数字租赁市场中的平台稳定性与契约风险：产权结构与收益可预期性的制度作用

Abstract

With the rapid development of the digital economy, platform-based industries have become key drivers of structural transformation and innovation. As a representative form of the platform economy, the ride-hailing sector has reshaped the traditional supply–demand structure of urban transportation and stimulated employment and consumption growth. Meanwhile, financial leasing has emerged as the dominant mechanism for drivers to acquire operating vehicles, lowering entry barriers and accelerating fleet expansion. Yet, at the intersection of platform operation and financial leasing, new contractual and credit risks have arisen. The tripartite relationship among platforms, drivers, and leasing companies is marked by information asymmetry, blurred boundaries, and misaligned incentives. Frequent adjustments in platform policies—such as subsidies, commission rates, and order-allocation algorithms—induce income volatility and weaken contractual compliance, leading to strategic default and moral hazard. Traditional credit risk frameworks focusing on borrower attributes and financial constraints fail to capture these institutionally driven risks. This study thus aims to reveal how the institutional characteristics of digital platforms shape contractual incentives and default behavior in platform-based financial leasing.
Using large-scale operational data from a leading financial leasing firm in the ride-hailing industry, this paper examines how platform stability and ownership structure jointly affect lessee default risk. Platform stability—defined as the continuity and predictability of order supply, revenue distribution, and rule enforcement—reflects the platform’s institutional robustness and governance capacity. Ownership structure distinguishes between company-owned and individually owned vehicle licenses, representing differences in residual claim rights and asset accountability. Building on the “external institution–internal incentive–behavioral decision” framework, the study analyzes their interactive effects while considering financial variables such as the down payment ratio.
Empirical results show that the effect of platform participation on default risk is not uniformly risk-reducing but contingent on platform stability. Under stable and predictable rules with steady order flows and consistent subsidy policies, drivers’ income expectations smooth out and contractual compliance improves—platforms then act as credit enhancers. Conversely, when stability deteriorates, frequent policy shifts and opaque algorithmic governance heighten income uncertainty and opportunity costs, raising default risk. Ownership structure moderates these effects: drivers under company-owned licenses, lacking asset ownership and relying mainly on institutional discipline, are more sensitive to instability, whereas individually licensed drivers, with stronger asset responsibility, are less affected. These findings confirm that platform stability and ownership jointly determine the behavioral foundation of contractual performance and default risk.
Theoretically, this paper revises the conventional assumption that “platform participation necessarily mitigates risk” by showing that the platform’s governance effect hinges on institutional stability. It operationalizes “platform stability” as a measurable institutional variable and integrates it into financial leasing risk analysis. The proposed dual-governance framework combines insights from principal–agent, property rights, and platform governance theories, offering an integrative explanation for behavioral risks in digital economies. Methodologically, the paper constructs an ordinal default severity index capturing both intensity and timing, estimated through an ordered logit model with proportional-odds testing and robust inference. This approach balances rigor and interpretability, providing a replicable empirical paradigm for future studies on platform-based financial contracts.
Practically, the study offers actionable implications for financial leasing firms, platform enterprises, and regulators. Leasing companies should incorporate platform stability and ownership structure into pricing and credit models, design differentiated clauses (e.g., dynamic deposits or adjustable lease terms), and implement early-warning systems for platform-induced risks. Platforms should treat stability as a core governance KPI, enhancing transparency in order allocation and policy disclosure to stabilize driver expectations and curb strategic default. Regulators may establish industry-wide disclosure and evaluation standards for platform stability, fostering risk-sharing mechanisms among platforms, financial institutions, and drivers.
Overall, this study redefines contractual risk in the digital economy as an outcome of institutional dynamics rather than individual heterogeneity. By linking platform governance, property rights, and behavioral incentives, it uncovers the institutional roots of default behavior and provides theoretical and empirical foundations for a sustainable tri-party governance framework among platforms, financial institutions, and workers in the platform economy.

Date of Award	20 Nov 2025
Original language	Chinese (Simplified)
Awarding Institution	China Europe International Business School
Supervisor	Yuhchang Hwang (Supervisor) & 马国良 (Supervisor)