G. Peter Zhang
Department Chair and Professor Department of Management- Education
- Ph.D., Kent State University
- M.S., East China Normal University
- B.S., East China Normal University
- Specializations
- operations management
- supply chain management
- neural networks
- Biography
G. Peter Zhang is Professor and Chair of the Department of Management. His research focuses on developing and applying decision-making tools such as artificial neural networks, time series models, and game theory to help solve operations problems in forecasting, inventory management, quality management, project management, and supply chain management.
Dr. Zhang’s research has appeared in top or leading journals such as Annals of Operations Research, Decision Sciences, European Journal of Operational Research, IIE Transactions, IEEE Transactions on Engineering Management, IEEE Transactions on Neural Networks, International Journal of Forecasting, Neurocomputing, Production and Operations Management, Safety Science, Service Science, and others. According to Google Scholar, Dr. Zhang’s research work has been cited over 22,000 times. He was ranked among the World’s Top 2% Most Cited Business Researchers in 2020 and 2023 by the Meta-Research Innovation Center at Stanford University.
Dr. Zhang has been recognized as a “key thinker” in the neural network forecasting area and “one of the top researchers in the area of applied neural computing.” His research has won several awards such as the Distinguished Paper Award, Outstanding Paper Award, and Best Paper Award and has been funded by the International Institute of Forecasters and SAS. The Robinson College of Business has recognized his research accomplishments, presenting him its college-wide award for excellence in research on three separate occasions. He has served or been serving as an Associate Editor or a member of Editorial Board for more than 10 scholarly journals such as Decision Analytics Journal, Decision Sciences, IEEE Transactions on Neural Networks, Neurocomputing, Decision Sciences, and Production and Operations Management.
Dr. Zhang also received the Robinson College of Business’s Faculty Recognition Award for Distinguished Contributions in Service and the Top Professor Award for his teaching in the M.S. in Managerial Sciences Cohort.
- Publications
- Xia, Y., T. Xiao, and G. P. Zhang, Service Investment and Channel Structure Decisions in Competing Supply Chains. Service Science, 11 (1), 57-74, 2019.
- Xia, Y., T. Xiao, and G. P. Zhang, The Impact of Product Returns and Retailer’s Service Investment on Manufacturer’s Channel Strategies. Decision Sciences, 48 (5), 918-955, 2017.
- Xia, Y., V. Singhal and G. P. Zhang, “Product Design Award and the Market Value of the Firm.” Production and Operations Management, 25 (6), 1038-1055, 2016.
- Zhang, G. P., J. Yu, and Y. Xia, “The Payback of Innovation: Empirical Evidence from Firms that Have Won Innovation Awards.” Production and Operations Management, 23 (8), 1401-1420, 2014.
- Zhang, G. P. and Y. Xia, “Does Quality Still Pay? A Reexamination of the Relationship between Effective Quality Management and Firm Performance.” Production and Operations Management, 22 (1), 120-136, 2013.
- Xia, Y. and G. P. Zhang, “The Impact of Online Channel on Retailer’s Performances.” Decision Sciences, 41 (3), 517-546, 2010.
- Zhang, G. P., C. Hill, Y. Xia, and F. Liang, “Modeling the Relationship between EDI Implementation and Firm Performance Improvement with Neural Networks.” IEEE Transactions on Automation Science and Engineering, 7 (1), 96-110, 2010.
- Zhang, G. P., “Avoiding Pitfalls in Neural Network Research,” IEEE Transactions on Systems, Man, and Cybernetics, 37, 3-16, 2007. (Lead Article).
- Berardi, V. L. and G. P. Zhang, “An Empirical Investigation of Bias and Variance in Time Series Forecasting: Modeling Considerations and Error Evaluation,” IEEE Transactions on Neural Networks, 14 (3), 668-679, 2003.
- Zhang, G. P., “Time Series Forecasting Using A Hybrid ARIMA and Neural Network Model,” Neurocomputing, 50, 159-175, 2003.
- Zhang, G. P., “Neural Networks for Classification: A Survey,” IEEE Transactions on Systems, Man, and Cybernetics, 30 (4), 451-462, 2000.
- Zhang, G., B. E. Patuwo and M. Y. Hu, “Forecasting with Artificial Neural Networks: The State of the Art,” International Journal of Forecasting, 14 (1), 35–62, 1998.