Social Network Analysis of an AI-Powered Recycling Startup: Insights from CIRSYS in the Peruvian Innovation Ecosystem

This study examines the social network structure of CIRSYS S.A.C., a Peruvian startup that develops artificial intelligence-based technologies for recycling, with the objective of understanding its position within the national innovation ecosystem. Using egocentric social network analysis applied to publicly available LinkedIn data, the research quantifies key structural metrics-including degree centrality, betweenness, network density, and clustering-and identifies subnetwork configurations across academic and business domains. The results indicate a highly cohesive educational network characterized by small-world properties and the presence of central student actors, but limited connectivity to executives, institutions, and commercial stakeholders. The analysis reveals underutilized brokerage potential, particularly among faculty actors, and a lack of crosssector integration that may constrain innovation diffusion and partnership formation. The study contributes to the literature on innovation networks in emerging economies by highlighting the relevance of actor-level positioning in early-stage ventures and offering practical guidance for strengthening strategic communication and stakeholder engagement. Recommendations are provided to improve institutional linkages and expand outreach to underrepresented segments of the ecosystem. Future research directions include longitudinal network analysis, comparative studies across Latin American startups, and integration of network data with innovation performance indicators.