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Artificial intelligence (AI)-powered autonomous vehicles (AVs) are one of the most highly anticipated technological advancements of our time, with potentially wide-ranging social implications in terms of driver/passenger safety, equity and environmental aspects. However, most consumers feel reluctant towards the adoption of AI-powered AVs. To analyse user acceptance of AI-powered AVs, we need to understand the related psychological, social and cognitive factors. To do so, we established a conceptual model based on the technology acceptance literature and considered how performance and effort expectancy, social recognition, hedonism technology security and privacy concerns influence both technology trust and user well-being as mediators that subsequently influence the behavioural intention of the use of AI-powered AVs. We used user innovativeness as a moderator, and we performed a survey in France. Our results from the structural equation modelling largely support the positive relationship between the behavioural intention to use AI-powered AVs and performance-/effort expectancy, social recognition, well-being, hedonism and technology trust, as well as security. On the other hand, privacy concerns negatively influence technology trust.

The personalization–privacy paradox persists because consumers appreciate the value of personalization, yet marketers’ exploitation of consumers’ personal information to provide such personalization raises privacy concerns. Consumers then may refuse to provide personal information, which limits personalization efforts. Attempts to rely on information technology (e.g., anonymizing techniques, peer-to-peer communication) to address privacy concerns largely have proven ineffective, often because they are overly sophisticated for consumers. Thus, even if the personalization–privacy paradox seemingly arose with mobile technologies, it must stem from a theoretical foundation. Prior information systems literature tends to adopt micro-oriented theories to understand the paradox, but this perspective article instead seeks to investigate the personalization–privacy paradox at a macro level, with an attention economy lens. By investigating the relationship among personalization, privacy, and attention, this study seeks to offer insights pertaining to the ecology of attention, choice architectures, and stylistic devices, as well as some relevant implications for research and practice.