Faculty

I have a PhD in Operations Management from, the University of Alabama. My research focuses on helping businesses understand the consequences of uncertainty and risk and help predict the efficacy of potential mitigation techniques. To that end, I create stylized and practical mathematical models and develop novel solution methodologies and analyses. My research uses non-linear programming, linear programming, integer programming (including branch-and-price), and statistical modeling. I create useful models to make both strategic and online decisions, as well as behavioral models and experiments to investigate the potential effect of decision-makers on the ability of firms to make optimal choices.

Research Interests:
Supply Chain Optimization, Transportation and Logistics, Vehicle Routing, Retail Analytics

Courses Taught:
Decision Science, Logistics and Supply Chain Management, Quantitative Fundamentals for Analytics, Optimization for Analytics

Select Publications/Grants/Awards:
Leveraging Concurrent Sourcing for Risk Mitigation and Pricing (2022)

Website: 
tcassidey.github.io

Yuanyuan Gao is an Assistant Professor at the College of Business and Economics, at California State University, East Bay. She received her Ph.D. in Information Systems from the University of Utah and her M.S. in Information Systems and Operations Management from the University of Florida. Her research focuses on data and network mining, business analytics, machine learning, and cost-sensitive learning. Gao has published papers in Management Information Systems Quarterly, Decision Support Systems, Information Systems Frontiers, and Journal of International Technology and Information Management.

Research Interests:
Health information technology (HIT), social media network analysis, real estate, and online marketing

Courses Taught:
Data Mining, Database Management Systems (Database and SQL), IT Management, Data Warehousing & BI, Big Data Tech. & Apps

Select Publications/Grants/Awards:
Yuanyuan Gao, Anqi Xu, Paul Jen-Hwa Hu, “Mining Patient-Generated Content for Medication Relations and Transition Network to Predict the Rankings and Volumes of Different Medications” Information Systems Frontiers (ISF), Published in September 2024;

Bo Wen, Paul Jen-Hwa Hu, Yuanyuan Gao “Examining the Effects of Usage Intensity on Cyberbullying Intention in Online Social Network Platforms: A Commitment Perspective” International Journal of Business Information Systems, Accepted in August 2023, and Forthcoming in 2024

Yuanyuan Gao, Anqi Xu, “How do Aspects of Chain Restaurants Affect the Overall Rating: Trip- Advisor Multi-dimensional Rating System Analysis” Journal of International Technology and Information Management (JITIM), Published in April 2022;

Xiao Fang*, Yuanyuan Gao* and Paul Jen-Hwa Hu* (These three authors have equal contributions to this project) “A Prescriptive Analytics Method for Cost Reduction in Clinical Decision Making” Management Information Systems Quarterly (MISQ), published in March 2021.

Yuanyuan Gao, Anqi Xu, Paul Jen-Hwa Hu, and Tsang-Hsiang Cheng. “Incorporating Association Rule Networks in Feature Category-Weighted Naive Bayes Model to Support Weaning Decision Making.” Decision Support Systems 96 (2017): 27-38.

Dr. Guo is an Assistant Professor in the Department of Management at California State University, East Bay. He holds a Ph.D. in Operations Management from the University of Alabama and specializes in supply chain network design, business analytics, and machine learning in business applications.

Research Interests:
Supply chain network design, optimization, and machine learning in business applications

Courses Taught:
Data Analytics, Optimization and Simulation, Machine Learning for Business Analytics, Operations Analytics

Select Publications/Grants/Awards:
"Designing a centralized distribution system for omnichannel retailing", Production and Operations Management

Inkyu Kim is an Assistant Professor in the College of Business and Economics at California State University, East Bay. He received his PhD in 2022 at the Broad College of Business at Michigan State University. His research includes routine dynamics and process management with particular emphasis on the role of contextual factors in processes.

Research Interests:
Routine Dynamics, Organizational Routines, Dynamic Network Analysis, Business Process Management

Courses Taught:
Deep Learning in Business Applications, Tech Fundamental for Business Analytics, Data Mining, Information Technology Management, E-Business Tech & Management, Operations Management

Select Publications/Grants/Awards:
Kim, I., Pentland, B.T., Frank, K.A., & Wolf, J.R. (2024) “Path coherence and disruption in routine dynamics”. Organization Science, forthcoming.

Pentland, B. T., Yoo, Y., Recker, J., & Kim, I. (2022). From lock-in to transformation: A path-centric theory of emerging technology and organizing. Organization Science, 33(1), 194-211.

Wolf, J. R., Kim, I., Xie, Y., Pentland, A. P., & Pentland, B. T. (2021). Suitability of Clinical Workflows for automation. Journal of Investigative Dermatology, 141(5), S66.

Wolf, J. R., Xie, Y., Kim, I., Pentland, A. P., & Pentland, B. T. (2020). Visit Complexity Reflects Billed Level of Service and Documentation Burden, Journal of Investigative Dermatology, 140 (7), S63.

Dr. Zinovy Radovilsky is a Professor of Management at the College of Business and Economics (CBE), California State University, East Bay. As a former chair of the Management Department, he played a pivotal role in developing and launching the Master of Science in Business Analytics (MSBA) program at CBE. For several years, Dr. Radovilsky also served as a coordinator of the Operations/Supply Chain Management and Analytics group of faculty in the Management Department. He has published over 40 research papers in peer-reviewed journals, four book chapters, and one textbook.

Research Interests:
Data Mining and Machine Learning, Time Series Forecasting, Operations and Supply Chain Optimization, Education and Curriculum Development in Business Data Analytics, Operations and Supply Chain Management

Courses Taught:
Optimization Methods in Analytics, Data Mining, Time Series Analytics, Data Sciences, Enterprise Resource Management and Planning, Operations Management, Service Management, Quality Management

Selected Recent Publications:
Radovilsky, Z. and Hegde V., “Student Performance in Different Modes of Online and In-person Assessments and Impact on Academic Integrity”, Curriculum and Teaching, Vol. 38, No 2, 2023, 73-92.

Radovilsky, Z. and Hegde, V., “Contents and Skills of Data Mining Course in Analytics Programs”, Journal of Information Systems Education, Vol. 22, No. 2, Spring 2022, 182-194.

Radovilsky, Z., Taneja, P., and Sahay, P. “Data Envelopment Analysis and Analytics Software for Optimizing Building Energy Efficiency”, International Journal of Business Analytics, Vol. 9, No.1, 2022, 1-17.

Radovilsky, Z., Hegde, V., and Damle, L. “Data Mining in Business Education: Exploratory Analysis of Course Data and Job Market Requirements”, Journal of Supply Chain and Operations Management, Vol. 18, No.1, March 2020, 119-139.

Selected Awards:
The Alan Khade Best Paper award for the co-authored paper titled “ Analyzing Consumer Satisfaction of Online Grocery Retailing Process Using Consumer Reviews” at the 2024 Annual CSUPOM Conference, Pomona, 2024.

Best Paper Finalist award winner for 2022 in the Journal of Information Systems Education for the paper “Contents and Skills of Data Mining Courses in Analytics Programs.” The award and plaque were received in 2023.

CBE’s Marc Remmich Outstanding Faculty Award in Teaching, 2020.

CSUEB’s George and Miriam Philips Outstanding Professor Award, 2015.

I hold a PhD in Operations Management from the University of Rochester. I am interested in the broad area of economics of healthcare and its operations. Technology is now key to increasing the efficiency of healthcare delivery and I work on some insightful aspects in this area including telemedicine and mHealth. I teach courses related to analytics, operations, and supply chain management.

Research Interests:
Telemedicine, Health, Healthcare operations, Healthcare technology, Healthcare Supply Chain, Patient Scheduling, Capacity allocation

Select Publications/Grants/Awards:
Jong Youl Lee, Balaraman Rajan, and Abraham Seidmann, Optimal location of remote dental units, European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2023.07.025

Balaraman Rajan, Arvind Sainathan, Saligrama Agnihothri, and Leon Cui (2022). The promise of mHealth for chronic disease management under different payment systems, Manufacturing & Service Operations Management (M&SOM), 24(6):3158-3176.

Dinesh R Pai, Balaraman Rajan, and Subhajit Chakraborty (2022). Do EHR and HIE deliver on their promise? Analysis of Pennsylvania acute care hospitals. International Journal of Production Economics, 245, 108398. https://doi.org/10.1016/j.ijpe.2021.108398

Balaraman Rajan, Tolga Tezcan, and Abraham Seidmann, Service systems with heterogeneous customers: Investigating the effect of telemedicine on patient care (2019). Management Science, 65(3):1236-67.

Balaraman Rajan, Abraham Seidmann, and Ray Dorsey, The competitive business impact of using telemedicine for the treatment of patients with chronic conditions (2013). Journal of Management Information Systems, 30(2): 127-157.

Dorsey ER, Venkataraman V, Grana MJ, Bull MT, George BP, Boyd CM, Beck CA, Rajan B, Seidmann A, Biglan KM. Randomized controlled clinical trial of “virtual house calls” for Parkinson's disease (2013). The Journal of the American Medical Association (JAMA) Neurology. 70(5): 565-70.

Lan Wang is an Associate Professor of Management at California State University East Bay. She holds a Ph.D. in Information Systems & Operations Management from the University of Florida and a Bachelor of Engineering in Industrial Engineering from Tsinghua University, Beijing. Lan studies sustainability issues in Supply Chain, interfaces between Operations Management and Marketing, Information Systems, and Business Analytics. Lan’s research has been published in top business journals such as Production and Operations Management and Decision Sciences. She won the Marv Remmich Research Award in 2020. Lan has teaching experiences in Operations Management, Supply Chain Analytics, and Data Analytics/Visualization. Her prior working experience includes IE intern at Nissan Motor Corporation and Supply Chain Consultant at the headquarters of Chick-fil-A, Inc.

Research Interests:
Supply Chain Management, Interfaces between OM and Marketing, Business Analytics, Information Systems

Courses Taught:
Business Analytics, Operations Data Analytics, Operations Management

Select Publications/Grants/Awards:
Production and Operations Management, Decision Sciences, Transportation Research

My academic background includes a Ph.D. in Business Administration from the University of Illinois at Urbana-Champaign, and an M.A. in Economics from Peking University, China. Over the years, I have been honored with several prestigious awards, such as a finalist for the Decision Sciences Journal's Best Paper Award. I am a lifetime member of the Association for the Advancement of Artificial Intelligence (AAAI). I am proud to have co-founded our MS Business Analytics program and served as its director/coordinator from 2015 to 2022. Nothing brings me more joy than witnessing our students' career successes, with many securing positions at top-tier companies, including the Magnificent Seven.

Research Interests:
Application of machine learning and artificial intelligence in various business domains, including but not limited to supply chain management, electric vehicles, and the real estate market.

Courses Taught:
Machine Learning, Optimization, Quant Fundamentals, Capstone

Select Publications/Grants/Awards:
I have published extensively in esteemed journals such as the International Journal of Production Research, the International Journal of Production Economics, and the Decision Sciences Journal.

Jiming Wu is a Full Professor at California State University, East Bay. He received his B.S. from Shanghai Jiao Tong University, M.S. from Texas Tech University, and Ph.D. from the University of Kentucky. His research interests include Artificial Intelligence, Big Data analytics, and IT adoption and acceptance. His work has appeared in MIS Quarterly, Journal of the Association for Information Systems, European Journal of Information Systems, Information & Management, Decision Support Systems, and elsewhere.

Research Interests:
Information and network security, Internet-based business applications and IT acceptance, Business Analytics and Big Data

Courses Taught:
Graduate Courses- Capstone Project, Technology Fundamentals for Analytics, Big Data Technology and Applications, Information Systems Management, Database Theory and Administration
Undergraduate Courses- Business Application Programming, Fundamentals of IS & Applications, Information Technology Management, Database Management and Application, Information Systems Development & Mgmt., Decision Science

Select Publications/Grants/Awards:
Marv Remmich Outstanding Faculty Award, College of Business & Economics, 2015

Outstanding New Researcher Award, California State University, East Bay, 2013

Wu, J. and Lederer, A. “A Meta-Analysis of the Role of Environment-Based Voluntariness in Information Technology Acceptance,” MIS Quarterly (33:2), 2009, 419-432.

Wu, J. and Lu, X. “Effects of Extrinsic and Intrinsic Motivators on Using Utilitarian, Hedonic, and Dual-Purposed Information Systems: A Meta-Analysis,” Journal of the Association for Information Systems (14:3), 2013, 153-191.

Wu, J. and Du, H. “Toward a Better Understanding of Behavioral Intention and System Usage Constructs” European Journal of Information Systems (21:6), 2012, 680-698.

Dr. Peng Xie is an Associate Professor at the College of Business and Economics, at California State University, East Bay. He received his Ph.D. in Business Administration and Management from Scheller College of Business at Georgia Institute of Technology.

Research Interests:
Social Media, Blockchain Technology, Financial Technology (FinTech), and Business Analytics

Courses Taught:
Text Analytics and Generative AI, Data Analytics with R, Database Management & Applications, Technology Fundamental for Analytics, Information Systems Analytics, Database Management & Applications, Business Application Programming, IS Development & Management, Information Technology Management, Fundamentals of Information Systems and Applications, Data Mining

Select Publications/Grants/Awards:
Peng Xie, Hongwei Du, Jiming Wu, Ting Chen, 2023. “The Failure of Online Endorsement Systems in Investment Communities: Evidence from Yahoo! Finance.” Information Technology & People

Peng Xie, 2022. “The Effect of Similarity and Dissimilarity on Information Network Formation and Their Implications in Accurate Information Identification.” Information & Management

Peng Xie, 2021. “The Interplay Between Investor Activity on Virtual Investment Community and the Trading Dynamics: Evidence From the Bitcoin
Market.” Information Systems Frontiers

Peng Xie, Hailiang Chen, Yu Jeffrey Hu. 2020. “Signal or Noise in Social Media Discussions: The Role of Network Cohesion in Predicting the Bitcoin Market.” Journal of Management Information Systems