Research

Academic Journals (*indicates student coauthors)
  1. Qiuping Yu, Gad Allon, and Achal Bassamboo (2017). “How do Delay Announcements Shape Customer Behavior? An Empirical Study.Management Science, 63(1): 1-20.
  2. Qiuping Yu, Gad Allon, Achal Bassamboo, and Seyed Iravani (2018). “Managing Customer Expectations and Priorities in Service Systems.Management Science, 64(8), 3942-3970.
  3. Qiuping Yu, Gad Allon, and Achal Bassamboo (2020), “The Reference Effect of Delay Announcements: A Field Experiment,” Management Science, Accepted.
  4. Masoud Kamalahmadi*, Qiuping Yu and Yong-Pin Zhou (2020). “Call to Duty: Just-in-Time Scheduling in a Restaurant Chain.”  Management Science, Accepted
  5. Qiuping Yu, Yiming Zhang*, and Yong-Pin Zhou (2021).Delay Information in Virtual Queues: A Large Scale Field Experiment On A Ridesharing Platform. Management Science (fast track), accepted.
    • Partner Platform’s Research Grant Award 2018 ($23,783)
    • First Place, 2021 INFORMS Service Science Best Paper Award Competition.
    • Second Place, 2021 CSAMSE Practice Award. 
    • Honorable Mention, 2021 INFORMS Behavioral Operations Management best working paper award (one of the five finalists among 59 submissions).
    • Featured in Harvard Business Review (Digital & Print), Scheller News.
    • Selected to present at Harvard Business School (COER) 2020 (COER Slides), Marketplace Innovation Workshop 2021, Columbia University, The Empirical Workshop at the Wharton School.  
Practitioner Journals
  1. Qiuping Yu, Shawn Mankad, Masha Shunko (2021). “Research: When a Higher Minimum Wage Leads to Lower Compensation.” Harvard Business Review. (Digital Article)
  2. Qiuping Yu (2020). “When Providing Wait Times, It Pays to Underpromise and Overdeliver.”  Harvard Business Review. (Digital Article)
  3. Qiuping Yu, Yiming Zhang*, Yong-Pin Zhou (2021). A Better Way to Manage Virtual Queues.”  Harvard Business Review. (IdeaWatch, January/February 2021 print issue ) 
  4. Masoud Kamalahmadi*, Qiuping Yu and Yong-Pin Zhou (2020). “The Costs of Last-Minute Scheduling.”Harvard Business Review. (IdeaWatch, January/February 2020 print issue, also available in Chinese)


Papers under Review/Revision
  1. Qiuping Yu, Shawn Mankad, and Masha Shunko. “Evidence of The Unintended Labor Scheduling Implications of Minimum Wage.MSOM, Major Revision (under 2nd round review).
  2. Shawn Mankad, Masha Shunko, and Qiuping Yu. “Too Close for Comfort? Understanding Peer Effects in Large Franchised Networks.” POMS, Major Revision
    • Wharton Customer Analytics Institute Data Grant Award
    • Selected to present at Harvard Business School (COER) 
  3. Qiuping Yu, Masha Shunko, and Shawn Mankad. “A Quality Value Chain Network: Linking Supply Chain Quality to Customer Lifetime Value.Management Science, Reject & Resubmit
    • Wharton Customer Analytics Institute Data Grant Award
    • Selected to present at The Wharton School (WCAI), Harvard Business School (COER)
  4. Eric Webb*, Qiuping Yu, and Kurt Bretthauer. “Linking Delay Announcements, Abandonment, and Service Time.Operations Research, Reject & Resubmit
    • Featured in Harvard Business Review (digital article)
    • Finalist, IBM Service Science Best Student Paper Award
    • Selected to present at the Behavioral Operations Workshop, University of Wisconsin, Madison
    • Previously titled “Linking Delay Announcement, Abandonment, and Staffing: A Behavioral Perspective”
Work-In-Progress
  1. “On the Display Format of Delay Information: A Large Scale Field Experiment on A Ridesharing Platform”, with Yiming Zhang* and Yong-Pin Zhou
  2. “Are Customers Satisfaction Biased: Evidence from a Restaurant Chain “, with Masoud Kamalahmadi* and Yong-Pin Zhou
  3. “Optimizing Real-time Compensation for Waiting in Queue: a Personalized Algorithm Validated by a Field Experiment on a ridesharing platform”, with Yiming Zhang and Yong-Pin Zhou
  4. “Fairness in Algorithm-driven Scheduling “
  5. “Timing Matters: Sourcing Workers in On-demand Freight Matching Platforms”, with Ziqi Dong* and Guangwen Kong
  6. “Fairness in Policing and Crime Prevention: a machine learning approach with causal inference”, with Zheng Dong, Yao Xie and He Wang