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...
Main Authors: | , , , , |
---|---|
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 |
id |
doaj-b9c8007aeb5d4070ad57c4acf385d613 |
---|---|
record_format |
Article |
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 |
work_keys_str_mv |
AT ahmadesmaeili anapplicationoffuzzylogictoassessservicequalityattributesinlogisticsindustry AT rezaahmadikahnali anapplicationoffuzzylogictoassessservicequalityattributesinlogisticsindustry AT rezarostamzadeh anapplicationoffuzzylogictoassessservicequalityattributesinlogisticsindustry AT edmundaskazimieraszavadskas anapplicationoffuzzylogictoassessservicequalityattributesinlogisticsindustry AT babakghoddami anapplicationoffuzzylogictoassessservicequalityattributesinlogisticsindustry AT ahmadesmaeili applicationoffuzzylogictoassessservicequalityattributesinlogisticsindustry AT rezaahmadikahnali applicationoffuzzylogictoassessservicequalityattributesinlogisticsindustry AT rezarostamzadeh applicationoffuzzylogictoassessservicequalityattributesinlogisticsindustry AT edmundaskazimieraszavadskas applicationoffuzzylogictoassessservicequalityattributesinlogisticsindustry AT babakghoddami applicationoffuzzylogictoassessservicequalityattributesinlogisticsindustry |
_version_ |
1721337970258083840 |