Xia, Huang, Duan and Whinston (2012)
|Xia, Huang, Duan and Whinston (2012)|
|Title:||To continue sharing or not to continue sharing? An empirical analysis of user decision in peer-to-peer sharing networks|
|Author(s):||Xia, M., Huang, Y., Duan, W., Whinston, A. B.|
|Citation:||Mu Xia, Yun Huang, Wenjing Duan, Andrew B. Whinston, (2012) Research Note—To Continue Sharing or Not to Continue Sharing? An Empirical Analysis of User Decision in Peer-to-Peer Sharing Networks. Information Systems Research 23(1):247-259.|
|Link(s):||Definitive , Open Access|
|Key Related Studies:|
|About the Data|
|Data Description:||Researchers logged all activities and commands sent to one of the largest IRC channels (more than 300 million) called #mp3passion, from March 2001 to May 2006. Researchers defined the time window as two weeks for a certain time period.
During the entire data collection period, the user size of the sharing channel was stable, with around 20,000 unique users (identifiable by user ID), whereas the number of sharers grew from 600 to more than 2,000. The researchers observed 55,031 unique sharers in total, along with 834,613 free riders.
Because data were extracted through online activity, information on user demographics was nonobservable.
|Data Type:||Primary data|
|Secondary Data Sources:|
|Data Collection Methods:|
|Data Analysis Methods:|
|Cross Country Study?:||No|
|Government or policy study?:||No|
|Time Period(s) of Collection:||
Peer-to-peer sharing networks have seen explosive growth recently. In these networks, sharing files is completely voluntary, and there is no financial reward for users to contribute. However, many users continue to share despite the massive free-riding by others. Using a large-scale data set of individual activities in a peer-to-peer music-sharing network, we seek to understand users’ continued-sharing behavior as a private contribution to a public good. We find that the more benefit users “get from” the network, in the form of downloads, browses, and searches, the more likely they are to continue sharing. Also, the more value users “give to” the network, in the form of downloads by other users and recognition by the network, the more likely they are to continue sharing. Moreover, our findings suggest that, overall, “getting from” is a stronger force for the continued-sharing decision than “giving to.”
Main Results of the Study
- A one standard deviation increase in variable of download leads to a 27% increase in the odds of continued sharing. Similarly, a one standard deviation increase of variables of browse, search, contribute, and been_browsed leads to a 23%, 33%, 32%, and 47% increase in the odds of continued sharing, respectively. Becoming a value use leads to a 146% increase in the odds of continued sharing.
- Overall, the results show that both self-use and continuous contribution provide strong incentives for users to continue sharing. In addition, “getting-from” is a stronger force for the continued-sharing decision than “giving-to.”
- Sharing history has a significant effect on users’ decisions to share across all models. The total number of files downloaded has a significantly negative effect on the sharers’ decision to continue sharing.
- In a PTP network, both the user’s benefits received from the network and the value the user provides to the network are significant predictors of her continued contribution. The level of social interaction and anonymity seems to have little to no effect on whether users continue to share.
Policy Implications as Stated By Author
- Results may be helpful both to record companies and to copyright holders seeking to design a method to thwart illegal file sharing, and especially to the management of content-sharing communities, such as YouTube and Flickr.
- Findings indicate the key to network growth is the continuous addition of new and fresh content for users. Further, showing more statistics to make a user’s use of the network more visible will help the user continue sharing. Finally, adding more features to show how a user’s contribution is used by others have a similar positive effect.
- Accordingly, recognition in visual representation of users’ contributions to the network can be quite effective in motivating a user’s continued contribution.
Coverage of Study
|Level of aggregation:||Individual data|
|Period of material under study:||2001-2006|