This study investigates factors influencing the efficiency of prosocial crowdlending, with a specific focus on campaign duration. We conduct multiple linear regression (MLR) analyses to identify trends and significant factors across two distinct periods: 2017–2019 and the Covid-19 pandemic. During 2017–2019 (Regression 1), our analysis reveals that campaigns with more hashtags, longer monthly repayment terms, individual borrowers, and a focus on the agriculture sector generally last longer. Conversely, shorter campaign durations are associated with detailed descriptions, borrowers from high human development index (HDI) countries, English-language campaigns, and those led by females. In contrast, Regression 2, which examines the Covid-19 period, shows that only longer descriptions and female-led campaigns correlate with shorter durations, reflecting the impact of external crises on crowdfunding dynamics. To further explore these findings, we suggest using Multi-objective Programming (MOP) and Goal Programming (GP) models. Insights from the regression analysis can inform the formulation of objectives and constraints for these models, helping to define specific goals such as maximizing the use of detailed descriptions and female-led campaigns while balancing other campaign needs. This integrated approach highlights the complex interplay between persistent patterns and external forces, including global crises, providing new insights into the factors that drive crowdlending success. Future research could further investigate evolving dynamics and explore how crowdfunding platforms can adapt to achieve optimal outcomes across various contexts.

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Poverty,Microcredit,Multiple linear regression (MLR),Multi-objective and goal programming (MOP/GP),Prosocial crowdfunding,Campaigns’ duration,Sustainable development goals (SDGs)

• Economia e Gestão - Ciências Sociais