Efficiency Analysis and Estimation of Factors Affecting the Efficiency with Decision Trees in Imbalanced Data: A Case of Turkey’s Environmental Sustainability
Abstract
Cities have proliferated and experienced increasing environmental issues in the modern world. The concept of environmental sustainability is one of the main problems to solve. Therefore, it is fundamental to establish statistical methods to measure environmental sustainability. The first aim of this study is to measure the environmental sustainability performance of 42 cities in Turkey by Data Envelopment Analysis. The second aim is to solve the imbalance in the efficiency values obtained using Synthetic Minority Oversampling Technique methods. After all, we expose the multiple relationships between input and output variables and efficiency using the Decision trees classifiers approach. As a result of the analyses, three internal factors were found to influence the environmental efficiency levels: residential sales, population intensity, and the number of completed industrial sites. It has been determined that the number of completed industrial sites and the increase in residential sales distorted environmental efficiency.
Keywords
Classification, decision trees, DEA, environmental sustainability, imbalanced data, SMOTE
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