{"title":"了解农民参与可追溯系统的意愿:来自 SEM-ANN-NCA 的证据","authors":"Yatao Huang, Shaoling Fu","doi":"10.3389/fsufs.2023.1246122","DOIUrl":null,"url":null,"abstract":"As a crucial technological tool for ensuring the quality and safety of agricultural products, the traceability system is of great importance in the agricultural sector. However, farmers’ participation in the system, especially among small-scale farmers, remains relatively low.This study investigates the factors that influence farmers’ intentions to participate in traceability systems by integrating moral norms and policy support into the technology acceptance model (TAM) and using a three-stage approach of structural equation modeling (SEM), artificial neural network (ANN), and necessary condition analysis (NCA).The findings indicated that farmers’ intentions were primarily influenced by perceived usefulness. Perceived usefulness and perceived ease of use were strongly affected by moral norms and policy support. To promote farmers’ intentions, it is necessary to achieve at least 75, 66.7, 45.5, and 50% of perceived usefulness, perceived ease of use, moral norms, and policy support, respectively.These findings provide valuable guidance to government agencies and technology developers in prioritizing adoption strategies. This study not only expands the scope of TAM research, but also represents an early application of a three-stage approach to agricultural technology adoption research.","PeriodicalId":36666,"journal":{"name":"Frontiers in Sustainable Food Systems","volume":" 12","pages":""},"PeriodicalIF":3.7000,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Understanding farmers’ intentions to participate in traceability systems: evidence from SEM-ANN-NCA\",\"authors\":\"Yatao Huang, Shaoling Fu\",\"doi\":\"10.3389/fsufs.2023.1246122\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As a crucial technological tool for ensuring the quality and safety of agricultural products, the traceability system is of great importance in the agricultural sector. However, farmers’ participation in the system, especially among small-scale farmers, remains relatively low.This study investigates the factors that influence farmers’ intentions to participate in traceability systems by integrating moral norms and policy support into the technology acceptance model (TAM) and using a three-stage approach of structural equation modeling (SEM), artificial neural network (ANN), and necessary condition analysis (NCA).The findings indicated that farmers’ intentions were primarily influenced by perceived usefulness. Perceived usefulness and perceived ease of use were strongly affected by moral norms and policy support. To promote farmers’ intentions, it is necessary to achieve at least 75, 66.7, 45.5, and 50% of perceived usefulness, perceived ease of use, moral norms, and policy support, respectively.These findings provide valuable guidance to government agencies and technology developers in prioritizing adoption strategies. This study not only expands the scope of TAM research, but also represents an early application of a three-stage approach to agricultural technology adoption research.\",\"PeriodicalId\":36666,\"journal\":{\"name\":\"Frontiers in Sustainable Food Systems\",\"volume\":\" 12\",\"pages\":\"\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2023-12-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Frontiers in Sustainable Food Systems\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://doi.org/10.3389/fsufs.2023.1246122\",\"RegionNum\":2,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"FOOD SCIENCE & TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Sustainable Food Systems","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.3389/fsufs.2023.1246122","RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"FOOD SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
摘要
作为确保农产品质量安全的重要技术手段,可追溯系统在农业领域具有重要意义。本研究通过将道德规范和政策支持纳入技术接受模型(TAM),采用结构方程建模(SEM)、人工神经网络(ANN)和必要条件分析(NCA)三阶段方法,研究了影响农民参与可追溯系统意向的因素。结果表明,农民的意向主要受感知有用性的影响,感知有用性和感知易用性受道德规范和政策支持的影响较大。要促进农民的意向,感知有用性、感知易用性、道德规范和政策支持必须分别达到至少 75%、66.7%、45.5% 和 50%。这项研究不仅拓展了 TAM 研究的范围,而且也是农业技术采用研究三阶段方法的早期应用。
Understanding farmers’ intentions to participate in traceability systems: evidence from SEM-ANN-NCA
As a crucial technological tool for ensuring the quality and safety of agricultural products, the traceability system is of great importance in the agricultural sector. However, farmers’ participation in the system, especially among small-scale farmers, remains relatively low.This study investigates the factors that influence farmers’ intentions to participate in traceability systems by integrating moral norms and policy support into the technology acceptance model (TAM) and using a three-stage approach of structural equation modeling (SEM), artificial neural network (ANN), and necessary condition analysis (NCA).The findings indicated that farmers’ intentions were primarily influenced by perceived usefulness. Perceived usefulness and perceived ease of use were strongly affected by moral norms and policy support. To promote farmers’ intentions, it is necessary to achieve at least 75, 66.7, 45.5, and 50% of perceived usefulness, perceived ease of use, moral norms, and policy support, respectively.These findings provide valuable guidance to government agencies and technology developers in prioritizing adoption strategies. This study not only expands the scope of TAM research, but also represents an early application of a three-stage approach to agricultural technology adoption research.