Data-Driven Ecosystem Business Models in Agriculture with Focus on Sustainability: A Systematic Literature Review

Digital transformation is reshaping agriculture through data-driven business models leveraging emerging technologies. Understanding these models' sustainability contributions is crucial given agriculture's challenges with climate change, resource constraints, and food security. Following PRISMA, Scopus and Web of Science were searched, yielding 1538 articles. After screenings, 80 papers were analyzed thematically. 32 distinct data-driven ecosystem business models were identified, categorized into three primary groups: Technology-Focused Models, Value Chain Integration Models, and Data & Governance Models. These models contribute to economic sustainability through resource optimization and new revenue streams; environmental sustainability through precision management and emissions reduction; and social sustainability through knowledge sharing and community development. Implementation challenges include technical integration, organizational adoption barriers, data governance concerns, and policy gaps. These models show significant potential for enhancing agricultural sustainability. Trust emerges as fundamental for implementation, while power dynamics remain critical concerns. Future research should focus on governance frameworks, user-centric design, and impact assessment.