Title: A full ranking method in data envelopment analysis with multi-criteria decision analysis

Authors: Madjid Tavana; Abbas Bonyani; Tooraj Karimi

Addresses: Business Systems and Analytics Department, Distinguished Chair of Business Analytics, La Salle University, Philadelphia, Pennsylvania, USA; Business Information Systems Department, Faculty of Business Administration and Economics, University of Paderborn, Paderborn, North Rhine-Westphalia, Germany ' Department of Industrial Management, Faculty of Management and Accounting, University of Tehran, Tehran, Iran ' Faculty of Management, College of Farabi, University of Tehran, Tehran, Iran

Abstract: This study presents a new hybrid Multi-Criteria Decision Analysis (MCDA) model for the full ranking of Decision-Making Units (DMUs) with multiple inputs and outputs. The Best-Worst Method (BWM) is used to rank the units, and the Charnes-Cooper-Rhodes (CCR) Data Envelopment Analysis (DEA) model is utilised to construct the pairwise comparison vector. The unit with the lowest efficiency is identified and compared with other units using DEA for each pair of units. Similarly, the unit with the highest efficiency is identified next and compared with the different units. A linear programming problem is formulated and solved to find the optimal weight of the units and rank them. The pairwise comparisons in the proposed BWM-DEA method are highly consistent because of the objective evaluation process. The proposed method has several advantages, including fewer and more consistent comparisons, leading to more reliable results than similar ranking methods in DEA.

Keywords: DEA; data envelopment analysis; MCDA; multi-criteria decision analysis; BWM; best worst method; analytics hierarchy process; pairwise comparison; ranking.

DOI: 10.1504/IJAMS.2025.143653

International Journal of Applied Management Science, 2025 Vol.17 No.1, pp.1 - 26

Received: 18 Jan 2024
Accepted: 28 Feb 2024
Published online: 03 Jan 2025 *

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