An explorative study of acceptance and usage of on-demand car functions technology
Abstract
This dissertation investigates the acceptance of on-demand car functions (ODCF) and proposes a conceptual framework incorporating key factors to explain behavioral intentions from an end-user perspective. Given the limited research on end-user responses to ODCF and the potential for adverse reactions¿where users may feel misled to pay for activating pre-installed features¿understanding the determinants influencing end-users' intention to accept ODCF is crucial for academic and practical application. While effective in explaining consumer behavior, existing acceptance models require adaptation and extension through exploratory qualitative studies, followed by quantitative analysis examining the relationships between relevant factors to improve their explanatory power in the context of ODCF. This study employs an exploratory sequential mixed-methods design to address these research gaps. Initially, qualitative research is conducted to identify factors pertinent to end-user acceptance of ODCF by semi-structured expert interviews. Subsequently, quantitative research is performed to evaluate these factors and associated hypotheses using symmetric (Partial Least Squares Structural Equation Modeling, PLS-SEM) and asymmetric (Fuzzy-set Qualitative Comparative Analysis, FsQCA) approaches based on data collected from an online survey of 198 end-users. The PLS-SEM results demonstrate that performance expectancy, price value, upgradeability, and knowledge have significant positive effects, while perceived ease of product trial and perceived betrayal significantly negatively impact the behavioral intention to accept ODCF. The FsQCA uncovers ten configurations that lead to high behavioral intention to accept ODCF and eighteen causal pathways that diminish this intention. The findings suggest that PLS-SEM and FsQCA are complementary analytical techniques, with FsQCA offering a more nuanced understanding of the complex causal relationships, including factors showing nonsignificant effects on the intention to accept ODCF (such as perceived ease of product modification, configurability, personalization, and trust). This dissertation confirms, extends, and contributes novel insights to the body of knowledge on the acceptance of ODCF, offering a comprehensive understanding of the factors influencing end-user intentions by integrating qualitative and quantitative methods.Administración y Dirección de Empresa- doctoralThesis
- Automotive industry
- Technological innovation
- Business model innovation
- Connected car
- On-demand car functions
- Consumer behavior
- Behavioral intentions
- End-user acceptance
- Technology acceptance
- TAM
- UTAUT
- Mixedmethods design
- Qualitative research
- Quantitative research
- Semi-structured interviews
- PLS-SEM
- FsQCA