技术接受模型
大流行
结构方程建模
背景(考古学)
可用性
风险感知
基站
眼动
独创性
2019年冠状病毒病(COVID-19)
心理学
应用心理学
计算机科学
社会心理学
地理
电信
人工智能
人机交互
医学
机器学习
传染病(医学专业)
疾病
考古
病理
神经科学
创造力
感知
作者
Hanliang Fu,Hong Zhu,Pengdong Xue,Xi Hu,Xiaotong Guo,Bingsheng Liu
标识
DOI:10.1108/ecam-10-2021-0946
摘要
Purpose This study applied eye-tracking techniques and questionnaires within the framework of the Stimulus-Organism-Response Model (SOR) and Technology Acceptance Model (TAM), to investigate the influencing factors of the public acceptance of 5G base stations. Design/methodology/approach This study used a combination of eye-tracking experiments and questionnaires. The data were analyzed using partial least squares structural equation modeling (PLS-SEM). Findings (1) The Technology Acceptance Model (TAM) could be used to explain the effects on public acceptance of 5G base stations in the context of the COVID-19 pandemic. The public's perceived usefulness and ease of use of 5G base stations positively affects public acceptance of 5G base stations. (2) The public's perceived risk of 5G base stations has a negative influence on the public acceptance of 5G base stations. (3) The public's visual attention to the different valence information about 5G base stations positively impacts the perceived ease of use while having negative impacts on perceived risk. (4) Visual attention to various valence information of 5G base stations can indirectly influence public acceptance through the perceived risk. Originality/value Applying the SOR and TAM to data obtained from eye-tracking experiments and questionnaires, this study analyzed the factors and mechanisms influencing public acceptance of 5G base stations in the context of the COVID-19 pandemic.
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