Using text mining to measure mobile banking service quality. Issue 5 (4th March 2021) - Leem, Byung-Hak; Eum, Seong-Won
Abstract : Purpose: The purpose of this study is to propose a method of measuring service quality as well as suggesting to detect customer complaints through analysis of customer online reviews of mobile bank, which is unstructured data. Design/methodology/approach: This study uses text mining approach for customer online reviews analysis. The research procedure includes: (1) extracting users' reviews for Kakao Mobile Bank, (2) pre-processing of the extracted review data, (3) analyzing the sentiment of each review, (4) measuring the service quality score of each dimension by analyzing keyword frequency and network for each polarity, (5) evaluating total score for mobile bank service quality, and (6) detecting customer complaints on online reviews. Findings: There are some findings. First, from the customer's point of view, it was possible to see which factors are important among the various dimensions of service quality and which factors should be managed well in mobile banking setting. Second, by periodically finding customer complaints, service failures can be prevented early, and service quality and customer satisfaction can be improved. Practical implications: From a practical point of view, mobile bank managers should pay more attention to the service quality dimensions of practicality and enjoyment. In addition, the results mean that the app design and aesthetics with the most negative reviews should be reviewed from the user's perspective rather than from the company's point of view. Second, it is possible for them to establish a systematic complaint management system that can prevent service failure in advance by detecting customer complaints early. Third, it is possible for them to make quick decisions regarding service quality with the help of real-time customer response through dashboard construction. Originality/value: This paper is a pioneer study measuring service quality with sentiment analysis, one of the text mining applications, using customers' reviews of a mobile bank.