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March–April 2023
Article

Market Segmentation Trees

By: Ali Aouad, Adam Elmachtoub, Kris J. Ferreira and Ryan McNellis

Problem definition: We seek to provide an interpretable framework for segmenting users in a population for personalized decision making. Methodology/results: We propose a general methodology, market segmentation trees (MSTs), for learning market... View Details

Keywords: Decision Trees; Computational Advertising; Market Segmentation; Analytics and Data Science; E-commerce; Consumer Behavior; Marketplace Matching; Marketing Channels; Digital Marketing

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January–February 2023
Article

Forecasting COVID-19 and Analyzing the Effect of Government Interventions

By: Michael Lingzhi Li, Hamza Tazi Bouardi, Omar Skali Lami, Thomas Trikalinos, Nikolaos Trichakis and Dimitris Bertsimas

We developed DELPHI, a novel epidemiological model for predicting detected cases and deaths in the prevaccination era of the COVID-19 pandemic. The model allows for underdetection of infections and effects of government interventions. We have applied DELPHI across more... View Details

Keywords: COVID-19 Pandemic; Epidemics; Analytics and Data Science; Health Pandemics; AI and Machine Learning; Forecasting and Prediction

2023
Working Paper

Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development

By: Daniel Yue, Paul Hamilton and Iavor Bojinov

Predictive model development is understudied despite its centrality in modern artificial intelligence and machine learning business applications. Although prior discussions highlight advances in methods (along the dimensions of data, computing power, and algorithms)... View Details

Keywords: Analytics and Data Science

2022
Article

Which Explanation Should I Choose? A Function Approximation Perspective to Characterizing Post hoc Explanations

By: Tessa Han, Suraj Srinivas and Himabindu Lakkaraju

A critical problem in the field of post hoc explainability is the lack of a common foundational goal among methods. For example, some methods are motivated by function approximation, some by game theoretic notions, and some by obtaining clean visualizations. This... View Details

Keywords: Mathematical Methods; Decision Choices and Conditions; Analytics and Data Science

October 2022 (Revised December 2022)
Case

SMART: AI and Machine Learning for Wildlife Conservation

By: Brian Trelstad and Bonnie Yining Cao

Spatial Monitoring and Reporting Tool (SMART), a set of software and analytical tools designed for the purpose of wildlife conservation, had demonstrated significant improvements in patrol coverage, with some observed reductions in poaching and contributing to wildlife... View Details

Keywords: Business and Government Relations; Emerging Markets; Technology Adoption; Strategy; Management; Ethics; Social Enterprise; AI and Machine Learning; Analytics and Data Science; Natural Environment; Technology Industry; Cambodia; United States; Africa

August 2022
Article

What Makes a Good Image? Airbnb Demand Analytics Leveraging Interpretable Image Features

By: Shunyuan Zhang, Dokyun Lee, Param Vir Singh and Kannan Srinivasan

We study how Airbnb property demand changed after the acquisition of verified images (taken by Airbnb’s photographers) and explore what makes a good image for an Airbnb property. Using deep learning and difference-in-difference analyses on an Airbnb panel dataset... View Details

Keywords: Sharing Economy; Airbnb; Property Demand; Computer Vision; Deep Learning; Image Feature Extraction; Content Engineering; Property; Marketing; Demand and Consumers

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March 2022 (Revised January 2025)
Technical Note

Prediction & Machine Learning

By: Iavor I. Bojinov, Michael Parzen and Paul Hamilton

This note provides an introduction to machine learning for an introductory data science course. The note begins with a description of supervised, unsupervised, and reinforcement learning. Then, the note provides a brief explanation of the difference between traditional... View Details

Keywords: Machine Learning; Data Science; Learning; Analytics and Data Science; Performance Evaluation; AI and Machine Learning

March 2022
Article

Where to Locate COVID-19 Mass Vaccination Facilities?

By: Dimitris Bertsimas, Vassilis Digalakis Jr, Alexander Jacquillat, Michael Lingzhi Li and Alessandro Previero

The outbreak of COVID-19 led to a record-breaking race to develop a vaccine. However, the limited vaccine capacity creates another massive challenge: how to distribute vaccines to mitigate the near-end impact of the pandemic? In the United States in particular, the new... View Details

Keywords: Vaccines; COVID-19; Health Care and Treatment; Health Pandemics; Performance Effectiveness; Analytics and Data Science; Mathematical Methods

2022
Working Paper

The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective

By: Satyapriya Krishna, Tessa Han, Alex Gu, Javin Pombra, Shahin Jabbari, Steven Wu and Himabindu Lakkaraju

As various post hoc explanation methods are increasingly being leveraged to explain complex models in high-stakes settings, it becomes critical to develop a deeper understanding of if and when the explanations output by these methods disagree with each other, and how... View Details

Keywords: AI and Machine Learning; Analytics and Data Science; Mathematical Methods

January 2022
Technical Note

Introduction to Capital Structure Analytics

By: Samuel Antill and Ted Berk

This technical note provides an overview of key analytical approaches that are useful in assessing the appropriateness of a firm’s capital structure and funding plan. This note introduces basic quantitative tools and metrics that are commonly used as inputs to this... View Details

Keywords: Budgets and Budgeting; Business Plan; Forecasting and Prediction; Borrowing and Debt; Corporate Finance; Capital Structure; Cash Flow; Financial Liquidity; Financial Management; Financing and Loans

Article

A Prescriptive Analytics Framework for Optimal Policy Deployment Using Heterogeneous Treatment Effects

By: Edward McFowland III, Sandeep Gangarapu, Ravi Bapna and Tianshu Sun

We define a prescriptive analytics framework that addresses the needs of a constrained decision-maker facing, ex ante, unknown costs and benefits of multiple policy levers. The framework is general in nature and can be deployed in any utility maximizing context, public... View Details

Keywords: Prescriptive Analytics; Heterogeneous Treatment Effects; Optimization; Observed Rank Utility Condition (OUR); Between-treatment Heterogeneity; Machine Learning; Decision Making; Analysis; Mathematical Methods

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August 2021 (Revised February 2024)
Case

Data Science at the Warriors

By: Iavor I. Bojinov and Michael Parzen

The case explores the development and early growth of a data science team at the Golden State Warriors, an NBA team based in San Francisco. The case begins by explaining the initial rationale for investing in data science, then covers a debate on the appropriate team... View Details

Keywords: Digital Marketing; Analysis; Forecasting and Prediction; Technological Innovation; Information Technology; Analytics and Data Science; Sports Industry; San Francisco; United States

June 2021
Technical Note

Introduction to Linear Regression

By: Michael Parzen and Paul Hamilton

This technical note introduces (from an applied point of view) the theory and application of simple and multiple linear regression. The motivation for the model is introduced, as well as how to interpret the summary output with regard to prediction and statistical... View Details

Keywords: Linear Regression; Regression; Analysis; Forecasting and Prediction; Risk and Uncertainty; Theory; Compensation and Benefits; Mathematical Methods; Analytics and Data Science

May 2021 (Revised February 2024)
Teaching Note

THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)

By: Ayelet Israeli and Jill Avery

THE YES, a multi-brand shopping app launched in May 2020 offered a new type of buying experience for women’s fashion, driven by a sophisticated algorithm that used data science and machine learning to create and deliver a personalized store for every shopper, based on... View Details

Keywords: Data; Data Analytics; Artificial Intelligence; AI; AI Algorithms; AI Creativity; Fashion; Retail; Retail Analytics; E-Commerce Strategy; Platform; Platforms; Big Data; Preference Elicitation; Predictive Analytics; App Development; ＂Marketing Analytics＂; Advertising; Mobile App; Mobile Marketing; Apparel; Online Advertising; Referral Rewards; Referrals; Female Ceo; Female Entrepreneur; Female Protagonist; Analytics and Data Science; Analysis; Creativity; Marketing Strategy; Brands and Branding; Consumer Behavior; Demand and Consumers; Forecasting and Prediction; Marketing Channels; Digital Marketing; Internet and the Web; Mobile and Wireless Technology; AI and Machine Learning; E-commerce; Digital Platforms; Fashion Industry; Retail Industry; Apparel and Accessories Industry; Consumer Products Industry; United States

2020
Working Paper

Is Accounting Useful for Forecasting GDP Growth? A Machine Learning Perspective

By: Srikant Datar, Apurv Jain, Charles C.Y. Wang and Siyu Zhang

We provide a comprehensive examination of whether, to what extent, and which accounting variables are useful for improving the predictive accuracy of GDP growth forecasts. We leverage statistical models that accommodate a broad set of (341) variables—outnumbering the... View Details

Keywords: Big Data; Elastic Net; GDP Growth; Machine Learning; Macro Forecasting; Short Fat Data; Accounting; Economic Growth; Forecasting and Prediction; Analytics and Data Science

2021
Working Paper

Time Dependency, Data Flow, and Competitive Advantage

By: Ehsan Valavi, Joel Hestness, Marco Iansiti, Newsha Ardalani, Feng Zhu and Karim R. Lakhani

Data is fundamental to machine learning-based products and services and is considered strategic due to its externalities for businesses, governments, non-profits, and more generally for society. It is renowned that the value of organizations (businesses, government... View Details

Keywords: Economics Of AI; Value Of Data; Perishability; Time Dependency; Flow Of Data; Data Strategy; Analytics and Data Science; Value; Strategy; Competitive Advantage

March 2021 (Revised January 2022)
Case

Philips: Redefining Telehealth

By: Regina E. Herzlinger, Alec Petersen, Natalie Kindred and Sara M. McKinley

As one of the world’s largest healthcare companies, Philips sought to reach beyond the walls of the hospital and expand its hospital-to-home program to gain future competitive advantage through technology solutions combining predictive analytics with care delivery. By... View Details

February 2021
Case

Digital Manufacturing at Amgen

By: Shane Greenstein, Kyle R. Myers and Sarah Mehta

This case discusses efforts made by biotechnology (biotech) company Amgen to introduce digital technologies into its manufacturing processes. Doing so is complicated by the fact that the process for manufacturing biologics—or therapeutics made from living cells—is... View Details

January 2021 (Revised March 2021)
Case

THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)

By: Jill Avery, Ayelet Israeli and Emma von Maur

THE YES, a multi-brand shopping app launched in May 2020 offered a new type of buying experience for women’s fashion, driven by a sophisticated algorithm that used data science and machine learning to create and deliver a personalized store for every shopper, based on... View Details

Keywords: Data; Data Analytics; Artificial Intelligence; AI; AI Algorithms; AI Creativity; Fashion; Retail; Retail Analytics; E-Commerce Strategy; Platform; Platforms; Big Data; Preference Elicitation; Preference Prediction; Predictive Analytics; App Development; ＂Marketing Analytics＂; Advertising; Mobile App; Mobile Marketing; Apparel; Online Advertising; Referral Rewards; Referrals; Female Ceo; Female Entrepreneur; Female Protagonist; Analytics and Data Science; Analysis; Creativity; Marketing Strategy; Brands and Branding; Consumer Behavior; Demand and Consumers; Forecasting and Prediction; Marketing Channels; Digital Marketing; Internet and the Web; Mobile and Wireless Technology; AI and Machine Learning; E-commerce; Digital Platforms; Fashion Industry; Retail Industry; Apparel and Accessories Industry; Consumer Products Industry; United States

June 2021
Article

From Predictions to Prescriptions: A Data-driven Response to COVID-19

By: Dimitris Bertsimas, Léonard Boussioux, Ryan Cory-Wright, Arthur Delarue, Vassilis Digalakis Jr, Alexander Jacquillat, Driss Lahlou Kitane, Galit Lukin, Michael Lingzhi Li, Luca Mingardi, Omid Nohadani, Agni Orfanoudaki, Theodore Papalexopoulos, Ivan Paskov, Jean Pauphilet, Omar Skali Lami, Bartolomeo Stellato, Hamza Tazi Bouardi, Kimberly Villalobos Carballo, Holly Wiberg and Cynthia Zeng

The COVID-19 pandemic has created unprecedented challenges worldwide. Strained healthcare providers make difficult decisions on patient triage, treatment and care management on a daily basis. Policy makers have imposed social distancing measures to slow the disease, at... View Details

Keywords: COVID-19; Health Pandemics; AI and Machine Learning; Forecasting and Prediction; Analytics and Data Science

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