亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

What drives people to accept automated vehicles? Findings from a field experiment

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 哲学 古生物学 会计 认识论 法学 纯数学 生物 沟通
作者
Zhigang Xu,Kaifan Zhang,Haigen Min,Zhen Wang,Xiangmo Zhao,Peng Liu
出处
期刊:Transportation Research Part C-emerging Technologies [Elsevier]
卷期号:95: 320-334 被引量:426
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.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
5秒前
飞快的孱发布了新的文献求助10
6秒前
8秒前
黑摄会阿Fay完成签到,获得积分10
8秒前
GingerF应助Ken采纳,获得50
9秒前
呆萌初南完成签到 ,获得积分10
11秒前
14秒前
小二郎应助Aleksibob采纳,获得30
15秒前
马嘉祺超绝鸡肉线完成签到,获得积分10
15秒前
17秒前
GavinYi完成签到,获得积分10
18秒前
小马甲应助琪琪采纳,获得10
19秒前
luyajie发布了新的文献求助10
20秒前
20秒前
21秒前
舒心谷雪完成签到 ,获得积分10
23秒前
小二郎应助刺猬采纳,获得10
23秒前
24秒前
Aleksibob完成签到,获得积分10
25秒前
SciGPT应助丰富的松鼠采纳,获得10
28秒前
喜悦宫苴完成签到,获得积分10
29秒前
29秒前
31秒前
乐乐应助Tracy采纳,获得10
34秒前
酷波er应助科研通管家采纳,获得10
35秒前
英姑应助渡己。采纳,获得10
35秒前
烟花应助科研通管家采纳,获得50
35秒前
JamesPei应助科研通管家采纳,获得10
35秒前
归尘应助科研通管家采纳,获得10
35秒前
赘婿应助科研通管家采纳,获得10
35秒前
香蕉觅云应助科研通管家采纳,获得10
35秒前
归尘应助科研通管家采纳,获得10
35秒前
研友_VZG7GZ应助科研通管家采纳,获得10
35秒前
田様应助科研通管家采纳,获得10
35秒前
我是老大应助科研通管家采纳,获得10
35秒前
Hello应助科研通管家采纳,获得10
35秒前
月子淇应助科研通管家采纳,获得10
35秒前
mingjing完成签到 ,获得积分10
37秒前
Chenzr完成签到,获得积分10
38秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Iron toxicity and hematopoietic cell transplantation: do we understand why iron affects transplant outcome? 2000
Teacher Wellbeing: Noticing, Nurturing, Sustaining, and Flourishing in Schools 1200
List of 1,091 Public Pension Profiles by Region 1041
睡眠呼吸障碍治疗学 600
A Technologist’s Guide to Performing Sleep Studies 500
EEG in Childhood Epilepsy: Initial Presentation & Long-Term Follow-Up 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5488365
求助须知:如何正确求助?哪些是违规求助? 4587236
关于积分的说明 14413292
捐赠科研通 4518528
什么是DOI,文献DOI怎么找? 2475911
邀请新用户注册赠送积分活动 1461433
关于科研通互助平台的介绍 1434314