Distance Functions in Primal and Dual Spaces.- DEA Cross Efficiency.- DEA Cross Efficiency Under Variable Returns to Scale.- Discrete and Integer Valued Inputs and Outputs in Data Envelopnebt Analysis.- DEA Models with Production Trade-offs and Weight Restrictions.- Facet Analysis in Data Envelopment Analysis.- Stochastic Nonparametric Approach to Efficiency Analysis: A Unified Framework.- Translation Invariance in Data Envelopment Analysis.- Scale Elasticity in Non-parametric DEA Approach.- DEA Based Benchmarking Models.- Data Envelopment Analysis with Non-Homogeneous DMUs.- Efficiency Measurement in Data Envelopment Analysis with Fuzzy Data.- Partial Input to Output Impacts in DEA: Production Considerations and Resource Sharing Among Business Sub-Units.- Super-efficiency in Data Envelopment Analysis.- DEA Models with Undesirable Inputs.- Frontier Differences and the Global Malmquist Index.
Professor Joe Zhu is one of the prominent researchers in the field of Data Envelopment Analysis (DEA). His research interests are in the areas of operations and business analytics, productivity modeling, and performance evaluation and benchmarking. He has published over 100 articles in peer-reviewed journals including Operations Research, Sloan Management Review, European Journal of Operational Research, Journal of the Operational Research Society, Naval Research Logistics, IIE Transactions, Journal of Banking and Finance, OMEGA, and others. He is an Area Editor of OMEGA, an Associate Editor of INFOR, and the Associate Series Editor of Springer's International Series in Operations Research and Management Science.
He is a Japan Society for Promotion of Science (JSPS) fellow and a William Evans Visiting Fellow of University of Otago, New Zealand. His research has been supported by KPMG Foundation, National Institute of Health, and Department of Veterans Affairs.