Riding personal mobility vehicles on the road: an analysis of the intentions of Chinese users
暂无分享,去创建一个
Zhongxiang Feng | Zhiwei Yang | Zhipeng Huang | Zhenhua Yu | Kang Jiang | Zhongxiang Feng | Kang Jiang | Zhiwei Yang | Zhenhua Yu | Zhipeng Huang
[1] Frédéric Vanderhaegen,et al. Toward a Petri Net Based Model to Control Conflicts of Autonomy between Cyber-Physical & Human-Systems , 2016 .
[2] Johanna Zmud,et al. Towards an Understanding of the Travel Behavior Impact of Autonomous Vehicles , 2017 .
[3] Edwin R. Galea,et al. Perceptions of autonomous vehicles: Relationships with road users, risk, gender and age , 2018 .
[4] Charitha Dias,et al. Evaluation of Safe Avoidance Distance for Pedestrians in Personal Mobility Vehicles and Pedestrian Mixed Traffic: A Simulation Based Study , 2017 .
[5] B. Sovacool,et al. Who buys New Energy Vehicles in China? Assessing social-psychological predictors of purchasing awareness, intention, and policy , 2018, Transportation Research Part F: Traffic Psychology and Behaviour.
[6] Natasha Merat,et al. What influences the decision to use automated public transport? Using UTAUT to understand public acceptance of automated road transport systems , 2017 .
[7] Charitha Dias,et al. Modeling pedestrians’ subjective danger perception toward personal mobility vehicles , 2018, Transportation Research Part F: Traffic Psychology and Behaviour.
[8] Frédéric Vanderhaegen. Dissonance Engineering: A New Challenge to Analyse Risky Knowledge When using a System , 2014, Int. J. Comput. Commun. Control.
[9] Susan A. Shaheen,et al. EasyConnect: low-speed modes linked to transit planning project: interim working paper , 2006 .
[10] Yanyong Guo,et al. Evaluating factors affecting electric bike users’ registration of license plate in China using Bayesian approach , 2018, Transportation Research Part F: Traffic Psychology and Behaviour.
[11] Marko Sarstedt,et al. Partial least squares structural equation modeling (PLS-SEM): A useful tool for family business researchers , 2014 .
[12] Dan Blanchette,et al. Adjusting for Unequal Selection Probability in Multilevel Models: A Comparison of Software Packages , 2005 .
[13] Yi-Shun Wang,et al. Why do people use information kiosks? A validation of the Unified Theory of Acceptance and Use of Technology , 2009, Gov. Inf. Q..
[14] Tao Zhou,et al. Integrating TTF and UTAUT to explain mobile banking user adoption , 2010, Comput. Hum. Behav..
[15] Venkatesh,et al. A Longitudinal Field Investigation of Gender Differences in Individual Technology Adoption Decision-Making Processes. , 2000, Organizational behavior and human decision processes.
[16] Guizhen Yu,et al. Are electric self-balancing scooters safe in vehicle crash accidents? , 2016, Accident; analysis and prevention.
[17] Caroline J Rodier,et al. EasyConnect II: Integrating Transportation, Information, and Energy Technologies at Transit Oriented Developments , 2005 .
[18] Megan S. Ryerson,et al. Factors influencing the choice of shared bicycles and shared electric bikes in Beijing , 2016 .
[19] Frédéric Vanderhaegen,et al. Reinforced learning systems based on merged and cumulative knowledge to predict human actions , 2014, Inf. Sci..
[20] Karl T. Ulrich,et al. ESTIMATING THE TECHNOLOGY FRONTIER FOR PERSONAL ELECTRIC VEHICLES , 2005 .
[21] Kimihiko Nakano,et al. Proposal for Personal Mobility Vehicle , 2009 .
[22] Frédéric Vanderhaegen,et al. Can dissonance engineering improve risk analysis of human–machine systems? , 2017, Cognition, Technology & Work.
[23] Ching-Fu Chen,et al. Behavioral intentions of public transit passengers--The roles of service quality, perceived value, satisfaction and involvement , 2011 .
[24] Kevin Fang,et al. Skateboarding for transportation: exploring the factors behind an unconventional mode choice among university skateboard commuters , 2019 .
[25] David Crundall,et al. An application of the theory of planned behaviour to truck driving behaviour and compliance with regulations. , 2008, Accident; analysis and prevention.
[26] Serge Debernard,et al. Principles of adjustable autonomy: a framework for resilient human–machine cooperation , 2010, Cognition, Technology & Work.
[27] Gordon B. Davis,et al. User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..
[28] Nelson Chan,et al. Mobility and the Sharing Economy: Potential to Facilitate the First- and Last-Mile Public Transit Connections , 2016 .
[29] Elliot W. Martin,et al. Evaluating public transit modal shift dynamics in response to bikesharing: a tale of two U.S. cities , 2014 .
[30] Takamasa Iryo,et al. Effect on Travelers' Activities and Environmental Impacts by Introducing a Next-Generation Personal Transport System in a City , 2013 .
[31] Ludwig Theuvsen,et al. Non-participants interest in CSA – Insights from Germany , 2019, Journal of Rural Studies.
[32] Charitha Dias,et al. Simulating Interactions between Pedestrians, Segway Riders and Cyclists in Shared Spaces Using Social Force Model , 2018 .
[33] D. Cicchetti. Guidelines, Criteria, and Rules of Thumb for Evaluating Normed and Standardized Assessment Instruments in Psychology. , 1994 .
[34] Jianping Ge,et al. Electric vehicle development in Beijing: An analysis of consumer purchase intention , 2019, Journal of Cleaner Production.
[35] Ryosuke Ando,et al. Measuring the Acceptability of Self-Balancing Two-Wheeled Personal Mobility Vehicles , 2013 .
[36] Noorminshah A. Iahad,et al. The history of UTAUT model and its impact on ICT acceptance and usage by academicians , 2012, Education and Information Technologies.
[37] Natasha Merat,et al. Acceptance of Automated Road Transport Systems (ARTS): An adaptation of the UTAUT model , 2016 .
[38] Lesley Strawderman,et al. Assessing the utility of TAM, TPB, and UTAUT for advanced driver assistance systems. , 2017, Accident; analysis and prevention.
[39] R. Sickles,et al. An International Comparison of Technology Adoption and Efficiency: A Dynamic Panel Model , 1999 .
[40] Ang Li,et al. An analysis on users' evaluation for self-balancing two-wheeled personal mobility vehicles , 2012, 2012 15th International IEEE Conference on Intelligent Transportation Systems.
[41] Frédéric Vanderhaegen,et al. Towards increased systems resilience: New challenges based on dissonance control for human reliability in Cyber-Physical&Human Systems , 2017, Annu. Rev. Control..
[42] Hideki Hashimoto,et al. Human balance control ability for affinitive personal vehicle , 2013, 2013 10th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI).
[43] Benjamin K. Sovacool,et al. Are electric vehicles masculinized? Gender, identity, and environmental values in Nordic transport practices and vehicle-to-grid (V2G) preferences , 2019, Transportation Research Part D: Transport and Environment.
[44] Yukun Bao,et al. Determinants of user acceptance and use of open government data (OGD): An empirical investigation in Bangladesh , 2019, Technology in Society.
[45] Hamed Khazaei,et al. Electric Vehicles and Factors That Influencing Their Adoption Moderating Effects of Driving Experience and Voluntariness of Use ( Conceptual Framework ) , 2016 .
[46] Il Im,et al. An international comparison of technology adoption: Testing the UTAUT model , 2011, Inf. Manag..
[47] Haris N. Koutsopoulos,et al. Evaluation of the effect of cooperative infrastructure-to-vehicle systems on driver behavior , 2012 .
[48] Ryosuke Ando,et al. Acceptability of Personal Mobility Vehicles to Public in Japan: Results of Social Trial in Toyota City , 2013 .
[49] Tarek Sayed,et al. Evaluating the safety impacts of powered two wheelers on a shared roadway in China using automated video analysis , 2018 .