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(668)
- News (145)
- Research (428)
- Events (20)
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- Faculty Publications (308)
Show Results For
- All HBS Web
(668)
- News (145)
- Research (428)
- Events (20)
- Multimedia (12)
- Faculty Publications (308)
- September 24, 2021
- Article
A Labor Movement for the Platform Economy
By: Li Jin, Scott Duke Kominers and Lila Shroff
Platforms are fundamentally changing the contract between workers and companies—and the workers and creatives that create value for platform companies, and rely on platforms for their livelihoods, often have little power when it comes to getting their concerns... View Details
Keywords: Gig Workers; Decentralized Collective Action; Internet and the Web; Labor; Labor and Management Relations; Digital Platforms
Jin, Li, Scott Duke Kominers, and Lila Shroff. "A Labor Movement for the Platform Economy." Harvard Business Review Digital Articles (September 24, 2021).
- 10 Jun 2017
- News
How big data helped secure Emmanuel Macron’s astounding victory
- September 2018
- Article
Aggregation of Consumer Ratings: An Application to Yelp.com
By: Weijia Dai, Ginger Jin, Jungmin Lee and Michael Luca
Because consumer reviews leverage the wisdom of the crowd, the way in which they are aggregated is a central decision faced by platforms. We explore this "rating aggregation problem" and offer a structural approach to solving it, allowing for (1) reviewers to vary in... View Details
Keywords: User Generated Content; Crowdsourcing; Yelp; Social and Collaborative Networks; Information; Internet and the Web; Learning; Mathematical Methods; E-commerce
Dai, Weijia, Ginger Jin, Jungmin Lee, and Michael Luca. "Aggregation of Consumer Ratings: An Application to Yelp.com." Quantitative Marketing and Economics 16, no. 3 (September 2018): 289–339.
- 2021
- Working Paper
The Demand for Executive Skills
By: Stephen Hansen, Raffaella Sadun, Tejas Ramdas and Joseph B. Fuller
We use a unique corpus of job descriptions for C-suite positions to document skills requirements in top managerial occupations across a large sample of firms. A novel algorithm maps the text of each executive search into six separate skill clusters reflecting... View Details
Keywords: C-Suite; Jobs and Positions; Competency and Skills; Management Skills; Job Search; Job Design and Levels
Hansen, Stephen, Raffaella Sadun, Tejas Ramdas, and Joseph B. Fuller. "The Demand for Executive Skills." Harvard Business School Working Paper, No. 21-133, June 2021.
- Winter 2016
- Article
Analytics for an Online Retailer: Demand Forecasting and Price Optimization
By: Kris J. Ferreira, Bin Hong Alex Lee and David Simchi-Levi
We present our work with an online retailer, Rue La La, as an example of how a retailer can use its wealth of data to optimize pricing decisions on a daily basis. Rue La La is in the online fashion sample sales industry, where they offer extremely limited-time... View Details
Ferreira, Kris J., Bin Hong Alex Lee, and David Simchi-Levi. "Analytics for an Online Retailer: Demand Forecasting and Price Optimization." Manufacturing & Service Operations Management 18, no. 1 (Winter 2016): 69–88.
- July 2025
- Case
The Future in Sight: LumineticsCore and the First Autonomous AI for Diagnostics
By: Michael Lingzhi Li and Tinglong Dai
After two decades of research, Dr. Michael Abramoff successfully launched LumineticsCore—the first autonomous AI system authorized by the FDA to diagnose diabetic retinopathy without physician oversight. The case traces his journey across algorithm design, clinical... View Details
- 2021
- Working Paper
The Demand for Executive Skills
By: Stephen Hansen, Tejas Ramdas, Raffaella Sadun and Joseph B. Fuller
We use a unique corpus of job descriptions for C-suite positions to document skills requirements in top managerial occupations across a large sample of firms. A novel algorithm maps the text of each executive search into six separate skill clusters reflecting... View Details
Hansen, Stephen, Tejas Ramdas, Raffaella Sadun, and Joseph B. Fuller. "The Demand for Executive Skills." NBER Working Paper Series, No. 28959, June 2021.
- March 2021
- Case
VideaHealth: Building the AI Factory
By: Karim R. Lakhani and Amy Klopfenstein
Florian Hillen, co-founder and CEO of VideaHealth, a startup that used artificial intelligence (AI) to detect dental conditions on x-rays, spent the early years of his company laying the groundwork for an AI factory. A process for quickly building and iterating on new... View Details
Keywords: Artificial Intelligence; Innovation and Invention; Disruptive Innovation; Technological Innovation; Information Technology; Applications and Software; Technology Adoption; Digital Platforms; Entrepreneurship; AI and Machine Learning; Technology Industry; Medical Devices and Supplies Industry; North and Central America; United States; Massachusetts; Cambridge
Lakhani, Karim R., and Amy Klopfenstein. "VideaHealth: Building the AI Factory." Harvard Business School Case 621-021, March 2021.
Eliminating unintended bias in personalized policies using Bias Eliminating Adapted Trees (BEAT) - PNAS
An inherent risk of algorithmic personalization is disproportionate targeting of individuals from certain groups (or demographic characteristics such as gender or race), even when the decision maker does not intend to discriminate based on those... View Details
- May 2023
- Technical Note
Dynamic Pricing: Timing is Everything
By: Elie Ofek
This note provides a comprehensive exposition to the topic of dynamic pricing (whereby the fee customers are charged is time-dependent). It covers the motivation for firms to engage in dynamic pricing, provides a typology of the main formats dynamic pricing can take,... View Details
Ofek, Elie. "Dynamic Pricing: Timing is Everything." Harvard Business School Technical Note 523-110, May 2023.
- Article
Crowdsourcing City Government: Using Tournaments to Improve Inspection Accuracy
By: Edward Glaeser, Andrew Hillis, Scott Duke Kominers and Michael Luca
The proliferation of big data makes it possible to better target city services like hygiene inspections, but city governments rarely have the in-house talent needed for developing prediction algorithms. Cities could hire consultants, but a cheaper alternative is to... View Details
Keywords: User-generated Content; Operations; Tournaments; Policy-making; Machine Learning; Online Platforms; Analytics and Data Science; Mathematical Methods; City; Infrastructure; Business Processes; Government and Politics
Glaeser, Edward, Andrew Hillis, Scott Duke Kominers, and Michael Luca. "Crowdsourcing City Government: Using Tournaments to Improve Inspection Accuracy." American Economic Review: Papers and Proceedings 106, no. 5 (May 2016): 114–118.
- February 2024
- Teaching Note
Data-Driven Denim: Financial Forecasting at Levi Strauss
By: Mark Egan
Teaching Note for HBS Case No. 224-029. Levi Strauss & Co. (“Levi Strauss”) partnered with the IT services company Wipro to incorporate more sophisticated methods, such as machine learning, into their financial forecasting process starting in 2018. The decision to... View Details
- April 2020
- Article
CEO Behavior and Firm Performance
By: Oriana Bandiera, Stephen Hansen, Andrea Prat and Raffaella Sadun
We measure the behavior of 1,114 CEOs in six countries parsing granular CEO diary data through an unsupervised machine learning algorithm. The algorithm uncovers two distinct behavioral types: "leaders" and "managers." Leaders focus on multi-function, high-level... View Details
Bandiera, Oriana, Stephen Hansen, Andrea Prat, and Raffaella Sadun. "CEO Behavior and Firm Performance." Journal of Political Economy 128, no. 4 (April 2020): 1325–1369.
- Spring 2016
- Article
Performance Responses to Competition Across Skill-Levels in Rank Order Tournaments: Field Evidence and Implications for Tournament Design
By: Kevin J. Boudreau, Karim R. Lakhani and Michael E. Menietti
Tournaments are widely used in the economy to organize production and innovation. We study individual contestant-level data from 2,796 contestants in 774 software algorithm design contests with random assignment. Precisely conforming to theory predictions, the... View Details
Boudreau, Kevin J., Karim R. Lakhani, and Michael E. Menietti. "Performance Responses to Competition Across Skill-Levels in Rank Order Tournaments: Field Evidence and Implications for Tournament Design." RAND Journal of Economics 47, no. 1 (Spring 2016): 140–165.
- April 2008
- Article
The Survey of Industrial R&D—Patent Database Link Project
By: William R. Kerr and Shihe Fu
This paper details the construction of a firm-year panel dataset combining the NBER Patent Dataset with the Survey of Industrial R&D conducted by the Census Bureau and National Science Foundation. The dataset constitutes a platform that offers an unprecedented view of... View Details
Keywords: Analytics and Data Science; Patents; Surveys; Research and Development; Innovation and Invention; Performance Productivity; Projects; Management Practices and Processes; Management Analysis, Tools, and Techniques
Kerr, William R., and Shihe Fu. "The Survey of Industrial R&D—Patent Database Link Project." Journal of Technology Transfer 33, no. 2 (April 2008): 173–186.
- July 2023
- Case
DayTwo: Going to Market with Gut Microbiome (Abridged)
By: Ayelet Israeli
DayTwo is a young Israeli startup that applies research on the gut microbiome and machine learning algorithms to deliver personalized nutritional recommendations to its users in order to minimize blood sugar spikes after meals. After a first year of trial rollout in... View Details
Keywords: Business Startups; AI and Machine Learning; Nutrition; Market Entry and Exit; Product Marketing; Distribution Channels
Israeli, Ayelet. "DayTwo: Going to Market with Gut Microbiome (Abridged)." Harvard Business School Case 524-015, July 2023.
- Research Summary
Overview
By: Antonio Moreno
Professor Moreno’s research explores how digital technologies are reshaping operational processes, with a particular focus on retail and service industries. His early work examined omnichannel retail—the integration of online and offline channels to create seamless... View Details
- 2024
- Working Paper
The Cram Method for Efficient Simultaneous Learning and Evaluation
By: Zeyang Jia, Kosuke Imai and Michael Lingzhi Li
We introduce the "cram" method, a general and efficient approach to simultaneous learning and evaluation using a generic machine learning (ML) algorithm. In a single pass of batched data, the proposed method repeatedly trains an ML algorithm and tests its empirical... View Details
Keywords: AI and Machine Learning
Jia, Zeyang, Kosuke Imai, and Michael Lingzhi Li. "The Cram Method for Efficient Simultaneous Learning and Evaluation." Working Paper, March 2024.