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- 2025
- Article
Emotion Regulation Contagion Drives Reduction in Negative Intergroup Emotions
By: Michael Pinus, Yajun Cao, Eran Halperin, Alin Coman, James J. Gross and Amit Goldenberg
When emotions occur in groups, they sometimes impact group behavior in undesired ways. Reducing group’s emotions with emotion regulation interventions can be helpful, but may also be a challenge, because treating every person in the group is often infeasible. One... View Details
- 2025
- Working Paper
Dynamic Personalization with Multiple Customer Signals: Multi-Response State Representation in Reinforcement Learning
Reinforcement learning (RL) offers potential for optimizing sequences of customer interactions by modeling the relationships
between customer states, company actions, and long-term value. However, its practical implementation often faces significant
challenges.... View Details
- 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... View Details
- 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
- February 9, 2024
- Article
Addressing Climate Change with Behavioral Science: A Global Intervention Tournament in 63 Countries
By: Madalina Vlasceanu, Kimberly C. Doell, Joseph B. Bak-Coleman, Boryana Todorova, Michael M. Berkebile-Weinberg, Amit Goldenberg, Eric Shuman and et al.
Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate... View Details
- 2025
- Working Paper
Enhancing Treatment Effect Prediction on Privacy-Protected Data: An Honest Post-Processing Approach
By: Ta-Wei Huang and Eva Ascarza
As firms increasingly rely on customer data for personalization, concerns over privacy and regulatory compliance have grown. Local Differential Privacy (LDP) offers strong individual-level protection by injecting noise into data before collection. While... View Details
- 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
The New Era of Industrial Policy Is Here
By: Willy C. Shih
Governments around the world are increasingly intervening in the private sector through industrial policies designed to help domestic sectors reach goals that markets alone are unlikely to achieve. Companies in targeted sectors—such as automakers, energy companies, and... View Details
- June 2023
- Simulation
Artea Dashboard and Targeting Policy Evaluation
By: Ayelet Israeli and Eva Ascarza
Companies deploy A/B experiments to gain valuable insights about their customers in order to answer strategic business problems. In marketing, A/B tests are often used to evaluate marketing interventions intended to generate incremental outcomes for the firm. The Artea... View Details
Keywords: Algorithm Bias; Algorithmic Data; Race And Ethnicity; Experimentation; Promotion; Marketing And Society; Big Data; Privacy; Data-driven Management; Data Analysis; Data Analytics; E-Commerce Strategy; Discrimination; Targeted Advertising; Targeted Policies; Pricing Algorithms; A/B Testing; Ethical Decision Making; Customer Base Analysis; Customer Heterogeneity; Coupons; Marketing; Race; Gender; Diversity; Customer Relationship Management; Marketing Communications; Advertising; Decision Making; Ethics; E-commerce; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; United States
- July 2023
- Article
Political Strategies for Climate and Environmental Solutions
By: Jonas Meckling and Valerie Karplus
Many of the barriers to progress in addressing environmental problems, such as climate change, are political. We argue that politics should not be seen only as a constraint but be recognized as a target of intervention to advance environmental solutions. We use the... View Details
- 2023
- Case
Christiana Figueres and the Collaborative Approach to Negotiating Climate Action
By: James K. Sebenius, Laurence A. Green, Hannah Riley-Bowles, Lara SanPietro and Mina Subramanian
This case study centers on Harvard’s Program on Negotiation 2022 Great Negotiator, Christiana Figueres, and her efforts as Executive Secretary of the United Nations Framework Convention on Climate Change (UNFCCC) to build momentum for, and ultimately pass, the 2015... View Details
- September 2022
- Article
Loneliness Versus Distress: A Comparison of Emotion Regulation Profiles
By: Alyssa J. Tan, Vincent Mancini, James J. Gross, Amit Goldenberg, Johanna C. Badcock, Michelle H. Lim, Rodrigo Becerra, Ben Jackson and David A. Preece
Loneliness, a negative emotion stemming from the perception of unmet social needs, is a major public health concern. Current interventions often target social domains but produce small effects and are not as effective as established emotion regulation (ER)-based... View Details
Keywords: Emotions
- 2022
- Chapter
Lessons Learned from Support to Business during COVID-19
By: Gabriel Chodorow-Reich, Benjamin Iverson and Adi Sunderam
The authors survey the new federal subsidies and loans provided to businesses in the first year of the pandemic—including the Paycheck Protection Program (PPP), the Economic Injury Disaster Loan (EIDL) program, and aid targeted at specific industries such as airlines... View Details
- Article
Megastudies Improve the Impact of Applied Behavioural Science
By: Katherine L. Milkman, Dena Gromet, Hung Ho, Joseph S. Kay, Timothy W. Lee, Pepi Pandiloski, Yeji Park, Aneesh Rai, Max Bazerman, John Beshears, Lauri Bonacorsi, Colin Camerer, Edward Chang, Gretchen Chapman, Robert Cialdini, Hengchen Dai, Lauren Eskreis-Winkler, Ayelet Fishbach, James J. Gross, Samantha Horn, Alexa Hubbard, Steven J. Jones, Dean Karlan, Tim Kautz, Erika Kirgios, Joowon Klusowski, Ariella Kristal, Rahul Ladhania, Jens Ludwig, George Loewenstein, Barbara Mellers, Sendhil Mullainathan, Silvia Saccardo, Jann Spiess, Gaurav Suri, Joachim H. Talloen, Jamie Taxer, Yaacov Trope, Lyle Ungar, Kevin G. Volpp, Ashley V. Whillans, Jonathan Zinman and Angela L. Duckworth
Policy-makers are increasingly turning to behavioural science for insights about how to improve citizens’ decisions and outcomes. Typically, different scientists test different intervention ideas in different samples using different outcomes over different time... View Details
- 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
- June 23, 2021
- Article
Research: When A/B Testing Doesn't Tell You the Whole Story
By: Eva Ascarza
When it comes to churn prevention, marketers traditionally start by identifying which customers are most likely to churn, and then running A/B tests to determine whether a proposed retention intervention will be effective at retaining those high-risk customers. While... View Details
Keywords: Customer Retention; Churn; Targeting; Market Research; Marketing; Investment Return; Customers; Retention; Research
- 2020
- Working Paper
Fresh Fruit and Vegetable Consumption: The Impact of Access and Value
By: Retsef Levi, Elisabeth Paulson and Georgia Perakis
The goal of this paper is to leverage household-level data to improve food-related policies aimed at increasing the consumption of fruits and vegetables (FVs) among low-income households. Currently, several interventions target areas where residents have limited... View Details
Keywords: Food Deserts; Food Access; Food Policy; Causal Inference; Food; Nutrition; Poverty; Government Administration
- 2020
- Working Paper
Targeting for Long-Term Outcomes
By: Jeremy Yang, Dean Eckles, Paramveer Dhillon and Sinan Aral
Decision makers often want to target interventions so as to maximize an outcome that is observed only in the long term. This typically requires delaying decisions until the outcome is observed or relying on simple short-term proxies for the long-term outcome. Here we... View Details
- September–October 2020
- Article
Managing Churn to Maximize Profits
By: Aurelie Lemmens and Sunil Gupta
Customer defection threatens many industries, prompting companies to deploy targeted, proactive customer retention programs and offers. A conventional approach has been to target customers either based on their predicted churn probability or their responsiveness to a... View Details