership, 0 indicates absolute non-membership, and 0.5 is the maximum ambiguity point for assessing whether an instance belongs to a set. Since the variables 'Village-Enterprise Cooperation,' 'Integration of Three Industries,' 'Agricultural Mechanization,' 'Agricultural Digitalization,' 'Agricultural Technology Extension,' and 'Pre-Production Quality and Safety Control Level' in this study were obtained through a four-point Likert scale, the original data must be transformed into values between 0 and 1 before fsQCA analysis. To calibrate the variables in each sample, this paper selects three anchor points: 4, 2.5, and 1. Consequently, the membership scores of each variable in the samples are shown in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eFuzzy set membership (partial).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSample\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEC1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eM1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eD1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eS1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eLC1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eN1\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e4.3. Single condition necessity analysis\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eFor the needs of fsQCA analysis, a necessity analysis must first be performed, where necessity refers to the explanatory power of a single conditional variable on the outcome variable. Before truth table analysis, a consistency threshold of 0.9 must be met for the conditional variable to be considered necessary. If the consistency is 1, this condition is essential, and the subset relationship between the conditional variable and the outcome variable is optimal. The analysis results are shown in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eResults of Necessary Condition Analysis.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInfluence factors\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConsistency\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCoverage\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.935353\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.870791\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eཞEC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.283002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.677489\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.817812\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.829056\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eཞI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.443038\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.876565\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.887432\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.828270\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eཞM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.337251\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.802150\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.917270\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.827150\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eཞD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.299729\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.782763\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.976490\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.790919\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eཞS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.215642\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.838313\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.555606\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.731983\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eཞLC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.684901\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.934608\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e4.4. Results\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eAfter conducting necessity analysis on individual conditional variables, this paper analyzes the sufficiency of configurations composed of different combinations of conditional variables on the outcome variable. Intermediate solutions are used to determine the number of configurations and the included conditions, and these are combined with parsimonious solutions to distinguish between core conditions and peripheral conditions. A solid circle indicates the presence of a conditional variable, a hollow circle indicates the absence of a conditional variable, a large circle represents a core condition, a small circle represents a peripheral condition, and a blank indicates that the conditional variable can be either present or absent. Standardized analysis is performed using fsQCA 4.0 software, and the configuration analysis results of the combinations of influencing factors for farmers' participation in vertical collaboration in the industrial chain are shown in Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 9.\u003c/strong\u003e Combined Pathways of Conditional Variables.\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\" width=\"694\" height=\"390\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e, the overall consistency of the configurations in this study is 0.912, indicating that the six configurations explain 0.912 of the extent to which leading agricultural enterprises guide farmers to participate in pre-production quality and safety control. The overall coverage rate is 0.941, indicating that the research results ultimately cover 94.1% of the case scenarios. The consistency of all configurations in this paper is higher than the acceptance standard of 0.8. These configurations and the willingness of farmers to participate in vertical collaboration in the industrial chain have a good subset relationship, demonstrating that the antecedent conditions have a good explanatory power for the outcome variable (pre-production quality and safety control level of agricultural products). Based on the above research, this paper has derived a total of six configurations with high levels of pre-production quality and safety control for agricultural products.\u003c/p\u003e\u003cp\u003eConfiguration N1 (ཞM*D*S*LC) indicates that a low level of agricultural mechanization, a high level of agricultural digitalization, a strong agricultural technology extension effort, and a high willingness for land trusteeship can result in high control over pre-production quality of agricultural products.\u003c/p\u003e\u003cp\u003eConfiguration N2 (~\u0026thinsp;I*D*S*LC) indicates that a low level of integration of three industries, a high level of agricultural digitalization, adequate agricultural technology extension, and a high willingness for land trusteeship can result in a high level of control over pre-production quality of agricultural products.\u003c/p\u003e\u003cp\u003eConfiguration N3 (EC*I*M*S) indicates that participation in cooperatives, a high level of integration of three industries, agricultural mechanization, and a strong agricultural technology extension effort can result in high control over pre-production quality of agricultural products.\u003c/p\u003e\u003cp\u003eConfiguration N4 (EC*I*D*S) indicates that participation in cooperatives, a high level of integration of three industries, a high degree of digitalization, and a strong agricultural technology extension effort can result in high control over pre-production quality of agricultural products. This configuration has the highest consistency index and the strongest explanatory power.\u003c/p\u003e\u003cp\u003eConfiguration N5 (EC*M*D*S) indicates that participation in cooperatives, high levels of agricultural mechanization and digitalization, and a strong agricultural technology extension effort can result in high control over pre-production quality of agricultural products.\u003c/p\u003e\u003cp\u003eConfiguration N6 (EC*M*S*LC) indicates that participation in cooperatives, a high level of agricultural mechanization, a strong agricultural technology extension effort, and a high willingness for land trusteeship can result in high control over pre-production quality of agricultural products.\u003c/p\u003e\u003cp\u003eThrough the interpretation of the above six configurations, it can be seen that all six configurations significantly affect the level of pre-production quality and safety control of agricultural products. The explanatory power ranking is: N4\u0026thinsp;\u0026gt;\u0026thinsp;N3\u0026thinsp;\u0026gt;\u0026thinsp;N5\u0026thinsp;\u0026gt;\u0026thinsp;N2\u0026thinsp;\u0026gt;\u0026thinsp;N6\u0026thinsp;\u0026gt;\u0026thinsp;N1.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e4.5. Robustness Check\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eRobustness checks are used to ensure that research findings are not accidental phenomena resulting from specific data or methodological choices. By altering certain parameters or conditions, if the results remain consistent, then these results can be considered reliable. Common robustness check methods include: adjusting calibration values, changing case frequency thresholds, varying consistency thresholds, and adding other conditions related to the outcome. This paper employs the method of changing case consistency thresholds to analyze whether the original results are robust by comparing the state of the set relationships and parameter differences before and after the change. By adjusting the case consistency threshold from 0.8 to 0.85, the generated configurations remain consistent with the original configurations, and the consistency and coverage of the solutions do not change. The robustness check shows that the configuration results are robust.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e4.6. Result Discussion\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eBased on the six configurations, three overarching configurational types can be summarized regarding how leading agricultural enterprises guide farmers to participate in pre-production quality and safety control.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eConfiguration 1: Three-Industry Integration Driven\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThis configuration includes configurations N3 and N4, characterized by the deep participation of cooperatives and the enhancement of three-industry integration levels, combined with the integrated application of agricultural mechanization, agricultural technology extension, and digital technologies. In configuration N3, the active involvement of cooperatives, high levels of three-industry integration, and the synergistic effect of agricultural mechanization and agricultural technology extension significantly enhance pre-production quality control capabilities of agricultural products. Configuration N4 further introduces higher levels of digital technology, strengthening the refined management of agricultural production, and demonstrating higher consistency indices and explanatory power in fsQCA analysis. This configuration is suitable for leading agricultural enterprises that promote industrial chain collaboration through modern agricultural production and deep industrial integration. By leading three-industry integration and modern technologies, these enterprises can stimulate farmers' willingness to participate and improve their behavioral performance in pre-production quality control. Therefore, the three-industry integration driven configuration not only helps to promote the coordinated development of agriculture, industry, and service sectors but also provides continuous momentum for high-quality agricultural production, enhancing the overall quality control level of the agricultural industrial chain by encouraging active farmer participation.\u003c/p\u003e\u003cp\u003eUnder this configuration, leading agricultural enterprises should collaborate with large-scale farmers to transfer and manage idle land to form large-scale planting, while also purchasing mechanized equipment and providing agricultural technology extension to part-time farmers and contract farmers to establish standardized production. Leading agricultural enterprises should further strengthen cooperation with cooperatives, promote the integrated development of agriculture with secondary and tertiary industries through the organized management of cooperatives, and facilitate the development of primary agricultural products towards processed agricultural products, branded products, and agricultural tourism, thereby upgrading products and increasing added value. Various types of farmers should participate in the integrated development of rural primary, secondary, and tertiary industries, forming a complete 'production-sales-tourism' industrial chain, which enhances farmers' subjective awareness of pre-production quality and safety control through industrial chain extension.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eConfiguration 2: Digital Intelligence Driven\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThis configuration encompasses configuration N5, emphasizing the core role of digital technologies and intelligent means in agricultural production, especially in the context of deep integration of agricultural mechanization and digital technologies. Configuration N5 indicates that, based on cooperative participation, the enhancement of agricultural mechanization levels, the widespread application of digital technologies, and the strengthening of agricultural technology extension jointly build an efficient pre-production quality control system. The digital intelligence driven configuration is particularly suitable for agricultural production environments with high digital technology penetration and advanced information levels. Under this configuration, relying on advanced digital and intelligent means can achieve precise monitoring and quality assurance of the entire agricultural production process, thereby promoting the transformation of agricultural production towards efficiency, greenness, and intelligence.\u003c/p\u003e\u003cp\u003eThis configuration emphasizes the leading role of agricultural enterprises in promoting and applying digital technologies to encourage farmers to actively participate in pre-production quality control, ensuring that agricultural products are produced more accurately and efficiently. The leading role of agricultural enterprises provides farmers with technical support and management tools to help them overcome the limitations of traditional production methods, thereby improving the overall quality control capabilities of the industrial chain. In this model, it is recommended that agricultural enterprises provide more comprehensive technical support to various types of farmers. For contract farmers and large-scale farmers, enterprises should use digital platforms and intelligent equipment to help farmers monitor the entire agricultural production process. Enterprises should improve information flow capabilities and socialized services such as agricultural machinery and technology for individual smallholders and part-time farmers, enhancing their initiative to participate in pre-production quality and safety control.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eConfiguration 3: Land Trusteeship Driven\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThis configuration includes configurations N1, N2, and N6, characterized by the high manifestation of land trusteeship willingness, supplemented by the support of agricultural mechanization and agricultural technology extension. The implementation of land trusteeship significantly reduces the presence of individual smallholders and promotes the increase of contract farmers, part-time farmers, and large-scale farmers, driving the intensive management model of farmers. In configurations N1 and N2, the combination of the strength of land trusteeship willingness, the level of agricultural digitalization, and effective agricultural technology extension plays a crucial role. Especially in the context of strong land trusteeship willingness, enterprises can improve farmers' willingness and ability to participate in pre-production quality control by optimizing land resource allocation and strengthening technical support. The land trusteeship model helps to reduce the dispersion among farmers, increase production scale, and thereby enhance their enthusiasm and efficiency in participating in quality control. In configuration N6, the synergistic application of land trusteeship and agricultural mechanization further enhances farmers' production capacity and quality control levels.\u003c/p\u003e\u003cp\u003eThe land trusteeship model helps farmers improve production efficiency and strengthen quality and safety control through centralized management, large-scale production, and technical support. The guidance and support of agricultural enterprises enable farmers, especially contract farmers, part-time farmers, and large-scale farmers, to better participate in the quality control process of agricultural products, thereby improving the quality and safety level of the entire industrial chain. The land trusteeship driven configuration highlights the positive role of land trusteeship in enhancing farmers' initiative to participate in pre-production quality control. This model is particularly suitable for areas where land trusteeship obligations and agricultural mechanization levels are at a medium to low stage. Agricultural enterprises should further improve land trusteeship and transfer mechanisms, optimize resource allocation, and strengthen cooperation with cooperatives. Through the organized management of cooperatives, they should promote the implementation of land trusteeship models and provide land trusteeship support for part-time farmers and individual smallholders. For contract farmers and large-scale farmers, enterprises should continuously promote the synergistic application of land trusteeship models and agricultural mechanization, improve farmers' production efficiency through advanced management systems, and strengthen quality monitoring to promote the quality improvement of the entire industrial chain.\u003c/p\u003e\u003cp\u003eThrough the summarization and analysis of the six configurations, it can be seen that under the combined effect of village-enterprise cooperation, three-industry integration, agricultural mechanization, digitalization, and agricultural technology extension, farmers show a strong willingness to participate in pre-production quality and safety control of agricultural products. These configurations not only effectively enhance the quality and safety control capabilities of agricultural product raw materials by leading agricultural enterprises but also reduce quality risks in the mid- and post-production stages, thereby improving the quality and safety control efficiency of the entire industrial chain. Furthermore, the research results indicate that the leading role of agricultural enterprises on farmers is the result of multi-factor synergy, which further verifies the complexity of the configurations and increases the credibility of problem analysis based on a configurational perspective.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThis study, focusing on leading agricultural enterprises and farmers in the Yangtze River Delta region of China, explores the configurational pathways of leading agricultural enterprises guiding farmers to participate in pre-production quality and safety control, combining grounded theory and fuzzy-set Qualitative Comparative Analysis (fsQCA). The research provides constructive suggestions for leading agricultural enterprises to guide farmers in participating in vertical collaboration within the industrial chain to a certain extent, but it still has some limitations. In the configuration analysis process, this paper selected five conditional variables\u0026mdash;village-enterprise cooperation, integration of three industries, agricultural mechanization, agricultural digitalization, and agricultural technology extension\u0026mdash;to study their configurational effects on farmers' participation in pre-production quality and safety control. Considering that enterprise quality control behaviors in grounded analysis can be further subdivided, future research could further refine the configurational effects of specific enterprise behaviors in quality control on guiding farmers' participation in pre-production quality control.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eInstitutional Review Board Statement\u003c/h2\u003e\u003cp\u003eNot applicable\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAuthor Contributions: Conceptualization, C.L. and Y.Y.; methodology, C.L., Y.Y. and W.L.; soft-ware, C.L. and Y.Y.; vali-dation, C.L. and Y.Y.; writing\u0026mdash;original draft preparation, C.L.; writ-ing\u0026mdash;review and editing, C.L. and W.L.; supervision, W.L. and Q.Y.; project administration, W.L.; funding acquisition, W.L. and Q.Y. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability Statement:\u003c/h2\u003e\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMa Juan. Opinions of the CPC Central Committee and the State Council on Effectively Promoting Rural Revitalization by Learning and Applying the Experience of the \u0026ldquo;Thousand Villages Demonstration, Ten Thousand Villages Renovation\u0026rdquo; Project. 2024, No. 6 State Council Bulletin, China Government Website. Available online: https://www.gov.cn/gongbao/2024/issue_11186/202402/content_6934551.html (accessed on 1 January 2024).\u003c/li\u003e\n\u003cli\u003eZhou, W.; Xu, L. 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Using Mixed Methods to Develop and Analyze Complex Mediation Models: A Case Study of Business Environment Promoting Innovation Vitality, Coordinating New Productive Forces, and \u0026quot;Employment Priority\u0026quot;. \u003cem\u003eManagement World\u003c/em\u003e, \u003cstrong\u003e40(6)\u003c/strong\u003e, 217\u0026ndash;237\u003cem\u003e, \u003c/em\u003e(2024).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"humanities-and-social-sciences-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"palcomms","sideBox":"Learn more about [Humanities \u0026 Social Sciences Communications](http://www.nature.com/palcomms/)","snPcode":"41599","submissionUrl":"https://submission.springernature.com/new-submission/41599/3","title":"Humanities and Social Sciences Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Agricultural leading enterprises, farmers, agricultural product quality, grounded theory, qualitative comparative analysis","lastPublishedDoi":"10.21203/rs.3.rs-6536489/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6536489/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe leadership of agricultural enterprises in guiding farmers to participate in pre-production quality and safety control not only helps promote high-quality agricultural development and drives the industrialization process of agriculture, but also provides important support for achieving the goal of building a strong agricultural nation. This paper focuses on agricultural leading enterprises and farmers in the Yangtze River Delta region of China. The study does not limit itself to exploring the independent influence of enterprise-led actions in guiding farmers' participation in pre-production quality and safety control, but rather investigates how multiple factors work together to lead farmers' participation under various interacting elements. The research employs a grounded theory approach to conduct a multi-case study, following the general logic of \" Motivations-Behaviors-Outcomes.\" Relevant data from case companies were extracted, analyzed, and coded to construct a theoretical interpretation, revealing the intrinsic mechanisms of agricultural leading enterprises in pre-production quality and safety control and identifying key influencing factors. Additionally, using fuzzy-set qualitative comparative analysis (fsQCA), the study explores how five enterprise control behaviors\u0026mdash;village-enterprise cooperation, integration of primary, secondary, and tertiary industries, agricultural mechanization, agricultural digitalization, and agricultural technology promotion\u0026mdash;collaborate to guide farmers\u0026rsquo; involvement in pre-production quality and safety control from a configurational perspective. The results indicate that agricultural leading enterprises guide farmers\u0026rsquo; participation in pre-production quality and safety control through organizational linkage mechanisms and new quality productive forces elements linkage mechanism, and based on this, six configurational paths are summarized, leading to the identification of three constructs: Industry Integration-driven, Digital Intelligence-driven, and Land Trusteeship-driven.\u003c/p\u003e","manuscriptTitle":"Research on Leading Agricultural Enterprises Guiding Farmers' Participation in Pre-Production Quality and Safety Control: Evidence from the Yangtze River Delta Region of China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-15 12:48:01","doi":"10.21203/rs.3.rs-6536489/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-07T17:12:30+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-01T08:22:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"84930331119094029589265021538465898350","date":"2025-08-31T14:09:34+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-15T13:03:39+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-08T07:31:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"222969126432285844308768309164288902470","date":"2025-07-16T13:20:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"322989607818035792662988224356121411504","date":"2025-07-14T01:12:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"257327361551109578830811574316606199281","date":"2025-07-13T09:55:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"324167109008683595687934253827304626235","date":"2025-07-11T03:24:14+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-11T00:48:44+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-05-21T07:30:13+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-21T07:29:33+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-21T07:28:20+00:00","index":"","fulltext":""},{"type":"submitted","content":"Humanities and Social Sciences Communications","date":"2025-04-26T17:55:05+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"humanities-and-social-sciences-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"palcomms","sideBox":"Learn more about [Humanities \u0026 Social Sciences Communications](http://www.nature.com/palcomms/)","snPcode":"41599","submissionUrl":"https://submission.springernature.com/new-submission/41599/3","title":"Humanities and Social Sciences Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"4b926723-eddb-474a-8ba0-dd39e42bd6c5","owner":[],"postedDate":"July 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[{"id":51461388,"name":"Business and commerce/Business and management"},{"id":51461389,"name":"Social science/Business and management"},{"id":51461390,"name":"Social science/Economics"},{"id":51461391,"name":"Social science/Environmental studies"}],"tags":[],"updatedAt":"2025-12-07T17:23:17+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-15 12:48:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6536489","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6536489","identity":"rs-6536489","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}