The rise of digital marketing channels and e-commerce has compelled businesses to shift to a digital economy, where the use and use of technology in business operations necessitates the development of technopreneurs rather than entrepreneurs. Moreover, technopreneurs can transform a technical idea into and market-ready product that consists of intellectual wealth as the gateway to financial wealth. This study aims to inspect the relationship between strategizing business models for transformation and development as well as the moderating role of Business Intelligence (BI) towards becoming a successful technopreneur. The study obtained 313 respondents among entrepreneurs from Small-Medium Enterprise (SME) in Malaysia using a simple random sampling method by utilizing an online survey (Google Forms) to participate in the main survey. They are recognized as highly knowledgeable respondents who use digital technology to improve their businesses; as a result, they possess the knowledge necessary to give a trustworthy response based on their actions and experiences to succeed as technopreneurs. The collected dataset was analyzed using SmartPLS software to test the hypotheses, and a structural model was utilized in the study to assess direct relationships. Based on p-values and t-statistics, the bootstrapping technique was used to increase the significance of both direct and indirect impacts (path coefficient). The findings of this study highlight that strategized business models and successful technopreneurs may become an innovative high technology-intensive context with the moderating role of BI technology prowess and entrepreneurial talent and skills that develop technopreneurs in the new age of entrepreneurs who make use of the digital economy.

The objective of research is to explore the impact of business intelligence systems, artificial intelligence, and digital leadership sustainability on the quality of learning and business performance at business schools of private universities in Jordan. Upon gathering and scrutinizing the research materials, a grand total of 281 samples were judged suitable for analysis using PLS software. The findings of this study suggest that the implementation of business intelligence systems, artificial intelligence, and digital leadership sustainability positively contribute to improving both the quality of learning and the performance of enterprises. The results demonstrate that the implementation of a business intelligence system, and Competitive Intelligence, directly and positively impacts the enhancement of learning quality and company performance. Furthermore, Artificial intelligence has a positive influence on the quality of learning and the performance of businesses, namely through the utilization of Deep learning, Digital Data, Graphical Processing Unit (GPU), and Data Safety and Security. Furthermore, digital leadership sustainability exerts a direct and favorable impact on the caliber of education and organizational achievement, encompassing Digital Competence, Flexibility and Agility, Interconnected Thinking, and Employee Orientation. Furthermore, the findings indicate that the level of education, encompassing Summative Assessment, Formative Assessment, Quizzes, and Presentations, is positively associated with enhancing firm productivity. Curiously, the present results contradict previous studies suggesting that the variables being examined had an influence on achieving digital leadership sustainability and business performance. Generally, the main research outcomes recommend that corporations should start adopting strategies related to enhancing learning effectiveness and improving business performance. This research focuses on the major aspects of business cleverness systems, artificial intelligence, and digital leadership sustainability to enhance the quality of learning and business performance in the business capabilities of private institutions of higher education in Jordan.

This research studies the impact of digital project management and sustainable performance enhancement by taking the role of business intelligence and the mediating role of big data analytics in destination management organizations in Jordan. The research aims to explore the main effects of business intelligence (BI) on digital project management and sustainable performance, with the role of big data analytics as a mediator. The research, using a quantitative approach, was employed by an online questionnaire aiming at employees and managers involved in digital project management in Jordanian Destination Management Organizations (DMOs). After collecting and analyzing 345 valid surveys through PLS-SEM, the results indicate that BI has an important positive effect on digital project management and sustainable performance, in addition to an indirect result through big data analytics (BDA). Furthermore, BI positively affects big data analytics skills, which sequentially give meaningfully to enhance digital project management. The intermediation analysis approves that BDA shows an important role in converting BI resources into real sustainable performance results. Generally, the research highlights the implication of supporting big data analytics talents to fully realize the revenues of BI systems and offers valuable theoretical and practical understandings for DMO managers looking to increase project results and provision digital transformation through data-driven decision-making.

As a concept, PMS is becoming increasingly important for determining the sustainable success of an organization. PMS refers to how the organizations execute project tasks in a sustainable manner while maintaining the economic, environmental and social equilibrium of their activities. Importantly, the PMS includes actions that are geared toward project goal achievement and sustainable development. At the current time, there is increasing dynamism and availability of information among organizations. Under such conditions, BI emerges as a concept. Business intelligence can be defined as the set of methodologies and tools employed by organizations to capture, analyze and interpret data to gain information. With BI, organizations can achieve increased visibility and improved planning and performance of projects. Despite the importance of BI in helping organizations achieve sustainable success in project results, it cannot be emphasized enough that the sustainability of project results requires even better techniques of information analysis. In this connection, organizations need DM as an advanced form of BI that aims at identifying underlying information from large amounts of data.

The objectives of the suggested study would be to investigate the effect of BI on the PME within the banking sector of Jordan and also explore the mediation of the effect by HRA. Due to the increased focus on data usage in current businesses, the Banks in Jordan have started to utilize BI for effective decision making and enhance the effectiveness of their projects. Nevertheless, there has been no research on how BI increases the effectiveness of projects, especially when it comes to enhancing human resource capabilities. The design of quantitative research has been selected where surveys would be employed and distributed among the employees participating in the project management tasks. As per the methodology, descriptive and analytical approaches would be followed by using PLS-SEM for analyzing the data. It is assumed that BI would significantly contribute to the increase in the level of PME both directly and indirectly through the mediation of the HRA.

This study aims to model the relationship between business intelligence (BI), supply chain integration (SCI), and firm performance in Jordanian small and medium-sized enterprises (SMEs) using structural equation modeling (SEM). The study utilizes a sample of 400 SMEs from different sectors in Jordan to investigate the hypothesized relationships between the constructs. The results show that BI positively influences SCI and firm performance in Jordanian SMEs. Moreover, SCI was found to mediate the relationship between BI and firm performance. The study also found that the impact of BI on firm performance is fully mediated by SCI, suggesting that SCI plays a crucial role in enhancing firm performance in the context of Jordanian SMEs. The study makes several significant contributions to the literature on supply chain management and business intelligence in the context of SMEs. First, it provides empirical evidence of the positive impact of BI on SCI and firm performance. Second, it sheds light on the mediating role of SCI in the relationship between BI and firm performance. Third, the study contributes to the limited literature on supply chain management and business intelligence in the context of Jordanian SMEs. The findings of this study have practical implications for managers of SMEs in Jordan. They highlight the importance of investing in BI tools and strategies to enhance SCI and firm performance. Additionally, the study suggests that managers should focus on improving their firms' SCI practices to fully exploit the benefits of BI and improve their overall performance. Overall, this study provides new insights into the relationship between BI, SCI, and firm performance in the context of Jordanian SMEs. The study's findings can guide policymakers, researchers, and practitioners in developing and implementing effective strategies to improve supply chain management and business intelligence practices in SMEs, particularly in emerging markets such as Jordan.

This research attempts to investigate the technological, organizational, and environmental aspects that impact the banking industry's use of business intelligence (BI). In addition, the present research aims to quantify the effect of business intelligence adoption on bank performance to contribute to the current understanding of business intelligence adoption. Upon the completion of the sample verification procedure, 232 samples are collected. Throughout the research investigation, the SEM software is used to process all the acquired data. The study's findings indicate that TOE had a direct and beneficial effect on the adoption of BI systems by banks. Based on the results of the study, the researchers believe that decision-maker and managers would define all activities, responsibilities, and work processes using business intelligence platforms in order to increase their organization's versatility and performance.

This research explores the mediating role of data analytics in the relationship between business intelligence and the advancement of digital project management in Jordanian small and medium enterprises. A quantitative research approach was adopted to collect data using an online survey tool from employees and managers in Jordanian SMEs involved in various tasks of digital project management. After collecting 456 valid questionnaires, the data were analyzed using PLS-SEM. The results revealed that business intelligence has a direct impact on advancing digital project management and an indirect, significant impact through data analytics. This study also found that business intelligence influences positive data analytics abilities, which in turn have a significant impact on the advancement of digital project management. The mediation analysis indicates that data analytics plays an important role in transforming business intelligence resources into effective digital project management performance. This finding highlights the importance of enhancing the capability of data analytics toward fully realizing the potential benefits of BI systems in driving the effective advancement of digital project management techniques within Jordanian SMEs. This research offers important theoretical and practical perspectives for SME leaders and policymakers seeking to improve project outcomes and expedite digital transformation via data-informed decision-making.

This study's objective is to analyze the factors that influence whether or not small and medium-sized enterprises (SMEs) use business intelligence. Based on an exhaustive assessment of the literature, the study offers a model dependent on the diffusion of innovation and augmented with factors expressing the idea of project management maturity (PMM). The research applied structural equation modelling (SEM) to examine data obtained from 112 Jordanian company workers. The findings showed that the adoption of business intelligence has a positive and significant relationship to the complexity, compatibility, and relative advantage of business intelligence; the level of project management maturity has a significant effect on the level of relative advantage, compatibility, and complexity; and the level of project management maturity is significantly associated with the change management and knowledge sharing practices in SMEs. However, we contend that further study has to be carried out, particularly in the context of developing nations, in order to get a comprehensive understanding of how different SMEs may effectively deploy and make use of business intelligence.

This study aimed to examine the effect of integrating Business Intelligence (BI) into the supply chain on supply chain agility, within the Jordanian manufacturing sector. Based on the resource-based view of the firm, this study developed and examined a research model, to achieve its goal. The impact of three dimensions of BI including managerial, technical, and cultural competencies was examined. Using an electronic questionnaire, data was gathered from 462 administrative personnel and employees. Structural equation modeling techniques were employed to analyze the data. Results revealed that the three dimensions of BI have statistically significant positive direct effects on supply chain agility. In addition to that, the results revealed that BI cultural competence has statistically significant positive direct effects on BI technical and managerial competencies. This study contributes to the literature on the role of BI in promoting supply chain agility, from the perspective of a developing country. The findings of this study are expected to help organizations' administrations in making better decisions regarding employing BI to achieve an agile supply chain.