Growth in number of population and development nowadays indicate a good sign for nation’s development. However, the development sometimes might neglects the preservation and conservation of nature and can reflects in environment performance. Concerning on this matters, Environmental Performance Index (EPI) has been introduced since 2006 to depict the environment performance for most of the countries in the world. The index considers ten policy categories associated with environmental public health and ecosystem sustainability. The main mathematics operation in establishing EPI is arithmetic mean of all ten policy categories. One of the weaknesses in the arithmetic mean is the operation might neglects some extreme values in data. Recently, Wan Ismail and Abdullah introduced the EPI using analytic hierarchy process (AHP) but the weight of policy category was not considered. This paper proposes a new ranking of EPI using a decision making tool of weighted correlation coefficient based on intuitionistic fuzzy sets (IFS). An original data of policy categories were converted into IFSs which benefiting in considering two-sided of membership and non membership. Criteria weights for alternatives in fuzzy correlation coefficient were utilized to set new EPI for nine ASEAN countries. A new ranking EPI among ASEAN countries show that Thailand is the highest EPI followed by Malaysia. The new ranking may offer an alternative measure in evaluating environmental performance particularly for ASEAN countries.

Abstract:Weighted correlation coefficient is one of the methods for intuitionistic fuzzy sets based multi-criteria decision making (IFS-MCDM). It uses a method of entropy to find criteria weights for alternatives. Entropy weight that employed the arithmetic operations of addition and subtraction in IFS memberships is used for establishing the weighted correlation coefficient. However, the entropy obtained from the use of the arithmetic operations may deprive the significance of membership degree, non-membership degree and hesitation degree of IFS. This paper proposes a sine function entropy weight for measuring weighted correlation coefficients of IFS-MCDM. An example is given to illustrate the proposed method. The comparison results are also presented to show the feasibility and effectiveness of the proposed sine function entropy weight.