{"title":"中国智慧农业规模测算与经济效益评价","authors":"Shaohua Zhang , Rentao Chen , Jian Wu , Ning Zhu","doi":"10.1016/j.seps.2025.102195","DOIUrl":null,"url":null,"abstract":"<div><div>In this paper, input‒output analysis is applied to assess the value-added scale of smart agriculture, with an emphasis on industrial linkages and final demand. The results reveal that smart agriculture constitutes 5.58 % of the agricultural sector and only 0.47 % of GDP in China. Although the value-added contribution of smart agriculture remains modest in comparison with that of traditional agriculture, it demonstrates strong integration with digital industrialization sectors and low dependency on inputs or demand growth from other industries. In terms of final demand, sensitivity analysis shows that smart agriculture is a consumption-dependent industry; however, the promotion of smart agriculture associated with various final demands remains limited, with the expansion of final demand predominantly benefiting traditional agriculture. The transformation of the industrial structure has been a key driver of the growth of smart agriculture since 2012. Between 2012 and 2020, changes in the structure of intermediate goods and final demand collectively contributed to a 44.9 % increase in the scale of smart agriculture.</div></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":"99 ","pages":"Article 102195"},"PeriodicalIF":5.4000,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Scale measurement and economic effect evaluation of smart agriculture in China\",\"authors\":\"Shaohua Zhang , Rentao Chen , Jian Wu , Ning Zhu\",\"doi\":\"10.1016/j.seps.2025.102195\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>In this paper, input‒output analysis is applied to assess the value-added scale of smart agriculture, with an emphasis on industrial linkages and final demand. The results reveal that smart agriculture constitutes 5.58 % of the agricultural sector and only 0.47 % of GDP in China. Although the value-added contribution of smart agriculture remains modest in comparison with that of traditional agriculture, it demonstrates strong integration with digital industrialization sectors and low dependency on inputs or demand growth from other industries. In terms of final demand, sensitivity analysis shows that smart agriculture is a consumption-dependent industry; however, the promotion of smart agriculture associated with various final demands remains limited, with the expansion of final demand predominantly benefiting traditional agriculture. The transformation of the industrial structure has been a key driver of the growth of smart agriculture since 2012. Between 2012 and 2020, changes in the structure of intermediate goods and final demand collectively contributed to a 44.9 % increase in the scale of smart agriculture.</div></div>\",\"PeriodicalId\":22033,\"journal\":{\"name\":\"Socio-economic Planning Sciences\",\"volume\":\"99 \",\"pages\":\"Article 102195\"},\"PeriodicalIF\":5.4000,\"publicationDate\":\"2025-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Socio-economic Planning Sciences\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0038012125000448\",\"RegionNum\":2,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/3/1 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Socio-economic Planning Sciences","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0038012125000448","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/3/1 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
Scale measurement and economic effect evaluation of smart agriculture in China
In this paper, input‒output analysis is applied to assess the value-added scale of smart agriculture, with an emphasis on industrial linkages and final demand. The results reveal that smart agriculture constitutes 5.58 % of the agricultural sector and only 0.47 % of GDP in China. Although the value-added contribution of smart agriculture remains modest in comparison with that of traditional agriculture, it demonstrates strong integration with digital industrialization sectors and low dependency on inputs or demand growth from other industries. In terms of final demand, sensitivity analysis shows that smart agriculture is a consumption-dependent industry; however, the promotion of smart agriculture associated with various final demands remains limited, with the expansion of final demand predominantly benefiting traditional agriculture. The transformation of the industrial structure has been a key driver of the growth of smart agriculture since 2012. Between 2012 and 2020, changes in the structure of intermediate goods and final demand collectively contributed to a 44.9 % increase in the scale of smart agriculture.
期刊介绍:
Studies directed toward the more effective utilization of existing resources, e.g. mathematical programming models of health care delivery systems with relevance to more effective program design; systems analysis of fire outbreaks and its relevance to the location of fire stations; statistical analysis of the efficiency of a developing country economy or industry.
Studies relating to the interaction of various segments of society and technology, e.g. the effects of government health policies on the utilization and design of hospital facilities; the relationship between housing density and the demands on public transportation or other service facilities: patterns and implications of urban development and air or water pollution.
Studies devoted to the anticipations of and response to future needs for social, health and other human services, e.g. the relationship between industrial growth and the development of educational resources in affected areas; investigation of future demands for material and child health resources in a developing country; design of effective recycling in an urban setting.