TF-IDF Decision Matrix to Measure Customers’ Satisfaction of Ride Hailing Mobile Application Services: Multi-Criteria Decision-Making Approach

Abstract

In recent years, the use of ride hailing mobile application services is increasing exponentially. Customers’ expectation of these phone services varies and change dynamically as the needs of each individual also vary. Customer reviews about mobile application are honest, voluntary opinions; and these could become essential input for mobile application providers to measure satisfaction. However, managing a large number of reviews into actionable plans could be challenging. This study combines the Term Frequency-Inverse Document Frequency (TF-IDF) and Multiple-Criteria Decision-Making (MCDM)-VIKOR approach to process 600 reviews into a meaningful insight to enhance ride hailing mobile application services. The four-phase method analysis concluded that application ease of use and affordability are the most important aspects that most contribute to customers’ satisfaction in ride hailing mobile application services.