Jing Peng

Associate Professor

Operations and Information Management

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Education

Ph.D., The Wharton School, University of Pennsylvania
M.E., Institute of Automation, Chinese Academy of Sciences
B.S., Xi’an Jiaotong University

Areas of Expertise

Econometrics, E-Commerce, Social Media, Gig Economy, Digital Health, Human-AI Interaction

Featured Journal Publications

(Google Scholar, ORCID, and SSRN)

1. Zishun Qian, Jing Peng, and Jianbin Li (2025) The Impact of Generative AI Announcements on Suppliers: Evidence from the Stock Market. Production and Operations Management (forthcoming).
2. Hongfei Li, Jing Peng, Gang Wang, and Xue Bai (2024) The Impact of Process- vs. Outcome-Oriented Reviews on the Sales of Healthcare Services. Information Systems Research, 35(4):1909-1927.
3. Jing Peng and Christophe Van den Bulte (2024) Participation vs. Effectiveness in Sponsored Tweet Campaigns: A Quality-Quantity Conundrum. Management Science, 70(11):7345-8215.
4. Jing Peng and Chen Liang (2023) On the Differences Between View-Based and Purchase-Based Recommender Systems. MIS Quarterly, 47(2):875-900.
5. Chen Liang, Jing Peng, YiliHong, and Bin Gu (2023) The Hidden Costs and Benefits of Monitoring in the Gig Economy. Information Systems Research, 34(1):297-318.
6. Hongfei Li, Jing Peng, Xinxin Li, and Jan Stallaert (2023) When More Can Be Less: The Effect of Add-on Insurance on the Consumption of Professional Services. Information Systems Research, 34(1):363-382.
7. Jing Peng (2023) Identification of Causal Mechanisms from Randomized Experiments: A Framework for Endogenous Mediation Analysis. Information Systems Research, 34(1):67-84.
8. Jing Peng, Julie Zhang, and Ram Gopal (2022) The Good, the Bad, and the Social Media: Financial Implications of Social Media Reactions to Firm-Related News. Journal of Management Information Systems, 39(3): 706-732.
9. Yili Hong, Jing Peng, Gordon Burtch, and Ni Huang (2021) Just DM Me (Politely): Direct Messaging, Politeness, and Hiring Outcomes in Online Labor Markets. Information Systems Research, 32(3): 675-1097.
10. Shu He, Jing Peng, Jianbin Li, and Liping Xu (2020) Impact of Platform Owner’s Entry on Third-Party Stores. Information Systems Research, 31(4): 1467-1484.
11. Jing Peng, Ashish Agarwal, Kartik Hosanagar, and Raghuram Iyengar (2018) Network Overlap and Content Sharing on Social Media Platforms. Journal of Marketing Research, 55(4), p. 571-585.

Selected Working Papers

• Michael Bailey, Jing Peng. A Random Effects Model of Non-Ignorable Nonresponse in Panel Survey Data. Conditional Accept at American Political Science Review.
• Huiyan Chen, Hongfei Li, Jing Peng, and Ramesh Shankar. Impact of Refundability on Sales of Digital Products: Evidence from a Knowledge-Sharing Platform. Minor Revision at MIS Quarterly.
• Jing Peng. Machine Learning for Instrumental Variable Regression: From Bias to Resilience. Under Revision at Management Science.
• Chen Liang, Jing Peng, Zhuoyan Li, and Ming Yin. The Valuation of Generative AI in Content Creation: Evidence from Gig Workers. Under Revision at MIS Quarterly.
• Tong Shen, Chen Liang, Jing Peng, Mengcheng Guan, and Jianbin Li. Breaking the Stigma: The Role of AI in Drug Purchases for Sensitive Health Conditions. Under Revision at Information Systems Research.
• Ning Wang, Jing Peng, Raghuram Iyengar, Mengcheng Guan, and Jianbin Li. Unboxing Privacy: How Discreet Packaging Shapes Consumer Purchases? Under Revision at Management Science.

Software Packages

I have a keen interest in developing novel econometric methods and have contributed three CRAN packages.

• CoxPlus: A fast and highly scalable R package estimating the Cox model (proportional hazards model) when an event has more than one cause. Application: multi-channel advertising, social influence identification, etc.
• PanelCount: A fast and scalable R package implementing random effects and sample selection models for panel count data. Application: panel count data with self-selection.
• endogeneity: A comprehensive R package that implements various recursive two-stage models to address the endogeneity issue. Application: endogenous mediators in experiments, endogenous treatment variables in observational studies.
• PanelSelect: A comprehensive R package extending the Heckman selection model to panel data with various types of outcomes. Application: sample selection in panel settings. 

Awards and Honors

INFORMS Information Systems Society Sandra A. Slaughter Early Career Award, 2025
Research Excellence Award, UConn School of Business, 2025
Best Paper Honorable Mention, ACM CHI conference on Human Factors in Computing Systems, 2024
Best Paper Honorable Mention, UConn School of Business, 2024
Best Paper Award, UConn School of Business, 2023
Workshop on e-Business Most Promising Ongoing Research Runner-Up Award, 2022
INFORMS Information Systems Society Gordon B. Davis Young Scholar Award, 2022
Dean’s Ackerman Scholar, UConn School of Business, 2022-2024
INFORMS eBusiness Best Paper Award Runner-Up, 2021
Best Paper Award, UConn School of Business, 2021
WISE Best Paper Award, 2018
INFORMS Social Media Analytics Student Best Paper Competition Runner-Up, 2015
Mack Institute Research Fellowship, 2015
Baker Center PhD Research Grant, 2015
President Gutmann’s Leadership Award, 2014
Baker Center PhD Research Grant, 2014
Penn Lauder CIBER PhD Grant Awards, 2013

Teaching

OPIM 6201 – Research Methods for Operations and Information Management (focus on Econometrics)
OPIM 5515 – Generative AI for Business
OPIM 4895 – AI Literacy: Navigating the Future of Business
OPIM 5671 – Data Mining and Business Intelligence
OPIM 5604 – Predictive Modeling
OPIM 5512 – Data Science using Python