User Acceptance of Internet of Vehicles Services: Empirical Findings of Partial Least Square Structural Equation Modeling (PLS-SEM) and Fuzzy Sets Qualitative Comparative Analysis (fsQCA)

Abstract

Recently, IoV-based services and vehicles have come to the forefront as part of the growing market for the automobile industry. Since IoV-based services and vehicles were introduced, they have been expected to grow rapidly. However, contrary to optimistic expectations for future market growth, the IoV-based services and vehicles market has appeared to hit a roadblock and remains at an early market stage. Therefore, research of the determinants leading to consumers’ intention to accept and purchase IoV-based services and vehicles is significant for either academics or practitioners. Drawing upon the extended unified theory of acceptance and use of technology acceptance model (UTAUT2), the perceived risk theory, and the initial trust model, we developed an integrated conceptual model and explored what and how various determinant antecedent conditions fit together on consumer intention to accept IoV-based services and vehicles. The proposed model and hypotheses were assessed by both symmetric (partial least square structural equation modeling, PLS-SEM) and asymmetric (fsQCA) approaches using online survey datasets with 362 Chinese consumers. The findings suggest that PLS-SEM and fsQCA are complementary analytical techniques providing comparable results. PLS-SEM results indicate that performance expectancy, price value, habit, and initial trust have significant effects on behavioral intention to accept IoV services. Despite other determinants, e.g., effort expectancy, social influence, facilitating conditions, hedonic motivation, and perceived risk, have no significant effect. FsQCA results reveal twelve different configurations of determinants resulting in a high level of behavioral intention to accept IoV services, and eight causal paths equifinally leading to the negation of behavioral intention to accept IoV services. These findings suggest that several conditions that were not significant in PLS-SEM are sufficient conditions when combined with other conditions. This study enriches relevant research studies on IoV-based services acceptance and provides relevant insights and marketing suggestions for incentivizing consumers to accept the IoV-based services.

Technology readiness, UTAUT2 and continued use of digital wellness services - A configurational approach

“…The configurations identify four of the seven possible variables as sufficient: high Technology Readiness, Effort Expectancy, Social Influence and Facilitating Conditions lead to the outcome of interest. This is in high contrast with existing studies on investigating user behavior through the lens of UTAUT2 model or Technology Readiness [5,9], in which identified configurations typically take a more complex form. In this study, the collected data shows a more straightforward, but not trivial, picture of why young elderly continue to use digital wellness services: if they perceive at least one of the four identified, core antecedents positively enough, this is sufficient to drive further use of the service.…”

“…In a similar approach, Liang et al [5] investigate the impact of the UTAUT2 dimensions on technology adoption in an autonomous vehicle context. In assessing their structural model, they find only PE, price value (PV) and habit to be significant predictors of behavioral intention.…”

Adoption of Mobile Government Cloud from the Perspective of Public Sector

“…Perceived risk means the potential problems and risks brought from the introduction of innovation [7], and it is the inhibitor for technology adoption [38,44,71]. Dialectically, everything has two sides.…”

Integrated Acceptance Model for On-demand Car Functions: exploring determinants of drivers' acceptance

“…In the same direction, recent 134 surveys in related contexts have shown that the consumers' intention to accept or purchase Internet-of-Vehicle (IoV) based services is generally low. Therefore, it is significant to explore the determinants of consumers' intention to accept and purchase IoV-based services (Liang et al, 2020). "A successful real-world deployment of innovative CV applications not only depends on their maturity and usability, but also hinges upon user acceptance" (Li et al, 2021, p. 1).…”

“…For example the Theory of Reasoned Action (TRA) (Fishbein & Ajzen, 1975), technology acceptance model (TAM) (Davis, 1989), theory of planned behavior (TPB) (Ajzen, 1991), task-technology fit (TTF) (Goodhue & Thompson, 1995), motivational model (MM) (Davis et al, 1992), unified theory of acceptance and use of technology (UTAUT) (Venkatesh et al, 2003(Venkatesh et al, , 2012, initial trust model (ITM) (McKnight et al, 2002), diffusion of innovation theory (IDT) (Rogers, 2010), and social cognitive theory (SCT) (Compeau et al, 1999). Numerous investigations have employed these frameworks in their original form or augmented them with novel constructs, resulting in the formulation of models that serve as conduits for their research endeavors across diverse technological contexts (Liang et al, 2020). Nonetheless, within context-specific investigations concerning acceptance, two models frequently assume foundational roles (Lee et al, 2003) and are concisely elucidated in the ensuing discussion.…”