Complete publication list, 91 works, newest first. Machine-readable: papers.json · works.bib (BibTeX) · research summaries.
2026
Lai, Jiayi, Leon Xu, Xin Fang, and Tinglong Dai. 2026. “Regulating Adaptive New Products: Can Less Oversight Lead to Better Development Practices?” Management Science, forthcoming. https://doi.org/10.2139/ssrn.5009572.
Ahmed, Mahnoor, Michael D. Abramoff, Harold P. Lehmann, Tinglong Dai, Risa M. Wolf, and Roomasa Channa. 2026. “Five-Year Cost-Effectiveness of AI for Adult Diabetic Eye Exams — A Health System Perspective.” npj Digital Medicine, forthcoming.
Dai, Tinglong, and Jayashankar M. Swaminathan. 2026. “Artificial Intelligence and Operations: A Foundational Framework of Emerging Research and Practice.” Production and Operations Management 35(9): 3255–3271. [lead article] https://doi.org/10.1177/10591478251412943.
Tinglong Dai, Kathryn M. McDonald, and Daniel C. Baumgart. 2026. “Global Advances in Health Artificial Intelligence: A Workforce Imperative.” The Lancet 408(10554): 572–576. PDF.
Yang, Haiyang, Tinglong Dai, and Risa M. Wolf. 2026. “Financial Incentives Increase Uptake and Perceived Effectiveness of Autonomous Medical AI, Yet Patients Still Seek Human Reconfirmation.” npj Digital Medicine 9: 587. https://www.nature.com/articles/s41746-026-02635-0.
Tinglong Dai. 2026. “The Sound We Haven’t Heard Before: A Commentary on ‘Fighting Fire with Fire: Infusing AI into Peer Review to Sustain Quality Scholarship’.” Management Science, ePub ahead of print, August 7, 2026.
Singh, Simrita, Naireet Ghosh, and Tinglong Dai. June 27, 2026. “Managing the Human Fallback: Skill Investment Under Improving AI and Worker Mobility.” Working paper. https://arxiv.org/abs/2606.29111.
Zhang, Minmin, Guihua Wang, and Tinglong Dai. 2026. “The Spillover Effect of Suspending Non-Essential Surgery: Evidence from Kidney Transplantation.” Management Science, ePub ahead of print. https://doi.org/10.1287/mnsc.2023.03624
Gilbert, Stephen, and Tinglong Dai. 2026. “Expert Perspectives on the Ecosystem of Medical AI Oversight in the GenAI Era.” npj Digital Medicine, 9: 395. https://www.nature.com/articles/s41746-026-02785-1. PDF
Gilbert, Stephen, and Tinglong Dai. 2026. “Expert Perspectives on US Regulatory Approaches to Large Language Models in Healthcare.” npj Digital Medicine, 9: 382. https://www.nature.com/articles/s41746-026-02787-z. PDF
Gilbert, Stephen, and Tinglong Dai. 2026. “Expert Perspectives on Recent US Digital Medicine Regulation Policy Changes and the TEMPO Pilot.” npj Digital Medicine, 9: 380. https://www.nature.com/articles/s41746-026-02786-0. PDF
Patil, Shefali V., Christopher G. Myers, and Tinglong Dai. 2026. “Protecting Clinical Value Judgment in the Age of AI.” npj Digital Medicine, 9: 269. https://www.nature.com/articles/s41746-026-02561-1. PDF
Patil, Shefali V., Tinglong Dai, and Christopher G. Myers. 2026. “The Hidden Costs of Outsourcing Judgment to AI Suppliers.” California Management Review Insights, March 10, 2026. https://cmr.berkeley.edu/2026/03/the-hidden-costs-of-outsourcing-judgment-to-ai-suppliers/. PDF
Hunt, Matthew S., Tinglong Dai, and Michael D. Abràmoff. 2026. “Evaluating Commercial Multimodal AI for Diabetic Eye Screening and Implications for an Alternative Regulatory Pathway.” npj Digital Medicine, 9: 42. https://www.nature.com/articles/s41746-025-02216-7. PDF
Zhong, Huaiyang, Guihua Wang, and Tinglong Dai. 2026. “Wheels on the Bus: Impact of Vaccine Rollouts on Demand for Public Transportation.” Production and Operations Management 35(3): 799–816. https://doi.org/10.1177/10591478251377162. [lead article]
Luan, Shujie, Shubhranshu Singh, and Tinglong Dai. August 12, 2026. “Algorithm Design and Physician Liability.” Working paper. https://doi.org/10.2139/ssrn.5046254.
Adida, Elodie, and Tinglong Dai. August 4, 2026. “Provider Payment Models for Transformative Technologies in Healthcare.” Working paper. http://dx.doi.org/10.2139/ssrn.5097711.
Dai, Tinglong, David Simchi-Levi, Michelle Xiao Wu, and Yao Xie. 2026. “Assured Autonomy: How Operations Research Powers and Orchestrates Generative AI Systems.” Production and Operations Management, ePub ahead of print, June 2026. https://doi.org/10.1177/10591478261455127.
Zuo, Ruiting, Tinglong Dai, and Jussi Keppo. 2026. “Incentive Design and Pricing Under Limited Inventory.” Manufacturing & Service Operations Management, ePub ahead of print, June 2026. https://doi.org/10.1287/msom.2026.0118.
Socal, Mariana P., Yunxiang Sun, Jeromie Ballreich, Joy Acha, Mohammad Ali Yazdi, Tinglong Dai, and Maqbool Dada. 2026. “Potential Impact of Tariffs on Active Pharmaceutical Ingredients on the Price of US-Made Generic Drugs.” Health Affairs Scholar 4(2), qxaf247. https://doi.org/10.1093/haschl/qxaf247. PDF
Bareamichael, Pineal, Tinglong Dai, Mariana P. Socal, and Gerard Anderson. 2026. “Balancing Opportunities and Risks of Artificial Intelligence in Drug Policy and Regulation.” American Journal of Health-System Pharmacy, zxag124. https://doi.org/10.1093/ajhp/zxag124.
Lee, Brian, Melissa Jay, Henry Fox, Jessica Padley, Tinglong Dai, and Adam S. Levin. 2026. “FDA-Cleared Artificial Intelligence Medical Devices in Orthopaedic Surgery.” JAAOS: Global Research and Reviews 10 (2): e25.00170. https://doi.org/10.5435/JAAOSGlobal-D-25-00170.
Gui, Luyi, and Tinglong Dai. 2026. “Power Couple? AI Growth and Renewable Energy Investment.” Working paper. https://doi.org/10.48550/arXiv.2603.26678.
2025
Dai, Tinglong, and Shubhranshu Singh. 2025. “Artificial Intelligence on Call: The Physician's Decision of Whether to Use AI in Clinical Practice.” Journal of Marketing Research 62(5): 854–875. https://doi.org/10.1177/00222437251332898.
Dai, Tinglong, Joseph C. Kvedar, and Daniel Polsky. 2025. “Policy Brief: Ambient AI Scribes and the Coding Arms Race.” npj Digital Medicine, Vol. 8, Article No. 780, Dec. 24, 2025. https://www.nature.com/articles/s41746-025-02272-z. PDF
Socal, Mariana P., Yunxiang Sun, Jeromie M. Ballreich, Jennifer Dailey Lambert, Tinglong Dai, and Maqbool Dada. 2025. “US Antibiotic Importation and Supply Chain Vulnerabilities.” JAMA Health Forum 6(10): e253871. Published online October 3, 2025. https://doi.org/10.1001/jamahealthforum.2025.3871. PDF
Li, Michael Lingzhi, and Tinglong Dai. 2025. “The Future in Sight: LumineticsCore and the First Autonomous AI for Diagnostics.” Harvard Business School Case. Product #: 626019-PDF-ENG.
Dai, Tinglong, and Simrita Singh. 2025. “Using Artificial Intelligence as Gatekeeper or Second Opinion: Designing Patient Pathways for Artificial Intelligence Augmented Healthcare.” Production and Operations Management, forthcoming. https://doi.org/10.1177/10591478251403269.
Dai, Tinglong, and Shubhranshu Singh. 2025. “Overdiagnosis and Undertesting for Infectious Diseases.” Marketing Science 44(2): 353–373. https://doi.org/10.1287/mksc.2022.0038.
In the press
- New York Timesand VoxEU
- Selected by COVID Economics as lead article of Issue 58
Lee, Branden, Patrick Kramer, Sara Sandri, Ritika Chanda, Crystal Favorito, Olivia Nasef, Joseph S. Ross, Joshua Sharfstein, Tinglong Dai. 2025. “Early Recalls and Clinical Validation Gaps in Artificial Intelligence–Enabled Medical Devices.” JAMA Health Forum 6(8): e253172. https://doi.org/10.1001/jamahealthforum.2025.3172. PDF
Yang, Haiyang, Tinglong Dai, Nestoras Mathioudakis, Amy M. Knight, Yuna Nakayasu, and Risa M. Wolf . 2025. “Peer Perceptions of Clinicians Using Generative AI in Medical Decision-Making.” npj Digital Medicine 8: 530. https://www.nature.com/articles/s41746-025-01901-x. PDF
Socal, Mariana P., Joy Acha, Chia-Yu Yang, Yunxiang Sun, Maqbool Dada, Tinglong Dai, Gerard Anderson, and Jeromie Ballreich. 2025. “Key Drivers and Mitigation Strategies of Oncology Drug Shortages 2023 to 2025.” The Cancer Journal 31(5). https://doi.org/10.1097/ppo.0000000000000791.
Martagan, Tugce, and Tinglong Dai. 2025. “Synergizing Artificial Intelligence and Operations Research for Advancements in Biomanufacturing.” Health Care Management Science, 28 (4): 930–935. https://doi.org/10.1007/s10729-025-09725-7.
Dada, Maqbool, Tinglong Dai, Yunxiang Sun, and Mariana Socal. 2025. “Tariffs as a Hidden Tax: Price Pass-through in Multi-Stage Supply Chains.” Working paper. http://doi.org/10.2139/ssrn.5237643.
Socal, Mariana, Maqbool Dada, and Tinglong Dai. 2025. “Prescription for Made in America? Tariffs and U.S. Drug Manufacturing.” Health Affairs Scholar 3(7), qxaf122. https://doi.org/10.1093/haschl/qxaf122. PDF
Ahmed, Mahnoor, Tinglong Dai, Roomasa Channa, Michael D. Abramoff, Harold P. Lehmann, and Risa M. Wolf. 2025. “Cost-Effectiveness of AI for Pediatric Diabetic Eye Exams from a Health System Perspective.” npj Digital Medicine 8: 3. https://www.nature.com/articles/s41746-024-01382-4. PDF
Sagona, Madeline, Tinglong Dai, Mario Macis, and Michael Darden. 2025. “Trust in AI-Assisted Health Systems and AI’s Trust in Humans.” npj Health Systems 2:10. https://www.nature.com/articles/s44401-025-00016-5.PDF
Cohen, Maxime C., Tinglong Dai, Georgia Perakis, Narendra Agrawal, Gad Allon, Robert Boute, Gérard Cachon, Zhe Chen, Morris Cohen, Rares Cristian, Vinayak Deshpande, Francis de Véricourt, Jan C. Fransoo, Joren Gijsbrechts, Pavithra Harsha, Ming Hu, Pınar Keskinocak, Caleb Kwon, Hau Lee, Sheng Liu, Konstantina Mellou, Ishai Menache, Jason Miller, Serguei Netessine, Tava Olsen, Jeevan Pathuri, Robert Peels, Yongzhi Qi, Ananth Raman, Anne Robinson, Max Shen, Masha Shunko, David Simchi-Levi, Hannah Smalley, Jeannette Song, Jayashankar M. Swaminathan, Christopher S. Tang, Sridhar Tayur, Maxi Udenio, Jan Van Mieghem, Lillian Yuqian Xu, Dennis Zhang. 2025.”Supply Chain Management in the AI Era: A Vision Statement from the Operations Management Community.” Manufacturing & Service Operations Management, 28 (3): 687--705. https://doi.org/10.1287/msom.2025.1065. [lead article]
Dai, Tinglong, and Terry Taylor. 2025. “Designing Enterprise AI Systems: Hallucination, Creativity, and Moral Hazard.” Working paper. https://doi.org/10.2139/ssrn.5996714.
Simchi-Levi, David, Tinglong Dai,Ishai Menache, and Michelle Xiao Wu. 2025. “Democratizing Optimization with Generative AI.” Working paper. https://doi.org/10.2139/ssrn.5511218.
Dai, Tinglong, Risa M. Wolf, and Haiyang Yang. 2025. “Unlearning in Medical AI: A New Frontier for Privacy, Regulation, and Trust.” Health Affairs Forefront. August 26. http://doi.org/10.1377/forefront.20250822.284476.
Lee, Branden, Shivam Patel, Crystal Favorito, Sara Sandri, Maria Rain Jennings, and Tinglong Dai. 2025. “Development and Commercialization Pathways of AI Medical Devices in the United States: Implications for Safety and Regulatory Oversight.” NEJM AI 2(7): AIra2500061. https://ai.nejm.org/doi/10.1056/AIra2500061. PDF
Wiberg, Holly, Tinglong Dai, Henry Lam, and Radhika Kulkarni. 2025. “Synergizing Artificial Intelligence and Operations Research: Perspectives from INFORMS Fellows on the Next Frontier.” INFORMS Journal on Data Science, ePub ahead of print. https://doi.org/10.1287/ijds.2025.0077.
Gilbert,Stephen, Tinglong Dai, and Rebecca Mathias. 2025. “Consternation as Congress Proposal for Autonomous Prescribing AI Coincides with the Haphazard Cuts at the FDA.” npj Digital Medicine 8: 165. https://www.nature.com/articles/s41746-025-01540-2.
Patel, Sohum, Steven Sparks, Di Dong, Tinglong Dai, and Brian Lee. 2025. “Emergence and Applications of FDA-Cleared Artificial Intelligence in Cardiovascular Care.” Circulation 152 (Suppl_3). https://doi.org/10.1161/circ.152.suppl_3.4345594.
2024
Adida, Elodie, and Tinglong Dai. 2024. “Impact of Physician Payment Scheme on Diagnostic Effort and Testing.” Management Science 70(8): 5408–5425. https://doi.org/10.1287/mnsc.2023.4937.
Abramoff, Michael, Tinglong Dai, and James Zou. 2024. “Scaling Adoption of Medical Artificial Intelligence: Reimbursement from Value-Based Care and Fee-for-Service Perspectives.” NEJM AI 1(5): AIpc2400083. https://ai.nejm.org/doi/10.1056/AIpc2400083. PDF
Ho, Cindy N., Tiffany Tian, Alessandra T. Ayers, Rachel E. Aaron, Vidith Phillips, Risa M. Wolf, Nestoras Mathioudakis, Tinglong Dai, and David C. Klonoff. 2024. “Qualitative Metrics from the Biomedical Literature for Evaluating Large Language Models in Clinical Decision-Making: A Narrative Review.” BMC Medical Informatics and Decision Making 24:357. https://doi.org/10.1186/s12911-024-02757-z.
Dai, Tinglong, and Christopher S. Tang. 2024. “De-Risking Global Supply Chains: Looking beyond Material Flows.” Asia Policy 19 (4): 153–176. https://doi.org/10.1353/asp.2024.a942841. Free PDF courtesy of the Hinrich Foundation
Dai, Tinglong, and Christopher S. Tang. 2024. “Natural Hazards and Supply Chain.” In Oxford Research Encyclopedia of Natural Hazard Science. D. Benouar (Ed), Oxford University Press. https://doi.org/10.1093/acrefore/9780199389407.013.512.
Dai, Tinglong, Hau L. Lee, and Christopher S. Tang. 2024. “Toward Supply-Chain-Aware ESG Measures.” In Responsible and Sustainable Operations: The New Frontier. C. S. Tang (Ed), pp. 235–252. Springer. https://doi.org/10.1007/978-3-031-60867-4_15.
2023
Dai, Tinglong, and Michael D.Abramoff. 2023. “Incorporating Artificial Intelligence into Healthcare Workflows: Models and Insights.” INFORMS TutORials in Operations Research, 133–155. https:/doi.org/10.1287/educ.2023.0257.
Abramoff,Michael D., Noelle Whitestone, Jennifer L. Patnaik, Emily Rich, Munir Ahmed, Lutful Husain, Mohammad Yeadul Hassan, Md. Sajidul Huq Tanjil, Dena Weitzman, Tinglong Dai, Brandie D. Wagner, David H. Cherwek, Nathan Congdon & Khairul Islam. 2023. “Autonomous Artificial Intelligence Increases Real-World Specialist Clinic Productivity in a Cluster-Randomized Trial.” npj Digital Medicine 6: 184. https://www.nature.com/articles/s41746-023-00931-7
2022
Wang, Guihua, Ronghuo Zheng, and Tinglong Dai. 2022. “Does Transportation Mean Transplantation? Impact of New Airline Routes on Sharing of Cadaveric Kidneys.” Management Science 68(5): 3660–3679. https://doi.org/10.1287/mnsc.2021.4103.
Honors
- Featured in Nobel laureate Al Roth’s Market Design blog
- Selected by Financial Times as a runner-up for the 2022 Responsible Business Education Awards
Mak, Ho-Yin, Tinglong Dai, and Christopher S. Tang. 2022. “Managing Two-Dose COVID-19 Vaccine Rollouts with Limited Supply: Operations Strategies for Distributing Time-Sensitive Resources.” Production and Operations Management 31 (12): 4424–4442. https://doi.org/10.1111/poms.13862.
Dai, Tinglong, Xiaofang Wang, and Chao-Wei Hwang. 2022. “Clinical Ambiguity and Conflicts of Interest in Interventional Cardiology Decision Making.” Manufacturing & Service Operations Management 24(2): 864–882. https://doi.org/10.1287/msom.2021.0969.
Honors
Honors
- Production and Operations Management Society (POMS) Best Healthcare Paper Award (Runner-Up), 2016
Dai, Tinglong, and Sridhar Tayur. 2022. “Designing AI-Augmented Healthcare Delivery Systems for Physician Buy-in and Patient Acceptance.” Production and Operations Management, 31 (12): 4443–4451.https://doi.org/10.1111/poms.13850.
Ahmadi, Farzin, Tinglong Dai, and Kimia Ghobadi. 2022. “You Are What You Eat: A Preference-Aware Inverse Optimization Approach.” Working paper. http://doi.org/10.2139/ssrn.4298746.
Balaguru, Logesvar, Chen Dun, Andrea Meyer, Sanuri Hennayake, Christi Walsh, Christopher Kung, Brittany Cary, Frank Migliarese, Tinglong Dai, Ge Bai, Kathleen Sutcliffe, and Martin Makary. 2022. “NIH Funding of COVID-19 Research in 2020: A Cross Sectional Study.” BMJ Open 12(5), e059041. http://dx.doi.org/10.1136/bmjopen-2021-059041
In the press
Lee, Soo-Hoon, Tinglong Dai, Phillip H. Phan, Nehama Moran, and Jerry Stonemetz. 2022. “The Association between Timing of Elective Surgery Scheduling and Operating Theater Utilization: A Cross-Sectional Retrospective Study.” Anesthesia & Analgesia 134 (3): 455-462. doi:10.1213/ane.0000000000005871.
Li, Yifu, Tinglong Dai, and Xiangtong Qi. 2022. A Theory of Interior Peaks: Activity Sequencing and Selection for Service Design. Manufacturing & Service Operations Management 24(2): 993–1001. https://doi.org/10.1287/msom.2021.0970.
Honors
- ◦ 2017 IBM Service Science Best Student Paper Award, Finalist
- ◦ 2018 POMS-HK International Conference, Best Student Paper Competition, Honorable Mention
Dai, Tinglong, and Christopher S. Tang. 2022. “Everybody Talks about Made in America. But It Isn’t That Simple.” Wall Street Journal. October 23. https://on.wsj.com/3zouROt.
Dai, Tinglong, and Christopher S. Tang. 2022. “Integrating ESG Measures and Supply Chain Management: Research Opportunities in the Post-Pandemic Era.” Service Science 14 (1): 1–12. https://doi.org/10.1287/serv.2021.0295. [lead article]
2021
Dai, Tinglong, and Jing-Sheng Song. 2021. “Transforming COVID-19 Vaccines into Vaccination.” Health Care Management Science 24 (3): 455–459. https://doi.org/10.1007/s10729-021-09563-3. [lead article]
Liljenquist, Dan, Tinglong Dai, and Ge Bai. 2021. “A Nonprofit Public Utility Approach to Enhance Next-Generation Vaccine Manufacturing Capacity.” Population Health Management 24 (5): 546–547. https://doi.org/10.1089/pop.2020.0377.
Jain, Amit, Tinglong Dai, Christopher G Myers, Punya Jain, and Shruti Aggarwal. 2021. “Prioritising Surgical Cases Deferred by the COVID-19 Pandemic: An Ethics-Inspired Algorithmic Framework for Health Leaders.” BMJ Leader 5 (2): 124–126. https://doi.org/10.1136/leader-2020-000343.
Dai, Tinglong, Katia Sycara, and Ronghuo Zheng. 2021. “Agent Reasoning in AI-Powered Negotiation.” Handbook of Group Decision and Negotiation, 2nd Edition. M. Kilgour and C. Eden (Eds), pp. 1187–1211. New York: Springer.
Dai, Tinglong, Rongzhu Ke, and Christopher Thomas Ryan. 2021. “Incentive Design for Operations-Marketing Multitasking.” Management Science 67 (4): 2211–2230. https://doi.org/10.1287/mnsc.2020.3651.
Yuan, Xuchuan, Tinglong Dai, Lucy Gongtao Chen, and Srinagesh Gavirneni. 2021. “Co-Opetition in Service Clusters with Waiting-Area Entertainment.” Manufacturing & Service Operations Management 23 (1): 106–122. https://doi.org/10.1287/msom.2019.0815.
In the press
- ◦ Featured by INFORMS Press Release and National University of Singapore
Dai, Tinglong, Muhammad H. Zaman, William Padula, and Patricia M. Davidson. 2021. “Supply Chain Failures amid Covid-19 Signal a New Pillar for Global Health Preparedness.” Journal of Clinical Nursing 30(1–2): e1–e3.
2020
Jain,Amit, Tinglong Dai, Kristin Bibee, and Christopher G. Myers. 2020. “Covid-19 Created an Elective Surgery Backlog. How Can Hospitals Get Back on Track?” Harvard Business Review, August 10, 2020. https://hbr.org/2020/08/covid-19-created-an-elective-surgery-backlog-how-can-hospitals-get-back-on-track.
Dai, Tinglong, and Sridhar Tayur. 2020. “OM Forum—Healthcare Operations Management: A Snapshot of Emerging Research.” Manufacturing & Service Operations Management 22 (5): 869–887. https://doi.org/10.1287/msom.2019.0778. [lead article]
Dai, Tinglong, and Shubhranshu Singh. 2020. “Conspicuous by Its Absence: Diagnostic Expert Testing under Uncertainty.” Marketing Science 39 (3): 540–563. https://doi.org/10.1287/mksc.2019.1201.
Dai, Tinglong, Ronghuo Zheng, and Katia Sycara. 2020. “Jumping the Line, Charitably: Analysis and Remedy of Donor-Priority Rule.” Management Science 66 (2): 622–641. https://doi.org/10.1287/mnsc.2018.3266.
Honors
- ◦ 2017 INFORMS Public Sector Operations Research Best Paper Award (First Place Winner)
Fattahi, Ali, Maqbool Dada, and Tinglong Dai. 2020. “A Subscription Model for Prescription Drugs.” Working paper. https://doi.org/10.2139/ssrn.3634063.
Wuest, Thorsten, Andrew Kusiak, Tinglong Dai, and Sridhar R. Tayur. 2020. “Impact of COVID-19 on Manufacturing and Supply Networks — The Case for AI-Inspired Digital Transformation.” Working report. https://doi.org/10.2139/ssrn.3593540.
In the press
- A shortened version, entitled “Impact of COVID-19: The Case for AI-Inspired Digital Transformation,” was published in the June 2020 issue of OR/MS Today and featured on the cover.
Chen, Ying-Ju, Tinglong Dai, C. Gizem Korpeoglu, Ersin Körpeoğlu, Ozge Sahin, Christopher S. Tang, and Shihong Xiao. 2020. “OM Forum—Innovative Online Platforms: Research Opportunities.” Manufacturing & Service Operations Management 22 (3): 430–445. https://doi.org/10.1287/msom.2018.0757. [lead article]
Dai, Tinglong, Ge Bai, and Gerard Anderson. 2020. “PPE Supply Chain Needs Data Transparency and Stress Testing.” Journal of General Internal Medicine 35(9): 2748-2749.
In the press
- Altmetric = 230 (as of July 2020); ranked No. 2 (the 98th percentile) of the 131 tracked articles of a similar age in Journal of General Internal Medicine and the 98th percentile of the 219,632 articles of a similar age in all journals
In the press
2019
Dai, Tinglong, Kelly Gleason, Chao‐Wei Hwang, and Patricia Davidson. 2019. “Heart Analytics: Analytical Modeling of Cardiovascular Care.” Naval Research Logistics 68 (1): 30–43. https://doi.org/10.1002/nav.21880.
Dai, Tinglong, and Kinshuk Jerath. 2019. “Salesforce Contracting under Uncertain Demand and Supply: Double Moral Hazard and Optimality of Smooth Contracts.” Marketing Science 38 (5): 852–70. https://doi.org/10.1287/mksc.2019.1171.
2017
Dai, Tinglong, Mustafa Akan, and Sridhar Tayur. 2017. “Imaging Room and beyond: The Underlying Economics behind Physicians’ Test-Ordering Behavior in Outpatient Services.” Manufacturing & Service Operations Management 19 (1): 99–113. https://doi.org/10.1287/msom.2016.0594.
Honors
- ◦ 2012 POMS Best Healthcare Paper Award (First Place Winner)
Dai, Tinglong, and Sridhar Tayur. 2017. “The Evolutionary Trends of POM Research in Manufacturing.” In Routledge Companion to Production and Operations Management. M. Starr and S. Gupta (Eds), pp. 647–662. London, U.K: Routledge. Link to preprint
2016
Dai, Tinglong, Soo-Haeng Cho, and Fuqiang Zhang. 2016. “Contracting for On-Time Delivery in the U.S. Influenza Vaccine Supply Chain.” Manufacturing & Service Operations Management 18 (3): 332–346. https://doi.org/10.1287/msom.2015.0574.
In the press
- ◦ Feature Article in the Summer 2016 issue of M&SOM
- ◦ Featured by Hub of Johns Hopkins University, Washington University in St. Louis Newsroom, and Pharmacy Times
Zheng, Ronghuo, Tinglong Dai, Katia Sycara, and Nilanjan Chakraborty. 2016. “Automated Multilateral Negotiation on Multiple Issues with Private Information.” INFORMS Journal on Computing 28 (4): 612–628. https://doi.org/10.1287/ijoc.2016.0701.
Dai, Tinglong, and Kinshuk Jerath. 2016. “Impact of Inventory on Quota-Bonus Contracts with Rent Sharing.” Operations Research 64 (1): 94–98. https://doi.org/10.1287/opre.2015.1461.
2013
Zheng, Ronghuo, Nilanjan Chakraborty, Tinglong Dai, and Katia Sycara. 2013. “Multiagent Negotiation on Multiple Issues with Incomplete Information.” In Proceedings of the 12th International Conference on Autonomous Agents and Multiagent Systems: AAMAS’13, 1279–1280. https://dl.acm.org/doi/10.5555/2484920.2485182.
Zheng, Ronghuo, Nilanjan Chakraborty, Tinglong Dai, Katia Sycara, and Michael Lewis. 2013. “Automated Bilateral Multiple-Issue Negotiation with No Information about Opponent.” In Proceedings of the 46th Hawaii International Conference on System Sciences. https://doi.org/10.1109/hicss.2013.626.
Dai, Tinglong, and Kinshuk Jerath. 2013. “Salesforce Compensation with Inventory Considerations.” Management Science 59 (11): 2490–2501. https://doi.org/10.1287/mnsc.2013.1809.
2012
Xu, Ying, Tinglong Dai, Katia Sycara, and Michael Lewis. 2012. “A Mechanism Design Model to Enhance Performance in Human-Multirobot Teams.” In Proceedings of the Annual Human Agent Robot Teamwork Workshop, Boston, MA.
In the press
- Cited as the first to propose “the idea of autonomous agents reporting problems to a central authority”
Sanchez-Anguix, Victor, Tinglong Dai, Zhaleh Semnani-Azad, Katia Sycara, and Vicente Botti. 2012. “Modeling Power Distance and Individualism/Collectivism in Negotiation Team Dynamics.” In Proceedings of the 45th Hawaii International Conference on System Sciences. https://doi.org/10.1109/hicss.2012.436.
2010
Xu, Ying, Tinglong Dai, Katia Sycara, and Michael Lewis. 2010. “Service Level Differentiation in Multi-Robots Control.” In Proceedings of 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems. https://doi.org/10.1109/iros.2010.5649366.
Dai, T. (2026). The Sound We Haven’t Heard Before: A Commentary on “Fighting Fire with Fire: Infusing AI into Peer Review to Sustain Quality Scholarship.” Management Science, mnsc.2026.02441. https://doi.org/10.1287/mnsc.2026.02441
Dada, M., Dai, T., Sun, Y., & Socal, M. (2025). Tariffs as a Hidden Tax: Price Pass-Through in Multi-Stage Supply Chains. SSRN. https://doi.org/10.2139/ssrn.5237643
Ahmadi, F., Dai, T., & Ghobadi, K. (2022). You are What You Eat: A Preference-Aware Inverse Optimization Approach. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4298746
Dai, T., Jain, A., Bibee, K., & Myers, C. G. (2020). COVID-19 Created an Elective Surgery Backlog. How Can Hospitals Get Back on Track? Harvard Business Review. https://hbr.org/2020/08/covid-19-created-an-elective-surgery-backlog-how-can-hospitals-get-back-on-track
Liljenquist, D., Dai, T., & Bai, G. (2021). A Nonprofit Public Utility Approach to Enhance Next-Generation Vaccine Manufacturing Capacity. Population Health Management, 24(5), 546–547. https://doi.org/10.1089/pop.2020.0377
Bareamichael, P., Dai, T., Socal, M., & Anderson, G. (2026). Balancing opportunities and risks of artificial intelligence in drug policy and regulation. American Journal of Health-System Pharmacy, zxag124. https://doi.org/10.1093/ajhp/zxag124
Balaguru, L., Dun, C., Meyer, A., Hennayake, S., Walsh, C., Kung, C., Cary, B., Migliarese, F., Dai, T., Bai, G., Sutcliffe, K., & Makary, M. (2022). NIH funding of COVID-19 research in 2020: a cross-sectional study. BMJ Open, 12(5), e059041. https://doi.org/10.1136/bmjopen-2021-059041
Dai, T., & Swaminathan, J. M. (2026). Artificial Intelligence and Operations: A Foundational Framework of Emerging Research and Practice. Production and Operations Management, 35(9), 3255–3271. https://doi.org/10.1177/10591478251412943
Dai, T., McDonald, K. M., & Baumgart, D. C. (2026). Global advances in health artificial intelligence: a workforce imperative. The Lancet, 408(10554), 572–576. https://doi.org/10.1016/S0140-6736(26)00693-8
Adida, E., & Dai, T. (2026). Provider Payment Models for Transformative Technologies in Healthcare [Working Paper]. Johns Hopkins University. https://doi.org/10.2139/ssrn.5097711
Lai, J., Xu, L., Fang, X., & Dai, T. (2026). Regulating Adaptive New Products: Can Less Oversight Lead to Better Development Practices? Management Science. https://doi.org/10.2139/ssrn.5009572
Yang, H., Dai, T., & Wolf, R. M. (2026). Financial incentives increase uptake and perceived effectiveness of autonomous medical AI, yet patients still seek human reconfirmation. Npj Digital Medicine, 9(1), 587. https://doi.org/10.1038/s41746-026-02635-0
Gui, L., & Dai, T. (2026). Power Couple? AI Growth and Renewable Energy Investment (2603.26678). arXiv. https://doi.org/10.48550/ARXIV.2603.26678
Singh, S., Ghosh, N., & Dai, T. (2026). Managing the Human Fallback: Skill Investment Under Improving AI and Worker Mobility (2606.29111). arXiv. https://doi.org/10.48550/arXiv.2606.29111
Dai, T., Sycara, K., & Zheng, R. (2021). Agent Reasoning in AI-Powered Negotiation. In D. M. Kilgour & C. Eden (Eds.), Handbook of Group Decision and Negotiation (pp. 1187–1211). Springer International Publishing. https://doi.org/10.1007/978-3-030-49629-6_26
Dai, T., Simchi-Levi, D., Wu, M. X., & Xie, Y. (2026). Assured Autonomy: How Operations Research Powers and Orchestrates Generative AI Systems. Production and Operations Management, 10591478261455127. https://doi.org/10.1177/10591478261455127
Wuest, T., Kusiak, A., Dai, T., & Tayur, S. R. (2020). Impact of COVID-19 on Manufacturing and Supply Networks — The Case for AI-Inspired Digital Transformation (Johns Hopkins University Working Paper ID 3593540). https://doi.org/10.2139/ssrn.3593540
Ho, C. N., Tian, T., Ayers, A. T., Aaron, R. E., Phillips, V., Wolf, R. M., Mathioudakis, N., Dai, T., & Klonoff, D. C. (2024). Qualitative Metrics from the Biomedical Literature for Evaluating Large Language Models in Clinical Decision-Making: A Narrative Review. BMC Medical Informatics and Decision Making, 24(1). https://doi.org/10.1186/s12911-024-02757-z
Dai, T., & Tang, C. S. (2024). De-Risking Global Supply Chains: Looking beyond Material Flows. Asia Policy, 19(4), 153–176. https://doi.org/10.1353/asp.2024.a942841
Lee, S.-H., Dai, T., Phan, P. H., Moran, N., & Stonemetz, J. (2022). The Association between Timing of Elective Surgery Scheduling and Operating Theater Utilization: A Cross-Sectional Retrospective Study. Anesthesia & Analgesia, 134(3), 455–462. https://doi.org/10.1213/ane.0000000000005871
Mak, H.-Y., Dai, T., & Tang, C. S. (2022). Managing Two-Dose COVID-19 Vaccine Rollouts with Limited Supply: Operations Strategies for Distributing Time-Sensitive Resources. Production and Operations Management, 31(12), 4424–4442. https://doi.org/https://doi.org/10.1111/poms.13862
Dai, T., & Song, J.-S. (2021). Transforming COVID-19 Vaccines into Vaccination. Health Care Management Science, 24(3), 455–459. https://doi.org/10.1007/s10729-021-09563-3
Dai, T., & Tang, C. S. (2022). Integrating ESG Measures and Supply Chain Management: Research Opportunities in the Postpandemic Era. Service Science, 14(1), 1–12. https://doi.org/10.1287/serv.2021.0295
Jain, A., Dai, T., Myers, C. G., Jain, P., & Aggarwal, S. (2021). Prioritising Surgical Cases Deferred by the COVID-19 Pandemic: An Ethics-Inspired Algorithmic Framework for Health Leaders. BMJ Leader, 5(2), 124–126. https://doi.org/10.1136/leader-2020-000343
Dai, T., & Singh, S. (2020). Conspicuous by Its Absence: Diagnostic Expert Testing under Uncertainty. Marketing Science, 39(3), 540–563. https://doi.org/10.1287/mksc.2019.1201
Dai, T., Zaman, M. H., Padula, W. V., & Davidson, P. M. (2021). Supply Chain Failures amid Covid-19 Signal a New Pillar for Global Health Preparedness. Journal of Clinical Nursing, 30(1--2), e1–e3. https://doi.org/10.1111/jocn.15400
Courtney, A., Howell, A.-M., Daulatzai, N., Savva, N., Warren, O., Mills, S., Rasheed, S., Milind, G., Tekkis, N., Gardiner, M., Dai, T., Safar, B., Efron, J. E., Darzi, A., Kontovounisios, C., & Tekkis, P. (2020). Colorectal Cancer Services during the COVID-19 Pandemic. British Journal of Surgery, 107(8), e255–e256. https://doi.org/10.1002/bjs.11706
Dai, T., & Jerath, K. (2019). Salesforce Contracting under Uncertain Demand and Supply: Double Moral Hazard and Optimality of Smooth Contracts. Marketing Science, 38(5), 852–870. https://doi.org/10.1287/mksc.2019.1171
Dai, T., Akan, M., & Tayur, S. (2017). Imaging Room and beyond: The Underlying Economics behind Physicians’ Test-Ordering Behavior in Outpatient Services. Manufacturing & Service Operations Management, 19(1), 99–113. https://doi.org/10.1287/msom.2016.0594
Zheng, R., Chakraborty, N., Dai, T., Sycara, K., & Lewis, M. (2013). Automated Bilateral Multiple-Issue Negotiation with No Information about Opponent. 2013 46th Hawaii International Conference on System Sciences, 520–527. https://doi.org/10.1109/hicss.2013.626
Xu, Y., Dai, T., Sycara, K., & Lewis, M. (2012). A Mechanism Design Model in Robot-Service-Queue Control with Strategic Operators and Asymmetric Information. 2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 6113–6119. https://doi.org/10.1109/CDC.2012.6426391
Dai, T., & Qi, X. (2007). An Acquisition Policy for a Multi-Supplier System with a Finite-Time Horizon. Computers & Operations Research, 34(9), 2758–2773. https://doi.org/10.1016/j.cor.2005.10.011
Xu, Y., Dai, T., Sycara, K., & Lewis, M. (2010). Service Level Differentiation in Multi-Robots Control. 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2224–2230. https://doi.org/10.1109/IROS.2010.5649366
Dai, T., Gleason, K., Hwang, C.-W., & Davidson, P. (2019). Heart Analytics: Analytical Modeling of Cardiovascular Care. Naval Research Logistics (NRL), 68(1), 30–43. https://doi.org/10.1002/nav.21880
Dai, T., & Tayur, S. (2022). Designing AI-Augmented Healthcare Delivery Systems for Physician Buy-in and Patient Acceptance. Production and Operations Management, 31(12), 4443–4451. https://doi.org/10.1111/poms.13850
Ahmed, M., Dai, T., Channa, R., Abràmoff, M. D., Lehmann, H. P., & Wolf, R. M. (2025). Cost-Effectiveness of AI for Pediatric Diabetic Eye Exams from a Health System Perspective. Npj Digital Medicine, 8(1). https://doi.org/10.1038/s41746-024-01382-4
Gilbert, S., Dai, T., & Mathias, R. (2025). Consternation as Congress Proposal for Autonomous Prescribing AI Coincides with the Haphazard Cuts at the FDA. Npj Digital Medicine, 8(1). https://doi.org/10.1038/s41746-025-01540-2
Sagona, M., Dai, T., Macis, M., & Darden, M. (2025). Trust in AI-Assisted Health Systems and AI’s Trust in Humans. Npj Health Systems, 2(1), 10. https://doi.org/10.1038/s44401-025-00016-5
Dai, T., Kvedar, J. C., & Polsky, D. (2025). Policy Brief: Ambient AI Scribes and the Coding Arms Race. Npj Digital Medicine, 8(1), 780. https://doi.org/10.1038/s41746-025-02272-z
Socal, M. P., Dada, M., & Dai, T. (2025). Prescription for Made in America? Tariffs and U.S. Drug Manufacturing. Health Affairs Scholar, 3(7), qxaf122. https://doi.org/10.1093/haschl/qxaf122
Hunt, M. S., Dai, T., & Abràmoff, M. D. (2026). Evaluating Commercial Multimodal AI for Diabetic Eye Screening and Implications for an Alternative Regulatory Pathway. Npj Digital Medicine, 9(1), 42. https://doi.org/10.1038/s41746-025-02216-7
Gilbert, S., & Dai, T. (2026). Expert Perspectives on Recent US Digital Medicine Regulation Policy Changes and the TEMPO Pilot. Npj Digital Medicine, 9(1), 380. https://doi.org/10.1038/s41746-026-02786-0
Gilbert, S., & Dai, T. (2026). Expert Perspectives on US Regulatory Approaches to Large Language Models in Healthcare. Npj Digital Medicine, 9(1), 382. https://doi.org/10.1038/s41746-026-02787-z
Gilbert, S., & Dai, T. (2026). Expert Perspectives on the Ecosystem of Medical AI Oversight in the GenAI Era. Npj Digital Medicine, 9(1), 395. https://doi.org/10.1038/s41746-026-02785-1
Zhang, M., Wang, G., & Dai, T. (2026). The Spillover Effect of Suspending Nonessential Surgery: Evidence from Kidney Transplantation. Management Science. https://doi.org/10.1287/mnsc.2023.03624
Zuo, R., Dai, T., & Keppo, J. (2026). Incentive Design and Pricing under Limited Inventory. Manufacturing & Service Operations Management. https://doi.org/10.2139/ssrn.3989971
Cohen, M. C., Dai, T., Perakis, G., Agrawal, N., Allon, G., Boute, R. N., Cachon, G. P., Chen, Z., Cohen, M., Cristian, R., Deshpande, V., De Véricourt, F., Fransoo, J. C., Gijsbrechts, J., Harsha, P., Hu, M., Keskinocak, P., Kwon, C., Lee, H., … Zhang, D. (2026). OM Forum—Supply Chain Management in the AI Era: A Vision Statement from the Operations Management Community. Manufacturing & Service Operations Management, 28(3), 687–705. https://doi.org/10.1287/msom.2025.1065
Patil, S. V., Myers, C. G., & Dai, T. (2026). Protecting Clinical Value Judgment in the Age of AI. Npj Digital Medicine, 9(1), 269. https://doi.org/10.1038/s41746-026-02561-1
Luan, S., Singh, S., & Dai, T. (2026). Algorithm Design and Physician Liability [Working Paper]. Johns Hopkins University. https://doi.org/10.2139/ssrn.5046254
Patil, S., Dai, T., & Myers, C. G. (2026). The Hidden Costs of Outsourcing Judgment to AI Suppliers. California Management Review Insights. https://cmr.berkeley.edu/assets/documents/pdf/2026-03-the-hidden-costs-of-outsourcing-judgment-to-ai-suppliers.pdf