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| Date | Time | Room | Speaker | Affiliation | Paper |
|---|---|---|---|---|---|
| September 20 | 9:30 AM | 3325 Graigner Hall | Chris Ryan | Booth School, University of Chicago | |
| October 29 | 9:30 AM | 3560 Grainger Hall | Kostas Nikolopoulos | Bangor University | Looking for the Needle in the Haystack: |
| OIM Research Workshop | |||||
| December 6 | 1:00 PM | 4580 Grainger Hall | Jan Van Mieghem | Kellogg School, Northwestern University | Dual Sourcing and Smoothing Under Non-Stationary Demand Time Series: Re-shoring with SpeedFactories |
| December 6 | 2:30 PM | 4580 Grainger Hall | Ryan Buell | Harvard Business School, Harvard University | Surfacing the Submerged State: Operational Transparency Increases Trust in and Engagement with Government |
| December 7 | 9:00 AM | 4580 Grainger Hall | Atalay Atasu | Scheller College of Business, Georgia Tech | |
| February 8 | 9:30 AM | 3070 Grainger Hall | Tinglong Dai | Carey Business School, Johns Hopkins UniversityTBD | Too Much? Too Little? Economic Modeling of Physician Testing Decisions |
| April 5 | 9:30 AM | Kumar Rajaram | Anderson School, UCLA | TBD | |
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We investigate the emerging trend of near-shoring a small part of the global production back to local SpeedFactories. The short lead time of the responsive SpeedFactory reduces the risk of making large volumes in advance, yet it does not involve a complete re-shoring of demand. Using a breakeven analysis we investigate the lead time, demand, and cost characteristics that make dual sourcing with a SpeedFactory desirable compared to off-shoring to a single supplier. We propose order rules that extend the celebrated inventory optimal order-up-to replenishment policy to settings where capacity costs exist and demonstrate their excellent performance. We highlight the significant impact of autocorrelated and non-stationary demand series, which are prevalent in practice yet challenging to analyze, on the economic benefit of re-shoring. Methodologically, we adopt Z−transforms and present an exact analysis of several discrete-time linear inventory models.
Prof. Tinglong Dai, Associate Professor, Carey Business School, Johns Hopkins University
Few issues in the healthcare ecosystem are more salient than the utilization of medical tests. By some estimates, up to 30% of medical-testing decisions are deemed inappropriate, which may entail either over- or under-testing. All too frequently, the public attention has centered on over-testing. By comparison, under-testing has received little media coverage, but frequently appears in the medical literature. In addition, contrary to popular belief, the US trails most OECD countries in terms of the utilization of medical tests.
In this talk, I discuss several recent modeling efforts aimed at understanding physician decision-making leading to over- and under-testing. These efforts, motivated by ophthalmology and interventional cardiology practices, reflect clinical, financial, and operational incentives. I will also highlight implications for policymakers and healthcare executives.
My talk will draw from three papers:
Tinglong Dai, Shubhranshu Singh. 2018. Conspicuous by Its Absence: Diagnostic Expert Testing under Uncertainty. Johns Hopkins University Working Paper.
Tinglong Dai, Mustafa Akan, 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.
Tinglong Dai, Xiaofang Wang, Chao-Wei Hwang. 2018. Clinical Ambiguity and Conflicts of Interests in Interventional Cardiology Decision-Making. Johns Hopkins University Working Paper.
Prof. Kumar Rajaram, Professor, Anderson School of Management, UCLA
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