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- 2024
- Working Paper
Primary Capital Market Transactions and Index Funds
By: Marco Sammon and Chris Murray
We document the effects of mechanical buying by CRSP-index-tracking funds on post-IPO returns and IPO deal structure. Leveraging a difference-in-differences-style design built on a 2017 CRSP rule change, we find that expected index fund demand leads fast track IPOs to...
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Keywords:
Investment Funds;
Initial Public Offering;
Investment Return;
Price;
Market Transactions;
Financial Markets
Sammon, Marco, and Chris Murray. "Primary Capital Market Transactions and Index Funds." Working Paper, August 2024.
- 2024
- Working Paper
Digital Platforms 2.0: Learnings, Opportunities, and Challenges
By: Shrabastee Banerjee, Ishita Chakraborty, Hana Choi, Hannes Datta, Remi Daviet, Chiara Farronato, Minkyung Kim, Anja Lambrecht, Puneet Manchanda, Aniko Oery, Ananya Sen, Marshall W Van Alstyne, Prasad Vana, Kenneth C Wilbur, Xu Zhang and Bobby Zhou
Platform-based digital ecosystems form the backbone of our interactions with the Internet. Over the past decade, digital ecosystems have witnessed significant growth, both in terms of industry footprint and academic research. Yet, the challenges associated with their...
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Banerjee, Shrabastee, Ishita Chakraborty, Hana Choi, Hannes Datta, Remi Daviet, Chiara Farronato, Minkyung Kim, Anja Lambrecht, Puneet Manchanda, Aniko Oery, Ananya Sen, Marshall W Van Alstyne, Prasad Vana, Kenneth C Wilbur, Xu Zhang, and Bobby Zhou. "Digital Platforms 2.0: Learnings, Opportunities, and Challenges." Working Paper, June 2024.
- July–August 2024
- Article
Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals
By: Ta-Wei Huang and Eva Ascarza
Firms are increasingly interested in developing targeted interventions for customers with the best response,
which requires identifying differences in customer sensitivity, typically through the conditional average treatment
effect (CATE) estimation. In theory, to...
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Keywords:
Long-run Targeting;
Heterogeneous Treatment Effect;
Statistical Surrogacy;
Customer Churn;
Field Experiments;
Consumer Behavior;
Customer Focus and Relationships;
AI and Machine Learning;
Marketing Strategy
Huang, Ta-Wei, and Eva Ascarza. "Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals." Marketing Science 43, no. 4 (July–August 2024): 863–884.
- 2024
- Working Paper
What Makes Players Pay? An Empirical Investigation of In-Game Lotteries
By: Tomomichi Amano and Andrey Simonov
In 2020, gamers spent more than $15 billion on loot boxes, lotteries of virtual items in video
games. Paid loot boxes are contentious. Game producers argue that loot boxes complement
the gameplay and expenditures on loot boxes reflect players’ enjoyment of the game....
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Keywords:
Product Design;
Consumer Behavior;
Ethics;
Governing Rules, Regulations, and Reforms;
Video Game Industry
Amano, Tomomichi, and Andrey Simonov. "What Makes Players Pay? An Empirical Investigation of In-Game Lotteries." Columbia Business School Research Paper, No. 4355019, June 2024.
- 2024
- Working Paper
Personalization and Targeting: How to Experiment, Learn & Optimize
By: Aurelie Lemmens, Jason M.T. Roos, Sebastian Gabel, Eva Ascarza, Hernan Bruno, Elea McDonnell Feit, Brett Gordon, Ayelet Israeli, Carl F. Mela and Oded Netzer
Personalization has become the heartbeat of modern marketing. Advances in causal inference and machine learning enable companies to understand how the same marketing action can impact the choices of individual customers differently. This article provides an academic...
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Keywords:
Personalization;
Targeting;
Experiments;
Observational Studies;
Policy Implementation;
Policy Evaluation;
Customization and Personalization;
Marketing Strategy;
AI and Machine Learning
Lemmens, Aurelie, Jason M.T. Roos, Sebastian Gabel, Eva Ascarza, Hernan Bruno, Elea McDonnell Feit, Brett Gordon, Ayelet Israeli, Carl F. Mela, and Oded Netzer. "Personalization and Targeting: How to Experiment, Learn & Optimize." Working Paper, June 2024.
- June 2024
- Article
Redistributive Allocation Mechanisms
By: Mohammad Akbarpour, Piotr Dworczak and Scott Duke Kominers
Many scarce public resources are allocated at below-market-clearing prices, and sometimes for free. Such "non-market" mechanisms sacrifice some surplus, yet they can potentially improve equity. We develop a model of mechanism design with redistributive concerns. Agents...
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Akbarpour, Mohammad, Piotr Dworczak, and Scott Duke Kominers. "Redistributive Allocation Mechanisms." Journal of Political Economy 132, no. 6 (June 2024): 1831–1875. (Authors' names are in certified random order.)
- 2024
- Working Paper
Business Experiments as Persuasion
By: Orie Shelef, Rebecca Karp and Robert Wuebker
Much of the prior work on experimentation rests upon the assumption that entrepreneurs and managers use—or should optimally adopt—a "scientific approach" to test possible decisions before making them. This paper offers an alternative view of experimental strategy,...
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Shelef, Orie, Rebecca Karp, and Robert Wuebker. "Business Experiments as Persuasion." Harvard Business School Working Paper, No. 24-065, March 2024.
- March 2024
- Case
Hippo: Weathering the Storm of the Home Insurance Crisis
By: Lauren Cohen, Grace Headinger and Sophia Pan
Rick McCathron, CEO of Hippo, considered how the firm’s underwriting model could account for the effects of climate change. Along with providing smart home packages, targeting risk-friendly customers, and using data-driven pricing, the Insurtech used technologically...
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Keywords:
Fintech;
Underwriters;
Big Data;
Insurance Companies;
Business Model Design;
Weather Insurance;
Business Model;
Forecasting and Prediction;
Climate Change;
Environmental Sustainability;
Green Technology;
Technological Innovation;
Natural Environment;
Natural Disasters;
Weather;
Business Strategy;
Competitive Advantage;
Business Earnings;
Insurance;
Social Issues;
Insurance Industry;
United States;
California
- March 2024
- Case
Unintended Consequences of Algorithmic Personalization
By: Eva Ascarza and Ayelet Israeli
“Unintended Consequences of Algorithmic Personalization” (HBS No. 524-052) investigates algorithmic bias in marketing through four case studies featuring Apple, Uber, Facebook, and Amazon. Each study presents scenarios where these companies faced public criticism for...
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Keywords:
Race;
Gender;
Marketing;
Diversity;
Customer Relationship Management;
Prejudice and Bias;
Customization and Personalization;
Technology Industry;
Retail Industry;
United States
Ascarza, Eva, and Ayelet Israeli. "Unintended Consequences of Algorithmic Personalization." Harvard Business School Case 524-052, March 2024.
- 2024
- Working Paper
Warnings and Endorsements: Improving Human-AI Collaboration Under Covariate Shift
By: Matthew DosSantos DiSorbo and Kris Ferreira
Problem definition: While artificial intelligence (AI) algorithms may perform well on data that are representative of the training set (inliers), they may err when extrapolating on non-representative data (outliers). These outliers often originate from covariate shift,...
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DosSantos DiSorbo, Matthew, and Kris Ferreira. "Warnings and Endorsements: Improving Human-AI Collaboration Under Covariate Shift." Working Paper, February 2024.
- December 2023
- Case
TikTok: The Algorithm Will See You Now
By: Shikhar Ghosh and Shweta Bagai
In a world where attention is a scarce commodity, this case explores the meteoric rise of TikTok—an app that transformed from a niche platform for teens into the most visited domain by 2021—surpassing even Google. Its algorithm was a sophisticated mechanism for...
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Keywords:
Social Media;
Applications and Software;
Disruptive Innovation;
Business and Government Relations;
International Relations;
Cybersecurity;
Culture;
Technology Industry;
China;
United States;
India
Ghosh, Shikhar, and Shweta Bagai. "TikTok: The Algorithm Will See You Now." Harvard Business School Case 824-125, December 2023.
- November 2023
- Article
Algorithmic Mechanism Design with Investment
By: Mohammad Akbarpour, Scott Duke Kominers, Kevin Michael Li, Shengwu Li and Paul Milgrom
We study the investment incentives created by truthful mechanisms that allocate resources using approximation algorithms. Some approximation algorithms guarantee nearly 100% of the optimal welfare, but have only a zero guarantee when one bidder can invest before...
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Akbarpour, Mohammad, Scott Duke Kominers, Kevin Michael Li, Shengwu Li, and Paul Milgrom. "Algorithmic Mechanism Design with Investment." Econometrica 91, no. 6 (November 2023): 1969–2003.
- 2023
- Article
Which Models Have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness
By: Suraj Srinivas, Sebastian Bordt and Himabindu Lakkaraju
One of the remarkable properties of robust computer vision models is that their input-gradients are often aligned with human perception, referred to in the literature as perceptually-aligned gradients (PAGs). Despite only being trained for classification, PAGs cause...
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Srinivas, Suraj, Sebastian Bordt, and Himabindu Lakkaraju. "Which Models Have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- Working Paper
An AI Method to Score Celebrity Visual Potential from Human Faces
By: Flora Feng, Shunyuan Zhang, Xiao Liu, Kannan Srinivasan and Cait Lamberton
Celebrities have extraordinary abilities to attract and influence others. Predicting celebrity visual potential is important in the domains of business, politics, media, and entertainment. Can we use human faces to predict celebrity visual potential? If so, which...
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Feng, Flora, Shunyuan Zhang, Xiao Liu, Kannan Srinivasan, and Cait Lamberton. "An AI Method to Score Celebrity Visual Potential from Human Faces." SSRN Working Paper Series, No. 4071188, November 2023.
- November–December 2023
- Article
Network Centralization and Collective Adaptability to a Shifting Environment
By: Ethan S. Bernstein, Jesse C. Shore and Alice J. Jang
We study the connection between communication network structure and an organization’s collective adaptability to a shifting environment. Research has shown that network centralization—the degree to which communication flows disproportionately through one or more...
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Keywords:
Network Centralization;
Collective Intelligence;
Organizational Change and Adaptation;
Organizational Structure;
Communication;
Decision Making;
Networks;
Adaptation
Bernstein, Ethan S., Jesse C. Shore, and Alice J. Jang. "Network Centralization and Collective Adaptability to a Shifting Environment." Organization Science 34, no. 6 (November–December 2023): 2064–2096.
- October 2023
- Article
Matching Mechanisms for Refugee Resettlement
By: David Delacrétaz, Scott Duke Kominers and Alexander Teytelboym
Current refugee resettlement processes account for neither the preferences of refugees nor the priorities of hosting communities. We introduce a new framework for matching with multidimensional knapsack constraints that captures the (possibly multidimensional) sizes of...
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Keywords:
Refugee Resettlement;
Matching;
Matching Markets;
Matching Platform;
Matching With Contracts;
Algorithms;
Refugees;
Market Design
Delacrétaz, David, Scott Duke Kominers, and Alexander Teytelboym. "Matching Mechanisms for Refugee Resettlement." American Economic Review 113, no. 10 (October 2023): 2689–2717.
- September–October 2023
- Article
Interpretable Matrix Completion: A Discrete Optimization Approach
By: Dimitris Bertsimas and Michael Lingzhi Li
We consider the problem of matrix completion on an n × m matrix. We introduce the problem of interpretable matrix completion that aims to provide meaningful insights for the low-rank matrix using side information. We show that the problem can be...
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Keywords:
Mathematical Methods
Bertsimas, Dimitris, and Michael Lingzhi Li. "Interpretable Matrix Completion: A Discrete Optimization Approach." INFORMS Journal on Computing 35, no. 5 (September–October 2023): 952–965.
- July 2023
- Article
Design and Analysis of Switchback Experiments
By: Iavor I Bojinov, David Simchi-Levi and Jinglong Zhao
In switchback experiments, a firm sequentially exposes an experimental unit to a random treatment, measures its response, and repeats the procedure for several periods to determine which treatment leads to the best outcome. Although practitioners have widely adopted...
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Bojinov, Iavor I., David Simchi-Levi, and Jinglong Zhao. "Design and Analysis of Switchback Experiments." Management Science 69, no. 7 (July 2023): 3759–3777.
- April 6, 2023
- Article
A New NFT Launch Strategy: The Wave Mint
By: Scott Duke Kominers and 1337 Skulls Sers
In an NFT project, the mint—the process by which tokens are initially allocated—largely determines who your community is and how they and the broader market view the project going forward. In this piece, we review a new minting strategy recently introduced by 1337...
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Keywords:
NFTs;
Mechanism Design;
Sales Management;
Sales Model;
Crypto Economy;
Non-fungible Tokens;
Networks;
Product Launch;
Auctions;
Market Design
Kominers, Scott Duke, and 1337 Skulls Sers. "A New NFT Launch Strategy: The Wave Mint." a16zcrypto.com (April 6, 2023).
- 2023
- Working Paper
Distributionally Robust Causal Inference with Observational Data
By: Dimitris Bertsimas, Kosuke Imai and Michael Lingzhi Li
We consider the estimation of average treatment effects in observational studies and propose a new framework of robust causal inference with unobserved confounders. Our approach is based on distributionally robust optimization and proceeds in two steps. We first...
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Bertsimas, Dimitris, Kosuke Imai, and Michael Lingzhi Li. "Distributionally Robust Causal Inference with Observational Data." Working Paper, February 2023.