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  • All HBS Web  (1,046)
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  • All HBS Web  (1,046)
    • People  (1)
    • News  (187)
    • Research  (679)
    • Events  (13)
    • Multimedia  (3)
  • Faculty Publications  (561)
← Page 15 of 1,046 Results →
  • 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
Keywords: AI and Machine Learning; Analytics and Data Science; Prejudice and Bias
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Chang, Peter W., Leor Fishman, and Seth Neel. "Feature Importance Disparities for Data Bias Investigations." Working Paper, March 2023.
  • 2022
  • Article

A Human-Centric Take on Model Monitoring

By: Murtuza Shergadwala, Himabindu Lakkaraju and Krishnaram Kenthapadi
Predictive models are increasingly used to make various consequential decisions in high-stakes domains such as healthcare, finance, and policy. It becomes critical to ensure that these models make accurate predictions, are robust to shifts in the data, do not rely on... View Details
Keywords: AI and Machine Learning; Research and Development; Demand and Consumers
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Shergadwala, Murtuza, Himabindu Lakkaraju, and Krishnaram Kenthapadi. "A Human-Centric Take on Model Monitoring." Proceedings of the AAAI Conference on Human Computation and Crowdsourcing (HCOMP) 10 (2022): 173–183.

    Julian De Freitas

    Julian De Freitas is an Assistant Professor of Business Administration in the Marketing Unit, and Director of the Ethical Intelligence Lab, at Harvard Business School. He earned his PhD in psychology from Harvard, masters from Oxford, and BA from Yale. He teaches... View Details

    Keywords: advertising; automotive; consumer products; e-commerce industry; insurance industry; marketing industry; nonprofit industry; software; transportation; video games
    • February 2021
    • Case

    Digital Manufacturing at Amgen

    By: Shane Greenstein, Kyle R. Myers and Sarah Mehta
    This case discusses efforts made by biotechnology (biotech) company Amgen to introduce digital technologies into its manufacturing processes. Doing so is complicated by the fact that the process for manufacturing biologics—or therapeutics made from living cells—is... View Details
    Keywords: Digital Technologies; Change; Change Management; Decision Making; Cost vs Benefits; Decisions; Information; Analytics and Data Science; Innovation and Invention; Innovation and Management; Innovation Leadership; Innovation Strategy; Technological Innovation; Jobs and Positions; Knowledge; Leadership; Organizational Culture; Science; Strategy; Information Technology; Technology Adoption; Biotechnology Industry; Pharmaceutical Industry; United States; California; Puerto Rico; Rhode Island
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    Greenstein, Shane, Kyle R. Myers, and Sarah Mehta. "Digital Manufacturing at Amgen." Harvard Business School Case 621-008, February 2021.
    • 2023
    • Working Paper

    Beyond the Hype: Unveiling the Marginal Benefits of 3D Virtual Tours in Real Estate

    By: Mengxia Zhang and Isamar Troncoso
    3D virtual tours (VTs) have become a popular digital tool in real estate platforms, enabling potential buyers to virtually walk through the houses they search for online. In this paper, we study home sellers’ adoption of VTs and the VTs’ relative benefits compared to... View Details
    Keywords: Marketing; AI and Machine Learning; Technology Adoption; Real Estate Industry
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    Zhang, Mengxia, and Isamar Troncoso. "Beyond the Hype: Unveiling the Marginal Benefits of 3D Virtual Tours in Real Estate." Harvard Business School Working Paper, No. 24-003, July 2023.
    • Article

    How to Use Heuristics for Differential Privacy

    By: Seth Neel, Aaron Leon Roth and Zhiwei Steven Wu
    We develop theory for using heuristics to solve computationally hard problems in differential privacy. Heuristic approaches have enjoyed tremendous success in machine learning, for which performance can be empirically evaluated. However, privacy guarantees cannot be... View Details
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    Neel, Seth, Aaron Leon Roth, and Zhiwei Steven Wu. "How to Use Heuristics for Differential Privacy." Proceedings of the IEEE Annual Symposium on Foundations of Computer Science (FOCS) 60th (2019).
    • 2023
    • Working Paper

    The Customer Journey as a Source of Information

    By: Nicolas Padilla, Eva Ascarza and Oded Netzer
    In the face of heightened data privacy concerns and diminishing third-party data access, firms are placing increased emphasis on first-party data (1PD) for marketing decisions. However, in environments with infrequent purchases, reliance on past purchases 1PD... View Details
    Keywords: Customer Journey; Privacy; Consumer Behavior; Analytics and Data Science; AI and Machine Learning; Customer Focus and Relationships
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    Padilla, Nicolas, Eva Ascarza, and Oded Netzer. "The Customer Journey as a Source of Information." Harvard Business School Working Paper, No. 24-035, October 2023. (Revised October 2023.)
    • April 2019 (Revised June 2019)
    • Case

    From Globalization to Dual Digital Transformation: CEO Thierry Breton Leading Atos Into 'Digital Shockwaves' (A)

    By: Tsedal Neeley, JT Keller and James Barnett
    Thierry Breton, chairman and CEO of IT company Atos, faced a pivotal juncture. After spending eight intense years scaling the company globally to over 100,000 employees in 70 countries, he was ready to take the next crucial step. Breton was convinced that rapid digital... View Details
    Keywords: Dual Digital Transformation; Transformation; Disruption; Employees; Competency and Skills; Training; Decision Making; Digital Transformation
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    Neeley, Tsedal, JT Keller, and James Barnett. "From Globalization to Dual Digital Transformation: CEO Thierry Breton Leading Atos Into 'Digital Shockwaves' (A)." Harvard Business School Case 419-027, April 2019. (Revised June 2019.)

      Zhongming Jiang

      Zhongming Jiang is a first-year Ph.D. student in Marketing (Quantitative) at Harvard Business School. His research focuses on developing methodologies for Customer Relationship Management (CRM) that enable personalized interventions, dynamic customer... View Details

      • 2020
      • Working Paper

      (When) Does Appearance Matter? Evidence from a Randomized Controlled Trial

      By: Prithwiraj Choudhury, Tarun Khanna, Christos A. Makridis and Subhradip Sarker
      While there is evidence about labor market discrimination based on race, religion, and gender, we know little about whether physical appearance leads to discrimination in labor market outcomes. We deploy a randomized experiment on 1,000 respondents in India between... View Details
      Keywords: Behavioral Economics; Coronavirus; Discrimination; Homophily; Labor Market Mobility; Limited Attention; Resumes; Personal Characteristics; Prejudice and Bias
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      Choudhury, Prithwiraj, Tarun Khanna, Christos A. Makridis, and Subhradip Sarker. "(When) Does Appearance Matter? Evidence from a Randomized Controlled Trial." Harvard Business School Working Paper, No. 21-038, September 2020.
      • July 2023 (Revised July 2023)
      • Background Note

      Generative AI Value Chain

      By: Andy Wu and Matt Higgins
      Generative AI refers to a type of artificial intelligence (AI) that can create new content (e.g., text, image, or audio) in response to a prompt from a user. ChatGPT, Bard, and Claude are examples of text generating AIs, and DALL-E, Midjourney, and Stable Diffusion are... View Details
      Keywords: AI; Artificial Intelligence; Model; Hardware; Data Centers; AI and Machine Learning; Applications and Software; Analytics and Data Science; Value
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      Wu, Andy, and Matt Higgins. "Generative AI Value Chain." Harvard Business School Background Note 724-355, July 2023. (Revised July 2023.)
      • May 2021
      • Teaching Note

      From Globalization to Dual Digital Transformation: CEO Thierry Breton Leading Atos Into 'Digital Shockwaves'

      By: Tsedal Neeley
      Teaching Note for HBS Case Nos. 419-027 and 419-046. Thierry Breton, chairman and CEO of IT company Atos, faces a pivotal juncture. After spending eight intense years scaling the company globally to over 100,000 employees in 70 countries, he sees digital shockwaves... View Details
      Keywords: Multinational Firms and Management; Transformation; Strategy; Disruption; Employees; Competency and Skills; Training; Organizational Culture; Digital Transformation; Information Technology Industry
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      Neeley, Tsedal. "From Globalization to Dual Digital Transformation: CEO Thierry Breton Leading Atos Into 'Digital Shockwaves'." Harvard Business School Teaching Note 421-096, May 2021.
      • Research Summary

      Overview

      Ms. Fedyk's main research interests lie at the intersection of asset pricing and behavioral finance, with a particular focus on information and belief formation. Her job market paper is part of a broader research agenda on the way in which information is incorporated... View Details
      • Research Summary

      Overview

      By: Shunyuan Zhang
      Professor Zhang uses machine learning to address marketing problems that have arisen within the nascent sharing economy. She conducts rigorous analyses of structured and unstructured data generated by new sharing economy platforms to address important issues emerging... View Details
      • September 15, 2021
      • Article

      Improving Deconvolution Methods in Biology Through Open Innovation Competitions: An Application to the Connectivity Map

      By: Andrea Blasco, Ted Natoli, Michael G. Endres, Rinat A. Sergeev, Steven Randazzo, Jin Hyun Paik, N.J. Maximilian Macaluso, Rajiv Narayan, Xiaodong Lu, David Peck, Karim R. Lakhani and Aravind Subramanian
      A recurring problem in biomedical research is how to isolate signals of distinct populations (cell types, tissues, and genes) from composite measures obtained by a single analyte or sensor. Existing computational deconvolution approaches work well in many specific... View Details
      Keywords: Deconvolution; Methods; Open Innovation Competition; Genomics; Research; Innovation and Invention
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      Blasco, Andrea, Ted Natoli, Michael G. Endres, Rinat A. Sergeev, Steven Randazzo, Jin Hyun Paik, N.J. Maximilian Macaluso, Rajiv Narayan, Xiaodong Lu, David Peck, Karim R. Lakhani, and Aravind Subramanian. "Improving Deconvolution Methods in Biology Through Open Innovation Competitions: An Application to the Connectivity Map." Bioinformatics 37, no. 18 (September 15, 2021).
      • July 2023 (Revised October 2024)
      • Case

      Revenue Recognition at Stride Funding: Making Sense of Revenues for a Fintech Startup

      By: Paul M. Healy and Jung Koo Kang
      The case explores the challenges of revenue recognition and financial reporting for Stride Funding (Stride), a fintech startup that has disrupted the student loan market. Stride leveraged proprietary machine learning and financial models to underwrite alternative... View Details
      Keywords: Revenue Recognition; Financial Reporting; Entrepreneurial Finance; Business Startups; Growth and Development Strategy; Governance Compliance; Accrual Accounting; Financial Services Industry; United States
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      Healy, Paul M., and Jung Koo Kang. "Revenue Recognition at Stride Funding: Making Sense of Revenues for a Fintech Startup." Harvard Business School Case 124-015, July 2023. (Revised October 2024.)
      • 2018
      • Working Paper

      Some Facts of High-Tech Patenting

      By: Michael Webb, Nick Short, Nicholas Bloom and Josh Lerner
      Patenting in software, cloud computing, and artificial intelligence has grown rapidly in recent years. Such patents are acquired primarily by large U.S. technology firms such as IBM, Microsoft, Google, and HP, as well as by Japanese multinationals such as Sony, Canon,... View Details
      Keywords: Patents; Applications and Software; Technological Innovation; United States
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      Webb, Michael, Nick Short, Nicholas Bloom, and Josh Lerner. "Some Facts of High-Tech Patenting." Harvard Business School Working Paper, No. 19-014, August 2018. (NBER Working Paper Series, No. 24793, July 2018.)
      • May 2021 (Revised February 2024)
      • Teaching Note

      THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)

      By: Ayelet Israeli and Jill Avery
      THE YES, a multi-brand shopping app launched in May 2020 offered a new type of buying experience for women’s fashion, driven by a sophisticated algorithm that used data science and machine learning to create and deliver a personalized store for every shopper, based on... View Details
      Keywords: Data; Data Analytics; Artificial Intelligence; AI; AI Algorithms; AI Creativity; Fashion; Retail; Retail Analytics; E-Commerce Strategy; Platform; Platforms; Big Data; Preference Elicitation; Predictive Analytics; App Development; "Marketing Analytics"; Advertising; Mobile App; Mobile Marketing; Apparel; Online Advertising; Referral Rewards; Referrals; Female Ceo; Female Entrepreneur; Female Protagonist; Analytics and Data Science; Analysis; Creativity; Marketing Strategy; Brands and Branding; Consumer Behavior; Demand and Consumers; Forecasting and Prediction; Marketing Channels; Digital Marketing; Internet and the Web; Mobile and Wireless Technology; AI and Machine Learning; E-commerce; Digital Platforms; Fashion Industry; Retail Industry; Apparel and Accessories Industry; Consumer Products Industry; United States
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      Israeli, Ayelet, and Jill Avery. "THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)." Harvard Business School Teaching Note 521-097, May 2021. (Revised February 2024.)

        Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development

        Predictive model development is understudied despite its importance to modern businesses. Although prior discussions highlight advances in methods (along the dimensions of data, computing power, and algorithms) as the primary driver of model quality, the value of... View Details
        • May 2024
        • Article

        Financial Innovation in the 21st Century: Evidence from U.S. Patents

        By: Josh Lerner, Amit Seru, Nick Short and Yuan Sun
        We develop a unique dataset of 24 thousand U.S. finance patents granted over the last two decades to explore the evolution and production of financial innovation. We use machine learning to identify the financial patents and extensively audit the results to ensure... View Details
        Keywords: Banking; Investment Banks; Information Technology; Regulation; Patents; Innovation and Invention; Trends
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        Lerner, Josh, Amit Seru, Nick Short, and Yuan Sun. "Financial Innovation in the 21st Century: Evidence from U.S. Patents." Journal of Political Economy 132, no. 5 (May 2024): 1391–1449.
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