Filter Results:
(1,819)
Show Results For
- All HBS Web
(7,002)
- Faculty Publications (1,819)
Show Results For
- All HBS Web
(7,002)
- Faculty Publications (1,819)
- May 2023
- Article
Self-Preferencing at Amazon: Evidence from Search Rankings
By: Chiara Farronato, Andrey Fradkin and Alexander MacKay
We study whether Amazon engages in self-preferencing on its marketplace by favoring its own brands (e.g., Amazon Basics) in search. To address this question, we collect new micro-level consumer search data using a custom browser extension installed by a panel of study... View Details
Farronato, Chiara, Andrey Fradkin, and Alexander MacKay. "Self-Preferencing at Amazon: Evidence from Search Rankings." AEA Papers and Proceedings 113 (May 2023): 239–243.
- 2025
- Working Paper
Turning Points in Inflation: A Structural Breaks Approach with Micro Data
By: Alberto Cavallo and Gastón García Zavaleta
We introduce a novel methodology for detecting inflation turning points that combines high-frequency, disaggregated price data with standard structural break techniques to provide policymakers with more precise and timely signals of inflation dynamics. The methodology... View Details
Cavallo, Alberto, and Gastón García Zavaleta. "Turning Points in Inflation: A Structural Breaks Approach with Micro Data." Working Paper, May 2025. (Preliminary draft.)
- April 12, 2023
- Article
Using AI to Adjust Your Marketing and Sales in a Volatile World
By: Das Narayandas and Arijit Sengupta
Why are some firms better and faster than others at adapting their use of customer data to respond to changing or uncertain marketing conditions? A common thread across faster-acting firms is the use of AI models to predict outcomes at various stages of the customer... View Details
Keywords: Forecasting and Prediction; AI and Machine Learning; Consumer Behavior; Technology Adoption; Competitive Advantage
Narayandas, Das, and Arijit Sengupta. "Using AI to Adjust Your Marketing and Sales in a Volatile World." Harvard Business Review Digital Articles (April 12, 2023).
- 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.)
- April 6, 2023
- Article
A New NFT Launch Strategy: The Wave Mint
By: Scott Duke Kominers and 1337 Skulls Sers
In an NFT project, the mint—the process by which tokens are initially allocated—largely determines who your community is and how they and the broader market view the project going forward. In this piece, we review a new minting strategy recently introduced by 1337... View Details
Keywords: NFTs; Mechanism Design; Sales Management; Sales Model; Crypto Economy; Non-fungible Tokens; Networks; Product Launch; Auctions; Market Design
Kominers, Scott Duke, and 1337 Skulls Sers. "A New NFT Launch Strategy: The Wave Mint." a16zcrypto.com (April 6, 2023).
- 2023
- Working Paper
Corporate Website-based Measures of Firms' Value Drivers
By: Wei Cai, Dennis Campbell and Patrick Ferguson
We develop and validate new text-based measures of firms’ financial and non-financial value drivers. Using the Wayback Machine to access public US firms’ archived websites from 1995-2020, we scrape text from corporate homepages. We use Kaplan and Norton’s (1992)... View Details
Cai, Wei, Dennis Campbell, and Patrick Ferguson. "Corporate Website-based Measures of Firms' Value Drivers." SSRN Working Paper Series, No. 4413808, April 2023.
- 2023
- Article
Estimating Causal Peer Influence in Homophilous Social Networks by Inferring Latent Locations.
By: Edward McFowland III and Cosma Rohilla Shalizi
Social influence cannot be identified from purely observational data on social networks, because such influence is generically confounded with latent homophily, that is, with a node’s network partners being informative about the node’s attributes and therefore its... View Details
Keywords: Causal Inference; Homophily; Social Networks; Peer Influence; Social and Collaborative Networks; Power and Influence; Mathematical Methods
McFowland III, Edward, and Cosma Rohilla Shalizi. "Estimating Causal Peer Influence in Homophilous Social Networks by Inferring Latent Locations." Journal of the American Statistical Association 118, no. 541 (2023): 707–718.
- 2023
- Working Paper
Feature Importance Disparities for Data Bias Investigations
By: Peter W. Chang, Leor Fishman and Seth Neel
It is widely held that one cause of downstream bias in classifiers is bias present in the training data. Rectifying such biases may involve context-dependent interventions such as training separate models on subgroups, removing features with bias in the collection... View Details
Chang, Peter W., Leor Fishman, and Seth Neel. "Feature Importance Disparities for Data Bias Investigations." Working Paper, March 2023.
- Spring 2023
- Article
Incentive Contract Design and Employee-Initiated Innovation: Evidence from the Field
By: Wei Cai, Susanna Gallani and Jee-Eun Shin
This study examines how the design of incentive contracts for tasks defined as workers’ official responsibilities (i.e., standard tasks) influences workers’ propensity to engage in employee-initiated innovation (EII). EII corresponds to innovation activities that are... View Details
Keywords: Employee-initiated Innovation; Contract Design; Rank-and-file; Extra-role Behaviors; Compensation and Benefits; Motivation and Incentives; Innovation and Management
Cai, Wei, Susanna Gallani, and Jee-Eun Shin. "Incentive Contract Design and Employee-Initiated Innovation: Evidence from the Field." Contemporary Accounting Research 40, no. 1 (Spring 2023): 292–323.
- April 2023
- Article
On the Privacy Risks of Algorithmic Recourse
By: Martin Pawelczyk, Himabindu Lakkaraju and Seth Neel
As predictive models are increasingly being employed to make consequential decisions, there is a growing emphasis on developing techniques that can provide algorithmic recourse to affected individuals. While such recourses can be immensely beneficial to affected... View Details
Pawelczyk, Martin, Himabindu Lakkaraju, and Seth Neel. "On the Privacy Risks of Algorithmic Recourse." Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) 206 (April 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... View Details
Keywords: Price; Demand and Consumers; AI and Machine Learning; Investment Return; Entertainment and Recreation Industry; Entertainment and Recreation 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
PRIMO: Private Regression in Multiple Outcomes
By: Seth Neel
We introduce a new differentially private regression setting we call Private Regression in Multiple Outcomes (PRIMO), inspired the common situation where a data analyst wants to perform a set of l regressions while preserving privacy, where the covariates... View Details
Neel, Seth. "PRIMO: Private Regression in Multiple Outcomes." Working Paper, March 2023.
- April 2023
- Article
The Real Exchange Rate, Innovation and Productivity
By: Laura Alfaro, Alejandro Cuñat, Harald Fadinger and Yanping Liu
We evaluate manufacturing firms' responses to changes in the real exchange rate (RER) using detailed firm-level data for a large set of countries for the period 2001-2010. We uncover the following stylized facts about regional variation of manufacturing firms'... View Details
Keywords: Real Exchange Rate; Firm Level Data; Innovation; Productivity; Exporting; Importing; Credit Constraints; Currency Exchange Rate; Innovation and Invention; Performance Productivity
Alfaro, Laura, Alejandro Cuñat, Harald Fadinger, and Yanping Liu. "The Real Exchange Rate, Innovation and Productivity." Journal of the European Economic Association 21, no. 2 (April 2023): 637–689.
- 2023
- Working Paper
Organizational Responses to Product Cycles
By: Achyuta Adhvaryu, Vittorio Bassi, Anant Nyshadham, Jorge Tamayo and Nicolas Torres
We use daily administrative data from a leading automobile manufacturer to study the organizational impacts of introducing new models to the auto assembly line. We first show that costly defects per vehicle spike when new models are introduced. As a response, the firm... View Details
Keywords: Product Quality Upgrading; Product Cycles; Organizational Behavior; Knowledge Hierarchies; Worker Skills; Auto Manufacturing; Training; Organizational Change and Adaptation; Knowledge Management; Production; Product; Organizational Structure; Auto Industry; Argentina
Adhvaryu, Achyuta, Vittorio Bassi, Anant Nyshadham, Jorge Tamayo, and Nicolas Torres. "Organizational Responses to Product Cycles." Harvard Business School Working Paper, No. 23-061, March 2023. (Revised August 2023. Revise & Resubmit Journal of Political Economy.)
- March 31, 2023
- Article
What Is the Optimal Pattern of a Customer Journey?
Even though customer experience (CX) leaders are becoming increasingly focused on optimizing their firms’ customer journeys, they face a clear challenge: Which touchpoints along the journey should they invest in? That is, which moments when the customer interacts with... View Details
De Freitas, Julian. "What Is the Optimal Pattern of a Customer Journey?" Harvard Business Review (website) (March 31, 2023).
- March 2023
- Teaching Note
VideaHealth: Building the AI Factory
By: Karim R. Lakhani
Teaching Note for HBS Case No. 621-021. The case “VideaHealth: Building the AI Factory” examines the creation of dental startup VideaHealth (Videa) and the development of its artificial intelligence (AI)-led business strategy through the eyes of founder and CEO Florian... View Details
- March 2023
- Supplement
Allianz Türkiye (B): Adapting to a Changing World
By: John D. Macomber and Fares Khrais
Keywords: Insurance And Reinsurance; Natural Disasters; Turkey; Insurance; Climate Change; Analytics and Data Science; Insurance Industry; Financial Services Industry; Turkey
Macomber, John D., and Fares Khrais. "Allianz Türkiye (B): Adapting to a Changing World." Harvard Business School Supplement 223-076, March 2023.
- March 2023
- Supplement
Allianz Türkiye (C): Managing the 2017 Hail Storm
By: John D. Macomber and Fares Khrais
Allianz Turkey is a property casualty insurance company operating in a region experiencing increasing losses from natural catastrophe events related to climate change, for example hail, wildfire, and flooding. There are also substantial other natural catastrophe... View Details
Keywords: Insurance And Reinsurance; Natural Disasters; Turkey; Insurance; Climate Change; Analytics and Data Science; Insurance Industry; Financial Services Industry; Turkey
Macomber, John D., and Fares Khrais. "Allianz Türkiye (C): Managing the 2017 Hail Storm." Harvard Business School Supplement 223-084, March 2023.
- March 2023 (Revised April 2024)
- Case
Allianz Türkiye: Adapting to Climate Change
By: John D. Macomber and Fares Khrais
Allianz Turkey is a property casualty insurance company operating in a region experiencing increasing losses from natural catastrophe events related to climate change, for example hail, wildfire, and flooding. There are also substantial other natural catastrophe... View Details
Keywords: Insurance And Reinsurance; Natural Disasters; Turkey; Insurance; Climate Change; Analytics and Data Science; Insurance Industry; Financial Services Industry; Turkey
Macomber, John D., and Fares Khrais. "Allianz Türkiye: Adapting to Climate Change." Harvard Business School Case 223-074, March 2023. (Revised April 2024.)
- March 2023
- Module Note
Client Interviewing and Data Collection
By: David G. Fubini and Patrick Sanguineti
A module note for the Mastering Consulting and Advisory Skills (MCAS) course, "Client Interviewing and Data Collection" introduces the essentials of client interviews and provides best practices for early career consultants and advisors. View Details
Fubini, David G., and Patrick Sanguineti. "Client Interviewing and Data Collection." Harvard Business School Module Note 423-082, March 2023.