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- research-articleJuly 2023
Ancillary Services in Targeted Advertising: From Prediction to Prescription
- Alison Borenstein,
- Ankit Mangal,
- Georgia Perakis,
- Stefan Poninghaus,
- Divya Singhvi,
- Omar Skali Lami,
- Jiong Wei Lua
Manufacturing & Service Operations Management (INFORMS-MSOM), Volume 25, Issue 4Pages 1285–1303https://doi.org/10.1287/msom.2020.0491Problem definition: Online retailers provide recommendations of ancillary services when a customer is making a purchase. Our goal is to predict the net present value (NPV) of these services, estimate the probability of a customer subscribing to each of ...
- research-articleMay 2023
COVID-19: Prediction, Prevalence, and the Operations of Vaccine Allocation
- Amine Bennouna,
- Joshua Joseph,
- David Nze-Ndong,
- Georgia Perakis,
- Divya Singhvi,
- Omar Skali Lami,
- Yannis Spantidakis,
- Leann Thayaparan,
- Asterios Tsiourvas
Manufacturing & Service Operations Management (INFORMS-MSOM), Volume 25, Issue 3Pages 1013–1032https://doi.org/10.1287/msom.2022.1160Problem definition: Mitigating the COVID-19 pandemic poses a series of unprecedented challenges, including predicting new cases and deaths, understanding true prevalence beyond what tests are able to detect, and allocating different vaccines across ...
- research-articleApril 2023
High-Low Promotion Policies for Peak-End Demand Models
In-store promotions are a highly effective marketing tool that can have a significant impact on revenue. In this research, we study the question of dynamic promotion planning in the face of Bounded-Memory Peak-End demand models. In order to determine ...
- research-articleMarch 2023
Pricing for Heterogeneous Products: Analytics for Ticket Reselling
Manufacturing & Service Operations Management (INFORMS-MSOM), Volume 25, Issue 2Pages 409–426https://doi.org/10.1287/msom.2021.1065Problem definition: We present a data-driven study of the secondary ticket market. In particular, we are primarily concerned with accurately estimating price sensitivity for listed tickets. In this setting, there are many issues including endogeneity, ...
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- research-articleMarch 2023
Detecting Customer Trends for Optimal Promotion Targeting
Manufacturing & Service Operations Management (INFORMS-MSOM), Volume 25, Issue 2Pages 448–467https://doi.org/10.1287/msom.2020.0893Problem definition: Retailers have become increasingly interested in personalizing their products and services such as promotions. For this, we need new personalized demand models. Unfortunately, social data are not available to many retailers because of ...
- research-articleMarch 2023
Robust Pricing and Production with Information Partitioning and Adaptation
We introduce a new distributionally robust optimization model to address a two-period, multiitem joint pricing and production problem, which can be implemented in a data-driven setting using historical demand and side information pertinent to the ...
- research-articleFebruary 2023
End-to-end learning for optimization via constraint-enforcing approximators
AAAI'23/IAAI'23/EAAI'23: Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence and Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence and Thirteenth Symposium on Educational Advances in Artificial IntelligenceArticle No.: 815, Pages 7253–7260https://doi.org/10.1609/aaai.v37i6.25884In many real-world applications, predictive methods are used to provide inputs for downstream optimization problems. It has been shown that using the downstream task-based objective to learn the intermediate predictive model is often better than using ...
- research-articleAugust 2022
The role of optimization in some recent advances in data-driven decision-making
Mathematical Programming: Series A and B (MPRG), Volume 200, Issue 1Pages 1–35https://doi.org/10.1007/s10107-022-01874-9AbstractData-driven decision-making has garnered growing interest as a result of the increasing availability of data in recent years. With that growth many opportunities and challenges have sprung up in the areas of predictive and prescriptive analytics. ...
- research-articleJuly 2022
Distribution-Free Pricing
Manufacturing & Service Operations Management (INFORMS-MSOM), Volume 24, Issue 4Pages 1939–1958https://doi.org/10.1287/msom.2021.1055Problem definition: We study a monopolistic robust pricing problem in which the seller does not know the customers’ valuation distribution for a product but knows its mean and variance. Academic/practical relevance: This minimal requirement for ...
- research-articleJuly 2022
Learning Personalized Product Recommendations with Customer Disengagement
Manufacturing & Service Operations Management (INFORMS-MSOM), Volume 24, Issue 4Pages 2010–2028https://doi.org/10.1287/msom.2021.1047Problem definition: We study personalized product recommendations on platforms when customers have unknown preferences. Importantly, customers may disengage when offered poor recommendations. Academic/practical relevance: Online platforms often ...
- research-articleMay 2022
On a Variation of Two-Part Tariff Pricing of Services: A Data-Driven Approach
Manufacturing & Service Operations Management (INFORMS-MSOM), Volume 24, Issue 3Pages 1369–1387https://doi.org/10.1287/msom.2021.1069Problem definition: We present a data-driven pricing problem motivated from our collaboration with a satellite service provider. In particular, we study a variant of the two-part tariff pricing scheme. The firm offers a set of data plans consisting of a ...
- doctoral_thesisJanuary 2022
Interior Point and Outer Approximation Methods for Conic Optimization
AbstractAny convex optimization problem may be represented as a conic problem that minimizes a linear function over the intersection of an affine subspace with a convex cone. An advantage of representing convex problems in conic form is that, under ...
- doctoral_thesisJanuary 2022
Predictive and Prescriptive Analytics in Operations Management
AbstractThe recent surge in data availability and advances in hardware and software and the recent developments and democratization of analytics highlight the critical importance of prediction and prescription in harnessing the power of data to create ...
- research-articleApril 2021
Promotion Optimization for Multiple Items in Supermarkets
Promotions are a critical decision for supermarket managers, who must decide the price promotions for a large number of items. Retailers often use promotions to boost the sales of the different items by leveraging the cross-item effects. We formulate the ...
- research-articleDecember 2020
Frontiers in Service Science: The Management of Data Analytics Services: New Challenges and Future Directions
In this short paper, we discuss the impact of data analytics in services and delineate future research directions for the field. After illustrating how data analytics are transforming different service sectors, we consider the provision of data analysis ...
- research-articleJune 2020
A Simple Rule for Pricing with Limited Knowledge of Demand
How should a firm price a new product for which little is known about demand? We propose a simple and practical pricing rule for new products where demand information is limited. The rule is simple: Set price as though the demand curve were linear. Our ...
- research-articleMay 2020
A Data-Driven Approach to Personalized Bundle Pricing and Recommendation
Manufacturing & Service Operations Management (INFORMS-MSOM), Volume 22, Issue 3Pages 461–480https://doi.org/10.1287/msom.2018.0756Problem definition: The growing trend in online shopping has sparked the development of increasingly more sophisticated product recommendation systems. We construct a model that recommends a personalized discounted product bundle to an online shopper that ...
- doctoral_thesisJanuary 2020
Investigations in Applied Probability and High-Dimensional Statistics
AbstractThis thesis makes contributions to the areas of applied probability and high-dimensional statistics. We introduce the Attracting Random Walks model. which is a Markov chain model on a graph. In the Attracting Random Walks model, particles move ...