背景(考古学)
预测能力
调解
差异(会计)
情感(语言学)
解释力
一致性(知识库)
社会心理学
结构方程建模
计算机科学
应用心理学
技术接受模型
可用性
心理学
领域(数学)
人机交互
业务
统计
政治学
数学
人工智能
纯数学
古生物学
哲学
会计
沟通
认识论
法学
生物
作者
Zhigang Xu,Kaifan Zhang,Haigen Min,Zhen Wang,Xiangmo Zhao,Peng Liu
标识
DOI:10.1016/j.trc.2018.07.024
摘要
This field study aims at understanding the influence of direct experience of an automated vehicle (AV, Level 3) and explaining and predicting public acceptance of AVs through a psychological model. The model includes behavioral intention (BI) to use self-driving vehicles (SDVs, Level 5), willingness to re-ride (WTR) in our AV (Level 3), and their four potential determinants, namely perceived usefulness (PU), perceived ease of use (PEU), trust related to SDVs, and perceived safety (PS) while riding in our AV. The last two determinants are largely ignored, but we consider them critical in the context of AVs. Three-hundred students were invited as participants (passengers) to experience the AV. The trust, PU, PEU, and BI of the participants were recorded prior to their experiencing the AV; after this experience, all the constructs of the psychological model were recorded. The participants’ experience with the AV was found to increase their trust, PU and PEU (but not BI), the consistency between PU/PEU and BI, and the explanatory power of BI. The model explained 55% of the variance in BI and 40% in WTR. PU, trust, and PS were found to be steady and direct predictors of both the acceptance measures; PEU predicted BI only after the participants’ AV experience. Mediation analysis showed that trust also can indirectly affect AV acceptance through other determinants. Out-of-sample prediction confirmed the model’s predictive capability for AV acceptance. The theoretical contributions and practical implications of the findings are discussed.
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