Mixed-methods analysis of supply chain dynamics in university markets reveals critical supplier relationships and improvement potential.
Goal: This study aims to model and analyze the supplier network of a university retail market to enhance supply chain efficiency, optimize supplier relationships, and improve service delivery to internal and external stakeholders. This study fills a gap in the literature by addressing the still underexplored context of supply chains in university markets, contributing new insights into the efficient management of supplier relationships and the provision of public services in academic environments.Design / Methodology / Approach: The research employed a mixed-methods approach, integrating qualitative data from semi-structured interviews and document analysis with quantitative metrics derived from Social Network Analysis (SNA). UCINET software was used to calculate centrality, cohesion, and network density indicators. The network structure was analyzed based on a case study at the State University of Maringá (UEM), involving internal and third-party suppliers.Results: The results reveal that the Focal Company (EF) occupies a central but vulnerable position, with high degree and betweenness centrality. Key suppliers, such as F12, show strong ties, while peripheral actors, like F3 and F4, exhibit weak and sparse connections. The network displays moderate density, suggesting potential for strengthening weak ties and diversifying sources. Identified challenges include supply irregularity, overdependence on specific nodes, and inefficiencies in logistics and inventory management.Limitations of the investigation: The study is limited by its single-case design, which may constrain the generalizability of the findings. Additionally, the use of self-reported data may introduce subjectivity.Practical implications: The findings support actionable recommendations, such as enhancing collaboration with peripheral suppliers, adopting AI-based forecasting tools, and expanding storage and transport capacity, contributing to greater supply chain resilience and service efficiency.Originality / Value: This research offers an innovative application of SNA in a university retail context, providing a replicable framework for analyzing and improving supplier interactions and supply chain performance.
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Costa et al. (2025) studied this question.
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