
This study integrates the Unified Theory of Technology Acceptance and Use (UTAUT) and Status Quo Bias (SQB) theories and draws on survey data covering nine dimensions: performance expectancy, effort expectancy, social influence, individual innovation, transition costs, sunk costs, inertia and resistance to use. The aim is to explore the underlying reasons and disparities that influence people's adoption of MaaS from both a facilitator and inhibitor perspective. To mitigate the confounding effect of group heterogeneity on the MaaS acceptance mechanism, the latent class clustering method was employed to naturally categorize respondents into three distinct groups: MaaS avoiders, wanderers and enthusiasts. A structural equation model was then developed to delineate the path of influence of users' intention to use and to contrast the differences in path coefficients between the different groups. The results show that individuals who are most dependent on public transport are not necessarily the most willing to use MaaS, while those who have used car-sharing services are more likely to adopt MaaS. It also highlights that there is no one-size-fits-all approach to promoting MaaS adoption, as different groups of people have different preferences, needs and concerns about the service. MaaS avoiders are predominantly middle-aged and older individuals with lower incomes, whose reluctance to switch stems from the associated transition costs, which create inertia. To encourage this group to adopt MaaS, operators should develop a gradual and user-friendly transition plan that minimizes complexity and addresses potential challenges such as unfamiliarity with the system and resistance to service changes. Conversely, MaaS wanderers’ willingness to engage with the service is strongly influenced by social influence and performance expectancy. Operators can increase their social media presence and raise awareness of the practicality of MaaS, helping to build an early customer base. In addition, the innovative mindset of MaaS enthusiasts plays a key role in their willingness to adopt the service, although operators must also be vigilant about privacy concerns and the risk of data breaches. Overall, this study enriches our understanding of the factors that shape MaaS adoption and provides actionable insights for improving services across different market segments.
Transportation engineering, TA1001-1280, Integrated transportation, Latent class analysis, Facilitators and inhibitors, Adoption intention, Transportation and communications, Mobility as a Service, HE1-9990
Transportation engineering, TA1001-1280, Integrated transportation, Latent class analysis, Facilitators and inhibitors, Adoption intention, Transportation and communications, Mobility as a Service, HE1-9990
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 3 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
