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- 2023
- Working Paper
A Welfare Analysis of Gambling in Video Games
By: Tomomichi Amano and Andrey Simonov
In 2020, gamers worldwide spent more than $15 billion on loot boxes, a lottery of virtual items built into video games. Loot boxes are contentious, as regulators worry that they constitute gambling. In contrast, video game companies maintain that loot boxes are...
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- January 23, 2023
- Article
Digital Public Health Interventions at Scale: The Impact of Social Media Advertising on Beliefs and Outcomes Related to COVID Vaccines
By: Susan Athey, Kristen Grabarz, Michael Luca and Nils Wernerfelt
Public health organizations increasingly use social media advertising campaigns in pursuit of public health goals. In this paper, we evaluate the impact of about $40 million of social media advertisements that were run and experimentally tested on Facebook and...
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- 2023
- Article
Experimental Evaluation of Individualized Treatment Rules
By: Kosuke Imai and Michael Lingzhi Li
The increasing availability of individual-level data has led to numerous applications of individualized (or personalized) treatment rules (ITRs). Policy makers often wish to empirically evaluate ITRs and compare their relative performance before implementing them in a...
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- 2022
- Book
Private Equity
By: Paul A. Gompers and Steven N. Kaplan
This Advanced Introduction provides an illustrative guide to private equity, integrating insights from academic research with examples to derive practical recommendations. Paul Gompers and Steven Kaplan begin by reviewing the history of private equity then exploring...
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- October 31, 2022
- Article
Achieving Individual—and Organizational—Value with AI
By: Sam Ransbotham, David Kiron, François Candelon, Shervin Khodabandeh and Michael Chu
New research shows that employees derive individual value from AI when using the technology improves their sense of competency, autonomy, and relatedness. Likewise, organizations are far more likely to obtain value from AI when their workers do. This report offers key...
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- 2022
- Article
The Ordinary Concept of a Meaningful Life: The Role of Subjective and Objective Factors in Third-Person Attributions of Meaning
By: Michael Prinzing, Julian De Freitas and Barbara L. Fredrickson
The desire for a meaningful life is ubiquitous, yet the ordinary concept of a meaningful life is poorly understood. Across six experiments (total N = 2,539), we investigated whether third-person attributions of meaning depend on the psychological states an agent...
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- 2022
- Article
Data Poisoning Attacks on Off-Policy Evaluation Methods
By: Elita Lobo, Harvineet Singh, Marek Petrik, Cynthia Rudin and Himabindu Lakkaraju
Off-policy Evaluation (OPE) methods are a crucial tool for evaluating policies in high-stakes domains such as healthcare, where exploration is often infeasible, unethical, or expensive. However, the extent to which such methods can be trusted under adversarial threats...
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- 2022
- Working Paper
Product2Vec: Leveraging Representation Learning to Model Consumer Product Choice in Large Assortments
By: Fanglin Chen, Xiao Liu, Davide Proserpio and Isamar Troncoso
We propose a method, Product2Vec, based on representation learning, that can automatically learn latent product attributes that drive consumer choices, to study product-level competition when the number of products is large. We demonstrate Product2Vec’s...
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- 2022
- Conference Presentation
Towards the Unification and Robustness of Post hoc Explanation Methods
By: Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu and Himabindu Lakkaraju
As machine learning black boxes are increasingly being deployed in critical domains such as healthcare and criminal justice, there has been a growing emphasis on developing techniques for explaining these black boxes in a post hoc manner. In this work, we analyze two...
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Keywords:
AI and Machine Learning
- 2022
- Article
Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis.
By: Martin Pawelczyk, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay and Himabindu Lakkaraju
As machine learning (ML) models become more widely deployed in high-stakes applications, counterfactual explanations have emerged as key tools for providing actionable model explanations in practice. Despite the growing popularity of counterfactual explanations, a...
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- January 2022 (Revised August 2022)
- Case
Geely SEA: New Electric Vehicle Platforms
By: Willy C. Shih and Shu Lin
Kent Bovellan, the Chief Engineer and Head of the Vehicle Architecture Center for Geely Holding, the Hangzhou, China headquartered global automotive group, was debating the platform choice for an upcoming "D" segment midsized battery electric vehicle (BEV). He had led...
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Keywords:
Product Innovation;
Product Architecture;
Product Engineering;
Platform Design;
Platform Strategy;
Information Infrastructure;
Digital Platforms;
Information Technology;
Product Design;
Product Development;
Cost Management;
Decision Making;
Competitive Strategy;
Industry Structures;
Auto Industry;
China;
Sweden
- January 2022
- Article
Artificial Intelligence, Data-Driven Learning, and the Decentralized Structure of Platform Ecosystems
By: David R. Clough and Andy Wu
Gregory, Henfridsson, Kaganer, and Kyriakou (2020) highlight the important role of data and AI as strategic resources that platforms may use to enhance user value. However, their article overlooks a significant conceptual distinction: the installed base of...
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- 2021
- Working Paper
Capitalism, Slavery, and the Legacy of Cesare Beccaria
The Milanese Marquis Cesare Beccaria (1738-1794) dedicated his life first to theorizing a more just and equal society grounded in individual rights, anchored in secular political economy rather than in religious dogma, then to realizing this bold vision...
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- 2021
- Working Paper
The Incidence of the Corporate Income Tax Is Irrelevant for Its (Benefit-Based) Justification
Robust support for corporate income taxation is a puzzle for standard tax theory because the tax’s incidence is uncertain and unreliable. We propose a resolution: if the corporate tax is seen as a benefit-based tax, its normative appeal depends on the correspondence...
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- 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...
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- November 2021
- Article
Panel Experiments and Dynamic Causal Effects: A Finite Population Perspective
By: Iavor Bojinov, Ashesh Rambachan and Neil Shephard
In panel experiments, we randomly assign units to different interventions, measuring their outcomes, and repeating the procedure in several periods. Using the potential outcomes framework, we define finite population dynamic causal effects that capture the relative...
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- 2021
- Working Paper
The Value of Data and Its Impact on Competition
By: Marco Iansiti
Common regulatory perspective on the relationship between data, value, and competition in online platforms has increasingly centered on the volume of data accumulated by incumbent firms. This view posits the existence of "data network effects," where more data leads to...
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- 2022
- Working Paper
Communication within Firms: Evidence from CEO Turnovers
By: Stephen Michael Impink, Andrea Prat and Raffaella Sadun
This paper uses novel, firm-level communication measures derived from communications
metadata several months before and after a CEO transition for 102 firms to study whether and
how this organizational event is reflected in employees’ communication flows. We find...
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- July 2021
- Article
Information Transparency, Multihoming, and Platform Competition: A Natural Experiment in the Daily Deals Market
By: Hui Li and Feng Zhu
Platform competition is shaped by the likelihood of multi-homing (i.e., complementors or consumers adopt more than one platform). To take advantage of multi-homing, platform firms often attempt to motivate their rivals’ high-performing complementors to adopt their own...
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- Article
Towards the Unification and Robustness of Perturbation and Gradient Based Explanations
By: Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu and Himabindu Lakkaraju
As machine learning black boxes are increasingly being deployed in critical domains such as healthcare and criminal justice, there has been a growing emphasis on developing techniques for explaining these black boxes in a post hoc manner. In this work, we analyze two...
View Details