Location
Hilton Hawaiian Village, Honolulu, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
3-1-2024 12:00 AM
End Date
6-1-2024 12:00 AM
Description
This study explores the impact of default news of peer-to-peer (P2P) lending platforms on their trading volumes, particularly during a market downturn, and examines the moderating effect of online word-of-mouth (WOM). Using a dataset encompassing 694 P2P lending platforms from P2PEye.com, a premier third-party P2P information portal in China, this study employs advanced econometric techniques such as staggered difference-in-differences and difference-in-difference-in-differences analyses. The results show that default news diminishes trading volumes of P2P platforms, an effect that is more pronounced on platforms with a more positive WOM. Moreover, we find that platforms affiliated with banks or operating without Internet Content Provider (ICP) certification appear to be less susceptible to the negative effects of default news. This study offers novel perspectives on the interplay between default news and online WOM within in a declining market. It contributes to the existing body of literature and provides actionable insights for various stakeholders.
Recommended Citation
Shang, Yanan; Hu, Jin; Tao, Cheng; Hu, Daning; and Yang, Xuan, "The Impact of Online Word-of-Mouth and Default News on Trading Volumes in Peer-to-Peer Lending Platforms" (2024). Hawaii International Conference on System Sciences 2024 (HICSS-57). 13.
https://aisel.aisnet.org/hicss-57/dsm/influencers/13
The Impact of Online Word-of-Mouth and Default News on Trading Volumes in Peer-to-Peer Lending Platforms
Hilton Hawaiian Village, Honolulu, Hawaii
This study explores the impact of default news of peer-to-peer (P2P) lending platforms on their trading volumes, particularly during a market downturn, and examines the moderating effect of online word-of-mouth (WOM). Using a dataset encompassing 694 P2P lending platforms from P2PEye.com, a premier third-party P2P information portal in China, this study employs advanced econometric techniques such as staggered difference-in-differences and difference-in-difference-in-differences analyses. The results show that default news diminishes trading volumes of P2P platforms, an effect that is more pronounced on platforms with a more positive WOM. Moreover, we find that platforms affiliated with banks or operating without Internet Content Provider (ICP) certification appear to be less susceptible to the negative effects of default news. This study offers novel perspectives on the interplay between default news and online WOM within in a declining market. It contributes to the existing body of literature and provides actionable insights for various stakeholders.
https://aisel.aisnet.org/hicss-57/dsm/influencers/13