Abstract
User generated content is being recognized as part of the value proposition of e-commerce organizations. To make available fresh content on topics, one needs to understand how individuals consider existing contributions in their decision to contribute. This study develops and tests three hypotheses based on a survey and archival data of 235 contributors of reviews at Amazon.com. Results from a LISREL analysis indicate that those with greater self-perceived competence tend to submit content on topics with fewer existing contributions. On the other hand, those with higher social adjustive motive toward others in general tend to contribute on topics where there are many existing contributions. In contrast, people for whom the social adjustive motive toward specific others is salient are equally likely to contribute on topics with few and many existing contributions. These findings suggest ways for site administrators to ensure a balanced coverage across topics by addressing these individual and social factors.
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Acknowledgments
I thank the Senior Editor Dr. Hans-Dieter Zimmermann and the anonymous reviewers for their comments and suggestions that have helped in improving this paper. Feedback from the following was also useful while developing this research: Shawn Curley, Gordon Davis, Jungpil Hahn, Mark Snyder, Mani Subramani, Weidong Xia, and participants at the Friday workshop at the University of Minnesota, the 2009 Summer Institute of the Consortium for the Science of Socio-technical Systems at Blue Mountain Lake, New York and the 2011 Americas Conference on Information Systems in Detroit, Michigan. An earlier version of this paper was published in the Proceedings of the Americas Conference on Information Systems, Detroit, Michigan (Peddibhotla 2011). I gratefully acknowledge financial support from the Juran Center for Leadership in Quality, University of Minnesota and the President’s Opportunity Fund for Faculty and Staff Development at the SUNY Institute of Technology.
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Responsible Editor: Hans-Dieter Zimmermann
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Peddibhotla, N. How individuals choose topics to contribute at an online context. Electron Markets 23, 241–250 (2013). https://doi.org/10.1007/s12525-013-0125-7
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DOI: https://doi.org/10.1007/s12525-013-0125-7
Keywords
- Online contexts
- User-generated content
- Product reviews
- Sequential position of contribution
- Bystander model
- Survey