Suchergebnisse

PURPOSE: The composite sustainable energy index could prove useful to evaluate both the state of the art and the progress of national energy towards sustainable development. However, different methods and procedures of selection and aggregation of variables can produce different results of index values and the ranking of objects. The objective of the paper is to evaluate different methods of data aggregation. ; DESIGN/METHODOLOGY/APPROACH: We choose three methods, SAW, TOPSIS and VIKOR in order to obtain the Sustainable Energy Development Aggregated Index (SEDAI) to rank the EU Member States. We apply 47 variables and also test the need to reduce variables due to their collinearity. We apply some measures of the quality of indexes and rankings based on linear correlation of the index with the diagnostic variables, as well as the up ratio based on ranks comparison and our modification of up measure (u'p). ; FINDINGS: We found that it is not possible to clearly indicate the method of selection and aggregation of variables that gives optimal ranking, however SAW method is most often indicated as the best method, according to evaluation measures applied in our research. ; PRACTICAL IMPLICATIONS: In this situation, one opportunity is to use the most intuitive SAW method, or we recommend using a set of rankings in order to aggregate the results of different methods as it is used in many machine learning methods. ; ORIGINALITY/VALUE: The added value of the article is the indication of the SAW method as the best one, according to most analyzed quality measures for creating indexes and rankings. Additionally, we propose a measure of the quality of rankings and a method of aggregating indexes obtained with the use of various methods. ; This research was funded by National Science Centre Poland, grant number 2018/29/B/HS4/00561, entitled "Sustainable regional energy – measure of implementation and development strategy selection". ; peer-reviewed