Abstract
Scientific research in digital transformation is expanding in scope, quantity, and relevance, bringing forth diverse perspectives on which factors and specific dimensions-such as organizational structure, culture, and technological readiness-affect the success of digital transformation initiatives. Numerous studies have proposed mechanisms to assess an organization's maturity through digital transformation across various models. Some of these models focus on external influences, others on internal factors, or both. Although these assessments provide valuable insights into a company's transformation state, they often lack consistency, and recent research highlights key gaps. Specifically, many models primarily reflect the views of senior management on the general progress of digital transformation rather than on measurable outcomes. Moreover, these models tend to target large enterprises, overlooking small and medium enterprises (SMEs), which are crucial to economic growth yet face unique challenges, such as limited resources and expertise. Our study addresses these gaps by concentrating on SMEs and introducing a novel approach to assessing digital transformation readiness-a metric that reflects how prepared an organization is to optimize transformation outcomes. Following design science research methodology, we develop a model that centers on the perspectives of general employees, offering companies an in-depth view of their readiness across 20 dimensions. Each dimension is evaluated through behaviors indicative of the highest level of digital transformation readiness, helping companies identify areas to maximize potential benefits. Our model focuses not on technological quality but on the degree to which behaviors essential for leveraging technology and innovative business models are integrated within the organization.

Abstract
Although implementing technologies is a continuous practice observed in organisations, many need help to achieve successful implementations and recognise its impact on their operations and outcomes. Therefore, this review paper aims to present the critical success factors that organisations consider when implementing technology in the Talent Management field. A comprehensive understanding of the technological implementation phenomenon requires adopting a strategic perspective. Consequently, this literature review centres on three clusters: challenges organisations are addressing (Challenges), the technological capabilities and the implementation/adoption process (Technology) and the expected impact (Impact). Findings indicate that a central area of research is the integration of technology in recruitment and, particularly, in the context of Small and Medium Enterprises. Digital Transformation, the Industrial Revolution, and a more diverse workforce are challenges that organisations face. Organisations aim to streamline Human Resources Management (HRM) practices, prioritising data-driven decisions. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Abstract
With the advent of Information and Communication Technologies in recent decades, organizations face several challenges today. Adopting Digital Transformation (DT) offers numerous opportunities for Small and Medium Enterprises (SMEs) to improve their efficiency and operations, reaching new markets, shareholders, and customers. However, there are potential risks associated with this process. With Digital Transformation, the radius of connectivity and interconnection between devices and systems increases in Mozambique and worldwide, creating more significant space cyberattacks. As Small and Medium-sized Enterprises (SMEs) connect to the digital world and move forward with adopting innovative digital technologies, they become more vulnerable to digital security risks. Hence, managing digital security risks effectively is crucial to realising the benefits of Digital Transformation. This position paper proposes to present the research work that will culminate in the proposal to develop a framework that fits Mozambican Small and Medium Enterprises through a Design Science Research (DSR) methodology, which can help to assist Mozambican Small and Medium Enterprises in the Digital Transformation (DT) process.

Abstract
This chapter examines how Artificial Intelligence (AI) and Learning Analytics (LA) are transforming distance education, accelerated by the COVID-19 shift to e-learning. By using data from Learning Management Systems (LMS), these technologies can personalize learning, improve student retention, and automate tasks. AI, particularly machine learning, enables dynamic adaptation to student needs, while LA provides valuable insights for informed instructional decisions. However, ethical concerns, including data privacy and algorithmic bias, must be addressed to ensure equitable access and fair learning outcomes. The future of distance learning lies in responsible integration of AI and LA, creating immersive and inclusive educational experiences.

Abstract