Expert Weighting Based Dynamic Eco-efficiency Assessment of World Consumption

Abstract

Optimizing the consumption of natural resources and ensuring the availability of resources for both current and future generations has been the target for sustainability research. This paper aims to assess the eco-efficiency of global resource consumption through the environmental footprint perspective. The study effectively utilized EXIOBASE 3.41, a multi-region input-output (MRIO) database, for collecting data and Multi-criteria decision making (MCDM) approach for eco-efficiency assessment. Besides, the present paper utilizes expert weighting strategies such as EPP, SAB, Harvard, and EQUAL for assigning relative significance to various environmental indicators. Primarily, the data sample represents the influence of environmental stressors like GHG emission, land use, energy use, material consumption, water consumption. The study expands through three major scenarios in terms of importance to the economic and environmental outcomes. As such, with three scenarios and four weighting strategies, twelve situations are considered for the purpose of the study. The study findings indicate that the eco-efficiency score for given weighting strategies concerning economic and environmental impact demonstrates a significant statistical difference. The countries like China, India, Russia, Mexico, and Turkey are worst performing while Switzerland, Japan, UK, Germany, and France are best performing in terms of eco-efficiency score. Finally, k-mean clustering algorithm has applied to rank the countries centered on eco-efficiency score and weighing strategies