Engaging Physicians with Introductory Incentives: References to Online and Offline Income

Xiaofei Zhang et al.

MIS Quarterly2025https://doi.org/10.25300/misq/2024/18172article
FT50UTD24AJG 4*ABDC A*
Weight
0.60

Abstract

Incentives make or break user contributions. While providing introductory incentives to attract new users has become increasingly popular among online communities, their impact on user contributions remains largely unknown. Utilizing a policy change that doubled the incentives paid to physicians in a leading online health community, we examined the impacts of both the initiation and the termination of such introductory incentives on physician contributions (in terms of patient consultations) and how the impacts varied according to the physician’s online and offline income. We found that despite an increase in physician contributions during the policy window, the introductory incentives unintentionally decreased physician contributions after the policy window ended. Additionally, physicians tended to anchor their contributions using their online rather than offline income as a reference point, suggesting that mental accounting was at play. Our findings provide a cautionary perspective on the unintended consequences of using introductory incentives and reveal the associated mechanisms of mental accounting when users make contributions (or not) to online communities. These findings provide important implications for incentive design and user engagement in online communities.

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https://doi.org/https://doi.org/10.25300/misq/2024/18172

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@article{xiaofei2025,
  title        = {{Engaging Physicians with Introductory Incentives: References to Online and Offline Income}},
  author       = {Xiaofei Zhang et al.},
  journal      = {MIS Quarterly},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.25300/misq/2024/18172},
}

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Evidence weight

0.60

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.62 × 0.4 = 0.25
M · momentum0.85 × 0.15 = 0.13
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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