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      • Faculty Publications  (1,261)

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      • January–February 2020
      • Article

      Competing in the Age of AI

      By: Marco Iansiti and Karim R. Lakhani
      Today’s markets are being reshaped by a new kind of firm—one in which artificial intelligence (AI) runs the show. This cohort includes giants like Google, Facebook, and Alibaba, and growing businesses such as Wayfair and Ocado. Every time we use their services, the... View Details
      Keywords: Artificial Intelligence; Algorithms; Technological Innovation; Business Model; Competition; Competitive Strategy; AI and Machine Learning
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      Iansiti, Marco, and Karim R. Lakhani. "Competing in the Age of AI." Harvard Business Review 98, no. 1 (January–February 2020): 60–67.
      • 2021
      • Working Paper

      Impact Investing: A Theory of Financing Social Enterprises

      By: Benjamin N. Roth
      I present a model of financing social enterprises to delineate the role of impact investors relative to “pure” philanthropists. I characterize the optimal scale and structure of a social enterprise when financed by grants, and when financed by investments. Impact... View Details
      Keywords: Impact Investing; Social Entrepreneurship; Finance; Investment; Mathematical Methods
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      Roth, Benjamin N. "Impact Investing: A Theory of Financing Social Enterprises." Harvard Business School Working Paper, No. 20-078, February 2020. (Revised June 2021.)
      • Article

      Fake AI People Won't Fix Online Dating

      By: Scott Duke Kominers
      Computer-generated images may inspire even more distrust and surely won’t lead to the love of a lifetime. View Details
      Keywords: Artificial Intelligence; Dating Services; Internet and the Web; Ethics; AI and Machine Learning
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      Kominers, Scott Duke. "Fake AI People Won't Fix Online Dating." Bloomberg Opinion (January 16, 2020).
      • 2020
      • Book

      Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World

      By: Marco Iansiti and Karim R. Lakhani
      In industry after industry, data, analytics, and AI-driven processes are transforming the nature of work. While we often still treat AI as the domain of a specific skill, business function, or sector, we have entered a new era in which AI is challenging the very... View Details
      Keywords: Artificial Intelligence; Technological Innovation; Change; Competition; Strategy; Leadership; Business Processes; Organizational Change and Adaptation; AI and Machine Learning
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      Iansiti, Marco, and Karim R. Lakhani. Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World. Boston: Harvard Business Review Press, 2020.
      • Article

      A Theories-in-Use Approach to Building Marketing Theory

      By: G. Zaltman, Valarie A. Zeithaml, Bernard Jaworski, Ajay K. Kohli, Kapil R. Tuli and Wolfgang Ulaga
      This article’s objective is to inspire and provide guidance on the development of marketing knowledge based on the theories-in-use (TIU) approach. The authors begin with a description of the TIU approach and compare it with other inductive and deductive research... View Details
      Keywords: Building Theory; Grounded Theory; Theories-in-use; Theory Construction; Theory Development; Marketing; Knowledge; Theory
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      Zaltman, G., Valarie A. Zeithaml, Bernard Jaworski, Ajay K. Kohli, Kapil R. Tuli, and Wolfgang Ulaga. "A Theories-in-Use Approach to Building Marketing Theory." Journal of Marketing 84, no. 1 (January 2020): 32–51.
      • Article

      Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error

      By: Celia Cintas, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan and Edward McFowland III
      Reliably detecting attacks in a given set of inputs is of high practical relevance because of the vulnerability of neural networks to adversarial examples. These altered inputs create a security risk in applications with real-world consequences, such as self-driving... View Details
      Keywords: Autoencoder Networks; Pattern Detection; Subset Scanning; Computer Vision; Statistical Methods And Machine Learning; Machine Learning; Deep Learning; Data Mining; Big Data; Large-scale Systems; Mathematical Methods; Analytics and Data Science
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      Cintas, Celia, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan, and Edward McFowland III. "Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error." Proceedings of the International Joint Conference on Artificial Intelligence 29th (2020).
      • May 2020
      • Article

      Scalable Holistic Linear Regression

      By: Dimitris Bertsimas and Michael Lingzhi Li
      We propose a new scalable algorithm for holistic linear regression building on Bertsimas & King (2016). Specifically, we develop new theory to model significance and multicollinearity as lazy constraints rather than checking the conditions iteratively. The resulting... View Details
      Keywords: Mathematical Methods; Analytics and Data Science
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      Bertsimas, Dimitris, and Michael Lingzhi Li. "Scalable Holistic Linear Regression." Operations Research Letters 48, no. 3 (May 2020): 203–208.
      • November 2019
      • Supplement

      Hapag-Lloyd AG: Complying with IMO 2020

      By: Benjamin C. Esty, Mette Fuglsang Hjortshoej and Emer Moloney
      A new environmental regulation known as IMO 2020 was creating what one industry analyst called “the biggest shakeup for the oil and shipping industries in decades.” According to the new regulation, all ocean-going ships would have to limit their sulfur emissions by... View Details
      Keywords: Valuation; Ship Transportation; Strategic Planning; Game Theory; Pollutants; Supply Chain; Corporate Accountability; Capital Budgeting; Environmental Sustainability; Shipping Industry; Transportation Industry; Germany
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      Esty, Benjamin C., Mette Fuglsang Hjortshoej, and Emer Moloney. "Hapag-Lloyd AG: Complying with IMO 2020." Harvard Business School Spreadsheet Supplement 220-713, November 2019.
      • November 2019
      • Case

      Hapag-Lloyd AG: Complying with IMO 2020

      By: Benjamin C. Esty, Mette Fuglsang Hjortshoej and Emer Moloney
      A new environmental regulation known as IMO 2020 was creating what one industry analyst called “the biggest shakeup for the oil and shipping industries in decades.” According to the new regulation, all ocean-going ships would have to limit their sulfur emissions by... View Details
      Keywords: Valuation; Ship Transportation; Strategic Planning; Game Theory; Pollutants; Supply Chain; Corporate Accountability; Capital Budgeting; Environmental Sustainability; Governing Rules, Regulations, and Reforms; Governance Compliance; Shipping Industry; Transportation Industry; Germany
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      Esty, Benjamin C., Mette Fuglsang Hjortshoej, and Emer Moloney. "Hapag-Lloyd AG: Complying with IMO 2020." Harvard Business School Case 220-003, November 2019.
      • 2020
      • Working Paper

      Tech Clusters

      By: William R. Kerr and Frederic Robert-Nicoud
      Tech clusters like Silicon Valley play a central role for modern innovation, business competitiveness, and economic performance. This paper reviews what constitutes a tech cluster, how they function internally, and the degree to which policy makers can purposefully... View Details
      Keywords: Clusters; Agglomeration; Innovation; Industry Clusters; Innovation and Invention; Entrepreneurship; Patents
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      Kerr, William R., and Frederic Robert-Nicoud. "Tech Clusters." Harvard Business School Working Paper, No. 20-063, November 2019. (Revised June 2020.)
      • 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).
      • 2019
      • Working Paper

      Design Rules, Volume 2: How Technology Shapes Organizations: Chapter 17 The Wintel Standards-based Platform

      By: Carliss Y. Baldwin
      The purpose of this chapter is to use the theory of bottlenecks laid out in previous chapters to better understand the dynamics of an open standards-based platform. I describe how the Wintel platform evolved from 1990 through 2000 under joint sponsorship of Intel and... View Details
      Keywords: Open Platforms; Bottlenecks; Wintel Platform; Disintermediation; Information Infrastructure; Applications and Software; Business History; Digital Platforms; Computer Industry
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      Baldwin, Carliss Y. "Design Rules, Volume 2: How Technology Shapes Organizations: Chapter 17 The Wintel Standards-based Platform." Harvard Business School Working Paper, No. 20-055, November 2019.
      • 2019
      • Working Paper

      The Impact of the General Data Protection Regulation on Internet Interconnection

      By: Ran Zhuo, Bradley Huffaker, KC Claffy and Shane Greenstein
      The Internet comprises thousands of independently operated networks, where bilaterally negotiated interconnection agreements determine the flow of data between networks. The European Union’s General Data Protection Regulation (GDPR) imposes strict restrictions on... View Details
      Keywords: Personal Data; Privacy Regulation; GDPR; Interconnection Agreements; Internet and the Web; Governing Rules, Regulations, and Reforms; European Union
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      Zhuo, Ran, Bradley Huffaker, KC Claffy, and Shane Greenstein. "The Impact of the General Data Protection Regulation on Internet Interconnection." NBER Working Paper Series, No. 26481, November 2019.
      • October 2019
      • Case

      Feeling Machines: Emotion AI at Affectiva

      By: Shane Greenstein and John Masko
      In 2016, Affectiva—a Boston-based emotion AI software company with a long track record of building emotion-sensing software for market research—had attempted to expand into new verticals by releasing a mobile software development kit (SDK) that downloaders could adapt... View Details
      Keywords: Artificial Intelligence; Market Research; Business Model; Finance; Revenue; Decision Making; Risk and Uncertainty; Market Entry and Exit; Applications and Software; AI and Machine Learning; Information Technology Industry; Auto Industry; United States
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      Greenstein, Shane, and John Masko. "Feeling Machines: Emotion AI at Affectiva." Harvard Business School Case 620-058, October 2019.
      • Article

      Machine Learning Approaches to Facial and Text Analysis: Discovering CEO Oral Communication Styles

      By: Prithwiraj Choudhury, Dan Wang, Natalie A. Carlson and Tarun Khanna
      We demonstrate how a novel synthesis of three methods—(1) unsupervised topic modeling of text data to generate new measures of textual variance, (2) sentiment analysis of text data, and (3) supervised ML coding of facial images with a cutting-edge convolutional neural... View Details
      Keywords: CEOs; Communication Style; Machine Learning; Spoken Communication; Nonverbal Communication; Personal Characteristics; Analysis; Performance
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      Choudhury, Prithwiraj, Dan Wang, Natalie A. Carlson, and Tarun Khanna. "Machine Learning Approaches to Facial and Text Analysis: Discovering CEO Oral Communication Styles." Strategic Management Journal 40, no. 11 (November 2019): 1705–1732.
      • October 2019
      • Case

      Leading Bank Leumi into the Future

      By: Joshua D. Margolis, Allison M. Ciechanover, Nicole Keller and Danielle Golan
      An unlikely but highly effective leader of a traditional bank, Rakefet Russak-Aminoach, simultaneously leads a classic change effort and an unconventional effort to innovate. She focuses her initial energy on making the bank more efficient in the face of industry... View Details
      Keywords: Mobile Banking; Digital Banking; Fintech; Startup; Financial Services; Artificial Intelligence; Innovation; Efficiency; Organizational Change; Personal Development; Female Ceo; Banks and Banking; Mobile and Wireless Technology; Leadership; Organizational Change and Adaptation; Innovation and Invention; Disruption; Information Technology; Opportunities; Performance Effectiveness; Personal Development and Career; AI and Machine Learning; Financial Services Industry; Banking Industry; Israel
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      Margolis, Joshua D., Allison M. Ciechanover, Nicole Keller, and Danielle Golan. "Leading Bank Leumi into the Future." Harvard Business School Case 420-063, October 2019.
      • October 2019 (Revised March 2021)
      • Background Note

      Modern Automation (B): Robotics

      By: William R. Kerr and James Palano
      Driven largely by advances in perception and situational awareness, robots in the 2010s were gaining functionality that allowed them to be applied to fundamentally new types of work. The expanding range of new tasks that could be completed by machines had significant... View Details
      Keywords: Robotics; Artificial Intelligence; Future Of Work; Technology Commercialization; Information Technology; Commercialization; Employment; AI and Machine Learning
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      Kerr, William R., and James Palano. "Modern Automation (B): Robotics." Harvard Business School Background Note 820-069, October 2019. (Revised March 2021.)
      • Article

      Organizational Innovation in the Multinational Enterprise: Internalization Theory and Business History

      By: Teresa da Silva Lopes, Mark Casson and Geoffrey Jones
      This article engages in a methodological experiment by using historical evidence to challenge a common misperception about internalization theory. The theory has often been criticized for maintaining that it assumes a hierarchically organized MNE based on knowledge... View Details
      Keywords: Internalization; Multinational Strategy; Business History; Organization And Management Theory; Globalization; Entrepreneurship; Governance; History; Organizations; Theory; Africa; Asia; Europe; Latin America; North and Central America
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      da Silva Lopes, Teresa, Mark Casson, and Geoffrey Jones. "Organizational Innovation in the Multinational Enterprise: Internalization Theory and Business History." Journal of International Business Studies 50, no. 8 (October 2019): 1338–1358.
      • 2019
      • Working Paper

      Soul and Machine (Learning)

      By: Davide Proserpio, John R. Hauser, Xiao Liu, Tomomichi Amano, Alex Burnap, Tong Guo, Dokyun Lee, Randall Lewis, Kanishka Misra, Eric Schwarz, Artem Timoshenko, Lilei Xu and Hema Yoganarasimhan
      Machine learning is bringing us self-driving cars, improved medical diagnostics, and machine translation, but can it improve marketing decisions? It can. Machine learning models predict extremely well, are scalable to “big data,” and are a natural fit to rich media... View Details
      Keywords: Machine Learning; Technological Innovation; Marketing; AI and Machine Learning
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      Proserpio, Davide, John R. Hauser, Xiao Liu, Tomomichi Amano, Alex Burnap, Tong Guo, Dokyun Lee, Randall Lewis, Kanishka Misra, Eric Schwarz, Artem Timoshenko, Lilei Xu, and Hema Yoganarasimhan. "Soul and Machine (Learning)." Harvard Business School Working Paper, No. 20-036, September 2019.
      • 2020
      • Working Paper

      Collusion in Brokered Markets

      By: John William Hatfield, Scott Duke Kominers and Richard Lowery
      The U.S. residential real estate agency market presents a puzzle for economic theory: commissions on real estate transactions have remained high for decades even though entry is frequent and costs are low. We model the real estate agency market, and other brokered... View Details
      Keywords: Real Estate; "Repeated Games"; Collusion; Antitrust; Brokered Markets; Game Theory; Real Estate Industry
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      Hatfield, John William, Scott Duke Kominers, and Richard Lowery. "Collusion in Brokered Markets." Harvard Business School Working Paper, No. 20-023, September 2019. (Revised July 2020.)
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