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  • All HBS Web  (653)
    • News  (145)
    • Research  (425)
    • Events  (20)
    • Multimedia  (12)
  • Faculty Publications  (300)

Show Results For

  • All HBS Web  (653)
    • News  (145)
    • Research  (425)
    • Events  (20)
    • Multimedia  (12)
  • Faculty Publications  (300)
← Page 14 of 653 Results →
  • 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
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Lakhani, Karim R., and Amy Klopfenstein. "VideaHealth: Building the AI Factory." Harvard Business School Case 621-021, March 2021.
  • 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
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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.
  • 29 May 2018
  • News

A Study of NASA Scientists Shows How to Overcome Barriers to Open Innovation

  • Oct 2020
  • Conference Presentation

Optimal, Truthful, and Private Securities Lending

By: Emily Diana, Michael J. Kearns, Seth Neel and Aaron Leon Roth
We consider a fundamental dynamic allocation problem motivated by the problem of securities lending in financial markets, the mechanism underlying the short selling of stocks. A lender would like to distribute a finite number of identical copies of some scarce resource... View Details
Keywords: Differential Privacy; Mechanism Design; Finance; Mathematical Methods
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Diana, Emily, Michael J. Kearns, Seth Neel, and Aaron Leon Roth. "Optimal, Truthful, and Private Securities Lending." Paper presented at the 1st Association for Computing Machinery (ACM) International Conference on AI in Finance (ICAIF), October 2020.
  • 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
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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.
  • 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
Keywords: Dynamic Pricing; Price
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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
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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.
  • October 2022
  • Exercise

Shanty Real Estate: Confidential Information for iBuyer 2

By: Michael Luca, Jesse M. Shapiro and Nathan Sun
Shanty is a simulation in which students inhabit the role of either a traditional home buyer or an iBuyer, both bidding on the same condo. The traditional home buyer has access to a “comp sheet” of similar properties that have recently sold, and has done a walkthrough.... View Details
Keywords: Decision Choices and Conditions; Decision Making; Market Timing; Measurement and Metrics
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Luca, Michael, Jesse M. Shapiro, and Nathan Sun. "Shanty Real Estate: Confidential Information for iBuyer 2." Harvard Business School Exercise 923-020, October 2022.
  • November 2020
  • Teaching Note

DayTwo: Going to Market with Gut Microbiome

By: Ayelet Israeli
Teaching Note for HBS Case No. 519-010. 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.... View Details
Keywords: Start-up Growth; Startup; Positioning; Targeting; Go To Market Strategy; B2B Vs. B2C; B2B2C; Health & Wellness; AI; Machine Learning; Female Ceo; Female Protagonist; Science-based; Science And Technology Studies; Ecommerce; Applications; DTC; Direct To Consumer Marketing; US Health Care; "USA,"; Innovation; Pricing; Business Growth; Segmentation; Distribution Channels; Growth and Development Strategy; Business Startups; Science-Based Business; Health; Innovation and Invention; Marketing; Information Technology; Business Growth and Maturation; E-commerce; Applications and Software; Health Industry; Technology Industry; Insurance Industry; Information Technology Industry; Food and Beverage Industry; Israel; United States
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Israeli, Ayelet. "DayTwo: Going to Market with Gut Microbiome." Harvard Business School Teaching Note 521-052, November 2020.
  • 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
Keywords: Forecasting; Regression; Machine Learning; Artificial Intelligence; Apparel; Corporate Finance; Forecasting and Prediction; AI and Machine Learning; Apparel and Accessories Industry; United States
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Egan, Mark. "Data-Driven Denim: Financial Forecasting at Levi Strauss." Harvard Business School Teaching Note 224-073, February 2024.
  • 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
Keywords: CEOs; Management; Behavior; Organizations; Performance; Analysis
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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
Keywords: Competition; Innovation Strategy
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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.

    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

    • November 2015 (Revised May 2016)
    • Case

    Aspiring Minds

    By: Karim R. Lakhani, Marco Iansiti and Christine Snively
    By 2015, India-based employment assessment and certification provider Aspiring Minds had helped facilitate over 300,000 job matches through its assessment tools. Aspiring Minds' flagship product, the Aspiring Minds Computer Adaptive Test (AMCAT), used machine learning... View Details
    Keywords: Information Technology; Strategy; Higher Education; Technological Innovation; Employment; Technology Industry; India; China
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    Lakhani, Karim R., Marco Iansiti, and Christine Snively. "Aspiring Minds." Harvard Business School Case 616-013, November 2015. (Revised May 2016.)
    • 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
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    Israeli, Ayelet. "DayTwo: Going to Market with Gut Microbiome (Abridged)." Harvard Business School Case 524-015, July 2023.
    • 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
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    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.
    • 17 Jun 2015
    • News

    High Yield On Main Street: Investors Earn 12% Lending To Small Business, When Banks Won't

    • 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
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    Jia, Zeyang, Kosuke Imai, and Michael Lingzhi Li. "The Cram Method for Efficient Simultaneous Learning and Evaluation." Working Paper, March 2024.
    • 20 Apr 2021
    • News

    10 Things Your Artificial Intelligence Initiative Needs to Succeed

    • Article

    Accuracy First: Selecting a Differential Privacy Level for Accuracy-Constrained ERM

    By: Katrina Ligett, Seth Neel, Aaron Leon Roth, Bo Waggoner and Steven Wu
    Traditional approaches to differential privacy assume a fixed privacy requirement ϵ for a computation, and attempt to maximize the accuracy of the computation subject to the privacy constraint. As differential privacy is increasingly deployed in practical settings, it... View Details
    Keywords: Differential Privacy; Empirical Risk Minimization; Accuracy First
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    Ligett, Katrina, Seth Neel, Aaron Leon Roth, Bo Waggoner, and Steven Wu. "Accuracy First: Selecting a Differential Privacy Level for Accuracy-Constrained ERM." Journal of Privacy and Confidentiality 9, no. 2 (2019).
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