Publication
A QFD-MCDM approach considering Kano model under uncertainty, case study: automotive industry in Portugal
| Summary: | In today's competitive market, most companies aim to improve the quality of their products to acquire new customers and to avoid customer churn. Quality Function Deployment (QFD) is a customer-oriented design tool that aims to meet customer needs in a better way and enhance organizational capabilities, while maximizing company goals. The premise that customer satisfaction is a crucial factor that significantly impacts the outcomes of a business, whether successful or unsuccessful, holds significant weight. Hence, it is important to determine those requirements of a product or service that bring more satisfaction than others. QFD and the Kano model can be integrated effectively to identify customer needs more specifically and yield maximum customer satisfaction. This study proposes an improved refined Kano method for identifying and prioritizing customer requirements (CRs) and engineering characteristics (ECs) called supplier attributes (SAs) in this study—integrated into multi-criteria decision-making (MCDM)- QFD process. This model uses fuzzy theory to rank the suppliers, aiming to enhance black uniformity (BU) as a luminance characteristic on the display surface, by evaluating the CRs and developing the SAs related to CRs. The main findings of this study were the identification, classification, and ranking of the CRs of a product in an automotive company due to classifying the SAs to satisfy these CRs, and finally, the ranking of the suppliers. As the initial stage of QFD, converting CRs into ECs and determining the technical importance of ECs are the foundation for the successful implementation of the QFD tool. However, as indicated by many researchers, there exist various shortcomings in conventional QFD, which limit its efficiency and potential applications. The first concern that exists in conventional QFD is quantifying the relationships between CRs and ECs based on crisp (exact) numbers. Obviously, in practical situations, it is often hard for experts to provide their opinions by using exact values due to environmental complexity and limited experience. The second concern refers to the determination of the CRs’ weights based on customers’ evaluations without having a structured pair-wise comparison among CRs. Moreover, ignoring decisionmakers’ preference behavior by using a linear aggregation method in the traditional QFD could be considered as the third concern. On the other hand, determining the crucial ECs in QFD is often regarded as a MCDM problem. To fill this gap of data uncertainty, the current thesis aimed to integrate the Kano model, QFD, and MCDM procedures into a hybrid methodology. |
|---|---|
| Main Authors: | Hariri, Ahmad |
| Subject: | Customer satisfaction Fuzzy theory Kano model Multi-criteria decision making Quality function deployment Desdobramento da função qualidade Modelo Kano Satisfação do cliente Teoria Fuzzy Tomada de decisão multicritério Engenharia e Tecnologia::Outras Engenharias e Tecnologias |
| Year: | 2024 |
| Country: | Portugal |
| Document type: | doctoral thesis |
| Access type: | open access |
| Associated institution: | Universidade do Minho |
| Language: | English |
| Origin: | RepositóriUM - Universidade do Minho |
| _version_ | 1867439498177019904 |
|---|---|
| author | Hariri, Ahmad |
| author_facet | Hariri, Ahmad |
| author_role | author |
| contributor_name_str_mv | Domingues, José Pedro Teixeira Sampaio, Paulo RepositóriUM - Universidade do Minho |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Hariri, Ahmad\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Domingues, José Pedro Teixeira Sampaio, Paulo RepositóriUM - Universidade do Minho |
| datacite.creators.creator.creatorName.fl_str_mv | Hariri, Ahmad |
| datacite.date.Accepted.fl_str_mv | 2024-02-27T00:00:00Z |
| datacite.date.available.fl_str_mv | 2024-05-21T14:54:03Z |
| datacite.date.embargoed.fl_str_mv | 2024-05-21T14:54:03Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | Customer satisfaction Fuzzy theory Kano model Multi-criteria decision making Quality function deployment Desdobramento da função qualidade Modelo Kano Satisfação do cliente Teoria Fuzzy Tomada de decisão multicritério Engenharia e Tecnologia::Outras Engenharias e Tecnologias |
| datacite.titles.title.fl_str_mv | A QFD-MCDM approach considering Kano model under uncertainty, case study: automotive industry in Portugal Uma abordagem QFD-MCDM considerando o modelo Kano sob incerteza, estudo de caso: indústria automóvel em Portugal |
| dc.contributor.none.fl_str_mv | Domingues, José Pedro Teixeira Sampaio, Paulo RepositóriUM - Universidade do Minho |
| dc.creator.none.fl_str_mv | Hariri, Ahmad |
| dc.date.Accepted.fl_str_mv | 2024-02-27T00:00:00Z |
| dc.date.available.fl_str_mv | 2024-05-21T14:54:03Z |
| dc.date.embargoed.fl_str_mv | 2024-05-21T14:54:03Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | https://hdl.handle.net/1822/91436 |
| dc.language.none.fl_str_mv | eng |
| dc.rights.cclincense.fl_str_mv | http://creativecommons.org/licenses/by-sa/4.0/ |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.rights.rights.copyright.fl_str_mv | openAccess |
| dc.subject.none.fl_str_mv | Customer satisfaction Fuzzy theory Kano model Multi-criteria decision making Quality function deployment Desdobramento da função qualidade Modelo Kano Satisfação do cliente Teoria Fuzzy Tomada de decisão multicritério Engenharia e Tecnologia::Outras Engenharias e Tecnologias |
| dc.title.fl_str_mv | A QFD-MCDM approach considering Kano model under uncertainty, case study: automotive industry in Portugal Uma abordagem QFD-MCDM considerando o modelo Kano sob incerteza, estudo de caso: indústria automóvel em Portugal |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_db06 |
| description | In today's competitive market, most companies aim to improve the quality of their products to acquire new customers and to avoid customer churn. Quality Function Deployment (QFD) is a customer-oriented design tool that aims to meet customer needs in a better way and enhance organizational capabilities, while maximizing company goals. The premise that customer satisfaction is a crucial factor that significantly impacts the outcomes of a business, whether successful or unsuccessful, holds significant weight. Hence, it is important to determine those requirements of a product or service that bring more satisfaction than others. QFD and the Kano model can be integrated effectively to identify customer needs more specifically and yield maximum customer satisfaction. This study proposes an improved refined Kano method for identifying and prioritizing customer requirements (CRs) and engineering characteristics (ECs) called supplier attributes (SAs) in this study—integrated into multi-criteria decision-making (MCDM)- QFD process. This model uses fuzzy theory to rank the suppliers, aiming to enhance black uniformity (BU) as a luminance characteristic on the display surface, by evaluating the CRs and developing the SAs related to CRs. The main findings of this study were the identification, classification, and ranking of the CRs of a product in an automotive company due to classifying the SAs to satisfy these CRs, and finally, the ranking of the suppliers. As the initial stage of QFD, converting CRs into ECs and determining the technical importance of ECs are the foundation for the successful implementation of the QFD tool. However, as indicated by many researchers, there exist various shortcomings in conventional QFD, which limit its efficiency and potential applications. The first concern that exists in conventional QFD is quantifying the relationships between CRs and ECs based on crisp (exact) numbers. Obviously, in practical situations, it is often hard for experts to provide their opinions by using exact values due to environmental complexity and limited experience. The second concern refers to the determination of the CRs’ weights based on customers’ evaluations without having a structured pair-wise comparison among CRs. Moreover, ignoring decisionmakers’ preference behavior by using a linear aggregation method in the traditional QFD could be considered as the third concern. On the other hand, determining the crucial ECs in QFD is often regarded as a MCDM problem. To fill this gap of data uncertainty, the current thesis aimed to integrate the Kano model, QFD, and MCDM procedures into a hybrid methodology. |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | doctoralThesis |
| fulltext.url.fl_str_mv | https://repositorium.uminho.pt/bitstreams/b45aa727-6184-46ff-a9b1-40be38d2676c/download |
| id | rum_5f6374d1bc7b06eeafa9bdd2ea170d39 |
| identifier.url.fl_str_mv | https://hdl.handle.net/1822/91436 |
| instacron_str | repositorium |
| institution | Universidade do Minho |
| instname_str | Universidade do Minho |
| language | eng |
| network_acronym_str | rum |
| network_name_str | RepositóriUM - Universidade do Minho |
| oai_identifier_str | oai:repositorium.uminho.pt:1822/91436 |
| organization_str_mv | urn:organizationAcronym:repositorium |
| person_str_mv | Hariri, Ahmad |
| publishDate | 2024 |
| reponame_str | RepositóriUM - Universidade do Minho |
| repository_id_str | urn:repositoryAcronym:rum |
| service_str_mv | urn:repositoryAcronym:rum |
| spelling | engporIn today's competitive market, most companies aim to improve the quality of their products to acquire new customers and to avoid customer churn. Quality Function Deployment (QFD) is a customer-oriented design tool that aims to meet customer needs in a better way and enhance organizational capabilities, while maximizing company goals. The premise that customer satisfaction is a crucial factor that significantly impacts the outcomes of a business, whether successful or unsuccessful, holds significant weight. Hence, it is important to determine those requirements of a product or service that bring more satisfaction than others. QFD and the Kano model can be integrated effectively to identify customer needs more specifically and yield maximum customer satisfaction. This study proposes an improved refined Kano method for identifying and prioritizing customer requirements (CRs) and engineering characteristics (ECs) called supplier attributes (SAs) in this study—integrated into multi-criteria decision-making (MCDM)- QFD process. This model uses fuzzy theory to rank the suppliers, aiming to enhance black uniformity (BU) as a luminance characteristic on the display surface, by evaluating the CRs and developing the SAs related to CRs. The main findings of this study were the identification, classification, and ranking of the CRs of a product in an automotive company due to classifying the SAs to satisfy these CRs, and finally, the ranking of the suppliers. As the initial stage of QFD, converting CRs into ECs and determining the technical importance of ECs are the foundation for the successful implementation of the QFD tool. However, as indicated by many researchers, there exist various shortcomings in conventional QFD, which limit its efficiency and potential applications. The first concern that exists in conventional QFD is quantifying the relationships between CRs and ECs based on crisp (exact) numbers. Obviously, in practical situations, it is often hard for experts to provide their opinions by using exact values due to environmental complexity and limited experience. The second concern refers to the determination of the CRs’ weights based on customers’ evaluations without having a structured pair-wise comparison among CRs. Moreover, ignoring decisionmakers’ preference behavior by using a linear aggregation method in the traditional QFD could be considered as the third concern. On the other hand, determining the crucial ECs in QFD is often regarded as a MCDM problem. To fill this gap of data uncertainty, the current thesis aimed to integrate the Kano model, QFD, and MCDM procedures into a hybrid methodology.application/pdfporA QFD-MCDM approach considering Kano model under uncertainty, case study: automotive industry in PortugalAlternativeTitleporUma abordagem QFD-MCDM considerando o modelo Kano sob incerteza, estudo de caso: indústria automóvel em PortugalHariri, AhmadDomingues, José Pedro TeixeiraSampaio, PauloHostingInstitutionOrganizationalRepositóriUM - Universidade do Minhoe-mailmailto:repositorium@usdb.uminho.ptrepositorium@usdb.uminho.ptTID1016726672024-05-21T14:54:03Z2024-02-2720242024-02-27T00:00:00ZHandlehttps://hdl.handle.net/1822/91436http://purl.org/coar/access_right/c_abf2open accessCustomer satisfactionFuzzy theoryKano modelMulti-criteria decision makingQuality function deploymentDesdobramento da função qualidadeModelo KanoSatisfação do clienteTeoria FuzzyTomada de decisão multicritériohttp://www.oecd.org/science/inno/38235147.pdfFields of Science and Technology (FOS)Engenharia e Tecnologia::Outras Engenharias e Tecnologias7059883 bytesliteraturehttp://purl.org/coar/resource_type/c_db06doctoral thesis2024-02-27http://creativecommons.org/licenses/by-sa/4.0/openAccesshttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://repositorium.uminho.pt/bitstreams/b45aa727-6184-46ff-a9b1-40be38d2676c/download |
| spellingShingle | A QFD-MCDM approach considering Kano model under uncertainty, case study: automotive industry in Portugal Hariri, Ahmad Customer satisfaction Fuzzy theory Kano model Multi-criteria decision making Quality function deployment Desdobramento da função qualidade Modelo Kano Satisfação do cliente Teoria Fuzzy Tomada de decisão multicritério Engenharia e Tecnologia::Outras Engenharias e Tecnologias |
| status | SINGLETON |
| subject.fl_str_mv | Customer satisfaction Fuzzy theory Kano model Multi-criteria decision making Quality function deployment Desdobramento da função qualidade Modelo Kano Satisfação do cliente Teoria Fuzzy Tomada de decisão multicritério |
| subject.other.fl_str_mv | Engenharia e Tecnologia::Outras Engenharias e Tecnologias |
| title | A QFD-MCDM approach considering Kano model under uncertainty, case study: automotive industry in Portugal |
| title_full | A QFD-MCDM approach considering Kano model under uncertainty, case study: automotive industry in Portugal |
| title_fullStr | A QFD-MCDM approach considering Kano model under uncertainty, case study: automotive industry in Portugal |
| title_full_unstemmed | A QFD-MCDM approach considering Kano model under uncertainty, case study: automotive industry in Portugal |
| title_short | A QFD-MCDM approach considering Kano model under uncertainty, case study: automotive industry in Portugal |
| title_sort | A QFD-MCDM approach considering Kano model under uncertainty, case study: automotive industry in Portugal |
| topic | Customer satisfaction Fuzzy theory Kano model Multi-criteria decision making Quality function deployment Desdobramento da função qualidade Modelo Kano Satisfação do cliente Teoria Fuzzy Tomada de decisão multicritério Engenharia e Tecnologia::Outras Engenharias e Tecnologias |
| topic_facet | Customer satisfaction Fuzzy theory Kano model Multi-criteria decision making Quality function deployment Desdobramento da função qualidade Modelo Kano Satisfação do cliente Teoria Fuzzy Tomada de decisão multicritério Engenharia e Tecnologia::Outras Engenharias e Tecnologias |
| url | https://hdl.handle.net/1822/91436 |
| visible | 1 |