02 Jan 2025
Recently, the collaborative paper titled "The Effects of Risk Preferences on Consumers’ Reference-Dependent Choices for Autonomous Vehicles" led by Professor Lixian Qian from the Department of Intelligent Operations and Marketing at the International Business School Suzhou (IBSS) of Xi'an Jiaotong-Liverpool University (XJTLU) has been accepted and published in the Risk Analysis, an international authoritative journal in the field of risk analysis. This study explores how consumers' risk preferences influence their choices between private, shared autonomous vehicles, and traditional vehicles, providing policymakers and industry operators with strategies and insights on how to enhance the acceptance of autonomous vehicles. The IBSS PhD graduate, Ya Liang, is the first author of this paper. His PhD principle supervisor, Professor Lixian Qian, is the corresponding author, and his co-supervisors, Dr. Yang Lu from IBSS and Professor Tolga Bektas from University of Liverpool Management School are the co-authors of this paper.
Advances in artificial intelligence (AI) are reshaping transport and mobility sector through autonomous vehicles (AVs), which may introduce various risks such as technical malfunctions, cybersecurity threats, and ethical dilemmas in decision-making. For policy makers and AV-based service operators, it is crucial to understand the complex influence of consumers’ risk preferences on AV acceptance. To fill this research gap, this paper explores how individuals’ risk preferences affect their choices among private AVs (PAVs), shared AVs (SAVs), and private conventional vehicles (PCVs).
Informed by Prospective Theory, researchers the team first derived four risk-preference parameters for each individual based on a lottery experiment and a self-reported survey. Then they conducted a stated preference experiment and developed an error componentmixed logit model to analyze reference-dependent preferences for key attributes of PAVs and SAVs, with reference to PCVs.
This study enhances the scholars’ understanding on risk preferences in AV acceptance and offers important policy and managerial implications in the AI-empowered smart mobility.
First, researchers’ the team’s analysis reveals that risk-tolerant consumers are more inclined toward PAVs or SAVs. Given that AV technology is still in its nascent stage, with many uncertainties, potential adopters might require a higher risk tolerance. Therefore, spotlighting AV advantages and increasing public engagement with the technology are strategic moves for marketers.
Second, the analysis underscores an asymmetric sensitivity among individuals, who react more to additional monetary costs of owning and using AVs than potential savings, which might hinder widespread AV acceptance. Thus, automakers and service providers should emphasize cost-effectiveness and adopt strategic pricing, particularly during the initial market introduction. Furthermore, government intervention through subsidies, tax breaks, and rebates for AV purchases and usage can help mitigate the deterring effects of these higher costs.
Third, the research identifies user liability in the event of crashes as a significant barrier to AV adoption. As control shifts from drivers to AV systems, it is imperative for policy makers to establish clear legal frameworks that delineate liability responsibilities. Allocating liability to manufacturers and technology providers rather than individual users can significantly alleviate consumer concerns, as our findings indicate that consumers are willing to pay a premium for AVs that offer liability exemptions.
Fourth, this research underscores the significant impact of enhanced privacy security on consumer preferences for AVs, highlighting the protection of personal data as a critical factor influencing consumer decision-making. Governments must introduce and enforce robust privacy and data security regulations specifically tailored to AV technologies.
Fifth, researchers’ findings reveal the importance of reduced access time and higher vehicle availability in shaping consumer preferences for SAV services. Specifically, consumers are willing to incur an additional running cost of 0.096 CNY per kilometer for each minute reduction in access time and roughly 0.033 CNY more per kilometer for a 1% increase in SAV availability. This underscores the need for prompt and available SAV services on booking. Consequently, governments should incentivize fleet expansion through subsidies and financial incentives, particularly in densely populated urban areas.
Professor Lixian Qian is a Professor in the Department of Intelligent Operations and Marketing at International Business School Suzhou (IBSS) of Xi’an Jiaotong-Liverpool University (XJTLU). He is currently serving as the Associate Dean for Research at IBSS and the Deputy Chair of University Research Committee. He is also the founding director of Smart Mobility Analytics Center of IBSS. He joined XJTLU in 2012 after obtaining his PhD degree at Lancaster University, UK. He obtained his Bachelor and Master degrees from Fudan University, China. He also had rich industry working experience in Furtune Global 500 companies (Intel and Emerson Electric).
Professor Qian’s research focuses on innovation/technology adoption and diffusion, data-driven marketing strategy, smart mobility, and sustainability. His research has been published widely on leading international journals, such as Production and Operations Management, Journal of Travel Research, Tourism Management, Journal of Business Ethics, Transportation Research Part A, Journal of Business Research, Technological Forecasting Social Change, among others. Three of his research articles were designated as ESI Highly Cited Papers by Web of Science. His research has been funded three times by the General Programme of National Natural Science Foundation of China (NSFC).
Professor Qian teaches a range of modules on marketing and research methods at undergraduate, postgraduate and executive education levels. He is the Fellow of the Higher Education Academy (FHEA) in the UK and the council member of China Marketing Association of Universities (CMAU). He serves as the Section Editor of Sustainable Futures (JCR Q2, CAS Q2), Associate Editor of Management & Marketing (JCR Q3), guest editor of Journal of Consumer Behaviour (JCR Q2, CAS Q3, ABDC-A) and ad-hoc reviewer for over 20 SCI/SSCI academic journals and international conferences.
Professor Qian received the 2016/2017 Outstanding Teacher Award of XJTLU, the 2018/2019 IBSS Research Excellence Award, the Outstanding Advisor of the Sixth China National College Students Competition on Energy Economics in 2020, the 2022 Honored Staff of XJTLU, and the Best Paper Proceeding of 2024 Academy of Management Annual Meeting and the Best Paper Award of 2024 Chinese Academy of Management Annual Conference. He was selected into the Jiangsu 333 High-level Talent Programme in 2022.
Dr. Yang Lu is an Assistant Professor in Management at the Department of Intelligent Operations and Marketing, International Business School Suzhou, Xi’an Jiaotong-Liverpool University. Her research interests focus on individuals’ acceptance, adoption and use of advanced technological innovations such as embodied AI, Internet of Things, robotics, and autonomous vehicles. She serves as reviewer for several prestigious journals and conferences, including Technological Forecasting and Social Change, Journal of Consumer Behaviour, American Marketing Association (AMA) Academic Conference, British Academy of Management (BAM), European Conference on Information Systems (ECIS), etc.
Risk Analysis is the ABS Academic Journal Guide Level 4 journal, and ranked among the top 10 journals in the ISI Journal Citation Reports under the social sciences, mathematical methods category, and provides a focal point for new developments in the field of risk analysis. This international peer-reviewed journal is committed to publishing critical empirical research and commentaries dealing with risk issues. A wide range of topics covered include human health and safety risks, microbial risks, engineering, mathematical modeling, risk characterization, risk communication, risk management and decision-making, risk perception, acceptability, and ethics, laws and regulatory policy and ecological risks.
02 Jan 2025