درخت حوزه‌های تخصصی

Services are important major element of the economy in today's societies, and banks as one of the most important service organizations direct and support many of the community's economic activities. The purpose of this study was to develop an optimal model for East Azarbaijan banks' performance based on organization risk management using the standardized questionnaire of Kosovo 2017. In order to achieve this purpose, the director or assistant director, head or deputy head, bank managers and experts of banks were selected for statistical sampling and structural equation Modeling approach was used for estimating the model and tests. Organizational risk management factors including "written job descriptions and resources to describe personnel duties, fraud risk assessment with regard to how management and other employees participate" were assessed as factors af-fecting bank performance. Therefore, the structural problems of the banking sys-tem should be resolved so that this system can function and develop in the future, and consequently, in order to resolve the crisis of the banking system, it is neces-sary to reform the banking system.

Allocating fixed costs with undesirable data has recently been one of the most important issues for managers to discuss. Lack of attention to undesirable data may lead to incorrect cost allocation. Considering and determining undesirable inputs and outputs, data envelopment analysis (DEA) technique can be significantly helpful in determining the cost allocation strategy. In-puts and outputs are divided into two desirable and undesirable groups. Obviously, desirable inputs and undesirable outputs must be reduced and undesirable inputs and desirable outputs must be increased to improve performance. This manuscript presents two strategies for allocating fixed costs with undesirable data. In the first strategy, each decision making unit (DMU) first determines the minimum and maximum shares that it can receive from the fixed resources while the efficiency of that DMU and other DMUs re-mains the same after receiving the fixed resources. Finally, the decision maker chooses the fixed cost for each DMU between the minimum and maxi-mum cost values proposed. In the second strategy, the allocation of fixed costs is done using the CCR multiplicative model with undesirable data. The effectiveness of both methods is examined by an applied study on the commercial banks.

The purpose of this study is to develop proposals for the introduction of ecological, digital, professional, innovation and social public procurements in the national strategy on E-Public Procurement Reform and the strategy of procurements on the company-customer level. The relevance of this study is due to the need to ensure the development of “smart”, sustainable, inclusive economy, which will help reduce unemployment, poverty, facilitate access for people with disabilities to work, create opportunities for the education of young people and adults, stimulate innovations, meet expectations of citizens, solve environmental problems, carry out digital transformations taking into consideration the best world practices. The share of public procurements in expenditures of the state budget and gross domestic product of Ukraine, the dynamics of the procurement’s participants in the B2G segment is evaluated. In Ukraine, the largest share of expenditures falls on security and social protection, however, the prosperity index in these categories is critical (“red” zone). In order to form The E-Public Procurement Strategy, the best world practices of introducing innovative, environmental and social procurement criteria should be considered. Strategic directions of public procurement, namely – ecological, digital, professional, innovation and social, which provide sustainable and inclusive development of economy, are proposed.

Women’s safety is very important for around the world and many anti-women safety incidents are happened in current decades. Women's criminality is on the rise in India, particularly on an hourly basis 1000 criminal cases are filed according to Indraprastha and Kannon organizations. The Internet of Things (IoT) application will assist women in difficult situations. This design with Dc-RFO-IoT has an emergency application that can be useful to provide critical thinking and suggestions to women in rescue time. When the emergency soft button is pushed, notifications are sent to registered contacts as well as to women's hotline lines with GPS and GSM. A GPS sensor is also used to transmit the position with longitude and latitude. Every one minute, the receiver sends a link to your location, updating them on your current position. The attacker may shut the victim's mouth and prevent her from requesting assistance. The speaker on this gadget generates high-frequency sound. It will raise the alarm in the surrounding area and make the attacker fearful. This IoT with deep learning application is giving accurate outcomes and measures are improved. The performance measures like accuracy 93.43%, sensitivity 92.87%, Recall 98.34%, safety ratio 97.34%, and F measure 97,89% had been improved these are outperformance the methodology and compete with present models.

Agriculture is one of the essential sources of occupation and revenue in India. Conferring to existing statistics, most agriculturalists are facing severe losses due to poor farming yield. Farming activities are challenged by various environmental factors that affect agricultural productivity to a greater extent. The present farming situation is above the average of the process involves more biochemical bases for managing the diseases and other destructing facts. The foremost problems they are facing in day-to-day farming tasks are crop or plant diseases affecting productivity. Also, the growth of weeds along with field crops has been another challenge.  The technology has developed to rectify the problems using some machine learning algorithms like Random Forest algorithms, Decision trees, Naïve Bayes, KNN, K-Means clustering, Support vector machines. The result has been evaluated and observed through the performance evaluation metrics using confusion matrix, accuracy, precision, Sensitivity, specificity with the observations, research, and studies. The statistics have expressed the overall accuracy of 98% by achieving the detection of diseases in plants and by removing the weeds that ruin the growth of plants.

Chatbots is a computer software powered by artificial intelligence designed to replicate human interaction. It is also possible to refer to them as digital assistants that comprehend the capacities of humans. The bot interprets the user's intent, then processes their queries and provides prompt responses. Chatbots perform their most crucial role: to analyse and detect the intent of the user's request to extract relevant entities. AI-powered chatbots were introduced to improve operational efficiency, eventually saving organisational costs. This study investigates the role of system and service quality in customer satisfaction in banking services. One hundred forty-five usable data were used for analysis. Data were analysed using the Smart PLS. The results revealed that response time, usability, adaptability, empathy and responsiveness were insignificant for customer satisfaction. The result is important as it gave the insight point of customers with regards to the new services. Business organisations may need to introduce chatbots and perhaps make some improvements from time to time to provide better services.

Over the last few decades, both developed and developing countries have an increasing trend in technology but with an enormous gap, particularly in the education sector. The e-learning following institutions can achieve benefits by evaluating their e-learning readiness through up-front analysis. Moreover, several models have been introduced to measure e-learning readiness for developed countries but these are not adequate for developing countries.  This paper introduced the e-learning readiness evaluation model for the developing country, Libya, by considering the primary education sector. Furthermore, this study examines the e-learning level of readiness in the staff of the primary school. The purpose of this study is to evaluate the e-learning readiness of staff by directing factors of e-learning readiness i.e. cultural readiness, content readiness, and technology readiness. To achieve this objective, this paper collects data through questionnaires, and respondents are 110 staff member of primary schools in Yefren, Libya. Therefore, the multivariate analysis shows that the e-learning readiness factors have e significant relationship with the adoption of e-learning because most teachers are well prepared and ready. Likewise, results indicate that technology is the most significant factor instead of other e-learning readiness factors. According to the views of staff, there should be more content development training required for primary school staff. Thus, the demographic structure is inadequate to enhance the e-learning but the staff is ready for e-learning. Consequently, this study emphasizes the significance of cultural readiness and its relationship with the adoption of e-learning in primary education sectors’ development in Yefren, Libya.

The bibliometric study aims to map and expand respective knowledge by establishing connections between important actors in academic research regarding the government venture capitals (GVCs). The scope is to analyze documents published on Scopus database starting from 2011 to 2020.  Accordingly, the United States (U.S.) is the top country in all categories with China catching up. Alperovych, Quas, and Colombo are top co-authors. On the other hand, Leleux, Grilli, Lerner and Cumming are prolific authors. Articles by Grilli and Li Y are two most cited documents. Investments, venture capital, economics, public policy, and government are most co-occurrence index keywords. Research policy, venture capital, and journal of technology transfer, journal of business venturing and small business economics are top sources of cited documents. Closely associated themes with respect to the study of GVCs are government role in venture capital support, effective Innovation financing policies, performance differential, performance of portfolio companies, funding challenges and investment strategy, decision making model and critical success factors for IT startups. The analysis generated gaps and directions for future research consisting of fund’s structure and characteristics, key personnel’s work experience and network, geographic location, investment horizon, shareholding rights.

The global spread of internet technology and the associated advancements are making it easier for women entrepreneurs to manage the work-family boundary. However, there is a need for more research on digital entrepreneurship (DE), especially on how different degrees of DE influence the success of work-family boundary management (WFBM). This study explores the effect of extreme, moderate, and mild pursuit of DE on women’s abilities to manage the boundary between work and family. This study uses a quantitative research method and collected data from 312 women entrepreneurs. The results show that DE enables women entrepreneurs to manage the work-family boundary. We found that with extreme DE, women are more likely to experience high levels of cross-role interruption behaviours and perceived boundary control, while with moderate DE, women experience high levels of identity centrality of work and family roles. Therefore, this study contributes to the literature on women’s DE by investigating different degrees of DE and its effects on work-family boundary management. The study also contributes to the literature on WFBM through examining the dynamics of DE in enabling women entrepreneurs to manage work-family boundaries to different extents. Therefore, this study captures the interplay between DE and managing work-family boundaries, which facilitates our understanding of women entrepreneurship and the role DE has in enabling the agentic potential of entrepreneurial actors.

Profit is one of the most important factors influencing economic decision making, the changes of which depend on various factors. Banks, as one of the most important business units, have a special reliance on the concept of profitability and their performance is significantly influenced by macroeconomic conditions. Government economic policies are placed. This paper aims at applying the panel regression model to study the effect of monetary policy on the profitability of banks from 2006 to 2018 using data from 30 provinces to find appropriate policy recommendations for decision-making in the banking system. The research method was the use of GMM regression technique in the context of combined data. According to the results, the performance and profitability of banks are improved by the implementation of expansionary monetary policy. However, bank lending and price inflation have a negative effect on banks' performance. According to the results of this study, control variables such as the amount of overdue claims and GDP also had a positive effect on the performance of banks. Also at the macro level, with regard to the negative effects of Expansion monetary policy and the growth of liquidity, with the controlled implementation of Expansion monetary policy, it helps to improve the performance of banks in the banking system.

Financial markets play a key role in economic development, and the insurance industry as a financial institution can be the bedrock of economic growth. Thus, risk and performance appraisal are very important in the insurance industry. There are several methods for evaluate risk and efficiency in financial markets, but since the performance of insurance companies is different from other financial institutions for the risk acceptance of other organizations and individuals, it is necessary to rank factors affecting efficiency and risk in insurance companies separately based on the performance of companies prior to focus on the calculation method. This paper discussed factors affecting the financial risks of insurance companies and efficiency and their rankings using the Delphi qualitative method and collecting expert’s opinions as well as data from domestic and forign papers. The statistical population of the research is experts and specialists in the field of risk and insurance. Spss, Eviews and Excell 2013 were used to review the questionnaires and estimate the results. The results of this paper identified the factors affecting each of the risks of financial wealth, liquidity, credit, operations and efficiency, and in the ranking obtained through Friedman test, efficiency is the highest rank, followed by liquidity, operational and credit risk in the rankings.