This systematic review critically examines the inclusive education practices for Students of Determination (SoDs) in Higher Education Institutions (HEIs), focusing on the specific case of the United Arab Emirates (UAE). The research will demonstrate best practices, key challenges, and most researched and less researched areas. In line with the PRISMA framework and using thematic analysis, this review synthesizes the findings of 41 peer-reviewed articles that focus on instructional practices, technological solutions, staff training, and institutional support. The results suggest that, globally, higher education institutions (HEIs) are increasingly adopting inclusive education policies, and that they are finding it challenging to implement these practices effectively, especially in the UAE. Important obstacles include restricted instructor education, variable institutional processes, and accessibility limitations. In addition, the use of assistive technologies has been shown to have positive outcomes, yet it remains underused because of the infrastructure and the training of faculty and students. This paper gives evidence-based suggestions to educational institutions like colleges or universities to make them more inclusive through better-trained faculty, better institutional policies, and the incorporation of assistive technologies. Also, the findings provide UAE-specific policy implications that underscore the importance of a well-defined national framework to support SoDs. Future studies must be longitudinal in nature, involving evaluations of the extent to which the strategies exert effects on SoDs’ academic performance and social inclusion.

This paper aims to study the role of HRM in contribution to organizational effectiveness (OE) and understand the evolving relationship between them over past years and in the future. This paper will also focus on evolution of HRM over the period of time and the challenging role of HRM in the 21st century. In last, paper will discuss about introduction of Information and Communication Technology (ICT) to HRM in terms of e-HRM and how e-HRM can contribute towards organizational sustainability.

Artificial Intelligence (AI) is transforming organizational behavior by reshaping employee engagement, performance, and decision-making processes. This study examines AI’s impact on workplace dynamics, focusing on its role in optimizing workload distribution, enhancing productivity, and supporting leadership adaptation. AI-driven tools, such as sentiment analysis and predictive modeling, facilitate engagement and efficiency but also introduce challenges related to job security, ethical concerns, and transparency. Using a qualitative approach, this research synthesizes findings from systematic literature reviews and meta-analyses to explore the implications of AI in modern organizations. The results indicate that AI-supported leadership and human-centered design principles contribute to motivation and long-term productivity. However, excessive AI reliance may disrupt trust and psychological contracts, potentially affecting organizational culture. This study emphasizes the need for ethical AI governance and strategic leadership to mitigate risks while leveraging AI’s benefits. By adopting a balanced approach to AI integration, organizations can foster employee well-being, maintain equitable decision-making, and align AI adoption with sustainable growth. These findings contribute to the discourse on AI in management, offering insights into how organizations can harness AI’s potential while safeguarding human-centered values.

This research intends to explore the relationship between subjective and objective environmental knowledge and green products purchase intention and if green products purchase intention leads to green products actual purchase behavior in the context of UAE consumers. It also intends to explore the moderating effect of Price consciousness on the relationship between green products purchase intention and green products actual purchase behavior. A self-administered questionnaire used to collect the data about the study variables, 186 respondents from UAE participated in this research and data analyzed using Statistical Package for Social Sciences (SPSS) version 22. The findings of this research indicate that Subjective and Objective Environmental Knowledge were determinants of Green Products Purchase Intention, and that Purchase Intention was positively and significantly associated with actual Purchase Behavior. No significant relationship found of price consciousness as a moderator.

Creating realistic simulations of human-machine interaction through virtual counterparts is a cutting-edge area of research that involves innovative approaches. This endeavor aims to develop lifelike simulations where humans can interact with virtual entities in a natural and intuitive manner. Researchers are exploring advanced artificial intelligence mechanisms and gesture recognition technologies to enhance the realism of these simulations. Additionally, the integration of virtual real-time and augmented reality technology plays a crucial role in providing immersive and engaging knowledge. By combining these components, the goal is to create virtual companions that not only human behaviors but also adapted and responding intelligently to user inputs, fostering an additional seamless and effectiveness interaction between humans and devices.

This paper examines the impact of AI-driven concept generation on development cycles and market responsiveness. As organisations face pressure to innovate rapidly, AI is increasingly leveraged to accelerate product ideation, streamline prototyping, and enhance decision-making. This study explores whether AI-driven concept generation reduces time-to-market while maintaining product-market alignment. This research synthesises existing literature and industry case studies on AI applications in product management, supply chain optimisation, and business model innovation. Drawing on interdisciplinary perspectives, it critically evaluates AI’s role in automated design exploration, data-driven decision-making, and market validation. A theoretical lens grounded in organisational behaviour and technology adoption frameworks underpins the analysis. AI-driven concept generation substantially reduces development cycles by enabling rapid prototyping, data-informed ideation, and real-time customer feedback loops. AI enhances firms’ adaptability to market fluctuations by automating design exploration and improving strategic decision-making. However, the effectiveness of AI-generated concepts is contingent on data quality, human oversight, and organisational integration. While AI fosters efficiency, its benefits predominantly accrue to larger firms with robust AI infrastructure, potentially reinforcing industry concentration. This paper contributes to the discourse on AI in organisational behaviour by synthesising insights across multiple domains. It provides a nuanced understanding of AI’s role in product innovation and strategic agility, offering implications for managers, policymakers, and researchers.