Tropical Scientific Journal

Assessing Relationship Between Enterprise Risk Management And Hospital Performance In UAE

Fatima Mohamed Hussain Rahmatalla Almaazmi — 2024-07-28

Objective: This paper aims to assess the relationship between enterprise risk management and hospital performance in the UAE.

Research Method: Data collection involved a quantitative approach using a structured questionnaire survey. The gathered data was analyzed with advanced multivariate analysis of structural equation modelling with the help of the SmartPLS software package.

Findings: ERM has a strong positive relationship with Business Model Innovation while ERM does not have a direct significant impact on Hospital Financial Performance Hospital Non-financial Performance Hospital Environmental Performance. Business Model Innovation has observed a direct significant effect on Hospital Financial Performance, Hospital Non-financial Performance and hospital environmental performance.

Originality: The findings of the study will assist the practitioners in strategic planning and improving hospital performance in the UAE.

Assessing Readiness Factors For Integrating Artificial Intelligence In UAE Disaster Response Management

Nayef Mohammed Abdulla Musabbeh Alneyadi — 2025-02-07

Objective: This study aims to uncover the readiness factors for AI integration by the National Emergency Crisis and Disasters Management Authority (NCEMA) in the UAE.

Research Method: The study employed a quantitative research methodology to gather data from 317 personnel employed by the National Emergency Crisis and Disasters Management Authority (NCEMA) in the UAE, using stratified random sampling to distribute the questionnaire.

Findings: The findings of this study emphasize the critical need for aligning the integration of AI in the UAE’s disaster response system with international standards and best practices. By prioritizing fairness, accountability, human oversight, ethical clarity, and transparency, the UAE can ensure that AI-driven disaster response efforts are both effective and trustworthy. A robust policy and regulatory framework are essential to enhance readiness for AI integration. Key considerations include ensuring data privacy and security, establishing tailored AI-specific policies, securing government support, complying with international regulations, and upholding ethical guidelines. These measures will contribute to the development of AI systems that are secure, ethically sound, and highly effective in disaster response. Furthermore, strengthening the UAE’s technological infrastructure is vital for successful AI integration. Access to computational power, availability of AI tools, seamless communication platforms, and reliable data analysis capabilities will collectively enhance AI-driven disaster response efforts. Government support and incentives also play a crucial role in fostering AI readiness. Investments in research and development, financial grants, tax incentives, and strategic partnerships will create a robust ecosystem for AI implementation, ultimately improving national disaster resilience.

Originality: This study aims to address the key readiness factors for AI integration in the UAE's disaster preparedness and response capabilities. By leveraging AI as a transformative tool, the UAE can mitigate risks, improve response efficiency, and safeguard communities against future disasters. This research aims to offer significant insights assessing readiness factors for integrating Artificial Intelligence in UAE Disaster Response Management

A Study Of Healthcare Risks And Mitigating Strategies: Case Of Shaam Hospital UAE

Fatema Ali Saeed Taffoof Alshehhi — 2025-01-22

Objective: Healthcare services in hospital environments are frequently beset by numerous risks that may result in negative outcomes and operational inefficiencies. This study seeks to examine the healthcare risks and their effects at Shaam Hospital, UAE.

Research Method: The study employed a quantitative research methodology to gather data from hospital operational staff. Statistical instrument Statistical Package for the Social Sciences (SPSS) was used to perform a comprehensive analysis of the data, discerning critical risk factors.

Findings: The risks are categorized in three categories as regulatory and legal risks; operational and resource Risks; clinical and patient care risks. In regulatory and legal risks; regulatory audits are conducted regularly to ensure legal compliance in operations, has the highest meanwhile in operational and resource Risks, the highest-ranked item is "There is effective management of hospital equipment and supplies". In clinical and patient care risks in a healthcare facility, "The hospital ensures timely and accurate diagnosis for all patients" is highest ranked risk. Mitigating and corrective strategies were also classified in three categories as Enhancement of Medication Safety Systems; Promotion of a Strong Safety Culture; implementation of comprehensive infection control programs. "The hospital uses technology, such as barcoding or electronic prescribing, to enhance medication safety"; "Safety rounds are regularly conducted to identify potential hazards and safety risks"; "Hand hygiene compliance is regularly enforced and monitored throughout the hospital" are highest ranked measures in the above categories respectively.

Originality: This research aims to offer significant insights into healthcare risk management, thereby enhancing the development of safer and more resilient healthcare systems in the UAE and beyond

The Solution Properties Of Liquid Detergent Modified With Carboxymethyl Cellulose From Banana Pseudo Stem

Ikechukwu Harrison Oseh — 2025-02-07

Objective: Carboxymethyl cellulose (CMC) can be used as thickener and rheology modifier in liquid detergents. In this research, liquid detergent of known concentration was prepared and the effect of CMC of different degrees of substitution (D.S) on the rheological properties and cleaning action of the liquid detergent was studied.

Research Method: The banana pseudo stems were converted to cellulose when pulped with sodium hydroxide (NaOH) solution bleached with sodium hypochlorite and dried. The cellulose was converted to CMC of different D.S by reaction with different amounts of chloroacetic acid in the presence of NaOH as alkalizing agent. Detergent was prepared by neutralizing 2-dodecylbenzene sulphonic acid with NaOH in the molar ratio of 2:1. The liquid detergent (1%, w/v) was modified with CMC of different D.S. The liquid detergent was characterized in terms of pH, lather volume, foam capacity, rheology and cleaning action.

Findings: The CMC prepared had D.S in the range of 0.67 to 0.91. The pH of 1% (w/v) aqueous detergent was 6.12. The lather volume and foam capacity of 1% (w/v) liquid detergent were 70.20mL and 3.51 respectively in distilled water and 51.30mL and 2.57 respectively in hard water. The rheological behaviors of the liquid detergent modified with CMC of different D.S were non-Newtonian.

Originality: The liquid detergent modified with CMC had better cleaning action and increased with D.S. Liquid detergent with known concentration was produced and CMC from banana pseudo modified the rheological properties of liquid detergent with increased D.S. The CMC also increased the cleaning action of the liquid detergent.

Modelling The Mediation Effect Of Management Support On The Relationship Between AI Adoption Innovation Dimensions And AI Implementation In The UAE Tourism Sector

Aesha Saeed Abdulla Zuwayyed Alshehhi — 2025-03-02

Objective: This study aims to develop an empirical framework of the mediation effect of management support on the relationship between AI adoption innovation dimensions and the successful implementation of AI technologies within the UAE tourism sector

Research Method: Data to validate the theoretical framework was collected from 370 employees of the Dubai Tourism Authority using purposive sampling. The validation process employed SmartPLS software, utilizing PLS-SEM techniques to examine relationships between variables. PLS-SEM is particularly well-suited for validating theoretical models and ensuring analytical robustness in developing the empirical framework

Findings: The empirical framework indicates that Management Support significantly enhances AI adoption by amplifying the impact of Compatibility, Relative Advantage, and Trialability, while Low Complexity has an insignificant indirect effect. Additionally, the direct effects of these innovation dimensions on AI adoption vary in strength. This framework has several practical applications. From a strategic AI implementation perspective, organizations can prioritize AI innovations that demonstrate strong direct and indirect influences on adoption, particularly focusing on Compatibility and Relative Advantage

Originality: Through applying this framework, tourism businesses and policymakers can develop optimized AI adoption strategies, ultimately improving efficiency, customer experiences, and overall industry competitiveness

A Study On The Adoption Of Intelligent Tutoring Systems (ITS) Readiness On UAE Higher Education Institutions

Mohammed Saeed Salem Alwami Alshmsi — 2025-02-05

Objective: Intelligent Tutoring Systems (ITS) in higher education utilize artificial intelligence to provide personalized learning experiences, effectively replicating one-on-one tutoring by adapting content and feedback to individual student needs. Despite advancements in educational technology, the adoption of ITS in UAE higher education institutions remains limited due to various cultural, social, and educational challenges. This study aims to assess the readiness for ITS adoption in UAE higher education institutions.

Research Method: A quantitative research approach was employed, utilizing a structured questionnaire survey administered to 234 participants. Descriptive analysis was conducted to rank key factors influencing ITS adoption readiness, while correlation analysis examined relationships between these factors and performance indicators.

Findings: The findings highlight critical determinants of ITS adoption readiness, revealing both strong support and existing concerns within the UAE higher education context. Correlation analysis indicates that ITS adoption readiness is positively influenced by factors such as Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, Innovativeness, and Optimism. These factors exhibit strong correlations with key performance indicators, including Performance Enhancement, Administrative Efficiency, and Personalized Learning, suggesting a generally high level of preparedness for ITS adoption. However, moderate correlations with factors like Discomfort and Insecurity underscore the need to address potential concerns regarding implementation challenges and perceived risks.

Originality: This study provides valuable insights for policymakers and educational institutions seeking to enhance ITS adoption and integration in UAE higher education.