News Release 

Columbia data scientist designs better e-commerce systems

Receives NSF award to study and enhance consumer flexibility

Data Science Institute at Columbia

Adam Elmachtoub, an assistant professor of industrial engineering and operations research and member of the Data Science Institute (DSI) at Columbia University, has won a National Science Foundation (NSF) CAREER Award to design more efficient e-commerce and service systems that embrace and leverage consumer flexibility. The five-year, $500,000 grant, which is the NSF's top honor awarded to junior faculty, will support his project to develop tools to manage demand with flexible options for the consumer and then convert consumer flexibility into operational efficiency for companies.

His NSF project will look specifically at consumer flexibility--a consumer's explicit willingness to receive one of an assortment of offered options in exchange for a reward or discount. For instance, consumers might be willing to purchase an article of clothing of an arbitrary color or receive a delivery in one of multiple time windows, in exchange for a price discount. The arbitrary color or multiple window options allow the consumer to sacrifice some of their choice in exchange for a price discount. From the seller's perspective, the consumer's flexibility allows them to make their operations more efficient.

"Creating more efficient e-commerce systems that leverage consumer flexibility is more important than ever in the time of Covid-19," Elmachtoub said. "Designing more efficient e-commerce and service systems that embrace and leverage consumer flexibility is more critical than ever. My students and I are excited to come up with new systems that simultaneously provide advantages to consumers and sellers."

Elmachtoub's goal is to benefit both consumers and firms by providing discounted flexible options to consumers while reducing operational costs of selling products and services. He plans to develop new analytical methods and tractable approximation approaches for modeling consumer behavior in choice models, which will lead to new pricing analysis and tools that address the inherent mathematical difficulties introduced by flexible options.

From the supply perspective, Elmachtoub and his graduate students will extend classical operational models to incorporate consumer flexibility. In inventory management, he will develop algorithms that quantify and leverage consumer flexibility to better balance inventory and reduce supply chain costs. He will also develop new models for scheduled services, such as grocery delivery, to guide the design of time windows that effectively manage capacity and ensure efficient vehicle routes. "For consumer flexibility to become more widely used, companies need a mathematical framework to show them the right products, the optimal prices, and the best windows of delivery times to offer consumers that will also maximize a company's revenue," he said. "Without that framework, we can't operationalize the data. And it has always been my mission to use operations research and data science to do some societal good."

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