Zhang wins Olin Award for research on Alibaba packing time

Dennis Zhang has won the 2020 Olin Award for research that creates a human-focused algorithm to improve warehouse workers’ packing time while also reducing material costs.

The Olin Award, which includes business school recognition and a $10,000 prize, is intended to promote scholarly research that has timely, practical applications for complex management problems.

Zhang, assistant professor of operations and manufacturing management, received notice that he had won this year’s award during a short meeting in Dean Mark Taylor’s office on Wednesday afternoon.

His winning research focused on bin packing at the Chinese online retail giant Alibaba to test a human-centric algorithm that, as it turns out, could save Alibaba more than $3 million a year. The paper, “Predicting Human Discretion to Adjust Algorithmic Prescription: A Large-Scale Field Experiment in Warehouse Operations,” is under revision in Management Science.

“Well, that’s a nice surprise,” said Zhang, laughing.

“This was a stunning piece of research,” Taylor told him. “A lot of the judges put ‘number one’ immediately.”

Richard J. Mahoney, former CEO of Monsanto and a Distinguished Executive-in-Residence at Olin, initiated the award, now in its 13th year.

This is Zhang’s second Olin Award. Last year, he and Jake Feldman, assistant professor of operations and manufacturing management, received the award for “Taking Assortment Optimization from Theory to Practice: Evidence from Large Field Experiments on  Alibaba.” They used data from Alibaba to test the benefits of—and recommend a solution for—presenting buyers the optimum variety of products available for purchase with individual online retail stores.

Human-centric algorithm

This year’s winning research focused on workers’ bin packing at Alibaba’s warehouse to test a human-centric algorithm. Conventional bin-packing algorithms prescribe which items to pack in which sequence in which box or bin. All the while, they focus on the best use of a bin’s volume. Here’s the rub: Those algorithms tend to overlook how humans might deviate from the plan.

“Today, the adoption of artificial intelligence (AI) and robotics is accelerating and revolutionizing business operations by augmenting human work,” Zhang and co-authors wrote in their award-winning paper.

“Indeed, rather than striving for autonomous automation, we believe that AI and robotics can improve human work by providing more decision support while always empowering human judgment, oversight and discretion.”

A panel of judges evaluated each of the 19 papers submitted this year for consideration for the Olin Award.

“The topic of the paper and applicability to business are very relevant as e-commerce continues to grow as a business channel in the United States and globally,” one judge wrote about Zhang’s paper. “Understanding how to save time on packing at warehousing is very relevant” and could deliver high savings for big operations like Alibaba and Amazon.

“This is a truly stellar paper,” another judge wrote.  “The issue addressed—how to anticipate human modification of computer algorithms in their work—is a large one across many sectors of the economy.  The randomized, controlled nature of the study makes the conclusions that much stronger. Well done.”

Zhang will be recognized at a luncheon on April 1, where he will have the opportunity to present his research.

Zhang’s co-authors are Jiankun Sun of Imperial College Business School, Haoyuan Hu of the Alibaba Group and Jan A. Van Mieghem of Northwestern University.

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2 Responses to "Zhang wins Olin Award for research on Alibaba packing time"

  1. avatar Olayinka 456

    Nice one

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