Earticle

초록

영어

Now is the time for IS scholars to demonstrate the added value of academic theory through its integration with text mining, clearly outline how to implement this for text mining experts outside of the academic field, and move towards establishing this integration as a standard practice. Therefore, in this study we develop a systematic theory-based text-mining framework (TTMF), and illustrate the use and benefits of TTMF by conducting a text-mining project in an actual business case evaluating and improving hotel service quality using a large volume of actual user-generated reviews. A total of 61,304 sentences extracted from actual customer reviews were successfully allocated to SERVQUAL dimensions, and the pragmatic validity of our model was tested by the OLS regression analysis results between the sentiment scores of each SERVQUAL dimension and customer satisfaction (star rates), and showed significant relationships. As a post-hoc analysis, the results of the co-occurrence analysis to define the root causes of positive and negative service quality perceptions and provide action plans to implement improvements were reported.

목차

ABSTRACT
Ⅰ. Introduction
Ⅱ. Literature Review and Methodological Framework
2.1. Current Status of Text Mining and Academic Research
2.2. Theory-based Text Mining Framework(TTMF)
Ⅲ. Illustration: Evaluating the Service Quality of Hotels in Seoul
3.1. TTMF Implementation
3.2. Comparative Findings between TTMF and a Data-driven Approach
Ⅳ. Conclusion
4.1. Research Findings
4.2. Theoretical Contribution
4.3. Practical Implications
4.4. Limitation of the Study and Further Directions
Acknowledgement

저자

• Choong C. Lee [ Professor, Graduate School of Information, Yonsei University, Korea ]
• Kun Kim [ M.S. Student, Graduate School of Information, Yonsei University, Korea ]
• Haejung Yun [ Assistant Professor, College of Science & Industry Convergence, Ewha Womans University, Korea ] Corresponding author

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