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All HBS Web
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- Faculty Publications (219)
- September 2020 (Revised June 2023)
- Supplement
Spreadsheet Supplement to Artea Teaching Note
By: Eva Ascarza and Ayelet Israeli
Spreadsheet Supplement to Artea Teaching Note 521-041. This collection of exercises aims to teach students about 1)Targeting Policies; and 2)Algorithmic bias in marketing—implications, causes, and possible solutions. Part (A) focuses on A/B testing analysis and...
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- September 2020
- Case
True North: Pioneering Analytics, Algorithms and Artificial Intelligence
By: Karim R. Lakhani, Kairavi Dey and Hannah Mayer
True North was a private equity fund that specialized in the growth and buyout of mid-market, India-centric companies. The leadership team initially believed that technology was not core to traditional businesses and steered clear of new age technology-oriented...
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Keywords:
Artificial Intelligence;
Information Technology;
Management;
Operations;
Organizations;
Leadership;
Innovation and Invention;
Business Model;
AI and Machine Learning;
Computer Industry;
Technology Industry
Lakhani, Karim R., Kairavi Dey, and Hannah Mayer. "True North: Pioneering Analytics, Algorithms and Artificial Intelligence." Harvard Business School Case 621-042, September 2020.
- Article
Conversational Receptiveness: Expressing Engagement with Opposing Views
By: M. Yeomans, J. Minson, H. Collins, H. Chen and F. Gino
We examine “conversational receptiveness”—the use of language to communicate one’s willingness to thoughtfully engage with opposing views. We develop an interpretable machine-learning algorithm to identify the linguistic profile of receptiveness (Studies 1A-B). We then...
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Keywords:
Receptiveness;
Natural Language Processing;
Disagreement;
Interpersonal Communication;
Relationships;
Conflict Management
Yeomans, M., J. Minson, H. Collins, H. Chen, and F. Gino. "Conversational Receptiveness: Expressing Engagement with Opposing Views." Organizational Behavior and Human Decision Processes 160 (September 2020): 131–148.
- September–October 2020
- Article
Managing Churn to Maximize Profits
By: Aurelie Lemmens and Sunil Gupta
Customer defection threatens many industries, prompting companies to deploy targeted, proactive customer retention programs and offers. A conventional approach has been to target customers either based on their predicted churn probability or their responsiveness to a...
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Keywords:
Churn Management;
Defection Prediction;
Loss Function;
Stochastic Gradient Boosting;
Customer Relationship Management;
Consumer Behavior;
Profit
Lemmens, Aurelie, and Sunil Gupta. "Managing Churn to Maximize Profits." Marketing Science 39, no. 5 (September–October 2020): 956–973.
- August 2020 (Revised March 2021)
- Supplement
Migros Turkey: Scaling Online Operations (B)
By: Antonio Moreno and Gamze Yucaoglu
The case opens in February 2020 as Ozgur Tort and Mustafa Bartin, CEO and chief large-format and online retail officer of Migros Ticaret A.S. (Migros), Turkey’s oldest and one of its largest supermarket chains, are looking over the results of the fulfillment pilot the...
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Keywords:
Grocery;
Business Model;
Strategy;
Digital Platforms;
Information Technology;
Technology Adoption;
Value Creation;
Globalization;
Competition;
Expansion;
Logistics;
Profit;
Resource Allocation;
Corporate Strategy;
Retail Industry;
Turkey
Moreno, Antonio, and Gamze Yucaoglu. "Migros Turkey: Scaling Online Operations (B)." Harvard Business School Supplement 621-027, August 2020. (Revised March 2021.)
- Article
Oracle Efficient Private Non-Convex Optimization
By: Seth Neel, Aaron Leon Roth, Giuseppe Vietri and Zhiwei Steven Wu
One of the most effective algorithms for differentially private learning and optimization is objective perturbation. This technique augments a given optimization problem (e.g. deriving from an ERM problem) with a random linear term, and then exactly solves it....
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Neel, Seth, Aaron Leon Roth, Giuseppe Vietri, and Zhiwei Steven Wu. "Oracle Efficient Private Non-Convex Optimization." Proceedings of the International Conference on Machine Learning (ICML) 37th (2020).
- 2021
- Conference Presentation
An Algorithmic Framework for Fairness Elicitation
By: Christopher Jung, Michael J. Kearns, Seth Neel, Aaron Leon Roth, Logan Stapleton and Zhiwei Steven Wu
We consider settings in which the right notion of fairness is not captured by simple mathematical definitions (such as equality of error rates across groups), but might be more complex and nuanced and thus require elicitation from individual or collective stakeholders....
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Jung, Christopher, Michael J. Kearns, Seth Neel, Aaron Leon Roth, Logan Stapleton, and Zhiwei Steven Wu. "An Algorithmic Framework for Fairness Elicitation." Paper presented at the 2nd Symposium on Foundations of Responsible Computing (FORC), 2021.
- Article
Development of a Deep Learning Algorithm for Periapical Disease Detection in Dental Radiographs
By: Michael G. Endres, Florian Hillen, Marios Salloumis, Ahmad R. Sedaghat, Stefan M. Niehues, Olivia Quatela, Henning Hanken, Ralf Smeets, Benedicta Beck-Broichsitter, Carsten Rendenbach, Karim R. Lakhani, Max Helland and Robert A. Gaudin
Periapical radiolucencies, which can be detected on panoramic radiographs, are one of the most common radiographic findings in dentistry and have a differential diagnosis including infections, granuloma, cysts, and tumors. In this study, we seek to investigate the...
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Keywords:
Artificial Intelligence;
Diagnosis;
Computer-assisted;
Image Interpretation;
Machine Learning;
Radiography;
Panoramic Radiograph;
AI and Machine Learning
Endres, Michael G., Florian Hillen, Marios Salloumis, Ahmad R. Sedaghat, Stefan M. Niehues, Olivia Quatela, Henning Hanken, Ralf Smeets, Benedicta Beck-Broichsitter, Carsten Rendenbach, Karim R. Lakhani, Max Helland, and Robert A. Gaudin. "Development of a Deep Learning Algorithm for Periapical Disease Detection in Dental Radiographs." Diagnostics 10, no. 6 (June 2020).
- May 2020
- Article
Inventory Auditing and Replenishment Using Point-of-Sales Data
By: Achal Bassamboo, Antonio Moreno and Ioannis Stamatopoulos
Spoilage, expiration, damage due to employee/customer handling, employee theft, and customer shoplifting usually are not reflected in inventory records. As a result, records often report phantom inventory, i.e., units of good not available for sale. We derive an...
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Keywords:
Shelf Availability;
Inventory Record Inaccuracy;
Optimal Replenishment;
Retail Analytics;
Performance Effectiveness;
Analysis;
Mathematical Methods
Bassamboo, Achal, Antonio Moreno, and Ioannis Stamatopoulos. "Inventory Auditing and Replenishment Using Point-of-Sales Data." Production and Operations Management 29, no. 5 (May 2020): 1219–1231.
- April 2020
- Article
CEO Behavior and Firm Performance
By: Oriana Bandiera, Stephen Hansen, Andrea Prat and Raffaella Sadun
We measure the behavior of 1,114 CEOs in six countries parsing granular CEO diary data through an unsupervised machine learning algorithm. The algorithm uncovers two distinct behavioral types: "leaders" and "managers." Leaders focus on multi-function, high-level...
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Bandiera, Oriana, Stephen Hansen, Andrea Prat, and Raffaella Sadun. "CEO Behavior and Firm Performance." Journal of Political Economy 128, no. 4 (April 2020): 1325–1369.
- 2020
- Working Paper
Topic Preference Detection: A Novel Approach to Understand Perspective Taking in Conversation
By: Michael Yeomans and Alison Wood Brooks
Although most humans engage in conversations constantly throughout their lives, conversational mistakes are commonplace— interacting with others is difficult, and conversation re-quires quick, relentless perspective-taking and decision making. For example: during every...
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Keywords:
Natural Language Processing;
Interpersonal Communication;
Perspective;
Decision Making;
Perception
Yeomans, Michael, and Alison Wood Brooks. "Topic Preference Detection: A Novel Approach to Understand Perspective Taking in Conversation." Harvard Business School Working Paper, No. 20-077, February 2020.
- 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...
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Keywords:
Artificial Intelligence;
Algorithms;
Technological Innovation;
Business Model;
Competition;
Competitive Strategy;
AI and Machine Learning
Iansiti, Marco, and Karim R. Lakhani. "Competing in the Age of AI." Harvard Business Review 98, no. 1 (January–February 2020): 60–67.
- January 2020
- Case
Lunchclub: Algorithmic Networking
By: Scott Duke Kominers and George Gonzalez
Algorithmic networking startup Lunchclub coordinates in-person meetings between professionals who would have been unlikely to meet. The company faces marketplace design, growth, and monetization challenges: The executive team has to refine Lunchclub's marketplace...
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Keywords:
Monetization Strategy;
Networking;
Business Startups;
Marketplace Matching;
Market Design;
Growth and Development Strategy;
Information Industry
Kominers, Scott Duke, and George Gonzalez. "Lunchclub: Algorithmic Networking." Harvard Business School Case 820-051, January 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...
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Keywords:
Artificial Intelligence;
Technological Innovation;
Change;
Competition;
Strategy;
Leadership;
Business Processes;
Organizational Change and Adaptation;
AI and Machine Learning
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.
- 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...
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Bertsimas, Dimitris, and Michael Lingzhi Li. "Scalable Holistic Linear Regression." Operations Research Letters 48, no. 3 (May 2020): 203–208.
- December 2019
- Article
Communicating with Warmth in Distributive Negotiations Is Surprisingly Counterproductive
By: M. Jeong, J. Minson, M. Yeomans and F. Gino
When entering into a negotiation, individuals have the choice to enact a variety of communication styles. We test the differential impact of being “warm and friendly” versus “tough and firm” in a distributive negotiation, when first offers are held constant and...
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Keywords:
Negotiation Style;
Communication Strategy;
Perception;
Performance Effectiveness;
Outcome or Result
Jeong, M., J. Minson, M. Yeomans, and F. Gino. "Communicating with Warmth in Distributive Negotiations Is Surprisingly Counterproductive." Management Science 65, no. 12 (December 2019): 5813–5837.
- December 2019
- Article
Costly Concessions: An Empirical Framework for Matching with Imperfectly Transferable Utility
By: Alfred Galichon, Scott Duke Kominers and Simon Weber
We introduce an empirical framework for models of matching with imperfectly transferable utility and unobserved heterogeneity in tastes. Our framework allows us to characterize matching equilibrium in a flexible way that includes as special cases the classic fully- and...
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Keywords:
Sorting;
Matching;
Marriage Market;
Intrahousehold Allocation;
Imperfectly Transferable Utility;
Marketplace Matching;
Mathematical Methods
Galichon, Alfred, Scott Duke Kominers, and Simon Weber. "Costly Concessions: An Empirical Framework for Matching with Imperfectly Transferable Utility." Journal of Political Economy 127, no. 6 (December 2019): 2875–2925.
- 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...
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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).
- Article
Advancing Computational Biology and Bioinformatics Research Through Open Innovation Competitions
By: Andrea Blasco, Michael G. Endres, Rinat A. Sergeev, Anup Jonchhe, Max Macaluso, Rajiv Narayan, Ted Natoli, Jin H. Paik, Bryan Briney, Chunlei Wu, Andrew I. Su, Aravind Subramanian and Karim R. Lakhani
Open data science and algorithm development competitions offer a unique avenue for rapid discovery of better computational strategies. We highlight three examples in computational biology and bioinformatics research where the use of competitions has yielded significant...
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Keywords:
Computational Biology;
Bioinformatics;
Innovation Competitions;
Research;
Collaborative Innovation and Invention
Blasco, Andrea, Michael G. Endres, Rinat A. Sergeev, Anup Jonchhe, Max Macaluso, Rajiv Narayan, Ted Natoli, Jin H. Paik, Bryan Briney, Chunlei Wu, Andrew I. Su, Aravind Subramanian, and Karim R. Lakhani. "Advancing Computational Biology and Bioinformatics Research Through Open Innovation Competitions." PLoS ONE 14, no. 9 (September 2019).
- 2019
- Article
More Amazon Effects: Online Competition and Pricing Behaviors
By: Alberto Cavallo
I study how online competition, with its shrinking margins, algorithmic pricing technologies, and the transparency of the web, can change the pricing behavior of large retailers in the U.S. and affect aggregate inflation dynamics. In particular, I show that in the past...
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Keywords:
Amazon;
Online Prices;
Inflation;
Uniform Pricing;
Price Stickiness;
Monetary Economics;
Economics;
Macroeconomics;
Inflation and Deflation;
System Shocks;
United States
Cavallo, Alberto. "More Amazon Effects: Online Competition and Pricing Behaviors." Jackson Hole Economic Symposium Conference Proceedings (Federal Reserve Bank of Kansas City) (2019).