International Journal of Management and Marketing Intelligence

The Impact of Administrative Leadership on the Preparation of the Second Line of Security Leadership: A Practical Study

Mohammed Al Othmani — 2025-09-30

This study aims to analyze the impact of administrative leadership on preparing the second tier of security leadership, considering it a crucial factor in ensuring sustainable security performance and achieving institutional excellence. The study highlights the role of administrative leadership in transferring expertise and enhancing leadership competencies to ensure a new generation is capable of assuming high-ranking security positions efficiently and effectively. The study adopted a quantitative methodology through a field survey distributed to 400 officers of various ranks in the UAE Ministry of Interior. Data was analyzed using SPSS to examine the relationship between administrative leadership and the effectiveness of preparing future security leaders. The findings revealed a strong positive correlation (α = 0.01) between administrative leadership and leadership preparation. The results also indicated that organizational culture, career planning, and performance evaluation are key factors in the success of leadership development programs. Based on these findings, the study recommends adopting integrated strategies to enhance administrative leadership, including sustainable training programs, empowering delegation mechanisms, and fostering a work environment that encourages innovation and effective leadership. Additionally, it emphasizes the necessity of structured knowledge transfer between current and emerging leaders to ensure continuity in security performance and higher levels of leadership readiness to tackle future challenges

Evaluation of Convolutional Neural Networks for Predicting Steering Angles in Autonomous Driving Systems Using the Udacity Simulator

Bashar Khawaldeh — 2025-09-30

This research explores the use of convolutional neural networks (CNNs) to develop autonomous driving systems, focusing on predicting steering angles for autonomous vehicles. A custom dataset was created using the Udacity simulator, which provides a high-fidelity simulation environment with multiple lanes and three-angle cameras to collect driving data. This data encompasses, but is not limited to, vehicle speed, steering angle, and gear position. To achieve this objective, two CNN models were utilized: the simple Comma.ai model and the more complex NVIDIA model. These models were utilized to compare performance and examine their ability to predict steering angles accurately. The experimental framework entailed the training of models on data using mean loss evaluation (MSE) and the subsequent validation of their performance on independent validation data. The findings of the study demonstrated that both models exhibited the capacity to differentiate driving patterns from visual data. However, the NVIDIA model exhibited superior performance in complex environments, a feat attributable to its advanced architecture and its ability to extract more accurate features. Conversely, the Comma model demonstrated superior performance in less complex environments, making it a suitable option for simpler systems.

The Influence of Song Recommendation Algorithm Strategies and User Experience on Listener Engagement with Spotify Among Young People in Depok City

Rayvienza Angelisa Soedira — 2025-09-30

The development of digital technology has shifted how people consume music, with streaming platforms like Spotify becoming increasingly popular, especially among young users. This study aims to examine the influence of song recommendation algorithm strategies and user experience on listener engagement with Spotify among young people in Depok City, Indonesia. Using a quantitative approach with purposive sampling, the study targeted users aged 10 to 29 years. The results showed that song recommendation algorithm strategies and user experience significantly influenced listener engagement on Spotify. Among the two variables, user experience had a more dominant influence. These findings indicate that optimizing the user interface and personalization features could enhance user engagement on music streaming platforms. The study highlights the importance of aligning technological features and personalized services with user expectations to maintain long-term engagement.

The Future of Performance Management in the Shift from Annual Appraisals to Continuous Feedback

Jasim Hamdan Mohammed Bin Jarsh — 2025-09-30

This study investigates how the Dubai Police Force transitioned from rigid, traditional annual appraisals to a dynamic, continuous-feedback performance-management system. Employing a quantitative methodology, a five-point Likert questionnaire was administered to a stratified random sample of 100 officers who experienced this shift firsthand. Data were analyzed using SPSS to identify central tendencies, correlations, and differences in perceptions. The findings reveal a high overall adoption index (mean = 4.563), indicating strong acceptance of the new system. Officers rated the ability to set flexible, personalized goals (mean = 4.789) and participation in self-assessments and peer reviews (mean = 4.671) most favorably. Criteria emphasizing collaboration, innovation, and adaptability scored 4.634, while real-time digital tracking tools scored 4.497. Continuous feedback mechanisms, replacing year-end reviews, scored 4.224, confirming broad support despite being the lowest-ranked item. Thematic analysis shows that immediate feedback reduces error accumulation, fosters continuous learning, and strengthens organizational commitment. A significant positive correlation was found between feedback frequency and job satisfaction, especially in dynamic operational environments. Continuous, two-way dialogue accelerates decision-making, enhances organizational agility, and improves the quality of managerial decisions by providing up-to-date performance data. While implementation challenges arise from traditional hierarchical cultures, pilot phases, digital platform integration, and leadership coaching mindsets can mitigate resistance. The study concludes that paragraph-based narrative evaluations, supported by smart digital tools, create a human-centered performance-management paradigm that aligns individual and institutional objectives, ultimately enhancing officer engagement, productivity, and strategic agility in security settings.

The impact of digital procurement, procurement policies, and supply chain resilience on organizational performance

Nawaf Al Awadhi — 2025-09-30

Organizations operate in an increasingly competitive and dynamic environment, which continues to pressure leadership to improve procurement processes, increase supply chain resilience, and follow policy paths for sustainable growth. Organizations are using digital technologies and resilient procurement as the drivers of organizational performance, which can address challenges in stakeholder demand for product costs, product availability, and global disruptions. Hence, this study examines the impact of digital procurement, procurement policies, and supply chain resilience on organizational performance. A quantitative research design was used in the context of the study, which consisted of survey data from 408 managerial-level employees within semi-government organizations in the UAE. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess both the measurement and structural models. The findings support all three hypotheses as examining digital procurement, procurement policies, and supply chain resilience positively influence organizational performance. The findings continue to emphasize that procurement roles are no longer purely transactional activities, but rather strategies for organizational growth and competitive advantage.