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Mei Li

Mei Li.

Mei Li

Associate Professor of Supply Chain Management

About Li

Mei Li received a Ph.D. from Arizona State University, where she studied supply chain management. Her primary research interests include Supply network as a complex adaptive system, Big Data and Its Usage in Operations and Supply Chain Management, Sustainability, and Interdisciplinary service research. Her research has appeared in Manufacturing & Service Operations ManagementProduction and Operations ManagementJournal of Operations ManagementJournal of MarketingStrategic Management JournalDecision SciencesJournal of Supply Chain ManagementJournal of Business LogisticsData Science and Management Journal, etc. Her Journal of Marketing article received the Best Service Article Award in 2015. Li serves on the Editorial Review Board of the Journal of Supply Chain Management and is an Associate Editor for Data Science and Management Journal.

  • Supply networks
  • Big data applications
  • Sustainability in supply chains
  • Interdisciplinary service research

Publications

  • Li, M., Guo, H., Lee, C., & Shah, Rachna. (2024) Is In-Game Purchase a Guilty Pleasure? Negative Perceptions and Their Key Sources. Forthcoming at Production and Operations Management.

  • Huang, Y., Li, M., Tsung, F. (2024) Mining Social Media Data via Supervised Topic Model: Can Social Media Posts Inform Customer Satisfaction? Forthcoming at Decision Sciences.

  • Yang, Y., Wu, Y., Chang, X., Li, M., Tan, Y. (2024) Toward a Fairness-Aware Scoring System for Algorithmic Decision-Making. Forthcoming at Production and Operations Management Journal

  • Wang, Y., Li, M., Ma, N., Zhang, H. (2024). Product Service Outsourcing: Impact of Environmental Uncertainty and Partial Observability. Forthcoming at Manufacturing & Service Operations Management.

  • Yan, Z., Li, M., Ni, J., McFadden, K. (2024). Examining Network Entry Decisions in Healthcare: Network and Organizational Characteristics. Decision Sciences 55(1): 68-87.

  • Li, M., Guo, H., Lee, C., & Shah, Rachna. (2024) Is In-Game Purchase a Guilty Pleasure? Negative Perceptions and Their Key Sources. Forthcoming at Production and Operations Management.
  • Huang, Y., Li, M., Tsung, F. (2024) Mining Social Media Data via Supervised Topic Model: Can Social Media Posts Inform Customer Satisfaction? Forthcoming at Decision Sciences.
  • Yang, Y., Wu, Y., Chang, X., Li, M., Tan, Y. (2024) Toward a Fairness-Aware Scoring System for Algorithmic Decision-Making. Forthcoming at Production and Operations Management Journal
  • Wang, Y., Li, M., Ma, N., Zhang, H. (2024). Product Service Outsourcing: Impact of Environmental Uncertainty and Partial Observability. Forthcoming at Manufacturing & Service Operations Management.
  • Yan, Z., Li, M., Ni, J., McFadden, K. (2024). Examining Network Entry Decisions in Healthcare: Network and Organizational Characteristics. Decision Sciences 55(1): 68-87.
  • Li, M, Choi, T., Sanders, N., Falcone, E., & Chang, X. (2021). The role of people in buyer–supplier collaboration: Strategic model vs. people-centric model. In PressJournal of Purchasing and Supply Management.
  • Li, M., Alam., Z., Bernardes, E., Giannoccaro, I., Skilton, P., Rahman., M. S. (2021). Out of Sight, Out of Mind? Modeling the Impacts of Financial Squeeze on Extended Supply Chain Networks. Forthcoming at Journal of Business Logistics.
  • Li, M., Arifin, S. M. N., Devaraj, S., Madey, G. R., & Casetti, A. (2021). An exploratory study of the growth of the accountable care organization and its impact on physician groups’ profit: A complex adaptive system approach. In PressData Science and Management Journal.
  • Chang, X., Huang, Y., Li, M., Bo, X., & Kumar, S. (2020). Efficient Detection of Environmental Violators: A Big Data Approach. Forthcoming at Production and Operations Management Journal.
  • Skilton, P. F., Bernardes, E., Li, M., & Creek, S. A. (2020). The Structure of Absorptive Capacity in Three Product Development Strategies. Journal of Supply Chain Management, 56(3), 47-65.
  • Li, M., Wu, Y., He, Y., Huang, S., & Nair, A. (2020). Sparse inverse covariance estimation: a data mining technique to unravel holistic patterns among business practices in firms. Decision Sciences Journal, 51(4), 1046-1073.
  • Dong, B., Li, M., & Sivakumar, K. (2019). Online review characteristics and trust: A cross-country examination. Decision Sciences Journal, 50(3), 537-566.
  • Li, M., Lin, Y., Huang, S., & Crossland, C. (2016). The use of sparse inverse covariance estimation for relationship detection and hypothesis generation in strategic management. Strategic Management Journal, 37(1), 86–97.
  • Sivakumar, K., Li, M., & Dong, B. (2014). Service quality: The impact of frequency, timing, proximity, and sequence of failures and delights. Journal of Marketing, 78(1), 41–58.
  • Li, M., Choi, T. Y., Rabinovich, E., & Crawford, A. (2013). Inter-customer interactions in self-service setting: Implications for perceived service quality and repeat purchasing intentions. Production and Operations Management Journal, 22(4), 888–914.
  • Barratt, M., Choi, T. Y., & Li, M. (2011). Qualitative case studies in operations management: Trends and future research implications (1992–2007). Journal of Operations Management 29(4), 329–342.
  • Li, M., & Choi, T. Y. (2009). Triads in services outsourcing: Bridge, bridge decay and bridge transfer. Journal of Supply Chain Management, 45(3), 27–39.

About OU's Price College of Business

The University of Oklahoma Michael F. Price College of Business has experienced significant growth over the past five years, becoming OU’s second-largest college with over 7,000 students. The college offers highly ranked undergraduate, master’s, executive and doctoral programs across six academic divisions. More information is available at price.ou.edu