Volume 55, Number 1, January-February 2021
|Page(s)||213 - 229|
|Published online||12 March 2021|
A common weights model for investigating efficiency-based leadership in the russian banking industry
Graduate School of Management, Saint Petersburg State University, St. Petersburg, Russia
2 Business Systems and Analytics Department, Distinguished Chair of Business Analytics, La Salle University, Philadelphia, PA 19141, USA
3 Business Information Systems Department, Faculty of Business Administration and Economics, University of Paderborn, Paderborn, Germany
4 Department of System Engineering, Faculty of Economics, Technical University of Ostrava, Ostrava, Czech Republic
5 Department of Operations Management & Business Statistics, College of Economics and Political Science, Sultan Qaboos University, Muscat, Oman
* Corresponding author: firstname.lastname@example.org
Accepted: 17 December 2020
In this race for productivity, the most successful leaders in the banking industry are those with high-efficiency and a competitive edge. Data envelopment analysis is one of the most widely used methods for measuring efficiency in organizations. In this study, we use the ideal point concept and propose a common weights model with fuzzy data and non-discretionary inputs. The proposed model considers environmental criteria with uncertain data to produce a full ranking of homogenous decision-making units. We use the proposed model to investigate the efficiency-based leaders in the Russian banking industry. The results show that the unidimensional and unilateral assessment of leading organizations solely according to corporate size is insufficient to characterize industry leaders effectively. In response, we recommend a multilevel, multicomponent, and multidisciplinary evaluation framework for a more reliable and realistic investigation of leadership at the network level of analysis.
Mathematics Subject Classification: 90-10 / 90C11 / 90C08 / 90C30
Key words: Data envelopment analysis / common weights / leadership / ideal point / fuzzy data / non-discretionary inputs / efficiency
© EDP Sciences, ROADEF, SMAI 2021
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