درخت حوزه‌های تخصصی

Managing a single portfolio is a basic assumption in the most of research. However, in reality, an advisor manages many accounts at the same time; therefore, there is a significant dependency among portfolios and correlation between decisions on one portfolio with the performance of others, so the results of multi portfolio is different with classic models (single portfolio management, that portfolios are optimized independently) due to market impact and the trade dependency of one account to the other accounts. We propose a structural model to optimize accounts simultaneously, considering interdependences, decision’s correlation and mutual behavioral effects of managed portfolios. Moreover, to compare and analyze both single portfolio and multi portfolio approaches, real data from Tehran Stock Exchange in 1398 are used and model is solved with GAMS. Results indicate that multi portfolio optimization excel other approach and consequence notable improvement on the perspective of customer and advisor. Also, for the validation of the proposed model, the selected stocks are considered in pairs to solve the model and the results show the proper performance of the model with different stocks, thus indicating the validity of the model.

The purpose of this study is to develop proposals and recommendations for the implementation of a process model for the development of leadership qualities of public servants and justification of the conditions for ensuring its effectiveness in terms of digital transformation. The relevance of this study is due to the need to ensure development of the process of professionalization of the senior civil service personnel on the basis of development of leadership qualities that will contribute to the effective operation of the civil service of Ukraine, change management and successful implementation of reforms in Ukraine, taking into account the best world practices. The methodology for assessing the level of managerial competencies of public servants according to the degree of implementation of strategic (key) competencies has been developed. The assessment of managerial competencies according to the degree of their significance for civil servants, the expert group identified the most important management competencies. An approach to understanding has proposed interaction of leadership competencies with managerial competencies, a diagnostic model for assessing the leadership of public servants has been developed. To implement the model, a system of indicators has been developed - single, complex and integrated indicators of civil servants' leadership, using tools: a tree of civil servants' leadership indicators, matrices for the calculated civil servants' leadership indicator, measurement scales for the corresponding level of indicators.

With the development of a new stage of the industrial revolution, the importance of digitalization of business development tools is growing. The purpose of this article is to study the applied aspects of digital marketing tools usage for business development in the B2C market. To achieve the purpose and objectives of the study general and special methods are used: comparative analysis of the results of economic and statistical surveys; method of expert assessments by questionnaires using a 5-point Likert scale. The concordance coefficient was used to determine the consistency of the experts' opinions taking into account the related ranks in method of expert assessments. According to the results of the research, it is established that the Ukrainian business of the B2C sector was actively mastering digital marketing tools. The analysis of penetration level of digital technologies in the development of trade business showed the emergence of basic conditions for updating marketing tools to influence the B2C market. There is a rapid coverage rate of multi-purpose use of the Internet among consumers and businesses; gradual growth of digital skills among practitioners; positive dynamics of development of interactive services in the trade sphere. However, the level of use of the retail businesses websites remains low in many spheres of customer service. An important trend of the current development stage of the consumer market is the usage of business Internet platforms designed for mass dissemination of information. Effective marketing channels of interaction with consumers include social media (social networks, blogs or microblogs, websites with multimedia content, knowledge sharing tools), websites, e-shops, and sales via mobile devices. According to the results of expert evaluation, foreground digital technologies, which are able to bring business to a qualitatively new level of interaction with consumers and the provision of trade services have been identified. These are artificial intelligence and cognitive technologies, BigData, Internet of Things (IoT), and cloud computing. The structural and logical scheme of research of digital marketing tools is used for business development which includes two stages is offered. In the first stage, trendwatching, benchmarking and evaluation of internal opportunities for the use of digital marketing tools are performed. In the second stage, three components of digital readiness of business are defined: technological; competence; institutional. The obtained results form the basis of further research to determine the priorities of adaptive digital business behavior for the productive use of existing digital opportunities.

On a global scale, one of the prevalent causes of dementia is Alzheimer’s disease (AD). It will cause a steady deterioration in the individual from the mild stage to the severe stage, and thus impair their capacity to finish any tasks with no aid. The diagnosis is done with the utilization of existing methods which include medical history; neuropsychological testing as well as MRI (Magnetic Resonance Imaging), a lack of sensitivity as well as precision does affect the consistency of efficient procedures. With the deep learning network’s utilization, it is possible to create a framework for detecting specific AD characteristics from the MRI images. While automatic diagnosis is done with the application of diverse machine learning techniques, the existing ones do suffer from certain constraints with regards to accuracy. Thus, this work’s key goal is to increase the classification’s accuracy through the inclusion of a pre-processing approach prior to the deep learning model. The Alzheimer's disease Neuroimaging Initiative (ADNI) database of AD patients was used to develop a deep learning approach for AD identification. In addition, this study will present ideas for Haralick features, feature extraction from Local Binary Pattern (LBP), Artificial Neural Network (ANN), and Visual Geometry Group (VGG)-19 network techniques. The results of the experiments show that the deep learners offered are more effective than other systems already in use.

Most real-time speech signals are frequently disrupted by noise such as traffic, babbling, and background noises, among other things. The goal of speech denoising is to extract the clean speech signal from as many distorted components as possible. For speech denoising, many researchers worked on sparse representation and dictionary learning algorithms. These algorithms, however, have many disadvantages, including being overcomplete, computationally expensive, and susceptible to orthogonality restrictions, as well as a lack of arithmetic precision due to the usage of double-precision. We propose a greedy technique for dictionary learning with sparse representation to overcome these concerns. In this technique, the input signal's singular value decomposition is used to exploit orthogonality, and here the ℓ1-ℓ2 norm is employed to obtain sparsity to learn the dictionary. It improves dictionary learning by overcoming the orthogonality constraint, the three-sigma rule-based number of iterations, and the overcomplete nature. And this technique has resulted in improved performance as well as reduced computing complexity. With a bit-precision of Q7 fixed-point arithmetic, this approach is also used in resource-constrained embedded systems, and the performance is considerably better than other algorithms. The greedy approach outperforms the other two in terms of SNR, Short-Time Objective Intelligibility, and computing time.

The spread of COVID-19 pandemic starting in late 2019 has changed the way we conduct our teaching and learning activities especially in Higher Education Institutions (HEIs). Since March 2020, classes have been conducted via online platforms. As a consequence, students missed the campus life, teamwork has been given less emphasis, fieldwork, industry visits and community service have been put aside, and most importantly the achievement of the learning outcomes towards a certain extent has been compromised. The implications of these changes need to be highly considered as they might affect the quality of graduates. This paper intends to discuss the impact of COVID-19 pandemic on the education system and highlight some potential solutions that can be considered by the academics and the top management of HEIs to address the negative repercussions of the current practices. Some research implications are also highlighted in the paper.

One of the biggest shortcomings of urban spaces in most cities of the country is the lack of suitable sports spaces, which in addition to improving the health of the general public, especially the youth, creates a lively environment and can boost the development of the tourism industry. Many projects in the country, especially sports, are slow or stopped due to not evaluating the relevant risks, so the purpose of this study is to identify and prioritize investment risks in the country's sports projects. The present study is a positive research in terms of philosophical foundations and is applied in terms of orientation. The statistical population of the study includes experts in the field of sports tourism and the sampling method has been done judgmentally. To conduct the research, in the first stage, the risks of investing in sports projects were assessed through literature review. The number of these risks was 15, and after screening with a Binominal test, 6 factors were excluded. The remaining 9 factors were evaluated in terms of degree of impact with Dematel technique and 5 factors, i.e. market risks, economic risks, legal risks, financing risks and stakeholder conflict risks were selected as the most effective risks in terms of net effect index. Finally, these 5 risks were ranked by Aras decision technique and it was observed that the economic, market and financing risks, had the highest priority.

Banks as the largest financial intermediaries play a vital role in collecting savings and directing them toward manufacturing activities. Hence, assets and liabilities management is crucial for them and their depositors. In this study, through system dynamics approach, a dynamic model was proposed to manage assets and liabili-ties optimally. After building the model and conducting validation and sensitivity analysis, three scenarios were devised and were simulated and analyzed via the proposed model. The results revealed that taking effective decisions and actions to collect more deposits, especially time deposits as well as increasing the quality of credit assets (if allocated optimally) can be effective in improving the performance of banks. Therefore, using systems thinking and system dynamics can aid banks in managing their assets and liabilities optimally. mary of the significant items in the paper, including the results and conclusions.

The main role of financial reporting in capital markets is to provide the necessary conditions for the optimal allocation of resources and making correct and timely decisions. Achieving this goal is possible if the financial statements are consistent with economic realities or even have the slightest deviation from economic performance. However, over the past few decades, fraud detected in corporate financial reporting has increased the risk of financial reporting. Therefore, the current paper aims at investigating the impact of internal control weaknesses on financial reporting risk in companies listed on the Tehran Stock Exchange. In order to achieve the purpose of the research, using the method of systematic elimination of information related to 143 companies among the companies listed on the Tehran Stock Exchange in the period from 2009 to 2019 was collected. A multivariate regression model based on composite data was used to test the research hypothesis. The research findings show the significant positive impact of internal control weaknesses on financial reporting risk. The results indicate that reducing the weaknesses of internal control can reduce the risk of financial reporting and reduce information asymmetry and consequently improve accountability processes.

The objective of this study is to present a framework to increase the return and profitability and reduce credit risk of Mellat Bank customers by developing the RFM model. In this study, which was conducted as a case study in Mellat Bank of Iran, first the variables of RFM model were identified. In the next step, relevant weights of RFM variables were calculated using AHP technique. In the next step, using the K-means algorithm, customers were clustered based on weighted RFM and extended RFM. The result included customer clusters. The results indicated that the three clusters 5, 1, and 7 obtained the highest scores for receiving facilities and the coefficients for receiving facilities were equal to 0.271, 0.173, and 0.556, respectively. By determining the facility coefficient for the cluster and consequently for the customers presented in these top groups, granting facility becomes more transparent and more purposeful, and therefore, it will help the company increase profitability, reduce the churn among high-efficiency customers, and create value for customers. This research demonstrates a systematic method for granting facilities to recognize the true value based on the capability and prevention of arbitrary acts

The complexity of the competitive business environment has highlighted the need to be aware of the organization's strengths and weaknesses and to continuously improve processes. Therefore, managers are looking for a solution for performance measurement of their organization to be able to promote and improve their organization. Evaluating the performance of listed companies in the stock exchange organization is important because in addition to the managers of the organizations, stock traders can also evaluate the companies and make the necessary decisions about holding, selling or buying the shares of these companies in a timely manner. One of the organization's performance measurement solutions is to use financial ratios. Given that a separate study of financial ratios does not provide a correct view of the efficiency of the organization, so the aggregation of the effect of financial ratios seems to be effective. DEA and MCDM are suitable because they enable the achievement of performance index by considering several factors simultaneously, so the performance obtained from this method is reliable. the main purpose of this study is to ranking pharmaceutical companies in the Tehran Stock Exchange between the years 2018 and 2020 using DEA approach and MCDM to provide a single ranking through the Copeland method.

Nowadays, the rapid growth of data in organizations has caused managers to look for a way to analyze them. Extracting useful knowledge from aggregation data can lead to appropriate strategic decision-making for the organization. This paper suggests an application of hybrid network based on amount month demand in every ATM device based on transaction mean of 9 months for 1377 devices to obtain customer behavior patterns, to do so, first designed a basic model based on an auto-regressive with exogenous input network (NARX) then, the optimization of the weight and bias of the designed network is made by the genetic algorithm (GA). As a result, finding the weights of the network represents a nonlinear optimization problem that is solved by the genetic algorithm. Paper results show that the NARX-ANFIS Hybrid network using GA for the learning of rules and to optimize the network weights and weights of the network and the fixed threshold can improve the accuracy of the prediction model. Also, classic models are more efficient and increased benefits and lower financing costs and more rational inventory cash control. As well, the designed model can lead to increase benefits and decrease costs in the bank so that, exact forecast and optimal cash upload in ATMs will lead to increase funds on the bank and rise customers and popularity the brand of the bank.

The increase in non-performing loans considerably reduces profit in the banking systems. To solve these problems, factors influencing the collection of non-performing loans have to be examined in a hopeful attempt to reduce it to an ac-ceptable level. The present study is conducted to analyze and study factors influ-encing the collection of non-performing loans in Shahr Bank. This research is an applied study regarding its goal. It was conducted in two sections, namely the qualitative and quantitative sections. In the qualitative sections, the factors influ-encing the collection of receivables were identified using the theoretical literature and interviews with senior managers of Shahr Bank through the encoding process. In the quantitative section, data was collected by surveying the opinions of 12 experts, including senior managers of Shahr Bank in 2020 using a questionnaire. Thereafter, the factors were selected using the fuzzy Delphi technique and the relationships between them were determined using the fuzzy DEMATEL method. Finally, the factors were weighted and prioritized using the fuzzy ANP method. The research findings showed that non-performing loans can be collected through six types of factors including organizational, regulatory, customer, banking, envi-ronmental, and operational factors. The environmental factor is the most influential factor, while the operational factor is the most influenced and most important factor. In addition, behavioural, contextual, and structural sub-factors have the highest level of importance in the collection of non-performing loans in the order mentioned. These findings can help bank managers make decisions to improve the collection of receivables.

مدیران با ثبات این توانایی را دارند که جریان های نقدی مازاد درون شرکت را به سمت فرصت های سرمایه گذاری مؤثر و سودآور هدایت کنند. هدف اصلی این تحقیق بررسی رابطه بین ثبات هیئت مدیره، کارایی سرمایه گذاری و دارایی های نقدی مازاد است. طرح/روش/روش شناسی: جامعه آماری این پژوهش شرکت های فعال در بورس اوراق بهادار تهران با گزینش سیستماتیک 140 شرکت در بازه زمانی 1394 تا 1401 می باشد. این تحقیق از نظر هدف کاربردی و با استفاده از رگرسیون خطی چندگانه می باشد. بر اساس داده های تابلویی برای آزمون فرضیه ها. یافته ها: یافته های تحقیق حاکی از وجود رابطه مثبت و معنادار بین ثبات هیئت مدیره و کارایی سرمایه گذاری است. به عبارت دیگر، شرکت هایی با اعضای هیئت مدیره پایدارتر، کارایی سرمایه گذاری بالاتری دارند. همچنین، نتایج نشان می دهد که بین ثبات هیئت مدیره و وجه نقد مازاد رابطه معنادار و منفی وجود دارد. شرکت هایی که ثبات هیئت مدیره بالاتری دارند، میزان نقدینگی مازاد کمتری دارند. این یافته ها نشان می دهد که ثبات هیئت مدیره نقش مهمی در کارایی سرمایه گذاری و مدیریت نقدینگی در شرکت ها ایفا می کند.

هدف: هدف اصلی این پژوهش، بررسی تأثیر عدالت سازمانی بر اعتماد سازمانی و همچنین تأثیر عدالت سازمانی از طریق اعتماد سازمانی بر وفاداری سازمانی کارکنان شرکت برق منطقه ای خراسان است. طرح/روش/روش شناسی: روش انجام تحقیق توصیفی و پیمایشی است. جامعه آماری این تحقیق شامل کلیه کارکنان شرکت برق منطقه ای خراسان مشهد می باشد به طوری که 93 نفر به روش نمونه گیری تصادفی ساده و بدون جایگزینی به عنوان نمونه مورد بررسی انتخاب شدند. برای جمع آوری اطلاعات مربوط به عدالت، اعتماد و وفاداری سازمانی از پرسشنامه استاندارد استفاده شد. پایایی پرسشنامه ها با استفاده از ضریب آلفای کرونباخ تأیید گردید. به منظور تجزیه و تحلیل داده ها از آمار توصیفی و استنباطی استفاده شد. در آمار استنباطی از مدل سازی معادلات ساختاری (SEM) و تحلیل مسیر استفاده شد. یافته ها: نتایج به دست آمده از پژوهش نشان داد که عدالت سازمانی تأثیر مثبت و معناداری بر اعتماد سازمانی داشته است. به عبارت دیگر، می توان ادعا کرد که اگر مدیران به بهبود فضای عدالت در سازمان بپردازند و به آن ادای احترام کنند، می توان انتظار داشت که سطح اعتماد سازمانی بهبود یابد. همچنین نتایج نشان داد که عدالت سازمانی از طریق اعتماد سازمانی تأثیر معناداری بر وفاداری سازمانی ندارد و این بدان معناست که تأثیر مثبت و معنادار عدالت سازمانی بر اعتماد سازمانی نمی تواند منجر به پیدایش وفاداری کارکنان نسبت به سازمان آنها شود.