Abstract
Digital transformation is critical for the competitiveness of SMEs. Digital Innovation Hubs (DIHs) aim to regionally support companies in the development of new products, processes, or services, providing access to advanced technologies. Since DIHs have to be financially sustainable, it is important to discuss which business models are put forward in such complex arrangements. Our main goal is to analyse how DIHs, specialized in Industry 4.0 technologies and services, create, offer, and capture value. The research was conducted through a documentary analysis of reports about DIHs' Business Models, generated by three European initiatives (encompassing more than 300 DIHs). Results demonstrate that one Business Model does not fit all, since regional characteristics, which vary among differentDIH's, are themain drivers to define value creation, offer and capture. This work aims to provide DIH managers insights to help them develop sustainability strategies.

Abstract
Innovation is one of the key aspects that drive economic growth and social welfare, one of the ways that it occurs is through technology transfer. However, using a patent to innovate through technology transfer is a complex process, full of uncertainties, and there is not a well-defined process available that enables entrepreneurs to develop business models based on patents. Therefore, this study aims to develop a methodology to support entrepreneurs in the development of businesses from patents available in technology transfer programs. The P2B methodology was developed within two research steps. Firstly, based on a structured literature review and on the case study analysis of the European Space Agency Business Incubation Center (ESA BIC), an initial conceptualization of the methodology was developed. Secondly, data was collected throughout thirteen semi-structured interviews with experts in technology transfer and management, innovation, and business model development to create the final proposed P2B methodology. The P2B methodology addresses the inherent challenges of the innovative business development process, specific to the technology transfer context, by providing a set of twenty-three activities, supported by sixteen tools, divided into four major phases: technology analysis, value analysis, business model, and business plan.

Abstract
Circular Economy is based on implementation of R-strategies to narrow or close the loop of material flows and to minimize raw material consumption by extending the life cycle of materials. Since this approach is expanding from individual organizational actions to a collaborative approach, the objective of this paper is to analyse the role of digital technologies such as AI and cloud platforms in facilitating and changing the collaboration between stakeholders to improve sustainability. This study adopts a qualitative multi case study methodology, using surveys, interviews and document analysis from 10 new ventures in the agri-food ecosystem supported by the cascade funding programme. The results show that collaboration among actors is changed by the different technologies and strategic drivers of circular economy in the considered ecosystem.

Abstract
This study investigates the antifragility of organizations, especially in strategic sectors highly exposed to disruptive events. Based on a qualitative approach with case studies in the wine and textile sectors in Portugal, the findings indicate that financial and market strength, as resilience capabilities, operate interdependently and are reinforced by digital maturity and supply chain integration. Companies with financial robustness and strong market intelligence tend to be more agile in strategically investing and reallocating resources during crises. The research adopts an expanded definition of antifragility, which incorporates resilience, innovation, and strategic reconfiguration in the face of disruptions. It concludes that organizational antifragility results from the articulation of financial resources, market intelligence, and digital collaboration, offering a sustainable competitive advantage in the face of uncertainty. The study contributes to theoretical debates and provides practical recommendations for managers and policymakers.

Abstract
The Circular Economy, an alternative to the linear make-use-dispose system, promotes sustainable development through novel business models. Thus, Circular Business Models emerge as systems that minimize resource input and waste by slowing, closing, and narrowing material and energy loops. Circular Startups play a crucial role in the transition to a Circular Economy. Despite their significance, there is a research gap in how these companies scale. Moreover, the slow transition is attributed to the limited scalability of Circular Business Models, which leads to the need to scale current practices. The present study aims to fill this gap by defining a typology of scalability strategies employed by circular startups. A qualitative case studies methodology is adopted, using document analysis and semi-structured interviews conducted in the context of the European project SoTecIn Factory. This research identifies five scalability strategies used by Circular Startups-impact, commercial, ecosystem, institutional and cultural-with the commercial strategy being the main focus in terms of growth approach. The findings underline a strong commitment across the observed value chains to minimize environmental impact, enhance social welfare, and foster economic growth. Other key findings reveal the presence of R-imperatives across different value chains, leading to industry-specific approaches. In addition to the theoretical contribution, this research can support sustainable growth by practitioners in their scaling efforts, thus, accelerating the circular transformation. © 2025 The Authors.

Abstract
The integration of AI in supply chains offers opportunities to enhance efficiency, sustainability, and decision-making. However, effective implementation requires attention to both technical and socio-technical aspects. This study examines AI maturity in the pulp and paper sector using the SC-STAI profiling tool, assessing AI integration across technical, social, human, and organizational domains. Based on nine case studies from Brazil and Portugal, the research identifies key areas for improvement and highlights uneven AI adoption. Findings show that performance and resilience are most impacted, while job role adoption remains the lowest. The study emphasizes the importance of Socio-Technical AI Maturity Models in guiding responsible AI adoption and improving socio-technical alignment in supply chains, contributing to a better understanding of AI readiness in traditional industries and demonstrating the SC-STAI tool's applicability for strategic AI planning.