The aim of the study is to identify the requirements for qualifying administrative leaders and the challenges they face at King Khalid University, in light of the general framework of the Human Capacities Development Program, which includes four dimensions (values and behaviours-basic skills-future skills-knowledge). A descriptive approach was used, and the study population consisted of academic leaders at King Khalid University, totalling (107). A questionnaire was used as a research tool, comprising three axes and (53) statements to collect data after ensuring their validity and reliability. The results showed the agreement of the study population on the axis of requirements for qualifying administrative leaders at King Khalid University to a very high degree, with an average score of (4.44), and their agreement on the challenges facing the qualification of administrative leaders at King Khalid University to a very high degree, with an average score of (4.11), and their agreement on the mechanisms for qualifying administrative leaders at King Khalid University to a very high degree, with an average score of (4.29). The results also showed no statistically significant differences at the significance level (0.05) between the means of responses of the study population on the requirements, challenges, and mechanisms for qualifying administrative leaders according to variables (gender-academic qualification—experience in the current job). In light of the study results, a proposed strategy was developed, and recommendations were made, including adopting the proposed strategy and governing the programs for qualifying administrative leaders at King Khalid University to ensure transparency, fairness, and accountability at all stages from nomination, preparation, and evaluation, in addition to considering the university’s strategic plan when designing programs for qualifying administrative leaders to adopt the values embraced by the administration and build leaders who contribute to achieving its vision and mission in the long term.
The major goal of decisions made by a business organization is to enhance business performance. These days, owners, managers and other stakeholders are seeking for opportunities of modelling and automating decisions by analysing the most recent data with the help of artificial intelligence (AI). This study outlines a simple theoretical model framework using internal and external information on current and potential clients and performing calculations followed by immediate updating of contracting probabilities after each sales attempt. This can help increase sales efficiency, revenues, and profits in an easily programmable way and serve as a basis for focusing on the most promising deals customising personal offers of best-selling products for each potential client. The search for new customers is supported by the continuous and systematic collection and analysis of external and internal statistical data, organising them into a unified database, and using a decision support model based on it. As an illustration, the paper presents a fictitious model setup and simulations for an insurance company considering different regions, age groups and genders of clients when analysing probabilities of contracting, average sales and profits per contract. The elements of the model, however, can be generalised or adjusted to any sector. Results show that dynamic targeting strategies based on model calculations and most current information outperform static or non-targeted actions. The process from data to decision-making to improve business performance and the decision itself can be easily algorithmised. The feedback of the results into the model carries the potential for automated self-learning and self-correction. The proposed framework can serve as a basis for a self-sustaining artificial business intelligence system.
This investigation extends into the intricate fabric of customer-based corporate reputation within the banking industry, applying advanced analytics to decipher the nuances of customer perceptions. By integrating structural equation modeling, particularly through SmartPLS4, we thoroughly examine the interrelations of perceived quality, competence, likeability, and trust, and how they culminate in customer satisfaction and loyalty. Our comprehensive dataset is drawn from a varied demographic of banking consumers, ensuring a holistic view of the sector’s reputation dynamics. The research reveals the profound influence of these constructs on customer decision-making, with likeability emerging as a critical driver of satisfaction and allegiance to the bank. We also rigorously test our model’s internal consistency and convergent validity, establishing its reliability and robustness. While the direct involvement of Business Intelligence (BI) tools in the research design may not be overtly articulated, the analytical techniques and data-driven approach at the core of our methodology are synonymous with BI’s capabilities. The insights garnered from our analysis have direct implications for data-driven decision-making in banking. They inform strategies that could include enhancing service personalization, refining reputation management, and improving customer retention efforts. We acknowledge the need to more explicitly detail the role of BI within the research process. BI’s latent presence is inherent in the analytical processes employed to interpret complex data and generate actionable insights, which are crucial for crafting targeted marketing strategies. In summary, our research not only contributes to academic discourse on marketing and customer perception but also implicitly demonstrates the value that BI methodologies bring to understanding and influencing consumer behavior in the banking sector. It is this blend of analytics and marketing intelligence that equips banks with the strategic leverage necessary to thrive in today’s competitive financial landscape.
Modern education attaches great importance to the innovation of teaching concepts, and teachers should be guided by it to provide students with high-quality educational resources and learning environment. Teachers should conduct in-depth research on auditing course materials, set certain training goals for students, and optimize their teaching ideas to conduct diversified evaluations of students. Teachers should create an environment for students to learn auditing and choose corresponding teaching methods based on their learning situation. Teachers should also guide students to master the courses and basic theories of auditing, so that they have certain operational skills and can apply relevant theories to analyze and develop problems encountered in the management profession.
Mind map is a new way of thinking that visualizes and visualizes radioactive thinking. The application of mind map in teaching is consistent with the expression of "development of thinking ability" in the "Chinese Curriculum Standards". Its concise construction and clear expression can, on the one hand, convey the ideas of language expressors more quickly and quickly, and on the other hand. On the one hand, it can make the language receiver easier and clearer to understand the message the other party wants to convey.This paper analyzes the application rules of mind map in classroom teaching, and expounds the application strategy of mind map in primary Chinese oral communication teaching from three aspects: picture-text combination, picture-introduction, and picture-introduction. The effective development of primary school students' innovative thinking and logical ability promotes the effective improvement of primary school students' oral communication skills.
This study examines the compliance between the accounting standard for Property, Plant and Equipment (PPE) and accountants’ practices in terms of disclosure and measurement, in order to determine its levels and drivers. Based on the assumption that a higher level of compliance is associated with a higher quality of the accounting information system, compliance indices are proposed and econometric regressions are used to analyze the determinants of this accounting compliance for Portuguese firms. The empirical evidence shows that compliance is not high, and that it tends to be higher for disclosing rather than for measuring. Moreover, the results suggest that firm size has a positive impact on compliance, both for measurement and disclosure, consistent with larger firms being subject to greater scrutiny. Liquidity, on the other hand, tends to have a negative effect on compliance, as more liquid firms are less dependent on external financing. Furthermore, while leverage tends to have a positive effect on measurement compliance, profitability has no effect on accounting compliance. Therefore, this study adds evidence straight from the perceptions of practitioners who interpret and apply accounting standards and then influence the quality of financial reporting, providing valuable insights that have the potential to affect confidence in firms.
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