Using AHP-Entropy weight and TOPSIS methodology in green supplier selection

Strategies that balance economic and environmental performance are increasingly sought after as enterprises focus more and more on the sustainability of their operations. Green supply chain management (GSCM) in particular, enables the integration of environmentally-friendly suppliers into the supply chain to be systematised to fit with specific environmental regulations and policies (Rao, 2002). More to the point, GSCM allows enterprises to improve profits whilst lowering impacts on the global environment (Van Hock and Erasmus, 2000). The purpose of the research is to develop a green supplier selection model using an index system based on a combination of traditional supplier and environmental supplier selection criteria. Four categories of supplier selection model feature prominently in the literature, namely:1. Linear-weighting models / Analytical hierarchy process (AHP)2. Mathematical programming models3. Total cost ownership (TCO) models4. DEA, ABC and other modelsEach has its strengths and weaknesses. AHP (Saaty, 1980) - the focus of this paper - is especially popular for dealing with multiple criteria decision making (MCDM) problems. However, AHP requires data which, reflecting experience, judgement and knowledge, are often of a subjective nature. What is more, if a new criterion is added to the AHP model, the calculation process has to start all over again. To overcome these drawbacks, the Entropy weight method (Shannon, 1948) was used in conjunction with AHP to form a comprehensive index system which allowed for objective and subjective weights simultaneously. These compromised weights were then used with the TOPSIS method (Hwang and Yoon, 1981) to determine the most appropriate supplier selection. Based on the latter, a prototype model was developed for an electrical SME located in China. The modified Delphi method was used to supply the AHP subjective criteria weights. Correspondingly, the snowball sampling method was used to generate the practical data needed for calculating the Entropy objective criteria weights.The new AHP-Entropy approach shows that traditional criteria weights are much higher than those for the environmental criteria. This indicates that the senior managers of this case company still consider that product quality, component price and delivery performance are more important than GSCM-related factors. The implication, therefore, is that until the economic benefits of sustainability are fully understood, it may take some time before environmental awareness can be fully assimilated into GSCM practice.The α parameter used to represent the AHP subjective weight’s importance in the compromised weight can be critical to the rankings obtained – emphasising how crucial sensitivity analysis is to the new method as it is with traditional AHP. The paper moves us a significant step closer to the application more widely, of AHP-Entropy / TOPSIS methodology to real-world situations.ReferencesHwang, C.L. and Yoon, K. (1981), Multiple Attribute Decision Making: Methods and Applications (Lecture Notes in Economics and Mathematical Systems), (1st edition), New York: Springer.Rao, P. (2002), “Greening the supply chain a new initiative in south East Asia”. International Journal of Operations & Production Management, 22:6, 632-655.Saaty, T. L. (1980), The analytic hierarchy process: planning, priority setting, resource allocation, (1st edition), New York: McGraw-Hill.Shannon, Claude E. (July/October 1948). A Mathematical Theory of Communication. Bell System Technical Journal 27 (3): 379–423.Van Hock, R. I. & Erasmus (2000), “From reversed logistics to green supply chains”. Logistics Solutions, 2, 28-33.