Factors Influencing Recommendation Intentions for Autonomous Vehicles: A Path Analysis
Abstract
Over the past decade, the rapid development of artificial intelligence has propelled the transition of autonomous vehicles from laboratories to real-world applications. However, autonomous vehicles are a long way from fully integrating into most people’s lives. Previous studies indicate that the word-of-mouth effect is often used by consumers to determine the quality of innovative technologies. Through the word-of-mouth effect, the intention to recommend can contribute to the growth of the autonomous driving market. Therefore, current research explores the mechanisms among the perceived risk of privacy safety, perceived defect, perceived behavioral control, intention to use, and intention to recommend through path analysis. Our findings, based on 264 online questionnaires, indicate that the perceived risk of privacy safety, perceived defects, and perceived behavioral control influence the intention to recommend. Notably, perceived risk of privacy safety directly affects the intention to recommend and also correlates with perceived behavioral control. These findings provide some empirical evidence for the recommendation of autonomous vehicles and the expansion of consumer groups.
Citation: Ruan, S., Li, S, & Qi, Y．(in press). Factors Influencing Recommendation Intentions for Autonomous Vehicles: A Path Analysis．Acta Psychologica