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9:00 AM - 10:00 AM
Laurens Debo and Robert Shumsky, Jeunghyun Kim
Wait Time Announcements to Increase Customer Satisfaction
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Wait Time Announcements to Increase Customer Satisfaction
Speaker:
Laurens Debo and Robert Shumsky,
Jeunghyun Kim
Time: 9:00 AM - 10:00 AM
Location:
Title. Wait Time Announcements to Increase Customer Satisfaction Authors. Jeunghyun Kim (Korea University Business School), Laurens Debo (Tuck), and Robert Shumsky (Tuck) Abstract. We develop a model to optimize the provision of queue-position information to waiting customers. A customer’s emotional response, and satisfaction with the wait, may be driven by loss aversion in expected waiting time and/or by disutility due to wait-time uncertainty (we call this latter effect ‘uncertainty awareness’). We first consider three announcement strategies: no-information where a customer does not receive any updates until service begins, arrival-only where a customer is informed of the initial queue position, and full-information where a customer is informed of the initial position as well as all subsequent changes in position. Using a diffusion approximation of an M/G/1 queue, we find that for loss averse customers, arrival-only is optimal, while for uncertainty aware customers full-information is optimal. For customers affected by both loss aversion and uncertainty, the arrival-only strategy becomes more appealing as the mean service time decreases or service time variance increases. We also examine partial information, where customers are informed of their arrival to some queue positions but not all. For the diffusion approximation we find that announcements that are evenly-spaced throughout the progression through the queue is optimal. In addition, uncertainty-aware disutility is convex in the number of announcements, indicating that ‘a little information can go a long way.’
12:00 PM - 1:30 PM
Alexandre Jacquillat
Branch-and-price for prescriptive contagion analytics
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Branch-and-price for prescriptive contagion analytics
Speaker: Alexandre Jacquillat
Time: 12:00 PM - 1:30 PM
Location:
12:00 PM - 1:30 PM
Shi Chen
Operations Management in Cloud Computing: Pricing and Capacity Planning
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Operations Management in Cloud Computing: Pricing and Capacity Planning
Speaker: Shi Chen
Time: 12:00 PM - 1:30 PM
Location:
12:15 PM - 1:30 PM
Swanand Kulkarni
Pay Model Intuitiveness and Transparency on On-Demand Service Platforms
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Pay Model Intuitiveness and Transparency on On-Demand Service Platforms
Speaker: Swanand Kulkarni
Time: 12:15 PM - 1:30 PM
Location:
11:30 AM - 1:30 PM
Evgeny Kagan
Beyond Averages: How Do Customers Respond to Wait Time Distributions?
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Beyond Averages: How Do Customers Respond to Wait Time Distributions?
Speaker: Evgeny Kagan
Time: 11:30 AM - 1:30 PM
Location:
12:15 PM - 1:30 PM
Clare Snyder
Algorithm Reliance, Fast and Slow
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Algorithm Reliance, Fast and Slow
Speaker: Clare Snyder
Time: 12:15 PM - 1:30 PM
Location:
12:15 PM - 1:30 PM
Tauhid Zaman
Social Media Suspensions and Shadow Banning: Political Bias or Genuine Disinformation Control?
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Social Media Suspensions and Shadow Banning: Political Bias or Genuine Disinformation Control?
Speaker: Tauhid Zaman
Time: 12:15 PM - 1:30 PM
Location:
12:00 PM - 5:00 PM
Ruth Beer, Park Sinchaisri, Enno Siemsen, Kamalini Ramdas, Michelle Kinch
Operations & Management Science Fall Workshop - 2 Days
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Operations & Management Science Fall Workshop - 2 Days
Speaker:
Ruth Beer,
Park Sinchaisri,
Enno Siemsen,
Kamalini Ramdas,
Michelle Kinch
Time: 12:00 PM - 5:00 PM
Location:
2 days: 12-5pm on 11/14 and 8am - 1pm on 11/15 Featuring talks by: Ruth Beer (Baruch) Park Sinchaisri (Berkeley Enno Siemsen (Wisconsin) Kamalini Ramdas (London) Michelle Kinch (Tuck)
12:15 PM - 1:30 PM
Manish Raghavan
The role of information in human-AI systems
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The role of information in human-AI systems
Speaker: Manish Raghavan
Time: 12:15 PM - 1:30 PM
Location:
12:15 PM - 1:30 PM
Lauren Lu
Generative AI in Action: Field Experimental Evidence on Worker Performance in E-Commerce Customer Service Operations
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Generative AI in Action: Field Experimental Evidence on Worker Performance in E-Commerce Customer Service Operations
Speaker: Lauren Lu
Time: 12:15 PM - 1:30 PM
Location:
12:15 PM - 1:30 PM
Michael Hamilton
Semi-Personalized Pricing: Algorithms and Implications
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Semi-Personalized Pricing: Algorithms and Implications
Speaker: Michael Hamilton
Time: 12:15 PM - 1:30 PM
Location:
12:00 PM - 1:45 PM
Bijan H. Mazaheri
Synthetic Potential Outcomes and Causal Mixture Identifiability
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Synthetic Potential Outcomes and Causal Mixture Identifiability
Speaker: Bijan H. Mazaheri
Time: 12:00 PM - 1:45 PM
Location:
12:15 PM - 1:45 PM
Galit Yom-Tov
Operationalizing Emotional Load: The Human Side of Queueing Systems
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Operationalizing Emotional Load: The Human Side of Queueing Systems
Speaker: Galit Yom-Tov
Time: 12:15 PM - 1:45 PM
Location:
12:15 PM - 1:30 PM
Daniel Guetta
Teaching Business School Students in the 21st Century: data, coding, AI, and more
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Teaching Business School Students in the 21st Century: data, coding, AI, and more
Speaker: Daniel Guetta
Time: 12:15 PM - 1:30 PM
Location:
The world is changing exponentially faster than it once was, and topics that used to be the preserve of engineers alone are now central to many businesses' core strategy. How should we change the way we teach technical topics in business schools in response? In this talk, I will begin by briefly sharing some lessons I have learned in my seven years at Columbia, during which I have had the privilege of teaching 10 distinct classes, with just under 7,000 students enrolled from Columbia Business School's MBA and EMBA programs, and from our joint programs with the engineering school. The bulk of my talk will then focus on five case studies, time permitting, in which I will discuss the tools and cases I use to teach five specific topics: the Lasso, fundamentals of deep learning, coding in Python, large language model embeddings, and market design. I will end with a discussion of what comes next for us as educators in business schools.
12:15 PM - 1:30 PM
Rad Niazadeh
Dynamic Matching for Refugee Resettlement: A Case Study
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Dynamic Matching for Refugee Resettlement: A Case Study
Speaker: Rad Niazadeh
Time: 12:15 PM - 1:30 PM
Location:
Refugee resettlement is an international effort that aims to provide a durable solution for the current global refugee crisis. The goal is to help refugee families to find a new home in a host country and eventually find a new job to get “resettled”. In this seminar, I will talk about a recent paper in partnership with a major national agency working on refugee resettlement in the United States. In this work, we re-design the core dynamic matching algorithm used by our partner, for sequential yearly assignment of refugee cases to our partner's affiliate locations. These localities should be thought of as service centers providing vocational services or assistance with job search, and many times are short in staff. I discuss various operational intricacies in this dynamic matching problem, such as lack of reliable arrival prior data, predicting employment outcomes of each match, and controlling backlogs in those service centers. I also discuss regulatory constraints imposed on the problem, such as family re-unification ties for refugees and their implications on our algorithm. Then I will introduce a new algorithmic framework to study this problem, through which I show how to design and analyze near-optimal learning-based primal-dual algorithms that aim to maximize employment outcomes while respecting operational and regulatory constraints in this problem. Time permits, I'll discuss a case study for evaluating the empirical performance of our algorithms using our partner's data and discuss some details of our collaboration.
12:15 PM - 1:30 PM
Canan Gunes Corlu
TBD
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TBD
Speaker: Canan Gunes Corlu
Time: 12:15 PM - 1:30 PM
Location:
12:00 PM - 5:00 PM
TBD
Operations Spring Conference
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Operations Spring Conference
Speaker: TBD
Time: 12:00 PM - 5:00 PM
Location:
8:00 AM - 1:00 PM
TBD
Operations Seminar Conference
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Operations Seminar Conference
Speaker: TBD
Time: 8:00 AM - 1:00 PM
Location: