Abstract
Purpose This paper aims to explore the changes imposed by the general data protection regulation (GDPR) on software engineering practices. The fundamental objective is to have a perception of the practices and phases that have experienced the greatest changes. Additionally, it aims to identify a set of good practices that can be adopted by software engineering companies. Design/methodology/approach This study uses a qualitative methodology through four case studies involving Portuguese software engineering companies. Two of these companies are small and medium enterprises (SMEs) while the other remaining two are micro-companies. The thematic analysis is adopted to identify patterns in the performed interviews. Findings The findings indicate that significant changes have occurred at all stages of software development. In particular, the initial stages of identifying requirements and modeling processes were the stages that experienced the greatest changes. On the opposite, the technical development phase has not noticeably changed but, nevertheless, it is necessary to look at the importance of training software developers for GDPR rules and practices. Research limitations/implications Two relevant limitations were identified as follows: only four case studies involving micro-companies and SMEs were considered, and only the traditional software development methodology was considered. The use of agile methodologies was not explored in this study and the findings can only be mainly applied to the waterfall model. Originality/value This study offers mainly practical contributions by identifying a set of challenges that are posed to software engineering companies by the implementation of GDPR. Through their knowledge, it is expected to help these companies to better prepare themselves and anticipate the challenges they will necessarily face.

Abstract
This study critically investigates and evaluates the childhood and adolescent year strategies, and efforts that parent-owners of family businesses incorporate to encourage and prepare children for a successful future succession. The sample consisted of six family businesses in the North East of Scotland: two successfully introduced a second-generation, two a third generation and one a fourth generation, with one still in the founder stage. The findings reveal that the succession planning process was an instantaneous event into generational bridging, where no formal planning process was commenced. Parent-owners influenced and facilitated knowledge transfer and education, leaving control to the child successors with career options. The research has also shown the difficulties in how the child successors of the future may find succession challenging and demanding with contextually complex issues. © 2022: Jahangir Wasim, Fernando Almeida.

Abstract
Traditionally, serious games have been used in the development of hard skills, particularly in technical areas such as health, engineering, defence or the environment. However, they can also be applied in the assessment and development of soft skills, which are increasingly key competencies for an individual in the twenty-first century. In this sense, this study proposes the adoption of the FLIGBY serious game in a higher education institution to evaluate and develop students' skills in this field. The findings indicate a large correspondence between the soft skills fundamental to the twenty-first century and the assessment dimensions recorded by the game. Furthermore, the findings reveal that FLIGBY can be used primarily to develop skills in dimensions such as leadership, conflict management, diplomacy and emotional intelligence. These findings are relevant for higher education institutions that intend to include and foster the development of soft skills competencies in their curricula.

Abstract
ABSTRACT This study explores the impact of Green Knowledge Sharing (GKS) on Organizational Performance (OP), considering the mediating roles of Green Organizational Culture (GOC) and Technological Innovation (TI). Addressing current gaps in the literature, the research extends beyond sector-specific analyses and incorporates a cross-country perspective, examining 297 small and medium-sized enterprises (SMEs) in Portugal, Spain, and the United Kingdom. Additionally, this study acknowledges the influence of digital transformation in enhancing GKS, a factor often overlooked in previous research. By adopting a Structural Equation Modeling (SEM) approach, this article confirms a direct and positive effect on both OP and GOC, with GOC further influencing OP, establishing its mediating role in this relationship. However, the relationships between GKS and TI, as well as the indirect effect of GKS on OP through TI, are not supported. These findings offer theoretical advancements by broadening the conventional understanding of OP beyond financial metrics and present practical implications for SME managers, highlighting strategies to foster a green organizational culture and leverage technological innovation for sustainable performance.

Abstract
Social entrepreneurship is crucial for sustainable development as it blends innovative business models with a focus on economic, social and environmental impact. This synergy can potentially accelerate progress towards the sustainable development goals, creating a more equitable and sustainable future. This study aims to explore this phenomenon by carrying out a systematic review of literature. It is adopted the PRISMA framework to identify 54 relevant studies in this field. The findings characterize the evolution of articles in this field, the number of citations, the relationship between key terms, and the respective clusters. Moreover, seven contributions of social entrepreneurship for sustainable development are identified. Finally, the role of technology in promoting and supporting the interconnection between social entrepreneurship and sustainable development is explored. This study is relevant to enhance understanding of how technology supports social entrepreneurship and helps social entrepreneurs to achieve sustainable development goals.

Abstract
PurposeDetecting anomalous access to electronic health records (EHRs) is critical for safeguarding patient privacy and ensuring compliance with healthcare regulations. Traditional anomaly detection methods often struggle in this domain due to extreme class imbalance, limited labelled data and the subtlety of insider threats. This study proposes a lightweight, hybrid anomaly detection framework that integrates unsupervised, supervised and rule-based approaches using a meta-classifier architecture.Design/methodology/approachAn experimental and model-development approach is employed, combining machine learning techniques with domain-inspired rule modelling to construct a hybrid anomaly detection framework for healthcare access logs. Performance of the algorithm is measured using standard classification metrics such as precision, recall, F1-score and accuracy.FindingsEvaluated on a synthetic but realistic dataset of 50.000 normal and 500 labelled anomalous healthcare access events, the proposed framework achieved superior performance compared to standalone models as well as other hybrid models, with an F1-score of 0.8989 and recall of 0.8180. It also maintained low inference latency (0.028 ms) and energy consumption (4.03e-07 kg CO2), making it suitable for deployment in resource-constrained clinical environments.Originality/valueThis study highlights the potential of a hybrid meta-classifier to enhance anomaly detection in healthcare access logs, capturing both subtle and obvious anomalies while outperforming conventional models and remaining efficient, scalable and practical for real-time monitoring.