درخت حوزه‌های تخصصی

Objective: The purpose of this research is The effect of media tourism and sports diplomacy on product brands. Methodology: This is a correlational study and the statistical population of this study is PhD students in sports in Iran. Based on Morgan's table, 150 Individuals were selected by random method. In order to achieve the research goals, a comprehensive list of sports indicators was prepared and adjusted and a researcher - made questionnaire was developed. The validity of the questionnaire was confirmed by 15 sports management professors and their reliability was in a preliminary study with 30 subjects and Cronbach's alpha was calculated to be 0.909 . Descriptive and inferential statistical methods such as exploratory factor analysis, and confirmatory factor analysis were used to analyze the data using SPSS and LISREL software. Results: The results showed that the main variables have eight general dimensions of sport tourism, sport diplomacy, sports investment, sporting-cultural, sports exports, sports people-sports, sports achievements and media sports, and has a total of 50 indicators. Conclusion: According to the results of the research and the identified indicators, the proposed model is a suitable theoretical model for sport indicators affecting the brand of the country.

Organizations face many challenges in the current unpredictable and changing business in which superiority in competition is one of their main goals. In this trend, the field of production has moved towards a paradigm called "Agile Production". If an organization wants to be agile, it must shorten the workflow of the process and provide the conditions for saving time. If a hospital is agile, it can respond when faced with internal and external changes and compete with other hospitals and provide appropriate and fast services to patients. Today, hospitals are currently trying to continuously evaluate their performance due to the increasing advancement of technology. A method in evaluating the performance of the organization is the Balanced Score Card (BSC) approach. In this, indicators measure the desired goals in the organization in four aspects of Internal process, Growth and Learning, Financial and Customer. In this approach, important aspects of sustainable development are ignored , therefore, the new method of Sustainable Balanced Score Card (SBSC) is used to evaluate the performance, which takes into account the environmental index. This study aimed to determine the factors that can be important for evaluating agility in the hospital and then classify them based on the perspectives of SBSC. In the next step, using a questionnaire and statistical hypothesis test, the effectiveness of these factors was confirmed. Then, the importance of each perspective in the field of agility was determined by hierarchical analysis, and this model was presented using the scoring method. Accordingly, the "Economic" index had the highest priority and the "Environmental" index had the lowest priority. Due to the high importance of the Economic index, suggestions were made, the most important of which is the use of long-term loans for the promotion and development of hospitals, effective cooperation, and the use of various insurance services of insurance organizations, considering inventory and tools. , Equipment, essential devices in the warehouse for greater efficiency. Regarding the innovation of this research, we can refer to the evaluation of agility from the perspective of the scorecard by considering the criterion of stability in the hospital.

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.

This research aims to design an integrated model for digital marketing based on marketing intelligence and validate the model in the ISACO Company. The research uses a mixed-methods descriptive survey design. In the qualitative phase, the model and nine theoretical hypotheses were proposed using grounded theory and a semi-structured questionnaire. Fourteen academic experts and managers in the area of marketing and sales were interviewed until theoretical saturation was achieved. Then, the model and proposed hypotheses were validated using the quantitative method of structural equation modeling. A questionnaire rated by the Likert scale was distributed among 340 active employees in the relevant areas to the research topic with at least a Bachelor’s degree chosen by the convenience sampling method in the ISACO Company and affiliated companies. The structural model and hypotheses related to causal factors, core category, contextual factors, strategies, and consequences (except the moderating role of environmental factors) were validated by the research findings.

To improve the operation level of the companies tailored to industry 4.0 it is necessary to develop logistics system. In order to develop the logistics level, the first step is to measure the growth and evolution of all logistics process. For measuring the evolution and growth of the logistics system (LS), the processes and components of the logistics system and then the evolution level should be determined, at the end their level of evolution should be measured for each firms. The purpose of this paper is to determine the evolution level of the LS in the large industries of Iran. The research method is descriptive - applied and Data were gathered in two steps. First utilizing interviews with logistics experts for identifying the logistics process and components. Second step was data collection by check list in local visits and direct observation in firms. Checklist was completed in group sessions with the help of managers and experts in each firm. Using the mean of the logistics components and degree of adoptive (DOA) technique, evolution of LS was measured in industries. Results shown that firms with heavy products have little progress in the evolution of logistics compared to other firms and also the firms that have automatic production system will growth in logistic evolution better than others especially in intra-logistics and material handling. The method and result of this paper can be seen as a roadmap for managers and organizations and they will plan development and evolution of logistics processes.