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ACADEMIC AND PROFESSIONAL ENGAGEMENT ACTIVITIES

Dr. Yu Shi’s research focuses on Data Envelopment Analysis (DEA), optimization modeling, and performance, productivity, and efficiency evaluation, as well as benchmarking. Her work has appeared in leading peer-reviewed journals, including the European Journal of Operational Research, Omega, Annals of Operations Research, and the Journal of the Operational Research Society. She has taught a range of analytics-oriented courses such as MBA810 Business Analytics & Statistics, MGT226 Business Analytics, and MGT251 Introduction to Programming for Data Science.

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.

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.

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.