Analysis of Integrated Railway QR Code Mobile Payment Systems’ Technology Acceptance - Tripradipta, Rahardianto; Priyanto, Sigit; Fahmi Amrozi, M. Rizka; Kemp, Andrew H (Universitas Ibn Khaldun Bogor, 2024)
This research investigates passengers' perceptions regarding the implementation of integrated railway Quick-response Code mobile payment systems. Their perception of the technology is crucial for determining the main factors that influence technology acceptance in transport tariff integration sector. The research locations are in Jakarta (Jaklingko application) and United Kingdom (Trainline application). The method used in this research was the technology acceptance model. The model was used to identify the construct and indicator variables hypothesized to influence acceptance. The model's dependability was then evaluated using the partial least squares – structural equation modelling method. After the model had been evaluated for dependability, it was tested on the determined hypothesis to determine factors that could increase passenger acceptance of the application. The analysis revealed that the technology acceptance model extension factors which influent the model were self-efficacy, informativeness, result demonstrability, subjective norms and perceived risk. This study's findings also suggest that policies implement travel behavior interventions, distribute information, instructing transportation operators to conduct targeted advertisement technology and comply with network security standards can increase technology acceptance. These results support previous research concerning the core concept of technology acceptance model but also found differences with several previous studies, namely that perceived risk does not influence perceived ease of use because the most significant concern of mobile telecommunication users is failure transactions. Moreover, the indicator difference between the two application models demonstrates that each technology implementation is unique and that there may be disparities in the indicators representing the model's construct variables.