情报科学 ›› 2024, Vol. 42 ›› Issue (5): 138-148.

• 业务研究 • 上一篇    下一篇

从制度信任到人际信任
——共享出行平台信息生态运行机制对策研究

  

  • 出版日期:2024-05-05 发布日期:2024-07-26

  • Online:2024-05-05 Published:2024-07-26

摘要:

【目的/意义】共享出行中因司机行为引发的恶性事件导致用户对司机群体产生信任危机。司机审核、警企
合作等平台机制作为约束司机行为和建立人际信任的重要资源,能够为用户提供制度保障并加强其使用意愿。【方
法/过程】本文基于信任转移理论和信号理论,在信息生态视角下构建了平台信任、司机群体信任和用户持续使用
意愿在平台机制调节下的结构方程模型(SEM),并实证检验平台信任到司机群体信任的转移过程及边界条件。【结
果/结论】结果表明,平台信任正向显著影响司机群体信任;司机群体信任正向显著影响用户的持续使用意愿;警企
合作机制负向调节平台信任与司机群体信任之间的关系,而第三方支付机制正向显著调节平台信任对司机群体信
任的影响。【创新/局限】研究发现,人际信任的构建来源于制度信任,并且这一转移过程受到平台层面制度环境的
调节影响,研究成果拓展了信任转移理论和信号理论在共享经济领域的应用,并为共享出行行业的持续健康发展
提供理论支撑和管理对策。

Abstract:

【Purpose/significance】 The vicious incidents caused by drivers' behaviors in ride-hailing lead to a crisis of trust in drivers.
As important resources to restrain drivers' behaviors and build interpersonal trust, platform mechanisms such as driver screening and
police-cooperation can provide institutional guarantee for users and strengthen their continuous use intention.【Method/process】
Based on trust transfer theory and signal theory, in the perspective of information ecology, this paper establishes structure equation
model (SEM) of trust in the platform, trust in the community drivers and continuous use intention under the moderation of platform
mechanisms, and empirically tests trust transfer process and boundary condition.【Result/conclusion】The results show that trust in the
platform positively influences trust in the community of drivers, trust in the community of drivers positively affects continuous use in⁃
tention, and in the condition of platform information environment, police-cooperation mechanism negatively moderates the trust trans⁃
fer from platform to the community of drivers while escrow mechanisms positively moderates.【Innovation/limitation】The findings indi⁃
cate that the development of interpersonal trust rely on institution-based trust, and the trust transfer process is affected by the environ⁃
ment of platform mechanisms. This paper enriches the adoption of trust transfer theory and signal theory in sharing economy, and pro⁃
vides management advice to the healthy development of ride-hailing industries.