{"title":"An interpretive structural modeling approach to enablers of green supply chain management on construction projects","authors":"B. Amade","doi":"10.5267/J.JPM.2021.1.003","DOIUrl":null,"url":null,"abstract":"The objective of this study is to understand and evaluate the interactions of the Green Supply Chain Management enablers from a construction project's perspective in Imo State, Nigeria. This paper discusses the mix of practical intuition and determination through an interpretive structural modeling (ISM)-driven methodology. Eight (8) enablers were identified from a literature review, expert consultation, and real-world examples. While Matrice d’Impacts croisesmultipication applique a classement analysis (MICMAC) was used to identify dependence and driving power, it was used as a way to understand the relationship between the enablers. The study found that strong, yet fragile, forces drive GSCM adoption, with enhanced awareness of GSCM, increased market appeal for green construction projects, and government support through incentives and tax rebates.","PeriodicalId":42333,"journal":{"name":"Journal of Project Management","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Project Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5267/J.JPM.2021.1.003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 1
Abstract
The objective of this study is to understand and evaluate the interactions of the Green Supply Chain Management enablers from a construction project's perspective in Imo State, Nigeria. This paper discusses the mix of practical intuition and determination through an interpretive structural modeling (ISM)-driven methodology. Eight (8) enablers were identified from a literature review, expert consultation, and real-world examples. While Matrice d’Impacts croisesmultipication applique a classement analysis (MICMAC) was used to identify dependence and driving power, it was used as a way to understand the relationship between the enablers. The study found that strong, yet fragile, forces drive GSCM adoption, with enhanced awareness of GSCM, increased market appeal for green construction projects, and government support through incentives and tax rebates.