QIAO Dandan

COM2-04-15

660 13789

www.qiaodandan.com

Associate Professor

Ph.D. (Tsinghua University)
B.S. (Beijing University of Posts and Telecommunications)

QIAO Dandan is an associate professor in the Department of Information Systems and Analytics at the School of Computing, National University of Singapore (NUS). Prior to joining NUS, she earned her PhD in Information Systems from Tsinghua University and visited the University of Texas at Austin as a research scholar for two years. Her research focuses on digital platform design and computational social science. Her work has been published in leading academic journals such as Management Science (MS), Information Systems Research (ISR), MIS Quarterly (MISQ), Journal of Management Information Systems (JMIS), and Production and Operations Management (POM). She received the AIS Early Career Award in 2024 and ISS Gordon B. Davis Young Scholar Award in 2023. She has also secured research grants from the Ministry of Education (MOE) in Singapore and the NET Institute. Since 2024, Dandan has been serving as a member of the Information Systems Research (ISR) Editorial Review Board. Additionally, she is an associate editor for the Special Issue in MIS Quarterly. She has been a reviewer for top-tier academic journals and conferences in her field, including serving as the co-organizer of the Feeder Workshop for the Workshop on Information Technologies and Systems (WITS) 2024, track Co-Chair for the Pacific Asia Conference on Information Systems (PACIS) 2023, and track Associate Editor for the International Conference on Information Systems (ICIS) over several years.

RESEARCH AREAS

Digital Transformation, Platforms & Innovation

Data Science & Business Analytics

RESEARCH INTERESTS

Economics of Information Systems
Economics of Dark Web
Online Altruism and Crowd Wisdom
Competitive Intelligence and Predictive Analytics

RESEARCH PROJECTS

Decoding Persuasion on Crowdfunding Platforms

This research proposes a novel prediction framework based on persuasion theory to enhance crowdfunding success predictions. It aims to identify persuasive elements in project descriptions and improve the prediction accuracy so as to provide guidance for crowdfunding project initiators. The study integrates computational methods and deep learning to not only boost prediction performance but also offer interpretable insights, contributing to information systems and crowdfunding design.

Data Science & Business Analytics, Computational Social Science

Understanding Online Contribution: Impact Evaluation and Crowd Wisdom Extraction

With the massive amount of online contributions shaping individual and organizational decision-making, this project delves into utilizing and understanding this valuable resource. By combining econometrics and natural language processing, the research seeks innovative insights to leverage these vast information pools and assess their impacts on commerce and society.

Data Science & Business Analytics

RESEARCH GROUPS

TEACHING INNOVATIONS

SELECTED PUBLICATIONS

Lu, Y., Qiao, D., He S., Tan, B.C.Y., “How Search Technology Breeds Illegal Transactions: Empirical Evidence from the Darknet”,Management Science, Forthcoming.
Qiu, L., Qiao, D., Tan, B.C.Y., Whinston, A.B., (2024) Leading the Horse to Water? Investigating the Impact of Ride-hailing Services on Hate Crimes, Production and Operations Management, 33(1), 342-363.Forthcoming.
Chan, J., He, S., Qiao, D., and Whinston, A. (2023) Shedding Light on the Dark: The Impact of Legal Enforcement on Darknet Transactions, Information Systems Research, 35(1), 145-164.
Khern-am-nuai, W., Ghasemkhani, H., Qiao, D., and Kannan, K. (2023) The Impact of Online Q&As on Product Sales: The Case of Amazon Answer, Information Systems Research, 35(2), 747-765.
Qiao, D., Rui, H. (2022). Text Performance on the Vine Stage? The Effect of Incentive on Product Review Text Quality”. Information Systems Research, 34(2), pp.676-697.
Qiao, D., Lee, S. Y., Whinston, A. B., & Wei, Q. (2021). Mitigating the Adverse Effect of Monetary Incentives on Voluntary Contributions Online. Journal of Management Information Systems, 38(1), 82-107.
Wang, L., Zhang, J., Chen, G., & Qiao, D. (2021). Identifying comparable entities with indirectly associative relations and word embeddings from web search logs. Decision Support Systems, 141, 113465.
Qiao, D., Lee, S. Y., Whinston, A. B., & Wei, Q. (2020). Financial incentives dampen altruism in online prosocial contributions: A study of online reviews. Information Systems Research, 31(4), 1361-1375.
Guo, X., Wei, Q., Chen, G., Zhang, J., & Qiao, D. (2017). Extracting Representative Information on Intra-Organizational Blogging Platforms. MIS Quarterly, 41(4), 1105-1127.
Wei, Q., Qiao, D., Zhang, J., Chen, G., & Guo, X. (2016). A novel bipartite graph based competitiveness degree analysis from query logs. ACM Transactions on Knowledge Discovery from Data (TKDD), 11(2), 1-25.
Qiao, D., Zhang, J., We, Q., Chen, G., 2017. Finding Competitive Keywords from Query Logs to Enhance Search Engine Advertising. Information & Management, 54(4), pp.531-543.