Country and company sustainable supply chain management by using multiple-criteria decision making approaches
| dc.contributor.author | Kim, Heather Hyein | |
| dc.contributor.examiningcommittee | Bhatt, Suresh (Supply Chain Management) Gajpal, Yuvraj (Supply Chain Management) Mandal, Saumen (Statistics) | en_US |
| dc.contributor.supervisor | Appadoo, Srimantoorao. S. (Supply Chain Management) | en_US |
| dc.date.accessioned | 2015-09-17T14:43:38Z | |
| dc.date.available | 2015-09-17T14:43:38Z | |
| dc.date.issued | 2015 | |
| dc.degree.discipline | Management | en_US |
| dc.degree.level | Master of Science (M.Sc.) | en_US |
| dc.description.abstract | Economic, social, and environmental uncertainty plays a crucial role in the implementation of supply chain management. Herein, the present study establishes sustainable supply chain management indices (SSCMI) including Logistical Performance Index (LPI) and Worldwide Governance Index (WGI) along with the sustainability indices adopted from Bilbao-Terol (2014): Adjusted Net Savings (ANS), Ecological Footprints (EF), Environmental Performance Index (EPI), and Human Development Index (HDI). All data used in the present work are publically available from reliable sources such as the World Bank, the Global Footprint Network, and the Yale University. Three sets of data are compared; Triple-Bottom Line (TBL), TBL+LPI, and SSCMI. TBL includes four indices adopted from Bilbao-Terol (2014), TBL+LPI adds LPI to TBL, and SSCMI adds WGI to TBL+LPI. Equal weights, Analytic Hierarchy Process (AHP), and the Technique for Order Preferences by Similarity to Ideal Solution (TOPSIS) are applied to three different datasets and compare sustainability rankings. The results are mapped into a world map for geographical visualization. Sustainability reports of Heineken Company from 22 countries are collected and empirical data are extracted and examined. The comparison of country and company sustainable supply chain management is not analyzed due to a lack of company information. However, in the presence of complete data from company sustainability reports, the analysis used in this thesis is practical and useful to observe relationship between country and company sustainable supply chain management. | en_US |
| dc.description.note | October 2015 | en_US |
| dc.identifier.uri | http://hdl.handle.net/1993/30820 | |
| dc.language.iso | eng | en_US |
| dc.rights | open access | en_US |
| dc.subject | Sustainability | en_US |
| dc.subject | Sustainable supply chain management indices (SSCMI) | en_US |
| dc.subject | Supply chain management | en_US |
| dc.subject | Multiple-criteria decision making (MCDM) | en_US |
| dc.subject | Analytic Hierarchy Process(AHP) | en_US |
| dc.subject | Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) | en_US |
| dc.title | Country and company sustainable supply chain management by using multiple-criteria decision making approaches | en_US |
| dc.type | master thesis | en_US |