{"title":"在线评论驱动的服务设计 Kano-QFD 方法","authors":"Chen Chen;Chenxi Zhang;Zeshui Xu","doi":"10.1109/TEM.2024.3387579","DOIUrl":null,"url":null,"abstract":"As customer demands continue to evolve, service quality has become increasingly important for service providers. In response, service providers have become more focused on service design and understanding customer requirements (CRs) to gain a competitive advantage. As a method to investigate the characteristics of CRs, the Kano model is often combined with quality function deployment (QFD) to analyze the CRs and translate them into design requirements (DRs). However, previous studies have overlooked the financial status of service providers, which is also essential for service design. To propose a service design method that can be applied to various service industries, this article proposes an online reviews-driven Kano-QFD method for service design. First, CRs are extracted from online reviews. Second, the Kano model is employed to classify CRs and determine their importance, while considering the financial statuses of the service providers. The QFD model is then used to convert CRs into DRs and an optimization model is constructed based on the importance of DRs, and their correlation with CRs. Moreover, a case study is presented to demonstrate the effectiveness of the proposed method in designing hotel services. Finally, the validity of the proposed method for service design is illustrated by comparing it with previous methods.","PeriodicalId":55009,"journal":{"name":"IEEE Transactions on Engineering Management","volume":"71 ","pages":"8153-8165"},"PeriodicalIF":4.6000,"publicationDate":"2024-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Online Reviews-Driven Kano-QFD Method for Service Design\",\"authors\":\"Chen Chen;Chenxi Zhang;Zeshui Xu\",\"doi\":\"10.1109/TEM.2024.3387579\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As customer demands continue to evolve, service quality has become increasingly important for service providers. In response, service providers have become more focused on service design and understanding customer requirements (CRs) to gain a competitive advantage. As a method to investigate the characteristics of CRs, the Kano model is often combined with quality function deployment (QFD) to analyze the CRs and translate them into design requirements (DRs). However, previous studies have overlooked the financial status of service providers, which is also essential for service design. To propose a service design method that can be applied to various service industries, this article proposes an online reviews-driven Kano-QFD method for service design. First, CRs are extracted from online reviews. Second, the Kano model is employed to classify CRs and determine their importance, while considering the financial statuses of the service providers. The QFD model is then used to convert CRs into DRs and an optimization model is constructed based on the importance of DRs, and their correlation with CRs. Moreover, a case study is presented to demonstrate the effectiveness of the proposed method in designing hotel services. Finally, the validity of the proposed method for service design is illustrated by comparing it with previous methods.\",\"PeriodicalId\":55009,\"journal\":{\"name\":\"IEEE Transactions on Engineering Management\",\"volume\":\"71 \",\"pages\":\"8153-8165\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-04-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Engineering Management\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10496849/\",\"RegionNum\":3,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Engineering Management","FirstCategoryId":"91","ListUrlMain":"https://ieeexplore.ieee.org/document/10496849/","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS","Score":null,"Total":0}
Online Reviews-Driven Kano-QFD Method for Service Design
As customer demands continue to evolve, service quality has become increasingly important for service providers. In response, service providers have become more focused on service design and understanding customer requirements (CRs) to gain a competitive advantage. As a method to investigate the characteristics of CRs, the Kano model is often combined with quality function deployment (QFD) to analyze the CRs and translate them into design requirements (DRs). However, previous studies have overlooked the financial status of service providers, which is also essential for service design. To propose a service design method that can be applied to various service industries, this article proposes an online reviews-driven Kano-QFD method for service design. First, CRs are extracted from online reviews. Second, the Kano model is employed to classify CRs and determine their importance, while considering the financial statuses of the service providers. The QFD model is then used to convert CRs into DRs and an optimization model is constructed based on the importance of DRs, and their correlation with CRs. Moreover, a case study is presented to demonstrate the effectiveness of the proposed method in designing hotel services. Finally, the validity of the proposed method for service design is illustrated by comparing it with previous methods.
期刊介绍:
Management of technical functions such as research, development, and engineering in industry, government, university, and other settings. Emphasis is on studies carried on within an organization to help in decision making or policy formation for RD&E.