Hierarchical non-Archimedean DEA models: application on mobile money agents locations in the city of Harare
by Jacob Muvingi; Arshad Ahmud Iqbal Peer; Farhad Hosseinzadeh Lotfi
International Journal of Data Science (IJDS), Vol. 5, No. 3, 2020

Abstract: Hierarchical non-Archimedean data envelopment analysis (DEA) models are proposed to evaluate the efficiency of two types of decision making units (DMUs) which are integrated. The determination of non-Archimedean values was extended to cater for DMUs with a hierarchical group structure. The proposed approach was applied in the location analysis of mobile money agents' (MMA) locations. In a bid to improve adjusted efficiency ratings of DMUs in groups with unequal size, an adjustment value on selected groups' average efficiency ratings was determined through identification of ideal location groups proxies. Three district location efficiency ratings (DLER-1, DLER-2 and DLER-3), were respectively generated through the non-Archimedean DEA hierarchical method, the DEA hierarchical method where the non-Archimedean epsilon is ignored, and the treatment of district locations as a system made-up of suburb locations. The application of the non-Archimedean value on district locations efficiency analysis reduced the number of efficient district locations.

Online publication date: Tue, 16-Feb-2021

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