Tseng Yafen, Lee Beyfen, Chen Chingi, He Wang
Digital Design and Information Management, Chung Hwa University of Medical Technology, Tainan 71703, Taiwan.
Department of Hospitality Management, Chung Hwa University of Medical Technology, Tainan 71703, Taiwan.
Int J Environ Res Public Health. 2022 Jan 26;19(3):1371. doi: 10.3390/ijerph19031371.
Scientists believed the outbreak of COVID-19 could be linked to the consumption of wild animals, so food safety and hygiene have become the top concerns of the public. An agri-food traceability system becomes very important in this context because it can help the government to trace back the entire production and delivery process in case of food safety concerns. The traceability system is a complicated digitalized system because it integrates information and logistics systems. Previous studies used the technology acceptance model (TAM), information systems (IS) success model, expectation confirmation model (ECM), or extended model to explain the continuance intention of traceability system users. Very little literature can be found integrating two different models to explain user intention, not to mention comparing three models in one research context. This study proposed the technology acceptance model (TAM), technology acceptance model-information systems (TAM-IS) success, and technology acceptance model-expectation confirmation model (TAM-ECM) integrated models to evaluate the most appropriate model to explain agri-food traceability system during the COVID-19 pandemic. A questionnaire was designed based on a literature review, and 197 agri-food traceability system users were sampled. The collected data were analyzed by partial least square (PLS) to understand the explanatory power and the differences between the three models. The results showed that: (1) the TAM model has a fair explanatory power of continuance intention (62.2%), but was recommended for its' simplicity; (2) the TAM-IS success integrated model had the best predictive power of 78.3%; and (3) the system providers should raise users' confirmation level, so their continuance intention could be reinforced through mediators, perceived value, and satisfaction. The above findings help to understand agri-food traceability system user intention, and provide theoretical and practical implications for system providers to refine their system design.
科学家们认为，新冠疫情的爆发可能与食用野生动物有关，因此食品安全和卫生已成为公众最关心的问题。在这种背景下，农业食品可追溯系统变得非常重要，因为在出现食品安全问题时，它可以帮助政府追溯整个生产和配送过程。可追溯系统是一个复杂的数字化系统，因为它整合了信息和物流系统。以往的研究使用技术接受模型（TAM）、信息系统（IS）成功模型、期望确认模型（ECM）或扩展模型来解释可追溯系统用户的持续使用意愿。很少有文献将两种不同的模型整合起来解释用户意愿，更不用说在一个研究背景下比较三种模型了。本研究提出了技术接受模型（TAM）、技术接受模型-信息系统（TAM-IS）成功模型和技术接受模型-期望确认模型（TAM-ECM）整合模型，以评估在新冠疫情期间解释农业食品可追溯系统最合适的模型。基于文献综述设计了一份问卷，并对197名农业食品可追溯系统用户进行了抽样调查。通过偏最小二乘法（PLS）对收集到的数据进行分析，以了解三种模型的解释力和差异。结果表明：（1）TAM模型对持续使用意愿有一定的解释力（62.2%），但因其简单性而被推荐；（2）TAM-IS成功整合模型具有最佳的预测能力，为78.3%；（3）系统供应商应提高用户的确认水平，以便通过中介变量、感知价值和满意度来增强他们的持续使用意愿。上述研究结果有助于理解农业食品可追溯系统用户的意愿，并为系统供应商优化其系统设计提供理论和实践意义。
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