Abstract
Sustainable development is crucial to ports due to the interconnection between port activities, the economy, and the environment. This study aims to explore how port digitalization initiatives played the role of promoting sustainable development. To this purpose, the author/authors adopted a mixed methods approach using as database the World Ports Sustainability Program, which features 74 port digitalization initiatives. The first step focused on a quantitative analysis of the distribution of said initiatives in terms of sustainable development goals, followed by a thematic analysis to explore their contribution. The findings indicate that more than 72% of ports addressed sustainable development goals 8, 9, 13, and 17. Digitalization initiatives in ports have mainly focused on improving their infrastructure and operational performance, enabling them to address climate change challenges. This work also recognized the role that partnerships can play in achieving this goal.

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This paper analyses the process of generalisation of an innovative government-led public practice in the healthcare sector. The scaling and embedding involved in this generalisation process are assumed to be dependent on the multiple implementation processes (consecutive or simultaneous) that lead to a routine use of the innovation in different adopters. This paper, therefore, proposes the use of a configurational theory approach to conceptualise each implementation of the innovation during the generalisation process and shed light on the generalisation's scaling and embedding efforts. It suggests a set of recommendations and practices for generalisation managers, most notably: i) they should regard generalisations as organic processes where their main role is to create space for experimentation, learning and negotiation, and ii) they should adopt different modes of governance to identify adequate mechanisms and strategies and guide their actions. This configurational perspective allows them to monitor and manage the evolution of implementations, informs the valuable learning processes that take place in a generalisation and has been found to be a useful tool to support the crucial collaboration among the actors involved in a generalisation.

Abstract
Artificial intelligence (AI) has gained significant evolution in recent years that, if properly harnessed, may meet or exceed expectations in a wide range of application fields. However, because Machine Learning (ML) models have a black-box structure, end users frequently seek explanations for the predictions made by these learning models. Through tools, approaches, and algorithms, Explainable Artificial Intelligence (XAI) gives descriptions of black-box models to better understand the models’ behaviour and underlying decision-making mechanisms. The AI development in companies enables them to participate in Industry 4.0. The need to inform users of transparent algorithms has given rise to the research field of XAI. This paper provides a brief overview and introduction to the subject of XAI while highlighting why this topic is generating more and more attention in many sectors, such as industry. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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[No abstract available]

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This study aims to explore how higher education institutions respond to the challenge of incorporating soft skills into their curricula. It employs a mixed-methods approach in which the quantitative analysis of the disciplines addressing this issue is complemented by a thematic analysis of semi-structured interviews conducted with four higher education institutions in Portugal. The findings indicate that although the number of subjects specifically addressing soft skills is small, there is a growing concern to incorporate soft skills in pedagogical and evaluation methodologies in each course. Several challenges, good practices, and future perspectives are also explored in this work.