Causal sustainable resource management model using a hierarchical structure and linguistic preferences

Abstract

Issues associated with resource exhaustion and climate change continue to worsen, and sustainable resource management is considered a method of resolving these problems. However, academia and industry have primarily focused on managing sustainable production and consumption and neglected resource management model. In addition, an appropriate tool must be developed for evaluating sustainable resource management model that considers the interrelationships and provides a guideline for performance improvement. This study proposes the application of an exploratory factor analysis to filter potential measures and the generation of a hybrid fuzzy synthetic method and decision-making and trial evaluation laboratory to assess the performance via a visual attribute map. The results demonstrate that social resources must prioritize and interact with environmental resources and indicate that economic resources are interrelated with social and environmental resources. Hence, this study enhances the understanding of causal sustainable resource management model by proposing a hybrid method for assessing performance via a hierarchical structure and offering a guideline to assist in performance improvements.