American Journal of Operations Research, 2014, 4, 268-279 Published Online July 2014 in SciRes. http://www.scirp.org/journal/ajor http://dx.doi.org/10.4236/ajor.2014.44026 How to cite this paper: Pakkar, M.S. (2014) Using DEA and AHP for Ratio Analysis. American Journal of Operations Research, 4, 268-279. http://dx.doi.org/10.4236/ajor.2014.44026 Using DEA and AHP for Ratio Analysis Mohammad Sadegh Pakkar Faculty of Management, Laurentian University, Sudbury, Canada Email: ms_pakkar@laurentian.ca Received 26 May 2014; revised 2 July 2014; accepted 10 July 2014 Copyright © 2014 by author and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/ Abstract This research proposes an integrated approach to the Data Envelopment Analysis (DEA) and Ana- lytic Hierarchy Process (AHP) methodologies for ratio analysis. According to this, we compute two sets of weights of ratios in the DEA framework. All ratios are treated as outputs without explicit inputs. The first set of weights represents the most attainable efficiency level for each Decision Making Unit (DMU) in comparison to the other DMUs. The second set of weights represents the relative priority of output-ratios using AHP. We assess the performance of each DMU in terms of the relative closeness to the priority weights of output-ratios. For this purpose, we develop a pa- rametric goal programming model to measure the deviations between the two sets of weights. In- creasing the value of a parameter in a defined range of efficiency loss, we explore how much the deviations can be improved to achieve the desired goals of the decision maker. This may result in various ranking positions for each DMU in comparison to the other DMUs. An illustrated example of eight listed companies in the steel industry of China is used to highlight the usefulness of the proposed approach. Keywords Data Envelopment Analysis, Analytic Hierarchy Process, Ratio Analysis, Goal Programming 1. Introduction Ratio analysis is a commonly used analytical tool for measuring the relative performance of a Decision Making Units (DMUs) by focusing on one input/output at a time [1]. In practical applications, the weighted average of a set of individual ratios is applied in order to produce a single measure of performance from various ratios. How- ever, the appropriate assignment of weights in this approach has been an issue of controversy for researchers. Fortunately, the development of modern Operations Research/Management Science (OR/MS) has provided us with two powerful methods called Data Envelopment Analysis (DEA) and Analytic Hierarchy Process (AHP) which can be used to derive ratio weights.