This study investigates the integration of sustainability principles into educational curricula, focusing on the gap between theoretical knowledge and practical application. Through a mixed-methods approach, the research identifies key institutional barriers, including outdated policies, insufficient teacher training, and limited resources. These barriers hinder the effective incorporation of sustainable development principles into education. The study reveals that while some educational systems struggle to adopt sustainability, examples from progressive institutions show that integrating these principles enhances student awareness and equips them with skills essential for sustainable development. The findings suggest that substantial changes are needed in existing educational frameworks to better support sustainability in curricula. Recommendations for future research include conducting longitudinal studies to assess the long-term impact of curriculum changes on sustainability outcomes and exploring the role of technology in advancing sustainable education. Policy recommendations emphasize the need for advocacy and the implementation of actionable strategies, such as industry collaborations for pilot projects and real-world applications. Furthermore, institutional support for teacher professional development is crucial, with structured programs that combine theoretical knowledge and practical skills in sustainability. Enhancing partnerships between educational institutions and industries, including co-designed curriculum modules and internship opportunities, is also essential for aligning education with the Sustainable Development Goals. This study highlights the importance of transforming educational practices to better address the challenges of sustainable infrastructure development, ultimately preparing students to contribute to a more sustainable future.

Recent times have seen significant advancements in AI and NLP technologies, poised to revolutionize logistical decision-making across industries. This study investigates integrating ChatGPT, an advanced AI language model, into strategic, tactical, and operational logistics. Examining its applicability, benefits, and limitations, the study delves into ChatGPT’s capacity for strategic logistics planning, facilitating nuanced decision-making through natural language interactions. At the tactical level, it explores ChatGPT’s role in optimizing route planning and enhancing real-time decision support. The operational aspect scrutinizes ChatGPT’s capabilities in micro-level logistics and emergency response. Ethical implications, encompassing data security and human-AI trust dynamics, are also analyzed. This report furnishes valuable insights for the logistics sector, emphasizing AI’s potential in reshaping decision-making while underscoring the necessity for foresight, evaluation, and ethical considerations in AI integration. In this publication, it is assumed that ChatGPT is not entirely reliable for decision-making in the logistics field: at the strategic level, it can be effectively used for “brainstorming” in preparing decisions, but at the tactical and operational level, the depth of the knowledge is not sufficient to make appropriate decisions. Therefore, the answers provided by ChatGPT to the defined logistic tasks are compared with real logistic solutions. The article highlights ChatGPT’s effectiveness at different levels of logistics and clarifies its potential and limitations in the logistics field.

The Malaysian government’s efforts to promote solar photovoltaic (PV) usage among households face a challenge due to its low adoption rate. This study delves into the factors influencing the exponential adoption of solar PV electricity generation among landed residential property owners in Malaysia. The research aims to comprehensively examine the predictors influencing the adoption of solar PV systems among Malaysian households. Hence, the study employs an enhanced Theory of Planned Behavior framework, integrating sustainable energy security dimensions such as availability, affordability, efficiency, acceptability, regulation, and governance. The sample comprised 556 Malaysian residents who owned and resided in the landed properties. The home locations where at least one solar PV installation existed within a residential street. Snowball sampling was employed through referrals, leveraging social and community networks. Collected data was analyzed using the partial least squares structural equation modeling. Attitude, affordability, and acceptability emerged as pivotal factors significantly impacting the intention to use solar PV systems among Malaysian households. This research not only enriches academic discourse but also offers practical implications for policymakers, guiding the formulation of targeted strategies to promote sustainable energy practices and facilitate the widespread adoption of solar PV systems in Malaysia.

Technological advancements in genetic research are crucial for nations aiming to uplift their population’s quality of life and ensure a sustainable economy. Genomic information and biotechnology can enhance healthcare quality, outcomes, and affordability. The “P4 medicine approach”—predictive, preventive, personalized, and participatory—aligns with objectives like promoting long-term well-being, optimizing resources, and reducing environmental impacts, all vital for sustainable healthcare. This paper highlights the importance of adopting the P4 approach extensively. It emphasizes the need to enhance healthcare operations in real-time and integrate cutting-edge genomic technologies. Eco-friendly designs can significantly reduce the environmental impact of healthcare. Additionally, addressing health disparities is crucial for successful healthcare reforms.

This study conducts a systematic literature review to analyze the integration of artificial intelligence (AI) within business excellence frameworks. An analysis of the findings in the reviewed articles yielded five major themes: AI technologies and intelligent systems; impact of AI on business operations, strategies, and models; AI-driven decision-making in infrastructure and policy contexts; new forms of innovation and competitiveness; and the impact of AI on organizational performance and value creation in infrastructure projects. The findings provide a comprehensive understanding of how AI can be integrated into organizational excellence emerged frameworks to address challenges in infrastructure governance, and sustainable development. Key questions addressed include: how AI affects consumer behavior and marketing strategies. What AI’s capabilities for businesses, especially marketing and digital strategies? How can organizations address the drivers and barriers to help make better use of AI in these business operations? Should organizations even do anything with these insights? These questions and more will be tackled throughout this discussion. This paper attempts to derive a comprehensive conceptual framework from several fields of human resources, operational excellence, and digital transformation, that can help guide organizations and policymakers in embedding AI into infrastructure and development initiatives. This framework will help practitioners navigate the complexities of AI integration, ensuring profitability and sustainable growth in a highly competitive landscape. By bridging the gap between AI technologies and development-related policy initiatives, this research contributes to the advancement of infrastructure governance, public management, and sustainable development.