The roles of initial trust and perceived risk in public’s acceptance of automated vehicles

[1]  J. Krems,et al.  The first impression counts – A combined driving simulator and test track study on the development of trust and acceptance of highly automated driving , 2019, Transportation Research Part F: Traffic Psychology and Behaviour.

[2]  Zhigang Xu,et al.  Public Acceptance of Fully Automated Driving: Effects of Social Trust and Risk/Benefit Perceptions , 2018, Risk analysis : an official publication of the Society for Risk Analysis.

[3]  Xingda Qu,et al.  Factors Affecting Consumer Acceptance of an Online Health Information Portal Among Young Internet Users , 2018, Computers, informatics, nursing : CIN.

[4]  George Dimitrakopoulos,et al.  An empirical investigation on consumers’ intentions towards autonomous driving , 2018, Transportation Research Part C: Emerging Technologies.

[5]  Zhen Wang,et al.  What drives people to accept automated vehicles? Findings from a field experiment , 2018, Transportation Research Part C: Emerging Technologies.

[6]  Sabyasachee Mishra,et al.  Predicting the adoption of connected autonomous vehicles: A new approach based on the theory of diffusion of innovations , 2018, Transportation Research Part C: Emerging Technologies.

[7]  Ali Shamshiripour,et al.  Eliciting preferences for adoption of fully automated vehicles using best-worst analysis , 2018, Transportation Research Part C: Emerging Technologies.

[8]  A. Pradhan,et al.  Psychosocial factors associated with intended use of automated vehicles: A simulated driving study. , 2018, Accident; analysis and prevention.

[9]  Sarah Sharples,et al.  Understanding Is Key: An Analysis of Factors Pertaining to Trust in a Real-World Automation System , 2018, Hum. Factors.

[10]  Kanwaldeep Kaur,et al.  Trust in driverless cars: Investigating key factors influencing the adoption of driverless cars , 2018 .

[11]  William J. Horrey,et al.  Automated driving: Safety blind spots , 2018 .

[12]  Moritz Körber,et al.  Introduction matters: Manipulating trust in automation and reliance in automated driving. , 2018, Applied ergonomics.

[13]  Jing Feng,et al.  Age differences in the takeover of vehicle control and engagement in non-driving-related activities in simulated driving with conditional automation. , 2017, Accident; analysis and prevention.

[14]  M. R. A. Hamid,et al.  Discriminant Validity Assessment: Use of Fornell & Larcker criterion versus HTMT Criterion , 2017 .

[15]  Jian Mou,et al.  Trust and Risk in Consumer Acceptance of e-Services: A Meta-Analysis and a Test of Competing Models , 2013, ICIS.

[16]  R. Peterson,et al.  A Meta-analysis of Online Trust Relationships in E-commerce , 2017 .

[17]  Josef F. Krems,et al.  Prior Familiarization With Takeover Requests Affects Drivers’ Takeover Performance and Automation Trust , 2017, Hum. Factors.

[18]  William Payre,et al.  Impact of training and in-vehicle task performance on manual control recovery in an automated car , 2017 .

[19]  Andreas Butz,et al.  SupportingTrust in Autonomous Driving , 2017, IUI.

[20]  Rathindra Sarathy,et al.  An experimental investigation of the influence of website emotional design features on trust in unfamiliar online vendors , 2017, Comput. Hum. Behav..

[21]  David E. Smith,et al.  Shaping Trust Through Transparent Design: Theoretical and Experimental Guidelines , 2017 .

[22]  Isabell M. Welpe,et al.  How and why do men and women differ in their willingness to use automated cars? The influence of emotions across different age groups , 2016 .

[23]  M. Nees Acceptance of Self-driving Cars , 2016 .

[24]  Kara M. Kockelman,et al.  Assessing Public Opinions of and Interest in New Vehicle Technologies: An Austin Perspective , 2016 .

[25]  Josef F. Krems,et al.  Keep Your Scanners Peeled , 2016, Hum. Factors.

[26]  Riender Happee,et al.  Conceptual Model to Explain, Predict, and Improve User Acceptance of Driverless Podlike Vehicles , 2016 .

[27]  Yogesh Kumar Dwivedi,et al.  Cronfa - Swansea University Open Access Repository , 2017 .

[28]  Liu Liu,et al.  Exploring consumer perceived risk and trust for online payments: An empirical study in China's younger generation , 2015, Comput. Hum. Behav..

[29]  Yong Gu Ji,et al.  Investigating the Importance of Trust on Adopting an Autonomous Vehicle , 2015, Int. J. Hum. Comput. Interact..

[30]  Riender Happee,et al.  Public opinion on automated driving: results of an international questionnaire among 5000 respondents , 2015 .

[31]  Masooda Bashir,et al.  Trust in Automation , 2015, Hum. Factors.

[32]  Martin Zsifkovits,et al.  Simulating resistances in innovation diffusion over multiple generations: an agent-based approach for fuel-cell vehicles , 2015, Central Eur. J. Oper. Res..

[33]  Klaus Bengler,et al.  Trust in Automation – Before and After the Experience of Take-over Scenarios in a Highly Automated Vehicle☆ , 2015 .

[34]  Daniel J. Fagnant,et al.  Preparing a Nation for Autonomous Vehicles: Opportunities, Barriers and Policy Recommendations , 2015 .

[35]  Andrina Granic,et al.  Technology acceptance model: a literature review from 1986 to 2013 , 2014, Universal Access in the Information Society.

[36]  William Payre,et al.  Intention to use a fully automated car: attitudes and a priori acceptability , 2014 .

[37]  Sajad Rezaei,et al.  User satisfaction with mobile websites: the impact of perceived usefulness (PU), perceived ease of use (PEOU) and trust , 2014 .

[38]  N. Epley,et al.  The mind in the machine: Anthropomorphism increases trust in an autonomous vehicle , 2014 .

[39]  Tiago Oliveira,et al.  Understanding the Internet banking adoption: A unified theory of acceptance and use of technology and perceived risk application , 2014, Int. J. Inf. Manag..

[40]  P. Suresh,et al.  REDUCTION OF VEHICULAR POLLUTION THROUGH FUEL ECONOMY IMPROVEMENT WITH THE USE OF AUTONOMOUS SELF-DRIVING PASSENGER CARS , 2014 .

[41]  Natasha Merat,et al.  Highly Automated Driving, Secondary Task Performance, and Driver State , 2012, Hum. Factors.

[42]  Patricia Delhomme,et al.  Simulator Training With a Forward Collision Warning System , 2012, Hum. Factors.

[43]  Viswanath Venkatesh,et al.  Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology , 2012, MIS Q..

[44]  Linda Ng Boyle,et al.  Extending the Technology Acceptance Model to assess automation , 2011, Cognition, Technology & Work.

[45]  Lu Wang,et al.  The Effects of Design Features on Users’ Trust in and Reliance on a Combat Identification System , 2011 .

[46]  José Manuel Ortega Egea,et al.  Explaining physicians' acceptance of EHCR systems: An extension of TAM with trust and risk factors , 2011, Comput. Hum. Behav..

[47]  Janet E. Miller,et al.  Designing for Human-Centered Systems: Situational Risk as a Factor of Trust in Automation , 2010 .

[48]  Mark A. Fuller,et al.  Clarifying the Integration of Trust and TAM in E-Commerce Environments: Implications for Systems Design and Management , 2010, IEEE Transactions on Engineering Management.

[49]  Yung-Ming Li,et al.  Increasing trust in mobile commerce through design aesthetics , 2010, Comput. Hum. Behav..

[50]  Richard J. Holden,et al.  The Technology Acceptance Model: Its past and its future in health care , 2010, J. Biomed. Informatics.

[51]  Hsin Hsin Chang,et al.  The impact of online store environment cues on purchase intention: Trust and perceived risk as a mediator , 2008, Online Inf. Rev..

[52]  H. Raghav Rao,et al.  A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents , 2008, Decis. Support Syst..

[53]  Shumaila Y. Yousafzai,et al.  Technology acceptance: a meta‐analysis of the TAM: Part 2 , 2007 .

[54]  John Richardson,et al.  Alarm timing, trust and driver expectation for forward collision warning systems. , 2006, Applied ergonomics.

[55]  John Richardson,et al.  The influence of alarm timing on braking response and driver trust in low speed driving , 2005 .

[56]  John D. Lee,et al.  Trust in Automation: Designing for Appropriate Reliance , 2004, Hum. Factors.

[57]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[58]  P. Pavlou,et al.  Consumer Acceptance of Electronic Commerce: Integrating Trust and Risk with the Technology Acceptance Model , 2003 .

[59]  Charles J. Kacmar,et al.  The impact of initial consumer trust on intentions to transact with a web site: a trust building model , 2002, J. Strateg. Inf. Syst..

[60]  Albert L. Lederer,et al.  The technology acceptance model and the World Wide Web , 2000, Decis. Support Syst..

[61]  Fred D. Davis,et al.  A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies , 2000, Management Science.

[62]  V. Mitchell Consumer perceived risk: conceptualisations and models , 1999 .

[63]  P. Bentler,et al.  Cutoff criteria for fit indexes in covariance structure analysis : Conventional criteria versus new alternatives , 1999 .

[64]  Rex B. Kline,et al.  Principles and Practice of Structural Equation Modeling , 1998 .

[65]  T. Raykov Estimation of Composite Reliability for Congeneric Measures , 1997 .

[66]  Raja Parasuraman,et al.  Humans and Automation: Use, Misuse, Disuse, Abuse , 1997, Hum. Factors.

[67]  Timothy C. Earle,et al.  Social Trust , 1995 .

[68]  Girish H. Subramanian,et al.  A Replication of Perceived Usefulness and Perceived Ease of Use Measurement , 1994 .

[69]  I. Ajzen The theory of planned behavior , 1991 .

[70]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[71]  P. M. Podsakoff,et al.  Self-Reports in Organizational Research: Problems and Prospects , 1986 .

[72]  C. Fornell,et al.  Evaluating Structural Equation Models with Unobservable Variables and Measurement Error , 1981 .