Search results

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.

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.

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.

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.

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.

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.

The study aims to evaluate the financial distress position of selected sample banks in India. The top 10 banks with the highest levels of gross non-performing assets (NPA) under both public and private sector ownerships have been chosen for the study. Application of the Altman Z-score model has been used to compare both ownership banks’ financial distress for five years from 2017 to 2021. Based on the study’s findings, it was found that private sector banks demonstrated better financial stability than their public sector counterparts. Specifically, the average Z-score of the selected sample banks was higher than the safe zone threshold of 2.9 during the study period.

Deposits, a liability component of banks’ balance sheet, are an important source of funding for commercial and retail banks. In this study, the authors consider deposits as dependent variable and examine factors (bank-specific, macrofinance and structural) that could plausibly explain deposits. Subsequently, the findings are expected to support analysts, bank managers and regulators, especially in small economies such as Fiji, for asset–liability management.

This study uses a balanced panel of six commercial banks and two credit institutions over the period 2000–2022. To control for bank heterogeneity, a fixed-effect regression method is used.

Bank-specific variables such as bank size, profitability, loan-to-deposit ratio and bank stability are positively associated with bank deposits, whereas the capital adequacy ratio is negatively associated with bank deposits. Macroeconomic variables such as remittances and gross domestic product per capita are positively associated with bank deposits. Moreover, institutional variables such as control of corruption, political stability and regulatory quality are positively associated with bank deposits. However, tail events such as the global financial crisis of 2007–09 and the COVID-19 pandemic negatively influence bank deposits. Structural breaks for 2007 and 2011 of two banks (Bank of the Baroda and Bank of the South Pacific, respectively) are positively associated with bank deposits.

Previous studies have considered profitability, competition, nonperforming loans and stability of banks in Fiji. To the best of the authors’ knowledge, this study is the first to consider the determinants of bank deposits, an important source of funds for banks in many small countries including Fiji. In addition, this study examines the impact of structural breaks, tail events such as the recent pandemic (COVID-19) and institutional variables.

This study gauges the profitability and performance of Indian commercial banks under the technology advancements. In this study, the authors identified three domains that give advantage to banks due to technology incorporation, that is, increased sales revenue, reduced operating expenses, and increased employee productivity. The authors assess the effect of these domains on banks’ profitability and performance. This study is conducted for the period between the years 2003 and 2018 across 34 public and private banks for empirical analysis. The authors examined the impact of investment in technology on the profitability using panel data analysis and evaluated the long-term effect of technology investment using the vector error correction model. This study found that there is a mixed effect of technology spend on the profitability and performance of Indian banks, where private sector banks are more aggressive in technology investment as compared to the public sector banks. This study recommends an optimal technology-related strategy to gain improved productivity for the banking business, that is, planned technology reserves, customer awareness campaigns about technology-enabled products, and robust employee–customer motivation policy.

Merger and acquisitions (M&A) is a process of restructuring two or more companies into one, a process that occurs frequently in many companies. Previous studies on M&A mainly paid attention to the potential gains from a merger, while ignored the problem of how to select the partners to merge. This paper aims to select the best partner from different candidates for a given company to merge.

Each company's historical data are used to identify each company's own production technology. With resources change, each company's new operation is restricted by its own production technology. Then, a 0–1 integer programming is proposed to select the best partner for M&A.

The banking industry involving 27 China's commercial banks is given to verify the applicability of our proposed model. The study shows the best partner selection for each bank company.

On the theoretical side, the study uses each company's own historical data to construct its own production technology to compressively reflect the production change after M&A. On the practical side, the study uses the proposed model to help the 27 commercial banks in China to select their best merger partner.

Due to the rapid development and innovation in the Internet-based technology, conventional banks are under pressure and have to compete with Internet-based finance. This has made banks adopt measures to improve operational efficiency and reduce input and increase output.

The authors had proposed a two-stage fairness concern efficiency model based on the classical theory of data envelopment analysis (DEA) and performed an empirical study to measure agricultural loan efficiency in the 20 major Chinese banks.

The findings of the empirical analysis are as follows: (1) peer-induced fairness concern has no impact on deposit efficiency in a centralized bank supply chain; (2) The China Merchants Bank (CMB) has the third lowest deposit efficiency; (3) monotonicity of loan efficiency with input allocation depends on a bank's ownership structure; (4) efficiency ranks are strongly affected by the fairness concern; (5) most Chinese banks show a low agricultural loan efficiency.

This paper contributes to the literature in several ways. First, to the best of the authors’ knowledge, this is the first attempt to analyze agricultural loan efficiency for a bank supply chain system with the fairness concern. This work reveals the hidden factor that restricts loan efficiency of Chinese banks. Second, the proposed fairness concern two-stage DEA model has shown good ability for full ranking. It can provide a new perspective to the classical DEA literature for ranking decision-making units (DMUs). Third, the authors have demonstrated empirical bank efficiency for the 20 major Chinese banks.

Systemic risk has been a cause of concern for the bank regulatory authorities worldwide since the global financial crisis. This study aims to identify systemically important banks (SIBs) in India by using SRISK to measure the expected capital shortfall of banks in a systemic event. The sample size comprises a balanced data set of 31 listed Indian commercial banks from 2006 to 2019.

In this study, the authors have used SRISK to identify banks that have a maximum contribution to the systemic risk of the Indian banking sector. Leverage, size and long-run marginal expected shortfall (LRMES) are used to compute SRISK. Forward-looking LRMES is computed using the GJR-GARCH-dynamic conditional correlation methodology for early prediction of a bank’s contribution to systemic risk.

This study finds that public sector banks are more vulnerable to macroeconomic shocks owing to their capital inadequacy vis-à-vis the private sector banks. This study also emphasizes that size should not be used as a standalone factor to assess the systemic importance of a bank.

Systemic risk has attracted a lot of research interest; however, it is largely limited to the developed nations. This paper fills an important research gap in banking literature about the identification of SIBs in an emerging economy, India. As SRISK uses both balance sheet and market-based information, it can be used to complement the existing methodology used by the Reserve Bank of India to identify SIBs.

This study examines the link of effective change implementation (CIE) with select human resource (HR) practices and employees' resistance to change (RTC) amidst ongoing mergers in Indian public sector banks (PSBs). It also intends to highlight the role of RTC as a mediator in this mechanism.

The authors used a structured questionnaire administered through a survey of employees of select PSBs that have undergone mergers. The hypothesized relationships were tested on 220 responses with structural equation modelling.

Training and communication of change as HR practices were found to have significant effects in implementing change. RTC fully mediated the relationship of training and CIE, and partially mediated the association of communication and CIE. Communication had a stronger influence on RTC than training. This finding upholds the importance of communication but also implies that training can reinforce effective communication of change and may not affect the implementation if not directed towards handling resistance.

The significance of communication as a finding supports the theory of planned behaviour. The authors’ results also align with the social exchange theory and can be extended to the job demands-resources model. PSBs may plan for phase-wise training initiatives starting from the announcement till the end of a merger. PSBs also need to effectively communicate all relevant HR issues to employees, thus being transparent and fair. Both online and offline modes of communication can be explored. Overall, the senior management has to imbibe the handholding of employees in the short term and a sense of empathy in the longer term.

Research on HR in Indian banking mergers seems to take a back seat vis-à-vis strategic issues and financial performance. There also is a limited empirical examination of the role of HR practices in effective change implementation. This paper addresses both these issues by proposing a conceptual model and empirically validating it amidst the merger of PSBs. The authors also highlight how training and communication are effective in handling resistance to change.

The purpose of this paper is to evaluate Chinese commercial banks efficiency based on different non-performing loans in the process. Moreover, we identified the difference among different types of banks (state-owned commercial banks, joint-stock commercial banks and city commercial banks) and different operation stages (deposit producing sub-stage, profit earning sub-stage and overall stage).

Assurance region (AR) restrictions are combined with a two-stage data envelopment analysis (DEA) model. The efficiency scores of 26 Chinese commercial banks (listed banks) are analyzed by a two-stage AR-DEA model in the study period of 2013–2017.

The results show that state-owned commercial banks had better performance than joint-stock commercial banks and city commercial banks over the five-year study period. The development of Internet finance has positive impact on deposit producing sub-stage and insignificant non-homogeneity existed among the different groups in the circumstances of considering different non-performing loans.

The research findings provide practical insights that help bank managers find the defects in operation process, which need to be improved.

Previous studies viewed non-performing loans as an integrated whole variable. The paper divides non-performing loans into three categories based on the risk and investigates the effect of different types of loans on bank efficiency scores.

The purpose of this paper is to critically examine sustainability reporting (SR) practices of top 10 Indian banks, on parameters derived from a Global Reporting Initiative (GRI)-G4-based persuasive communication framework.

SR metrics from GRI-G4 guidelines were mapped to persuasive communication parameters to develop a blended analytical framework. Content analysis (CA) technique was used to assess SR of top 10 banks on this framework.

The study has three key findings. First, most of the top 10 Indian banks are yet to adopt adequate disclosure and transparency practices in SR. Second, even though environmental and social goals are broadly reported, there are glaring omissions on metrics like “equal remuneration,” “occupational health and safety” and “customer privacy.” Third, stakeholder engagement focus is weak as reflected in low persuasive appeal of SR content of most banks.

The blended framework provides a theoretical and analytical pathway for operationalizing the sustainability context principle, which has been inadequately addressed even within the GRI framework implementation.

The paper provides a “health check” and identifies “red flags” in SR of top 10 Indian banks, enabling them to undertake a critical review of their sustainability metrics and reporting practices.

The paper establishes the significance of evaluating non-financial reporting practices addressing broader sustainability metrics in the banking sector, in an emerging economy context.

This paper develops a GRI-G4-based persuasive communication framework for SR assessment, and conducts an evaluation of top 10 Indian banks using CA technique.