Work

Incentive Strategies in Security Crowdsourced Testing Platforms Under White Hat Preferences

Year: 2026

Type: article

Abstract: Platforms often fail to incorporate the needs of white hats who prefer non-material incentives when designing reward schemes. To study incentive design under private preference information, this paper develops a dynamic game with incomplete information and examines how appointing communications specialists can facilitate truthful preference disclosure and improve the platform’s incentive strategy. The results indicate that the platform’s decision depends on the white hats’ net utility from participation, white hats’ reputational losses, and the platform’s prior probability that white hats participate. When the platform appoints communications specialists, white hats disclose their preference information truthfully once their net utility from participation exceeds a threshold. Under this condition, the platform can identify their preference types and match incentive types to white hats’ preferences. Under misaligned signaling, where white hats use material (non-material) incentives to signal non-material (material) preferences, the platform has no incentive to appoint communications specialists.

Source: Mathematics

DOI: 10.3390/math14061005

Authors: Liurong Zhao, Qiongyao Wang, Xinyi Zhu

Institution: Nanjing Tech University

Language: English

Topic: Game Theory and Applications

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDG: Peace, justice, and strong institutions

Open Access status: gold

Estimated APC paid: $3,137