学术讲座| 市场营销学系讲座 (2026-04-17)

Abstract

Intermediary agents such as microfinance institutions (MFIs) are essential in global microfinance as they provide value to end-users (i.e., borrowers). However, many MFIs suffer from funding issues and potential mission drift - the tendency to prioritize financial performance over social outreach. Despite the promise of crowdfunding as an alternative and sustainable funding source in recent years, the value of crowdfunding to MFIs and the impact on mission drift are unclear.

In this study, we investigate these two concerns in the context of when the leading crowdfunding platform Kiva is engaged as a funding partner for MFIs. Theoretically, we draw on the framework of institutional logic and specify crowdfunding’s two legitimacy criteria - a pragmatic criterion (driven by self-interest) and a moral criterion (driven by moral norms), that guide crowdfunding platforms’ backers’ decision-making. We utilize a weakly-supervised learning technique to operationalize the legitimacy criteria from MFIs' loan descriptions. We then provide testable predictions on how these two criteria might influence MFIs' operational focus and affect MFIs' three critical operating outcomes - scale, financial performance, and social outreach.

We test these predictions using global longitudinal datasets sourced from Kiva and Microfinance Information Exchange. Results show that crowdfunding partnerships can improve MFIs’ scale and financial performance and that the improved financial performance is mediated by operational efficiency. More importantly, our analyses show that crowdfunding partnership has improved resistance to mission drift in general, and such effect is most prominent for MFIs who can balance financial performance and social outreach well and for MFIs of medium maturity. This research provides nuanced results for the value of crowdfunding in microfinance for economic development.

Introduction

Jonathan Z. Zhang is the Dr. Ajay Menon Professor in Business and Associate Professor of Marketing at Colorado State University, and an affiliate of the CSU Data Science Research Institute. He holds a Ph.D. in Quantitative Marketing from Columbia University and dual degrees in Economics and Mathematical Statistics from Rutgers University. His research uses econometric and machine learning methods to study customer behavior, pricing, and growth strategies across B2B and B2C contexts, with a focus on how firms leverage data and technology to acquire, retain, and develop customer relationships.

His work also examines the intersection of marketing, technology, and organizations, particularly the responsible deployment of emerging technologies and new business models. Zhang’s research has been published in leading journals such as Marketing Science, Management Science, Journal of Marketing, Journal of the Academy of Marketing Science, Quantitative Marketing and Economics, and Journal of Consumer Psychology, as well as practitioner outlets including Harvard Business Review, MIT Sloan Management Review, and California Management Review. He currently serves as Associate Editor at Journal of Marketing and Journal of the Academy of Marketing Science, and is on the editorial board of Journal of Marketing Research and Journal of Retailing. His work has been recognized by the academic community with awards including MSI Scholar (2024) and the Louis W. Stern Award.