Paper Number

ICIS2025-2514

Paper Type

Short

Abstract

Donation-based crowdfunding platforms often face uneven funding distribution, where popular campaigns attract disproportionate support, leaving worthy but less visible campaigns underfunded. To address this imbalance, we introduce the novel concept of “contrarian donation”, where donors intentionally support overlooked campaigns. Drawing from Organizational Justice Theory, we propose a theoretical model that investigates how two types of AI transparency—procedural (clarifying how recommendations are made) and outcome (clarifying the purpose behind recommendations)—influence contrarian donation behavior through perceived fairness and psychological ownership. We further suggest that these effects are amplified for humanitarian campaigns, where emotional and moral engagement is higher. To test our hypotheses, we plan a controlled laboratory experiment using a factorial design. This study contributes to IS research by differentiating procedural and outcome transparency, theorizing contrarian donation behavior, and demonstrating how transparent AI recommendations can promote fairness, ownership, and equitable resource allocation in crowdfunding.

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19-SharingEconomy

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Dec 14th, 12:00 AM

Helping the Underdog Campaigns through AI Transparency: A Contrarian Donation Perspective

Donation-based crowdfunding platforms often face uneven funding distribution, where popular campaigns attract disproportionate support, leaving worthy but less visible campaigns underfunded. To address this imbalance, we introduce the novel concept of “contrarian donation”, where donors intentionally support overlooked campaigns. Drawing from Organizational Justice Theory, we propose a theoretical model that investigates how two types of AI transparency—procedural (clarifying how recommendations are made) and outcome (clarifying the purpose behind recommendations)—influence contrarian donation behavior through perceived fairness and psychological ownership. We further suggest that these effects are amplified for humanitarian campaigns, where emotional and moral engagement is higher. To test our hypotheses, we plan a controlled laboratory experiment using a factorial design. This study contributes to IS research by differentiating procedural and outcome transparency, theorizing contrarian donation behavior, and demonstrating how transparent AI recommendations can promote fairness, ownership, and equitable resource allocation in crowdfunding.

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