An application of fuzzy logic to assess service quality attributes in logistics industry

Differentiation, growing competitive advantage, and excellence has been proved to be the result of service quality. At the same time, measuring attributes of service quality and customer satisfaction is fuzzy and ambiguous, and methods available for their measurement are generally classical. This p...

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Main Authors: Ahmad Esmaeili, Reza Ahmadi Kahnali, Reza Rostamzadeh, Edmundas Kazimieras Zavadskas, Babak Ghoddami
Format: Article
Language:English
Published: Vilnius Gediminas Technical University 2015-06-01
Series:Transport
Subjects:
Online Access:https://journals.vgtu.lt/index.php/Transport/article/view/1773
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spelling doaj-b9c8007aeb5d4070ad57c4acf385d6132021-07-02T05:57:22ZengVilnius Gediminas Technical UniversityTransport1648-41421648-34802015-06-0130210.3846/16484142.2015.1046402An application of fuzzy logic to assess service quality attributes in logistics industryAhmad Esmaeili0Reza Ahmadi Kahnali1Reza Rostamzadeh2Edmundas Kazimieras Zavadskas3Babak Ghoddami4Dept of Industrial Management, Allameh Tabataba’i University, Tehran, IranDept of Management, Hormozgan University, Bandar Abbas, IranDept of Management, Urmia Branch, Islamic Azad University, Urmia, IranResearch Institute of Smart Building Technologies, Vilnius Gediminas Technical University, Vilnius, LithuaniaDept of Industrial Management, Allameh Tabataba’i University, Tehran, Iran Differentiation, growing competitive advantage, and excellence has been proved to be the result of service quality. At the same time, measuring attributes of service quality and customer satisfaction is fuzzy and ambiguous, and methods available for their measurement are generally classical. This paper proposes a fuzzy method to identify the service quality attributes. This approach was developed using crisp assessment methods in a logistics company. Applying the proposed fuzzy approach, service quality attributes and indicators are identified and then organized into 8 categories, to see the uncertainty level of each. The proposed method was successfully conducted in a real logistics company. The results show the membership degree of each indicator, suggesting customer expectations regarding quality. Also, the membership degrees of the service quality attributes suggest the ability of each to describe service quality in logistics industry. https://journals.vgtu.lt/index.php/Transport/article/view/1773fuzzy sets theoryfuzzy entropyservice qualityquality attributeslogistics
collection DOAJ
language English
format Article
sources DOAJ
author Ahmad Esmaeili
Reza Ahmadi Kahnali
Reza Rostamzadeh
Edmundas Kazimieras Zavadskas
Babak Ghoddami
spellingShingle Ahmad Esmaeili
Reza Ahmadi Kahnali
Reza Rostamzadeh
Edmundas Kazimieras Zavadskas
Babak Ghoddami
An application of fuzzy logic to assess service quality attributes in logistics industry
Transport
fuzzy sets theory
fuzzy entropy
service quality
quality attributes
logistics
author_facet Ahmad Esmaeili
Reza Ahmadi Kahnali
Reza Rostamzadeh
Edmundas Kazimieras Zavadskas
Babak Ghoddami
author_sort Ahmad Esmaeili
title An application of fuzzy logic to assess service quality attributes in logistics industry
title_short An application of fuzzy logic to assess service quality attributes in logistics industry
title_full An application of fuzzy logic to assess service quality attributes in logistics industry
title_fullStr An application of fuzzy logic to assess service quality attributes in logistics industry
title_full_unstemmed An application of fuzzy logic to assess service quality attributes in logistics industry
title_sort application of fuzzy logic to assess service quality attributes in logistics industry
publisher Vilnius Gediminas Technical University
series Transport
issn 1648-4142
1648-3480
publishDate 2015-06-01
description Differentiation, growing competitive advantage, and excellence has been proved to be the result of service quality. At the same time, measuring attributes of service quality and customer satisfaction is fuzzy and ambiguous, and methods available for their measurement are generally classical. This paper proposes a fuzzy method to identify the service quality attributes. This approach was developed using crisp assessment methods in a logistics company. Applying the proposed fuzzy approach, service quality attributes and indicators are identified and then organized into 8 categories, to see the uncertainty level of each. The proposed method was successfully conducted in a real logistics company. The results show the membership degree of each indicator, suggesting customer expectations regarding quality. Also, the membership degrees of the service quality attributes suggest the ability of each to describe service quality in logistics industry.
topic fuzzy sets theory
fuzzy entropy
service quality
quality attributes
logistics
url https://journals.vgtu.lt/index.php/Transport/article/view/1773
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