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- 2024
- Working Paper
Design of Panel Experiments with Spatial and Temporal Interference
By: Tu Ni, Iavor Bojinov and Jinglong Zhao
One of the main practical challenges companies face when running experiments (or A/B tests) over a panel is interference, the setting where one experimental unit's treatment assignment at one time period impacts another's outcomes, possibly at the following time...
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Keywords:
Research
Ni, Tu, Iavor Bojinov, and Jinglong Zhao. "Design of Panel Experiments with Spatial and Temporal Interference." Harvard Business School Working Paper, No. 24-058, March 2024.
- 2024
- Working Paper
Choosing and Using Information in Evaluation Decisions
By: Katherine Baldiga Coffman, Scott Kostyshak and Perihan O. Saygin
Most studies of gender discrimination consider how male versus female candidates are assessed given otherwise identical information about them. But, in many settings of interest, evaluators have a choice about how much information to acquire about a candidate before...
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- January 2024
- Article
Population Interference in Panel Experiments
By: Kevin Wu Han, Guillaume Basse and Iavor Bojinov
The phenomenon of population interference, where a treatment assigned to one experimental unit affects another experimental unit’s outcome, has received considerable attention in standard randomized experiments. The complications produced by population interference in...
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Han, Kevin Wu, Guillaume Basse, and Iavor Bojinov. "Population Interference in Panel Experiments." Journal of Econometrics 238, no. 1 (January 2024).
- 2023
- Working Paper
Debiasing Treatment Effect Estimation for Privacy-Protected Data: A Model Auditing and Calibration Approach
By: Ta-Wei Huang and Eva Ascarza
Data-driven targeted interventions have become a powerful tool for organizations to optimize business outcomes
by utilizing individual-level data from experiments. A key element of this process is the estimation
of Conditional Average Treatment Effects (CATE), which...
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Huang, Ta-Wei, and Eva Ascarza. "Debiasing Treatment Effect Estimation for Privacy-Protected Data: A Model Auditing and Calibration Approach." Harvard Business School Working Paper, No. 24-034, December 2023.
- November 2023
- Case
Aviva plc: Examining Net Zero
By: Peter Tufano, Brian Trelstad and Matteo Gasparini
The board of Aviva Plc, one of the world’s largest insurers, must review its climate risk exposures and evaluate next steps. Risk experts at the firm have conducted a robust set of analyses prepared for its regulator, the Bank of England, simulating how various climate...
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- November 2023
- Case
Khanmigo: Revolutionizing Learning with GenAI
By: William A. Sahlman, Allison M. Ciechanover and Emily Grandjean
Already a leader in the edtech space since its 2008 launch, Khan Academy was now one of the first edtech organizations to embrace generative artificial intelligence ("genAI"). In March 2023, Khan Academy began beta testing Khanmigo, a genAI “guide” and tutor built with...
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- 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 2023
- Supplement
Root Capital and the Efficient Impact Frontier Simulation Dataset for Students
By: Shawn Cole
- September 2023
- Teaching Note
Shad Process Flow Design Exercise: Kick-Off Class
By: Willy C. Shih
The Shad Process Flow Design Exercise is a simulation designed to help students cement what they learn in the process fundamentals section of the RCTOM course by giving them the opportunity to translate classroom concepts into actual physical processes and experience...
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- July 2023
- Article
Takahashi-Alexander Revisited: Modeling Private Equity Portfolio Outcomes Using Historical Simulations
By: Dawson Beutler, Alex Billias, Sam Holt, Josh Lerner and TzuHwan Seet
In 2001, Dean Takahashi and Seth Alexander of the Yale University Investments Office developed a deterministic model for estimating future cash flows and valuations for the Yale endowment’s private equity portfolio. Their model, which is simple and intuitive, is still...
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Beutler, Dawson, Alex Billias, Sam Holt, Josh Lerner, and TzuHwan Seet. "Takahashi-Alexander Revisited: Modeling Private Equity Portfolio Outcomes Using Historical Simulations." Journal of Portfolio Management 49, no. 7 (July 2023): 144–158.
- June 2023
- Supplement
Applied Intuition (A)
By: Andy Wu
Applied Intuition CEO Qasar Younis provides an overview of the automotive industry and the role of simulation software in the development of autonomous vehicles.
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Keywords:
Autonomous Vehicles;
Software;
Strategy;
Competitive Strategy;
Growth and Development Strategy;
Valuation;
Auto Industry;
Technology Industry;
California;
Detroit
Wu, Andy. "Applied Intuition (A)." Harvard Business School Multimedia/Video Supplement 723-869, June 2023. (Click here to access this supplement.)
- June 2023
- Supplement
Clash of Two Giants Simulation Exercise
By: Feng Zhu and Marco Iansiti
Many markets are organized around platforms that connect consumers with complementary applications and services. These platforms are two-sided because both sides - consumers and those providing applications or services - need access to the same platform to interact. A...
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- June 2023
- Exercise
Clash of Two Giants Simulation Exercise Instructions
By: Feng Zhu and Marco Iansiti
Many markets are organized around platforms that connect consumers with complimentary applications and services. These platforms are two-sided because both sides - consumers and those providing applications or services - need access to the same platform to interact. A...
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Keywords:
Platform Strategies;
Technology Platform;
Customer Acquisition;
Network Effects;
Digital Platforms;
Marketplace Matching;
Strategy
Zhu, Feng, and Marco Iansiti. "Clash of Two Giants Simulation Exercise Instructions." Harvard Business School Exercise 623-092, June 2023.
- June 2023 (Revised August 2023)
- Teaching Note
Clash of Two Giants Simulation Exercise Teaching Note
By: Feng Zhu
Teaching Note for HBS Case No. 623-092. Many markets are organized around platforms that connect consumers with complimentary applications and services. These platforms are two-sided because both sides - consumers and those providing applications or services - need...
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- June 2023
- Simulation
Clash of Two Giants: Competing in the Age of Platforms Simulation
By: Feng Zhu and Marco Iansiti
- 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...
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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
- June 2023 (Revised September 2023)
- Simulation
Managing the Customer Journey Marketing Simulation: Adobe's Data-Driven Operating Model (DDOM)
By: Sunil Gupta, Rajiv Lal and Celine Chammas
Adobe started monitoring Annual Recurring Revenue (ARR), one of its primary metrics, when it shifted from selling its software in a box to selling the software as a subscription-based cloud service. They wanted to know when, where, and how much to invest in marketing....
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- 2023
- Working Paper
Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness
By: Neil Menghani, Edward McFowland III and Daniel B. Neill
In this paper, we develop a new criterion, "insufficiently justified disparate impact" (IJDI), for assessing whether recommendations (binarized predictions) made by an algorithmic decision support tool are fair. Our novel, utility-based IJDI criterion evaluates false...
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Menghani, Neil, Edward McFowland III, and Daniel B. Neill. "Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness." Working Paper, June 2023.
- 2023
- Working Paper
Design-Based Confidence Sequences: A General Approach to Risk Mitigation in Online Experimentation
By: Dae Woong Ham, Michael Lindon, Martin Tingley and Iavor Bojinov
Randomized experiments have become the standard method for companies to evaluate the performance of new products or services. In addition to augmenting managers’ decision-making, experimentation mitigates risk by limiting the proportion of customers exposed to...
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Keywords:
Performance Evaluation;
Research and Development;
Analytics and Data Science;
Consumer Behavior
Ham, Dae Woong, Michael Lindon, Martin Tingley, and Iavor Bojinov. "Design-Based Confidence Sequences: A General Approach to Risk Mitigation in Online Experimentation." Harvard Business School Working Paper, No. 23-070, May 2023.