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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.

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.

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 direct effect of shocks is to create uncertainty in economic variables. These unpredictable fluctuations influence all economic decisions of the government and the private sector. Also, the formation of people's expectations causes these shocks to have dynamic effects on all economic variables. Inflation is a general, disproportionate, and self-inflicted rise in prices that is often irreversible. The purpose of this study is to investigate the structure of inflation and unemployment of the new Keynesian model with a dynamic general equilibrium approach. Also in this study, dynamic CGE models of long-term relationships related to the decisions of economic institutions such as households and investors were used. Data were analyzed using the proposed practical models. According to the results, inflation in the whole country increases with currency shock. The stronger the currency shock, the stronger the consequent increase in inflation. But unemployment is temporarily reduced by a currency shock.

The purpose of this paper is to provide a new approach to incorporating uncertainty into assessing the profitability of investment projects. In the real world, the capital budgeting problem is accompanied by uncertainty and risk associated dealing with imprecise data. The major contribution of this research is the development of a novel approach to evaluating the profitability of an investment project in uncertainty condition. At first, we presented a new discount method that can be used by investors when they wants to be able to make an investment decision. That is, we developed a new method to evaluate the profitability of investment projects by or-dered fuzzy net present value (OFNPV). In addition, ordered fuzzy numbers (OFN) are used to describe the dynamics of changes of the defined investment parameters in the assumed time horizon. By using ordered fuzzy numbers, we develop an effective tool for assessing the profitability of investment projects. This assessment tool not only enables decision-makers to decide under uncertainty conditions whether or not a given investment project should be carried out or rejected, but also facilitates selecting the most effective project, e.g. a project with the most expected probability of success.

Providing credit facilities to clients can be regarded as one of the most important tasks of banks. As a result, the current research is carried out with the aim of developing a model of financial and non-financial factors that influence credit risk in the Maskan Bank. This study was divided into two sections: qualitative and quantitative. In the qualitative portion, the Delphi technique was used to identify financial and non-financial variables impacting credit risk in the Maskan Bank by interviewing 18 experts. In the quantitative section, the selected components of the questionnaire were initially created in a 5-point Likert scale. The questionnaire was then presented to 361 legal clients of Maskan Bank from the statistical sam-ple of the quantitative section. The quantitative component was completed using LISREL software and modeling the structural equations of SEM. Three primary components (financial, market, and management) and 33 sub-components were identified as financial and non-financial indicators impacting credit risk based on the results of the qualitative section. The quantitative findings also revealed that the indicators of guarantee status in the financial component, price level in the market component, and manpower motivation and productivity, as well as man-agement continuity and trade in the management component, had the largest factor loads.

In this research, using Analytic Hierarchy Process (AHP) and TOPSIS method (TOP) based on financial criteria, earnings per share, dividend per share, operating cash flow growth, earnings per share growth, beta (systematic) risk, volatility Operating profit, stock liquidity and price-to-earnings ratio selected according to the opinions of investment experts, formed a portfolio. Then, the criteria for evaluating the performance of risk-adjusted portfolios according to modern portfolio theory (Sharp, Trainer and Alpha Jensen) were calculated based on monthly stock prices during the 5-year period from 1393 to 1397 and com-pared with the criteria for evaluating portfolio performance according to Marko-witz model. The results showed that the selection of stock portfolio using the mentioned financial criteria and using the Analytic Hierarchy Process (AHP) model leads to the acquisition of adjusted returns with more risk than the Marko-witz optimization model and the TOPSIS model (TOP).

The article justified the feasibility of an investment project by analysing the performance indicators while taking into account risk and uncertainty of the use of information technologies. The impact of the above calculations of the investment project results is due to the fact that the evaluation of the investment performance depends on the projected cash flows. The purpose of the article is to assess the impact of risks on making investment decisions using information technologies in order to increase the financial security of enterprises. Methodological and practical aspects of risk modelling of the investment project were further developed, using the Monte Carlo method, which allows to construct a model by minimizing data, as well as to maximize the value of data used in the model. This model involves the use of probability theory and random number tables. The results show the distribution of probabilities of the successful project variable and the coefficient of variation of the performance indicator, allowing the investor to take uncertainty into account when making a decision.

Online reviews play a crucial role in the consumer decision-making process in the glamping industry. Some reviews are misleading; therefore, users need to identify credible reviews to form objective opinions. This study examined dimensions of perceived review credibility and its influence on purchase intention within the glamping business. Online surveys were conducted with respondents with relevant travel experiences to examine the key credibility factors. Findings identified that review length, amount of detail, writing style, and travelers’ images; as well as mixed, moderate, and two-sided reviews influence perceived review credibility. It was also found that perceived review credibility influences purchase intention; that management response impacts perceived company credibility and purchase intention; and that personalized management response is valuable for the perceived credibility and purchase intention. A revised conceptual framework was developed to demonstrate the sources of perceived credible online reviews and the role of management responses in the reviews. In addition to the theoretical contribution, this study can have practical marketing implications for businesses when creating online promotional material for their products and engaging with customers

This research aims to evaluate the effect of consumer traits, service quality, perception-based factors, customer satisfaction, and e-trust on electronic brand love and e-loyalty. In this study, a cross-sectional survey is conducted based on the questionnaire method to collect data from a sample of 300 customers of the Digikala Website in Isfahan, Iran. Structural equation modeling (SEM) is used to test the research hypotheses. According to the results, the service quality, consumer traits, and perception-based factors significantly affected customer satisfaction. Also, e-brand love had a significant impact on e-trust and e-loyalty; e-trust significantly affected e-brand love and e-loyalty, and e-brand love had a significant impact on e-loyalty. To the best of the authors’ knowledge, this research stands among the first to evaluate the factors affecting electronic brand love and loyalty. The evaluation of brand love on loyalty demonstrated that the greater the amount of love and fascination with a brand, the higher the positive effect on consumer loyalty. Overall, managers are recommended to do their best to eliminate misunderstandings and create an interest in consumers, ultimately leading to greater customer loyalty. Managers should pay more attention to brand experience dimensions, such as sensory marketing. In this regard, creating a brand community by e-retailers is very helpful.

With the rapid advancement of information and communication technology (ICT), public administration has adopted the concept of e-government. The academic literature produced many studies in the field of E-government (E-GOV) services, however, there is limited research on such services from the perspective of bibliometric and Network analysis. Therefore, this study aims to present a bibliometric and network analysis of the E-government services literature review obtained from the Scopus database, published between 2011 to 2021. This study uses a five-step method including (1) defining keywords, (2) initializing search outcomes, (3) inclusion and exclusion of some elements of the initial result, (4) compiling initial data statistics, and (5) undertaking analysis of data. The analysis starts by identifying more than 4,880 published articles related to E-government services published between 2011 and 2021. The study findings revealed that the highest number of publications on the E-government Service was in 2019 (102 articles), the top contributing affiliation was Brunel University London, the leading influential country was the USA, and the top contributing Source was Electronic Government. Furthermore, Lu J. occupied the first rank in the list of the most influential authors in terms of citations, while Weerakkody V. occupied the list of the top authors with high publications 20 papers. Likewise, this study showed that there is a collaboration among some authors. This research identified four research clusters by which researchers could be encouraged to widen the research of E-government services in the future. The bibliometric and network analysis of E-government services helps to graphically display the publication's assessment over time and identify domains of current studies' interests and potential directions for further studies. Finally, this research draws a roadmap for future investigation into E-government services.