Jiaru Bai
Assistant Professor
Assistant Professor
Operations and Decision Analytics
Office: 344 Harriman Hall
Email: jiaru.bai AT stonybrook.edu
Education:
Ph.D. in Operations and Decision Technologies, University of California, Irvine, 2017.
M.S. in Statistics, University of California, Irvine, 2014.
B.S. in Economics, Beijing University, 2012.
B.S. in Engineering, Beihang University, 2012.
Biography
Jiaru Bai is an assistant professor at the Stony Brook University College of Business. She received her Ph.D. in Management from the Paul Merage School of Business at the University of California, Irvine. She obtained a Master's degree in Statistics from UC Irvine, a B.S. degree in Engineering from Beihang University, and a double B.S. degree in Economics from Beijing University.
Her research interests lie in crowd-sourcing platforms, sustainability, and healthcare analytics. Her research projects apply economic and statistical models to analyze the tradeoffs between cost and effectiveness in various domains for both managers and individual decision-makers. Her research has been published in academic journals such as Manufacturing & Service Operations Management, Production and Operations Management, Decision Sciences, European Journal of Operational Research, Gynecologic Oncology, etc.
Publications
Hiding in Plain Sight: Surge Pricing and Strategic Providers
Jiaru Bai, Hans Sebastian (Seb) Heese, Manish Tripathy
Forthcoming at Production and Operations Management. (UTD 24, FT 50, ABDC A*) LINK
Concealing Borrowers’ Failure History in Online P2P Lending: A Natural Experiment
Jiaru Bai, Qiang Gao
Forthcoming at Decision Sciences. (ABDC A*) LINK
Can Two Competing On-demand Service Platforms be Profitable?
Jiaru Bai, Christopher S. Tang
International Journal of Production Economics, 2022 Oct; 250:108672. (ABDC A) LINK
Special Issue Celebrating Volume 250 of the International Journal of Production Economics
Optimal Subsidy Schemes and Budget Allocations for Government-Subsidized Trade-in Programs
Jiaru Bai, Shu Hu, Luyi Gui, Kut C. So, Zujun Ma
Production and Operations Management, 2021, 30(8):2689-706. (UTD 24, FT 50, ABDC A*) LINK
Retail Distribution Strategy with Outlet Stores
Jiaru Bai, Haresh Gurnani, Shuya Yin
Production and Operations Management, 2022, 31(1):281-303. (UTD 24, FT 50, ABDC A*) LINK
Coordinating Supply and Demand on an On-demand Service Platform with Impatient Customers
Jiaru Bai, Kut C. So, Christopher S. Tang, Xiqun (Michael) Chen, Hai Wang
Manufacturing & Service Operations Management, 2019, 21(3): 556-570. (UTD 24, FT 50, ABDC A*) LINK
MSOM Blog: Demand-Based Payout Ratio for Coordinating Supply and Demand on an On-Demand Ride Sharing Platform.
UCLA Anderson Review: Uber-Like Services: Variable Driver-Company Revenue Split Improves Profit.
Binghamton University SOM Magazine: Be ``Dynamic".
This work has received the 2017 POMS Supply Chain Management College Student Paper Competition First Prize.
Cost-effectiveness of maintenance therapy in advanced ovarian cancer: Paclitaxel, bevacizumab, niraparib, rucaparib, olaparib, and pembrolizumab.
Juliet E. Wolford, Jiaru Bai, Lindsey E. Minion, Robin Keller, et al.
Journal of Clinical Oncology 36, no. 15_suppl (May 20, 2018) 5508-5508. LINK
2018 Best of ASCO projects
This project has received the 2018 Conquer Cancer Foundation of ASCO/Sherwin Family Endowed Merit Award
Evaluating the cost-effectiveness of current FDA-approved PARP inhibitors for the treatment of recurrent ovarian cancer
Juliet E. Wolford, Jiaru Bai, Ramez H. Eskander, Robin L. Keller, et al.
Journal of Clinical Oncology 35, no. 15_suppl (May 2017) 5516-5516. LINK
Cancer Network: PARP Inhibitors Effective but Costly for Recurrent Ovarian Cancer.
Top 15 most accessed articles of 2017 (Society of Gynecology Oncology).
A queueing model for managing small projects under uncertainties
Jiaru Bai, Kut C. So, Christopher S. Tang
European Journal of Operational Research, 2016, 253(3): 777-790. (ABDC A*) LINK
Other Publications
Cost-effectiveness of niraparib, rucaparib, and olaparib for treatment of platinum-resistant, recurrent ovarian carcinoma
Juliet E. Wolford, Jiaru Bai, Kathleen N. Moore, et al.
Gynecologic Oncology, 2020, 157(2), 500-507. LINK
Comparing Markov and non-Markov alternatives for cost-effectiveness analysis: Insights from a cervical cancer case
Cristina del Campo, Jiaru Bai, L Robin Keller
Operations Research for Health Care, 2019, 21, 32-43. LINK
SOLO1 versus SOLO2: Cost-effectiveness of olaparib as maintenance therapy for newly diagnosed and platinum-sensitive recurrent ovarian carcinoma among women with germline BRCA mutations (gBRCAmut).
Juliet E. Wolford, Krishnansu Sujata Tewari, Su-Ying Liang, Jiaru Bai, et al.
Journal of Clinical Oncology 37, no. 15_suppl (May 20, 2019) 5545-5545. LINK
Time-based payout ratio for coordinating supply and demand on an on-demand service platform
Jiaru Bai, Kut C. So, Christopher S. Tang, Xiqun (Michael) Chen, Hai Wang
Sharing Economy: Making Supply Meet Demand. 2019:115-36. LINK
Evaluating the cost-effectiveness of current FDA-approved PARP inhibitors for the treatment of recurrent ovarian cancer
Juliet E. Wolford, Jiaru Bai, Ramez Hassef Eskander, Robin Keller, et al.
Journal of Clinical Oncology 35, no. 15_suppl (May 20, 2017) 5516-5516. LINK
Markov chain models in practice: A review of low cost software options.
Jiaru Bai, Cristina del Campo, Robin Keller
Investigación Operacional 38, no.1(2017). LINK
Lindsey Minion, John K. Chan, Bradley J. Monk, and Krishnansu Sujata Tewari. "A Markov model to evaluate cost-effectiveness of the PARP inhibitor, olaparib, for fourth-line treatment of recurrent ovarian cancer." (2016): 5563-5563.
Juliet E. Wolford, Jiaru Bai, Ramez Hassef Eskander, Robin Keller, et al.
Journal of Clinical Oncology 34, no. 15_suppl (May 20, 2016) 5563-5563. LINK
A Markov model to evaluate cost-effectiveness of antiangiogenesis therapy using bevacizumab in advanced cervical cancer
Lindsey E. Minion, Jiaru Bai, Bradley J. Monk, Robin L. Keller, et al.
Gynecologic Oncology, 2015, 137(3): 490-496. LINK
Teaching
Operations Management, UG
The objective of the course is to help students understand core concepts in operations management. Through a mixture of lectures, discussions, in-class exercises, and games, the course provides students with the tools and means to develop and manage efficient business processes that have the capacity to deliver high-quality products/services to meet their ever-changing customer demands in a timely and cost-effective manner.
Process Analytics, MSBA
Topics covered in the course include process flow analysis, flow-time analysis, capacity analysis, inventory analysis, and so on. By the end of the course, the students will learn the key concepts in process analytics, understand the complexity and challenges of process analytics, learn a set of core strategies and analytical models in process analytics, develop the ability to design the appropriate process model that fits into the business model of the company and the market needs.
Supply Chain Analytics, MSBA
The objective of the course is to help students develop a comprehensive understanding of the material, financial and information flow in a supply chain from the source of raw materials to the end customers.
Spreadsheet Modeling, UG/MBA
Improves students' decision-making ability in an uncertain and complex environment. Teaches techniques widely used to assess and manage risk, structure problems, determine the optimal decision and estimate the impact of a decision on performance measures of interest. Through cases, lectures and exercises, sharpens students' problem-solving skills and analytical and logical thinking ability.
Supply Chain Manamagement, UG/MBA
This course intends to provide students with an overview of the managerial aspects of Supply Chain Management and B2B e-business. The course integrates the perspectives on supply chain management from information systems, operations, marketing and finance. Topics include supply chain strategy, demand planning, inventory management, transportation, distribution, warehousing, and supply chain coordination. It uses lectures, readings, cases, and online simulation games.
Business Statistics, UG
This course covers the most important statistical techniques and discuss their applications. The course objectives are: To apply statistical methodologies to analyze a real-world decision-making problem; To understand and explain the results of statistical analysis to business managers in layman terms; To gain proficiency with a statistical software package.
Awards and Honors
2024, Top 10% of the Most Downloaded Papers Published in Decision Sciences, Wiley
2021-2022, Robinson-Lightcap Faculty Fellowship, Wake Forest University
2018, Best of ASCO Projects
2018, Conquer Cancer Foundation of ASCO/Sherwin Family Endowed Merit Award based on the project "Cost-effectiveness of maintenance therapy in advanced ovarian cancer: Paclitaxel, bevacizumab, niraparib, rucaparib, olaparib, and pembrolizumab"
2017, Top 15 Most Accessed Articles of 2017 by the Society of Gynecology Oncology
2017, Dean’s Honor Roll for Excellence in Teaching, Binghamton University, SUNY
2017, First Prize, Supply Chain Management College Student Paper Competition, POMS
2016, Ray Watson Fellowship, UC Irvine