An integrated SOR and SCT model approach to exploring chinese public perception of autonomous vehicles - Jingwen Wu; Sok-Tae Kim (Scientific Reports)
Abstract The media’s influence on public attitudes and decisions exhibits a dual nature, serving as a catalyst for both positive and negative perceptions, especially regarding autonomous vehicles (AVs). Although extensive research has addressed the role of social and mass media in this domain, the differential impacts of mass media and electronic word-of-mouth (eWOM) on the adoption of these technologies remain underexplored. To bridge this gap, this study explores how various media channels shape public perception and adoption intentions toward AVs. A key innovation of this study lies in its integration of the stimulus-organism-response (SOR) model and social cognitive theory (SCT) to examine how external environmental stimuli and internal belief systems jointly shape consumer behavior in autonomous vehicles. Methodologically, the study employed a structured questionnaire to survey Chinese consumers, gathering data on their media-influenced perceptions. This study’s theoretical implications were grounded in the TAM framework. Two types of external environmental stimuli: mass media and electronic word-of-mouth, were introduced, enriching the environmental variable system of the technology adoption model. Secondly, by using the integrated perspective of SOR-SCT, it revealed the differentiated influence mechanisms of different information sources on consumers’ adoption intentions through three psychological paths: self-efficacy, subjective norms, and trust. Practically, the research offers insights into how service providers can strategically use media channels to enhance public acceptance of new technologies. The results indicate that mass media has a positive impact on the public’s willingness to adopt autonomous vehicles. EWOM facilitated the creation of subjective norms by providing authentic, transparent, and diverse information, as well as enabling interaction with other users.