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3. A non-parametric synthesis measure for board quality: empirical evidence from Indian banks.

Author

Singh, Rohit Kumar and Sharma, Supran Kumar

Subjects
BANKING industry, GENDER nonconformity, DATA envelopment analysis, PAPER arts, BOARDS of directors, BANK directors
Abstract

Purpose: The paper aims to craft a non-parametric composite value for the board quality of Indian banks where the weights can be assigned endogenously. Design/methodology/approach: The study employed a non-parametric data envelopment analysis (DEA)-based novel extension known as the benefit of doubt approach. To measure the strength of the Indian bank corporate board in terms of board efficiency (BEF), the study used a mixed approach, i.e. first, the study calculates the percentile ranks of the five attributes that the study assumes are the characteristics of the strong board including board size, number of outside directors, frequency of meetings, non-duality leadership and board gender diversity. Thereafter, the study performs the benefit-to-doubt approach to finally measure the efficiency of the board. Findings: The findings of the study establish that the methodological framework present in the study to measure the strength of the board in terms of BEF has been a much superior method over the other weighted and non-weighted linear average methods. Practical implications: This methodology aids the shareholders, investors and regulatory bodies in rating the Indian banks based on their strength in terms of better monitoring boards and ensuring a smooth agent–owner relationship. Originality/value: The benefit of doubt approach has been a unique and novel methodology to craft the composite value for any multidimensional phenomenon. One of the major benefits of using this approach is that it assigns the weights endogenously to each dimension and thereafter collectively determines the efficiency of such a phenomenon. [ABSTRACT FROM AUTHOR]

Published
2024
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16. Measuring paper industry's ecological performance in an imprecise and vague scenario: a fuzzy DEA-based analytical framework

Author

A. Rajeev, Sunil Kumar Jauhar, Natthan Singh, and Millie Pant

Subjects
Operations research, Computer science, Strategy and Management, Data envelopment analysis, Business and International Management, Fuzzy logic
Abstract

PurposeProductivity improvement is key to sustainability performance improvements of organizations. In a real-world scenario, the nature of inputs and outputs is likely to be imprecise and vague, leading to complexity in comparing firms' efficiency measurements. Implementation of fuzzy-logic based measurement systems is a method for dealing with such cases. This paper presents a fuzzy weight objective function to solve Data Envelopment Analysis (DEA) CCR model for measuring paper mills' performance in India for 15 years.Design/methodology/approachAn integrated methodology is proposed to solve DEA models having fuzzy weights. The fuzzy DEA methodology is an extended version of the DEA approach that researchers have used for performance measurement purposes in imprecise and vague scenarios. The ecological performance of the paper industry is evaluated, considering some desirable and undesirable outputs. The effect of non-discretionary input on the performance of a paper mill is also analyzed.FindingsAnalysis suggests that the productivity of the paper industry is improving consistently throughout the period. The comparative evaluation of methods suggests that a diverse cluster of DMUs and integration of DEA with the fuzzy logic increases the diversity in the efficiency score while DEA-DE imitates the results of CCR DEA.Originality/valueProposed a fuzzy DEA-based analytical framework for measuring the paper industry's ecological performance in an imprecise and vague scenario. The model is tested on data from the paper industry in a developing country context and comparative performance analysis using DEA, fuzzy DEA and DE algorithm is done.

Published
2021