Please use this identifier to cite or link to this item: http://ithesis-ir.su.ac.th/dspace/handle/123456789/5859
Title: ANALYTIC NETWORK PROCESS FOR GREEN SUPPLIER SELECTION: A CASE OF A CONSTRUCTION PROJECT
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Authors: Ran YANG
Ran Yang
Noppakun Sangkhiew
นพคุณ แสงเขียว
Silpakorn University
Noppakun Sangkhiew
นพคุณ แสงเขียว
Sangkhiew_n@silpakorn.edu
Sangkhiew_n@silpakorn.edu
Keywords: Analytic network process
multi-criteria decision analysis
decision science
construction industry
green supply chain
Issue Date:  22
Publisher: Silpakorn University
Abstract: Supplier selection is a fundamental problem within the field of decision science. Occasionally, it can be intricate and ambiguous. This study aims to address a complex decision problem, specifically the selection of environmentally-friendly suppliers. Given green materials' scarcity, uncertainty, and interdependence, the most suitable approach to address this issue is the analytic network process technique. The study commenced by conducting a comprehensive examination of the elements involved in selecting environmentally-friendly suppliers as documented in the existing body of literature. Subsequently, five individuals responsible for making decisions in the construction company sample confirmed the existence of five clusters based on fifteen criteria, utilizing the item objective congruence index. Subsequently, the four-step procedure of the analytic network approach was utilized to assess and analyze three suppliers that specialize in environmentally friendly products: local, regional, and international. The results indicate that the regional supplier had the highest local weight, measured at 0.4503. Furthermore, the criterion of material pricing had the most significance among all the criteria. The three orders were ranked based on three factors: GHG emission technology, ordering cost, and delivery cost, with corresponding global weights of 0.1360, 0.1148, and 0.1010. This study demonstrates the advantages of utilizing the analytic network approach. This method effectively resolves intricate decision-making scenarios involving multiple criteria, mainly when the criteria are interdependent.
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URI: http://ithesis-ir.su.ac.th/dspace/handle/123456789/5859
Appears in Collections:Engineering and Industrial Technology

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