The paper aims to analyze the Technical Efficiency of 70 Commercial banks from 19 African countries from 2009-2020. Using the Data Envelopment Analysis (DEA) method of the two main approaches, Variable Return to Scale (VRS) and Constant Return to Scale (CRS) technique on a Panel Data. We find that African banks have a higher efficacy assessment with the VRS than the CRS technique, thus, with a Pure Technical Efficiency (PTE) score than Technical Efficiency (TE) . Our findings show that the majority of the banks are operating at very low levels of efficiency (not technically efficient), and inability to optimize the conversion of bank assets and liabilities into loan production for customers. Furthermore, the banks are operating inefficiently in scale, economic, and allocative manner due to mismatches in scale of production. Considering these findings, the implications of these inefficiencies extend to the overall economic development and financial stability of the region.

The increasing population in Indonesia results in the rising demand for consumer goods, including salt. Meanwhile, salt production in Indonesia remains traditional, using direct methods by evaporating seawater in open ponds near the coast, producing a final product called “solar salt”. This process depends on sunlight, air, weather, and seasonal climate conditions. This research aims to analyze the technical, technological, and managerial disparities among traditional solar salt farming businesses operated by local communities across regions in Madura Island—the foremost solar salt-producing region in Indonesia. This study employs primary data collected through surveys conducted during the production season in 2023/2024 in three regencies in Madura: Pamekasan, Sampang, and Sumenep. The structured questionnaires captured the input and output data. Meta-frontier Data Envelopment Analysis (meta-DEA) was applied to assess the technical efficiency of conventional solar salt productions across the research regions. The efficiency analysis revealed that, with the current production methods, solar salt farmers achieved an efficiency rate of 46.98%, with an average technical efficiency of 80.83%. This result shows that the decision-making units (DMUs) can enhance their technical efficiency by 19.07%. Meanwhile, the technology gap ratio (TGR) analysis indicates that Sumenep Regency has the highest TGR value, nearing the threshold of 1, suggesting a relatively low technology gap in this regency. The meta-DEA decomposition indicates that the determinant of the average meta-technical inefficiency among solar salt farmers is the technological disparities, with average technological gap inefficiency (TGI) values surpassing managerial gap inefficiency (MGI) values. Conversely, Sumenep Regency has a larger MGI than TGI value, implying that solar salt farmers in Sumenep possess lower managerial decision-making skills than in other regions. The findings suggest the need to enhance the adoption of the latest production technology innovations to address technological gaps in the research locations.

Farmers face various risks such as production risks in the use of technology, pests, climate change and natural disasters. Farmers in disaster-prone areas have different responses depending on their behavior towards the risks posed. The main problem in this research is how farmers behave towards production risks due to flooding and the technical efficiency of rice farming in flood-prone areas. The aim of this research is to analyze farmers' behavior towards production risks due to flooding and the technical efficiency of rice farmers in flood-prone areas. The results of this research will provide important information for policy simulations that the government can implement towards farmers affected by natural disasters and for sustainable disaster mitigation strategies. The novelty of this research is that it combines two theories, namely risk behavior and agricultural technical efficiency in producing disaster mitigation strategies. The research location was determined purposefully in Pasuruan and Bojonegoro Regencies. The data in this research are primary and secondary data with the sample in this research being farmers. The sampling technique in this research is a multi-stage cluster sampling technique. The analysis method in this research uses Just Pope. and the Cobb-Douglas production function model with the Stochastic Production Frontier approach. The target of these research findings is a model of the types of behavior regarding the risks of farmers who are flood victims, as well as the level of technical efficiency of rice farming and the factors that influence it. The expected findings are policy recommendations regarding disaster mitigation from economic and agricultural risk aspects to create sustainable agriculture.

Cement & material sector is instrumental in infrastructural development of any economy. The same holds about Saudi cement sector which has contributed substantially to the economic and construc-tion boom in Kingdom of Saudi Arabia (KSA). The cement sector of KSA holds the highest place among other GCC countries. Though, during the last couple of years, the sector seems to be grap-pled with capacity and weighted down due to certain reasons. Nevertheless, almost all of the cement companies in KSA are underplaying their actual capacities. Still, plenty of untapped growth oppor-tunities for cement sector are available in KSA and other GCC countries. Henceforth, considering the growth potential and taking cue from the current scenario of KSA cement sector, the current study endeavors to measure the efficiency of listed cement companies in KSA. The study endeavors to be engrossed in identifying a set of companies which plays on efficiency frontier. Therefore, the technical efficiency performance of fourteen listed cement companies in KSA was measured using Data Envelopment Analysis (DEA) methodology. Two basic models of DEA methodology (i.e. CRS & VRS) were used to estimate the pure and technical efficiency of identified DMUs over a pe-riod of four years from 2016 to 2019. The study reveals that over a period of four years and on an average efficiency scale, only 23% of the firms were purely technically efficient on a CRS scale, while 46% of the firms were technically efficient. Only 23% of the firms were scale and technically efficient. Though, companies in the sector have a vast potential to outperform on efficiency front. Yet, the overall efficiency level among Saudi cement companies are remained depressing. Moreo-ver, the study has noticed that the companies which are inefficient did not have a considerable dis-tance from the efficiency frontier. The study also provided significant insights on the input factors causing inefficiency and suggestion to achieve the total technical efficiency. Furthermore, the effi-ciency analysis also provided benchmarking firms, which are efficient under several criteria for oth-ers to imitate their best practices for becoming a significant player on efficiency frontier.

This paper examines the technical efficiency of small-scale manufacturing enterprises in Vietnam. The research uses primary data from a survey from June, 2019 to August, 2019 with 321 observations of six subsectors, including Textile, Garment; Building materials; Vegetable, Fruit and Bulb; Manufacture of Steel; Furniture Manufacturing and Food Processing. The research’s results show that the mean technical efficiency was 71.26 percent. However, there are considerable differences between sub-sectors ranging from 55.97 percent to 95.97 percent. The above mentioned results indicate that with the same level of inputs, Vietnamese small size enterprises can increase the present level of output by 44.03 percent; 38.05 percent; 30.92 percent; 26.07 percent; 21.05 percent and 4.08 percent for the sectors of Food Processing, Building Material; Textile, Garment; Vegetable, Fruit and Bulb; Manufacture of Steel and Furniture Manufacturing, respectively. The estimated results further suggest that manufacturing small-scale enterprise in Vietnam should improve their technology, labor quality and the initiative of input materials, especially, the sectors of Textile, Garment; Building Materials and Food Processing in order to move the production frontier upward as their technical efficiency are maintaining at low level.

The healthcare system is a vital element for any community, as it extremely affects the socio-economic development of any country. The current study aims to assess the performance of the healthcare systems of the countries above fifty million citizens in facing the spread of the COVID-19 pandemic since late December 2019. For this purpose, seven scenarios were adopted via the DEA methodology with six variables, which are the number of medical practitioners (doctors and nurses), hospital beds, Conducted Covid-19 tests, affected cases, recovered cases, and death cases. To shed light on the relative efficiency of drivers, the Tobit analysis was used. Besides, the study carried out various statistical tests for the DEA models' findings to validate the choice of the variables and the obtained scores. The DEA results reveal that less than half of the considered countries are relatively efficient. Moreover, the Tobit regression analysis showed that the main impact on the efficiency scores was due to the number of affected and recovered cases. Finally, the results of the tests of Spearman, Mann-Whitney U, and Kruskal-Wallis H indicate the internal validity and robustness of the chosen DEA models. The current study findings raise important implications, which can be helpful for decision makers regarding continuous improvement of performance, in which the findings assert the importance of achieving the best practices regarding relative efficiency through the linkage between the healthcare systems’ resources, and the needed outputs.

The ownership - efficiency relationship in a firm has always been an important topic. In this paper, we focus on the state owned versus non-state-owned status of Vietnamese manufacturing firms, to shed light into the relationship between these two variables when using a more state-of-the-art method as a stochastic meta-frontier method. Applying the method for two periods: one during the global economic crisis and the other after the end of the crisis, the study determines that in both periods, there was a strong evidence that non-state-owned firms performed much better than state owned counterpart. We also found that the difference became even larger during the harsh time and sub-industries with non-state-owned firms could outperform the state-owned firms, significantly.

Most recent studies are based on benchmarking analysis allowing the measure of company efficiency relatively to a reference performance. Benchmarking is a helpful tool to analyze and promote efficiency in insurance companies. The fast development of X-efficiency notion makes traditional performance measures (ROA, ROE, etc.) obsolete. Indeed, various methods have been used, various input-output measures have been proposed and various research fields have been explored in insurance company investigation. So, after reviewing most known efficiency concepts and their definitions, this section explores the literature review of two principal points of discussion: the first point is focused on the different used techniques to measure efficiency, including the developed approaches to define inputs, outputs and their prices. The second point represents an overview of efficiency investigations in insurance industry.

Measuring technical efficiency of different industries plays an important role on making managerial decisions. In this paper, we present an empirical study to measure technical efficiencies of various industries based on two-digit ISIC classification method in Iran. The proposed model uses stochastic frontier analysis (SFA) and implements maximum likelihood estimation (MLE) to estimate the parameters. The proposed study gathers the necessary data from year 2001 to year 2008 and implemented two methods where the second method is an extended model by using energy as part of efficiency estimation. The results of the survey indicate that auto industry was the most productive sector followed by equipments and the paper industry was among inefficient sectors.