Network DEA Models with Stochastic Data to Assess the Sustainability Performance of Agricultural Practices: An Application for Sistan and Baluchestan Province in Iran

Abstract

This article aims to determine the sustainability of agricultural performance in the cities of Sistan and Baluchestan Province of Iran by introducing a new network structure with weight restrictions in the presence of stochastic data by data envelopment analysis (DEA). Given that the functional structure of agriculture has many details, a closer and deeper look into the performance complexities can lead to a more realistic evaluation of efficiency. Therefore, the cities of Sistan and Baluchestan provinces are considered network units with weight restrictions to determine sustainability based on the environmental, social, and economic aspects. Agricultural practices were divided into two stages: the environmental stage (planting and maintaining) and the economic stage (harvesting), which use shared resources. On the other hand, DEA mainly treats all data as deterministic. Since there is a large amount of data in different periods of various actual-world problems, the use of stochastic programming approaches in DEA is of great importance for studying the behavior of this volume of data. Regarding data collected from agricultural activities in 5 periods and stochastic DEA, new network DEA models were proposed in this article to determine the sustainability levels of agricultural practices.