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Understanding farmers’ intentions to participate in traceability systems: evidence from SEM-ANN-NCA
Understanding farmers’ intentions to participate in traceability systems: evidence from SEM-ANN-NCA
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Understanding farmers’ intentions to participate in traceability systems: evidence from SEM-ANN-NCA
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Understanding farmers’ intentions to participate in traceability systems: evidence from SEM-ANN-NCA
Understanding farmers’ intentions to participate in traceability systems: evidence from SEM-ANN-NCA

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Understanding farmers’ intentions to participate in traceability systems: evidence from SEM-ANN-NCA
Understanding farmers’ intentions to participate in traceability systems: evidence from SEM-ANN-NCA
Journal Article

Understanding farmers’ intentions to participate in traceability systems: evidence from SEM-ANN-NCA

2023
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Overview
IntroductionAs 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.MethodsThis 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).ResultsThe 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.DiscussionThese 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.