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Academic Conference: Doing Good With OM and OR

November 12 | 9:00 am - 4:30 pm

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The Supply Chain Resource Cooperative (SCRC) invites you to join us for an in-person, one day academic conference on Friday, November 12th, “Doing Good With OM and OR”. 

We will have 6 great speakers (details below) talk to us about their work on topics such as sustainability, COVID-19, healthcare, and supply chain disruptions.

The event is open to anyone interested in research in this domain. PhD students are encouraged to attend.

Registration and parking for this event is free*. 

*Please do not register if you cannot commit to attending. Space is limited to 50 people, and an accurate headcount is necessary for us to plan for food and parking.


View the conference agenda

Speaker Sessions

“Optimal Subsidy Schemes and Budget Allocations for Government-Subsidized Trade-in Programs”

Jiaru Bai
Assistant Professor, Robinson-Lightcap Faculty Fellow, Wake Forest University

Applications of government subsidies to speed up consumer trade-ins of used products can be commonly observed in practice. This study investigates the design of such trade-in subsidy programs and aims to provide implementable insights for practice. We develop a three-stage Stackelberg game model that captures the essence of the interaction between the government’s subsidy decision, the manufacturer’s trade-in rebate decision, and the consumer’s product replacement decision. We show that a sharing subsidy scheme under which the government subsidy is proportional to the manufacturer’s rebate is more effective in encouraging consumer trade-ins than fixed-amount subsidies. Moreover, a product with a higher environmental impact, a larger market size, a longer lifespan, or a lower value to consumers typically demands a larger subsidy budget allocation. We further use our results to derive a simple proportional budget allocation rule that can provide robust and near-optimal performance. We illustrate our results by a case study based on the “old-for-new” program in China that subsidizes home appliance trade-ins.


“Effect of Guided Delegation and Information Proximity on Multitier Responsible Sourcing”

Jeannette Song
R. David Thomas Professor of Business Administration and Professor of Operations Management, Fuqua School of Business, Duke University 

To manage supplier responsibility risks, many companies practice guided delegation in sourcing. That is, they provide their Tier-1 suppliers a list of authorized higher-tier suppliers as a guideline but delegate the ultimate supplier selection and inspection responsibility to Tier-1 suppliers. This approach allows companies to focus more resources on core competencies. It also leverages Tier-1 suppliers’ information proximity — they work closer to their direct suppliers and thus have better information about these suppliers than the downstream. However, this approach may fail to deliver the intended outcome, evidenced by many responsibility violations at deep-tier suppliers. We develop a three-tier supply chain model to analyze why and under what situations guided delegation may not align profit objectives with socially responsible goals. We also offer suggestions to external stakeholders on which actions can effectively encourage multitier responsible sourcing and when to take cautions. (Joint work with Sammi Tang of University of Miami.)


“Net-Metered Distributed Renewable Energy: A Peril for Utilities?”

Nur Sunar
Associate Professor of Operations, Kenan-Flagler Business School, UNC at Chapel Hill 

Electricity end-users have been increasingly generating their own electricity via rooftop solar panels. We study the impact of such distributed renewable energy (DRE) on utility profits and social welfare under net metering, which is a widespread policy in the United States. Utilities have been lobbying against net-metered distributed solar based on the common belief that it harms utility profits. In contrast, we find that when wholesale market dynamics are considered, net-metered DRE may be a positive for utilities. That is, net-metered DRE strictly improves the expected utility profit when the utility’s self-supply is below a threshold and the wholesale electricity price is sufficiently responsive to wholesale demand fluctuations. This result provides general guidelines to utilities regarding their lobbying strategies on rooftop solar panels.  Our paper identifies these guidelines by distinctively considering both downstream and upstream impacts of net-metered DRE on utilities and analyzing the tradeoff between these impacts. Our results also suggest that utilities might benefit from emerging business strategies that motivate their customers to adopt solar panels. Our numerical study uses rich data on the distributed solar in California and the wholesale electricity market operated by the California Independent System Operator, and demonstrates that our findings hold under realistic parameters.


“Sourcing Under Supply Disruption And Responsibility Violation Risks: A Behavioral Investigation”

Vincent Yu
Postdoctoral Research Scholar, Poole College of Management, NC State University  

We combine modeling and experimental methods to investigate how managers make sourcing decisions between a high-cost supplier with no risk and a low-cost supplier with potential risks. We focus on two types of risk: (1) supply disruption risk that influences the flow of product supply, and (2) responsibility violation risk that influences the flow of customer demand. To better understand the differences between these two risk types, we propose a framework to disentangle their differing dimensions and introduce new risk types to serve as references for comparison. Through a series of behavioral experiments, we demonstrate how elements of different risk types can shape buyers’ ordering decisions through cognitive processing and affective reactions.


“Testing with Limited Capacity and Pooling”

Serhan Ziya
Professor, College of Arts and Sciences, Statistics and Operations Research, UNC Chapel Hill 

Motivated by the persistent lack of testing capacity in the initial stages of the COVID-19 pandemic, we study the question, “Who should be tested?” When capacity is limited, tests have errors, and patients differ in their prior probabilities of being infected.  We use a stylized optimization model incorporating costs and rewards for different test outcomes.  We find that it may be better to focus on patients who are less likely to be infected, particularly when the false-negative rate is substantial. When pooled testing is an option, it may be optimal to test two groups of individuals: those who are very likely to be infected and those who are very unlikely to be infected. This is joint work with Alex Mills. 

“Session TBD”

Julie Ivy
Professor, Edward P. Fitts Department of Industrial and Systems Engineering and Fitts Faculty Fellow in Health Systems Engineering, NC State University 


View the conference agenda


To register for this event, please click here.



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