Skip to Main Content
HBS Home
  • About
  • Academic Programs
  • Alumni
  • Faculty & Research
  • Baker Library
  • Giving
  • Harvard Business Review
  • Initiatives
  • News
  • Recruit
  • Map / Directions
Faculty & Research
  • Faculty
  • Research
  • Featured Topics
  • Academic Units
  • …→
  • Harvard Business School→
  • Faculty & Research→
  • Research
    • Research
    • Publications
    • Global Research Centers
    • Case Development
    • Initiatives & Projects
    • Research Services
    • Seminars & Conferences
    →
  • Publications→

Publications

Publications

Filter Results: (600) Arrow Down
Filter Results: (600) Arrow Down Arrow Up

Show Results For

  • All HBS Web  (3,053)
    • Faculty Publications  (600)

    Show Results For

    • All HBS Web  (3,053)
      • Faculty Publications  (600)

      Machine Learning ModelsRemove Machine Learning Models →

      ← Page 15 of 600 Results →

      Are you looking for?

      →Search All HBS Web
      • June 2022
      • Article

      The Use and Misuse of Patent Data: Issues for Finance and Beyond

      By: Josh Lerner and Amit Seru
      Patents and citations are powerful tools for understanding innovation increasingly used in financial economics (and management research more broadly). Biases may result, however, from the interactions between the truncation of patents and citations and the changing... View Details
      Keywords: Patents; Analytics and Data Science; Corporate Finance; Research
      Citation
      Find at Harvard
      Read Now
      Related
      Lerner, Josh, and Amit Seru. "The Use and Misuse of Patent Data: Issues for Finance and Beyond." Review of Financial Studies 35, no. 6 (June 2022): 2667–2704.
      • 2022
      • Conference Presentation

      Towards the Unification and Robustness of Post hoc Explanation Methods

      By: Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu and Himabindu Lakkaraju
      As machine learning black boxes are increasingly being deployed in critical domains such as healthcare and criminal justice, there has been a growing emphasis on developing techniques for explaining these black boxes in a post hoc manner. In this work, we analyze two... View Details
      Keywords: AI and Machine Learning
      Citation
      Read Now
      Related
      Agarwal, Sushant, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu, and Himabindu Lakkaraju. "Towards the Unification and Robustness of Post hoc Explanation Methods." Paper presented at the 3rd Symposium on Foundations of Responsible Computing (FORC), 2022.
      • May 2022
      • Case

      AWS and Amazon SageMaker (A): The Commercialization of Machine Learning Services

      By: Karim R. Lakhani, Shane Greenstein and Kerry Herman
      Citation
      Educators
      Purchase
      Related
      Lakhani, Karim R., Shane Greenstein, and Kerry Herman. "AWS and Amazon SageMaker (A): The Commercialization of Machine Learning Services." Harvard Business School Case 622-060, May 2022.
      • May 2022
      • Supplement

      AWS and Amazon SageMaker (B): The Commercialization of Machine Learning Services

      By: Karim R. Lakhani, Shane Greenstein and Kerry Herman
      Citation
      Purchase
      Related
      Lakhani, Karim R., Shane Greenstein, and Kerry Herman. "AWS and Amazon SageMaker (B): The Commercialization of Machine Learning Services." Harvard Business School Supplement 622-086, May 2022.
      • May 2022 (Revised July 2022)
      • Supplement

      AWS and Amazon SageMaker (C): The Commercialization of Machine Learning Services

      By: Karim R. Lakhani, Shane Greenstein and Kerry Herman
      Citation
      Purchase
      Related
      Lakhani, Karim R., Shane Greenstein, and Kerry Herman. "AWS and Amazon SageMaker (C): The Commercialization of Machine Learning Services." Harvard Business School Supplement 622-087, May 2022. (Revised July 2022.)
      • May 2022 (Revised June 2024)
      • Case

      LOOP: Driving Change in Auto Insurance Pricing

      By: Elie Ofek and Alicia Dadlani
      John Henry and Carey Anne Nadeau, co-founders and co-CEOs of LOOP, an insurtech startup based in Austin, Texas, were on a mission to modernize the archaic $250 billion automobile insurance market. They sought to create equitably priced insurance by eliminating pricing... View Details
      Keywords: AI and Machine Learning; Technological Innovation; Equality and Inequality; Prejudice and Bias; Growth and Development Strategy; Customer Relationship Management; Price; Insurance Industry; Financial Services Industry
      Citation
      Educators
      Purchase
      Related
      Ofek, Elie, and Alicia Dadlani. "LOOP: Driving Change in Auto Insurance Pricing." Harvard Business School Case 522-073, May 2022. (Revised June 2024.)
      • May 2022 (Revised July 2022)
      • Case

      The Voice War Continues: Hey Google vs. Alexa vs. Siri in 2022

      By: David B. Yoffie and Daniel Fisher
      In 2022, after five years of pursuing a new "AI-first" strategy, Google had captured a sizeable share of the American and global markets for voice assistants. Google Assistant was used by hundreds of millions of users around the world, but Amazon retained the largest... View Details
      Keywords: Strategy; Artificial Intelligence; Deep Learning; Voice Assistants; Smart Home; Market Share; Globalized Markets and Industries; Competitive Strategy; Digital Platforms; AI and Machine Learning; Technology Industry; United States
      Citation
      Educators
      Purchase
      Related
      Yoffie, David B., and Daniel Fisher. "The Voice War Continues: Hey Google vs. Alexa vs. Siri in 2022." Harvard Business School Case 722-462, May 2022. (Revised July 2022.)
      • May 2022
      • Article

      Coins for Bombs: The Predictive Ability of On-Chain Transfers for Terrorist Attacks

      By: Dan Amiram, Evgeny Lyandres and Daniel Rabetti
      This study examines whether we can learn from the behavior of blockchain-based transfers to predict the financing of terrorist attacks. We exploit blockchain transaction transparency to map millions of transfers for hundreds of large on-chain service providers. The... View Details
      Keywords: Blockchain; Bitcoin; Accounting; AI and Machine Learning; National Security; Governing Rules, Regulations, and Reforms
      Citation
      Read Now
      Related
      Amiram, Dan, Evgeny Lyandres, and Daniel Rabetti. "Coins for Bombs: The Predictive Ability of On-Chain Transfers for Terrorist Attacks." Journal of Accounting Research 60, no. 2 (May 2022): 427–466.
      • Article

      Developing a Digital Mindset: How to Lead Your Organization into the Age of Data, Algorithms, and AI

      By: Tsedal Neeley and Paul Leonardi
      Learning new technological skills is essential for digital transformation. But it is not enough. Employees must be motivated to use their skills to create new opportunities. They need a digital mindset: a set of attitudes and behaviors that enable people and... View Details
      Keywords: Machine Learning; AI; Information Technology; Transformation; Competency and Skills; Employees; Technology Adoption; Leading Change; Digital Transformation
      Citation
      Find at Harvard
      Read Now
      Purchase
      Related
      Neeley, Tsedal, and Paul Leonardi. "Developing a Digital Mindset: How to Lead Your Organization into the Age of Data, Algorithms, and AI." S22032. Harvard Business Review 100, no. 3 (May–June 2022): 50–55.
      • 2022
      • Article

      Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis.

      By: Martin Pawelczyk, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay and Himabindu Lakkaraju
      As machine learning (ML) models become more widely deployed in high-stakes applications, counterfactual explanations have emerged as key tools for providing actionable model explanations in practice. Despite the growing popularity of counterfactual explanations, a... View Details
      Keywords: Machine Learning Models; Counterfactual Explanations; Adversarial Examples; Mathematical Methods
      Citation
      Read Now
      Related
      Pawelczyk, Martin, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay, and Himabindu Lakkaraju. "Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis." Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) 25th (2022).
      • 2022
      • Book

      The Digital Mindset: What It Really Takes to Thrive in the Age of Data, Algorithms, and AI

      By: Paul Leonardi and Tsedal Neeley
      The pressure to "be digital" has never been greater, but you can meet the challenge. The digital revolution is here, changing how work gets done, how industries are structured, and how people from all walks of life work, behave, and relate to each other. To thrive... View Details
      Keywords: Digital; Artificial Intelligence; Big Data; Digital Transformation; Technological Innovation; Transformation; Learning; Competency and Skills
      Citation
      Purchase
      Related
      Leonardi, Paul, and Tsedal Neeley. The Digital Mindset: What It Really Takes to Thrive in the Age of Data, Algorithms, and AI. Boston, MA: Harvard Business Review Press, 2022.
      • April 2022
      • Supplement

      Mastercard Labs (B)

      By: Linda A. Hill, Sunil Gupta, Emily Tedards and Julia Kelley
      When Ajaypal (Ajay) Banga became the CEO of Mastercard in 2010, digital technologies were on the rise, and innovation needed to become a strategic imperative at the company. Banga tasked Garry Lyons, who had joined Mastercard through the 2009 acquisition of Orbiscom,... View Details
      Keywords: Organizational Behavior; Culture; Transformation; Organizational Culture; Culture Change; Organizational Adaptation; Organizational Effectiveness; Alignment; Leadership; Leadership Development; Innovation; Innovation Ecosystems; Diversity; Collaboration; Co-creation; Learning Organizations; Empowerment; Ecosystem; Agility; Prototype; Experiment; Partnerships; Operating Model; Risk Management; Digital Transformation; Metrics; Payments; Financial Industry; Financial Inclusion; Ambidexterity; Corporate Innovation; Innovation Lab; Accelerator; Start-up; Fintech
      Citation
      Purchase
      Related
      Hill, Linda A., Sunil Gupta, Emily Tedards, and Julia Kelley. "Mastercard Labs (B)." Harvard Business School Supplement 422-081, April 2022.
      • April 2022 (Revised May 2022)
      • Case

      Mastercard Labs (A)

      By: Linda A. Hill, Sunil Gupta, Emily Tedards and Julia Kelley
      When Ajaypal (Ajay) Banga became the CEO of Mastercard in 2010, he shifted the company’s competitive focus from card networks to cash itself. Mastercard’s new vision of a “World Beyond Cash” distilled into a three-pronged framework: Grow the core business, Diversify... View Details
      Keywords: Organizational Behavior; Culture; Culture Change; Organizational Adaptation; Organizational Effectiveness; Alignment; Leadership; Leadership Development; Innovation; Innovation Ecosystems; Ecosystem; Diversity; Collaboration; Co-creation; Learning Organizations; Empowerment; Globalization; Agility; Prototype; Experiment; Partnerships; Operating Model; Risk Management; Metrics; Payments; Financial Inclusion; Financial Industry; Ambidexterity; Corporate Innovation; Innovation Lab; Digital Transformation; Digital Strategy; Credit Cards; Innovation Leadership; Organizational Culture
      Citation
      Educators
      Purchase
      Related
      Hill, Linda A., Sunil Gupta, Emily Tedards, and Julia Kelley. "Mastercard Labs (A)." Harvard Business School Case 422-080, April 2022. (Revised May 2022.)
      • April 2022 (Revised May 2022)
      • Case

      Mastercard Labs (A) (Abridged)

      By: Linda A. Hill, Sunil Gupta, Emily Tedards and Julia Kelley
      When Ajaypal (Ajay) Banga became the CEO of Mastercard in 2010, he shifted the company’s competitive focus from card networks to cash itself. Mastercard’s new vision of a “World Beyond Cash” distilled into a three-pronged framework: Grow the core business, Diversify... View Details
      Keywords: Organizational Behavior; Culture; Organizational Culture; Culture Change; Organizational Adaptation; Organizational Effectiveness; Alignment; Leadership; Leadership Development; Innovation; Innovation Ecosystems; Diversity; Collaboration; Co-creation; Learning Organizations; Empowerment; Ecosystem; Agility; Prototype; Experiment; Partnerships; Operating Model; Risk Management; Metrics; Payments; Financial Inclusion; Financial Industry; Ambidexterity; Corporate Innovation; Innovation Lab; Accelerator; Start-up; Intrapreneurship; Competitive Strategy; Business Model; Technological Innovation; Growth and Development Strategy; Digital Transformation
      Citation
      Educators
      Purchase
      Related
      Hill, Linda A., Sunil Gupta, Emily Tedards, and Julia Kelley. "Mastercard Labs (A) (Abridged)." Harvard Business School Case 422-082, April 2022. (Revised May 2022.)
      • April–June 2022
      • Other Article

      Commentary on 'Causal Decision Making and Causal Effect Estimation Are Not the Same... and Why It Matters'

      By: Edward McFowland III
      There has been a substantial discussion in various methodological and applied literatures around causal inference; especially in the use of machine learning and statistical models to understand heterogeneity in treatment effects and to make optimal decision... View Details
      Keywords: Causal Inference; Treatment Effect Estimation; Treatment Assignment Policy; Human-in-the-loop; Decision Making; Fairness
      Citation
      Find at Harvard
      Purchase
      Related
      McFowland III, Edward. "Commentary on 'Causal Decision Making and Causal Effect Estimation Are Not the Same... and Why It Matters'." INFORMS Journal on Data Science 1, no. 1 (April–June 2022): 21–22.
      • March 2022 (Revised January 2025)
      • Technical Note

      Prediction & Machine Learning

      By: Iavor I. Bojinov, Michael Parzen and Paul Hamilton
      This note provides an introduction to machine learning for an introductory data science course. The note begins with a description of supervised, unsupervised, and reinforcement learning. Then, the note provides a brief explanation of the difference between traditional... View Details
      Keywords: Machine Learning; Data Science; Learning; Analytics and Data Science; Performance Evaluation; AI and Machine Learning
      Citation
      Educators
      Purchase
      Related
      Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Prediction & Machine Learning." Harvard Business School Technical Note 622-101, March 2022. (Revised January 2025.)
      • Article

      Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)

      By: Eva Ascarza and Ayelet Israeli

      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 “protected”... View Details

      Keywords: Algorithm Bias; Personalization; Targeting; Generalized Random Forests (GRF); Discrimination; Customization and Personalization; Decision Making; Fairness; Mathematical Methods
      Citation
      Read Now
      Related
      Ascarza, Eva, and Ayelet Israeli. "Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)." e2115126119. Proceedings of the National Academy of Sciences 119, no. 11 (March 8, 2022).
      • March 2022 (Revised May 2022)
      • Case

      Winning Business at Russell Reynolds (A)

      By: Ethan Bernstein and Cara Mazzucco
      In an effort to make compensation drive collaboration, Russell Reynolds Associates’ (RRA) CEO Clarke Murphy sought to re-engineer the bonus system for his executive search consultants in 2016. As his HR analytics guru, Kelly Smith, points out, that risks upsetting–and... View Details
      Keywords: Compensation; Collaboration; Executive Search Firms; Consulting Firms; Compensation and Benefits; Restructuring; Human Resources; Human Capital; Management Practices and Processes; Organizational Culture; Organizational Change and Adaptation; Social and Collaborative Networks; Recruitment; Selection and Staffing; Talent and Talent Management; Consulting Industry; Employment Industry; Asia; Europe; Latin America; Middle East; North and Central America; South America; Oceania
      Citation
      Educators
      Purchase
      Related
      Bernstein, Ethan, and Cara Mazzucco. "Winning Business at Russell Reynolds (A)." Harvard Business School Case 422-045, March 2022. (Revised May 2022.)
      • March 2022
      • Supplement

      Winning Business at Russell Reynolds (B)

      By: Ethan Bernstein and Cara Mazzucco
      In an effort to make compensation drive collaboration, Russell Reynolds Associates’ (RRA) CEO Clarke Murphy sought to re-engineer the bonus system for his executive search consultants in 2016. As his HR analytics guru, Kelly Smith, points out, that risks upsetting–and... View Details
      Keywords: Compensation; Collaboration; Executive Search Firms; Consulting Firms; Compensation and Benefits; Restructuring; Human Resources; Human Capital; Management Practices and Processes; Organizational Culture; Organizational Change and Adaptation; Social and Collaborative Networks; Recruitment; Selection and Staffing; Talent and Talent Management; Consulting Industry; Employment Industry; Asia; Europe; Latin America; Middle East; North and Central America; South America; Oceania
      Citation
      Purchase
      Related
      Bernstein, Ethan, and Cara Mazzucco. "Winning Business at Russell Reynolds (B)." Harvard Business School Supplement 422-046, March 2022.
      • March 2022
      • Article

      Winner Takes All? Tech Clusters, Population Centers, and the Spatial Transformation of U.S. Invention

      By: Brad Chattergoon and William R. Kerr
      U.S. invention has become increasingly concentrated around major tech centers since the 1970s, with implications for how much cities across the country share in concomitant local benefits. Is invention becoming a winner-takes-all race? We explore the rising spatial... View Details
      Keywords: Clusters; Invention; Agglomeration; Artificial Intelligence; Innovation and Invention; Patents; Applications and Software; Industry Clusters; AI and Machine Learning
      Citation
      Find at Harvard
      Read Now
      Related
      Chattergoon, Brad, and William R. Kerr. "Winner Takes All? Tech Clusters, Population Centers, and the Spatial Transformation of U.S. Invention." Art. 104418. Research Policy 51, no. 2 (March 2022).
      • ←
      • 15
      • 16
      • …
      • 29
      • 30
      • →

      Are you looking for?

      →Search All HBS Web
      ǁ
      Campus Map
      Harvard Business School
      Soldiers Field
      Boston, MA 02163
      →Map & Directions
      →More Contact Information
      • Make a Gift
      • Site Map
      • Jobs
      • Harvard University
      • Trademarks
      • Policies
      • Accessibility
      • Digital Accessibility
      Copyright © President & Fellows of Harvard College.