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  • Web

Accounting & Management - Faculty & Research

Wittenberg-Moerman July 2025 | Article | Accounting Review To mitigate information asymmetry about borrowers in developing economies, digital lenders use machine-learning algorithms and nontraditional data from borrowers’ mobile devices.... View Details
  • 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
  • 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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  • 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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  • 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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  • 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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  • Web

Technology & Operations Management - Faculty & Research

without physician oversight. The case traces his journey across algorithm design, clinical validation, regulatory navigation, and the challenges of real-world adoption. It explores the interplay between technological innovation and... View Details
  • 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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  • 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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  • 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
  • 06 Mar 2025
  • HBS Seminar

Vivek Farias, MIT Sloan

  • 28 Feb 2018
  • HBS Seminar

Kartik Hosanagar, Wharton, University of Pennsylvania

  • Web

Africa - Global

Regina Wittenberg-Moerman To mitigate information asymmetry about borrowers in developing economies, digital lenders use machine-learning algorithms and nontraditional data from borrowers’ mobile devices. Consequently, digital lenders... View Details
  • 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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    Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem

    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,... View Details
    • 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
    • 22 May 2019
    • Blog Post

    What is FIELD Global Immersion?

    to travel based on where their home country is, and where they have extensive travel or professional experience. With these considerations in mind, country and team assignments (aka: Global Section assignments) are made via an algorithm... View Details
    • 07 Feb 2022
    • Research & Ideas

    Digital Transformation: A New Roadmap for Success

    algorithms can lead to unintended bias that harms certain employees and customers, and the company’s reputation (a bias story can go viral on social media within minutes). 5. Design for inclusive and agile problem-solving As they become... View Details
    Keywords: by Linda A. Hill, Ann Le Cam, Sunand Menon, and Emily Tedards
    • 18 Feb 2025
    • HBS Seminar

    Andrey Simonov, Columbia University