This study utilises the modified Transtheoretical Model of Change (TTMC) to investigate the levels of adoption of transport-multi-function apps or Transport-SuperApp (TSA) and also examine the influence of users’ personality, socio-demographic factors, residential location, perceived built environment, and motivations of use. The analysis is based on data collected from 1,051 users in four Indonesian cities. In this study, a latent class cluster analysis (LCCA) was used which identified four distinct classes of TSA level of adoption: Over Enthusiast (OE) (42%) comprising users who extensively explore and utilise the functions of the apps; Exploring but has Disinterest (ED) (36%) comprising those who primarily use apps for popular functions such as transportation, shopping, and payment services, but lack interest in utilising other services; Shopping-oriented but has Broad Interest (SBI) (14%) comprising those who heavily use shopping services while displaying a high interest in other functions; and Minimalist and Unaware (MU) (8%) comprising those who utilises the core functions of TSA for transportation and shopping while exhibiting low awareness of other available functions within the apps. The study found that transportation and shopping services have the highest level of adoption compared to other TSAs’ functions. The findings also suggest that the behaviour surrounding TSA utilization may evolve in the future and adoption levels are influenced by hedonic and utilitarian motivations. The OE users are associated with authority/control and tend to be more disorganised. Whereas SBI users tend to be more creative and open to new experiences. Compared to other classes, OE users are mostly found in Jakarta, a megapolitan area, and primarily reside near activity centres.


    Access

    Download


    Export, share and cite



    Title :

    Exploring levels of adoption of multi-function transport apps: Transtheoretical model of change on the customer journey of Transport-SuperApp (TSA) users


    Contributors:


    Publication date :

    2024




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown