Search results

This study used data envelopment analysis (DEA) models to measure financial efficiency of twelve commercial banks listed in the Egyptian stock exchange (CBLSE), along with evaluating changes to the financial efficiency during the period 2017–2019.

The study used BCC-I, cross-efficiency, super-efficiency models, and Malmquist productivity index (MPI) to assess financial efficiency of the examined banks. The available data from both inputs and outputs were analyzed using R. studio V.I.3. 1056 software.

Out of twelve banks examined, only four banks were efficient under BCC-I model over different years of the study period; however, only one bank (CIB) appeared to be the most efficient compared to other peers in the study sample. Moreover, MPI results revealed decreased financial efficiency during the study period, due to the decreased technological innovation, except for HDB. Tobit regression results confirmed that total assets and total equity are significant factors impacted financial efficiency of CBLSE.

This study sheds light on the importance of evaluating financial efficiency of CBLSE to all stakeholders, to pinpoint weaknesses in banks' performance, and for evaluating financial policies and investment decisions.

Several studies sought to implement different models of DEA to assess banking performance in different regions of the world, but very few studies examined financial efficiency of banks. To the best of authors’ knowledge, this study is one of those few that addressed financial efficiency of banks in Egypt.

This study aims to develop and test a framework for integration between data envelopment analysis (DEA) and artificial neural networks (ANN) to predict the best financial performance concerning return on assets and return on equity for banks listed on the Egyptian Exchange, to help managers generate what-if scenarios? For performance improvement and benchmarking.

The study empirically tested the three-stage DEA-ANN framework. First, DEA was used as a preprocessor of the banks’ efficiency scores. Second, a back-propagation neural network as a multi-layer perceptron-ANN’s model was designed using expected data sets from DEA to learn optimal performance patterns. Third, the superior performance of banks was forecasted.

The results indicated that banks are not operating under their most productive operations, and there is room for potential improvements to reach outperformance. Moreover, the neural networks’ empirical test results showed high correlations between the actual and expected values, with low prediction errors in both the test and prediction phases.

Based on best performance prediction, banks can generate alternative scenarios for future performance improvement and enabling managers to develop effective strategies for performance control under uncertainty and limited data. Besides, supporting the decision-making process and proactive management of performance.

Despite the growing research stream supporting DEA-ANN integration applications, these are still limited and scarce, especially in the Middle East and North Africa region. Therefore, the study trying to fill this gap to help bank managers predict the best financial performance.

This study used Data Envelopment Analysis (DEA) to measure and evaluate the operational efficiency of 26 isolation hospitals in Egypt during the COVID-19 pandemic, as well as identifying the most important inputs affecting their efficiency.

To measure the operational efficiency of isolation hospitals, this paper combined three interrelated methodologies including DEA, sensitivity analysis and Tobit regression, as well as three inputs (number of physicians, number of nurses and number of beds) and three outputs (number of infections, number of recoveries and number of deaths). Available data were analyzed through R v.4.0.1 software to achieve the study purpose.

Based on DEA analysis, out of 26 isolation hospitals, only 4 were found efficient according to CCR model and 12 out of 26 hospitals achieved efficiency under the BCC model, Tobit regression results confirmed that the number of nurses and the number of beds are common factors impacted the operational efficiency of isolation hospitals, while the number of physicians had no significant effect on efficiency.

The limits of this study related to measuring the operational efficiency of isolation hospitals in Egypt considering the available data for the period from February to August 2020. DEA analysis can also be an important benchmarking tool for measuring the operational efficiency of isolation hospitals, for identifying their ability to utilize and allocate their resources in an optimal manner (Demand vs Capacity Dilemma), which in turn, encountering this pandemic and protect citizens' health.

Despite the intensity of studies that dealt with measuring hospital efficiency, this study to the best of our knowledge is one of the first attempts to measure the efficiency of hospitals in Egypt in times of health' crisis, especially, during the COVID-19 pandemic, to identify the best allocation of resources to achieve the highest level of efficiency during this pandemic.

This study aims to examine performance assessment of organizational units through psychological empowerment (PE) and employee engagement (EE) approach and whether this relationship differs among efficient and inefficient organization units.

This study drew on merging the principal component analysis (PCA), data envelopment analysis (DEA) and partial least square-multigroup analysis (PLS-MGA) to benchmark the performance of organizational units affiliated with Zagazig University in Egypt using PE dimensions as inputs and EE as output. Besides investigating whether PE inputs have the same effect among efficient and inefficient units.

Performance assessment based on independent data showed that all the investigated organizational units are not at the same efficiency level. The results revealed that there are eight efficient units versus seven inefficient ones. Moreover, PLS-MGA results demonstrated that no significant differences concerning the impact of PE inputs on EE between efficient and inefficient units groups. Nevertheless, the effect of these inputs was slightly higher in the former.

Studies on EE performance in the service sector are scarce in the literature, this study is a novel contribution of exploring EE efficiency in Egypt as a developing economy. Specifically, using the PCA-DEA-structural equation modeling approach.

Given the remarkable increase in entrepreneurial activities initiated by women in the Egyptian context in addition to the scarcity of empirical studies on digital self-employment there, the authors of the present paper aim to identify what motivates women to engage in digital entrepreneurship, and to identify how those women establish their digital entrepreneurial activities.

The authors employed a qualitative research method through semi-structured interviews with 30 women entrepreneurs who own and manage digital businesses. Thematic analysis was subsequently used to determine the main ideas in the transcripts.

The authors have found that enjoying absolute independence, securing more time for family, guaranteeing an independent source of income in addition to the ease of accessing extensive online markets are the main motives behind the engagement of women in the Egyptian context in digital entrepreneurship activities. Moreover, the authors have also asserted that the minimal training and government support stimulate women entrepreneurs there to start and continue their digital business activities informally.

This paper contributes by filling a gap in entrepreneurship studies in which empirical studies on establishing and managing digital entrepreneurship among women in developing economies has been limited so far.

Corrosion inhibitors are widely used in industry, although in many cases their surface chemistry is not well understood. Several nitrogen‐containing organic compounds have been used as corrosion inhibitors. Corrosion inhibition is a surface process which involves the specific adsorption of inhibitors on the metal surface. The extent of inhibition of metallic corrosion may depend on the nature of the metal surface and extent of adsorption of the inhibitor. The type of interaction of the inhibitor on the metal surface during corrosion has been deduced from its adsorption characteristics.

The current status of nanotechnology research and development in Jordan is analyzed. In recent years, Jordanian institutions demonstrated considerable interest in the development and production of nanotechnology. Here the purpose of this paper is to provide detailed information about the status of nanotechnology in Jordan in terms of several factors that influence selectivity in nanotechnology and the number of published peer-reviewed research articles.

Several factors that influence selectivity in nanotechnology and the number of published peer-reviewed research articles were analyzed. A detailed analysis of the collected data reveals that the number of publications, citations, and patents is highly dependent on the amount of research fund.

The development in nanotechnology is associated with presence and accessibility of sensitive laboratory equipment. The nanotechnology research output in Jordan is still lower than it should be due to the lack of necessary laboratory infrastructure. This is due to the insufficient funds allocated to scientific research, the restrictive access to available instruments and the bureaucracy of some governmental departments. Compared to some developed countries, Jordan is noticeably behind in developing a nanotechnology system of research and industry. It will take time as well as technical and financial resources in order to achieve an advanced level in the field of nanotechnology in Jordan. Nevertheless, many Jordanian researchers are doing their best and are producing some good research articles.

The many applications to the same approach.

Time and publications’ resources.

Peer cooperation.

First comprehensive review ever. A base for researchers and decision makers.