A uni­fy­ing theme of my research is how oper­a­tional constraints/frictions inter­act with strate­gic deci­sion-mak­ing. I gained this per­spec­tive through work­ing in the health­care domain, where I came to real­ize that indi­vid­u­als and orga­ni­za­tions rarely make deci­sions in a free-form fash­ion. Rather, they oper­ate under con­vo­lut­ed and evolv­ing con­straints that define the healthcare ecosystem. This real­iza­tion has led me to study top­ics at the macro (pol­i­cy mod­el­ing), meso (sup­ply-chain con­tract­ing), and micro (physi­cian behav­ior) levels:

• At the macro lev­el, my health­care research on pol­i­cy mod­el­ing is relat­ed to organ trans­plan­ta­tion. I have stud­ied organ donation, which is essen­tial to expand organ sup­ply but has received lit­tle atten­tion from the organ trans­plan­ta­tion lit­er­a­ture that focus­es on organ allo­ca­tion. I’ve also added to the empirical underpinning of the organ trans­plan­ta­tion lit­er­a­ture, which had pre­vi­ous­ly been large­ly the­o­ret­i­cal. My work helps inform pol­i­cy­mak­ers by high­light­ing oper­a­tional con­straints threat­en­ing to hold back the organ trans­plan­ta­tion sys­tem that is not ready to accom­mo­date new policies.
• At the meso lev­el, health­care orga­ni­za­tions’ deci­sions, espe­cial­ly those relat­ed to sup­ply-chain con­tract­ing, inter­act with logis­tics con­straints. In the case of the US influenza vaccine supply chain, I have stud­ied how a key oper­a­tional metric—on-time deliv­ery performance—molds the inter­ac­tion between health­care providers and phar­ma­ceu­ti­cal firms. I have also stud­ied an inno­v­a­tive Netflix-like contracting model through which health­care providers gain wider access to pre­scrip­tion drugs essen­tial to pub­lic health. Recent­ly, amid the COVID-19 pan­dem­ic, my work reveals how a lack of data avail­abil­i­ty has con­tributed to short­ages of personal protective equipment (PPE).
• At the micro lev­el, physi­cians make impor­tant resource-pro­vi­sion deci­sions. Accord­ing­ly, my work at this lev­el focus­es on mod­el­ing physi­cian behav­ior. The top­ics I have stud­ied include physi­cians’ test-ordering behavior in an out­pa­tient set­ting, in which they choose the inten­si­ty of care based on clin­i­cal, finan­cial, and oper­a­tional con­sid­er­a­tions. Anoth­er top­ic involves diag­nos­ti­cians who rely on refer­rals from their peers and hence have rep­u­ta­tion­al con­cerns. I show diag­nos­ti­cians may strategically under-test to sig­nal their skill lev­els. In an interventional cardiology set­ting, I have stud­ied how physi­cians deter­mine their diag­nos­tic path­ways when more advanced tests reduce clin­i­cal uncer­tain­ty but may hurt their revenues.

While focus­ing on health­care, my the­o­ret­ic inter­est in infor­ma­tion eco­nom­ics has led me to con­tribute to the mar­ket­ing-oper­a­tions inter­faces lit­er­a­ture: In con­trast to this lit­er­a­ture that focus­es on how mar­ket­ing con­sid­er­a­tions influ­ence oper­a­tional deci­sions, I study how oper­a­tional con­straints influ­ence mar­ket­ing deci­sions. In a series of papers pub­lished in 2013, 2016, and 2019, I have chal­lenged the assump­tion that the sup­ply is unbound­ed and shown the strik­ing strate­gic role of lim­it­ed inven­to­ry in incen­tive design. More recent­ly, I have stud­ied an operations-marketing multitasking prob­lem moti­vat­ed by the retail setting.

Below are sev­er­al links via which you may dis­cov­er more about my research:

‣ Madeline Sagona, Tin­g­long Dai, Mario Macis, Michael Darden. 2025. Trust in AI-Assisted Health Systems and AI’s Trust in Humans. npj Health Sys­tems. March 28.

‣ Stephen Gilbert, Tin­g­long Dai, Rebecca Mathias. 2025. Consternation as Congress Proposal for Autonomous Prescribing AI Coincides With the Haphazard Cuts at the FDA. npj Dig­i­tal Med­i­cine. March 18.

‣ Segev Wasserkrug, Vinod Cheriyan, Tin­g­long Dai, Juan R. Jaramillo, Sven Koenig, Ramayya Krishnan, Radhika Kulkarni, Henry Lam, Fred Oswald, Thiago Serra, Mark S. Squillante, Anjana Susarla, Pascal Van Hentenryck, Holly Wiberg. 2025. A Prominent Role for INFORMS in the Age of AI: Bringing Together AI and OR/MS for Better Organizational and Societal Decision-Making. OR/MS Today. March 3.

‣ Tin­g­long Dai, Christopher S. Tang. 2025. How Tariffs Can Hurt American Supply Chains. Bal­ti­more Sun. Feb­ru­ary 25.

‣ Tin­g­long Dai. 2025. What to Watch in the Coming AI Policy Shake-Up. Deseret News. Jan­u­ary 18.

‣ Tin­g­long Dai, Christopher S. Tang. 2024. De-risking Global Supply Chains: Looking Beyond Material Flows. Asia Pol­i­cy 19 (4): 153–176. Octo­ber 25. [Free PDF courtesy of the Hinrich Foundation]

‣ Tin­g­long Dai. 2024. Supply Chain Resilience in the Age of Climate Change. Phar­ma Man­u­fac­tur­ing. Sep­tem­ber 25.

‣ Tin­g­long Dai. 2024. To Make Effective AI Policy You Must Trust Those Who’ve Been There. Fed­er­al News Net­work. June 11.

‣ Tin­g­long Dai, Michael Abramoff. 2024. Toward a Science of Scaling Medical Artificial Intelligence. Med­ical Eco­nom­ics. June 7.

‣ Tin­g­long Dai. 2024. History Says Tariffs Rarely Work, but Biden’s 100% Tariffs on Chinese EVs Could Defy the Trend. The Con­ver­sa­tion. May 17.

‣ Kofi Arhin, Tin­g­long Dai. 2024. The Class of 2024 and the Art of Generative AI. Inno­va­tion & Tech Today. May 1.

‣ Yuna Nakayasu, Tin­g­long Dai. 2024. Taking Geographical Luck Out of Emergency Care With AI: Generative AI With Vision Will Be Essential to the Future of Emergency Medicine. EMS1. April 29.

‣ Michael Abramoff, Tin­g­long Dai, James Zou. 2024. Scaling Adoption of Medical Artificial Intelligence: Reimbursement from Value-Based Care and Fee-for-Service Perspectives. NEJM AI 1(5): AIpc2400083. April 12.

‣ Tin­g­long Dai. 2024. Despite Fears, Supply-Chain Crisis from Key Bridge Collapse Can Be Averted. Bal­ti­more Ban­ner. March 28.

‣ Tej D. Azad, Tin­g­long Dai. 2024. Do No Harm — The Imperative for Purposeful AI Regulation in Health Care. Med­ical Eco­nom­ics. March 21.

‣ Tin­g­long Dai. 2023. U.S. Needs to Shore Up Medical Device Manufacture or Risk Vulnerability in Times of Crisis. Bal­ti­more Sun. Decem­ber 26.

‣ Tin­g­long Dai, Christopher S. Tang, Hau Lee. 2023. LEGO’s ESG Dilemma: Why an Abandoned Plan to Use Recycled Plastic Bottles Is a Wake-Up Call for Supply Chain Sustainability. The Con­ver­sa­tion. Octo­ber 5.

‣ Tin­g­long Dai, Christopher S. Tang. 2023. China Derisking Is Inevitable. To Minimize the Pain, Supply Chains Need a Revolution. Bar­ron’s. Sep­tem­ber 6.

‣ Tin­g­long Dai. 2023. The Role of Artificial Intelligence in Managing Postpandemic Supply-Chain Risks. Bio­Process Inter­na­tion­al 21(7–8), 56.

‣ Tin­g­long Dai, Christopher S. Tang. 2023. America’s Shaky Pharmaceutical Supply Chain Is a Prescription for Disaster. Bar­ron’s. June 28.

‣ Tin­g­long Dai. 2023. Generative AI Is Not Entertainment — It Is Already a Threat to Our Way of Life. The Hill. June 10.

‣ Tin­g­long Dai. 2023. Is It Legal for Generative AI to Use Copyrighted Material without Permission? CQ Researcher. April 21.

‣ Tin­g­long Dai, Christopher S. Tang. 2022. China’s Sudden Shift on Zero-Covid Puts Supply Chains at Risk Again. Bar­ron’s. Decem­ber 14.

‣ Lauren Murphy, Tin­g­long Dai. 2022. Prioritizing Women Supply Chain Workers in ESG Efforts. Bloomberg Law. Novem­ber 17.

‣ Tin­g­long Dai, Christopher S. Tang. 2022. Everybody Talks About Made in America. But It Isn’t That Simple. Wall Street Jour­nal. Octo­ber 23.

‣ Tin­g­long Dai, Ho-Yin Mak, Christopher S. Tang. 2022. Making EVs Without China’s Supply Chain Is Hard, but Not Impossible—3 Supply Chain Experts Outline a Strategy. The Con­ver­sa­tion. August 31.

◦ Repub­lished in MarketWatch

‣ Tin­g­long Dai, Ho-Yin Mak, Christopher S. Tang. 2022. With Monkeypox, the U.S. Is Repeating Its Covid Supply-Chain Mistakes. Bar­ron’s. August 19.

‣ Tin­g­long Dai, Kara Morgan. 2022. In Fight Against Monkeypox, Government Isn’t Learning From Past Experience. Chica­go Sun-Times. August 6.

‣ Tin­g­long Dai, Kara Morgan. 2022. The Food Safety System Is Failing. Indus­try Week. July 13.

‣ Tin­g­long Dai, Christopher S. Tang. 2022. The Baby Formula Crisis Shows the Urgent Need to Fix Supply Chain Resilience. Bar­ron’s. June 2.

‣ Tin­g­long Dai. 2022. Supply Chain Transparency: A Growth Engine in the Wake of Crises. CEVA Insights. April 19.

‣ Tin­g­long Dai, Christopher S. Tang. 2022. It's the End of the Global Supply Chain as We Know It. Newsweek. April 19.

‣ Tin­g­long Dai. 2022. Russia’s War With Ukraine Could Permanently Reshape the Global Supply Chain. Fast Com­pa­ny. March 15

◦ Orig­i­nal­ly pub­lished in The Conversation on March 11, 2022, with the title of “Ukraine War and Anti-Rus­sia Sanc­tions on Top of COVID-19 Mean Even Worse Trou­ble Lies Ahead for Glob­al Sup­ply Chains”

‣ Loges­var Bal­agu­ru, Chen Dun, Andrea Mey­er, Sanuri Hen­nayake, Christi Walsh, Christo­pher Kung, Brit­tany Cary, Frank Migliarese, Tin­g­long Dai, Ge Bai, Kathleen Sutcliffe, 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

◦ Fea­tured by New York Times

‣ Tin­g­long Dai, Shubhranshu Singh. 2022. Overdiagnosis and Undertesting for Infectious Diseases. Johns Hop­kins Uni­ver­si­ty Work­ing Paper. Jan­u­ary 21. https://doi.org/10.2139/ssrn.3725057.

◦ Fea­tured by New York Times and VoxEU
◦ Select­ed by COVID Economics as lead arti­cle of Issue 58

‣ Tin­g­long Dai, Christopher S. Tang. 2022. Unifying ESG and Supply Chain Thinking: An Urgent Call to Action in the Post-Pandemic Era. Asia­Glob­al Papers No. 5. Jan­u­ary 6. Asia Global Institute, Uni­ver­si­ty of Hong Kong.

‣ Tin­g­long Dai, Christopher S. Tang. 2021. The Infrastructure Bill Is Here. Can America Still Do Megaprojects?. Bar­ron’s. Novem­ber 16.

‣ Tin­g­long Dai, Christopher S. Tang. 2021. ESG Investing Has a Blind Spot That Puts the $35 Trillion Industry’s Sustainability Promises in Doubt: Supply Chains. The Con­ver­sa­tion. Novem­ber 9.

‣ Tin­g­long Dai, Kate Dwyer. 2021. Q+A: Supply Chain Issues Spike Shoppers’ Demands. The Hub (Johns Hop­kins Uni­ver­si­ty). Novem­ber 1.

‣ Dan Liljenquist, Tin­g­long Dai, Ge Bai. 2021. A Nonprofit Public Utility Approach to Enhance Next-Generation Vaccine Manufacturing Capacity. Pop­u­la­tion Health Man­age­ment 24(5), 546–547.

‣ Ravi Mittal, Surbhi Jain, Christopher G. Myers, Tin­g­long Dai, Amit Jain. 2021. A 100% COVID Vaccination Rate Is Possible – We Did It: The Raigarh Success Story Shows the Power of Behavioral and Motivational Strategies. Med­Page Today. Octo­ber 22.

‣ Sheldon H. Jacobson, Tin­g­long Dai. 2021. Lessons Learned From Hurricane Recovery Can Improve Supply Chains. The Hill. Sep­tem­ber 27.

‣ Tin­g­long Dai, Jeannette Song. 2021. Transforming COVID-19 Vaccines into Vaccination: Challenges and Opportunities for Management Scientists. Health Care Man­age­ment Sci­ence (3): 455–59. https://doi.org/10.1007/s10729-021-09563-3. [lead article] 

‣ Amit Jain, Tin­g­long Dai, Christopher G. Myers, Pun­ya Jain, 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.

‣ Guihua Wang, Tin­g­long Dai. 2021. Does a Rising Tide Lift All Boats? Kidney Transplantation through Surgery Suspension and Resumption. Johns Hop­kins Uni­ver­si­ty Work­ing Paper. April 12.

‣ Tin­g­long Dai. 2021. Why Johnson & Johnson Throwing Out 15 Million COVID-19 Vaccine Doses Shouldn’t Scare You. The Con­ver­sa­tion, April 1.

‣ Tin­g­long Dai, Christopher S. Tang, Ho-Yin Mak. 2021. Opinion: The Backlash Against Johnson & Johnson’s COVID-19 Vaccine Is Real and Risky — Here’s Exactly How To Make the Rollout a Success. Mar­ket­Watch. March 10.

◦ Read more than 700,000 times across The Con­ver­sa­tion and Mar­ket­Watch, among oth­er outlets

◦ Orig­i­nal­ly pub­lished in The Con­ver­sa­tion on March 5, 2021, with the title of “Backlash Against Johnson & Johnson’s COVID-19 Vaccine Is Real and Risky – Here’s How To Make Its Rollout a Success”

‣ Tin­g­long Dai, Ho-Yin Mak, Christopher S. Tang. 2021. The Great Promise of a One-Dose Vaccine. Bar­ron’s. Feb­ru­ary 26.

‣ Tin­g­long Dai. 2021. How To Fix the Mess of COVID-19 Vaccine Appointment Scheduling. Fast Com­pa­ny. Feb­ru­ary 23.

◦ Orig­i­nal­ly pub­lished in The Conversation on Feb­ru­ary 22, 2021, with the title of “How To Real­ly Fix COVID-19 Vac­cine Appoint­ment Scheduling”

◦ Repub­lished in The Daily Beast, MarketWatch, Nextgov, and Yahoo! News

‣ Tin­g­long Dai. 2021. The US Government’s $44 Million Vaccine Rollout Website Was a Predictable Mess – Here’s How To Fix the Broken Process Behind It. The Con­ver­sa­tion. Feb­ru­ary 4.

‣ Tin­g­long Dai. 2021. The Simple Reason West Virginia Leads the Nation in Vaccinating Nursing Home Residents. The Asso­ci­at­ed Press. Jan­u­ary 29.

◦ Orig­i­nal­ly pub­lished in The Conversation on Jan­u­ary 14, 2021

◦ Repub­lished in Fast Company, Quartz, and U.S. News & World Report

‣ Tin­g­long Dai, Prashant Yadav. 2021. Why Holding Second Doses of COVID-19 Vaccines in Reserve Is the Wrong Strategy. USA Today. Jan­u­ary 12.

◦ Pub­lished in the nation­al print edi­tion (Jan­u­ary 13, page 7A) with the title of “Release Sec­ond Dos­es To Speed Vaccinations”

‣ Saralyn Cruickshank, Tin­g­long Dai. 2021. Q+A: Making Sense of the Lagging U.S. COVID-19 Vaccination Effort. The Hub (Johns Hop­kins Uni­ver­si­ty). Jan­u­ary 8.

‣ Tin­g­long Dai, Muhammad H. Zaman, William Padula, 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.

‣ Tin­g­long Dai, Shubhranshu Singh. 2020. COVID-19 Diagnostic Testing and Viral Load Reporting. VoxEU.org. Decem­ber 23.

‣ Tin­g­long Dai, Christopher S. Tang. 2020. How to Distribute the COVID-19 Vaccine: Lessons From Amazon and Walmart. Fast Com­pa­ny. Decem­ber 16.

◦ Orig­i­nal­ly pub­lished in The Conversation on Decem­ber 15, 2020, with the title of “What Vac­cine Dis­tri­b­u­tion Plan­ners Can Learn From Ama­zon and Walmart”

◦ Repub­lished in National Interest, Quartz, Salon, and Scroll.in

◦ Trans­lat­ed to Span­ish and pub­lished in El Financiero and The Logistics World 

‣ Tin­g­long Dai, Patrick Ercolano. 2020. Q+A: The Business of Delivering a Pandemic Vaccine. The Hub (Johns Hop­kins Uni­ver­si­ty). Decem­ber 4.

‣ Tin­g­long Dai, Guihua Wang, Ronghuo Zheng. 2020. How the Airline Industry Recovers From COVID-19 Could Determine Who Gets Organ Transplants. The Con­ver­sa­tion. Sep­tem­ber 28.

◦ Based on the paper enti­tled “Does Transportation Mean Transplantation? Impact of New Airline Routes on Sharing of Cadaveric Kidneys”

◦ Repub­lished by Associated Press, Austin’ NPR Station—KUT, Houston Chronicle, Public Radio International, National Interest, Simple Flying, and Yahoo! News

‣ Tin­g­long Dai, Christopher S. Tang. 2020. Safety First for Online Markets, or Customers May Shop Elsewhere. Bar­ron’s. August 25. (Repub­lished in MarketWatch.)

‣ Amit Jain, Tin­g­long Dai, Kristin Bibee, Christopher G. Myers. 2020. Covid-19 Created an Elective Surgery Backlog. How Can Hospitals Get Back on Track? Har­vard Busi­ness Review. August 10 (PDF).

‣ Tin­g­long Dai, Christopher S. Tang. 2020. Amazon Has a Trust Problem. Bar­ron’s. August 7. (Repub­lished in MarketWatch.)

‣ Ge Bai, Tin­g­long Dai, Shivaram Rajgopal. 2020. The PPE Supply Chain Is a Black Box—That Needs to Change. For­tune. July 25.

‣ Tin­g­long Dai, Christopher S. Tang. 2020. How to Build a Coronavirus Vaccine Supply Chain. Bloomberg Law. July 21.

‣ Tin­g­long Dai, Christopher S. Tang. 2020. Influenza Vaccine Supply Chain Lessons for Coronavirus. Bloomberg Law. July 21.

‣ Tin­g­long Dai, Christopher S. Tang. 2020. Too Fast, Too Furious: Is U.S. Vaccine Development Headed in the Wrong Direction? Bar­ron’s. July 16. (Repub­lished in MarketWatch.)

‣ Tin­g­long Dai, Ge Bai, Gerard Anderson. 2020. PPE Supply Chain Needs Data Transparency and Stress Testing. Jour­nal of Gen­er­al Inter­nal Med­i­cine 35(9), 2748–2749.

◦ 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

‣ Tin­g­long Dai. 2020. Where Does Your PPE Come From? A Lack of Transparency Is Hurting Americans. Fast Com­pa­ny. July 15.

◦ Orig­i­nal­ly pub­lished in The Conversation on July 13, 2020, under the title of “What US Med­ical Sup­ply Chain Can Learn From the Fash­ion Indus­try”; also repub­lished in Yahoo! News, Scroll.in, Mic, and Houston Chronicle

‣ Tin­g­long Dai, Christopher S. Tang. 2020. The U.S. Medical Supply Chain Isn’t Ready for a Second Wave. Bar­ron’s. June 24. Fea­tured Arti­cle. (Repub­lished in MarketWatch.)

‣ Thorsten Wuest, Andrew Kusiak, Tin­g­long Dai, Sridhar Tayur. 2020. Impact of COVID-19: The Case for AI-Inspired Digital Transformation. OR/MS Today. 47 (3) 34–39.

‣ Tin­g­long Dai, Christopher S. Tang. 2020. Needed: A PPE Industrial Commons. EE Times. May 27.

‣ Tin­g­long Dai, Ashley Kilgore, Sridhar Tayur. 2020. From Products to People: The Growing Impact of Supply Chain Interruptions during the Coronavirus Pandemic. Resound­ing­ly Human Pod­cast (INFORMS). March 18.

‣ Goker Aydin, Tin­g­long Dai, Tim Parsons. 2020. Q+A: How Coronavirus Will Affect the Global Supply Chain. The Hub (Johns Hop­kins Uni­ver­si­ty). March 6.

Papers by Topic (For a chronological list, visit tinglongdai.com/papers)

Healthcare

‣ 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, forth­com­ing. https://doi.org/10.1177/00222437251332898.

‣ 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.

◦ Fea­tured by New York Times and VoxEU
◦ Select­ed by COVID Economics as lead arti­cle of Issue 58

‣ Lee, Branden, Shivam Patel, Crystal Favorito, Sara Sandri, Maria Rain Jennings, and Tin­g­long Dai. “Devel­op­ment and Com­mer­cial­iza­tion Path­ways of AI Med­ical Devices in the U.S.: Impli­ca­tions for Safe­ty and Reg­u­la­to­ry Over­sight.” NEJM AI, forth­com­ing.

‣ 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.

‣ 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.

‣ 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. http://doi.org/10.1056/AIpc2400083. [PDF]

‣ Luan, Shujie, Shubhranshu Singh, and Tin­g­long Dai. 2024. “Algorithmic Bias and Physician Liability.” Work­ing paper. https://doi.org/10.2139/ssrn.5046254.

‣ Lai, Jiayi, Leon Xu, Xin Fang, and Tin­g­long Dai. 2024. “Regulating Adaptive Medical Artificial Intelligence: Can Less Oversight Lead to Greater Compliance?.” Work­ing paper. https://doi.org/10.2139/ssrn.5009572.

‣ Adida, Elodie, and Tin­g­long Dai. 2025. “Provider Payment Models for Generative AI in Healthcare.” Work­ing paper. http://dx.doi.org/10.2139/ssrn.5097711.

‣ Dai, Tin­g­long, and Simrita Singh. 2024. “Using AI as Gatekeeper or Second Opinion: Designing Patient Pathways for AI-Augmented Healthcare.” Work­ing paper. http://doi.org/10.2139/ssrn.5055325.

‣ Wang, Guihua, Minmin Zhang, and Tin­g­long Dai. 2024. “The Spillover Effect of Suspending Non-essential Surgery: Evidence from Kidney Transplantation.” Work­ing paper. https://doi.org/10.2139/ssrn.3719662.

‣ 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

‣ 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.

◦ 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
◦ Fea­tured by Associated Press, Austin’ NPR Station—KUT, The Conversation, Financial Times, Public Radio International, National Interest, Simple Flying, and Yahoo! News

‣ 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.

◦ Johns Hopkins Discovery Award, 2015

◦ 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.

‣ Zhong, Huaiyang, Guihua Wang, and Tin­g­long Dai. 2023. “Wheels on the Bus: Impact of Vaccine Rollouts on Demand for Public Transportation.” Work­ing paper. https://doi.org/10.2139/ssrn.3874150.

‣ 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] 

‣ 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] 

‣ 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

◦ Fea­tured by New York Times

‣ 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.

◦ Fea­tured by Agency for Healthcare Research and Quality, Hub of Johns Hopkins University and INFORMS Podcast

‣ 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.

◦ 2017 INFORMS Pub­lic Sec­tor Oper­a­tions Research Best Paper Award (First Place Winner)

‣ 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, 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.

◦ 2012 POMS Best Health­care Paper Award (First Place Winner)

‣ 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.

◦ 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

‣ 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.

‣ 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.

‣ 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.

‣ Fattahi, Ali, Maqbool Dada, and Tin­g­long Dai. 2020. “A Subscription Model for Prescription Drugs.” Work­ing paper. https://doi.org/10.2139/ssrn.3634063.

 

Human-AI Interaction

‣ Lee, Branden, Shivam Patel, Crystal Favorito, Sara Sandri, Maria Rain Jennings, and Tin­g­long Dai. “Devel­op­ment and Com­mer­cial­iza­tion Path­ways of AI Med­ical Devices in the U.S.: Impli­ca­tions for Safe­ty and Reg­u­la­to­ry Over­sight.” NEJM AI, forth­com­ing.

‣ 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, forth­com­ing. https://doi.org/10.1177/00222437251332898.

‣ 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.

‣ 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.

‣ 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.

‣ 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. http://doi.org/10.1056/AIpc2400083. [PDF]

‣ Luan, Shujie, Shubhranshu Singh, and Tin­g­long Dai. 2024. “Algorithmic Bias and Physician Liability.” Work­ing paper. https://doi.org/10.2139/ssrn.5046254.

‣ Lai, Jiayi, Leon Xu, Xin Fang, and Tin­g­long Dai. 2024. “Regulating Adaptive Medical Artificial Intelligence: Can Less Oversight Lead to Greater Compliance?.” Work­ing paper. https://doi.org/10.2139/ssrn.5009572.

‣ Adida, Elodie, and Tin­g­long Dai. 2025. “Provider Payment Models for Generative AI in Healthcare.” Work­ing paper. http://dx.doi.org/10.2139/ssrn.5097711.

‣ Dai, Tin­g­long, and Simrita Singh. 2024. “Using AI as Gatekeeper or Second Opinion: Designing Patient Pathways for AI-Augmented Healthcare.” Work­ing paper. http://doi.org/10.2139/ssrn.5055325.

‣ 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 Abramoff, Michael. 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.

‣ 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.

‣ 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, and 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

‣ 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.

◦ Fea­tured by Agency for Healthcare Research and Quality, Hub of Johns Hopkins University and INFORMS Podcast

‣ 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.

‣ 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). New York: Springer.

‣ 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.

◦ 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.

‣ 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.

‣ 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.

‣ 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.

◦ 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.

‣ 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.

 

Marketing-Operations Interfaces

‣ 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, forth­com­ing. https://doi.org/10.1177/00222437251332898.

‣ 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.

◦ Fea­tured by New York Times and VoxEU
◦ Select­ed by COVID Economics as lead arti­cle of Issue 58

‣ 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.

‣ Zuo, Ruiting, Tin­g­long Dai, and Jussi Keppo. 2023. “Incentive Design and Pricing under Limited Inventory.” Work­ing paper. http://dx.doi.org/10.2139/ssrn.3989971.

‣ 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.

◦ 2017 IBM Ser­vice Sci­ence Best Stu­dent Paper Award, Finalist
◦ 2018 POMS-HK Inter­na­tion­al Con­fer­ence, Best Stu­dent Paper Com­pe­ti­tion, Hon­or­able Mention

‣ 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.

◦ Fea­tured by Agency for Healthcare Research and Quality, Hub of Johns Hopkins University and INFORMS Podcast

‣ 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.

◦ Fea­tured by INFORMS Press Release and National University of Singapore

‣ 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.

‣ 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, 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.

‣ 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.

 

Global Supply Chains

‣ 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.

‣ Dai, Tin­g­long, and Christopher S. Tang. “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] 

‣ 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, 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.

‣ 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.

‣ 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.

◦ 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

◦ Fea­tured in the final report by the U.S. National Academies of Sciences, Engineering, and Medicine Committee on Security of America’s Medical Supply Chain

‣ 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.

◦ 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.

‣ 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]

‣ 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.

◦ 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

Handbook of Healthcare Analytics: Theoretical Minimum for Conducting 21st Century Research on Healthcare Operations

Edi­tors: Tin­g­long Dai and Sridhar Tayur

Pub­lished by John Wiley & Sons, Sep­tem­ber 2018; ISBN: 978-1-119-30094-6

Endorsed by:

Nitin Nohria, John P. Roberts, Alvin E. Roth, and Christopher S. Tang

Contributors:

‣ Mustafa Akan (Carnegie Mellon)
‣ Itai Ashlagi (Stan­ford)
‣ Baris Ata (Chica­go Booth)
‣ Turgay Ayer (Geor­gia Tech)
‣ Qiushi Chen (Penn State)
‣ Soo-Haeng Cho (Carnegie Mellon)
‣ Donald Fischer (High­mark)
‣ Nagesh Gavirneni (Cor­nell)
‣ Joel Goh (NUS/Harvard)
‣ Diwas KC (Emory)
‣ Vidyadhar Kulkarni (UNC)
‣ Nadia Lahrichi (Poly­tech­nique Montréal)
‣ Jay Levine (MIT)
‣ Nan Liu (BC)
‣ Karthik Natarajan (Min­neso­ta)
‣ Rema Padman (Carnegie Mellon)
‣ Cem Randa (UCSF)
‣ Louis-Martin Rousseau (Poly­tech­nique Montréal)
‣ Alan Scheller-Wolf (Carnegie Mellon)
‣ Hummy Song (Whar­ton)
‣ Jay Swaminathan (UNC)
‣ Van-Anh Truong (Colum­bia)
‣ Willem-Jan Van Hoeve (Carnegie Mellon)
‣ Senthil Veeraraghavan (Whar­ton)
‣ Hui Zhao (Penn State)

Buy/Read the Book:

Wiley, Amazon, Apple Books, Google Books

‣ Dean’s Award for Fac­ul­ty Excel­lence, 2016, 2017, 2018, 2019

‣ Black & Deck­er Com­pet­i­tive Research Grant, 2018, 2019

‣ Pro­duc­tion and Oper­a­tions Man­age­ment Best Review­er Award, 2018

‣ INFORMS Pub­lic Sec­tor Oper­a­tions Research Best Paper Award, 2017
for the paper “Jumping the Line, Charitably: Analysis and Remedy of Donor-Priority Rule”

‣ The Johns Hop­kins Dis­cov­ery Award, 2015
for the project “Clin­i­cal Ambi­gu­i­ty and Con­flicts of Inter­ests in Inter­ven­tion­al Car­di­ol­o­gy Deci­sion-Mak­ing” (role: lead PI)

‣ POMS Best Health­care Paper Award (First Place Win­ner), 2012
for the paper enti­tled “Imaging Room and Beyond: The Underlying Economics behind Physicians’ Test-Ordering Behavior in Outpatient Services.”

‣ INFORMS Pier­skalla Award for the Best Paper in Health­care (Run­ner-Up), 2012
for the paper enti­tled “Contracting for On-Time Delivery in the U.S. Influenza Vaccine Supply Chain.”

‣ POMS Best Health­care Paper Award (Run­ner-Up), 2016
for the paper enti­tled “Clinical Ambiguity and Conflicts of Interests in Interventional Cardiology Decision-Making.”

‣ POMS Col­lege of Sup­ply Chain Man­age­ment Best Stu­dent Paper Award (Final­ist), 2013
for the paper enti­tled “Contracting for On-Time Delivery in the U.S. Influenza Vaccine Supply Chain.”

‣ Elwood S. Buf­fa Doc­tor­al Dis­ser­ta­tion Award (Final­ist), 2014
for the dis­ser­ta­tion enti­tled “Incen­tives in U.S. Health­care Oper­a­tions” (Summary).

‣ INFORMS Case Com­pe­ti­tion (Sec­ond Place Win­ner), 2012
for the teach­ing case “Patient Expe­ri­ence Improve­ment at UPMC Eye Center.”

‣ Amer­i­can Uni­ver­si­ty, Kogod School of Busi­ness (2024)
‣ Ari­zona State Uni­ver­si­ty, Cen­ter for Accel­er­at­ing Oper­a­tional Effi­cien­cy (2021)
‣ Aston Uni­ver­si­ty, Aston Busi­ness School (2023)
‣ Bilkent Uni­ver­si­ty, Depart­ment of Indus­tri­al Engi­neer­ing (2021)
‣ Boston Col­lege, Car­roll School of Man­age­ment (2018)
‣ Bran­deis Uni­ver­si­ty, Inter­na­tion­al Busi­ness School (2021)
‣ Cardiff Uni­ver­si­ty, School of Math­e­mat­ics (2017)
‣ Carnegie Mel­lon Uni­ver­si­ty, Tep­per School of Busi­ness & INFORMS Chap­ter (2021)
‣ Carnegie Mel­lon Uni­ver­si­ty, Tep­per School of Busi­ness (2017)
‣ Case West­ern Reserve Uni­ver­si­ty, Weath­er­head School of Man­age­ment (2024)
‣ Chi­nese Uni­ver­si­ty of Hong Kong, CUHK Busi­ness School (2017)
‣ City Uni­ver­si­ty of Hong Kong, CityU Col­lege of Busi­ness (2016)
‣ City Uni­ver­si­ty of New York, Baruch Col­lege (2020)
‣ Clark­son Uni­ver­si­ty, School of Busi­ness (2015)
‣ Col­lege of William & Mary, Depart­ment of Math­e­mat­ics (2016)
‣ Cor­nell Uni­ver­si­ty, SC John­son Col­lege of Busi­ness (2018)
‣ Cor­nell Uni­ver­si­ty, John­son Grad­u­ate School of Man­age­ment (2013)
‣ Duke Uni­ver­si­ty, Fuqua School of Busi­ness (2021)
‣ Emory Uni­ver­si­ty, Goizue­ta Busi­ness School (2023)
‣ George Wash­ing­ton Uni­ver­si­ty, School of Busi­ness (2023)
‣ George­town Uni­ver­si­ty, McDo­nough School of Busi­ness (2017)
‣ Geor­gia Insti­tute of Tech­nol­o­gy, Scheller Col­lege of Busi­ness, (2024)
‣ Geor­gia Insti­tute of Tech­nol­o­gy, H. Mil­ton Stew­art School of Indus­tri­al and Sys­tems Engi­neer­ing (2017)
‣ Har­vard Uni­ver­si­ty, Har­vard Busi­ness School (2023)
‣ Hong Kong Uni­ver­si­ty of Sci­ence & Tech­nol­o­gy, Depart­ment of Indus­tri­al Engi­neer­ing and Logis­tics Man­age­ment (2016)
‣ Indi­ana Uni­ver­si­ty, Kel­ley School of Busi­ness (2020)
‣ INSEAD (2020)
‣ Insti­tute for Math­e­mat­i­cal and Sta­tis­ti­cal Inno­va­tion (2023)
‣ Johns Hop­kins Med­i­cine, JHI Part­ners Forum (2019)
‣ Johns Hop­kins Uni­ver­si­ty, Depart­ment of Applied Math­e­mat­ics and Sta­tis­tics (2022)
‣ Johns Hop­kins Uni­ver­si­ty, Bloomberg School of Pub­lic Health, Cen­ter for Health Ser­vices Out­comes Research (2023)
‣ Johns Hop­kins Uni­ver­si­ty, Bloomberg School of Pub­lic Health, Cen­ter for Health Ser­vices Out­comes Research (2021)
‣ Johns Hop­kins Uni­ver­si­ty, Carey Busi­ness School (2013)
‣ Johns Hop­kins Uni­ver­si­ty, Divi­sion of Infec­tious Dis­eases (2024)
‣ Johns Hop­kins Uni­ver­si­ty, Hop­kins Busi­ness of Health Ini­tia­tive (2022)
‣ Johns Hop­kins Uni­ver­si­ty, School of Med­i­cine, Depart­ment of Plas­tic & Recon­struc­tive Surgery (2023)
‣ Johns Hop­kins Uni­ver­si­ty, School of Nurs­ing, Cen­ter for Immer­sive Learn­ing and Dig­i­tal Inno­va­tions (2023)
‣ Johns Hop­kins Uni­ver­si­ty, School of Nurs­ing, Health Equi­ty Sem­i­nar (2024)
‣ Johns Hop­kins Uni­ver­si­ty, School of Nurs­ing, Health Equi­ty Sem­i­nar (2023)
‣ Lehigh Uni­ver­si­ty, Col­lege of Busi­ness (2024)
‣ Lon­don Busi­ness School (2019)
‣ McGill Uni­ver­si­ty, Desau­tels Fac­ul­ty of Man­age­ment (2024)
‣ McGill Uni­ver­si­ty, Ben­sadoun School of Retail Man­age­ment, Thought Leader Series (2021)
‣ Nation­al Uni­ver­si­ty of Sin­ga­pore, NUS Busi­ness School (2020)
‣ The Ohio State Uni­ver­si­ty, Fish­er Col­lege of Busi­ness (2022)
‣ Ore­gon State Uni­ver­si­ty, Sup­ply Chain Coun­cil (2022)
‣ Queen’s Uni­ver­si­ty, Smith School of Busi­ness (2023)
‣ Rice Uni­ver­si­ty, Jones Grad­u­ate School of Busi­ness (2024)
‣ Rut­gers Uni­ver­si­ty, Rut­gers Busi­ness School, Post-Pan­dem­ic Sup­ply Chain and Health­care Man­age­ment Con­fer­ence (2021)
‣ Sapien­za Uni­ver­si­ty of Rome, Depart­ment of Com­put­er, Con­trol, and Man­age­ment Engi­neer­ing Anto­nio Ruber­ti (2019)
‣ Sin­ga­pore Man­age­ment Uni­ver­si­ty, Lee Kong Chi­an School of Busi­ness (2020)
‣ Stan­ford Uni­ver­si­ty, Grad­u­ate School of Busi­ness (2023)
‣ Stan­ford Uni­ver­si­ty, Eco­nom­ics of Trans­plan­ta­tion Work­shop (2020)
‣ Stevens Insti­tute of Tech­nol­o­gy, School of Busi­ness (2013)
‣ Syra­cuse Uni­ver­si­ty, Whit­man School of Man­age­ment (2025, scheduled)
‣ Tem­ple Uni­ver­si­ty, Fox School of Busi­ness (2024)
‣ Tem­ple Uni­ver­si­ty, Fox School of Busi­ness (2021)
‣ Texas Chris­t­ian Uni­ver­si­ty, Nee­ley School of Busi­ness, Nee­ley Ana­lyt­ics Ini­tia­tive, Keynote speak­er (2022)
‣ Uni­ver­si­ty at Buf­fa­lo, School of Man­age­ment (2024)
‣ Uni­ver­si­ty Col­lege Lon­don, UCL School of Man­age­ment (2019)
‣ Uni­ver­si­ty of Alber­ta, Alber­ta School of Busi­ness (2023)
‣ Uni­ver­si­ty of British Colum­bia, Saud­er School of Busi­ness (2017)
‣ Uni­ver­si­ty of Cal­i­for­nia, Berke­ley, Haas School of Busi­ness (2013)
‣ Uni­ver­si­ty of Cal­i­for­nia, Irvine, Paul Mer­age School of Busi­ness (2024)
‣ Uni­ver­si­ty of Cal­i­for­nia, Los Ange­les, UCLA Ander­son School of Man­age­ment (2022)
‣ Uni­ver­si­ty of Cal­i­for­nia, River­side, School of Busi­ness (2022)
‣ Uni­ver­si­ty of Cam­bridge, Judge Busi­ness School (2023)
‣ Uni­ver­si­ty of Cam­bridge, Judge Busi­ness School (2019)
‣ Uni­ver­si­ty of Chica­go, Booth School of Busi­ness (2017)
‣ Uni­ver­si­ty of Chica­go, Booth School of Busi­ness (2016)
‣ Uni­ver­si­ty of Cincin­nati, Lind­ner Col­lege of Busi­ness (2023)
‣ Uni­ver­si­ty of Con­necti­cut, School of Busi­ness (2021)
‣ Uni­ver­si­ty of Dubai, Col­lege of Busi­ness Admin­is­tra­tion (2023)
‣ Uni­ver­si­ty of Hong Kong, Asia Glob­al Insti­tute (2022)
‣ Uni­ver­si­ty of Hong Kong, Fac­ul­ty of Busi­ness and Eco­nom­ics (2013)
‣ Uni­ver­si­ty of Illi­nois Urbana-Cham­paign, Gies Col­lege of Busi­ness (2022)
‣ Uni­ver­si­ty of Kansas, School of Busi­ness (2021)
‣ Uni­ver­si­ty of Liv­er­pool, Man­age­ment School (2024)
‣ Uni­ver­si­ty of Mary­land, Robert H. Smith School of Busi­ness (2022)
‣ Uni­ver­si­ty of Mass­a­chu­setts Amherst, INFORMS Chap­ter (2022)
‣ Uni­ver­si­ty of Mem­phis, FedEx Insti­tute of Tech­nol­o­gy (2025, scheduled)
‣ Uni­ver­si­ty of Mia­mi, Mia­mi Her­bert Busi­ness School, Health­care Ana­lyt­ics Work­shop (2024)
‣ Uni­ver­si­ty of Min­neso­ta, Carl­son School of Man­age­ment (2013)
‣ Uni­ver­si­ty of Nebraska–Lincoln, Col­lege of Busi­ness (2022)
‣ Uni­ver­si­ty of North Car­oli­na at Chapel Hill, Kenan Fla­gler Busi­ness School (2022)
‣ Uni­ver­si­ty of North Car­oli­na at Chapel Hill, Kenan Fla­gler Busi­ness School–Healthcare OM Work­shop (2019)
‣ Uni­ver­si­ty of Ore­gon, Lundquist Col­lege of Busi­ness (2025, scheduled)
‣ Uni­ver­si­ty of Oxford, Saïd Busi­ness School (2019)
‣ Uni­ver­si­ty of Penn­syl­va­nia, The Whar­ton School (2023)
‣ Uni­ver­si­ty of Rochester, Simon Busi­ness School (2019)
‣ Uni­ver­si­ty of South­ern Cal­i­for­nia, Gould School of Law (2023)
‣ Uni­ver­si­ty of South­ern Cal­i­for­nia, Mar­shall School of Busi­ness, (2023)
‣ Uni­ver­si­ty of South­ern Cal­i­for­nia, Depart­ment of Indus­tri­al and Sys­tems Engi­neer­ing (2015)
‣ Uni­ver­si­ty of Texas at Dal­las, Naveen Jin­dal School of Man­age­ment (2018)
‣ Uni­ver­si­ty of Toron­to, Rot­man School of Man­age­ment (2023)
‣ Uni­ver­si­ty of Utah, David Eccles School of Busi­ness (2013)
‣ Uni­ver­si­ty of Vir­ginia, Dar­d­en School of Busi­ness (2018)
‣ Uni­ver­si­ty of Wash­ing­ton, Fos­ter School of Busi­ness, MSCM Leader Series (2021)
‣ Uni­ver­si­ty of Water­loo, Depart­ment of Man­age­ment Sci­ences (2015)
‣ Uni­ver­si­ty of Wisconsin–Madison, Wis­con­sin School of Busi­ness (2019)
‣ Vir­ginia Tech, Pam­plin Col­lege of Busi­ness (2025, scheduled)
‣ Wash­ing­ton Uni­ver­si­ty in St. Louis, Olin Busi­ness School (2020)
‣ Yale Uni­ver­si­ty, Yale School of Man­age­ment (2013)