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- April 2024
- Article
Detecting Routines: Applications to Ridesharing CRM
By: Ryan Dew, Eva Ascarza, Oded Netzer and Nachum Sicherman
Routines shape many aspects of day-to-day consumption. While prior work has established the importance of habits in consumer behavior, little work has been done to understand the implications of routines—which we define as repeated behaviors with recurring, temporal...
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Keywords:
Ride-sharing;
Routine;
Machine Learning;
Customer Relationship Management;
Consumer Behavior;
Segmentation
Dew, Ryan, Eva Ascarza, Oded Netzer, and Nachum Sicherman. "Detecting Routines: Applications to Ridesharing CRM." Journal of Marketing Research (JMR) 61, no. 2 (April 2024): 368–392.
- March 2024
- Case
Angel City Football Club: Scoring a New Model
By: Jeffrey F. Rayport, Jennifer Fonstad and Nicole Tempest Keller
In January 2024, Kara Nortman, Julie Uhrman, and Natalie Portman, the founders of Angel City Football Club (ACFC) were developing the club’s first three-year strategic plan. Founded in 2020, ACFC had a star-studded investor group, including Portman and celebrities such...
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- January 2024
- Article
Dog Eat Dog: Balancing Network Effects and Differentiation in a Digital Platform Merger
By: Chiara Farronato, Jessica Fong and Andrey Fradkin
Digital platforms are increasingly the subject of regulatory scrutiny. In comparison to multiple competitors, a single platform may increase consumer welfare if network effects are large or may decrease welfare due to higher prices or reduction in platform variety. We...
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Keywords:
Platform Differentiation;
Digital Platforms;
Network Effects;
Measurement and Metrics;
Mergers and Acquisitions;
Outcome or Result
Farronato, Chiara, Jessica Fong, and Andrey Fradkin. "Dog Eat Dog: Balancing Network Effects and Differentiation in a Digital Platform Merger." Management Science 70, no. 1 (January 2024): 464–483.
- 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.
- October 2023 (Revised March 2024)
- Case
KOKO Networks: Bridging Energy Transition and Affordability with Carbon Financing
By: George Serafeim, Siko Sikochi and Namrata Arora
The problem was massive: two million hectares of African forests were lost annually to charcoal production for cooking, an area equivalent to 13 times Greater London, resulting in one billion tons of carbon emissions yearly. At the same time, an estimated 700,000...
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Keywords:
Africa;
Clean Tech;
Energy;
Sustainability;
Health;
Digital;
Carbon Credits;
Carbon Offsetting;
Market Design;
Regulation;
Climate Change;
Entrepreneurship;
Energy Industry;
Consumer Products Industry;
Africa
Serafeim, George, Siko Sikochi, and Namrata Arora. "KOKO Networks: Bridging Energy Transition and Affordability with Carbon Financing." Harvard Business School Case 124-022, October 2023. (Revised March 2024.)
- 2023
- Working Paper
Causal Interpretation of Structural IV Estimands
By: Isaiah Andrews, Nano Barahona, Matthew Gentzkow, Ashesh Rambachan and Jesse M. Shapiro
We study the causal interpretation of instrumental variables (IV) estimands of nonlinear, multivariate structural models with respect to rich forms of model misspecification. We focus on guaranteeing that the researcher's estimator is sharp zero consistent, meaning...
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Keywords:
Mathematical Methods
Andrews, Isaiah, Nano Barahona, Matthew Gentzkow, Ashesh Rambachan, and Jesse M. Shapiro. "Causal Interpretation of Structural IV Estimands." NBER Working Paper Series, No. 31799, October 2023.
- October, 2023
- Article
Cleaning Up the Great Lakes: Housing Market Impacts of Removing Legacy Pollutants
By: Alecia Cassidy, Robyn C. Meeks and Michale R. Moore
The Great Lakes and their tributaries make up the largest freshwater system on the planet, providing drinking water and recreational value to millions of people. Yet manufacturing plants left a legacy of toxic pollutants in the region, tarnishing it as part of the...
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Keywords:
Valuation Of Environmental Effects;
Housing Demand;
Water Pollution;
Water Quality;
Infrastructure;
Pollution;
Consumer Behavior
Cassidy, Alecia, Robyn C. Meeks, and Michale R. Moore. "Cleaning Up the Great Lakes: Housing Market Impacts of Removing Legacy Pollutants." Journal of Public Economics 226 (October, 2023).
- July–August 2023
- Article
Demand Learning and Pricing for Varying Assortments
By: Kris Ferreira and Emily Mower
Problem Definition: We consider the problem of demand learning and pricing for retailers who offer assortments of substitutable products that change frequently, e.g., due to limited inventory, perishable or time-sensitive products, or the retailer’s desire to...
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Keywords:
Experiments;
Pricing And Revenue Management;
Retailing;
Demand Estimation;
Pricing Algorithm;
Marketing;
Price;
Demand and Consumers;
Mathematical Methods
Ferreira, Kris, and Emily Mower. "Demand Learning and Pricing for Varying Assortments." Manufacturing & Service Operations Management 25, no. 4 (July–August 2023): 1227–1244. (Finalist, Practice-Based Research Competition, MSOM (2021) and Finalist, Revenue Management & Pricing Section Practice Award, INFORMS (2019).)
- 2024
- Working Paper
Residential Battery Storage - Reshaping the Way We Do Electricity
By: Christian Kaps and Serguei Netessine
In this paper, we aim to understand when private households invest in behind-the-meter battery storage next to rooftop solar and how those batteries impact households, the electricity market, and emissions. We answer three main research questions: 1) When do customers...
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Keywords:
Solar Power;
Energy Storage;
Technology And Innovation Management;
Energy;
Energy Policy;
Renewable Energy;
Technological Innovation;
Innovation and Management;
Energy Industry
Kaps, Christian, and Serguei Netessine. "Residential Battery Storage - Reshaping the Way We Do Electricity." Working Paper, February 2024.
- 2023
- Working Paper
Algorithm Failures and Consumers' Response: Evidence from Zillow
By: Isamar Troncoso, Runshan Fu, Nikhil Malik and Davide Proserpio
In November 2021, Zillow announced the closure of its iBuyer business. Popular media largely attributed this to a failure of its proprietary forecasting algorithm. We study the response of consumers to Zillow’s iBuyer business closure. We show that after the iBuyer...
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Keywords:
Algorithmic Pricing;
Price;
Forecasting and Prediction;
Consumer Behavior;
Real Estate Industry
Troncoso, Isamar, Runshan Fu, Nikhil Malik, and Davide Proserpio. "Algorithm Failures and Consumers' Response: Evidence from Zillow." Working Paper, July 2023.
- May–June 2023
- Article
Need for Speed: The Impact of In-Process Delays on Customer Behavior in Online Retail
By: Santiago Gallino, Nil Karacaoglu and Antonio Moreno
The impact of delays has been widely studied in various offline services. The focus of this study is online services, and we explore the impact of in-process delays—measured by website speed—on customer behavior. We leverage novel retail and website speed data to...
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Keywords:
Online Retail;
Quasi-experiments;
Abandonment;
Synthetic Control;
E-commerce;
Internet and the Web;
Consumer Behavior;
Policy;
Retail Industry
Gallino, Santiago, Nil Karacaoglu, and Antonio Moreno. "Need for Speed: The Impact of In-Process Delays on Customer Behavior in Online Retail." Operations Research 71, no. 3 (May–June 2023): 876–894.
- 2023
- Working Paper
Using GPT for Market Research
By: James Brand, Ayelet Israeli and Donald Ngwe
Large language models (LLMs) have quickly become popular as labor-augmenting tools
for programming, writing, and many other processes that benefit from quick text generation.
In this paper we explore the uses and benefits of LLMs for researchers and...
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Keywords:
Large Language Model;
Research;
AI and Machine Learning;
Analysis;
Customers;
Consumer Behavior;
Technology Industry;
Information Technology Industry
Brand, James, Ayelet Israeli, and Donald Ngwe. "Using GPT for Market Research." Harvard Business School Working Paper, No. 23-062, April 2023. (Revised July 2023.)
- March–April 2023
- Article
Pricing for Heterogeneous Products: Analytics for Ticket Reselling
By: Michael Alley, Max Biggs, Rim Hariss, Charles Herrmann, Michael Lingzhi Li and Georgia Perakis
Problem definition: We present a data-driven study of the secondary ticket market. In particular, we are primarily concerned with accurately estimating price sensitivity for listed tickets. In this setting, there are many issues including endogeneity, heterogeneity in...
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Keywords:
Price;
Demand and Consumers;
AI and Machine Learning;
Investment Return;
Entertainment and Recreation Industry;
Sports Industry
Alley, Michael, Max Biggs, Rim Hariss, Charles Herrmann, Michael Lingzhi Li, and Georgia Perakis. "Pricing for Heterogeneous Products: Analytics for Ticket Reselling." Manufacturing & Service Operations Management 25, no. 2 (March–April 2023): 409–426.
- 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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Keywords:
Consumer Behavior;
Policy;
Games, Gaming, and Gambling;
Product Design;
Video Game Industry
Amano, Tomomichi, and Andrey Simonov. "A Welfare Analysis of Gambling in Video Games." Harvard Business School Working Paper, No. 23-052, February 2023.
- Article
Recovering Investor Expectations from Demand for Index Funds
We use a revealed-preference approach to estimate investor expectations of stock market returns. Using data on demand for index funds that follow the S&P 500, we develop and estimate a model of investor choice to flexibly recover the time-varying distribution of...
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Keywords:
Stock Market Expectations;
Demand Estimation;
Exchange-traded Funds (ETFs);
Demand and Consumers;
Investment
Egan, Mark, Alexander J. MacKay, and Hanbin Yang. "Recovering Investor Expectations from Demand for Index Funds." Review of Economic Studies 89, no. 5 (October 2022): 2559–2599.
- August 2022
- Supplement
Zalora: Data-Driven Pricing Recommendations
By: Ayelet Israeli
This exercise can be used in conjunction with the main case "Zalora: Data-Driven Pricing" to facilitate class discussion without requiring data analysis from the students. Instead, the exercise presents reports that were created by the data science team to answer the...
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Keywords:
Pricing;
Pricing Algorithms;
Dynamic Pricing;
Ecommerce;
Pricing Strategy;
Pricing And Revenue Management;
Apparel;
Singapore;
Startup;
Demand Estimation;
Data Analysis;
Data Analytics;
Exercise;
Price;
Internet and the Web;
Apparel and Accessories Industry;
Retail Industry;
Fashion Industry;
Singapore
Israeli, Ayelet. "Zalora: Data-Driven Pricing Recommendations." Harvard Business School Supplement 523-032, August 2022.
- 2022
- Working Paper
The Effect of Employee Lateness and Absenteeism on Store Performance
By: Caleb Kwon and Ananth Raman
We empirically analyze the effects of employee lateness and absenteeism on store performance by examining 25.5 million employee shift timecards covering more than 100,000 employees across more than 500 U.S. retail grocery store locations over a four year time period....
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Kwon, Caleb, and Ananth Raman. "The Effect of Employee Lateness and Absenteeism on Store Performance." Working Paper, August 2022.
- 2023
- Working Paper
Dynamic Pricing, Intertemporal Spillovers, and Efficiency
By: Alexander J. MacKay, Dennis Svartbäck and Anders G. Ekholm
Pricing technology that allows firms to rapidly adjust prices has two potential benefits.
Time-varying prices can respond to high-frequency demand shocks to generate greater revenues,
and they can also be used to smooth out demand to reduce costs. Using data...
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MacKay, Alexander J., Dennis Svartbäck, and Anders G. Ekholm. "Dynamic Pricing, Intertemporal Spillovers, and Efficiency." Harvard Business School Working Paper, No. 23-007, July 2022. (Revised December 2023.)
- March 2022
- Article
Learning to Rank an Assortment of Products
By: Kris Ferreira, Sunanda Parthasarathy and Shreyas Sekar
We consider the product ranking challenge that online retailers face when their customers typically behave as “window shoppers”: they form an impression of the assortment after browsing products ranked in the initial positions and then decide whether to continue...
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Keywords:
Online Learning;
Product Ranking;
Assortment Optimization;
Learning;
Internet and the Web;
Product Marketing;
Consumer Behavior;
E-commerce
Ferreira, Kris, Sunanda Parthasarathy, and Shreyas Sekar. "Learning to Rank an Assortment of Products." Management Science 68, no. 3 (March 2022): 1828–1848.
- 2022
- Working Paper
How Do Copayment Coupons Affect Branded Drug Prices and Quantities Purchased?
By: Leemore S. Dafny, Kate Ho and Edward Kong
Drug copayment coupons to reduce patient cost-sharing have become nearly ubiquitous for high-priced brand-name prescription drugs. Medicare bans such coupons on the grounds that they are kickbacks that induce utilization, but they are commonly used by...
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Keywords:
Prescription Drugs;
Coupons;
Impact;
Health Care and Treatment;
Markets;
Price;
Spending;
Pharmaceutical Industry;
United States
Dafny, Leemore S., Kate Ho, and Edward Kong. "How Do Copayment Coupons Affect Branded Drug Prices and Quantities Purchased?" NBER Working Paper Series, No. 29735, February 2022.