An algorithm for identifying loyal customers in C2C electronic commerce models

Azarnoush Ansari and Ali Sanayei

International Journal of Productivity and Quality Management, 2020, vol. 31, issue 1, 79-97

Abstract: Today, the use of the internet for commercial transactions and sales has dramatically increased. E-commerce has different models including the consumer-to-consumer (C2C) model. The purpose of this study is to identify the factors influencing Iranian users' intentions when buying from C2C websites. The research model was developed based on the factors affecting the trust between members of C2C websites and other factors impacting consumer buying behaviour. The data was collected from the users of two C2C websites in Iran. The research method was quantitative and data collection was performed using questionnaire. The collected data was analysed through structural equation modelling. The relationships between the variables in the research model including familiarity with other members, perceived similarity with other members, perception of structural assurances, trust propensity, trust in members, trust in website, intention to get information, and purchase intention from C2C website were tested using structural equation modelling technique. In the end, based on hypothesis testing results, important recommendations were suggested for better design and management of C2C websites.

Keywords: perception of structural assurances; consumer buying behaviour; consumer-to-consumer websites; e-commerce; electronic commerce. (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=109359 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijpqma:v:31:y:2020:i:1:p:79-97

Access Statistics for this article

More articles in International Journal of Productivity and Quality Management from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().