Purpose – The purpose of this paper is to present a tie-breaking procedure for computing performance efficiencies to improve benchmarking and performance evaluation process in a business situation. Design/methodology/approach – The authors propose a unified approach based on data envelopment analysis (DEA) and technique for order of preference by similarity to ideal solution (TOPSIS), to overcome the difficulty of unique ranking in the prevalent benchmarking and performance evaluation processes such as DEA, Super efficiency DEA model, etc., under constant return to scale (CRS) assumption. This model is called as efficiency ranking method using DEA and TOPSIS (ERM-DT). In order to check the consistency of the approach, various input-output combinations (to calculate the efficiencies) have been illustrated. Further, the authors present a case of an Indian Bank to illustrate an application of the proposed approach. Findings – The proposed approach, ERM-DT enables assign a unique rank to decision making units and provides a tie breaking procedure. Results obtained using the proposed approach are statistically compared with those obtained from the CRS DEA approach and super efficiency DEA approach using Friedman’s test. Practical implications – The proposed model provides an efficiency ranking method based on a score obtained by considering the minimum distance from the best value and maximum distance from the worst value. The proposed methodology is capable of handling negative data and undesirable output variables. This approach is unit invariant and makes the calculations simple. The authors present an application to compute the efficiency of various branches of an Indian bank. The authors hope the proposed method can enhance the decision-making ability of the management in complex situations. Originality/value – The authors propose an integrated DEA and TOPSIS framework for better benchmarking and performance evaluation. This approach provides a tie-breaking procedure for the efficiencies computed using CRS DEA approach. Ranks are assigned based on score obtained by considering the distance from the worst and the best solution. The proposed approach can be used with non-positive data points and undesirable output variables.
Purpose The purpose of this paper is to propose a performance evaluation framework using an integrated approach of stochastic frontier analysis (SFA) and technique of order preference with similarity to ideal solution (TOPSIS) called efficiency ranking method using SFA and TOPSIS (ERM-ST) specifically in the banking sector where service excellence is of prime importance for business growth. Design/methodology/approach The proposed approach ERM-ST measures the performance of a DMU in the SFA framework by considering multiple outputs and multiple inputs. It is a non-parametric tool which does not need any prior model assumptions which enhances its applicability in real-life business scenarios. Moreover, the efficiency score obtained using the proposed model ERM-ST lies between 0 and 1, unlike in case of super efficiency data envelopment analysis (DEA) which may go well above 1. Findings The proposed framework is evaluated for its applicability using two various data sets and is further used to evaluate the performance of a group of 26 public sector banks in India. The results obtained by the proposed method ERM-ST are compared with those obtained by super efficiency DEA using Friedman’s test. Originality/value The proposed approach ERM-ST is developed to evaluate the performance of a service unit with multiple outputs and multiple inputs in the SFA framework.
India is expected to be ranked among the top three healthcare markets in terms of growth by 2020. The scale and scope for delivery of quality healthcare services demand high levels of service performance to provide effective and efficient services to patients. The purpose of this study is to assess the performance efficiency of Indian private hospitals using data envelopment analysis (DEA) and super-efficiency DEA. The analysis uses an output-oriented approach with a mix of four inputs and one output variables to identify the most efficient hospitals. In the first stage, a sample of 25 private hospitals is evaluated using DEA, and in the second stage, the same sample is analysed using super-efficiency DEA for discriminating the performance of the efficient hospitals. The results show seven hospitals as the most efficient ones using DEA in the first stage. Fortis Hospital Ltd emerges as the super-efficient hospital using super-efficiency DEA analysis in the second stage. The results obtained have managerial implications and provide the decision maker (DM) the requisite guidance for corrective actions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.