What drives the upcoming utopia? A mixed-methods inquiry into public acceptance of flying cars in China

Abstract

As flying cars transition from a utopian vision to a tangible reality, their societal integration hinges on public acceptance. Existing research, often relying on pre-defined theoretical frameworks, may fail to capture the nuanced, emergent concerns specific to this disruptive technology within diverse socio-cultural contexts. To address this gap, this study employs a sequential exploratory mixed-methods design, integrating Latent Dirichlet Allocation (LDA) with Structural Equation Modeling (SEM), to develop a data-driven model of public acceptance intention for flying cars in China.

First, we analyzed social media data via LDA to identify public concerns, revealing five core constructs: trust, performance expectancy, effort expectancy, perceived risk, and a novel construct we term perceived value barriers. Subsequently, a theoretical model incorporating these constructs and media exposure was developed and tested using survey data.

The research outcomes reveal that trust is the pivotal determinant of the public's intention to use flying cars. It not only directly affects behavioral intention but also indirectly influences it through effort expectancy. Notably, performance expectancy and perceived risk did not directly influence behavioral intention. Furthermore, media exposure was found to enhance trust and mitigate perceived value barriers, though it did not significantly alter direct risk perception.

Theoretically, this study proposes a trust-centric acceptance framework for disruptive technologies that incorporates social value barriers. Practically, our findings provide data-driven insights for governmental governance and manufacturer marketing strategies, emphasizing that building trust through value-oriented narratives, rather than through purely technical specifications, is paramount.