A social commerce purchasing decision model with trust network and item review information

2022 
Abstract Shopping without much experience on target items is not unusual in social commerce (s-commerce). Inexperienced users are often influenced by user reviews when making purchasing decisions, which can be easily distorted due to low review quality. To address this issue, this study integrates two important review dimensions into purchasing decision model, i.e. the trust relationships to experienced users and the reliability of experienced users’ reviews. A purchasing decision model for s-commerce is proposed based on trust computation and item reviews. The trust degree of inexperienced users to experienced ones is computed based on item reviews and propagated using the parameterized Hamacher t-norm operator. Based on the item review information, inexperienced users can make the final purchasing decisions on target items with trust information to experienced users and their reliability on item reviews. A numerical example with a data subset of Epinions.com is provided and the comparative analysis is conducted to verify the effectiveness of the proposed method. This study proposes an inexperienced purchasing decision method considering the risk attitude of users with flexible trust propagation parameters, which can provide a new perspective for the s-commerce recommendations.
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