درخت حوزه‌های تخصصی

In recent years, Blockchain technology has been recognized as one of the most important new technologies affecting businesses and society, with a very bright future ahead. This technology is known as one of the most critical technologies of industry 4. Given that Blockchain technology is a new concept, before implementing it, the organization must understand it and be prepared to accept it; otherwise, the organization will incur irreparable damages. The main purpose of this study is to provide a framework within which organizations can evaluate their readiness to implement Blockchain technology. For this purpose, after a library study and systematic literature review, this study provided the initial research framework using the meta-synthesis method. Finally, the Lawshe model was applied to validate the proposed framework for the organization's readiness to implement Blockchain technology. Based on the findings, the final established framework included seven main dimensions, including Blockchain-based business strategy, operations of a distributed system, culture, people in Blockchain decentralized network, decentralized governance, technology, and Blockchain-based product traceability. Besides, 37 main criteria affected these dimensions, which can help companies increase the level of Blockchain technology readiness. Finally, this framework was used to measure the readiness of an airline company. According to the results of the analysis, Blockchain-based business strategy, culture, and Blockchain-based product traceability showed a medium level of readiness. Moreover, none of the main dimensions of Blockchain technology readiness were sufficiently prepared in this case study. This paper suggests practical recommendations to improve the level of Blockchain technology readiness for the managers

Sentiment Analysis or opinion mining is NLP's method to computationally identify and categorize user opinions expressed in textual data.  Mainly it is used to determine the user's opinions, emotions, appraisals, or judgments towards a specific event, topic, product, etc. is positive, negative, or neutral. In this approach, a huge amount of digital data generated online from blogs and social media websites is gathered and analyzed to discover the insights and help make business decisions. Social media is web-based applications that are designed and developed to allow people to share digital content in real-time quickly and efficiently.  Many people define social media as apps on their Smartphone or tablet, but the truth is, this communication tool started with computers. It became an essential and inseparable part of human life. Most business uses social media to market products, promote brands, and connect to current customers and foster new business. Online social media data is pervasive. It allows people to post their opinions and sentiments about products, events, and other people in the form of short text messages. For example, Twitter is an online social networking service where users post and interact with short messages, called "tweets." Hence, currently, social media has become a prospective source for businesses to discover people's sentiments and opinions about a particular event or product. This paper focuses on the development of a Multinomial Naïve Bayes Based social media data emotion analyzer and sentiment classifier. This paper also explains various enriched methods used in pre-processing techniques. This paper also focuses on various Machine Learning Techniques and steps to use the text classifier and different types of language models.

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.

It has been proved that in the era of globalization and the development of information technologies, the need to optimize the supply chain of services increases, since the integration of participants in this chain is performed without the use of modern management information systems. In the paper, with the help of logic-cognitive, structural-functional methods, structural-logical and imitation modelling, a management approach to simulation of business interaction in the integration of enterprises with elements of ERP-system and CBIP is developed and proposed, which allows you to create a flexible, adaptive and secure IT infrastructure , which increases the efficiency of the enterprise and allows you to optimize the management of relations with other participants in the service supply chain. As a result of this application of modern supply chain management systems, a synergistic effect is achieved that allows you to minimize the number of technological operations, shorten the production cycle and reduce the cost of services both for each individual enterprise and in the service supply chain as a whole.