Efficiency ranking method using DEA and TOPSIS (ERM-DT): case of an Indian bank

Analysis of Efficiency and Productivity of Commercial Banks in Turkey Pre- and during COVID-19 with an Integrated MCDM Approach

Above all, this study is original in that it reveals the efficiency and productivity of banks exposed to the current pandemic situation. The aim of this study is to evaluate bank efficiency and productivity of commercial banks operating in Turkey pre- and during COVID-19 by using a novel integrated multi-criteria decision-making (MCDM) approach. We divided the banks into three groups in order to evaluate the differences in terms of their efficiency and productivity: state banks, foreign banks and private domestic banks. This paper fills a gap in the literature by using a novel integrated MCDM approach including SWARA II as a subjective weighting method, MEREC as an objective weighting method, and MARCOS as a ranking method to evaluate bank efficiency and productivity. The results reveal that banks with foreign investors achieved higher productivity than other bank groups and the productivity of state banks decreased especially during the COVID-19 period. It should also be noted that state banks are restricted to certain political objectives.

A circular economy model for waste management in India

Management of waste is one of the major challenges faced by many developing countries. This study therefore attempts to develop a circular economy (CE) model to manage wastes and closing the loop and reducing the generation of residual wastes in Indian municipalities. Through extant literature review, the researchers found 30 success factors of CE implementation. Using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) SIMOS approach, the rating and weight of decision makers (DMs) for each factor were collected. A structured questionnaire has been developed incorporating all these 30 factors, to extract the most important factors. The data was collected from top 10 officials (DMs) from the Chennai municipality, who handle three regions (metropolitan, suburbia and industrial). Based on the TOPSIS SIMOS analysis, nine CE implementing factors (critical success factors (CSFs)) among the 30 variables that were significant based on the cut-off value was identified. A CE model has been proposed based on these nine CSFs for waste management in India.

G, Nair S, Chakraborty A, Antony J. Assessment of critical failure factors (CFFs) of Lean Six Sigma in real life scenario

Purpose

Many projects focus on the reliable operation of the activities in the project. Any failure in the process activities leads to major problems resulting in waste, defects, equipment damage, which has a direct impact on the consumers. In addition, Lean Six Sigma (LSS) is not new to this issue. LSS projects have faced an interruption in the process flow and unforeseen defects. Therefore, the purpose of this paper is to identify the vital failure factors of LSS projects.

Design/methodology/approach

Through extant literature review, the researchers found 44 critical failure factors (CFFs) of LSS. Using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) SIMOS approach, the decision makers’ (DMs) rating and weight for each factor were collected. Moreover, the study was conducted in both the manufacturing and service industries to identify the impact of CFFs in LSS projects.

Findings

CFFs and their evaluation have received little attention in the literature. Most of the previous studies deal only with the identification of the success factors in general. Therefore, the study identified 44 CFFs and ranked them through DMs. In addition, the TOPSIS SIMOS approach ranked the vital failure factors enabling the management to avert the LSS project from failures.

Research limitations/implications

The study focused on project failures due to CFFs of LSS. Nevertheless, it did not consider other failure factors of project and knowledge management. Further, the sample used to test the approach was considerably small. Therefore, the study can be repeated with significant samples and the vital failure factors compared.

Practical implications

In real-life application, all the parameters in the LSS project need to be understood in a better manner. In such a condition, the practitioner needs to know that the project never fails due to the CFFs and TOPSIS SIMOS approach can prevent the LSS project failures.

Originality/value

The study applied TOPSIS SIMOS approach to rank the CFFs in an LSS project, which is first of its kind and aids the practitioners to make the right decisions in the business environment.

Benchmarking performance of governance quality in Indian states using MCDM techniques

Purpose

The purpose of this paper is to benchmarking the governance performance of Indian states.

Design/methodology/approach

This paper provides a framework to measure governance performance at the state level. Using the data on 28 key indicators, the authors evaluate Indian states on seven broad dimensions of governance quality covering several aspects of public service delivery, regulatory quality and law and order. The empirical methodology involves the application of multi-criteria decision making techniques in two steps. The authors, first develop suitable weights of the identified dimensions and criteria under each dimension by applying the inputs of an expert-based decision-panel in a best-worst framework. Next, using these weights, the authors evaluate ranking of each state using TOPSIS and PROMETHEE-II methods.

Findings

The results indicate wide disparities in the governance performance of Indian states. Based on different indicators, the paper evaluates the rank of all the major Indian states. Results reveal that “Social Service Delivery(S)” is the most influencing dimension for the development of a state. Overall, the authors find Andra Pradesh, NCT of Delhi and Goa to be the leading states in terms of governance quality.

Research limitations/implications

The paper provides policy makers with easy to use operational indicators to analyse the governance performance of Indian states. These would help in better monitoring of these states through competitive goal-setting for continuous improvement.

Originality/value

To the best of the authors’ knowledge, this study is the first formal assessment of governance quality in the Indian states in a multi-criteria framework. To this end, the paper addresses the issue of wide regional disparities in the country. The findings of the paper provide powerful insights to policy makers in setting up appropriate strategies to eliminate these disparities.

Brand resonance score for CBBE model: an application in financial services

Purpose

Brand resonance will significantly improve the profits of the services industry in the twenty-first century. The purpose of this paper is to find the resonance score for modified customer-based brand equity (CBBE) model in mutual fund financial services and improve the conceptualization of customer-based mutual fund services’ brand equity through brand resonance.

Design/methodology/approach

The path values of SEM model was used to estimate the relative weights of criteria and sub-criteria in analytic hierarchy process (AHP) model and it was empirically tested with a sample of 240 mutual fund investors.

Findings

The brand resonance using AHP has been quantified. The resonance quantification of each brand has been demonstrated using two renowned Indian mutual fund services brands State Bank of India and Hong Kong and Shanghai Banking Corporation.

Research limitations/implications

The interdependency of the factors which influence the resonance score is not explored.

Practical implications

Research findings provide useful guidelines for fund managers/analysts of mutual fund services companies while improving the brand equity and strong brand’s resonance with investors.

Originality/value

The paper examines quantification of resonance for modified CBBE model in mutual fund services using data from a sample of investors in India with two mutual fund brands. The AHP structure model helps firms effectively quantify the resonance score.

DEA and Monte Carlo simulation approach towards green car selection

Purpose

Automakers are engaged in manufacturing both efficient and inefficient green cars. The purpose of this paper is to categorize efficient green cars and inefficient green cars followed by improving efficiencies of identified inefficient green cars for distribution fitting.

Design/methodology/approach

The authors have used 2014 edition of secondary data published by the Automotive Research Centre of the Automobile Club of Southern California. The paper provides the methodology of applying data envelopment analysis (DEA) consisting of 50 decision-making units (DMUs) of green cars with six input indices (emission, braking, ride quality, acceleration, turning circle, and luggage capacity) and two output indices (miles per gallon and torque) integrated with Monte Carlo simulation for drawing significant statistical inferences graphically.

Findings

The findings of this study showed that there are 27 efficient and 23 inefficient DMUs along with improvement matrix. Additionally, the study highlighted the best distribution fitting of improved efficient green cars for respective indices.

Research limitations/implications

This study suffers from limitations associated with 2014 edition of secondary data used in this research.

Practical implications

This study may be useful for motorists with efficient listing of green cars, whereas automakers can be benefitted with distribution fitting of improved efficient green cars using Monte Carlo simulation for calibration.

Originality/value

The paper uses DEA to empirically examine classification of green cars and applies Monte Carlo simulation for distribution fitting to improved efficient green cars to decide appropriate range of their attributes for calibration.

An application of data envelopment analysis for Korean banks with negative data

Purpose

The purpose of this paper is to measure the comparative efficiency of 18 Korean commercial banks under the presence of negative observations and examine performance differences among them by grouping them according to their market conditions.

Design/methodology/approach

The authors employ two data envelopment analysis (DEA) models such as a Banker, Charnes, and Cooper (BCC) model and a modified slacks-based measure of efficiency (MSBM) model, which can handle negative data. The BCC model is proven to be translation invariant for inputs or outputs depending on output or input orientation. Meanwhile, the MSBM model is unit invariant in addition to translation invariant. The authors compare results from both models and choose one for interpreting results.

Findings

Most Korean banks recovered from the worst performance in 2011 and showed similar performance in recent years. Among three groups such as national banks, regional banks, and special banks, the most special banks demonstrated superb performance across models and years. Especially, the performance difference between the special banks and the regional banks was statistically significant. The authors concluded that the high performance of the special banks was due to their nationwide market access and ownership type.

Practical implications

This study demonstrates how to analyze and measure the efficiency of entities when variables contain negative observations using a data set for Korean banks. The authors have tried two major DEA models that are able to handle negative data and proposed a practical direction for future studies.

Originality/value

Although there are research papers for measuring the performance of banks in Korea, all of the papers in the topic have studied efficiency or productivity using positive data sets. However, variables such as net incomes and growth rates frequently include negative observations in bank data sets. This is the first paper to investigate the efficiency of bank operations in the presence of negative data in Korea.