Research on express service defect evaluation based on semantic network diagram and SERVQUAL model

This paper constructs a defect evaluation model of express service, uses the text mining methods of web crawler, SVM (Support Vector Machine) emotion analysis and LDA (Linear Discriminant Analysis) topic model to capture and clean up the online negative comment data of express service, establishes a...
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Autor*in:	Suishan Gu [verfasserIn] Kangyu Wang [verfasserIn] Lianyue Gao [verfasserIn] Jun Liu [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	express service defects text mining semantic network diagram SERVQUAL model LDA topic model

Übergeordnetes Werk:	In: Frontiers in Public Health - Frontiers Media S.A., 2013, 10(2022)
Übergeordnetes Werk:	volume:10 ; year:2022

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3389/fpubh.2022.1056575

Katalog-ID:	DOAJ085918202

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spelling	10.3389/fpubh.2022.1056575 doi (DE-627)DOAJ085918202 (DE-599)DOAJ2d7f5871981544e1968536a6e2edc89d DE-627 ger DE-627 rakwb eng RA1-1270 Suishan Gu verfasserin aut Research on express service defect evaluation based on semantic network diagram and SERVQUAL model 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper constructs a defect evaluation model of express service, uses the text mining methods of web crawler, SVM (Support Vector Machine) emotion analysis and LDA (Linear Discriminant Analysis) topic model to capture and clean up the online negative comment data of express service, establishes a semantic network diagram, and uses LDA topic model to extract the characteristic words of defect topic. Based on SERVQUAL model, it can classify the subject characteristic words of express service defects from the dimensions of tangibility, reliability, responsiveness, assurance, empathy and economy, etc., calculate the degree value and attention value of express service defects, and establish IPA model for defect mapping and identify the improvement direction. The evaluation model constructed in this paper has reference value for evaluating the defects of service industry and improving service quality. It is found that the “responsiveness” defect is the primary improvement direction, and the reliability, assurance and economy are the secondary improvement defects. Among them, the “responsiveness” defect has five improvement detail defects. The evaluation model constructed in this paper has reference value for evaluating the defects of service industry and improving service quality. express service defects text mining semantic network diagram SERVQUAL model LDA topic model Public aspects of medicine Kangyu Wang verfasserin aut Lianyue Gao verfasserin aut Jun Liu verfasserin aut In Frontiers in Public Health Frontiers Media S.A., 2013 10(2022) (DE-627)742224589 (DE-600)2711781-9 22962565 nnns volume:10 year:2022 https://doi.org/10.3389/fpubh.2022.1056575 kostenfrei https://doaj.org/article/2d7f5871981544e1968536a6e2edc89d kostenfrei https://www.frontiersin.org/articles/10.3389/fpubh.2022.1056575/full kostenfrei https://doaj.org/toc/2296-2565 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2022
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allfieldsSound	10.3389/fpubh.2022.1056575 doi (DE-627)DOAJ085918202 (DE-599)DOAJ2d7f5871981544e1968536a6e2edc89d DE-627 ger DE-627 rakwb eng RA1-1270 Suishan Gu verfasserin aut Research on express service defect evaluation based on semantic network diagram and SERVQUAL model 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper constructs a defect evaluation model of express service, uses the text mining methods of web crawler, SVM (Support Vector Machine) emotion analysis and LDA (Linear Discriminant Analysis) topic model to capture and clean up the online negative comment data of express service, establishes a semantic network diagram, and uses LDA topic model to extract the characteristic words of defect topic. Based on SERVQUAL model, it can classify the subject characteristic words of express service defects from the dimensions of tangibility, reliability, responsiveness, assurance, empathy and economy, etc., calculate the degree value and attention value of express service defects, and establish IPA model for defect mapping and identify the improvement direction. The evaluation model constructed in this paper has reference value for evaluating the defects of service industry and improving service quality. It is found that the “responsiveness” defect is the primary improvement direction, and the reliability, assurance and economy are the secondary improvement defects. Among them, the “responsiveness” defect has five improvement detail defects. The evaluation model constructed in this paper has reference value for evaluating the defects of service industry and improving service quality. express service defects text mining semantic network diagram SERVQUAL model LDA topic model Public aspects of medicine Kangyu Wang verfasserin aut Lianyue Gao verfasserin aut Jun Liu verfasserin aut In Frontiers in Public Health Frontiers Media S.A., 2013 10(2022) (DE-627)742224589 (DE-600)2711781-9 22962565 nnns volume:10 year:2022 https://doi.org/10.3389/fpubh.2022.1056575 kostenfrei https://doaj.org/article/2d7f5871981544e1968536a6e2edc89d kostenfrei https://www.frontiersin.org/articles/10.3389/fpubh.2022.1056575/full kostenfrei https://doaj.org/toc/2296-2565 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2022
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callnumber-first	R - Medicine
author	Suishan Gu
spellingShingle	Suishan Gu misc RA1-1270 misc express service defects misc text mining misc semantic network diagram misc SERVQUAL model misc LDA topic model misc Public aspects of medicine Research on express service defect evaluation based on semantic network diagram and SERVQUAL model
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title	Research on express service defect evaluation based on semantic network diagram and SERVQUAL model
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title_full	Research on express service defect evaluation based on semantic network diagram and SERVQUAL model
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title_auth	Research on express service defect evaluation based on semantic network diagram and SERVQUAL model
abstract	This paper constructs a defect evaluation model of express service, uses the text mining methods of web crawler, SVM (Support Vector Machine) emotion analysis and LDA (Linear Discriminant Analysis) topic model to capture and clean up the online negative comment data of express service, establishes a semantic network diagram, and uses LDA topic model to extract the characteristic words of defect topic. Based on SERVQUAL model, it can classify the subject characteristic words of express service defects from the dimensions of tangibility, reliability, responsiveness, assurance, empathy and economy, etc., calculate the degree value and attention value of express service defects, and establish IPA model for defect mapping and identify the improvement direction. The evaluation model constructed in this paper has reference value for evaluating the defects of service industry and improving service quality. It is found that the “responsiveness” defect is the primary improvement direction, and the reliability, assurance and economy are the secondary improvement defects. Among them, the “responsiveness” defect has five improvement detail defects. The evaluation model constructed in this paper has reference value for evaluating the defects of service industry and improving service quality.
abstractGer	This paper constructs a defect evaluation model of express service, uses the text mining methods of web crawler, SVM (Support Vector Machine) emotion analysis and LDA (Linear Discriminant Analysis) topic model to capture and clean up the online negative comment data of express service, establishes a semantic network diagram, and uses LDA topic model to extract the characteristic words of defect topic. Based on SERVQUAL model, it can classify the subject characteristic words of express service defects from the dimensions of tangibility, reliability, responsiveness, assurance, empathy and economy, etc., calculate the degree value and attention value of express service defects, and establish IPA model for defect mapping and identify the improvement direction. The evaluation model constructed in this paper has reference value for evaluating the defects of service industry and improving service quality. It is found that the “responsiveness” defect is the primary improvement direction, and the reliability, assurance and economy are the secondary improvement defects. Among them, the “responsiveness” defect has five improvement detail defects. The evaluation model constructed in this paper has reference value for evaluating the defects of service industry and improving service quality.
abstract_unstemmed	This paper constructs a defect evaluation model of express service, uses the text mining methods of web crawler, SVM (Support Vector Machine) emotion analysis and LDA (Linear Discriminant Analysis) topic model to capture and clean up the online negative comment data of express service, establishes a semantic network diagram, and uses LDA topic model to extract the characteristic words of defect topic. Based on SERVQUAL model, it can classify the subject characteristic words of express service defects from the dimensions of tangibility, reliability, responsiveness, assurance, empathy and economy, etc., calculate the degree value and attention value of express service defects, and establish IPA model for defect mapping and identify the improvement direction. The evaluation model constructed in this paper has reference value for evaluating the defects of service industry and improving service quality. It is found that the “responsiveness” defect is the primary improvement direction, and the reliability, assurance and economy are the secondary improvement defects. Among them, the “responsiveness” defect has five improvement detail defects. The evaluation model constructed in this paper has reference value for evaluating the defects of service industry and improving service quality.
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title_short	Research on express service defect evaluation based on semantic network diagram and SERVQUAL model
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Research on express service defect evaluation based on semantic network diagram and SERVQUAL model

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