Match Frictions and Engagement: Two-sided Matching for Digital Business Mentoring in Emerging Markets
(A2026-134184)

AUTHORS

Soniya Gupta-Rawal, University of Cambridge/Judge Business School, University of Cambridge; Ahmed Khwaja, University of Cambridge Judge Business School; Jaideep Prabhu, University of Cambridge

ABSTRACT

Digital mentoring platforms expand entrepreneurs’ access to advice and networks, but it remains unclear who matches with whom and why some matches deepen while others stall. This paper analyses entrepreneur–mentor interactions on a global mentoring platform in emerging markets, treated as a two-sided market for business knowledge. Using profile data and multilingual conversation text, we construct an engagement index that captures the quantity and quality of interactions. A two-stage econometric framework separates the drivers of reply at first contact from those of sustained engagement, using opener-time match frictions and a control-function residual to address selection. Results show that communication and capacity frictions primarily determine who receives a reply, whereas venture-type alignment and venture maturity predict which pairs build deeper relationships. The study shows how marketing analytics can inform matching rules, platform design, and user engagement.