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RESEARCH

Publications

[1] “The crowd beyond funders – An integrative review of and research agenda for crowdfunding”

with Vivianna He (St. Gallen) and Alex Murray (U of Oregon) - Academy of Management Annals, 2024, Vol. 18, No. 1, 348–394. https://doi.org/10.5465/annals.2022.0064.

 

Abstract: Crowdfunding, or soliciting small contributions from large and dispersed crowds through online platforms, is an increasingly indispensable strategy for established firms, young ventures, and aspiring entrepreneurs alike. Synthesizing research in the fields of management, entrepreneurship, innovation, operations, information systems, and marketing, we conduct an integrative review of the crowdfunding research accumulated over the past decade. We aim to break down disciplinary silos to develop a framework that integrates insights across research communities. We identify three underlying dimensions that differentiate extant research: the goal of the campaigner, the role of the crowd, and the boundary of the crowdfunding event. Scholars have brought two perspectives to bear on these questions: an elemental perspective and a processual perspective. We outline an integrative model that takes account of crowdfunding as a process involving heterogeneous participants with idiosyncratic monetary and non-monetary goals at different stages. Our multidisciplinary review of this expanding body of literature not only integrates dispersed insights but also, more importantly, stimulates a future research agenda that goes beyond the traditional boundaries of crowdfunding research.

Working Papers

[2] “Harnessing the Crowd: How ventures bounce back from failure”

with Sen Chai (McGill) – Preparing for submission

nominated: AoM 2023 Best PhD Paper Finalist, TIM Division

 

Abstract: We examine how ventures harness the crowd to “bounce back” from initial failure. Using archival data from 23 cases of entrepreneurial reentry, we unpack venture-crowd exchanges during and after failure and observe how ventures react and adapt for reentry. Our sample consists of ventures pitched in the same entrepreneurial space with similar project quality and failure experience, with only some succeeding in their second attempt and others failing again. We induce a crowd control framework comprised of anticipating, bridging, and stabilizing practices that ventures perform in a bidirectional sequenced exchange with the crowd. Departing from extant literature, which assumes a discrete event with clear temporal structures and unambiguous information flowing from crowds to ventures, we show that “bouncing back” from failure is a continuous process that may already have been nurtured before the dichotomous failure occurs. By unpacking how ventures harness crowds despite initial failure, we contribute to the literature on entrepreneurial resource mobilization and non-financial support provided by crowds.

[3] “Crowd Consensus: Evidence from large-scale group experiments”

with Vivianna He (St. Gallen) and Phanish Puranam (INSEAD) - First manuscript draft

nominated: SMS 2024 Best Conference Paper

nominated: SMS 2024 Best PhD Paper 

Abstract: Coordinating crowds to jointly solve problems is challenging. While participation increases the likelihood of diverse input and novel solutions, social interactions tend to amplify the emergence of differing viewpoints, typically hindering crowd consensus. When solution seekers, such as online community managers, resort to authority to break the deliberation deadlock, they undermine the principle of open participation—the very principle that attracts crowd participants in the first place. How to navigate the dilemma between high-quality deliberation (and, in turn, solutions) and consensus? We explore a minimally invasive and scalable intervention that assists the crowd in decomposing problems into their underlying dimensions. In two large-scale online experiments, we find that deliberation quality and in turn, solution quality, on a divisive topic can be significantly enhanced using this approach, without impinging on the consensus process. Our study thus provides initial empirical evidence for resolving the critical trade-off between crowd deliberation and consensus.

Research In Progress

[4] “Generative AI and scientific work”

with Sen Chai (McGill) and Anil Doshi (UCL) - Data analysis

[5] “Crowd feedback and aspiration levels”

with Jiongni Mao (Bocconi) – Ideation stage

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