Customer Satisfaction Analysis of Online Taxi Mobile Apps

Army Justitia · Rini Semiati · Nadhila Ramadhini Ayuvinda

43 citations0/0 files storedJournal of Information Systems Engineering and Business Intelligence

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Customer Service Quality and Loyalty Technology Adoption and User Behaviour Health, Technology, Consumer Behavior

Abstract

Background: High number of complaints that have been filed about the performance of online taxi services has prompted research on customer satisfaction factor analysis. Substantial research has addressed customer satisfaction factors in online taxi services, but none of them investigated the satisfaction in using the mobile apps.Objective: This study aims to find out the level of customer satisfaction and customer satisfaction factors in the online taxi mobile app services.Methods: This study is quantitative in nature, using questionnaires and purposive sampling method. The Customer Satisfaction Index (CSI) and Important-Performance Analysis (IPA) were used to determine the customer satisfaction factors, with the variables being route detection, connection, interaction, content, and service quality; as well as customer satisfaction, customer’s complaint, and customer loyalty. The data was processed using SPSS software.Results: The results showed that the level of customer satisfaction was 76.117% and fell into Cause of Concern category. This means that the system performance did not meet customer expectations. The results also showed that the best three factors in online taxi mobile apps are route detection, interaction, and content quality. Meanwhile, the factors that caused customer dissatisfaction were connection and service quality. The variables that led to satisfaction need to be maintained and the variables that did not were in Quadrant 1.Conclusion: The customer satisfaction was low so it is advisable that the companies immediately take an action to improve their performance and revise their strategic planning. In doing so, they must prioritize the attributes which have the biggest gap because these are the ones that will improve customer satisfaction.

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1977Importance-Performance Analysis 2009The relationships among service quality, perceived value, customer satisfaction, and post-purchase intention in mobile value-added services 2014Importance-performance analysis: A valid management tool?2002Information Quality for Mobile Internet Services: A Theoretical Model with Empirical Validation 2009A New Customer Satisfaction Index for Evaluating Transit Service Quality 2004The conceptualization and measurement of m-commerce user satisfaction 2017Mobile taxi booking application service’s continuance usage intention by users 2017Service Quality Analysis for Online Transportation Services: Case Study of GO-JEK

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