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  • All HBS Web  (702)
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    • Research  (431)
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Show Results For

  • All HBS Web  (702)
    • News  (144)
    • Research  (431)
    • Events  (20)
    • Multimedia  (12)
  • Faculty Publications  (315)
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  • June 2020
  • Article

Real-time Data from Mobile Platforms to Evaluate Sustainable Transportation Infrastructure

By: Omar Isaac Asensio, Kevin Alvarez, Arielle Dror, Emerson Wenzel, Catharina Hollauer and Sooji Ha
By displacing gasoline and diesel fuels, electric cars and fleets reduce emissions from the transportation sector, thus offering important public health benefits. However, public confidence in the reliability of charging infrastructure remains a fundamental barrier to... View Details
Keywords: Environmental Sustainability; Transportation; Infrastructure; Behavior; AI and Machine Learning; Demand and Consumers
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Asensio, Omar Isaac, Kevin Alvarez, Arielle Dror, Emerson Wenzel, Catharina Hollauer, and Sooji Ha. "Real-time Data from Mobile Platforms to Evaluate Sustainable Transportation Infrastructure." Nature Sustainability 3, no. 6 (June 2020): 463–471.
  • 2017
  • Working Paper

The Need for Speed: Effects of Uncertainty Reduction in Patenting

By: Mike Horia Teodorescu
Patents are essential in commerce to establish property rights for ideas and to give equal protection to firms that develop new technologies. Young firms especially depend on the protection of intellectual property to bring a product from concept to market. However,... View Details
Keywords: Startups; Natural Language Processing; Machine Learning; Patents; Business Startups; Risk and Uncertainty; Outcome or Result; Green Technology Industry
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Teodorescu, Mike Horia. "The Need for Speed: Effects of Uncertainty Reduction in Patenting." Working Paper, September 2017. (Job Market Paper.)
  • July 2011
  • Article

Kidney Paired Donation

By: C. Bradley Wallis, Kannan P. Samy, Alvin E. Roth and Michael A. Rees
Kidney paired donation (KPD) was first suggested in 1986, but it was not until 2000 when the first paired donation transplant was performed in the U.S. In the past decade, KPD has become the fastest growing source of transplantable kidneys, overcoming the barrier faced... View Details
Keywords: Philanthropy and Charitable Giving; Health Care and Treatment; Growth and Development Strategy; Success; Problems and Challenges; Programs; System; United States
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Wallis, C. Bradley, Kannan P. Samy, Alvin E. Roth, and Michael A. Rees. "Kidney Paired Donation." Nephrology, Dialysis, Transplantation 26, no. 7 (July 2011): 2091–2099.
  • 05 Sep 2013
  • Working Paper Summaries

Performance Responses to Competition Across Skill-Levels in Rank Order Tournaments: Field Evidence and Implications for Tournament Design

Keywords: by Kevin J. Boudreau, Constance E. Helfat, Karim R. Lakhani & Michael E. Menietti.
  • 2023
  • Article

Benchmarking Large Language Models on CMExam—A Comprehensive Chinese Medical Exam Dataset

By: Junling Liu, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Lei Zhu and Michael Lingzhi Li
Recent advancements in large language models (LLMs) have transformed the field of question answering (QA). However, evaluating LLMs in the medical field is challenging due to the lack of standardized and comprehensive datasets. To address this gap, we introduce CMExam,... View Details
Keywords: Large Language Model; AI and Machine Learning; Analytics and Data Science; Health Industry
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Liu, Junling, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Lei Zhu, and Michael Lingzhi Li. "Benchmarking Large Language Models on CMExam—A Comprehensive Chinese Medical Exam Dataset." Conference on Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track 36 (2023).
  • December 2022 (Revised June 2023)
  • Case

Hacking the U.S. Election: Russia's Misinformation Campaign

By: Shikhar Ghosh
The case discusses the relatively low technology approach used by Russia to influence the U.S. Presidential Election in 2016. Although political parties manipulating the media was not a new phenomenon, the Russians ran a broad, well-financed, and sophisticated social... View Details
Keywords: Political Elections; International Relations; Social Media; Power and Influence; Information; Russia; United States
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Ghosh, Shikhar. "Hacking the U.S. Election: Russia's Misinformation Campaign." Harvard Business School Case 823-043, December 2022. (Revised June 2023.)
  • 2016
  • Working Paper

Foreign Competition and Domestic Innovation: Evidence from U.S. Patents

By: David Autor, David Dorn, Gordon H. Hanson, Pian Shu and Gary Pisano
Manufacturing is the locus of U.S. innovation, accounting for more than three quarters of U.S. corporate patents. The rise of import competition from China has represented a major competitive shock to the sector, which in theory could benefit or stifle innovation. In... View Details
Keywords: Patents; Competition; System Shocks; Trade; Innovation and Invention; Manufacturing Industry; China; United States
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Autor, David, David Dorn, Gordon H. Hanson, Pian Shu, and Gary Pisano. "Foreign Competition and Domestic Innovation: Evidence from U.S. Patents." NBER Working Paper Series, No. 22879, December 2016.
  • 22 Feb 2024
  • Research & Ideas

How to Make AI 'Forget' All the Private Data It Shouldn't Have

predictions about the world. And now, even though generative AI feels very different from making a simple prediction, at a technical level, that's really what it is. In order to train these predictive systems, you need lots of example data input and output pairs. The... View Details
Keywords: by Rachel Layne; Technology; Information Technology
  • Article

Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable Recourses

By: Kaivalya Rawal and Himabindu Lakkaraju
As predictive models are increasingly being deployed in high-stakes decision-making, there has been a lot of interest in developing algorithms which can provide recourses to affected individuals. While developing such tools is important, it is even more critical to... View Details
Keywords: Predictive Models; Decision Making; Framework; Mathematical Methods
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Rawal, Kaivalya, and Himabindu Lakkaraju. "Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable Recourses." Advances in Neural Information Processing Systems (NeurIPS) 33 (2020).
  • 2021
  • Working Paper

Time Dependency, Data Flow, and Competitive Advantage

By: Ehsan Valavi, Joel Hestness, Marco Iansiti, Newsha Ardalani, Feng Zhu and Karim R. Lakhani
Data is fundamental to machine learning-based products and services and is considered strategic due to its externalities for businesses, governments, non-profits, and more generally for society. It is renowned that the value of organizations (businesses, government... View Details
Keywords: Economics Of AI; Value Of Data; Perishability; Time Dependency; Flow Of Data; Data Strategy; Analytics and Data Science; Value; Strategy; Competitive Advantage
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Valavi, Ehsan, Joel Hestness, Marco Iansiti, Newsha Ardalani, Feng Zhu, and Karim R. Lakhani. "Time Dependency, Data Flow, and Competitive Advantage." Harvard Business School Working Paper, No. 21-099, March 2021.
  • March 2022
  • Article

Where to Locate COVID-19 Mass Vaccination Facilities?

By: Dimitris Bertsimas, Vassilis Digalakis Jr, Alexander Jacquillat, Michael Lingzhi Li and Alessandro Previero
The outbreak of COVID-19 led to a record-breaking race to develop a vaccine. However, the limited vaccine capacity creates another massive challenge: how to distribute vaccines to mitigate the near-end impact of the pandemic? In the United States in particular, the new... View Details
Keywords: Vaccines; COVID-19; Health Care and Treatment; Health Pandemics; Performance Effectiveness; Analytics and Data Science; Mathematical Methods
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Bertsimas, Dimitris, Vassilis Digalakis Jr, Alexander Jacquillat, Michael Lingzhi Li, and Alessandro Previero. "Where to Locate COVID-19 Mass Vaccination Facilities?" Naval Research Logistics Quarterly 69, no. 2 (March 2022): 179–200.
  • 2022
  • Article

Towards Robust Off-Policy Evaluation via Human Inputs

By: Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez and Himabindu Lakkaraju
Off-policy Evaluation (OPE) methods are crucial tools for evaluating policies in high-stakes domains such as healthcare, where direct deployment is often infeasible, unethical, or expensive. When deployment environments are expected to undergo changes (that is, dataset... View Details
Keywords: Analytics and Data Science; Research
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Singh, Harvineet, Shalmali Joshi, Finale Doshi-Velez, and Himabindu Lakkaraju. "Towards Robust Off-Policy Evaluation via Human Inputs." Proceedings of the AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (2022): 686–699.
  • 22 May 2024
  • HBS Case

Banned or Not, TikTok Is a Force Companies Can’t Afford to Ignore

Practice at HBS who authored the case study with HBS researcher Shweta Bagai. Businesses need to “understand how it is that they’re doing what they’re doing so that they can incorporate the power of algorithmic technologies into their... View Details
Keywords: by Rachel Layne; Technology
  • 19 Dec 2023
  • Research & Ideas

The 10 Most Popular Articles of 2023

life that includes rest, relationships, and a rewarding career. Is AI Coming for Your Job?In a post-AI world, where an algorithm can draft marketing copy—or even pop songs and movie scripts—anything seems possible. Harvard Business School... View Details
Keywords: by Danielle Kost
  • July 2024
  • Article

How Artificial Intelligence Constrains Human Experience

By: A. Valenzuela, S. Puntoni, D. Hoffman, N. Castelo, J. De Freitas, B. Dietvorst, C. Hildebrand, Y.E. Huh, R. Meyer, M. Sweeney, S. Talaifar, G. Tomaino and K. Wertenbroch
Many consumption decisions and experiences are digitally mediated. As a consequence, consumer behavior is increasingly the joint product of human psychology and ubiquitous algorithms (Braun et al. 2024; cf. Melumad et al. 2020). The coming of age of Large Language... View Details
Keywords: Large Language Model; User Experience; AI and Machine Learning; Consumer Behavior; Technology Adoption; Risk and Uncertainty; Cost vs Benefits
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Valenzuela, A., S. Puntoni, D. Hoffman, N. Castelo, J. De Freitas, B. Dietvorst, C. Hildebrand, Y.E. Huh, R. Meyer, M. Sweeney, S. Talaifar, G. Tomaino, and K. Wertenbroch. "How Artificial Intelligence Constrains Human Experience." Journal of the Association for Consumer Research 9, no. 3 (July 2024): 241–256.
  • December 2016
  • Article

Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud

By: Michael Luca and Georgios Zervas
Consumer reviews are now part of everyday decision making. Yet, the credibility of these reviews is fundamentally undermined when businesses commit review fraud, creating fake reviews for themselves or their competitors. We investigate the economic incentives to commit... View Details
Keywords: Ethics; Marketing Reference Programs
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Luca, Michael, and Georgios Zervas. "Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud." Management Science 62, no. 12 (December 2016): 3412–3427.
  • 2015
  • Working Paper

Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud

By: Michael Luca and Georgios Zervas
Consumer reviews are now part of everyday decision-making. Yet, the credibility of these reviews is fundamentally undermined when businesses commit review fraud, creating fake reviews for themselves or their competitors. We investigate the economic incentives to commit... View Details
Keywords: Information; Competition; Internet and the Web; Ethics; Reputation; Social and Collaborative Networks; Retail Industry; Food and Beverage Industry
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Luca, Michael, and Georgios Zervas. "Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud." Working Paper. (May 2015. Revise and resubmit, Management Science.)
  • 30 Nov 2010
  • Working Paper Summaries

Sponsored Links’ or ’Advertisements’?: Measuring Labeling Alternatives in Internet Search Engines

Keywords: by Benjamin Edelman & Duncan S. Gilchrist; Advertising; Technology
  • October–December 2022
  • Article

Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem

By: Mochen Yang, Edward McFowland III, Gordon Burtch and Gediminas Adomavicius
Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data, followed... View Details
Keywords: Machine Learning; Econometric Analysis; Instrumental Variable; Random Forest; Causal Inference; AI and Machine Learning; Forecasting and Prediction
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Yang, Mochen, Edward McFowland III, Gordon Burtch, and Gediminas Adomavicius. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem." INFORMS Journal on Data Science 1, no. 2 (October–December 2022): 138–155.
  • 29 Apr 2013
  • Working Paper Summaries

Exclusive Preferential Placement as Search Diversion: Evidence from Flight Search

Keywords: by Benjamin G. Edelman & Zhenyu Lai; Publishing; Technology
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