Sustainable Development and Corporate Profitability: Data Mining Approach

Abstract

With the expansion of business activities around the world and the importance of sustainability in various fields, corporate sustainability has become a strategic imperative for management plans and investment decision. Therefore, this study focuses on examining the contribution of sustainability variables, i.e., economic, social, and environmental (ESG), to corporates profitability at 5936 companies distributed globally in an industry sectors using the data mining methods. The data extracted from Thomson Reuters database (ASSET4 ESG) for the period of 2002–2017 was used for modelling. Different algorithms, such as decision tree, support vector machine, and Naïve Bayes, were used for modelling. Since the current study uses a multi-class classification, the Kappa criterion was used to assess the quality of the classification algorithm. The results of the study confirmed that none of the sustainability dimensions had a negative impact on corporate profitability.