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.

Project Risk Management contains processes ranging from planning to control. It is applied to identify risks, analyze them, and design responses to change the occurrence rate and/or the effect of project risks. It is important for project managers to analyze the effects of the risks in projects and also consider project risks in their decisions. If project risks are not addressed during the risk management process, issues such as schedule delays, cost overruns, and even project failure may occur. This paper aims to introduce a Markov method to integrate project risk analysis and risk response planning. This method is applied to forecast the following status of the project when limited information about the project is available. Moreover, earned value management (EVM) methods were used to include various types of project risks through the project lifecycle. The model also offers the capability to choose the most effective risk response for managing project risks through the application of the Markov decision process (MDP). Eventually, we introduce a case study to demonstrate functionality and effectiveness of the presented approach. Solving the model allows for identifying the best set of risk response strategies tailored to each specific project state. The computational results illustrate that the current state of the project has a significant impact in the process of risk response planning. Since uncertainty is the inherent characteristic of projects, the use of the project’s current state is more reliable than the previous status of projects, and the Markov method is applied in this research because it uses the current state for its modelling. Using this method, managers can predict the future state of projects and find the best response in each status of projects.

This research strives to offer valuable insights into business intelligence and analytics utilization. Besides, its expansion encompasses essential success factors for business intelligence and strategic management in the hospitality industry. The study's sample comprises 387 hotel managers from the Jordanian hospitality industry. Data collected to support the research goal was examined using multiple regression analysis through SPSS, with the assistance of PROCESS Macro v3.5. The results of this study reveal that business intelligence and analytics can serve as a bridge to connect crucial success factors for business intelligence and strategic management. These findings have implications for existing literature and stakeholders. Hotels that have integrated business intelligence and analytics acknowledge the advantages of enhancing their strategic management capabilities and decision-making processes.

This research investigates the mediating effect of Innovative Behavior on the relationship between Emotional Intelligence, Intellectual Intelligence, and supply chain performance. Data were collected from 198 employees of water supply companies across five major cities in Central Java, using purposive sampling and analyzed through structural equation modeling. The findings indicate that both Emotional Intelligence and Intellectual Intelligence positively and significantly impact supply chain performance. Additionally, Innovative Behavior not only positively influences supply chain performance but also mediates the relationship between Emotional and Intellectual Intelligence with supply chain performance. The study suggests that enhancing Emotional and Intellectual Intelligence through Innovative Behavior can significantly improve supply chain performance in water supply companies. Organizations are recommended to incorporate Emotional Intelligence into selection and training programs, develop initiatives to boost Emotional and Intellectual Intelligence through training in areas such as emotional management, interpersonal communication, problem-solving, critical thinking, and creativity, and create a supportive work environment that encourages innovative behavior. Implementing these strategies can lead to more efficient operations, better resource management, and increased customer satisfaction, thereby enhancing overall supply chain performance.

The study aimed to explore The Role of Big Data in Improving the Balanced Scorecard in Jordanian Commercial Banks. The descriptive approach was employed, and the quantitative method was adopted to achieve the study’s objectives and test its hypotheses. A questionnaire tool was developed, consisting of four sections for big data and four sections for the balanced scorecard, comprising a total of 48 items. The validity and reliability of the tool were verified. The questionnaire was allocated to a sample of 400 employees of the study community which is the Jordanian commercial banks. The study's findings revealed that big data has a statistically significant impact on enhancing the balanced scorecard in Jordanian commercial banks. Dimensions of big data, such as "variety" and "veracity," had a positive and direct effect on improving all aspects of the balanced scorecard, including financial performance, customer service, learning, and growth. On the other hand, the impact of "volume" and "velocity" was limited or statistically insignificant in some aspects. According to multiple regression analyses, big data contributes to explaining 82% of the improvements observed in the balanced scorecard, highlighting the importance of investing in big data to enhance operational and financial performance.

Halal supply chain management, with its focus on Islamic values in tourism, is increasingly recognized for enhancing destination competitiveness and visitor satisfaction. This study examines how Islamic attributes, motivations, and norms influence visitor satisfaction and word of mouth in Medan City's tourism sector. In the halal tourism industry, supply chain management plays a crucial role in ensuring that every stage from procurement, production, distribution, to service delivery complies with halal standards. The research aims to evaluate the impact of Islamic Physical Attributes, Islamic Non-Physical Attributes, Push Motivation, Pull Motivation, and Islamic Norms on visitor satisfaction and their subsequent effect on word of mouth. By employing a quantitative approach, the study utilizes structured questionnaires based on previous research and applies Structural Equation Modeling (SEM) for analysis. Data were collected from 300 tourists in Medan City, including both local and international visitors. The study finds that Islamic Non-Physical Attributes and Pull Motivation significantly enhance visitor satisfaction. Islamic Physical Attributes also positively affect satisfaction, while Push Motivation does not. Satisfaction strongly influences word of mouth, but Islamic Norms negatively moderate this relationship. Islamic attributes and motivations play a crucial role in shaping visitor satisfaction in the tourism context. Islamic norms, however, may complicate the satisfaction-word of mouth link. The implementation of effective halal supply chain management can ensure that all aspects of supply chain management in halal tourism, from products to services, meet the expected halal standards. Practically, destination managers should emphasize Islamic attributes and motivational factors to improve visitor satisfaction. Theoretically, the study contributes to understanding the complex dynamics between satisfaction, norms, and word of mouth in halal tourism.

The objective of this study is to assess the joint effect of corporate entrepreneurship (CE) and supply chain management (SCM) strategies on firm performance in the circumstance of Saudi Arabian manufacturing firms. This is interesting in the sense that while previous scholars have focused on CE and SCM separately, the combinative aspect of the two particularly in nonwestern countries seems still to be short of attention. In this respect, this paper attempts to apply a resource-based view and suggest that CE and SCM complement each other and in the end performance of the firm will be increased. Out of the 84 Saudi manufacturing firms covered in the structured survey, data was analyzed using Ordinary Least Squares (OLS) regression. The results indicate that CE, particularly dimensions such as new business venturing, product innovation, technological entrepreneurship, mission reformulation, reorganization and system-wide changes, significantly enhances firm performance. Additionally, SCM strategies were found to have a positive and statistically significant impact on firm performance, highlighting the critical role of effective supply chain management in operational efficiency and competitive positioning. The findings contribute to the literature by providing empirical evidence from a Middle Eastern context, thereby enhancing the generalizability of existing theories on CE and SCM. The study also offers practical implications for managers and policymakers, suggesting that aligning CE initiatives with SCM strategies can drive sustained competitive advantage. These insights are particularly relevant for firms operating in emerging markets, where economic reforms and diversification efforts, such as Saudi Arabia's Vision 2030, necessitate strategic innovation and supply chain optimization.

This study investigates the critical role of information technology integration in enhancing project risk management, specifically examining the mediating effect of risk identification effectiveness. Based on a quantitative approach, the study collected data from 173 respondents working in the construction, engineering, and telecommunication sectors using a comprehensive questionnaire. We employed Smart PLS-SEM for data analysis to test the study hypotheses. Our findings reveal that IT integration significantly and positively influences both risk identification effectiveness and overall project risk management. Importantly, the study confirms the mediating role of risk identification effectiveness, indicating that IT's contribution to successful project risk management is significantly enhanced when it empowers teams to identify potential risks early and accurately. These findings indicate the strategic importance for organizations in these sectors to prioritize investments in IT solutions that not only streamline project management processes but also specifically enhance risk identification capabilities. Discussion and conclusion were depicted at the end of work.

Integrating project management (PM) and sustainable development (SD) is not merely an option but a necessity for smart cities (SC) to secure a prosperous future for the next generations. Also, useful PM plays a vital role in fostering sustainable growth within SC, as it enhances the quality of life, conserves natural resources, and encourages technological creation. Therefore, this study aimed to examine the significance of PM in advancing the SD of SC. Randomly 189 questionnaires were distributed to possible respondents working in PM by email, hardcopy mailings, and web-collection apps. The statistical analysis was carried out using SPSS version 25, by using a quantitative research approach. The results showed that all study variables (smart technologies company policies, resource management, and organizational culture) positively impacted smart cities' SD. Therefore, the study recommends enhancing the incorporation of PM and SD in SC by implementing effective processes and technologies that connect harmoniously with technological advancement and environmental and social sustainability.

The study sought to determine how bank financial performance (BFP) was affected by credit risk (CR), liquidity risks (LR), operational risks (OR), financing risks (FR), market risks (MR), in the presence of risk management (RM) as a moderator in conventional and Islamic banks in the Middle East and North Africa. To this end, stratified random sampling and systematic sampling methods were used, with a sample size of thirty conventional banks and thirty Islamic banks from the Kingdom of Saudi Arabia and the Arab Republic of Egypt acting as the unit of analysis. 344 participants that were targeted had completed questionnaires that could be analyzed. The database of the target banks was used to quickly and affordably choose samples. Structural equation modeling was done in conjunction with a tool named Smart PLS 4 (SEM). A 92% reliability coefficient was used to evaluate the instrument's dependability. By assessing study variables using commonly used terminology and consulting with subject matter experts on the research issue, the content validity of the findings was confirmed. PLS 4 was one of the clever analytical approaches used to characterize the study's findings. The following describes the relationship between risk management practices and BFP when utilizing a modified variable (RM): "The study showed that CR does not positively affect BFP in conventional banks when employing a modified RM variable. The study demonstrated that the risk ratio had no positive influence on BFP in Islamic banks using a modified RM variable. It has been established by study that LR has no positive impact on BFP. The study also demonstrated that the LR has no positive effects when the variable RM rate is used in conventional banks. The study's findings demonstrated that the OR does not change when the variable RM rate is used. It is advantageous for BFP in traditional banks. The study discovered that there is a negative correlation between OR and BFP in Islamic banks and that OR has no beneficial effect on BFP when the RM rate variable is included. The study's findings demonstrated a favorable correlation between OR and BFP. The research indicates that in typical banks, FR does not positively increase BFP when employing the adjusted RM variable. The study discovered that there is no correlation between FR and BFP in Islamic banks when the modified RM variable is used. Rather than suggesting a good association between FR and BFP, the results pointed to a negative investigation.