A Review of Uncertain Decision-Making Methods in Energy Management Using Text Mining and Data Analytics

The managerial and environmental studies conducted in the energy research area reflect its substantial importance, particularly when optimizing and modifying consumption patterns, transitioning to renewable sources away from fossil ones, and designing plans and systems. The aim of this study is to provide a systematic review of the literature allowing us to identify which research subjects have been prioritized in the fields of energy and sustainability in recent years, determine the potential reasons explaining these trends, and categorize the techniques applied to analyze the uncertainty faced by decision-makers. We review articles published in highly ranked journals through the period 2003–2020 and apply text analytics to cluster their main characteristics; that is, we rely on pre-processing and text mining techniques. We analyze the title, abstract, keywords, and research methodology of the articles through clustering and topic modeling and illustrate what methods and fields constitute the main focus of researchers. We demonstrate the substantial importance of fuzzy-related methods and decision-making techniques such as the Analytical Hierarchy Process and Technique for Order Preferences by Similarity to Ideal Solutions (TOPSIS). We also show that subjects such as renewable energy, energy planning, sustainable energy, energy policy, and wind energy have gained relevance among researchers in recent years.