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Artificial Intelligence (AI)-powered technologies are revolutionising the landscape of education, ushering in a myriad of possibilities and challenges. This article delves into the dual nature of AI-driven tools in education, spotlighting pivotal advancements like automated grading, personalised learning algorithms, online monitoring, content filtering, AI-based learning tools, Chat Generative Pre-trained Transformer (ChatGPT) and standardised testing (ST) platforms. Ultimately, the examination reveals a spectrum of advantages, risks and considerations associated with AI-driven educational applications. Employing the PRISMA protocol, this study systematically reviews peer-reviewed literature concerning the implementation and ethical implications of AI in higher education. The analysis incorporates 36 scholarly articles, uncovering the entrepreneurial advantages of AI, such as tailored learning experiences, self-assessment opportunities, heightened efficiency, skill enhancement and reduced educational disparities. Concurrently, the research identifies potential hazards, including user profiling, plagiarism, academic integrity breaches and excessive reliance on technology that may hinder creative learning dynamics. Crucial concerns emerge, encompassing the possible devaluation of educators' roles, privacy issues inherent in personalised learning platforms and the intrusive nature of online surveillance. Additionally, the study highlights biases embedded within AI algorithms and apprehensions regarding job displacement within the academic community. To steer AI integration responsibly within higher education, the investigation explores ethical frameworks and models, offering pragmatic suggestions for institutions. Recommendations advocate for a balanced approach, emphasising judicious AI utilisation and the formulation of institutional policies. This chapter's distinctiveness lies in its innovative stance, striving to reconcile the technical and entrepreneurial benefits of AI applications with the preservation of creativity in higher education contexts.

In this chapter, we describe the importance of good governance in the metaverse. It offers unlimited opportunities and presents unique governance challenges. First, we describe the concept of good governance and its relevance to the metaverse. We emphasize that the speed of metaverse adoption depends upon the presence or absence of effective governance. Recognizing the metaverse as the next iteration of the internet, we present significant governance issues. Some issues such as interoperability, security, safety, privacy, law, and digital inequality are critical governance issues in the metaverse. Next, we explore the diverse governance frameworks to ensure the implementation of policies and regulations. These frameworks include decentralized governance, cross-sector collaboration, and standards-based governance. We also describe the best practices which are essential for good governance. To materialize the concepts and principles discussed, we present a compelling case study centered on Decentraland. This insightful exploration dissects a decentralized autonomous organization (DAO)-based governance structure, offering valuable insights into the intricacies and stages of governance proposals. We acknowledge both the merits and potential drawbacks inherent to this approach. This chapter aims to offer an all-encompassing view of metaverse governance, essentially serving as a comprehensive roadmap for traversing the multifaceted landscape of this digital frontier.

This study examines green absorptive capacity as an important intervening variable that elucidates the relationship between green supply chain management (GSCM) practices (specifically, green purchasing, customer cooperation and investment recovery) and firm performance.

Drawing from the theoretical underpinnings of the natural-resource-based view theory and information processing theory, a research model is developed and tested using data obtained from 368 manufacturing firms in Ghana. Data analysis was conducted using structural equation modeling.

The results indicate that green purchasing, customer cooperation and investment recovery have a direct positive and significant effect on firm performance. Additionally, green purchasing and customer cooperation have a positive and significant effect on green absorptive capacity but investment recovery does not. Further, the results show that the paths from green purchasing and customer cooperation to firm performance are positively mediated by green absorptive capacity.

The study reveals to supply chain managers that green absorptive capacity is an important conduit through which firms can achieve enhanced firm performance from GSCM initiatives.

This study makes a contribution by integrating the absorptive capacity literature and green management literature and establishes green absorptive capacity as a mechanism through which GSCM practices enhance firm performance.