The research investigated the relationship among Key Performance Indicators (KPIs), risk assessment capabilities and value creation in service sector firms. The study also sought to examine the effect of KPI`s components on risk assessment & value capitalisation, and how they either facilitate or hinder implementation, monitoring and continuous improvement processes. In this context, a quantitative cross-sectional research design was applied using an online survey of shared middle and senior managers in service organizations. After filtering, the final version of segmented sample included a total of 215 respondents engaged in different service businesses. The analysis was determined using Partial Least Squares Structural Equation Modeling. The results showed that all components of KPIs have significant positive relationships with risk assessment and value improvement outcomes First, performance drivers were found to be the most significant predictor of both constructs. As such, the results show that both risk assessment and value improvement had a positive effect on implementation/monitoring processes which in turn enabled continuous improvements. Performance measurement, risk management and value creation in service organizations: A performance at-risk-based conceptual model. The results have numerous managerial, practical and policy implications for the service sector. This drives home the necessity of creating integrated KPI systems that include risk assessment and value improvement factors. In building on existing theory, the study is of substantial interest in that it provides empirical evidence for these organizational mechanisms related to service organizations. Resilient Organizations in the Service Sector picture of Resilience across Performance Management with KPIs, Risk Assessment and Value Creation strategies offering a comprehensive foundation for sustainable organizational success.

The research investigates the link between technology, organization, and environment, and the uptake of artificial intelligence among SMEs in Jordan. The objective is to get a deeper understanding of the factors that promote or hinder enterprises' use of artificial intelligence during the recruitment of leaders. A total of 295 participants, who were owners or managers in several SME sectors, manufacturing, including services, construction, and agriculture, were selected via judgmental sampling. Data collection was conducted utilizing a survey instrument, and the collected data was processed employing Smart PLS. The findings demonstrated a substantial correlation between attitude toward artificial intelligence uptake and factors such as relative advantage, complexity, top management commitment, and organizational preparedness. Nevertheless, factors like competitive pressure, external assistance, a favorable regulatory environment, compatibility, and staff flexibility do not significantly influence the attitude toward the uptake of artificial intelligence. In summary, these findings provide valuable insights for decision-making and resource distribution. They underscore the significance of factors such as relative advantage, complexity, top management commitment, and organizational readiness in achieving goals in the field of artificial intelligence. Additionally, they identify areas where efforts may not result in significant effects. The practical ramifications and future study paths are emphasized according to current technological needs.

This study investigates the relationship between business intelligence adoption (Business Intelligence (BI), Data Analysis and Reporting (DAR), Business Process Integration (BPI), and Continuous Improvement and Innovation (CII)) and marketing effectiveness in the Jordanian telecom industry. It specifically examines the mediating role of customer satisfaction in this relationship. A survey design method using the cross-sectional survey was utilized during the research process, involving quantification. The data was collected from 285 employees across the Jordanian telecom sector via electronic response forms. As the analysis's method, the partial least squares structural equation modeling (PLS-SEM) was utilized. The results, which showed BI, DAR and CII to have a positive direct effect on marketing effectiveness, whilst BPI displayed a negative direct impact, were compelling. But clear signs of positive influence on CS by the four dimensions of BI (BI, DAR, BPI, and CII) have also been observed, and this result has been proved to be a mediator between them and business effectiveness. The above study is a source of invaluable learning for the managers of telecom companies in Jordan is a tool that managers in the Jordanian telecom industry will greatly benefit from in the sense that it brings out all the importance of integrating BI, DAR, BPI, and CII practices that emphasize high quality customer service. By properly utilizing these assets and up-to-the-market, companies can improve the effectiveness of marketing and the whole organizational efficiency. The study enhances the existing theory of the interrelationships between the adoption of business intelligence, customer satisfaction, and marketing power which can be viewed from both resource-based view (RBV) theory and expectation-based theory (EDT). It affirms an idea that the RBV was rooted in that when organizational assets are valuable, firms have a competitive advantage and better performance. Also, an EDT states that customer satisfaction increases if the expectations of customers are met. Innovation - The essay is innovative and takes an original angle to explore the multifaceted interconnectivity among business intelligence adoption, customer satisfaction, and marketing effectiveness in the framework of the Jordanian telecom industry. It highlights the steps to customer satisfaction problem solutions and the caution comes with process integration efforts, hence, helping to arrive at a full comprehension of the aspirations for organizational performance in the field.

This quantitative study investigates the relationships between Management Information Systems (MIS), Business Intelligence (BI), and Strategic Planning (SP) within Jordanian Public Listed Companies, with a focus on the mediating role of BI. The target population comprises employees from the 108 public shareholding companies listed on the Amman Stock Exchange, totaling an estimated 1,080 senior managers involved in strategic planning. A random sample of 285 employees was surveyed to achieve a 95% confidence level with a 5% margin of error. Data were collected using a structured questionnaire with multi-item scales adapted from prior studies. Structural equation modeling (SEM) was employed to test the conceptual framework and hypothesized relationships, utilizing the two-step SEM approach with AMOS software. The results reveal significant positive relationships among MIS, BI, and SP. Specifically, MIS exhibits a statistically significant positive effect on SP, supporting previous research indicating MIS provides comprehensive data for informed planning. Furthermore, MIS significantly influences BI capabilities, underscoring the importance of robust MIS infrastructure for advanced BI analytics. BI, in turn, positively impacts SP, aligning with literature suggesting BI tools enhance planning agility and effectiveness through data-driven insights. Bootstrapping analysis demonstrates that BI partially mediates the relationship between MIS and SP. While BI acted as a significant mediating variable, MIS had a significant direct impact on SP, implying that though MIS has a direct impact on SP, it has an indirect impact, through BI, as well. Further analysis revealed that the constructs are interconnected, and that the mediation of BI is a necessary part of the process in Jordanian Public Listed Companies. As such, acknowledging the relevance of MIS, BI, and SP and the mediating role of BI, organizations can adapt their decision-making to achieve sustained competitive advantage within the dynamic business environment in Jordan.

Technology has significantly transformed knowledge, education, and access to information by introducing online learning platforms, interactive games, and virtual reality simulations in traditional classrooms, creating a dynamic, engaging, and inclusive learning environment. The ChatGBT project (a pre-developed transformer for training) is a remarkable achievement in artificial intelligence technology. It allows students tailored and efficient learning experiences by providing individual feedback and explanations. ChatGPT e-learning platform has been extensively studied for its adoption and acceptance, but there is a significant gap in research on its acceptability and use, highlighting the need for further exploration. The goal of this work is to bridge this disparity by introducing a comprehensive model that includes three basic elements: performance expectation, expected effort, and social impact. A total of 241 graduate students were surveyed and their data were analyzed using structural equation modeling techniques. The results indicate that “expectation of performance and expected effort” have the greatest impact and importance in determining students’ intentions to use learning platforms via ChatGPT, while social influence does not play an important role. This study enhances the current body of knowledge related to artificial intelligence and environmental sustainability, and provides important insights for professionals, policymakers, and producers of artificial intelligence products. These observations may provide guidance for creating and implementing artificial intelligence technologies to match consumers’ needs and preferences more effectively, while also taking into account broader environmental conditions.

The present study examines the effect of variables on contemporary management accounting practices' adoption in the public sector. The present research further investigates the relationship between the uptake of contemporary management accounting practices and organizational performance and change. 520 surveys were mailed to the public sector in Jordan to gather data, which was subsequently analyzed employing SEM. The findings of the research indicate that there are substantial relationships between accounting staff qualifications and management accounting practices. Results indicate that modern management accounting practices could help public sector practitioners enhance performance and promote organizational change. The investigation offers concrete insight into the public sector's uptake of management accounting practices. The research conducted offers a field study of the impact of implementing a suite of management accounting practices in the public sector.

This study investigates the impact of sustainability initiatives, choice of content, and engagement with environmental content on environmental awareness. Employing a sample of 435 respondents and utilizing Partial Least Squares (PLS) analysis, the research provides valuable insights into the role of digital marketing strategies in fostering environmental consciousness. The findings of this study highlight the substantial influence that digital marketing techniques can have on shaping individuals' awareness and attitudes towards environmental concerns. The confirmed hypotheses underscore the effectiveness of these strategies in promoting environmental awareness among diverse audiences. As the digital landscape continues to evolve, the research contributes to the growing synergy between digital marketing and environmental advocacy, encouraging further exploration and practical applications for a more sustainable future.

The accelerated progress of Artificial Intelligence (AI) within the accounting field has resulted in a heightened use of this technology in international enterprises, therefore generating noteworthy ethical concerns. This research investigates the ethical implications that arise from the use of AI in accounting practices, focusing on international corporations operating in Jordan. The objective of this research is to provide a comprehensive framework for the ethical and responsible integration of AI within the accounting domain. The research used a survey methods approach while 379 respondents were selected using cluster and proportional sampling. The qualitative component of the research investigates the viewpoints and concerns of persons pertaining to the use of AI. The study results provide significant contributions to the development of a context-specific paradigm for AI ethics that prioritizes concepts such as transparency, fairness, and accountability. The findings of this study have substantial value for multinational corporations engaged in commercial operations in Jordan and similar regions. The results provide organizations with the necessary tools to proficiently address the ethical dilemmas that emerge as a result of using artificial intelligence in accounting procedures.