The study provides a framework for improving the most key performance indicators and arranging them according to the degree of impact in order to enhance decision-making, speed and increase accuracy in data analysis, reduce mismanagement and time to take appropriate decisions a timely manner and ensure that the organization is moving towards achieving its goals, through one of the techniques of business intelligence (Data Mining and Knowledge discovery) and choosing the best technique that can be used to improve the key performance indicators.
Over the past decades, social media attracted individuals to express their feelings on any topic or item, resulting in an incremental growth in the size of created data. These feelings and unstructured data paved the path for business organizations to gather information and build statistical analysis. Various machine learning and natural language processing-based approaches are used for sentiment and emotion analysis. Moreover, deep learning-based approaches recently gained popularity due to their remarkable performance in text analysis. This paper provides a comprehensive overview of the prominent machine learning models applied in emotion analysis. It explores various emotion analysis taxonomies, in addition to the constraints of prevalent deep learning architectures. The paper also reviews some of the previously presented contributions in emotion analysis with a focus on deep learning methodologies as well as the most common datasets. It presents a comprehensive comparison between several emotion analysis models. This paper demonstrates the effectiveness of learning-based techniques in tackling emotion analysis challenges.
E-CRM strives to enhance customer service, build relationships with customers, and keep key clients. E-CRM deals with technology, people, and processes and with the goal of fostering customer loyalty. This paper aims to investigate the relationship between E-CRM, service quality, customer satisfaction, trust, and loyalty in banking industry. In order to gather sufficient reviews, a literature review was carried out utilizing a number of corresponding publications that were indexed in reliable databases. A model that highlights the relation between E-CRM and customer satisfaction, service quality, trust, and loyalty is also shown in this study. The supervisors of administrative organizations can utilize this research's insights into E-CRM to build client loyalty and increase the revenue and profitability of their firm
The main objective of any educational institution is to provide its students with the best educational knowledge and experience so, they can be employed to meet the labor market demands. Due to the rapidly changing in the technology industry and the expanding need for information technology (IT) professionals. The mismatch between IT graduates and the needs of the labor market leads to their inability to employ and job misplacement. Therefore, this paper aims to identify the most significant factors affecting IT graduates' employability and their ability to compete in the local, regional, and international labor markets through a detailed literature review and by conducting two surveys, one for IT graduates and the other for IT employers. Then, data were collected and analyzed by Statistical Package for Social Sciences (SPSS) 28.0 to build our proposed framework which will integrate all factors and parties involved to enhance graduates’ employability to match the labor market demands. The proposed model will assist all parties in improving their plans for producing graduates who are skilled, knowledgeable, and meet the labor market demands.
Agile methodologies have become one of the most applied methods in the software development industry. However, agile methodologies face some challenges such as less documentation and wasting time considering changes. This review presents how the previous studies attempted to cover issues of agile methodologies and the modifications in the performance of agile methodologies. The paper also highlights unresolved issues to get the attention of developers, researchers, and software practitioners
