Extending the Resource-Based View of Social Entrepreneurship: The Role of Artificial Intelligence in Scaling Impact

Abstract

This paper extends the resource-based view (RBV) of social entrepreneurship by introducing artificial intelligence (AI) as a dynamic, integrative capability that enhances the acquisition and optimization of four foundational forms of capital: human, social, political, and financial. While social ventures have long faced constraints in scaling impact due to resource limitations and institutional barriers, AI technologies—such as predictive analytics, machine learning, and natural language processing—offer new pathways for improving operational efficiency, stakeholder engagement, advocacy strategies, and financial sustainability. Through the development of a conceptual model and a series of theoretical propositions, this study positions AI as a transformative force that not only strengthens individual resource domains but also enables synergistic feedback loops across them. In doing so, the paper contributes to emerging debates on technology adoption in hybrid organizations, scalability in resource-constrained contexts, and the evolution of strategic management theory in the digital age. Practical implications are outlined for social entrepreneurs, policymakers, and funders seeking to responsibly integrate AI into social impact ecosystems, and future research directions are proposed to empirically test the framework across sectors and global settings.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 8 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.