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Publications
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- February 2025
- Article
Variation in Batch Ordering of Imaging Tests in the Emergency Department and the Impact on Care Delivery
By: Jacob C. Jameson, Soroush Saghafian, Robert S. Huckman and Nicole Hodgson
Objectives: To examine heterogeneity in physician batch ordering practices and measure the impact of a physician's tendency to batch order imaging tests on patient outcomes and resource utilization.
Study Setting and Design: In this retrospective study, we used... View Details
Study Setting and Design: In this retrospective study, we used... View Details
- 2025
- Article
Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments
By: Kosuke Imai and Michael Lingzhi Li
Researchers are increasingly turning to machine learning (ML) algorithms to investigate causal heterogeneity in randomized experiments. Despite their promise, ML algorithms may fail to accurately ascertain heterogeneous treatment effects under practical settings with... View Details
- January–February 2025
- Article
Want Your Company to Get Better at Experimentation?: Learn Fast by Democratizing Testing
By: Iavor Bojinov, David Holtz, Ramesh Johari, Sven Schmit and Martin Tingley
For years, online experimentation has fueled the innovations of leading tech companies, enabling them to rapidly test and refine new ideas, optimize product features, personalize user experiences, and maintain a competitive edge. The widespread availability and lower... View Details
- October 2024
- Article
Sampling Bias in Entrepreneurial Experiments
By: Ruiqing Cao, Rembrand Koning and Ramana Nanda
Using data from a prominent online platform for launching new digital products, we document that ‘sampling bias’—defined as the difference between a startup’s target customer base and the actual sample on which early ‘beta tests’ are conducted—has a systematic and... View Details
- July 2024 (Revised January 2025)
- Case
Dynamic Pricing at Wendy’s: Where’s the Beef?
By: Elie Ofek, Alicia Dadlani and Martha Hostetter
In early 2024, Wendy’s new CEO announced on an earnings call that the company would install digital menus in its US locations so it could begin testing dynamic pricing—changing prices up or down in response to shifts in supply and demand – as well as allow engaging in... View Details
- July 2024
- Article
JUE Insight: Infrastructure and Finance: Evidence from India's GQ Highway Network
By: Abhiman Das, Ejaz Ghani, Arti Grover, William Kerr and Ramana Nanda
We use data from Reserve Bank of India to study the impact of India's Golden Quadrilateral (GQ) highway project on finance-dependent activity. Loan volumes increase by 20-30% in districts along GQ and are stronger in industries more dependent upon external finance.... View Details
- July 2024
- Article
The Home State Effect: How Subnational Governments Shape Climate Coalitions
By: Jonas Meckling and Samuel Trachtman
Organized business interests often seek to block public interest regulations. But whether firms oppose regulation depends on institutional context. We argue that, in federal systems, sub-national policies and politics can have a home state effect on firms' national... View Details
- June 2024 (Revised August 2024)
- Case
Revlon India's Turnaround: Navigating Online-Offline Decisions Using a Balanced Scorecard
By: Tatiana Sandino and Samuel Grad
Revlon India was founded as a joint venture in 1995, pairing the industrial conglomerate UMG with the global beauty brand Revlon, Inc. to bring international color cosmetics to India. After growing rapidly and pioneering the Beauty Advisor (BA) model in India, the... View Details
Keywords: Balanced Scorecard; Restructuring; Training; Supply Chain Management; Distribution; E-commerce; Business Model; Business Plan; Decision Choices and Conditions; Marketing Strategy; Alignment; Brands and Branding; Negotiation; Joint Ventures; Strategic Planning; Salesforce Management; Competition; Retail Industry; Consumer Products Industry; Beauty and Cosmetics Industry; India
- 2024
- Working Paper
Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization
This paper introduces Incrementality Representation Learning (IRL), a novel multitask representation learning framework that predicts heterogeneous causal effects of marketing interventions. By leveraging past experiments, IRL efficiently designs and targets... View Details
- April 2024
- Article
A Machine Learning Algorithm Predicting Risk of Dilating VUR among Infants with Hydronephrosis Using UTD Classification
By: Hsin-Hsiao Scott Wang, Michael Lingzhi Li, Dylan Cahill, John Panagides, Tanya Logvinenko, Jeanne Chow and Caleb Nelson
Backgrounds: Urinary Tract Dilation (UTD) classification has been designed to be a more objective grading system to evaluate antenatal and post-natal UTD. Due to unclear association between UTD classifications to specific anomalies such as vesico-ureteral reflux (VUR),... View Details
- April 2024
- Article
Speaking up and Taking Action: Psychological Safety and Joint Problem-solving Orientation in Safety Improvement
By: Hassina Bahadurzada, Michaela J. Kerrissey and Amy C. Edmondson
Healthcare organizations face stubborn challenges in ensuring patient safety and mitigating clinician turnover. This paper aims to advance theory and research on patient safety by elucidating how the role of psychological safety in patient safety can be enhanced with... View Details
- 2024
- Working Paper
The Cram Method for Efficient Simultaneous Learning and Evaluation
By: Zeyang Jia, Kosuke Imai and Michael Lingzhi Li
We introduce the "cram" method, a general and efficient approach to simultaneous learning and evaluation using a generic machine learning (ML) algorithm. In a single pass of batched data, the proposed method repeatedly trains an ML algorithm and tests its empirical... View Details
Keywords: AI and Machine Learning
- 2024
- Working Paper
Anytime-Valid Inference in Linear Models and Regression-Adjusted Causal Inference
By: Michael Lindon, Dae Woong Ham, Martin Tingley and Iavor I. Bojinov
Linear regression adjustment is commonly used to analyze randomized controlled experiments due to its efficiency and robustness against model misspecification. Current testing and interval estimation procedures leverage the asymptotic distribution of such estimators to... View Details
- 2023
- Working Paper
Design-Based Inference for Multi-arm Bandits
By: Dae Woong Ham, Iavor I. Bojinov, Michael Lindon and Martin Tingley
Multi-arm bandits are gaining popularity as they enable real-world sequential decision-making across application areas, including clinical trials, recommender systems, and online decision-making. Consequently, there is an increased desire to use the available... View Details
- February 2024
- Module Note
Data-Driven Marketing in Retail Markets
By: Ayelet Israeli
This note describes an eight-class sessions module on data-driven marketing in retail markets. The module aims to familiarize students with core concepts of data-driven marketing in retail, including exploring the opportunities and challenges, adopting best practices,... View Details
Keywords: Data; Data Analytics; Retail; Retail Analytics; Data Science; Business Analytics; ＂Marketing Analytics＂; Omnichannel; Omnichannel Retailing; Omnichannel Retail; DTC; Direct To Consumer Marketing; Ethical Decision Making; Algorithmic Bias; Privacy; A/B Testing; Descriptive Analytics; Prescriptive Analytics; Predictive Analytics; Analytics and Data Science; E-commerce; Marketing Channels; Demand and Consumers; Marketing Strategy; Retail Industry
- October 2023 (Revised February 2024)
- Technical Note
Design and Evaluation of Targeted Interventions
By: Eva Ascarza and Ta-Wei (David) Huang
Targeted interventions serve as a pivotal tool in business strategy, streamlining decisions for enhanced efficiency and effectiveness. This note delves into two central facets of such interventions: first, the design of potent decision guidelines, or targeting... View Details
- September 2023
- Supplement
Design and Evaluation of Targeted Interventions
By: Eva Ascarza
Targeted interventions serve as a pivotal tool in business strategy, streamlining decisions for enhanced efficiency and effectiveness. This note delves into two central facets of such interventions: first, the design of potent decision guidelines, or targeting... View Details
- September–October 2023
- Article
Prospective Evaluation of the Cost of Performing Breast Imaging Examinations Using Time-Driven Activity-Based Costing Method: A Single Center Study
By: Aamir Ali, Jordana Phillips, Damir Ljuboja, Syed S. Shehab, Etta D. Pisano, Robert S. Kaplan and Ammar Sarwar
We use time-driven activity-based costing (TDABC) to measure the cost of performing breast imaging using different modalities: full-field digital mammography (FFDM), digital breast tomosynthesis (DBT), contrast-enhanced mammography (CEM), US and MRI exams, and... View Details
- September 2023
- Article
The Dynamics of Team Learning: Harmony and Rhythm in Teamwork Arrangements for Innovation
By: Jean-François Harvey, Johnathan R. Cromwell, Kevin J. Johnson and Amy C. Edmondson
Innovation teams must navigate inherent tensions between different learning activities to produce high levels of performance. Yet, we know little about how teams combine these activities—notably reflexive, experimental, vicarious, and contextual learning—most... View Details
- August 2023
- Article
Status and Mortality: Is There a Whitehall Effect in the United States?
By: Tom Nicholas
The influential Whitehall studies found that top-ranking civil servants in Britain experienced lower mortality than civil servants below them in the organizational hierarchy due to differential exposure to workplace stress. I test for a Whitehall effect in the United... View Details