This study offers a comprehensive investigation of the complex interconnections between High-Performance Work Systems, Knowledge Sharing, Entrepreneurial Leadership, and Employee Intrapreneurial Behavior in the telecommunications sector of Jordan. By using a quantitative method, this research employs structured questionnaires to gather comprehensive empirical findings from a sample of industry specialists. With 312 verified replies providing a solid framework, advanced analytical methods such as Structural Equation Modeling (SEM) and Partial Least Squares (PLS) were utilized to clarify the complex paths and linkages of the proposed hypothesis. The main findings of this study reveal that Entrepreneurial Leadership plays a crucial role in enhancing the influence of High-Performance Work Systems in fostering a dynamic intrapreneurial culture. It acts as a catalyst that magnifies the intrapreneurial inclinations among workers. Furthermore, knowledge sharing has arisen as a mediator, facilitating the influence of High-Performance Work Systems in fostering EIB. The research offers a thorough and intricate analysis that enriches our understanding of the diverse elements and mechanisms at play. The acquisition of this invaluable knowledge can be effectively employed to enlighten organizational strategies and policies, with the ultimate objective of cultivating an atmosphere that is conducive to innovation and intrapreneurial triumph within the swiftly evolving telecommunications sector of Jordan.

In the technological and digital revolution, the world is witnessing unprecedented environmental uncertainty as big data becomes more complex in the labor market. Hence, the study examined the relationship between business analytics, big data, and decision-making insights. The study design used a quantitative approach through a questionnaire distributed to a sample of 412 management levels from international organizations located in King Hussein Business Park in Jordan, named CISCO, Microsoft, Oracle, MBC, Samsung, Migrate, Aramex, Experia, and Ericsson. The data were managed through PROCESS Micro v3.5 software via SPSS packages to investigate the total effects of the study variables. The results confirmed the positive relationship between business analytics, big data, and decision-making insights at a statistically significant level (p < 0.01). The study presented a theoretical development of the role of management in achieving mature visions based on big data that constitute solutions to the complex interactions between technology and human orientation, facilitating the organizational complexities supported by the digital age and transforming them in favor of business decisions in the organizational environment of business companies.