Qingyu Zhang
ABSTRACT
In recent years, the concept of sharing economy has entered our lives. Transactions of second-hand products over electronic platforms are the concrete manifestation of this type of concept in practice. Academic research on e-commerce platforms and online consumers’ purchase intentions has shown a rapid growth trend. Based on this background, this paper studies the influencing factors of individual participation willingness on platforms of second-hand products. This research establishes a model to analyze the influencing factors of individuals participating in transactions of second-hand products based on the theory of innovation diffusion theory, technology acceptance model and its evolution model. The research results show that job relevance, social influence, perceived value, perceived ease of use, and perceived cost have a significant impact on participation intention; participation intention and enabling factors have a significant positive impact on actual participation.
- Sun Guoqiang. (2005). A new paradigm of circular economy: the theory and practice of circular economy eco-city. Tsinghua University Press Co., Ltd.Google Scholar
- Thaler, R. (1985). Mental accounting and consumer choice. Marketing science, 4(3), 199-214.Google Scholar
- Han Rong. (1984). Overview of the development of value engineering at home and abroad. Value engineering, 1(984), 01.Google Scholar
- He, D., Lu, Y., & Zhou, D. (2008). Empirical study of consumers' purchase intentions in C2C electronic commerce. Tsinghua Science & Technology, 13(3), 287-292.Google Scholar
- Bitner, M. J., & Hubbert, A. R. (1994). Encounter satisfaction versus overall satisfaction versus quality. Service quality:New direction s in theory and practice, 34(2), 72-94.Google Scholar
- Cheng, C. H., & Chen, Y. S. (2009). Classifying the segmentation of customer value via RFM model and RS theory. Expert systems with applications, 36(3), 4176-4184.Google Scholar
- Kang Kai. (2004). Theory and Model of Technological Innovation Diffusion. Tianjin University Press.Google Scholar
- Tarde, G., & Antoine, J. P. (2001). Les lois de l'imitation (pp. 1973-1998). Paris: Seuil.Google Scholar
- Ryan, B., & Gross, N. C. (1943). The diffusion of hybrid seed corn in two Iowa communities. Rural sociology, 8(1), 15.Google Scholar
- Rice, R. E., & Rogers, E. M. (1980). Reinvention in the innovation process. Knowledge, 1(4), 499-514.Google Scholar
- Davis, F. D. (1993). User acceptance of information technology: system characteristics, user perceptions and behavioral impacts. International journal of man-machine studies, 38(3), 475-487.Google Scholar
- Fishbein, M., & Ajzen, I. (1977). Belief, attitude, intention, and behavior: An introduction to theory and research.Google Scholar
- Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179-211.Google Scholar
- Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478.Google Scholar
- Dishaw, M. T., & Strong, D. M. (1999). Extending the technology acceptance model with task–technology fit constructs. Information & management, 36(1), 9-21.Google Scholar
- Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information & management, 40(3), 191-204.Google Scholar
- Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204.Google Scholar
- Chen Fangli, & Hu Zuguang. (2008). Research on the Design and Implementation of Quantitative Scheme Design and Implementation of the Participation of Technological Elements in Profit Distribution. Scientific Research Management, 29(002), 89-96.Google Scholar
- Wei Mingxia, & Xiao Kaihong. Analysis of Perceptual Factors Affecting B2C E-commerce Online Consumption Behavior. Research on Science and Technology Management.Google Scholar
- Gu Rui, Hu Libin, & Wang Kanliang. (2013). An Empirical Study on the Impact of Social Networking Website Value Perception and Social Influence on User Loyalty. Journal of Information Resources Management (01), 10-21.Google Scholar
Recommendations
Factors influencing continuance intention to use social network sites
Factors influencing continuance intention to use Facebook are examined.Satisfaction and perceived usefulness influence continuance intention.Enjoyment and subjective norms influence continuance intention.Habit mediates the relationship between ...
Factors influencing adoption of mobile banking by Jordanian bank customers
The study examines the factors influencing behavioral intentions and adoption of Mobile banking by Jordanian bank customers.The study uses extended unified theory of acceptance and use (UTAUT2) as a basic model.The data were collected by conducting a ...
Factors influencing the usage of websites: the case of a generic portal in The Netherlands
In this paper, we empirically investigate an extension of the Technology Acceptance Model (TAM) to explain the individual acceptance and usage of websites. Conceptually, we examine perceived ease-of-use, usefulness, enjoyment, and their impact on ...
Comments