A purchasing-intention model in C2C e-commerce of China: The role of perceived risk, trust, perceived benefit and their antecedents

Huiying Li, Qiang Ye, Chun Hung Roberts Law, Zhisheng Wang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

2 Citations (Scopus)


From the perspectives of psychology, marketing and information technology, this study developed a theoretical framework describing the purchasing-intention model in C2C e-commerce of China. The model demonstrated that trust, perceived risk, perceived benefit and their antecedents would have an influence on costumers' intention of purchase. Then this study tested the proposed model using Structural Equation Modeling on Internet consumer purchasing behavior data collected via web-based surveys. The results of the study show that Internet consumers' trust, perceived benefit and perceived risk have strong impacts on their intention of purchase. Reputation of sellers, website security, familiarity with websites and group purchase have strong effects on consumers' trust. However, only seller accessibility has a significant impact on perceived risk. Moreover, group purchase has a strong impact on perceived benefit. The results and implications of this research are discussed.
Original languageEnglish
Title of host publicationICEC 2010 - Proceedings of the 12th International Conference on Electronic Commerce
Subtitle of host publicationRoadmap for the Future of Electronic Business
Number of pages1
Publication statusPublished - 1 Dec 2010
Event12th International Conference on Electronic Commerce, ICEC 2010 - Honolulu, HI, United States
Duration: 2 Aug 20104 Aug 2010


Conference12th International Conference on Electronic Commerce, ICEC 2010
Country/TerritoryUnited States
CityHonolulu, HI


  • Antecedents of trust
  • Costumers' intention of purchase
  • Customer trust
  • Group purchase
  • Perceived risk

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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