My research interests are in Behavioral Modeling and my work focuses on bridging the gap between empirical findings and prior theoretical research in Operations Management. In particular, I use analytical tools to study how (empirically verified) gig worker behaviors and consumer behaviors impact firms' operations strategies (pricing strategies, product selling strategies, and information provision policies) as well as each stakeholder's welfare. To achieve this objective, I have initiated theoretical studies of customer overconfidence in service systems, gig worker reference-dependent preferences in ridesharing platforms, and gig workers' job selection and participation behaviors in on-demand delivery platforms.
I am also enthusiastic about pursuing research on Sustainable Operations and Behavioral AI.
I employ game theory, queueing theory, and applied probability in my research. I aim to enhance my analytical modeling skills to be a great modeler and address relevant questions in practical business scenarios.
Publications
[1] Na Zhang, Anand Paul, Xu Sun. Managing Service Systems with Overconfident Customers (2025). Published in Manufacturing & Service Operations Management. [Journal] [E-Companion] [SSRN]
The 16th International Workshop on Behavioral Operations Management Best Student Paper Award, 2024
Selected for the 2023 ISOM Workshop, Warrington College of Business, University of Florida
[2] Vashkar Ghosh, Anand Paul, Na Zhang, Lingjiong Zhu. Network Structures, Audit Policies and the Cost of Security Breaches (2025). Published in Production and Operations Management. [Journal] [SSRN]
Working Papers
[3] Na Zhang, Anand Paul, Liangfei Qiu. Ridesharing Platforms with Reference-Dependent Gig Workers. [SSRN]
[4] Add-On Pricing under Consumer Valuation Uncertainty. With Hongseok Jang, Quan Zheng, and Xiajun Amy Pan. [Paper available upon request]
[5] Na Zhang. On-Demand Delivery Platforms: Independent Workers and Employee Workers. [SSRN]