Riris Amigo Simatupang, Gaby P.F Tampubolon, Idrus Hamonangan Pane, Muammar Rinaldi

The Impact of E-ticketing Implementation and Service Quality on Kai-Access Application User Satisfaction

Introduction

The impact of e-ticketing implementation and service quality on kai-access application user satisfaction. Explore how e-ticketing implementation and service quality influence user satisfaction with the KAI Access application. Quantitative and qualitative findings reveal key factors and areas for improvement in transportation digitalization.

Abstract

The increase in digitalization within the transportation sector has driven PT Kereta Api Indonesia (PT KAI) to implement an e-ticketing system through the KAI Access application. However, there are still challenges related to service quality that may affect user satisfaction. This study aims to analyze the impact of e-ticketing implementation and service quality on user satisfaction with the KAI Access application. The research focuses on identifying factors that contribute to user experience and customer satisfaction. The study employs a quantitative approach using multiple linear regression analysis. Data were collected through questionnaires distributed to KAI Access users and analyzed using statistical software. The main variables examined include information quality, system quality, service quality, and customer satisfaction. More specifically, this research adopts a mixed-methods design with a sequential explanatory strategy. The initial quantitative phase involved 30 KAI Access users selected through purposive sampling. Multiple linear regression analysis was used to test the hypotheses regarding the influence of E-Ticketing (X1) and Service Quality (X2) on Customer Satisfaction (Y). The T-test results show that E-Ticketing (t = 2.565; p = 0.016) and Service Quality (t = 2.226; p = 0.035) each have a significant partial effect on Customer Satisfaction. Simultaneously (F-test), both variables also have a significant effect (F = 31.697; p = 0.001) with a contribution of 70.1% (Adjusted R Square). In the second phase, the qualitative analysis deepens these findings through in-depth interviews. Thematic analysis reveals that although users appreciate the ease of use, there are still notable complaints regarding system speed during peak hours and the need for additional features such as delay tracking. This study concludes that e-ticketing and service quality are strong predictors of customer satisfaction and recommends improving system performance to optimize the user experience.

Review

This study presents a timely and relevant examination of user satisfaction with the KAI Access e-ticketing application, a critical component of PT KAI's digitalization efforts. The research effectively highlights the significant roles of e-ticketing implementation and overall service quality as strong predictors of customer satisfaction. Utilizing a mixed-methods approach, the authors not only quantify these relationships with statistically significant findings (e.g., 70.1% of satisfaction explained) but also enrich the understanding through qualitative insights. The identification of user appreciation for ease of use, coupled with specific complaints about system speed during peak hours and the absence of features like delay tracking, provides a well-rounded and actionable perspective for stakeholders aiming to optimize the user experience. The methodological strength lies in its mixed-methods design, which allows for both the statistical validation of hypotheses and a deeper qualitative exploration of user perceptions. The quantitative analysis, despite its small sample size, yielded statistically significant results for both e-ticketing and service quality's impact on satisfaction, demonstrating a strong association. The qualitative phase is particularly commendable for pinpointing concrete areas for improvement, such as system performance during high-demand periods and the need for enhanced features. This dual approach offers valuable insights that are both empirically supported and contextually rich, providing a solid foundation for the study's conclusions and recommendations. However, a primary limitation that warrants attention is the relatively small sample size of 30 KAI Access users for the quantitative phase. While the statistical results indicate significance, such a sample may limit the generalizability and statistical power of the multiple linear regression findings to the broader user population. Future research would significantly benefit from replicating this study with a larger, more diverse, and representatively sampled user base to enhance the robustness and external validity of the quantitative conclusions. Furthermore, clearer operationalization of the "E-Ticketing (X1)" variable would strengthen the methodological clarity for readers. Expanding the qualitative phase to include more diverse user demographics or usage patterns could also provide even richer and more comprehensive insights into specific pain points and feature requirements.

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