درخت حوزه‌های تخصصی

This study assessed the use of social media application significantly influence the students' decision-making to enrol at private higher education institutions (HEIs) within the Malaysian context. The underpinning theory applied in this study was the Theory of Reasoned Action (TRA). A quantitative method, stratified sampling technique and systematic sampling technique applied in this study to test the proposed hypotheses based on a sample of 500 first-year students in their first academic semester at 23 selected private HEIs in Kuala Lumpur and Selangor. Data analysis was carried out using smartPLS software. The analysis outcome of the focal study had expounded a significant positive relationship between the use of social media application and students' decision-making as a direct relationship. Thus, analysis of the structural model had further verified that hypotheses h1 of the focal study were accepted. The result shows a  significant positive relationship between social media application and students' decision-making indicated by a path coefficient of  0.630, t-value of 24.103, and p-value of 0.000.

Accurate stock market prediction can assist in an efficient portfolio and risk management. However, accurately predicting stock price trends still is an elusive goal, not only because the stock market is affected by policies, market environment, and market sentiment, but also because stock price data is inherently complex, noisy, and nonlinear. Recently, the rapid development of deep learning can make the classifiers more robust, which can be used to solve nonlinear problems. This study proposes a hybrid framework using Long Short-Term Memory, Autoencoder, and Deep Neural Networks (LSTM-AE-DNNs). Specifically, LSTM-AE is responsible for extracting relevant features, and in order to predict price movement, the features are fed into two deep learning models based on a recurrent neural network (RNN) and multilayer perceptron (MLP). The dataset used for this is Dow Jones daily stock for 2008-2018, which was used in this article. Besides, to further assess the prediction performance of the proposed model, original stock features are fed to the single RNN and MLP models. The results showed that the proposed model gives the more accurate and best results compared to another. In particular, LSTM-AE+RNN shows a better performance than the LSTM-AE+MLP. In addition, hybrid models show better performance compared to a single DNN fed with the all-stock features directly.

The purpose of this study was to investigate the effect of business intelligence, foreign market knowledge and entrepreneurial characteristics on the speed of internationalization with the mediating role of organizational agility in SME pharmaceutical companies in Alborz province. The statistical population of this research was formed by those who hold a position and responsibility in SME pharmaceutical companies. In fact, they are decision makers. Therefore, it is possible to consider those who are part of the managerial positions, assistants, supervisors, senior decision makers, board members, and experts of different departments of SME pharmaceutical companies of Alborz province as members involved in the statistical population. did In this research, Klein's approach was used to determine the sample size. He believes that 10 or 20 samples are necessary for each variable. Considering the presence of 8 variables in the research, the sample size is estimated to be 20 times that is 160 samples. Non-probability sampling method was used. A researcher-made questionnaire was used to collect data and its Cronbach's alpha coefficient was 0.950, which indicates the reliability of the research tool. Also, the KMO test was confirmed in the validity of the research instrument construct. Smart PLS software was used to analyze the data and test the research hypotheses. The research findings out of the ten mentioned hypotheses show the confirmation of seven hypotheses and the rejection of three hypotheses. The foreign market knowledge construct did not show any positive and significant relationship with organizational agility structures and the speed of internationalization and also its mediating role was not confirmed. But other structures, namely business intelligence and entrepreneurial characteristics, showed a significant and positive relationship with organizational agility and the speed of internationalization, both directly and indirectly through the mediating role of organizational agility.

Internet of Things could be current paradigm, with promising recent wireless communication. Simultaneously as its will likely deliver compelling and effective arrangement, security of the gadgets and organization could be challenge issue. Therefore security has arisen as quite difficult for the IoT during this paper is expect to create security challenges of the IoT, structural design of IoT through handling security troubles at every layer of the design, key advancements in IoT and use of IoT.

Financial assessment has been of great interest to both academic and practitioners in the past decades. Among several performance assessment approaches, Data Envelopment Analysis (DEA) has become one of the crucial tools that have been commonly adopted to financially evaluate firms in various fields. The main aim of this review article is to review of DEA models in regarding to evaluation of the financial performance. This paper presents the first comprehensive and structured literature review of the use of DEA models for financially assessment. To this end, this paper reviewed and summarized the different models of DEA models that have been applied around the world to development of financial assessment problems. Consequently, a review of 455 published scholarly papers appearing in 160 journals between 1994 and 2021 have been obtained to achieve a comprehensive review of DEA application in financial efficiency. Accordingly, the selected articles have been categorized based on year of publication, authors, nationalities, scope of study, time duration, application area, study purpose, results, outcomes, etc. The discussion and the findings of this paper can be used as a guideline to analysts to determine the best fit financial assessment method when DEA evaluation is applied to any dataset. Future perspectives and challenges are discussed.

Due to the importance of public transportation, which has become today an important urban problem with special conditions, this study was conducted aimed at determining the parameters affecting the mathematical programming model of the appropriate transportation system. The study was performed by modeling method, and the problem was solved in three different sizes (small, medium and large) to show the efficiency of the model and the proposed solution methods. Some common test problems in the literature were selected and the required characteristics of the problem under study were defined for them as needed, since there are no sample test problems in the literature to examine the performance of the developed algorithms. The results indicated that some of the most important parameters affecting the designed mathematical model were movement risks, fatigue and drowsiness while driving, demands at the source node, demands at the destination node, number of vehicles across the network, the time interval between requests, and the time interval between two consecutive requests. The mentioned parameters were so effective that little changes in parameters such as demands at the source node, demands at the destination node, and the number of vehicles across the network significantly increased time and decreased profitability. the company has a significant effect on the debt cost rate and capital cost rate and does not have a significant effect on stock prices. Finally, the share price shows little sensitivity to the company's financial structure.