This study sought to investigate the impacts of big data, artificial intelligence (AI), and business intelligence (BI) on Firms' e-learning and business performance at Jordanian telecommunications industry. After the samples were checked, a total of 269 were collected. All of the information gathered throughout the investigation was analyzed using the PLS software. The results show a network of interconnections can improve both e-learning and corporate effectiveness. This research concluded that the integration of big data, AI, and BI has a positive impact on e-learning infrastructure development and organizational efficiency. The findings indicate that big data has a positive and direct impact on business performance, including Big Data External and Internal, Innovative Usage, Indexing, and Sources Accuracy. In addition, Artificial intelligence positively affects business performance, including Data Accuracy, Data Transparency, Data Speed, and Creative Thinking and Learning. Moreover, business intelligence has a direct and positive impact on business performance, including Data Warehouse, Data Mining, Business Process Management, and Competitive Intelligence. In addition, the findings indicate that e-learning which represents system quality, information quality, and self-efficacy has a positive relationship on enhancing business performance. Interestingly, the present findings are inconsistent with those of previous studies showing the variables of interest which have no effect on e-learning and business performance. Taken together, the findings of this study suggest that firms should begin to apply processes related with applying e-learning and developing business performance. The novelty of the present study lies in highlighting the key dimensions of big data, artificial intelligence, and business intelligence when it comes to enhancing e-learning and business performance at Jordanian telecommunications industry.
Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an
... Show MoreThis study assesses the short-term and long-term interactions between firm performance, financial education and political instability in the case of Malaysia Small to Medium Enterprises (SMEs). The simultaneous insertion of financial education and political instability within the study is done intentionally to inspect the effect of these two elements in one equation for the Malaysian economy. Using the bound testing methodology for cointegration and error correction models, advanced within an autoregressive distributed lag (ARDL) framework, we examine whether a long-run equilibrium connection survives between firm performance and the above mentioned independent variables. Using this method, we uncover evidence of a positive long-term link b
... Show MoreThe research aims to study the effect of knowledge upgrade on business continuity in private colleges and universities in Baghdad. The research problem is summarized in the main question (were the academic leaders able to employ knowledge upgrading to enhance business continuity). The most important of this sector were the universities and the private college in the city of Baghdad as a field for this research, the researchers conducted a field visit to (10) universities or private colleges, the research sample consisted of (177) individuals from the deans of colleges and their assistants, as well as heads of scientific and administrative departments. The data was analyzed and the hypotheses were tested using the appropriate statistical
... Show MoreDatabase is characterized as an arrangement of data that is sorted out and disseminated in a way that allows the client to get to the data being put away in a simple and more helpful way. However, in the era of big-data the traditional methods of data analytics may not be able to manage and process the large amount of data. In order to develop an efficient way of handling big-data, this work studies the use of Map-Reduce technique to handle big-data distributed on the cloud. This approach was evaluated using Hadoop server and applied on EEG Big-data as a case study. The proposed approach showed clear enhancement for managing and processing the EEG Big-data with average of 50% reduction on response time. The obtained results provide EEG r
... Show MorePhysical measurements are one of the basic factors that affect the performance of the goalkeeper, especially when confronting fixed kicks that require special skills such as the reaction and accuracy in concentration, and with technological development artificial intelligence has become an effective tool for analyzing mathematical data that is difficult to discover in traditional methods The study aims to employ techniques Artificial intelligence to study the relationship between physical measurements and the accuracy of confronting the fixed kicks of goalkeepers in football. This study will contribute to providing a deeper understanding of physical factors that affect the performance of goalkeepers, in addition to designing dedicat
... Show MoreThe current research aims to provide a conceptual and applied frame on the subject of multi- level analysis in the research of business administration. The research tries to address some of the problems that befall the preparation of research and studies at the Arab level and local level, where the unity of theory and measurement and analysis, as well as clarify the various types of conceptual constructs and give researchers the ability to distinguish different models related to the level of analysis. On the other hand, this research provides an example of
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