Biography
Dr Kejia Hu is an Associate Professor of Management Science at Saïd Business School, University of Oxford, a Fellow at Exeter College, Founding Director of the Human-Algorithm Interaction Lab, and Co-Director of the Oxford Executive Diploma in Artificial Intelligence for Business.
Before joining Oxford in 2023, she was an Associate Professor of Operations Management at China Europe International Business School and an Assistant Professor of Operations Management at Vanderbilt University’s Owen Graduate School of Management. She received her PhD in Operations Management from the Kellogg School of Management, Northwestern University; her MS in Statistics from the University of California, Davis; and her BSc in Statistics from Fudan University.
Kejia’s work brings together rigorous quantitative research and practical engagement with organisations navigating technological change. She has collaborated with companies across hospitality, e-commerce, manufacturing, mobility, healthcare, and technology, and advises senior leaders on AI transformation and strategy. In 2023, Poets & Quantsrecognised her as one of the Best 40 Under 40 Business School Professors worldwide.
She is Chair of the INFORMS Service Science Section, a Board Member of the POMS College of Service Operations, and an Academic Scholar at the Cornell Institute for Healthy Futures. She also serves as Department Editor for IEEE Transactions on Engineering Management, Senior Editor for Production and Operations Management, Associate Editor for Decision Sciences, Guest Editor for Omega and ACM Transactions on Social Computing, and a member of the Editorial Review Board of the Journal of Operations Management.
Research
Kejia’s research focuses on service-system design, forecasting, and human–AI interaction in decision-making. She studies how organisations can use data and AI to improve operational performance, create customer value, and redesign work while preserving sound human judgement, accountability, and trust.
Her earlier research in service operations examined how organisations should balance standardisation and customisation, how customers value service speed and quality, and how firms can manage multi-channel engagement. Her forecasting research has developed practical models for decision-making under uncertainty, including product life-cycle forecasting and data-driven planning.
More recently, Kejia’s work has focused on how AI changes organisational decision-making and the relationship between human expertise and algorithmic systems. She developed the Four-Level AI Transformation Framework, which moves from automation and personalisation to operational innovation and business-model innovation. The framework provides leaders with a structured way to assess how AI can create value across different stages of organisational maturity.
Her current work examines trust in digital systems, calibrated reliance on AI-assisted decisions, human bias in algorithmic settings, and the role of generative AI in organisational transformation.
Teaching
Kejia teaches Business Analytics on the Oxford MBA and Statistical Research Methods for DPhil students. She also teaches Harness the Power of AI on Executive MBA and executive education programmes.
As Co-Director of the Oxford Executive Diploma in Artificial Intelligence for Business, she works with experienced professionals, technical specialists, and organisational leaders on AI strategy, implementation, governance, and responsible adoption. Her teaching combines analytical rigour with real-world cases, helping students and executives understand not only how AI works, but how it can be deployed responsibly to improve organisational performance and decision-making.
Previously, at Vanderbilt University, she taught Management of Service Operations on the MBA programme and Operations Management to undergraduate students. At CEIBS, she taught Business Analytics, Strategic Operations Management, and executive education on AI and business strategy.
Selected Publications
- Hu, K., Lam, S., Wu, T., and Xu, J. S. D. Navigating AI Transformation: Business Innovation, Strategy, and Risk. Springer Nature, 2026.
- Kong, L., Hu, K., Shi, L., and Wang, T. ‘Teaching at a Distance, Scrutinized Up Close: Bias in Online Student Evaluation of Teaching’. Production and Operations Management, 2026.
- Jia, Z., Hu, K., Hu, J.-Q., and Ahuja, V. ‘Intrinsic Benefits of Preference Satisfaction: Impact on Surgeons’ Service Performance’. Manufacturing & Service Operations Management, 2026.
- Hu, K., Li, X., and Xu, J. ‘Building Trust in the Digital Economy’. Digital Transformation and Society, 2026.
- Zou, F., Dong, Y., Hu, K., and Venkataraman, S. ‘Delegation with Technology Migration: An Empirical Analysis of Mobile Virtual Network Operators’. Management Science, 2024.
- Hu, K., and Karacaoglu, N. ‘WeStore or AppStore: Customer Behavior Differences in Mobile Apps and Social Commerce’. Production and Operations Management, 2024.
- Hu, K., Kong, L., and Jia, Z. ‘Supplier Selection Criteria under Heterogeneous Sourcing Needs: Evidence from an Online Marketplace for Selling Production Capacity’. Production and Operations Management, 2024.
- Hu, K., Kong, L., and Verma, R. ‘Service Chains’ Operational Strategies: Standardization or Customization? Evidence from the Nursing Home Industry’. Manufacturing & Service Operations Management, 2022.
- Hu, K., Allon, G., and Bassamboo, A. ‘Understanding Customers’ Retrial in Call Centers: Preferences of Service Speed and Service Quality’. Manufacturing & Service Operations Management, 2021.
- Hu, K., Acimovic, J., Erize, F., Thomas, D. J., and Van Mieghem, J. A. ‘Forecasting Product Life Cycle Curves: A Practical Approach and Empirical Analysis’. Manufacturing & Service Operations Management, 2018.
A full list of publications is available at www.kejiahu.com.