{"title":"农民采用绿色技术:来自政府补贴和信息共享的影响","authors":"Xianpei Hong, Ying‐Ju Chen, Yeming Gong, Hua Wang","doi":"10.1002/nav.22150","DOIUrl":null,"url":null,"abstract":"Abstract While the previous literature on green technology adoption has not fully considered information sharing, we consider the impact of demand information sharing on the adoption of green technologies by risk‐averse farmers in a vertical agricultural supply chain. We find that government subsidies and information sharing do not always promote farmers' adoption of green technologies. The accuracy of the information plays a vital role in promoting farmers' adoption of green technologies; however, the increased green technology adoption induced by more accurate information may be detrimental to farmer welfare in the presence of production diseconomies. Information sharing can reduce the amount of government subsidies for promoting green technology adoption, thereby suggesting the substitutable role of information and monetary instruments. Nonetheless, information‐sharing may lead to lower water savings and thus should be adopted with caution. Risk aversion has a nontrivial impact on agricultural technology adoption: farmers are more likely to adopt traditional agricultural technologies when their risk aversion is either very low or very high. Finally, we validate our decision model with U.S. Department of Agriculture cotton production data and propose management insights to help farmers make appropriate adoption decisions under information asymmetry and risk‐averse attitudes.","PeriodicalId":49772,"journal":{"name":"Naval Research Logistics","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Farmers' green technology adoption: Implications from government subsidies and information sharing\",\"authors\":\"Xianpei Hong, Ying‐Ju Chen, Yeming Gong, Hua Wang\",\"doi\":\"10.1002/nav.22150\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract While the previous literature on green technology adoption has not fully considered information sharing, we consider the impact of demand information sharing on the adoption of green technologies by risk‐averse farmers in a vertical agricultural supply chain. We find that government subsidies and information sharing do not always promote farmers' adoption of green technologies. The accuracy of the information plays a vital role in promoting farmers' adoption of green technologies; however, the increased green technology adoption induced by more accurate information may be detrimental to farmer welfare in the presence of production diseconomies. Information sharing can reduce the amount of government subsidies for promoting green technology adoption, thereby suggesting the substitutable role of information and monetary instruments. Nonetheless, information‐sharing may lead to lower water savings and thus should be adopted with caution. Risk aversion has a nontrivial impact on agricultural technology adoption: farmers are more likely to adopt traditional agricultural technologies when their risk aversion is either very low or very high. Finally, we validate our decision model with U.S. Department of Agriculture cotton production data and propose management insights to help farmers make appropriate adoption decisions under information asymmetry and risk‐averse attitudes.\",\"PeriodicalId\":49772,\"journal\":{\"name\":\"Naval Research Logistics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2023-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Naval Research Logistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1002/nav.22150\",\"RegionNum\":4,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"OPERATIONS RESEARCH & MANAGEMENT SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Naval Research Logistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/nav.22150","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
Farmers' green technology adoption: Implications from government subsidies and information sharing
Abstract While the previous literature on green technology adoption has not fully considered information sharing, we consider the impact of demand information sharing on the adoption of green technologies by risk‐averse farmers in a vertical agricultural supply chain. We find that government subsidies and information sharing do not always promote farmers' adoption of green technologies. The accuracy of the information plays a vital role in promoting farmers' adoption of green technologies; however, the increased green technology adoption induced by more accurate information may be detrimental to farmer welfare in the presence of production diseconomies. Information sharing can reduce the amount of government subsidies for promoting green technology adoption, thereby suggesting the substitutable role of information and monetary instruments. Nonetheless, information‐sharing may lead to lower water savings and thus should be adopted with caution. Risk aversion has a nontrivial impact on agricultural technology adoption: farmers are more likely to adopt traditional agricultural technologies when their risk aversion is either very low or very high. Finally, we validate our decision model with U.S. Department of Agriculture cotton production data and propose management insights to help farmers make appropriate adoption decisions under information asymmetry and risk‐averse attitudes.
期刊介绍:
Submissions that are most appropriate for NRL are papers addressing modeling and analysis of problems motivated by real-world applications; major methodological advances in operations research and applied statistics; and expository or survey pieces of lasting value. Areas represented include (but are not limited to) probability, statistics, simulation, optimization, game theory, quality, scheduling, reliability, maintenance, supply chain, decision analysis, and combat models. Special issues devoted to a single topic are published occasionally, and proposals for special issues are welcomed by the Editorial Board.