Quantitative efficiency assessment based on the dynamic slack-based network data envelopment analysis for commercial banks in Ghana

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Nested dynamic network data envelopment analysis models with infinitely many decision making units for portfolio evaluation

Dynamic network data envelopment analysis model with fuzzy inputs and outputs: An application for Iranian Airlines

BackgroundIn recent years, measuring and evaluating the efficiency of health systems has been explored in the context of seeking resources to ensure the sustainability of ‘countries’ health and social systems and addressing various crises in the health sector. The study aims to quantify and compare the efficiency of OECD health systems in 2000, 2008, and 2016. The contribution to research in the field of efficiency in the healthcare system can be seen in the application of Dynamic Network Data Envelopment Analysis (DNDEA), which help us to analyse not only the overall efficiency of the healthcare system but analyse the overall efficiency as the result of the efficiencies of individual interconnected areas (public and medical care area). By applying the DNDEA model, we can realise the analysis not only within one year, but we can find out if the measures and improvements taken in the healthcare sector have a positive impact on its efficiency in a later period (eight-year interval).MethodsThe analysis focuses on assessing the efficiency of the health systems of OECD countries over three periods: 2000, 2008, and 2016. Data for this study were derived from the existing OECD database, which provides aggregated data on OECD countries on a comparable basis. In this way, it was possible to compare different countries whose national health statistics may have their characteristics. The input-oriented Dynamic Network Data Envelopment Analysis model was used for data processing. The efficiency of OECD health systems has been analysed and evaluated comprehensively and also separately in two divisions: public health sub-division and medical care sub-division. The analysis combines the application of conventional and unconventional methods of measuring efficiency in the health sector.ResultsThe results for the public health sub-division, medical care sub-division and overall health system for OECD countries under the assumption of constant returns to scale indicate that the average overall efficiency was 0.8801 in 2000, 0.8807 in 2008 and 0.8472 in 2016. The results of the input-oriented model with the assumption of constant returns to scale point to the overall average efficiency of health systems at the level of 0.8693 during the period. According to the Malmquist Index results, the OECD countries improved the efficiency over the years, with performance improvements of 19% in the public health division and 8% in the medical care division.ConclusionsThe results of the study are beneficial for health policymakers to assess and compare health systems in countries and to develop strategic national and regional health plans. Similarly, the result will support the development of international benchmarks in this area. The issue of health efficiency is an intriguing one that could be usefully explored in further research. A greater focus on combining non-parametric and parametric models could produce interesting findings for further research. The consistency in the publication and updating of the data on health statistics would help us establish a greater degree of accuracy.

Assessing the performance of water supply operations in Chinese water companies: A union dynamic multi-activity network data envelopment analysis

Purpose: Having regard for growing interest in the sustainability discourse, this study examined the moderating effect of corporate stability in the relationship between sustainability reporting practices and financial performance of commercial banks in Ghana. Methodology: Using data sampled from the annual reports of twenty (20) commercial banks in Ghana from the period 2010 to 2022, we used system General Method of Moments (GMM) estimation technique for analysis. Findings: The study found a significant negative effect of sustainability reporting practices on the financial performance of commercial banks in Ghana. However, the significant negative effect was found to be positive with the moderating role of corporate stability. The findings are robust against endogeneity and instruments proliferation through a Hansen J-test and Arellano-Bond Serial Correlation Test robustness check. Implications: The findings of the study will contribute to policy and regulation formulation in the area of sustainability practices. It also provides empirical basis for banks to make sustainability commitments, having regard to their stability status. Originality / Research value: The study is the first of its kind to examine the influence of corporate stability in the sustainability-performance relationship.

The objective of this paper is to assess the sustainability of supply chains by proposing a dynamic network data envelopment analysis (DNDEA) model in the presence of interval data, due to the fact that in many real-world applications, the condition of convexity in the production technology might be violated. To prevent this issue, a DNDEA model based on the free disposal hull (FDH) approach is developed. For the first time, this paper develops a DNDEA version of the free disposal hull (FDH) model in the context of the SCOR framework. It is also shown that this model always presents a finite efficiency score for assessing the sustainability of supply chains. Moreover, using this model, real benchmarks can be calculated to improve the sustainability of unsustainable supply chains. A case study in print industry is given. The results validate our proposed model.

Commercial banks are key in modern economies by mobilizing savings, allocating credit, and supporting sustainable economic growth. In recent years, growing climate risks, regulatory pressures, and stakeholder expectations have expanded the definition of bank performance beyond traditional financial indicators to include sustainability considerations. Green finance has therefore emerged as a strategic mechanism through which banks can align profitability objectives with environmental responsibility. Despite increasing policy attention and voluntary sustainability frameworks, the extent to which green finance influences the performance of commercial banks in developing economies such as Ghana, remains insufficiently documented. This study sought to assess the effect of green finance on the performance of commercial banks in Ghana, focusing on profitability, asset quality, and long-term financial sustainability. The study adopted a desktop review research design guided by a positivist research philosophy. Relevant studies were identified using key search terms related to green finance, green banking practices, sustainable finance, commercial bank performance, and climate finance. The findings from the reviewed studies indicate that green finance generally have positive influence on the performance of commercial banks. Banks engaging in green lending, environmentally screened investments, and sustainable finance practices tend to record improvements in profitability, asset quality, and performance stability. These gains are largely associated with enhanced risk management, reduced exposure to environmentally risky assets, and alignment with emerging sustainable growth sectors. The study concludes that green finance represents a viable pathway for enhancing the performance of commercial banks in Ghana, provided it is embedded within core banking strategies and supported by strong institutional and regulatory frameworks. In view of these findings, the study recommends that policymakers should support enabling frameworks and incentives to support effective green finance integration among commercial banks in Ghana. Keywords: Green finance; Commercial bank performance; Sustainable banking; Financial sustainability; Environmental risk management

The Effect of Leadership Styles on Employees’ Stress and Wellbeing: A Study of Commercial Banks in Ghana

The purpose of the study was to examine the influence of board audit committee characteristics on the financial performance of selected commercial banks in Ghana during the period of 2008 to 2017. The correlational design was employed. The study population was 23 commercial banks licensed under the Bank and Special Deposit Taking Institution Act with audit committee on their board and offices in Ghana as at December 2018. The sample size for the study was 13 commercial banks in Ghana. The lottery method of simple random sampling technique was used to select the 13 banks. The study made use of only secondary data. Statistical tools such as means, standard deviations, Pearson product moment correlation, and linear multiple regression analysis were used to analyse the data. The findings of the study revealed that when banks audit committee increase the frequency of their meetings, increase the number and quality of financial qualifications of member on board and also increase the size of the audit committee members on total board membership, it will have a significant influence on the banks’ financial performance. It was recommended to Bank of Ghana (BoG) and managers of the various commercial banks to ensure that audit committee members are independent, meaningfully represented at boards of the banks, and are people with expertise in accounting/finance.

Food security is a global challenge. With rising world population and demand for food being compounded by resource and arable land constraints, raising the efficiency of food production and use has become increasingly important. While much of the research on food security is focused on farm efficiency and productivity, most neglect post-harvest (PH) handling which is critical in determining the availability of food. In this study, we employ the network Data Envelopment Analysis (DEA) model to evaluate the PH efficiency of milling, using data from Kenya’s rice processing industry. The results show lower efficiency scores when using a network DEA model, which reflects its greater discriminatory power when compared to the standard DEA approach. The study also quantified sources of productive efficiency using a fractional regression model and identified storage space and distance to market as having an impact on drying efficiency; while experience, age of mill, servicing and energy type influenced milling efficiency. The results suggest that policy makers should focus on investing in drying technologies and storage facilities to improve drying efficiency. To improve milling efficiency, policy recommendations include enhancing millers’ access to better technologies, investing in reliable sources of energy and providing PH handling workshops to reduce PH losses.

This study evaluates the circular economy performance of global chemical companies from 2013 to 2022, focusing on production efficiency and circular efficiency. Dynamic network Data Envelopment Analysis model is employed to assess the overall, production and circular performance of firms. Additionally, management decision matrix is presented, offering firms a clearer understanding of their efficiency levels and a detailed projection analysis on the optimization adjustments needed for both resource inputs and outputs. The findings reveal varying levels of overall efficiency among the observed firms. While some companies have managed to maintain or improve their efficiency over the study period, others exhibit significant inefficiencies. Opportunities for operational streamlining and resource optimization are identified, particularly in reducing resource consumption without compromising production capacity. The analysis of circular efficiency further highlights substantial potential for improving sustainability practices, particularly through enhanced waste reuse and a reduction in environmental impact. This study provides practical implication of circular economy performance in the chemical industry, offering a new way to measure and improve resource efficiency and sustainability practices.

Universalization of Access to Sanitation Services and the Efficiency of Brazilian Water and Sewage Utility Companies: A Dynamic Network Analysis

Urban health efficiency is influenced by both urban planning decisions and the functioning of the public health system. However, there is currently a lack of effective methods to simultaneously examine urban planning and public health when assessing urban health efficiency. This study proposes a two-stage network data envelopment analysis (DEA) model for evaluating urban health efficiency. The urban planning and public health sectors act as interconnected stages where the public facilities and living quality are mediating variables. The urban health efficiencies of 303 Japanese cities are examined using the proposed model, showing that most Japanese cities still have room for urban planning improvement with pure technical efficiency ranging between 0.7 and 0.9. At the same time, most public health sectors of Japanese cities reach pure technical efficiencies larger than 0.95 but are limited by the scale efficiency. Further analysis points out that public health sectors are in decreasing-return-to-scale, meaning that excessive urban scale adversely affects urban health efficiency. Furthermore, cities that joined the Alliance for Healthy Cities (AFHC) performed better on average, suggesting that information sharing and national and international networking can boost urban health. The study shows that the proposed two-stage network DEA model can be applied to analyze urban health efficiency and identify the impact of technology and urban scale in different stages.

When the number of Decision-Making Units (DMUs) is not large enough compared to the total number of input parameters and outputs, traditional Data Envelopment Analysis (DEA) and Network Data Envelopment Analysis (NDEA) models often produce solutions that identify many DMUs as efficient, in addition to obtaining unrealistic weight distributions. In fact, this poor discrimination power and unrealistic weight distribution presented by DEA and NDEA models remain a major challenge, leading to the development of models to improve this performance. Thus, this paper proposes a Multiple Criteria Network Data Envelopment Analysis (MCNDEA), based on relational NDEA models. The idea of this model is to be used in network structures. To test the MCNDEA model, one a real instance linked to an evaluation problem of academic departments of a public university was used. Other instances were also used to validate the proposed MCNDEA, and these tests are included in the supplementary files. Finally, it should be noted that, in summary, the model proposed in this article had greater discrimination power of the analyzed DMUs, being able to identify the most efficient departments in each of the considered stages, besides pointing out to the University Management points of improvement regarding the best use of its resources for each department.