Trust and fairness in platform–supplier contracts: Navigating supplier concerns in the sharing economy
Ying Yin & Xishu Li
Abstract
Trust and fairness are critical to the sustainable development of the sharing economy, particularly in platform–supplier relationships, where numerous individual suppliers offer access to their durable assets without transferring ownership. Motivated by the real‐world phenomenon of personalized wages and informed through direct interactions with relevant constituents, this study examines a contracting problem between a share‐based platform and its supplier, where the platform designs contracts that differ in information‐sharing and revenue‐sharing structures. The supplier evaluates these contracts based on their expected utility, incorporating trust in the information shared and fairness concerns over revenue sharing. In addition to trust and fairness, we incorporate deception cost for both parties: for the platform, they operationalize trustworthiness as a reluctance to misrepresent information, while for the supplier, they constrain opportunism such as underreporting revenue. Using a game‐theoretical model, we derive the optimal contracting mechanism under different conditions. Our results reveal that trustworthiness, rather than trust alone, shapes optimal contracting outcomes. Under platform‐managed contracts, the revenue‐sharing ratio increases with either trust or fairness—but not both simultaneously. For supplier‐managed contracts, dishonesty leads to a vicious cycle between commission fees and underreporting and the supplier who seeks to be treated fairly will cheat more, resembling fairness‐driven supplier opportunism. Our findings offer actionable insights for platforms in designing contracts that consider suppliers' trust and fairness, ensure compliance, and mitigate opportunism, contributing to sustainable and ethical supplier relationships.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.