Avoiding the Diffusion of Responsibility in Social Networking Groups: A Field Experiment on Responses to Online Help-Request Referrals
Feng, Nan, Hu, Zhongtao, Wu, Yi, Choi, Ben
Journal of the Association for Information Systems · 2023 · Volume 24 · Issue 2
Abstract
Help-request referral (HRR) campaigns are being increasingly adopted by online service providers to attract online traffic and engage new users. In these campaigns, participants are required to collect a specific amount of help from their social network in exchange for attractive rewards. Participants often face challenges in obtaining positive feedback from their social networking groups due to the diffusion of responsibility. Based on the triangle model of responsibility, this study proposes and empirically tests a research model that examines two key determinants (i.e., request personalization and relational closeness) of recipients’ perceived responsibility that further shape their responses to HRR. Our field experiment empirically supports the research hypotheses. Overall, this study enriches the literature on online social referrals by focusing on HRR, where social referrals are broadcasted and senders reap referral benefits. The study also provides practical insights for HRR designers and social networking service providers.
Keywords
Help-Request Referral Campaign, Triangle Model of Responsibility, Request Personalization, Relational Closeness, Perceived Responsibility, Helping, Endorsing
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