{"title":"A fuzzy synthetic evaluation of capabilities for improving supply chain resilience of industrialised construction: a Hong Kong case study","authors":"E. Ekanayake, Geoffrey Q. P. Shen, M. Kumaraswamy","doi":"10.1080/09537287.2021.1946330","DOIUrl":null,"url":null,"abstract":"Abstract Inspired by multiple benefits, including competitive advantages from developing resilient supply chains, this study was designed for the development of effective assessment models to evaluate Supply Chain Capabilities (SCC), improving resilience in Industrialised Construction (IC) in one of the high-density cities: Hong Kong (HK). First identifying appropriate SCC, this study aimed to develop multi-stage-mathematical models to evaluate the adoption of SCC of IC in HK. Experts’ judgements were solicited and analysed using fuzzy synthetic evaluation. Forty-one measurement items were grouped under nine critical SCC components, and their ‘importance’ and ‘current practice’ indices were determined. The importance index of SCC is high, spotlighting the significance of the contribution of SCC to resilience whereas the current practice index is comparatively low, highlighting the dire need to bridge this gap with capability improvements. To the authors' knowledge, these evaluation models are the first set of structured models designed to assess SCC of IC, providing valuable insights to practitioners for well-informed decision-making in formulating strategies to initiate and nurture resilient supply chains in IC in HK.","PeriodicalId":20627,"journal":{"name":"Production Planning & Control","volume":"38 1","pages":"623 - 640"},"PeriodicalIF":6.1000,"publicationDate":"2021-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Production Planning & Control","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1080/09537287.2021.1946330","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 12
Abstract
Abstract Inspired by multiple benefits, including competitive advantages from developing resilient supply chains, this study was designed for the development of effective assessment models to evaluate Supply Chain Capabilities (SCC), improving resilience in Industrialised Construction (IC) in one of the high-density cities: Hong Kong (HK). First identifying appropriate SCC, this study aimed to develop multi-stage-mathematical models to evaluate the adoption of SCC of IC in HK. Experts’ judgements were solicited and analysed using fuzzy synthetic evaluation. Forty-one measurement items were grouped under nine critical SCC components, and their ‘importance’ and ‘current practice’ indices were determined. The importance index of SCC is high, spotlighting the significance of the contribution of SCC to resilience whereas the current practice index is comparatively low, highlighting the dire need to bridge this gap with capability improvements. To the authors' knowledge, these evaluation models are the first set of structured models designed to assess SCC of IC, providing valuable insights to practitioners for well-informed decision-making in formulating strategies to initiate and nurture resilient supply chains in IC in HK.
期刊介绍:
Production Planning & Control is an international journal that focuses on research papers concerning operations management across industries. It emphasizes research originating from industrial needs that can provide guidance to managers and future researchers. Papers accepted by "Production Planning & Control" should address emerging industrial needs, clearly outlining the nature of the industrial problem. Any suitable research methods may be employed, and each paper should justify the method used. Case studies illustrating international significance are encouraged. Authors are encouraged to relate their work to existing knowledge in the field, particularly regarding its implications for management practice and future research agendas.