Qiuping Yu
Assistant Professor at Kelley School of Business
Assistant Professor at The Scheller College of Business
Schools
- The Scheller College of Business
- Kelley School of Business
Links
Biography
Kelley School of Business
Areas of Expertise
Service Operations, Empirical Operations Management, Business Analytics, Structure Estimations, Consumer Behavior, Queuing Systems, Optimization
Academic Degrees
- PhD in Industrial Engineering and Management Sciences, Northwestern University
- MA in Economics, Northwestern University
- BSc in Mathematics and Physics, Hong Kong University of Science and Technology (HKUST)
Awards, Honors & Certificates
- ODT Research Scholar Award, Indiana University, 2017
- Management Science Meritorious Service Award, 2016
- First Prize Winner, CSAMSE Annual Conference/Columbia China Business Initiative Best Paper Award, 2016
- Wharton Customer Analytics Initiative Research Award, 2015
- Walter Murphy Fellowship, Northwestern University, 2009
- Outstanding Student Scholarship, HKUST (full tuition and stipend), 2005 – 2009
- Paul and May Chu Research Award, HKUST, 2008
- Leadership Fellowship, HKUST, 2007
- Outstanding Student Award, Zhejiang, China, 2005
Selected Publications
- Yu, Qiuping, Gad Allon, Achal Bassamboo, and Seyed Iravani (2017), "Managing Customer Expectations and Priorities in Service Systems," forthcoming, Management Science.
Abstract We study how to use delay announcements to manage customer expectations while allowing the firm to prioritize among customers with different sensitivities to time and value. We examine this problem by developing a framework which characterizes the strategic interaction between the firm and heterogeneous customers. When the firm has information about the state of the system, yet lacks information on customer types, delay announcements play a dual role: they inform customers about the state of the system, while they also have the potential to elicit information on customer types based on their response to the announcements. The tension between these two goals has implications to the type of information that can be shared credibly. To explore the value of the information on customer types, we also study a model where the firm can observe customer types. We show that having information on the customer type may improve or hurt the credibility of the firm. While the creation of credibility increases the firm''s profit, the loss of credibility does not necessarily hurt its profit.
- Yu, Qiuping, Gad Allon, and Achal Bassamboo (2017), "How do Delay Announcements Shape Customer Behavior? An Empirical Study," Management Science, 63(1): 1-20.
Abstract In this paper, we explore the impact of delay announcements using an empirical approach by analyzing the data from a medium-sized call center. We first explore the question of whether delay announcements impact customers'' behavior using a nonparametric approach. The answer to this question appears to be ambiguous. We thus turn to investigate the fundamental mechanism by which delay announcements impact customer behavior, by constructing a dynamic structural model. In contrast to the implicit assumption made in the literature that announcements do not directly impact customers'' waiting costs, our key insights show that delay announcements not only impact customers'' beliefs about the system, but also directly impact customers'' waiting costs. In particular, customers'' per unit waiting cost decreases with the offered waiting times associated with the announcements. The results of our counterfactual analysis show that it may not be necessary to provide announcements with very fine granularity.
The Scheller College of Business
Research
Service Operations
Business Analytics
Education
PhD in Operations Research, Northwestern University
MA in Economics, Northwestern University
B.S. in Mathematics and Physics, HKUST
Biography
Qiuping Yu is an assistant professor of Operations Management and Business Analytics at the Scheller College of Business of Georgia Tech. Her broad research interests lie in the areas of service operations. She is particularly interested in exploring how fundamental operational drivers impact consumer and worker behavior, and in turn how firms can use such behavioral insights to improve operational decisions in service systems. For her research, she uses a broad range of empirical and analytical methodologies, (e.g., structural estimation, causal inference, machine learning, and stochastic dynamic programming).
Recently, she has studied how informing customers on anticipated delay and how operational capacity decisions (e.g., staffing, scheduling, and capacity allocations in service networks) shape customer and worker behavior in industries such as call centers, restaurants and ride-sharing platforms. Her research has been published in journals such as Management Science.
Dr Yu earned her PhD in Operations Research and M.A. in Economics from Northwestern University. She did her undergraduate in Mathematics and Physics at the Hong Kong University of Science and Technology (HKUST). Before she joined Scheller, she taught at the Kelley School of Business, Indiana University.
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