International Journal of Data Science and Advanced Analytics

Digital Transformation as a Catalyst for Activity-Based Funding Implementation

Mon, 01 Sep 2025 00:00:00 +0000

Activity-Based Funding (ABF) has gained traction globally to enhance hospital reimbursement by linking payments to volume and complexity of care via Diagnosis-Related Groups (DRGs). Empirical evidence on ABF’s effectiveness remains mixed and context dependent. Notably, the Middle East and North Africa (MENA) region lacks rigorous analyses of ABF implementation due to lack of understanding of advanced digital health technologies. This study investigated the role of digital transformation in ABF implementation within Saudi Arabia’s healthcare system considering institutional, organizational, and technological factors. A comparative qualitative case study was employed, analyzing policy documents, implementation reports, and stakeholder interviews. The study applied the framework of the principal-agent theory to interpret incentive structures and utilized a digital maturity lens to assess the integration of health information systems supporting ABF. Findings revealed that ABF reforms were initiated and aligned with national development agendas. Saudi Arabia’s relatively advanced digital health ecosystem has facilitated more effective cost accounting, data integration, and transparency, enabling smoother ABF rollout. This Saudi context underscores the necessity of aligning stakeholder incentives and building organizational capabilities for data-driven decision-making to realize ABF’s efficiency and quality improvement goals. In conclusion, this study contributed to the research dialogue by demonstrating that successful ABF implementation in emerging economies surpasses financial restructuring per se, to leverage digital transformation to overcome systemic barriers. Policymakers are advised to prioritize investments in digital health infrastructure and governance frameworks to support sustainable, value-based healthcare financing reforms in the MENA region.

Hybrid Crime Scene Policing in the Digital Evidence Era: A Conceptual Framework for Artificial Intelligence and Immersive Training

Saleh MANSOUR, Jamila Bukar Gana, Evans Kiprop, Mira Mansour, Wadih Gerges — Fri, 01 Aug 2025 00:00:00 +0000

Hybrid crime scene policing in the digital evidence era increasingly involves the integration of physical and digital evidence, creating new operational, legal, and training challenges for law enforcement. This paper presents a conceptually framed, practice-informed analytical synthesis of selected literature and documented international use cases examining the role of artificial intelligence (AI) and immersive technologies in crime scene training and investigation. It proposes a tiered conceptual framework for AI and immersive training that integrates immersive simulation, AI-facilitated performance analysis, and hybrid physical–digital training, and discusses the associated legal, ethical, and operational considerations necessary for responsible implementation.

Phase Locking Values and Analytics for Finding Patterns from Rhythms of Hormones

Hillol Biswas — Sat, 02 Aug 2025 00:00:00 +0000

The body's hormones have exact timing patterns that function as codes for regular physiology. Sleep, metabolism, temperament, immunity, and reproduction are all influenced by the manner in which a hormone is produced, not just its quantity. The same hormone level can have quite different consequences when these time patterns are disturbed, which can result in issues like poor glucose control, infertility, or sleep disturbances. Internal conflict results from improper signal timing, whereas organs and cells function in unison when signals are timed correctly. Light, food, and activity are examples of external stimuli that have a significant impact on these patterns. Natural timing-restoring clinical treatments frequently perform better than dose-only alternatives. Essentially, the timing of hormone action is just as important to health as their intensity. However, data are not available for all these hormones at one place for a broader study based on analytical techniques for finding any overall relation. This paper describes the different hormones from available resources/data and using this based on a synthetic data generation of 50 number of hormones with temporal characteristics make analytics for finding a broader overview.

Early Adoption of Online and Mobile Banking: An Analysis of Consumer Attitudes

Wed, 30 Jul 2025 00:00:00 +0000

Consumer behaviour is influenced by a variety of factors, among which consumer attitudes are particularly significant. Attitudes play a pivotal role in shaping individuals’ purchasing and consumption decisions. This study conducts a literature review focusing on consumer attitudes toward online and mobile banking during the early stages of their adoption, specifically between 2002 and 2011. As digital banking channels gained popularity, this behavioural shift contributed to a gradual decline in the relevance of physical bank branches. The review is guided by three primary objectives: (1) to explore general consumer attitudes toward online and mobile banking, (2) to identify the factors associated with of these digital banking platforms that positively or negatively influenced consumer perceptions, and (3) to examine demographic variations in consumer attitudes. The findings indicate a generally favourable consumer disposition toward online and mobile banking during the study period, with increased adoption reflecting growing acceptance. Positive influences on consumer attitudes included time efficiency, ease of use, convenience, and enhanced autonomy through 24/7 account access and control. Conversely, concerns related to security and the loss of in-person interactions emerged as key negative factors. Demographic analysis revealed that younger consumers were more inclined to embrace digital banking compared to older age groups. These insights offer practical implications for financial institutions, suggesting strategic areas for improving customer engagement and service delivery in the digital banking landscape.

Enhancing Judicial Efficiency through Artificial Intelligence: Analyzing Federal Justice Systems from an Organizational Behavior Perspective- A Data-Driven Study

Saleh MANSOUR, Dulari Rajput — Sat, 26 Jul 2025 00:00:00 +0000

Artificial Intelligence (AI) has brought transformation prospects in many fields, and that covers the U.S. Federal Justice System. This study specifically identifies AI-powered risk assessment algorithms, predictive analytics, and automated case management systems as holding potential to minimize judicial backlogs, foster more consistent decision-making, and reduce recidivism rates. With this integration of AI, on the other hand, comes some new challenges: it risks reinforcing historical biases; there are some ethical concerns about transparency; and a few related to public trust. This paper discusses the impacts of organizational behavior using both quantitative data and qualitative insights, assesses ethical risks, and presents recommendations for the responsible deployment of AI. Results have indicated a considerable gain in efficiency after the integration of AI, but at the same time pointed out that continuous refinement of AI tools is necessary in the course of upholding the principles of fairness and justice. The paper concludes by discussing some policy suggestions, laying out future directions for research to better improve AI's role at the judiciary.