Abstract
PurposeThis study explores the role of ports in achieving the United Nations Sustainable Development Goals (SDGs), focusing on the interconnection between key SDGs. It aims to characterize how port sustainability initiatives address multiple SDGs to increase their impact.Design/methodology/approachIt examines through mixed methods research how ports align their development projects with these SDGs, analyzing the policy implications of integrating economic, environmental, and social objectives. It considers 401 projects from the World Ports Sustainability Program (WPSP).FindingsThe findings indicate the most achieved SDGs and reveal six common themes that ports follow to address multiple SDGs. These characteristics include environmental sustainability, energy transition, social inclusion, digitalization, governance and ethical practices, and innovation and collaboration.Originality/valueThis study brings original contributions on the SDGs addressed by ports, considering not only the individual SDGs addressed by the sustainability initiatives promoted by ports, but also the joint effects of addressing multiple SDGs. This study also emphasizes the need for supporting these initiatives in international collaboration, green technologies, and climate resilience.

Abstract
This study investigates metropolitan-level initiatives in the Porto Metropolitan Area, located in northern Portugal, aimed at fostering healthy and sustainable communities. It maps 41 ongoing municipal projects and analyzes their key thematic areas. In addition to identifying focus areas, the study explores the governance models behind these initiatives, with particular attention to citizen participation and intersectoral coordination. It also examines how local authorities mobilize resources and implement policies, while assessing the integration of Sustainable Development Goals 3 and 11 (SDGs 3 and 11). Employing a qualitative approach through a thematic analysis, and using a comparative framework analysis, this study identifies strong thematic convergence around civic participation, social inclusion, well-being, and environmental sustainability. These elements emerge as key pillars of sustainable development, supporting systemic action across all levels. Citizen participation proves to be a strategic governance tool, requiring structured mechanisms like participatory budgeting. The study also highlights the role of stakeholders, especially schools and companies, in scaling good practices and stresses inclusive policies to reach vulnerable groups. It concludes by advocating for collaborative local governance capable of effectively coordinating diverse actors and promoting equitable, sustainable outcomes.

Abstract
Purpose - The objective of this study is to integrate various theories of identity within entrepreneurship and derive insights and propositions that enhance the understanding of how an incubation program influences the formation and development of entrepreneurial team identity. Design/methodology/approach - This study adopts a qualitative multiple case study design to explore how entrepreneurial team identity develops within ventures incubated at CEU iLab. The analysis is based primarily on interviews with individual entrepreneurs from five selected ventures, complemented by secondary data to enrich and contextualize the findings. Findings - The findings revealed the interconnections between entrepreneurial team formation processes, social interactions, networking, entrepreneurial team stability, feedback mechanisms, team dynamics and intrateam trust and legitimacy. Moreover, the cultivation of a culture defined by trust, open communication and the active integration of feedback mechanisms played a pivotal role in the creation of collaborative team environments. Furthermore, the process of building an entrepreneurial team is heavily reliant on shared vision, common values, complementary skill sets, intrateam trust and pre-existing relationships. Originality/value - This study addresses a notable gap in the existing literature by studying how entrepreneurial teams and individual entrepreneurial team members manage to form and develop their entrepreneurial identity. By focusing on the dynamic processes behind identity formation within teams, this research provides novel insights into the motivations that drive individuals and teams to engage in entrepreneurial activities. This focus on the interplay between identity and team processes represents a distinctive and timely addition to the field.

Abstract
This study aims to explore the impact of seven dimensions of local communities’ involvement in the context of the sustainable open innovation paradigm on entrepreneurial performance considering a tri-dimensional perspective comprising turnover, innovation capacity (IC), and employability. A quantitative methodology was adopted, applying correlational analysis and hypothesis testing to a total of 296 new ventures based in European science parks. The findings indicate that only the entrepreneurial capacity of new ventures has improved, but not turnover and employment. Also, only years of experience in open innovation networks contribute to increasing the performance of entrepreneurs in their IC, but age and gender are not significant factors. This study broadens the scope of sustainable open innovation by positioning local communities as central actors rather than peripheral stakeholders. It enriches key theoretical frameworks such as Sustainable Development Goals (SDGs) and social capital theory by emphasizing community-driven innovation. Practically, it offers actionable strategies for engaging communities and guiding policymakers toward inclusive innovation policies, thereby contributing to both academic discourse and real-world impact in sustainability and innovation ecosystems.

Abstract
Purpose: This study aims to present an innovative sandbox platform that implements a decision support system (DSS) to assess the sustainable development goals (SDGs) addressed at the municipal level. It intends to determine the relative importance of each SDG in municipalities and explore the synergies that can be discovered among them. Design/methodology/approach: Participatory action research is used to develop a DSS and an algorithm designated as discrete heavy fuzzy was also developed, which extends the Apriori algorithm to include discrete quantitative assessments of the level of SDG compliance by each project. A scenario consisting of three municipalities in Portugal (i.e. Porto, Loulé and Castelo de Vide) was chosen to demonstrate the implementation of the sandbox platform and to interpret the observed results. Findings: The results reveal significant differences in the typology of SDGs addressed by each municipality. It was found that municipal sustainable projects are strongly influenced by the contextual factors of each municipality. Porto has projects that address the first five SDGs. Loulé appears projects that promote innovation, the fight against climate change and the development of sustainable cities. Castelo de Vida has initiatives related to innovation and infrastructure and decent work and economic growth. Research limitations/implications: This study provides knowledge about the relative importance of the SDGs in Portuguese municipalities and explores the synergies among them. The proposed sandbox platform fills the gaps of the ODSlocal Webtool by proposing a dynamic and interactive approach for the exploration of quantitative indicators regarding the implementation status of the SDGs established in the 2030 Agenda. Originality/value: This study provides knowledge about the relative importance of the SDGs and the various synergies that exist between them considering the Portuguese municipalities. The sandbox platform presented and developed within this study allows filling the gaps of the ODSlocal Webtool that gathers essentially qualitative information about each project and offers a dynamic and interactive exploration with quantitative indicators of the implementation status of the SDGs established in the 2030 Agenda.

Abstract
Purpose Detecting 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/approach An 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. Findings Evaluated 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/value This 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.