[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-450470-105":59,"doc-detail-450470-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","driving-agricultural-strength-through-digital-transformation","Driving agricultural strength through digital transformation","","The study systematically examines how agricultural digital transformation influences the development of a strong agricultural country. It builds a multidimensional evaluation framework across digital infrastructure, technology applications, service platforms, talent cultivation, and policy environment. Using entropy to measure digitization across Chinese provinces from 2014 to 2023, it applies CRS to assess fluctuations in overall agricultural productivity, then analyzes spatiotemporal evolution via kernel density estimation, Markov chains, and σ convergence. Results show sustained digitization growth across regions and significant positive effects on agricultural total factor productivity, with impacts also operating through efficiency and innovation pathways.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/driving-agricultural-strength-through-digital-transformation/450470/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/driving-agricultural-strength-through-digital-transformation/450470.png","ImageObject",300,407,{"name":92,"@type":93},"Kyle","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-06","2026-09-30",true,{"@type":102,"interactionType":103,"userInteractionCount":14},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What evaluation system does the study use to measure agricultural digitization?","Question",{"text":112,"@type":113},"It constructs a comprehensive indicator framework with five dimensions: digital infrastructure, technology applications, service platforms, talent cultivation, and policy environment.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How does the paper measure agricultural digitization and agricultural productivity over time?",{"text":117,"@type":113},"Agricultural digitization is measured with the entropy method across Chinese provinces from 2014 to 2023, while agricultural overall productivity fluctuations are evaluated using Constant Returns to Scale (CRS).",{"name":119,"@type":110,"acceptedAnswer":120},"What do the findings indicate about the relationship between digitization and agricultural productivity?",{"text":121,"@type":113},"Total factor productivity increases from 1.031 in 2014 to 1.089 in 2023, and regression results show agricultural digitization has a significant positive driving coefficient of 2.789 at the 1% level.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},450470,1791294369,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":14,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145},3985741905716,"https://ap-avatar.wpscdn.com/davatar_994ba38a5ba835b3df7d355c54d3ed8d","[www. nature.com/scientificreports](www. nature.com/scientificreports)  \nOPEN  \nDriving agricultural strength through digital transformation  \nJijie Dong1􀀍 & Jianguo Xu2  \nThe research aims to systematically explore the core issue of how agricultural digital transformation affects the level of building a strong agricultural country. To this end, the study first constructsa comprehensive evaluation system covering five dimensions: digital infrastructure, technology applications, service platforms, talent cultivation, and policy environment. The entropy method is used to measure the level of agricultural digitization in various provinces of China from 2014 to  \n2023. Meanwhile, the Constant Returns to Scale (CRS) is used to evaluate the fluctuations in overall agricultural productivity in various regions over the past decade, thereby measuring progress in building a strong agricultural country. Finally, the spatiotemporal evolution characteristics are analyzed using kernel density estimation, Markov chain, and σ convergence models. The findings demonstrate that from 2014 to 2023, the degree of agricultural digitization in China’s eastern, central, and western regions exhibits a sustained growth trend. The level of agricultural digitization development is highest in the east, followed by the central region, and while the starting point is lower in the west, it also experiences annual increases. The total factor productivity of agriculture increases from 1.031 in 2014 to 1.089 in 2023, indicating a significant enhancement in China’s agricultural production efficiency, which is generally higher in eastern provinces, albeit with variations. The regression coefficient of the core variable calculated through multiple linear regression analysis shows that the coefficient of agricultural digitization is 2.789 and significant at the 1% level. This coefficient indicates that for every 1 unit increase in the level of agricultural digital development index, the total factor productivity index of agriculture will significantly increase by 2.789 units. This indicates that after controlling for individual fixed effects, agricultural digitization has shown a strong driving effect on the level of building an agricultural powerhouse. Moreover, the impact exceeds core mediating variables such as agricultural production efficiency and agricultural technological innovation capability. Consequently, to further promote the development of a strong agricultural sector, the digital advancement of agriculture should be encouraged from multiple dimensions. The main contribution of the research is the construction of a systematic framework for measuring agricultural digitization, and the revelation of its internal mechanism of driving the construction of an agricultural powerhouse through multiple paths, providing a theoretical basis for precise policy formulation. Future research directions include constructing comprehensive evaluation indicators for agricultural power that cover multiple dimensions such as economy, society, and ecology, deepening mechanism research through micro surveys and big data technology, and exploring more effective instrumental variables to address endogeneity challenges.  \nKeywords Digitization of agriculture, Agricultural powerhouse, Indicator system, Entropy method, Total factor productivity, Intermediary pathways, Regional differences  \nWith the rapid development of information technology, digitization has become a new driving force for global economic expansion1. In this context, digitization has not only become a new engine for global economic expansion, but also a core driving force for promoting the upgrading and modernization of various industries2. Asa fundamental industry of the national economy, the digital transformation of agriculture is related to the overall strategy of food security, sustainable development, and rural revitalization. It is an inevitable choice to achieve agricultural modernization and build a “str","cbCailFufh71sXrg","https://ap.wps.com/l/cbCailFufh71sXrg","pdf",4978238,21,"English","# Introduction\n## Research background and significance\n# Methodology\n## Evaluation system for agricultural digitization\n## Measurement of digitization and productivity\n## Spatiotemporal evolution models\n# Results\n## Regional trends in digitization (2014-2023)\n## Effects on total factor productivity\n## Mechanism and intermediary pathways\n# Conclusions and Implications\n## Policy-oriented multi-dimensional promotion\n# Future Directions\n## Expanded indicators and deeper mechanism research","[{\"question\":\"What evaluation system does the study use to measure agricultural digitization?\",\"answer\":\"It constructs a comprehensive indicator framework with five dimensions: digital infrastructure, technology applications, service platforms, talent cultivation, and policy environment.\"},{\"question\":\"How does the paper measure agricultural digitization and agricultural productivity over time?\",\"answer\":\"Agricultural digitization is measured with the entropy method across Chinese provinces from 2014 to 2023, while agricultural overall productivity fluctuations are evaluated using Constant Returns to Scale (CRS).\"},{\"question\":\"What do the findings indicate about the relationship between digitization and agricultural productivity?\",\"answer\":\"Total factor productivity increases from 1.031 in 2014 to 1.089 in 2023, and regression results show agricultural digitization has a significant positive driving coefficient of 2.789 at the 1% level.\"}]","Driving agricultural strength through digital transformation | PDF",1790733273,53]