Biography
Ruomeng Cui is a Goizueta Foundation Term Chair Associate Professor in the Department of Information System and Operations Management at Emory University’s Goizueta Business School. Professor Cui’s research focuses on causal-driven decision making in platforms, retail, and supply chains. Her expertise lies in causal-driven decision making, identify-then-optimize models, causal inference, causal machine learning, and economics. In her research, Professor Cui investigates how operations strategies create and deliver value in companies' digital and AI transformation. Specifically, she studies how digitization and AI reshapes how companies compete and operate. Professor Cui has published papers in leading academic journals, including Management Science, Manufacturing & Service Operations Management (M&SOM), Operations Research, Production & Operations Management (POM), Harvard Business Review and others.
Her research has been recognized by 19 prestigious and highly competitive prizes including 2022 POMS Early Career Research Accomplishments Award, 2023 & 2024 M&SOM Best Paper in Management Science Award, 2019 INFORMS Junior Faculty Interest Group (JFIG) Paper Competition award, and 2019 M&SOM Practice-Based Paper Competition award. Professor Cui’s research has been widely covered by the media, including NPR, Financial Times, Fox News, Fortune Magazine, and HBR.
Professor Cui has consulted in various capacities for Amazon, Alibaba, JD.com, PepsiCo, Tencent, Cainiao, Meituan, Collage.com, and many other leading firms. She has been a visiting scholar at Amazon since 2022, where she designed, developed, and implemented cutting-edge causal inference, machine learning, optimization, and economic models to drive supply chain and robotics decisions in various spaces.
Education
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PhD in Operations ManagementNorthwestern University, Kellogg School of Management
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BSc in Industrial EngineeringTsinghua University
Sooner or Later? Promising Delivery Speed in Online Retail
Abstract. Problem definition: Online retailers have to provide customers with an estimate of how fast an order can be delivered before they decide to make the purchase. Retailers can strategically adjust this delivery speed promise online without changing offline infrastructure, and doing so may fundamentally impact business outcomes. It can influence consumers’ purchasing decisions and postpurchase experiences, often in the opposite direction.
AI and Procurement
Problem definition: In this research, we study how buyers’ use of artificial intelligence (AI) affects suppliers’ price quoting strategies. Specifically, we study the impact of automation—that is, the buyer uses a chatbot to automatically inquire about prices instead of asking in person—and the impact of smartness—that is, the buyer signals the use of a smart AI algorithm in selecting the supplier.
Gender Inequality in Research Productivity During the COVID-19 Pandemic
We study the disproportionate impact of the lockdown as a result of the COVID-19 outbreak on female and male academics' research productivity in social science. The lockdown has caused substantial disruptions to academic activities, requiring people to work from home. How this disruption affects productivity and the related gender equity is an important operations and societal question. We collect data from the largest open-access preprint repository for social science on 41,858 research preprints in 18 disciplines produced by 76,832 authors across 25 countries over a span of two years.
Learning from Inventory Availability Information: Evidence from Field Experiments on Amazon
Many online retailers provide real-time inventory availability information. Customers can learn from the inventory level and update their beliefs about the product. Thus, consumer purchasing behavior may be impacted by the availability information.
Value of High-Quality Logistics: Evidence from a Clash Between SF Express and Alibaba
Consumers regard product delivery as an important service component that influences their shopping decisions on online retail platforms. Delivering products to customers in a timely and reliable manner enhances customer experience and companies’ profitability. In this research, we explore the extent to which customers value a high-quality delivery experience when shopping online.
Reducing Discrimination with Reviews in the Sharing Economy: Evidence from Field Experiments on Airbnb
Recent research has found widespread discrimination by hosts against guests of certain races in online marketplaces. In this paper, we explore ways to reduce such discrimination using online reputation systems. We conducted four randomized field experiments among 1,801 hosts on Airbnb by creating fictitious guest accounts and sending accommodation requests to them.
Oversight and Efficiency in Public Projects: A Regression Discontinuity Analysis
In the United States, 42% of public infrastructure projects report delays or cost overruns. To mitigate this problem, regulators scrutinize project operations. We study the effect of oversight on delays and overruns with 262,857 projects spanning 71 federal agencies and 54,739 contractors.
Information Sharing in Supply Chains: An Empirical and Theoretical Valuation
We provide an empirical and theoretical assessment of the value of information sharing in a two-stage supply chain. The value of downstream sales information to the upstream firm stems from improving upstream order fulfillment forecast accuracy.