Yu Shi

ACADEMIC AND PROFESSIONAL ENGAGEMENT ACTIVITIES

Dr. Yu Shi is an Assistant Professor of Business Analytics at the Lubin School of Business, Pace University. Her research focuses on Data Envelopment Analysis (DEA), optimization modeling, and non-parametric methods for benchmarking, performance evaluation, and productivity and efficiency analysis. She is particularly interested in integrating machine learning techniques into DEA and related operational research frameworks to enhance predictive power and interpretability. Her work has been published in leading peer-reviewed journals, including the European Journal of Operational Research, Omega, Annals of Operations Research, INFOR: Information Systems and Operational Research, and the Journal of the Operational Research Society. Dr. Shi’s research has been recognized internationally, including receiving an EJOR Editors’ Choice distinction. In addition to her scholarly contributions, she is actively engaged in professional service as an ad-hoc reviewer for major journals in operations research and analytics. Dr. Shi teaches a range of analytics-oriented courses, including MBA810 Business Analytics & Statistics, MGT226 Business Analytics, and MGT251 Introduction to Programming for Data Science, emphasizing applied data-driven decision making and modern analytical tools.

SELECTED CONTRIBUTIONS & PUBLICATIONS

Liang, N., Shi, Y., Chen, Y. (2025). R&D and operational efficiency in China’s innovative high-tech enterprises: Empirical analysis with two-stage slack based measure data envelopment analysis and threshold regression. Omega. Read More >>

Shi, Y., Charles, V., Zhu, J. (2024). Bank financial sustainability evaluation: Data envelopment analysis with random forest and Shapley additive explanations. European Journal of Operational Research. Read More >>

Yu, A., Zhang, H., Liu, H., Shi, Y., Bi, W. (2024). An Integrated machine learning and DEA-predefined performance outcome prediction framework with high-dimensional imbalanced data. Annals of Operations Research. 341(1), 451-483.

Yu, A., Shi, Y., Zhu, J. (2021). Acceleration of Large-Scale DEA Computations Using Random Forest Classification. Data-Enabled Analytics: DEA for Big Data. (pp. 31-39). Springer International Publishing.

Shi, Y., Higgins, H.N., Zhu, J. (2021). Shared and unsplittable performance links in network DEA. Annals of Operations Research. 303(1), 507-528.

Yu, A., Shi, Y., You, J., Zhu, J. (2021). Innovation performance evaluation for high-tech companies using a dynamic network data envelopment analysis approach. European Journal of Operational Research. 292(1), 199-212.

Zhou, H., Yang, Y., Chen, Y., Zhu, J., Shi, Y. (2021). DEA application in sustainability 1996–2019: The origins, development, and future directions. Pursuing Sustainability. (pp. 71-109). Springer.

Shi, Y., Zhu, J., Charles, V. (2020). Data science and productivity: A bibliometric review of data science applications and approaches in productivity evaluations. Journal of the Operational Research Society.