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- November 2024
- Article
Price Discounts and Cheapflation During the Post-Pandemic Inflation Surge
By: Alberto Cavallo and Oleksiy Kryvtsov
We study how within-store price variation changes with inflation, and whether households exploit it to attenuate the inflation burden. We use micro price data for food products sold by 91 large multi-channel retailers in ten countries between 2018 and 2024. Measuring... View Details
Keywords: Macroeconomics; Inflation and Deflation; Price; Consumer Behavior; Personal Finance; Product Positioning
Cavallo, Alberto, and Oleksiy Kryvtsov. "Price Discounts and Cheapflation During the Post-Pandemic Inflation Surge." Journal of Monetary Economics 148 (November 2024).
- August 2024
- Article
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... View Details
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?" American Economic Journal: Economic Policy 16, no. 3 (August 2024): 314–346.
- 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
Keywords: Long-run Targeting; Heterogeneous Treatment Effect; Statistical Surrogacy; Customer Churn; Field Experiments; Consumer Behavior; Customer Focus and Relationships; AI and Machine Learning; Marketing Strategy
Huang, Ta-Wei, and Eva Ascarza. "Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals." Marketing Science 43, no. 4 (July–August 2024): 863–884.
- 2024
- Working Paper
Navigating Software Vulnerabilities: Eighteen Years of Evidence from Medium and Large U.S. Organizations
By: Raviv Murciano-Goroff, Ran Zhuo and Shane Greenstein
How prevalent are severe software vulnerabilities, how fast do software users respond to the availability of secure versions, and what determines the variance in the installation distribution? Using the largest dataset ever assembled on user updates, tracking server... View Details
Murciano-Goroff, Raviv, Ran Zhuo, and Shane Greenstein. "Navigating Software Vulnerabilities: Eighteen Years of Evidence from Medium and Large U.S. Organizations." NBER Working Paper Series, No. 32696, July 2024.
- 2024
- Working Paper
What Makes Players Pay? An Empirical Investigation of In-Game Lotteries
By: Tomomichi Amano and Andrey Simonov
In 2020, gamers spent more than $15 billion on loot boxes, lotteries of virtual items in video
games. Paid loot boxes are contentious. Game producers argue that loot boxes complement
the gameplay and expenditures on loot boxes reflect players’ enjoyment of the game.... View Details
Keywords: Product Design; Consumer Behavior; Ethics; Governing Rules, Regulations, and Reforms; Video Game Industry
Amano, Tomomichi, and Andrey Simonov. "What Makes Players Pay? An Empirical Investigation of In-Game Lotteries." Columbia Business School Research Paper, No. 4355019, June 2024.
- 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... View Details
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 (Revised April 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... View Details
Keywords: Sports; Entertainment; Entrepreneurship; Brands and Branding; Venture Capital; Business Model; Corporate Strategy; Digital Marketing; Sports Industry; Entertainment and Recreation Industry; United States; California; Los Angeles
Rayport, Jeffrey F., Jennifer Fonstad, and Nicole Tempest Keller. "Angel City Football Club: Scoring a New Model." Harvard Business School Case 824-192, March 2024. (Revised April 2024.)
- 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... View Details
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... View Details
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.
- 2023
- Working Paper
Flow-Driven ESG Returns
I show that the recent returns to ESG investing are strongly driven by price impact
from flows towards ESG funds. Using data on institutional trades, I estimate the
market’s ability to accommodate the demand of ESG funds, which is given by the
elasticity of... View Details
Keywords: Investment Funds; Corporate Social Responsibility and Impact; Financial Markets; Investment Return
van der Beck, Philippe. "Flow-Driven ESG Returns." Swiss Finance Institute Research Paper Series, No. 21-71, November 2023.
- 2023
- Working Paper
The Equity Market Implications of the Retail Investment Boom
By: Philippe van der Beck and Coralie Jaunin
This paper quantifies the impact of Robinhood traders on the US equity market. Within a structural model, we estimate retail and institutional demand curves and derive aggregate pricing implications via market clearing. The inelastic nature of institutional demand... View Details
van der Beck, Philippe, and Coralie Jaunin. "The Equity Market Implications of the Retail Investment Boom." Swiss Finance Institute Research Paper Series, No. 21-12, November 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... View Details
Keywords: Clean Tech; Digital; Carbon Credits; Carbon Offsetting; Climate Change; Entrepreneurship; Energy Sources; Environmental Sustainability; Health; Market Design; Business Startups; Transition; Environmental Regulation; Policy; Energy Industry; Consumer Products Industry; Africa; Kenya; Rwanda
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... View Details
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.
- 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... View Details
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... View Details
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... View Details
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... View Details
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.
- 2024
- Working Paper
Using LLMs for Market Research
By: James Brand, Ayelet Israeli and Donald Ngwe
Large language models (LLMs) have rapidly gained popularity 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
practitioners... View Details
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 LLMs for Market Research." Harvard Business School Working Paper, No. 23-062, April 2023. (Revised July 2024.)
- 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... View Details
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.
- Article
Recovering Investor Expectations from Demand for Index Funds
By: Mark Egan, Alexander J. MacKay and Hanbin Yang
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... View Details
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.