Earticle

초록

영어

Recently, demand on application or using Bigdata analytics for CRM (Customer Relationship Management) has emerged in industry and academic research. However, most of previous text analytics studies validated algorithms and reported results of analysis without theoretical background or standardized framework. According to this reasons, expanding studies on various contexts and utilization have been limited. This study aims to develop theory-based framework on text mining techniques to evaluate service quality. Hence, previous studies and business cases are reviewed for selecting appropriate algorithms for measuring service quality. In this process, developed framework was applied to analysis customer’s online reviews. This study will be useful initial guideline on business operators who want to evaluate their service quality from user-generated-contents. It also has values on introductory business research on applied text data analysis and expand research scope and method on service research.

목차

Abstract
 Introduction
 Literature Review and Conceptual Background
  Evaluating Service Quality
  Text Mining on Customer’s Online Reviews.
 Framework for evaluating Service quality
  Step1. Data Collection
  Step2. Refine data to analysis
  Step3. Text analysis
  Step4. Reporting
 Results
 Implications and Future Research
 References

저자

• G. Kim [ Graduate School of Information, Master Student Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Korea ]
• Hae-jung Yun [ Graduate School of Information, Research Professor Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Korea ]
• Seung-hyun Yun [ Electric & Electrical Engineering, Undergraduate Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Korea ]
• Choong C. Lee [ Graduate School of Information, Professor Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Korea ]

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