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How online social interactions influence customer information contribution behavior in online social shopping communities: A social learning theory perspective
Author(s) -
Cheung Christy M.K.,
Liu Ivy L.B.,
Lee Matthew K.O.
Publication year - 2015
Publication title -
journal of the association for information science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.903
H-Index - 145
eISSN - 2330-1643
pISSN - 2330-1635
DOI - 10.1002/asi.23340
Subject(s) - reputation , social learning , perspective (graphical) , online community , observational learning , online participation , social learning theory , customer intelligence , customer retention , marketing , knowledge management , psychology , business , computer science , experiential learning , the internet , social psychology , sociology , world wide web , service (business) , service quality , artificial intelligence , mathematics education , social science
Online social shopping communities are transforming the way customers communicate and exchange product information with others. To date, the issue of customer participation in online social shopping communities has become an important but underexplored research area in the academic literature. In this study, we examined how online social interactions affect customer information contribution behavior. We also explored the moderating role of customer reputation in the relationship between observational learning and reinforcement learning as well as customer information contribution behavior. Analyses of panel data from 6,121 customers in an online social fashion platform revealed that they are significant factors affecting customer information contribution behavior and that reinforcement learning exhibits a stronger effect than observational learning. The results also showed that customer reputation has a significant negative moderating effect on the relationship between observational learning and customer information contribution behavior. This study not only enriched our theoretical understanding of information contribution behavior but also provided guidelines for online social shopping community administrators to better design their community features.