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Article
Publication date: 13 July 2020

Jolly Puri and Meenu Verma

This paper is focused on developing an integrated algorithmic approach named as data envelopment analysis and multicriteria decision-making (DEA-MCDM) for ranking decision-making…

Abstract

Purpose

This paper is focused on developing an integrated algorithmic approach named as data envelopment analysis and multicriteria decision-making (DEA-MCDM) for ranking decision-making units (DMUs) based on cross-efficiency technique and subjective preference(s) of the decision maker.

Design/methodology/approach

Self-evaluation in data envelopment analysis (DEA) lacks in discrimination power among DMUs. To fix this, a cross-efficiency technique has been introduced that ranks DMUs based on peer-evaluation. Different cross-efficiency formulations such as aggressive and benevolent and neutral are available in the literature. The existing ranking approaches fail to incorporate subjective preference of “one” or “some” or “all” or “most” of the cross-efficiency evaluation formulations. Therefore, the integrated framework in this paper, based on DEA and multicriteria decision-making (MCDM), aims to present a ranking approach to incorporate different cross-efficiency formulations as well as subjective preference(s) of decision maker.

Findings

The proposed approach has an advantage that each of the aggressive, benevolent and neutral cross-efficiency formulations contribute to select the best alternative among the DMUs in a MCDM problem. Ordered weighted averaging (OWA) aggregation is applied to aggregate final cross-efficiencies and to achieve complete ranking of the DMUs. This new approach is further illustrated and compared with existing MCDM approaches like simple additive weighting (SAW) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to prove its validity in real situations.

Research limitations/implications

The choice of cross-efficiency formulation(s) as per subjective preference of the decision maker and different orness levels lead to different aggregated scores and thus ranking of the DMUs accordingly. The proposed ranking approach is highly useful in real applications like R and D projects, flexible manufacturing systems, electricity distribution sector, banking industry, labor assignment and the economic environmental performances for ranking and benchmarking.

Practical implications

To prove the practical applicability and robustness of the proposed integrated DEA-MCDM approach, it is applied to top twelve Indian banks in terms of three inputs and two outputs for the period 2018–2019. The findings of the study (1) ensure the impact of non-performing assets (NPAs) on the ranking of the selected banks and (2) are enormously valuable for the bank experts and policy makers to consider the impact of peer-evaluation and subjective preference(s) in formulating appropriate policies to improve performance and ranks of underperformed banks in competitive scenario.

Originality/value

To the best of the authors’ knowledge, this is the first study that has integrated both DEA and MCDM via OWA aggregation to present a ranking approach that can incorporate different cross-efficiency formulations and subjective preference(s) of the decision maker for ranking DMUs.

Details

Data Technologies and Applications, vol. 54 no. 4
Type: Research Article
ISSN: 2514-9288

Keywords

Article
Publication date: 3 June 2020

Sayyid Ali Banihashemi and Mohammad Khalilzadeh

Classical models of data envelopment analysis (DEA) calculate the efficiency of decision-making units do not differentiate between efficient units. The purpose of this paper is to…

Abstract

Purpose

Classical models of data envelopment analysis (DEA) calculate the efficiency of decision-making units do not differentiate between efficient units. The purpose of this paper is to present a new method for ranking efficient units and compare it with the other methods presented in this field.

Design/methodology/approach

In this paper, a new method is presented for ranking efficient units. To validate the proposed method, a real case, which was studied by Li et al. (2016) is examined and the rankings of the efficient units are compared with four other methods including the Andersen and Petersen’s super-efficiency, game theory and the concept of Shapley value and the technique for order of preference by similarity to ideal solution methods.

Findings

The results show that there is a high correlation between the rankings of efficient units obtained by the new proposed method and the other methods such as Andersen and Petersen’s super-efficiency, game theory and Shapley value methods.

Originality/value

The problem of ranking efficient units with the DEA method is an important issue for researchers. Extensive studies have been proposed to provide methods for ranking efficient units. This paper proposes a simple and fast method for ranking efficient units that achieves better results.

Details

World Journal of Engineering, vol. 17 no. 4
Type: Research Article
ISSN: 1708-5284

Keywords

Article
Publication date: 16 May 2016

Mehdi Abbasi and Mohamad Amin Kaviani

Competition in dynamic markets requires operational excellence and effective operations strategy. Hence, organizations have to evaluate their operational performance in comparison…

Abstract

Purpose

Competition in dynamic markets requires operational excellence and effective operations strategy. Hence, organizations have to evaluate their operational performance in comparison to their rivals. The purpose of this paper is to present an operational performance evaluation framework for analyzing and ranking the organizations based on the effectiveness of their operations strategies.

Design/methodology/approach

In this study three uncertain data envelopment analysis (DEA) models consist of fuzzy DEA (FDEA), imprecise DEA (IDEA) and Grey DEA are applied to assess the performance of organizations in terms of the operations. The applicability of the proposed framework is demonstrated through a case study at Fars province cement manufacturers of Iran.

Findings

The ranking results assist the mangers of service and manufacturing enterprises in finding out the current positions of their companies and the effectiveness of their operations strategies in comparison to their rivals. Accordingly they can make proper strategic and operational decisions to improve the performance of the operations.

Originality/value

Based on the previous literature, this is the first study which uses FDEA and IDEA methods in an operational performance evaluation problem. Furthermore this study proposes a novel framework for evaluating and ranking the operational performance of firms from the perspective of operations strategy.

Details

Management Decision, vol. 54 no. 4
Type: Research Article
ISSN: 0025-1747

Keywords

Open Access
Article
Publication date: 9 December 2022

Jae-Dong Hong

The recent COVID-19 outbreak and severe natural disasters make the design of the humanitarian supply chain network (HSCN) a crucial strategic issue in a pre-disaster scenario. The…

Abstract

Purpose

The recent COVID-19 outbreak and severe natural disasters make the design of the humanitarian supply chain network (HSCN) a crucial strategic issue in a pre-disaster scenario. The HSCN design problem deals with the location/allocation of emergency response facilities (ERFs). This paper aims to propose and demonstrate how to design an efficient HSCN configuration under the risk of ERF disruptions.

Design/methodology/approach

This paper considers four performance measures simultaneously for the HSCN design by formulating a weighted goal programming (WGP) model. Solving the WGP model with different weight values assigned to each performance measure generates various HSCN configurations. This paper transforms a single-stage network into a general two-stage network, treating each HSCN configuration as a decision-making unit with two inputs and two outputs. Then a two-stage network data envelopment analysis (DEA) approach is applied to evaluate the HSCN schemes for consistently identifying the most efficient network configurations.

Findings

Among various network configurations generated by the WGP, the single-stage DEA model does not consistently identify the top-ranked HSCN schemes. In contrast, the proposed transformation approach identifies efficient HSCN configurations more consistently than the single-stage DEA model. A case study demonstrates that the proposed transformation method could provide a more robust and consistent evaluation for designing efficient HSCN systems. The proposed approach can be an essential tool for federal and local disaster response officials to plan a strategic design of HSCN.

Originality/value

This study presents how to transform a single-stage process into a two-stage network process to apply the general two-stage network DEA model for evaluating various HSCN configurations. The proposed transformation procedure could be extended for designing some supply chain systems with conflicting performance metrics more effectively and efficiently.

Details

Journal of Humanitarian Logistics and Supply Chain Management, vol. 13 no. 1
Type: Research Article
ISSN: 2042-6747

Keywords

Article
Publication date: 5 September 2008

Reza Farzipoor Saen

The purpose of this paper is to propose an innovative algorithm for ranking suppliers in the presence of volume discount offers, with regard to various criteria, based on…

1416

Abstract

Purpose

The purpose of this paper is to propose an innovative algorithm for ranking suppliers in the presence of volume discount offers, with regard to various criteria, based on super‐efficiency analysis.

Design/methodology/approach

This paper introduces an innovative approach, which is based on super‐efficiency analysis (one of the data envelopment analysis models).

Findings

To rank the suppliers in the conditions that they offer volume discounts, an algorithm was introduced.

Practical implications

The results of this paper can be applied from both a buyer's and supplier's perspective. The buyer can use it as a tool in ranking the suppliers. The supplier can use these results from a marketing perspective. A specific supplier who achieves a high mean score, when compared to the other suppliers, can use these results for promoting its product. On the other hand, if a particular supplier is poorly performing, then the supplier can use the analysis for benchmarking purposes. This result may mean that the supplier must provide better performance levels at the same input.

Originality/value

To the best of the author's knowledge, there is no comprehensive and feasible model that deals with supplier ranking by super‐efficiency analysis in the presence of volume discount offers.

Details

International Journal of Physical Distribution & Logistics Management, vol. 38 no. 8
Type: Research Article
ISSN: 0960-0035

Keywords

Article
Publication date: 13 June 2019

Seyed Hadi Mousavi-Nasab, Jalal Safari and Ashkan Hafezalkotob

Resource allocation has always been a critical problem with significant economic relevance. Many industries allocate the resources based on classical methods such as overall…

Abstract

Purpose

Resource allocation has always been a critical problem with significant economic relevance. Many industries allocate the resources based on classical methods such as overall equipment effectiveness (OEE) and data envelopment analysis (DEA). The lack of OEE factors’ weight, how it is defined, analyzed, interpreted and compared in OEE and selection of unrealistic weights, self-appraisal and disability of complete ranking in DEA are challenges that are possible to occur. These defects may result in unfair allocation of the resources. This study aims to overcome the mentioned weaknesses.

Design/methodology/approach

In this paper, an approach using a set of various DEA models and Nash bargaining solution (NBS) is designed to solve the resource allocation problem based on OEE, among a set of comparable and uniform DMUs (decision-making units) in a fair way.

Findings

The results show that a unique Pareto optimal allocation solution is obtained by the proposed DEA–NBS model among the DMUs. This allocation is more acceptable for players, because the allocation results are commonly determined by all DMUs rather than a specific one. Furthermore, the rankings achieved by the utilized methods and TOPSIS (technique for order preference by similarity to ideal solution) are compared by Spearman’s rank correlation coefficient to validate the resource allocation plan. The findings indicate that the DEA–NBS method has the best correlation with the TOPSIS approach.

Originality/value

To the best of authors’ knowledge, no research has considered the use of DEA and NBS with OEE.

Details

Kybernetes, vol. 49 no. 3
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 1 February 2016

Asmita Chitnis and Omkarprasad S Vaidya

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…

Abstract

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.

Details

Benchmarking: An International Journal, vol. 23 no. 1
Type: Research Article
ISSN: 1463-5771

Keywords

Article
Publication date: 5 June 2007

A. Azadeh, S.F. Ghaderi and V. Ebrahimipour

This paper seeks to present an integrated principal component analysis (PCA) data envelopment analysis (DEA) framework for assessment and ranking of manufacturing systems based on…

1115

Abstract

Purpose

This paper seeks to present an integrated principal component analysis (PCA) data envelopment analysis (DEA) framework for assessment and ranking of manufacturing systems based on equipment performance indicators.

Design/methodology/approach

The integrated framework discussed in this paper is based on PCA and DEA. The validity of the integrated model is further verified and validated by numerical taxonomy (NT) methods.

Findings

The results of the integrated PCA DEA framework show the ranking of sectors and weak and strong points of each sector with regard to equipment and machinery. Moreover, a non‐parametric correlation method, namely, Spearman correlation experiment shows high level of correlation among the findings of PCA, DEA and NT. Furthermore, it identifies which indicators have major impacts on the performance of manufacturing sectors.

Practical implications

To achieve the objectives of this study, a comprehensive study was conducted to locate all economic and technical indicators which influence equipment performance. These indicators are related to equipment productivity, efficiency, effectiveness and profitability. Standard factors such as down time, time to repair, mean time between failure, operating time, value added and production value were considered as shaping factors. The manufacturing sectors are selected according to the format of International Standard for Industrial Classification.

Originality/value

The modeling approach of this paper could be used for ranking and analysis of other sectors in particular or countries in general.

Details

Engineering Computations, vol. 24 no. 4
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 17 June 2019

Kiran Mehta, Renuka Sharma and Vishal Vyas

This study aims to assign efficiency score and then ranking the Indian companies known for best practices to control carbon-emission in the environment. It is destined to…

Abstract

Purpose

This study aims to assign efficiency score and then ranking the Indian companies known for best practices to control carbon-emission in the environment. It is destined to benchmark one company for best performance on the basis of selected alternatives among its peer group companies.

Design/methodology/approach

The present study has used a hybrid model by applying data envelopment analysis (DEA)-technique for order performance by similarity to ideal solution (TOPSIS) to measure the efficiency and ranking of various decision units on the basis of specified variables.

Findings

The findings of DEA have given the best alternative or best decision-making unit (DMU) among the set of 25 DMUs considered for empirical testing. The DEA technique is used with TOPSIS, which is another popular multi-criteria decision model. The integrated DEA-TOPSIS model has helped to compute the efficiency score of all 25 DMUs of study and also provide a unique rank to each of the efficient unit identified with the help of DEA technique.

Practical implications

The findings of the study have provided Benchmark Company amongst the companies following best practices for saving energy and having best operating profits too. This benchmark business unit can be studied extensively by peer group companies to compare various parameters affecting their efficiency and profits both.

Social implications

The findings of the study will promote the socially responsible practices by corporate citizens and adopt the practices to reduce their carbon footprints. It will also suggest to socially responsible investors to select the benchmark and most efficient companies for investment purpose.

Originality/value

The study is original in terms of measuring efficiency and ranking of companies known for best practices for controlling their carbon footprints and suggesting a benchmark company to its peer group. Also, the integrated approach of using DEA-TOPSIS for such type of studies also makes it distinctive from earlier work done in the related field.

Details

Journal of Indian Business Research, vol. 11 no. 2
Type: Research Article
ISSN: 1755-4195

Keywords

Article
Publication date: 3 April 2018

Davood Gharakhani, Abbas Toloie Eshlaghy, Kiamars Fathi Hafshejani, Reza Kiani Mavi and Farhad Hosseinzadeh Lotfi

Conventional data envelopment analysis (DEA) models permit each decision-making unit (DMU) to assess its efficiency score with the most favorable weights. In other words, each DMU…

Abstract

Purpose

Conventional data envelopment analysis (DEA) models permit each decision-making unit (DMU) to assess its efficiency score with the most favorable weights. In other words, each DMU selects the best weighting schemes to obtain maximum efficiency for itself. Therefore, using different sets of weights leads to many different efficient DMUs, which makes comparing and ranking them on a similar basis impossible. Another issue is that often more than one DMU is evaluated as efficient because the selection of weights is flexible; therefore, all DMUs cannot be completely differentiated. The purpose of this paper is to development a common weight in dynamic network DEA with a goal programming approach.

Design/methodology/approach

In this paper, a goal programming approach has been proposed to generate common weights in dynamic network DEA. To validate the applicability of the proposed model, the data of 30 non-life insurance companies in Iran during 2013-2015 have been used for measuring their efficiency scores and ranking all of the companies.

Findings

Findings show that the proposed methodology is an effective and practical approach to measure the efficiency of DMUs with dynamic network structure.

Originality/value

The proposed model delivers more knowledge of the common weight approaches and improves the DEA theory and methodology. This model makes it possible to measure efficiency scores and compare all DMUs from multiple different standpoints. Further, this model allows one to not only calculate the overall efficiency of DMUs throughout the time period but also consider dynamic change of the time period efficiency and dynamic change of the divisional efficiency of DMUs.

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