Saudi Cultural Missions Theses & Dissertations
Permanent URI for this communityhttps://drepo.sdl.edu.sa/handle/20.500.14154/10
Browse
2 results
Search Results
Item Restricted Employing Business Intelligence and Data Analysis Techniques in Evaluating Institutional Performance: An Applied Study of the Non-Profit Sector in Charitable Associations in Al-Jauf(Saudi Digital Library, 2025) AlBuniyah AlNusairi, Turki Hamdan Shafaq; AlShabool, Khaledهدفت الدراسة إلى التعرف على أثر توظيف تقنيات ذكاء الأعمال في تقييم الأداء المؤسسي بالقطاع غير الربحي في الجمعيات الخيرية بمنطقة الجوف. استخدمت الدراسة المنهج الوصفي التحليلي، وجمعت البيانات عبر الاستبانة الإلكترونية. وتمثل مجتمع الدراسة في عدد 11654 موظف ومتدرب في الجمعيات الخيرية، وتم الحصول على الاستجابات من عينة عشوائية قوامها 200 موظف وموظفة. ركزت الدراسة على أبعاد ذكاء الأعمال (أنظمة ذكاء الأعمال القائمة على السحابة، التحليلات المعرفية، معالجة اللغة الطبيعية، لوحات التحكم التفاعلية) كمتغير مستقل، وتقييم الأداء المؤسسي كمتغير تابع. أظهرت النتائج أن جميع أبعاد ذكاء الأعمال سجلت مستويات مرتفعة، وأن مستوى تقييم الأداء المؤسسي كان أيضًا مرتفعًا، مما يؤكد التأثير الإيجابي والواضح لتوظيف تقنيات ذكاء الأعمال على تقييم الأداء المؤسسي في القطاع غير الربحي. أوصت الدراسة بالاستثمار المستمر في تبني وتطوير هذه التقنيات، مع التركيز على تطوير القدرات البشرية، وبناء ثقافة تنظيمية داعمة للبيانات، وتشجيع استخدام لوحات التحكم التفاعلية، وتطوير أنظمة تقييم الأداء لتكون أكثر مرونة. كما تشدد على أهمية تعزيز التعاون وتبادل الخبرات بين الجمعيات، والاستفادة من التحليلات المعرفية ومعالجة اللغة الطبيعية لتقييم الجوانب النوعية للأداء A study was conducted to examine the impact of employing business intelligence techniques on institutional performance evaluation in the non-profit sector, specifically within charitable organizations in the Al-Jouf region. The study utilized a descriptive analytical approach, collecting data through an electronic questionnaire. The study population consisted of 11,654 employees and trainees in charitable organizations, with responses obtained from a random sample of 200 employees. The research focused on four dimensions of business intelligence (cloud-based business intelligence systems, cognitive analytics, natural language processing, and interactive dashboards) as the independent variable, and institutional performance evaluation as the dependent variable. The results indicated that all business intelligence dimensions were at a high level, and the level of institutional performance evaluation was also high, confirming the clear and positive impact of using business intelligence technologies on institutional performance evaluation in the non-profit sector. The study recommended continuous investment in adopting and developing these technologies, with an emphasis on developing human capabilities, building a data-supportive organizational culture, encouraging the use of interactive dashboards, and developing more flexible performance evaluation systems. It also stressed the importance of enhancing cooperation and knowledge exchange among organizations and utilizing cognitive analytics and natural language processing to evaluate qualitative aspects of performance.2 0Item Restricted The Role of Artificial Intelligence in Monitoring the Quality of Construction Project (Case Study) in Al-Jouf Region(Saudi Digital Library, 2025) Alsharari, Abdulmohsen; AlBtoush, MuhammedThis study investigates the current status and potential of Artificial Intelligence (AI) applications in Construction Engineering and Management (CEM) in the Al-Jouf region of Saudi Arabia. AI has demonstrated significant promise in enhancing resource use, project performance, and quality control in a number of industries; however, Al-Jouf's implementation of AI is beset by particular difficulties, including a lack of funding, a lack of skilled AI specialists, and limited infrastructure. The study uses a descriptive-analytical methodology to fill this gap, combining a review of the literature with primary data gathered from stakeholders in ongoing construction projects in Al-Jouf using a structured questionnaire. The approach includes both secondary sources (academic literature, journals, and reports) and primary sources (field responses from engineers, project managers, and administrative personnel). Data analysis was conducted using SPSS software to evaluate AI awareness, current applications, challenges, and impacts on construction quality dimensions—namely technical compliance, time performance, cost control, and customer satisfaction. The structured questionnaire was designed based on a pilot test and adapted to reflect local construction sector dynamics. Non-probability purposive sampling was used to ensure the selection of knowledgeable participants. The study offers practical insights and recommendations to policymakers, engineers, and industry stakeholders for facilitating AI adoption, aligning it with local project requirements, and supporting sustainable development in the construction sector. The study results indicate a generally positive impression of AI in the construction sector in Al-Jouf region, with a high average score of 3.76. The field “Impact of AI on the Quality of Construction Projects” received the highest score (M = 3.97), while the second field, “Challenges of Applying AI in Construction Projects” received a high score (M = 3.93). The field “Using AI in Project Quality Control” also received a high score (M = 3.76). The lowest-rated field was “Awareness of AI in the Construction Sector” (M = 3.37). The study recommended promoting a culture of artificial intelligence in the sector through collaboration between government agencies and educational institutions with construction companies to ensure regular workshops, seminars, and technical training courses on the fundamentals of artificial intelligence and its applications in the construction sector.30 0