A new method based on fuzzy logic to evaluate the contract service provider performance

This paper puts forward a fuzzy inference system for evaluating the service quality performance of service contract providers. An application service provider (ASP) model for computerized maintenance management was used in establishing common performance indicators of the quality of service. This mo...

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Autores:
Tipo de recurso:
Fecha de publicación:
2008
Institución:
Universidad del Rosario
Repositorio:
Repositorio EdocUR - U. Rosario
Idioma:
eng
OAI Identifier:
oai:repository.urosario.edu.co:10336/22395
Acceso en línea:
https://doi.org/10.1080/03091900701860277
https://repository.urosario.edu.co/handle/10336/22395
Palabra clave:
Arsenic compounds
Contracts
Cost reduction
Fuzzy inference
Fuzzy logic
Fuzzy systems
Maintenance
Application service provider (ASP)
Computerized maintenance
Contract service providers
Fuzzy Inference System (FIS)
Performance indicators
Service contracting
Service quality performance
UK Ltd
(CO)
Quality of service
Article
Biomedical engineering
Computer aided design
Cost benefit analysis
Fuzzy logic
Health care facility
Hospital management
Job performance
Quality control
Quantitative analysis
Scoring system
Worker
Artificial Intelligence
Contract Services
Decision Support Techniques
Fuzzy Logic
Outsourced Services
Program Evaluation
Clinical engineering
Fuzzy logic
Service contract management
Technology management
Rights
License
Abierto (Texto Completo)
id EDOCUR2_1c15db706740cfe3c7bb89f3a974aab5
oai_identifier_str oai:repository.urosario.edu.co:10336/22395
network_acronym_str EDOCUR2
network_name_str Repositorio EdocUR - U. Rosario
repository_id_str
spelling 6cf8e74d-db63-462b-99a0-31933a194a1d-153c8116d-5ce9-4797-9cd0-f151914932b4-19dee7e2d-25bf-46dd-8527-70d06f20042d-12020-05-25T23:56:19Z2020-05-25T23:56:19Z2008This paper puts forward a fuzzy inference system for evaluating the service quality performance of service contract providers. An application service provider (ASP) model for computerized maintenance management was used in establishing common performance indicators of the quality of service. This model was implemented in 10 separate hospitals. As a result, inference produced a service cost/acquisition cost (SC/AC) ratio reduction from 16.14% to 6.09%, an increase of 20.9% in availability, with a maintained repair quality (NRR) in the period of December 2001 to January 2003. © 2008 Informa UK Ltd.application/pdfhttps://doi.org/10.1080/030919007018602773091902https://repository.urosario.edu.co/handle/10336/22395eng314No. 4305Journal of Medical Engineering and TechnologyVol. 32Journal of Medical Engineering and Technology, ISSN:3091902, Vol.32, No.4 (2008); pp. 305-314https://www.scopus.com/inward/record.uri?eid=2-s2.0-48249129736&doi=10.1080%2f03091900701860277&partnerID=40&md5=ee5d3366f49201f2da0ee09165484e03Abierto (Texto Completo)http://purl.org/coar/access_right/c_abf2instname:Universidad del Rosarioreponame:Repositorio Institucional EdocURArsenic compoundsContractsCost reductionFuzzy inferenceFuzzy logicFuzzy systemsMaintenanceApplication service provider (ASP)Computerized maintenanceContract service providersFuzzy Inference System (FIS)Performance indicatorsService contractingService quality performanceUK Ltd(CO)Quality of serviceArticleBiomedical engineeringComputer aided designCost benefit analysisFuzzy logicHealth care facilityHospital managementJob performanceQuality controlQuantitative analysisScoring systemWorkerArtificial IntelligenceContract ServicesDecision Support TechniquesFuzzy LogicOutsourced ServicesProgram EvaluationClinical engineeringFuzzy logicService contract managementTechnology managementA new method based on fuzzy logic to evaluate the contract service provider performancearticleArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501Miguel, C. A.Barr, C.Moreno, M. J. L.10336/22395oai:repository.urosario.edu.co:10336/223952022-05-02 07:37:20.379204https://repository.urosario.edu.coRepositorio institucional EdocURedocur@urosario.edu.co
dc.title.spa.fl_str_mv A new method based on fuzzy logic to evaluate the contract service provider performance
title A new method based on fuzzy logic to evaluate the contract service provider performance
spellingShingle A new method based on fuzzy logic to evaluate the contract service provider performance
Arsenic compounds
Contracts
Cost reduction
Fuzzy inference
Fuzzy logic
Fuzzy systems
Maintenance
Application service provider (ASP)
Computerized maintenance
Contract service providers
Fuzzy Inference System (FIS)
Performance indicators
Service contracting
Service quality performance
UK Ltd
(CO)
Quality of service
Article
Biomedical engineering
Computer aided design
Cost benefit analysis
Fuzzy logic
Health care facility
Hospital management
Job performance
Quality control
Quantitative analysis
Scoring system
Worker
Artificial Intelligence
Contract Services
Decision Support Techniques
Fuzzy Logic
Outsourced Services
Program Evaluation
Clinical engineering
Fuzzy logic
Service contract management
Technology management
title_short A new method based on fuzzy logic to evaluate the contract service provider performance
title_full A new method based on fuzzy logic to evaluate the contract service provider performance
title_fullStr A new method based on fuzzy logic to evaluate the contract service provider performance
title_full_unstemmed A new method based on fuzzy logic to evaluate the contract service provider performance
title_sort A new method based on fuzzy logic to evaluate the contract service provider performance
dc.subject.keyword.spa.fl_str_mv Arsenic compounds
Contracts
Cost reduction
Fuzzy inference
Fuzzy logic
Fuzzy systems
Maintenance
Application service provider (ASP)
Computerized maintenance
Contract service providers
Fuzzy Inference System (FIS)
Performance indicators
Service contracting
Service quality performance
UK Ltd
(CO)
Quality of service
Article
Biomedical engineering
Computer aided design
Cost benefit analysis
Fuzzy logic
Health care facility
Hospital management
Job performance
Quality control
Quantitative analysis
Scoring system
Worker
Artificial Intelligence
Contract Services
Decision Support Techniques
Fuzzy Logic
Outsourced Services
Program Evaluation
Clinical engineering
Fuzzy logic
Service contract management
Technology management
topic Arsenic compounds
Contracts
Cost reduction
Fuzzy inference
Fuzzy logic
Fuzzy systems
Maintenance
Application service provider (ASP)
Computerized maintenance
Contract service providers
Fuzzy Inference System (FIS)
Performance indicators
Service contracting
Service quality performance
UK Ltd
(CO)
Quality of service
Article
Biomedical engineering
Computer aided design
Cost benefit analysis
Fuzzy logic
Health care facility
Hospital management
Job performance
Quality control
Quantitative analysis
Scoring system
Worker
Artificial Intelligence
Contract Services
Decision Support Techniques
Fuzzy Logic
Outsourced Services
Program Evaluation
Clinical engineering
Fuzzy logic
Service contract management
Technology management
description This paper puts forward a fuzzy inference system for evaluating the service quality performance of service contract providers. An application service provider (ASP) model for computerized maintenance management was used in establishing common performance indicators of the quality of service. This model was implemented in 10 separate hospitals. As a result, inference produced a service cost/acquisition cost (SC/AC) ratio reduction from 16.14% to 6.09%, an increase of 20.9% in availability, with a maintained repair quality (NRR) in the period of December 2001 to January 2003. © 2008 Informa UK Ltd.
publishDate 2008
dc.date.created.spa.fl_str_mv 2008
dc.date.accessioned.none.fl_str_mv 2020-05-25T23:56:19Z
dc.date.available.none.fl_str_mv 2020-05-25T23:56:19Z
dc.type.eng.fl_str_mv article
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_6501
dc.type.spa.spa.fl_str_mv Artículo
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1080/03091900701860277
dc.identifier.issn.none.fl_str_mv 3091902
dc.identifier.uri.none.fl_str_mv https://repository.urosario.edu.co/handle/10336/22395
url https://doi.org/10.1080/03091900701860277
https://repository.urosario.edu.co/handle/10336/22395
identifier_str_mv 3091902
dc.language.iso.spa.fl_str_mv eng
language eng
dc.relation.citationEndPage.none.fl_str_mv 314
dc.relation.citationIssue.none.fl_str_mv No. 4
dc.relation.citationStartPage.none.fl_str_mv 305
dc.relation.citationTitle.none.fl_str_mv Journal of Medical Engineering and Technology
dc.relation.citationVolume.none.fl_str_mv Vol. 32
dc.relation.ispartof.spa.fl_str_mv Journal of Medical Engineering and Technology, ISSN:3091902, Vol.32, No.4 (2008); pp. 305-314
dc.relation.uri.spa.fl_str_mv https://www.scopus.com/inward/record.uri?eid=2-s2.0-48249129736&doi=10.1080%2f03091900701860277&partnerID=40&md5=ee5d3366f49201f2da0ee09165484e03
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.acceso.spa.fl_str_mv Abierto (Texto Completo)
rights_invalid_str_mv Abierto (Texto Completo)
http://purl.org/coar/access_right/c_abf2
dc.format.mimetype.none.fl_str_mv application/pdf
institution Universidad del Rosario
dc.source.instname.spa.fl_str_mv instname:Universidad del Rosario
dc.source.reponame.spa.fl_str_mv reponame:Repositorio Institucional EdocUR
repository.name.fl_str_mv Repositorio institucional EdocUR
repository.mail.fl_str_mv edocur@urosario.edu.co
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