Earticle

초록

영어

This study aims to analyze service improvement and success factors of electric scooter sharing service companies by using text mining after collecting reviews of shared electric scooter service applications among various models of sharing economy. In this study, the factors of satisfaction and dissatisfaction of service users were identified using the term frequency inverse document frequency (TF-IDF) technique, and topics for each keyword were extracted using the Latent Dirichlet Allocation (LDA) Topic Modeling technique. According to the analysis results, the main topics were entertainment, safety, service area, application complaints, use complaints, convenience, and mobility. Using the analysis results of this study, employees and researchers of electric scooter sharing service companies will be able to contribute to the improvement and success of related services.

목차

Abstract
1. Introduction
2. Related Research
2.1 Sharing Economy
2.2 E-Scooter Sharing
3. Research Methodology
3.1 Data Collection and Preprocessing
3.2 Analysis Methods
4. Result
4.1 TF-IDF Analysis
4.2 LDA Topic Modeling
5. Conclusion
5.1 Conclusion and Business Implications
5.2 Limitations and Future Research Directions
References

키워드

저자

• Kyoung-ae Seo [ Doctoral candidate, Department of Business Administration, Hoseo University ] First Author
• Jung Seung Lee [ Associate Professor, School of Business, Hoseo University ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  JITAM [Journal of Information Technology Applications and Management]

• 간기

  격월간

• pISSN

  1598-6284

• eISSN

  2508-1209

• 수록기간

  1999~2026

• 십진분류

  KDC 005 DDC 005