درخت حوزه‌های تخصصی

Penetration of smartphones and increasing use of social media on always-on devices has attracted the attention of enterprises and organizations to benefit from such platforms for better understanding of customers’ needs and more effectively communicate with potential consumers. For this purpose, the present study investigates the impact of social media adoption and media needs on online purchasing behavior. This study has also examined the moderating role of media type, gender and age in the relationship between variables of social media adoption and online purchasing behavior. A total of 410 questionnaires were collected on social media such as Instagram, Telegram and WhatsApp. SEM technique using PLS used as the analytical method to empirically test the proposed hypotheses. Results show that the effects of tension dimension on online purchasing behavior is mediated by social media adoption. Moreover, the effects of social media adoption on online purchasing behavior are moderated by age and medium type based on Multi-Group Analysis. The IPMA matrix shows that social media adoption had the highest importance, but the lowest performance. This study is significant in terms of innovation due to the use of new indicators effective in the area of statistical analyses. The use of FIMIX, CTA, permutation test, MGA, and IPMA matrix analyses is part of it.

Security solutions of stereo images are always a major concern during the transmission and communication. In this manuscript, a simple yet efficient framework for encrypting stereo images is formulated using discrete cosine transform (DCT), generalized logistic map, Schur decomposition and magic square method. The framework initiated with the integration of DCT and generalized logistic map to unify both pair of images. This unified image is then encrypted using the Schur decomposition and magic square method. The various experiments and analysis have been done to explore the validity, proficiency and performance of the purport framework.

The purpose of this study is to explore and determinants the risk management and prevention in credit card business of Malaysian commercial banks. There were five factors derived through the literature and experimental investigation that are affecting the banks due to credit card which are External Fraud Risk, Internal Operational Risk, Credit Risk of Cardholders, Science and Technology and Intermediary Agency Trades Risk. Hence, 250 respondents participated in this study from state of Selangor and Federal Capital Kuala Lumpur. The data was collected and analyzed by SPPS software and it was concluded that that External fraud risk, Internal operational risk, Credit risk of Cardholder, Science and technology are positively correlated with the Credit card business risks of commercial Banks in Malaysia. These papers have highlighted suggestion for future research to develop this study further by considering the data derived from this study by using Delphi Technique

The purpose of research is focused on the insight into the future of Bitcoin on the financial situation, its implications and challenges. The problem of study is to investigate how to deal with a new type of digital currencies (such Bitcoin) that does not have a physical presence and there is no specific body to issue. Thus, this study aims to identify the nature of Bitcoin currency and what are the challenges associated with it as well as exchange rates with some currencies, as the research hypothesized the main hypothesis that Bitcoin will contribute to financial development in the future, the research also used the analytical rooted approach to present concepts and data, using financial technical analysis to display the results The research also came up with a number of conclusions and recommendations. The results of paper significantly contribute to the literature through providing evidence from financial data of Bitcoin.

The ability of now-casting and eventuality is the most crucial and vital achievement of big data analytics in the area of policy-making. To recognize the trends and to render a real image of the current condition and alarming immediate indicators, the significance and the specific positions of big data in policy-making are undeniable. Moreover, the requirement for policy-making institutions to produce a structured model based on big data analytics for now-casting and eventuality of predictive policies is growing rapidly. The literature review demonstrates that a comprehensive model to assist policy-making institutions by providing all components and indicators in now-casting of predictive policies based on big data analytics is not devised yet. The presentation of the model is the main finding of this research. This research aims to provide a comprehensive model of now-casting and eventuality of predictive policies based on big data analytics for policy-making institutions. The research findings indicate that the dimensions of the comprehensive model include: the alignment of now-casting strategies and the big data analytics’ architecture, now-casting ecosystem, now-casting data resources, now-casting analytics, now-casting model and now-casting skill. The results of using the model were analyzed and the recommendations were presented.

Heart disease is stated as the world's biggest killer. The risk factors of this deadly disease are due to some bad habits such as being overweight, bad eating diet, smoking, assumption of alcohol, etc. Nevertheless, patients can live a healthy lifestyle if they have the proper guidance of persuasive-emotional featured technologies. In line with this, this study focuses on developing an emotional-persuasive habit-change support mobile application called BeHabit to improve heart disease patients’ lifestyles. Persuasive-emotional features are two different features that are integrated with BeHabit to distinguish this application from the existing ones. The proposed system is designed, implemented, tested, and evaluated by 10 users. In conclusion, the users are satisfied to used BeHabit to change their bad habits. Emotional and persuasive features that are integrated into BeHabit are the key to help patients to change their bad habits. BeHabit and the integrated feature can be used as a guideline for healthcare developers and providers for the improvement of mHealth services.

The purpose of this research was to identify the skills and abilities learners need in a digital learning environment during the Corona crisis. The research approach was applied in terms of objective and the data collected using the mixed-method approach. In the first part, using a qualitative approach and a document search method, 33 components (related to the skills and abilities of e-learners) were identified, and then19 components out of 33 with the highest frequencies were selected. The target population for this study included all MA students of the University of Tehran who had the experience of studying in an online learning environment, then 374 individuals were selected as a sample using the random sampling method. In the second part, using a quantitative approach and a descriptive-analytical research method, the questionnaire developed by the researcher relies on 19 components identified in the previous step. The experts' opinions proved the validity of the questionnaire—moreover, its reliability in 0.94 (Cronbach alpha). The data was analyzed by SPSS and LISREL, and the results of the data analysis demonstrate that the proposed model is a good fit. Among the 19 components surveyed, all are above average. Finally, the results indicated that the most critical components from e-learners’ view which more critical in digital learning were effective communication, use of the computer, active learning, learning skills, resilience, motivation toward e-learning, emotional intelligence, interaction with e-learning system, self-direct learning, time management, flexibility and adaptability, critical thinking, creativity, asking someone for help, leadership skills, stress management, self-organized, cognitive skills and self-assessment

Although Blockchain can significantly change the future of ERP systems as an innovative tech-nology, few researchers have gone into the details of this development. Most have given an overview of the changes ahead. Therefore, in this research, we have tried to use the method of Exploratory Content Analysis (ECA) by reviewing more than three hundred scientific articles in the field of Blockchain to analyze the effects of this technology on ERP system modules such as supply chain management, maintenance, finance, project management, manufacturing, and hu-man capital management. The result of this exploratory research is an architectural model for a blockchain-based ERP system. The researchers describe the functions of this system carefully, and the role of supporting technologies such as Smart Contract, IoT, Digital Wallet, Cloud Com-puting, and Building Information Model is clarified. We genuinely believe that this research could use as a reference model for ERP vendors and researchers in information systems and business process management