Proceedings of the 2nd International Conference on Educational Development and Social Sciences (EDSS 2025)

<Previous Article In Volume
Next Article In Volume>

A Study of Satisfaction for Service Recovery in Novel-Tea by Data Mining Technology

Authors
Chien-Hua Wang1, Chia-Hsuan Yeh2, *, Chin-Tzong Pang2
1School of Business, Lingnan Normal University, 524048, Zhanjiang, China
2Dept. of Information Management, Yuan Ze University, 320315, Taoyuan, Taiwan, China
*Corresponding author. Email: imcyeh@saturn.yzu.edu.tw
Corresponding Author
Chia-Hsuan Yeh
Available Online 15 May 2025.
DOI
10.2991/978-2-38476-400-6_71How to use a DOI?
Keywords
Data mining; novel-tea drinks; service errors; service recovery; satisfaction
Abstract

Customers’ requirements for tea drinks increase as time goes on. Coupled with the emergence of novel-tea drinks, which are deeply loved by young people, the audience and market size of tea drinks have gradually expanded, and various brands have emerged one after another. However, many problems in tea shops have gradually emerged under this situation. Mistakes made in service and consumer dissatisfaction are the most probable cases. Based on this background, this research applies data mining technology to explore the analysis of novel-tea drinks’ satisfaction with service recovery. In order to deeply explore the important attributes and their correlations that affect service recovery satisfaction, this research explores and analyzes the characteristics of customer groups whose responses regarding service recovery satisfaction are dissatisfied. In addition, through the analysis of the association rule model, we describe the characteristics and attributes that often accompany dissatisfaction in the service quality satisfaction as well as the correlations between them, and propose corresponding measures so as to provide reference for novel-tea drinkers.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the 2nd International Conference on Educational Development and Social Sciences (EDSS 2025)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
15 May 2025
ISBN
978-2-38476-400-6
ISSN
2352-5398
DOI
10.2991/978-2-38476-400-6_71How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Chien-Hua Wang
AU  - Chia-Hsuan Yeh
AU  - Chin-Tzong Pang
PY  - 2025
DA  - 2025/05/15
TI  - A Study of Satisfaction for Service Recovery in Novel-Tea by Data Mining Technology
BT  - Proceedings of the 2nd International Conference on Educational Development and Social Sciences (EDSS 2025)
PB  - Atlantis Press
SP  - 604
EP  - 614
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-400-6_71
DO  - 10.2991/978-2-38476-400-6_71
ID  - Wang2025
ER  -