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This study investigates the role of market concentration and efficiency in banking system stability during the COVID-19 pandemic. We empirically test the hypothesis that market concentration and efficiency are significant determinants of bank performance and stability during the time of crises, using a sample of 575 banks in 20 countries in the Middle East and North Africa (MENA).

The main sources of bank data are the BankScope and BankFocus (Bureau van Dijk) databases, World Bank development indicators, and official websites of banks in MENA countries. This study combined descriptive and analytical approaches. We utilize a panel dataset and adopt panel data econometric techniques such as fixed/random effects and the Generalized Method of Moments (GMM) estimator.

The results reveal that market concentration negatively affects bank profitability, whereas improved efficiency further enhances bank performance and contributes to the banking sector’s overall stability. Furthermore, our analysis indicates that during the COVID-19 pandemic, bank stability strongly depended on the level of market concentration, but not on bank efficiency. However, more efficient banks are more profitable and stable if the banking institutions are Islamic. Similarly, Islamic banks with the same level of efficiency demonstrated better overall financial performance during the pandemic than their conventional peers did.

The main limitation is related to the period of COVID-19 pandemic that was covered in this paper (2020–2021). Therefore, further investigation of the COVID-19 effects on bank profitability and risk will require an extended period of the pandemic crisis, including 2022.

This study provides information that will enable bank managers and policymakers in MENA countries to assess the growing impact of market concentration and efficiency on the banking sector stability. It also helps them in formulating suitable strategies to mitigate the adverse consequences of the COVID-19 pandemic. Our recommendations are useful guides for policymakers and regulators in countries where Islamic and conventional banking systems co-exist and compete, based on different business models and risk management practices.

The authors contribute to the banking stability literature by investigating the role of market concentration and efficiency as the main determinants of bank performance and stability during the COVID-19 pandemic. This study is the first to analyze banking sector stability in the MENA region, using both individual and risk-adjusted aggregated performance measures.

Estimation of (in)efficiency became a popular practice that witnessed applications in virtually any sector of the economy over the last few decades. Many different models were deployed for such endeavors, with Stochastic Frontier Analysis (SFA) models dominating the econometric literature. Among the most popular variants of SFA are Aigner, Lovell, and Schmidt (1977), which launched the literature, and Kumbhakar, Ghosh, and McGuckin (1991), which pioneered the branch taking account of the (in)efficiency term via the so-called environmental variables or determinants of inefficiency. Focusing on these two prominent approaches in SFA, the goal of this chapter is to try to understand the production inefficiency of public hospitals in Queensland. While doing so, a recognized yet often overlooked phenomenon emerges where possible dramatic differences (and consequently very different policy implications) can be derived from different models, even within one paradigm of SFA models. This emphasizes the importance of exploring many alternative models, and scrutinizing their assumptions, before drawing policy implications, especially when such implications may substantially affect people’s lives, as is the case in the hospital sector.

The study evaluates the accident-adjusted dynamic efficiency of public bus operators providing bus transportation services in eight major metropolitan cities of India.

The slack-based measure (SBM)–undesirable window analysis approach is used to gauge the dynamic efficiency levels and identify the sources of inefficiency in bus transportation services. This innovative approach integrates the SBM model developed by Tone (2001, 2004) and the window analysis approach of Charnes et al. (1985). The main advantage of this approach is that one can explicitly incorporate the number of accidents in the production technology specification as an undesirable (bad) output and potently handle the issue of the “curse of dimensionality” in a small sample like ours.

The key empirical findings suggest wide variations in average efficiency levels across sample bus operators in metropolitan cities. The Chennai Transport Corporation is observed as the most efficient and consistent bus operator due to its most stable efficiency performance. The results additionally unveil that the role of managerial inefficiency was diminutive, and the scale-related issues were the real cause of sub-optimal or supra-optimal behaviour of sample bus operators in the resource-utilisation process.

There is an urgent requirement for effective policy intercessions to mitigate the sizeable observed inefficiency in the production process and resolve scale-related issues of public bus operators offering transit services in major metropolitan cities of India.

This paper is maybe the first to assess the dynamic efficiency of public bus transit systems in India's major metropolitan cities after treating accidents.

This study aims to investigate the intricate relationship between corruption and the credit costs faced by small and medium-sized enterprises (SMEs) in OECD countries, a critical yet underexplored area in financial crime research. The primary aim is to dissect and understand how corruption impacts SMEs’ access to credit, highlighting a significant yet overlooked aspect of financial crime. This research seeks to fill a gap in the literature by providing empirical insights into the economic consequences of corruption, specifically on SMEs financing.

This study used secondary panel data from the World Bank and OECD databases. The data covered the period 2007–2020 for 25 OECD countries. This study used interest rate for SMEs loans as a dependent variable and GDP per capita, inflation and corruption index as independent variables. This study used the panel autoregressive distributed lag (ARDL) model to examine the relationship between variables.

The empirical findings derived from Panel ARDL postulate an intriguing dichotomy in the effects of GDP per capita, inflation rate and corruption on interest rates in both the short and long run. It was discerned that an increase in GDP per capita and inflation rate correlates with a decrement in interest rates in the long run, suggesting a potential compromise by central banks between controlling inflation and fostering economic growth.

This paper makes a novel contribution to the field of financial crime by illuminating the often-overlooked economic dimensions of corruption in the context of SMEs financing. It provides a unique perspective on the ripple effects of corrupt practices in credit markets, enriching the academic discourse and informing practical approaches to combating financial crime.

Using cross-country data on the 1,000 largest global banks for 2019, the paper aims to examine the response of bank risk and returns to the pandemic.

The author employs weighted least squares (WLS) techniques for the purposes of analysis.

The findings suggest that banks with Islamic windows increased their riskiness in response to the pandemic, although there was not much impact on profitability. Additionally, the author categorizes banks based on certain major characteristics and find that these findings are manifest primarily for well-capitalized and less liquid banks.

Research as to the impact of the pandemic on banks' balance sheets has been an unaddressed area of research. By focusing on a large sample of banks across countries with both Islamic and conventional banking presence, the analysis sheds light on the balance sheet response of banks to the pandemic, an aspect that has not been addressed earlier.

The present study assesses the commercial bank profit efficiency and its relationship to banking sector competition in a rapidly growing emerging economy, India from 2009 to 2019 using stochastic frontier analysis (SFA).

Lerner indices, conventional and efficiency-adjusted, quantify competition. Two SFA models are employed to calculate alternative profit efficiency (inefficiency) scores: the two-step time-decay approach proposed by Battese and Coelli (1992) and the recently developed single-step pairwise difference estimator (PDE) by Belotti and Ilardi (2018). In the first step of the BC92 framework, profit inefficiency is calculated, and in the second step, Tobit and Fractional Regression Model (FRM) are utilized to evaluate profit inefficiency correlates. PDE concurrently solves the frontier and inefficiency equations using the maximum likelihood process.

The results suggest that foreign banks are less profit efficient than domestic equivalents, supporting the “home-field advantage” hypothesis in India. Further, increasing competition drives bank managers to make riskier lending and investment choices, decreasing bank profit efficiency. However, this effect varies depending on bank ownership and size.

Literature on the competition bank efficiency link is conspicuously scant, with a focus on technical and cost efficiency. Less is known regarding the influence of competition on bank profit efficiency. The article is one of the first to examine commercial bank profit efficiency and its relationship to banking sector competition. Additionally, the study work represents one of the first applications of the FRM presented by Papke and Wooldridge (1996) and the PDE provided by Belotti and Ilardi (2018).

This study aims to explore marketing strategies that UK fish farming businesses can use to gain a competitive advantage. The marketing strategies examined include product branding and core competencies, sales promotion, market positioning and segmentation.

A survey through an online questionnaire was mailed to five randomly selected trade associations of UK fish farming businesses and distributed to their registered members, of which 200 responded. Both male and female genders with different age groups and levels of experience in the UK fish farming business participated. In addition, ten articles were sampled for a systematic review.

Results show that UK fish farming businesses could increase sales by using ecolabels in product branding to attract premium prices, build consumer confidence and using high-quality packages for fish products will keep fish fresh for a longer period.

The scope of this research is limited to the UK. The findings cannot be generalised and used for other jurisdictions because of variable economic and market conditions.

A significant recommendation from this case study is that fish farming businesses need to be creative and innovative in ways such as leveraging branding, sales promotions and core competencies to win the trust and confidence of consumers. Most importantly, each fish farming business should know the specific marketing strategy that works for them; this case study shows that not all branding and sales promotion techniques enhance competitiveness. The scope of this research is limited to the UK. The findings cannot be generalised and used for other jurisdictions because of variable economic and market conditions.

The purpose of this study is to explore the antecedents of uncaptured sustainable value and strategies to generate opportunities to capture it in the circular supply chain of post-consumer used clothing.

This study is based on an inductive analysis of 21 semi-structured interviews conducted with various stakeholders in the circular clothing supply chain (for-profit and not-for-profit) using the value mapping approach, as previously applied in the literature on sustainable business models.

Fifteen antecedents of uncaptured sustainable value, and thirteen value opportunity strategies were revealed that hinder or generate multi-dimensional value types. Economic value is impacted the most, while there is lack of explicit understanding of the impact of these antecedents and strategies on environmental and social value capture. From a multi-stakeholder perspective, the ecosystem is emerging as new for-profit actors are developing novel process technologies, while not-for-profit actors are consolidating their positions by offering new service options. There is also an emerging “coopetition” between the different stakeholders.

More granularity in the different types of uncaptured value could be considered, and external supply chain stakeholders, such as the government, could be included, leading to more detailed value mapping.

This research provides practitioners with a value-mapping tool in circular clothing supply chains, thus providing a structured approach to explore, analyse and understand uncaptured value and value opportunities.

This extended value perspective draws upon the value-mapping approach from the sustainable business model literature and applies it in the context of the circular clothing supply chain. In doing so, this research illustrates circular clothing supply chains in a new way that facilitates an improved understanding of multi-dimensional and multi-stakeholder value for embedded actors.

Africa has been identified as an area where higher mortality happens due to un-accessibility to health care, drugs and other health facilities. Nigeria, as one of the African countries, is not excluded from such difficulties. This study aims to examine the determinants of efficient last-mile delivery at selected health facilities and the Kaduna State Health Supplies Management Agency (KADSHMA).

The study sourced data from KADSHMA and the health facilities’ staff, with a total of 261 observations used. Likewise, the respondents were picked from warehouses of each health facility and KADSHMA. The data was analysed using the partial least square structural equation modelling analysis to estimate the relationship among the variables of the study.

The study’s findings revealed that all five variables of the study (i.e. determinants) were significantly affecting the efficient last-mile delivery. Four constructs (delivery cost [DC], delivery time [DT], mode of delivery [MD] and facilities technology [FT]) have shown a positive and significant association with efficient last-mile delivery, whereas one variable (product mix [PM]) indicated a negative and significant association with efficient last-mile delivery. The study concludes that DC, DT, MD, FT and PM played significant roles in efficient last-mile delivery.

The study provides that specific means of transportation should always be on standby to transport health supplies. Time schedules should always be prepared and adhered to when transporting health supplies to the facilities, and each facility should network with robust technology to ease communication in terms of order and order planning. Additionally, facilities should try as much as possible to reduce the varieties of products when ordering health supplies, as it will increase the efficiency of the delivery.

To the best of the authors’ knowledge, this study is the first of its kind that considered these five variables (DC, DT, MD, FT and PM) with impact on the last-mile delivery in one model, especially in the Nigerian case. This is a great contribution to knowledge, more importantly, to the last-mile delivery of the health sector. The result confirmed the importance of these determinants (DC, DT, FT and PM) of last-mile delivery efficiency in saving lives.

The study evaluates the influence of human capital efficiency (HCE) and market power on bank performance.

The study employs two measures of bank performance: profitability and stability. Unbalanced panel data of 35 banks operating in Kenya for 2005–2020 collected from published financial statements is utilized. The study employs the feasible generalized least squares (FGLS) method in the analysis and the two-step system generalized method of moments (GMM) for robustness check.

The study affirms an inverted U-shaped relationship between market power and bank performance. The effect of market power on bank profitability is enhanced when a bank has highly efficient human capital. Further, HCE significantly impacts bank stability for banks with low HCE. Interestingly, a further increase in HCE narrows the net interest margins for banks with high HCE, conferring welfare benefits to customers as interest rate spreads shrink.

This study provides important insights into the role of human capital in bank performance. First, banks ought to invest in promoting HCE through training and development. As regulators root for bank consolidation, attention to HCE is imperative for fostering profitability and stability.

The study fills an essential gap in the literature by evaluating the effect of firm-level market power on bank performance in an emerging market. We adopt a novel stochastic frontier estimator to generate the Lerner index. Further, this is the first study known to the authors to evaluate the effect of market power on bank performance in the context of human capital efficiency variations.