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IJML 2012 Vol.2(5): 640-643
doi: 10.7763/IJMLC.2012.V2.205

Measuring Service Quality Using Complement Methods for Gap Model

Zahra Mokhtary , Behrouz Pazhouh

  • Mathematical Institution of Azar Pazhouhan, Tabriz, Iran.

Abstract

purpose of this study is to empirically assess three comparative approaches to measure service quality: gap model, TOPSIS, and loss function. Statically populations of this research are the insurants of five branches of social security organization in Tabriz that gathered in the second half of the year 2009. Empirically evidence obtained from a sample of four hundreds numbers from customer data in service quality of branches by SERVEQUAL questionnaire. Service quality evaluation obtained by these three distinct methods are compared and tested for their mutual agreement. We answered questions of the research by this data. Findings show that ranking obtained by these methods are Results show that branch three is the best and branch four is the worst of the branches.<br /> This research provides profound concepts and is a framework for managers to improve service quality. This structure measures service quality gaps, selects an optimal combination of attribute levels to keep customer satisfied, and focuses on reducing the future loss caused by poor quality.

Keywords

  • Measuring service quality
  • quality management
  • Gap analysis
  • SERVEQUAL
205-L30036

How to Cite

Copied

Zahra Mokhtary and Behrouz Pazhouh, "Measuring Service Quality Using Complement Methods for Gap Model," International Journal of Machine Learning, vol. 2, no. 5, pp. 640-643, 2012. https://doi.org/10.7763/IJMLC.2012.V2.205

Copyright & License

Copyright © 2012 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).

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General Information

  • E-ISSN: 2972-368X
  • Abbreviated Title: Int. J. Mach. Learn.
  • DOI: 10.18178/IJML
  • Frequency: Quarterly
  • Average Days to Accept: 68 days
  • Acceptance Rate: 27%
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • DOI: 10.18178/IJML
  • Abstracing/Indexing: Google Scholar, Crossref, ProQuest, Electronic Journals Library, CNKI.
  • E-mail: editor@ijml.org
  • APC: 500USD