R. Septifani, Ardaneswari Dyah Pitaloka Citraresmi, Galuh Melisa Emaradina
{"title":"Application of objective matrix to improve performance green supply chain management","authors":"R. Septifani, Ardaneswari Dyah Pitaloka Citraresmi, Galuh Melisa Emaradina","doi":"10.21776/ub.afssaae.2022.005.02.1","DOIUrl":null,"url":null,"abstract":"The eucalyptus oil factory (PMKP) Sukun Ponorogo is an industry with complex supply chain activities, starting from the raw material’s procurement, production processes, distribution, and reverse logistics. Some of these activities may result in environmental problems. Therefore, measurement of its supply chain management (SCM) performance related to environmental conditions is critical. The green supply chain management (GSCM) concept can help the company to assess the supply chain's performance conditions that could harm the environment. This study aimed to assess the current SCM and measure its performance, as well as to evaluate the potential implementation on GSCM in the PMKP Sukun Ponorogo. The analytical network process (ANP) was used in this study, consisting of 36 key performance indicators (KPI) from five categories of plan, source, deliver, make, and return. The study results show that all KPIs from the responsiveness dimension in the deliver category have the lowest weight, thus require priority for improvement. The results of the scoring system using the objective matrix (OMAX) method indicated two KPIs were in the red category (or need improvement), including on-time delivery of raw materials to production site and the rejection rate of raw materials. This study suggested to improve the estimated delivery time for avoiding any delays during the production process. This improvement may support the company to continuously offer on-time production process and product’s distribution.","PeriodicalId":325722,"journal":{"name":"Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21776/ub.afssaae.2022.005.02.1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The eucalyptus oil factory (PMKP) Sukun Ponorogo is an industry with complex supply chain activities, starting from the raw material’s procurement, production processes, distribution, and reverse logistics. Some of these activities may result in environmental problems. Therefore, measurement of its supply chain management (SCM) performance related to environmental conditions is critical. The green supply chain management (GSCM) concept can help the company to assess the supply chain's performance conditions that could harm the environment. This study aimed to assess the current SCM and measure its performance, as well as to evaluate the potential implementation on GSCM in the PMKP Sukun Ponorogo. The analytical network process (ANP) was used in this study, consisting of 36 key performance indicators (KPI) from five categories of plan, source, deliver, make, and return. The study results show that all KPIs from the responsiveness dimension in the deliver category have the lowest weight, thus require priority for improvement. The results of the scoring system using the objective matrix (OMAX) method indicated two KPIs were in the red category (or need improvement), including on-time delivery of raw materials to production site and the rejection rate of raw materials. This study suggested to improve the estimated delivery time for avoiding any delays during the production process. This improvement may support the company to continuously offer on-time production process and product’s distribution.