We studied the role of industry-academic collaboration (IAC) in the enhancement of educational opportunities and outcomes under the digital driven Industry 4.0 using research and development, the patenting of products/knowledge, curriculum development, and artificial intelligence as proxies for IAC. Relevant conceptual, theoretical, and empirical literature were reviewed to provide a background for this research. The investigator used mainly principal (primary) data from a sample of 230 respondents. The primary statistics were acquired through a questionnaire. The statistics were evaluated using the structural equation model (SEM) and Stata version 13.0 as the statistical software. The findings indicate that the direct total effect of Artificial intelligence (Aint) on educational opportunities (EduOp) is substantial (Coef. 0.2519916) and statistically significant (p < 0.05), implying that changes in Aint have a pronounced influence on EduOp. Additionally, considering the indirect effects through intermediate variables, Research and Development (Res_dev) and Product Patenting (Patenting) play crucial roles, exhibiting significant indirect effects on EduOp. Res_dev exhibits a negative indirect effect (Coef = −0.009969, p = 0.000) suggesting that increased research and development may dampen the impact of Aint on EduOp against a priori expectation while Patenting has a positive indirect effect (Coef = 0.146621, p = 0.000), indicating that innovation, as reflected by patenting, amplifies the effect of Aint on EduOp. Notably, Curriculum development (Curr_dev) demonstrates a remarkable positive indirect effect (Coef = 0.8079605, p = 0.000) underscoring the strong role of current development activities in enhancing the influence of Aint on EduOp. The study contributes to knowledge on the effective deployment of artificial intelligence, which has been shown to enhance educational opportunities and outcomes under the digital driven Industry 4.0 in the study area.

With society’s continuous development and progress, artificial intelligence (AI) technology is increasingly utilized in higher education, garnering increased attention. The current application of AI in higher education impacts teachers’ instructional methods and students’ learning processes. While acknowledging that AI advancements offers numerous advantages and contribute significantly to societal progress, excessive reliance on AI within education may give rise to various issues, students’ over-dependence on AI can have particularly severe consequences. Although many scholars have recently conducted research on artificial intelligence, there is insufficient analysis of the positive and negative effects on higher education. In this paper, researchers examine the existing literature on AI’s impact on higher education to explore the opportunities and challenges presented by this super technology for teaching and learning in higher educational institutions. To address our research questions, we conducted literature searches using two major databases—Scopus and Web of Science—and we selected articles using the PRISMA method. Findings indicate that AI plays a significant role in enhancing student efficiency in academic tasks and homework; However, when considering this issue from an ethical standpoint, it becomes apparent that excessive use of AI hinders the development of learners’ knowledge systems while also impairing their cognitive abilities due to an over-reliance on artificial technology. Therefore, our research provides essential guidance for stakeholders on the wise use of artificial intelligence technology.

This paper examines the transformative potential of e-government in public administration, focusing on its capacity to enhance service delivery, transparency, accessibility, cost efficiency, and civic engagement. The study identifies key challenges, including inadequate technological infrastructure, cybersecurity vulnerabilities, resistance to change within public institutions, and a lack of public awareness about e-government services. These barriers hinder the seamless operation and adoption of digital government initiatives. Conversely, the study highlights significant opportunities such as streamlined service delivery, enhanced transparency through real-time access to government data, increased accessibility for marginalized and remote communities, substantial cost savings, and greater civic engagement via digital platforms. Addressing these challenges through targeted strategies—enhancing technological infrastructure, bolstering cybersecurity, managing organizational change, and raising public awareness—can help policymakers and public administrators implement more effective and inclusive e-government initiatives. Additionally, the integration of these digital solutions can drive sustainable development and digital inclusion, fostering social equity and economic growth. By leveraging these opportunities, governments can achieve more efficient, transparent, and accountable governance. Ultimately, the successful implementation of e-government can transform the relationship between citizens and the state, building trust and fostering a more participatory democratic process.

Sustainability has turned into a critical focus for businesses, drawing considerable interest from the commercial sector and scholarly environments. While empirical investigations have been conducted regarding sustainability reporting within small and medium enterprises, only a limited number of companies are subjected to increased pressure to adopt sustainability reporting practices, thereby ensuring enhanced transparency and disclosure in their financial and sustainability disclosures. This research, framed by Institutional Theory, delves into how challenges in sustainability reporting obstruct organizations from properly evaluating and sharing their progress on sustainability aims. With an explanatory research framework in place, we circulated survey questionnaires to 400 participants, who were randomly drawn from a population of 28,927 registered SMEs in Metro Manila, Philippines. The application of Interpretative Structural Modelling and MICMAC Analysis revealed that the absence of regulatory frameworks, governmental assistance, and sustainability infrastructure constitutes the most critical obstacles impacting other determinants. In contrast, neither the deficiency in sustainability awareness nor the inadequacy of training and skills demonstrated a considerable impact on the other identified barriers. This study clarifies the complex interactions and interrelations among the obstacles to sustainability reporting, thus providing significant perspectives for organizations aiming to overcome these difficulties. The findings suggest that business leaders and stakeholders can formulate targeted strategies and interventions to facilitate the adoption of sustainability reporting practices within organizations. The application of the institutional theory framework highlights that pressures arise from a diverse array of institutional actors, including regulators, customers, and local communities, which collectively shape corporate behavior and reporting methodologies.

Decentralized cryptocurrencies, such as bitcoin, use peer-to-peer software protocol, disintermediating the traditional intermediaries that used to be banks and other financial intermediaries, effectuating cross-border transfer. In fact, by removing the requirement for a middleman, the technology has the potential to disrupt current financial transactions that rely on a trusted authority or intermediary operator. Traditional financial regulation, primarily based on the command-and-control approach, is ill-suited to regulating decentralized cryptocurrencies. The present paper aims to investigate the policy option most suitable for regulating decentralized cryptocurrencies. The study employs content analysis method to effectuate the purpose of the study. The paper argues that the combination of both direct and indirect regulatory approaches would be a feasible option for regulating decentralized cryptocurrencies. The absence of centralized authority and the borderless nature of decentralized cryptocurrencies would make them antithetical to centralized direct regulation. Therefore, the findings of the study suggest that regulators should focus on regulating intermediaries bridging the connection between the online world (crypto ecosystem) and the physical world (the point of converting crypto into fiat money). These intermediaries can work as passive actors or surrogate regulators who are indirectly responsible for implementing policy options on behalf of the central authority.

The integration of Big Earth Data and Artificial Intelligence (AI) has revolutionized geological and mineral mapping by delivering enhanced accuracy, efficiency, and scalability in analyzing large-scale remote sensing datasets. This study appraisals the application of advanced AI techniques, including machine learning and deep learning models such as Convolutional Neural Networks (CNNs), to multispectral and hyperspectral data for the identification and classification of geological formations and mineral deposits. The manuscript provides a critical analysis of AI's capabilities, emphasizing its current significance and potential as demonstrated by organizations like NASA in managing complex geospatial datasets. A detailed examination of selected AI methodologies, criteria for case selection, and ethical and social impacts enriches the discussion, addressing gaps in the responsible application of AI in geosciences. The findings highlight notable improvements in detecting complex spatial patterns and subtle spectral signatures, advancing the generation of precise geological maps. Quantitative analyses compare AI-driven approaches with traditional techniques, underscoring their superiority in performance metrics such as accuracy and computational efficiency. The study also proposes solutions to challenges such as data quality, model transparency, and computational demands. By integrating enhanced visual aids and practical case studies, the research underscores its innovations in algorithmic breakthroughs and geospatial data integration. These contributions advance the growing body of knowledge in Big Earth Data and geosciences, setting a foundation for responsible, equitable, and impactful future applications of AI in geological and mineral mapping.