Dynamic evaluation of operational, environmental, and unified efficiencies: A DEA application in agriculture

Data Envelopment Analysis (DEA) is a prominent tool used to assess the efficiency of decision-making units (DMUs). While static DEA models measure performance without considering time dependency, dynamic DEA incorporates time as a factor in the modeling. In recent years, environmental concerns have become a significant focus for the world community. In the context of DEA, these concerns are often expressed as undesirable outputs of the production process. Therefore, in addition to evaluating operational efficiency, it is essential to consider environmental efficiency to obtain a comprehensive measurement of DMUs’ performance. This paper presents the assessment of operational and environmental efficiency and their integration into a unified efficiency measure within the dynamic DEA framework. The time dependency of efficiency is taken into account and the links between consecutive time periods are categorized as either good or bad types. Additionally, static environmental models are established to enable comparison of dynamic and static efficiency. The proposed models are used to evaluate the performance of twenty-one countries in the agriculture sector. In this study, GHG emissions and cumulative agricultural loss due to disasters are selected as undesirable factors. Environmental efficiency generally improves over 2016–2018; however, while the static assessment shows steady progress, the dynamic assessment rises until 2017 and then slightly declines in 2018. The number of efficient countries in the operational dimension is much more than those in the environmental dimension, which shows that the economic dimension has a higher priority among countries.