UGC (User-generated content) websites routinely deploy incentive hierarchies, where users achieve increasingly higher status in the community after achieving increasingly more difficult goals, to motivate users to contribute. Yet the existing empirical literature remains largely unclear whether such hierarchies are indeed effective in inducing user contributions. We gathered data from a large online crowd-based knowledge exchange to answer this question, and drew on the goal setting theory to study users' contributions before and after they reach consecutive levels of a vertical incentive hierarchy. We found evidence that even though these "glory"-based incentives may motivate users to contribute more before the goals are reached, user contribution levels dropped significantly after that. In other words, the cumulative effect appears only temporary. Our results hence highlight some unintended and heretofore undocumented effects of incentive hierarchies, and have important implications for business models that rely on user contributions, such as knowledge exchange and crowdsourcing, as well as the broader phenomenon of "gamification" in other contexts.
Enabled by Web 2.0 technologies social media provide an unparalleled platform for consumers to share their product experiences and opinions---through word-of-mouth (WOM) or consumer reviews. It has become increasingly important to understand how WOM content and metrics thereof are related to consumer purchases and product sales. By integrating network analysis with text sentiment mining techniques, we propose product comparison networks as a novel construct, computed from consumer product reviews. To test the validity of these product ranking measures, we conduct an empirical study based on a digital camera dataset from Amazon.com. The results demonstrate significant linkage between network-based measures and product sales, which is not fully captured by existing review measures such as numerical ratings. The findings provide important insights into the business impact of social media and user-generated content, an emerging problem in business intelligence research. From a managerial perspective, our results suggest that WOM in social media also constitutes a competitive landscape for firms to understand and manipulate.
Reputation has often been proposed as the central mechanism that creates trust in the sharing economy. However, some sharing platforms that focus primarily on social rather than economically driven exchanges have managed to facilitate exchanges between users without the use of a reputation system. This could indicate that socially driven exchanges are in less need of reputation systems and that having sufficient trust is less problematic. We examine the effect of seller reputation on sales and price as proxies for trust, using a large dataset from a Dutch meal-sharing platform. This platform aims to stimulate social interactions between people via meal sharing. Multilevel regression analyses were used to test the association of reputation with trust. Our main empirical results are that reputation affects both sales and price positively, consistent with the existing reputation literature. We also found evidence of the presence of an information effect, i.e., the influence of reputation on sharing decreases when additional profile information is provided (e.g., a profile photo, a product description). Our results thus confirm the effectiveness of reputation in more socially driven exchanges also. Consequently, platform owners are advised to use reputation on their platform to increase sharing between its users.
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