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IJMLC 2020 Vol.10(3): 423-430 ISSN: 2010-3700
DOI: 10.18178/ijmlc.2020.10.3.952

The Discussion of Kano Two-Dimensional Quality Mode on the Essential Service Quality Attributes of Taiwan Power Company

Chang-Hsien Hsu, Chiu-Yu Hung, Yu-Hsuan Lan, and Zheng-Ji Chen

Abstract—Taiwan Power Company (T-Company) is the only power generation company in Taiwan. However, as a state-owned enterprise with exclusive market, its service items and service quality often have a gap with the expectations of the people. Therefore, this study used the SERVQUAL scale to investigate the service quality elements of a business district in the central part of the Taiwan Power Company, and explored the service quality attributes of Taiwan Power Company in conjunction with the two-dimensional quality model of Kano. Using questionnaires is to understand the importance of the service elements from the points of view of the public? According to the statistical results, among the service quality factors, there are 7 one-dimensional quality elements, 3 attractive quality elements, 8 indifference quality elements, and 9 Must-be quality elements. It is recommended that T-Company can promote their services with the survey results. The elements are improved to further enhance their service quality so as to implement the concept of sustainable business.

Index Terms—T-Company, Kano two-dimensional quality mode, service quality, SERVQUAL questionnaire.

The authors are with the Department of Business Administration, Asia University, Taiwan (e-mail: taylor@wellball.com.tw).

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Cite: Chang-Hsien Hsu, Chiu-Yu Hung, Yu-Hsuan Lan, and Zheng-Ji Chen, "The Discussion of Kano Two-Dimensional Quality Mode on the Essential Service Quality Attributes of Taiwan Power Company," International Journal of Machine Learning and Computing vol. 10, no. 3, pp. 423-430, 2020.

Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

 

General Information

  • E-ISSN: 2972-368X
  • Abbreviated Title: Int. J. Mach. Learn.
  • Frequency: Quaterly
  • DOI: 10.18178/IJML
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Inspec (IET), Google Scholar, Crossref, ProQuest, Electronic Journals LibraryCNKI.
  • E-mail: ijml@ejournal.net


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