This study analyzes social capital as a mediator/moderator of social value creation in social entrepreneurship (SE); thus, we adopted a mixed methods review that was performed in two stages. In the first stage, we overviewed the reviews in order to summarize key findings from the analysis of social entrepreneurship. At this stage, the aim was to show the gap in the existing research, with an explicit focus on impact generation and measuring that impact within social enterprises. Then, we conducted a literature review focusing on studies that analyse the relationship between social entrepreneurship and social capital. Our assumption is that social capital is an impact generation mechanism that works at different interaction levels. Our analysis identifies three pathways which show how social entrepreneurship can have an impact, and how it can be generated by higher levels of social capital. These three pathways involve productivity, community resilience, and institutional development. The proposed classification of the empirically identified SE impact pathways offers insights that are useful to informing the available approaches concerning social impact creation and methods which approximate tangible SE outcomes. In addition, the mediator/moderator approach to social capital identifies these pathways as being complementary value creation processes.

The increasing complexity and globalization of agrifood supply chains (AFSCs) issue significant challenges to ensuring food safety and quality. These risks, ranging from microbial contamination and chemical hazards to traceability failures and food fraud, need innovative and scalable risk management strategies. This systematic literature review synthesizes findings from 164 peer-reviewed articles published between 2011 and 2023, investigating the role of Industry 4.0 (I4.0) technologies in managing food safety and quality risks across the AFSC. Technologies analyzed include artificial intelligence (AI), machine learning (ML), Blockchain (BC), Internet of Things (IoT), big data (BD), digital twins (DT), robotics, and more. Findings reveal that I4.0 technologies enhance real-time monitoring, predictive analytics, traceability, and process automation, leading to reduced contamination risks, operational efficiency, and improved stakeholder trust. AI and big data support early hazard detection and decision-making and blockchain and IoT improve traceability and transparency, while digital twins simulate disruptions and optimize safety–critical operations. Despite the benefits demonstrated, key barriers exist, including high implementation costs, data interoperability issues, and limited digital literacy among small and medium-sized enterprises. The review highlights the need for integrated, sector-specific applications, regulatory adaptation, and interdisciplinary collaboration to overcome these obstacles. Future research should focus on scalable, secure, and sustainable solutions, particularly those that empower stakeholders and enhance supply chain resilience. This study provides a comprehensive overview of digital transformation trends in food safety, offering actionable insights for industry practitioners, researchers, and policymakers aiming to foster safer and more transparent agrifood systems.

The aim of the present study is to analyze social capital as a spatial resource that regions might use differently in their developmental process. We propose a theoretical framework in order to identify the different regional social capital workings as leading to either an open system of relations (the virtuous social capital—development spiral) or to a rather closed system of relations (the vicious social capital—development cycle). At the empirical level, we test the presence of these two developmental paths by two operational hypotheses that are tested through the development and use of appropriate entropy technique for order of preference by similarity to ideal solution (TOPSIS) techniques. Our analysis involves an inclusive theorization of social capital as composed of trust, norms/values, and networks. Using individual and aggregate level economic indicators, we obtain different rankings of the Greek regions compared to the initial entropy weights rankings. Overall, our results provide support to the presence of both developmental paths in the case of Greece while the Greek regions might be categorized as dynamic, stagnant, and unstable.