Improving Service Quality With the Fuzzy TOPSIS Method: A Case Study of the Beijing Rail Transit System

Rail transit (RT) has been favored by passengers because it effectively alleviates the problems of dense population, housing shortages, small natural areas, and serious air pollution in urban centers. In this paper, we propose a framework that combines statistical analysis, fuzzy theory, and the tec...
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Autor*in:	Jianmin Li [verfasserIn] Xinyue Xu [verfasserIn] Zhenxing Yao [verfasserIn] Yi Lu [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Schlagwörter:	Rail transit fuzzy theory TOPSIS service quality

Übergeordnetes Werk:	In: IEEE Access - IEEE, 2014, 7(2019), Seite 114271-114284
Übergeordnetes Werk:	volume:7 ; year:2019 ; pages:114271-114284

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1109/ACCESS.2019.2932779

Katalog-ID:	DOAJ023581964

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spelling	10.1109/ACCESS.2019.2932779 doi (DE-627)DOAJ023581964 (DE-599)DOAJ3015ddcc057c45d68c7bfffa0d880adb DE-627 ger DE-627 rakwb eng TK1-9971 Jianmin Li verfasserin aut Improving Service Quality With the Fuzzy TOPSIS Method: A Case Study of the Beijing Rail Transit System 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Rail transit (RT) has been favored by passengers because it effectively alleviates the problems of dense population, housing shortages, small natural areas, and serious air pollution in urban centers. In this paper, we propose a framework that combines statistical analysis, fuzzy theory, and the technique for order preference by similarity to an ideal solution (TOPSIS) to evaluate the service quality of RT. First, the passenger perception of service quality is modeled as trapezoidal fuzzy numbers from the fuzzy theory, which solves the uncertainty problem of passenger perception that how factors affect service quality. Next, a case study that evaluates the service quality of the Beijing metro system is proposed using the fuzzy TOPSIS method. During the evaluation process, 8011 surveys are collected from 16 metro lines operated by Beijing Metro Operating Company Ltd. The evaluation results show that transfers, in-vehicle experience, and ticket purchases or recharges are the three factors that passengers find most unsatisfactory about metro travel and that need to be greatly improved in the future construction and management of metros. Furthermore, we analyze the stableness of the fuzzy TOPSIS method by the ranking change of service quality for a line from different comparison sets of metro lines. Finally, we provide suggestions and guidance for the optimization of RT infrastructure and investment. Rail transit fuzzy theory TOPSIS service quality Electrical engineering. Electronics. Nuclear engineering Xinyue Xu verfasserin aut Zhenxing Yao verfasserin aut Yi Lu verfasserin aut In IEEE Access IEEE, 2014 7(2019), Seite 114271-114284 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:7 year:2019 pages:114271-114284 https://doi.org/10.1109/ACCESS.2019.2932779 kostenfrei https://doaj.org/article/3015ddcc057c45d68c7bfffa0d880adb kostenfrei https://ieeexplore.ieee.org/document/8786155/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2019 114271-114284
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allfieldsGer	10.1109/ACCESS.2019.2932779 doi (DE-627)DOAJ023581964 (DE-599)DOAJ3015ddcc057c45d68c7bfffa0d880adb DE-627 ger DE-627 rakwb eng TK1-9971 Jianmin Li verfasserin aut Improving Service Quality With the Fuzzy TOPSIS Method: A Case Study of the Beijing Rail Transit System 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Rail transit (RT) has been favored by passengers because it effectively alleviates the problems of dense population, housing shortages, small natural areas, and serious air pollution in urban centers. In this paper, we propose a framework that combines statistical analysis, fuzzy theory, and the technique for order preference by similarity to an ideal solution (TOPSIS) to evaluate the service quality of RT. First, the passenger perception of service quality is modeled as trapezoidal fuzzy numbers from the fuzzy theory, which solves the uncertainty problem of passenger perception that how factors affect service quality. Next, a case study that evaluates the service quality of the Beijing metro system is proposed using the fuzzy TOPSIS method. During the evaluation process, 8011 surveys are collected from 16 metro lines operated by Beijing Metro Operating Company Ltd. The evaluation results show that transfers, in-vehicle experience, and ticket purchases or recharges are the three factors that passengers find most unsatisfactory about metro travel and that need to be greatly improved in the future construction and management of metros. Furthermore, we analyze the stableness of the fuzzy TOPSIS method by the ranking change of service quality for a line from different comparison sets of metro lines. Finally, we provide suggestions and guidance for the optimization of RT infrastructure and investment. Rail transit fuzzy theory TOPSIS service quality Electrical engineering. Electronics. Nuclear engineering Xinyue Xu verfasserin aut Zhenxing Yao verfasserin aut Yi Lu verfasserin aut In IEEE Access IEEE, 2014 7(2019), Seite 114271-114284 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:7 year:2019 pages:114271-114284 https://doi.org/10.1109/ACCESS.2019.2932779 kostenfrei https://doaj.org/article/3015ddcc057c45d68c7bfffa0d880adb kostenfrei https://ieeexplore.ieee.org/document/8786155/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2019 114271-114284
allfieldsSound	10.1109/ACCESS.2019.2932779 doi (DE-627)DOAJ023581964 (DE-599)DOAJ3015ddcc057c45d68c7bfffa0d880adb DE-627 ger DE-627 rakwb eng TK1-9971 Jianmin Li verfasserin aut Improving Service Quality With the Fuzzy TOPSIS Method: A Case Study of the Beijing Rail Transit System 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Rail transit (RT) has been favored by passengers because it effectively alleviates the problems of dense population, housing shortages, small natural areas, and serious air pollution in urban centers. In this paper, we propose a framework that combines statistical analysis, fuzzy theory, and the technique for order preference by similarity to an ideal solution (TOPSIS) to evaluate the service quality of RT. First, the passenger perception of service quality is modeled as trapezoidal fuzzy numbers from the fuzzy theory, which solves the uncertainty problem of passenger perception that how factors affect service quality. Next, a case study that evaluates the service quality of the Beijing metro system is proposed using the fuzzy TOPSIS method. During the evaluation process, 8011 surveys are collected from 16 metro lines operated by Beijing Metro Operating Company Ltd. The evaluation results show that transfers, in-vehicle experience, and ticket purchases or recharges are the three factors that passengers find most unsatisfactory about metro travel and that need to be greatly improved in the future construction and management of metros. Furthermore, we analyze the stableness of the fuzzy TOPSIS method by the ranking change of service quality for a line from different comparison sets of metro lines. Finally, we provide suggestions and guidance for the optimization of RT infrastructure and investment. Rail transit fuzzy theory TOPSIS service quality Electrical engineering. Electronics. Nuclear engineering Xinyue Xu verfasserin aut Zhenxing Yao verfasserin aut Yi Lu verfasserin aut In IEEE Access IEEE, 2014 7(2019), Seite 114271-114284 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:7 year:2019 pages:114271-114284 https://doi.org/10.1109/ACCESS.2019.2932779 kostenfrei https://doaj.org/article/3015ddcc057c45d68c7bfffa0d880adb kostenfrei https://ieeexplore.ieee.org/document/8786155/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2019 114271-114284
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callnumber-first	T - Technology
author	Jianmin Li
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topic	misc TK1-9971 misc Rail transit misc fuzzy theory misc TOPSIS misc service quality misc Electrical engineering. Electronics. Nuclear engineering
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title	Improving Service Quality With the Fuzzy TOPSIS Method: A Case Study of the Beijing Rail Transit System
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title_auth	Improving Service Quality With the Fuzzy TOPSIS Method: A Case Study of the Beijing Rail Transit System
abstract	Rail transit (RT) has been favored by passengers because it effectively alleviates the problems of dense population, housing shortages, small natural areas, and serious air pollution in urban centers. In this paper, we propose a framework that combines statistical analysis, fuzzy theory, and the technique for order preference by similarity to an ideal solution (TOPSIS) to evaluate the service quality of RT. First, the passenger perception of service quality is modeled as trapezoidal fuzzy numbers from the fuzzy theory, which solves the uncertainty problem of passenger perception that how factors affect service quality. Next, a case study that evaluates the service quality of the Beijing metro system is proposed using the fuzzy TOPSIS method. During the evaluation process, 8011 surveys are collected from 16 metro lines operated by Beijing Metro Operating Company Ltd. The evaluation results show that transfers, in-vehicle experience, and ticket purchases or recharges are the three factors that passengers find most unsatisfactory about metro travel and that need to be greatly improved in the future construction and management of metros. Furthermore, we analyze the stableness of the fuzzy TOPSIS method by the ranking change of service quality for a line from different comparison sets of metro lines. Finally, we provide suggestions and guidance for the optimization of RT infrastructure and investment.
abstractGer	Rail transit (RT) has been favored by passengers because it effectively alleviates the problems of dense population, housing shortages, small natural areas, and serious air pollution in urban centers. In this paper, we propose a framework that combines statistical analysis, fuzzy theory, and the technique for order preference by similarity to an ideal solution (TOPSIS) to evaluate the service quality of RT. First, the passenger perception of service quality is modeled as trapezoidal fuzzy numbers from the fuzzy theory, which solves the uncertainty problem of passenger perception that how factors affect service quality. Next, a case study that evaluates the service quality of the Beijing metro system is proposed using the fuzzy TOPSIS method. During the evaluation process, 8011 surveys are collected from 16 metro lines operated by Beijing Metro Operating Company Ltd. The evaluation results show that transfers, in-vehicle experience, and ticket purchases or recharges are the three factors that passengers find most unsatisfactory about metro travel and that need to be greatly improved in the future construction and management of metros. Furthermore, we analyze the stableness of the fuzzy TOPSIS method by the ranking change of service quality for a line from different comparison sets of metro lines. Finally, we provide suggestions and guidance for the optimization of RT infrastructure and investment.
abstract_unstemmed	Rail transit (RT) has been favored by passengers because it effectively alleviates the problems of dense population, housing shortages, small natural areas, and serious air pollution in urban centers. In this paper, we propose a framework that combines statistical analysis, fuzzy theory, and the technique for order preference by similarity to an ideal solution (TOPSIS) to evaluate the service quality of RT. First, the passenger perception of service quality is modeled as trapezoidal fuzzy numbers from the fuzzy theory, which solves the uncertainty problem of passenger perception that how factors affect service quality. Next, a case study that evaluates the service quality of the Beijing metro system is proposed using the fuzzy TOPSIS method. During the evaluation process, 8011 surveys are collected from 16 metro lines operated by Beijing Metro Operating Company Ltd. The evaluation results show that transfers, in-vehicle experience, and ticket purchases or recharges are the three factors that passengers find most unsatisfactory about metro travel and that need to be greatly improved in the future construction and management of metros. Furthermore, we analyze the stableness of the fuzzy TOPSIS method by the ranking change of service quality for a line from different comparison sets of metro lines. Finally, we provide suggestions and guidance for the optimization of RT infrastructure and investment.
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title_short	Improving Service Quality With the Fuzzy TOPSIS Method: A Case Study of the Beijing Rail Transit System
url	https://doi.org/10.1109/ACCESS.2019.2932779 https://doaj.org/article/3015ddcc057c45d68c7bfffa0d880adb https://ieeexplore.ieee.org/document/8786155/ https://doaj.org/toc/2169-3536
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