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All HBS Web
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- Faculty Publications (527)
- September 2023
- Supplement
Root Capital and the Efficient Impact Frontier Simulation: Guidelines and Suggestions
By: Shawn Cole
Cole, Shawn. "Root Capital and the Efficient Impact Frontier Simulation: Guidelines and Suggestions." Harvard Business School Supplement 224-034, September 2023.
- September 2023
- Supplement
CMA CGM: Reducing the Carbon Footprint of Container Shipping
By: Willy Shih
Marine transport is the most cost-effective way to move large volumes over long distances, and container shipping is the backbone of international trade in goods. Yet shipping contributed 3% of worldwide greenhouse gas emissions, and the deep-sea segment, which...
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- September 2023
- Supplement
CMA CGM: Reducing the Carbon Footprint of Container Shipping
By: Willy Shih
Marine transport is the most cost-effective way to move large volumes over long distances, and container shipping is the backbone of international trade in goods. Yet shipping contributed 3% of worldwide greenhouse gas emissions, and the deep-sea segment, which...
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- 2023
- Working Paper
Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality
By: Fabrizio Dell'Acqua, Edward McFowland III, Ethan Mollick, Hila Lifshitz-Assaf, Katherine C. Kellogg, Saran Rajendran, Lisa Krayer, François Candelon and Karim R. Lakhani
The public release of Large Language Models (LLMs) has sparked tremendous interest in how humans will use Artificial Intelligence (AI) to accomplish a variety of tasks. In our study conducted with Boston Consulting Group, a global management consulting firm, we examine...
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Keywords:
Large Language Model;
AI and Machine Learning;
Performance Efficiency;
Performance Improvement
Dell'Acqua, Fabrizio, Edward McFowland III, Ethan Mollick, Hila Lifshitz-Assaf, Katherine C. Kellogg, Saran Rajendran, Lisa Krayer, François Candelon, and Karim R. Lakhani. "Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality." Harvard Business School Working Paper, No. 24-013, September 2023.
- September–October 2023
- Article
Interpretable Matrix Completion: A Discrete Optimization Approach
By: Dimitris Bertsimas and Michael Lingzhi Li
We consider the problem of matrix completion on an n × m matrix. We introduce the problem of interpretable matrix completion that aims to provide meaningful insights for the low-rank matrix using side information. We show that the problem can be...
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Keywords:
Mathematical Methods
Bertsimas, Dimitris, and Michael Lingzhi Li. "Interpretable Matrix Completion: A Discrete Optimization Approach." INFORMS Journal on Computing 35, no. 5 (September–October 2023): 952–965.
- August 2023 (Revised January 2024)
- Supplement
Arla Foods: Data-Driven Decarbonization (A)
By: Michael Parzen, Michael W. Toffel, Amram Migdal and Susan Pinckney
Arla implemented a data-based price incentive system to measure, track, and influence climate friendly changes to reduce CO2 emissions across the world’s fourth largest dairy cooperative.
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Keywords:
Dairy Industry;
Business Earnings;
Earnings Management;
Environmental Accounting;
Agribusiness;
Animal-Based Agribusiness;
Acquisition;
Mergers and Acquisitions;
Decision Making;
Decisions;
Voting;
Environmental Management;
Climate Change;
Environmental Regulation;
Environmental Sustainability;
Green Technology;
Pollution;
Moral Sensibility;
Values and Beliefs;
Financial Strategy;
Price;
Profit;
Revenue;
Food;
Geopolitical Units;
Global Strategy;
Ownership Type;
Cooperative Ownership;
Performance Efficiency;
Performance Evaluation;
Problems and Challenges;
Natural Environment;
Science-Based Business;
Business Strategy;
Commercialization;
Cooperation;
Corporate Strategy;
Food and Beverage Industry;
Agriculture and Agribusiness Industry;
Europe;
United Kingdom;
European Union;
Germany;
Denmark;
Sweden;
Luxembourg;
Belgium
- August 2023 (Revised March 2024)
- Case
Arla Foods: Data-Driven Decarbonization (A)
By: Michael Parzen, Michael W. Toffel, Susan Pinckney and Amram Migdal
The case describes Arla’s history, in particular its climate change mitigation efforts, and how it implemented a price incentive system to motivate individual farms to implement scope 1 greenhouse gas emissions mitigation measures and receive a higher milk price. The...
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Keywords:
Dairy Industry;
Business Earnings;
Agribusiness;
Animal-Based Agribusiness;
Acquisition;
Mergers and Acquisitions;
Decision Making;
Decisions;
Voting;
Environmental Management;
Climate Change;
Environmental Regulation;
Environmental Sustainability;
Green Technology;
Pollution;
Moral Sensibility;
Values and Beliefs;
Financial Strategy;
Price;
Profit;
Revenue;
Food;
Geopolitical Units;
Global Strategy;
Ownership Type;
Cooperative Ownership;
Performance Efficiency;
Performance Evaluation;
Problems and Challenges;
Natural Environment;
Science-Based Business;
Business Strategy;
Commercialization;
Cooperation;
Corporate Strategy;
Food and Beverage Industry;
Agriculture and Agribusiness Industry;
Europe;
United Kingdom;
European Union;
Germany;
Denmark;
Sweden;
Luxembourg;
Belgium
Parzen, Michael, Michael W. Toffel, Susan Pinckney, and Amram Migdal. "Arla Foods: Data-Driven Decarbonization (A)." Harvard Business School Case 624-003, August 2023. (Revised March 2024.)
- August 2023 (Revised January 2024)
- Supplement
Arla Foods: Data-Driven Decarbonization (B)
By: Michael Parzen, Michael W. Toffel, Susan Pinckney and Amram Migdal
The case describes Arla’s history, in particular its climate change mitigation efforts, and how it implemented a price incentive system to motivate individual farms to implement scope 1 greenhouse gas emissions mitigation measures and receive a higher milk price. The...
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Keywords:
Dairy Industry;
Earnings Management;
Environmental Accounting;
Animal-Based Agribusiness;
Mergers and Acquisitions;
Decisions;
Voting;
Climate Change;
Environmental Regulation;
Environmental Sustainability;
Green Technology;
Pollution;
Moral Sensibility;
Values and Beliefs;
Financial Strategy;
Price;
Profit;
Revenue;
Food;
Geopolitical Units;
Cross-Cultural and Cross-Border Issues;
Global Strategy;
Cooperative Ownership;
Performance Efficiency;
Performance Evaluation;
Problems and Challenges;
Natural Environment;
Science-Based Business;
Business Strategy;
Commercial Banking;
Cooperation;
Corporate Strategy;
Food and Beverage Industry;
Agriculture and Agribusiness Industry;
Europe;
United Kingdom;
European Union;
Denmark;
Sweden;
Luxembourg;
Belgium
Parzen, Michael, Michael W. Toffel, Susan Pinckney, and Amram Migdal. "Arla Foods: Data-Driven Decarbonization (B)." Harvard Business School Supplement 624-036, August 2023. (Revised January 2024.)
- August 2023
- Supplement
Reimagining Hindustan Unilever (B)
By: Sunil Gupta and Rachna Tahilyani
In April 2023, as the CEO and MD of Hindustan Unilever (HUL), India’s largest fast-moving consumer goods (FMCG) firm, prepared to hand over the firm’s reins to his successor, he proudly reflected on the last decade. His quest to digitally transform HUL into an...
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- 2023
- Article
Towards Bridging the Gaps between the Right to Explanation and the Right to Be Forgotten
By: Himabindu Lakkaraju, Satyapriya Krishna and Jiaqi Ma
The Right to Explanation and the Right to be Forgotten are two important principles outlined to regulate algorithmic decision making and data usage in real-world applications. While the right to explanation allows individuals to request an actionable explanation for an...
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Keywords:
Analytics and Data Science;
AI and Machine Learning;
Decision Making;
Governing Rules, Regulations, and Reforms
Lakkaraju, Himabindu, Satyapriya Krishna, and Jiaqi Ma. "Towards Bridging the Gaps between the Right to Explanation and the Right to Be Forgotten." Proceedings of the International Conference on Machine Learning (ICML) 40th (2023): 17808–17826.
- 2023
- Working Paper
Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness
By: Neil Menghani, Edward McFowland III and Daniel B. Neill
In this paper, we develop a new criterion, "insufficiently justified disparate impact" (IJDI), for assessing whether recommendations (binarized predictions) made by an algorithmic decision support tool are fair. Our novel, utility-based IJDI criterion evaluates false...
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Menghani, Neil, Edward McFowland III, and Daniel B. Neill. "Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness." Working Paper, June 2023.
- 2023
- Article
Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse
By: Martin Pawelczyk, Teresa Datta, Johannes van-den-Heuvel, Gjergji Kasneci and Himabindu Lakkaraju
As machine learning models are increasingly being employed to make consequential decisions in real-world settings, it becomes critical to ensure that individuals who are adversely impacted (e.g., loan denied) by the predictions of these models are provided with a means...
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Pawelczyk, Martin, Teresa Datta, Johannes van-den-Heuvel, Gjergji Kasneci, and Himabindu Lakkaraju. "Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse." Proceedings of the International Conference on Learning Representations (ICLR) (2023).
- 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...
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Chang, Peter W., Leor Fishman, and Seth Neel. "Feature Importance Disparities for Data Bias Investigations." Working Paper, March 2023.
- March 2023
- Background Note
A Primer on OKRs
By: Suraj Srinivasan and Li-Kuan (Jason) Ni
The OKR framework is a popular goal-setting and strategy execution tool that uses goal setting through “Objectives” and measuring performance using “Key Results” on a periodic basis to measure and drive performance. The OKR framework has been adopted and practiced at...
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Keywords:
Business Organization;
Talent and Talent Management;
Framework;
Corporate Governance;
Goals and Objectives;
Growth and Development;
Growth and Development Strategy;
Growth Management;
Management Analysis, Tools, and Techniques;
Management Practices and Processes;
Management Skills;
Management Systems;
Measurement and Metrics;
Outcome or Result;
Performance Effectiveness;
Performance Evaluation;
Performance Expectations;
Performance Productivity;
Performance Efficiency
Srinivasan, Suraj, and Li-Kuan (Jason) Ni. "A Primer on OKRs." Harvard Business School Background Note 123-081, March 2023.
- February 2023
- Case
Graphic Packaging: Project Cowboy (A)
By: Benjamin C. Esty and E. Scott Mayfield
In July 2019, Graphic Packaging CEO Michael Doss was proposing a $600 million investment in a new machine to produce coated recycled board (CRB), a type of paper packaging used for consumer products (cups, cereal boxes, beverage boxes, etc.) that utilized recycled...
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Keywords:
Capital Budgeting;
Growth Management;
Demand and Consumers;
Duopoly and Oligopoly;
Competitive Strategy;
Competitive Advantage;
Expansion;
Value Creation;
Supply and Industry;
Pulp and Paper Industry;
Manufacturing Industry;
United States;
North America
Esty, Benjamin C., and E. Scott Mayfield. "Graphic Packaging: Project Cowboy (A)." Harvard Business School Case 223-009, February 2023.
- February 2023
- Supplement
Graphic Packaging: Project Cowboy (A) Courseware
By: Benjamin C. Esty and Scott Mayfield
In July 2019, Graphic Packaging CEO Michael Doss was proposing a $600 million investment in a new machine to produce coated recycled board (CRB), a type of paper packaging used for consumer products (cups, cereal boxes, beverage boxes, etc.) that utilized recycled...
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- February 2024
- Article
An Economic Framework for Vaccine Prioritization
By: Mohammad Akbarpour, Eric Budish, Piotr Dworczak and Scott Duke Kominers
We propose an economic framework for determining the optimal allocation of a scarce supply of vaccines that become gradually available during a public health crisis, such as the Covid-19 pandemic. Agents differ in observable and unobservable characteristics, and the...
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Keywords:
Vaccine;
Fairness;
Public Finance;
Public Goods;
Allocation Problems;
Allocative Efficiency;
Allocation Rules;
Social Welfare;
Pandemics;
Inequality;
COVID-19;
COVID-19 Pandemic;
Public Sector;
Resource Allocation;
Market Design;
Marketplace Matching;
Public Administration Industry
Akbarpour, Mohammad, Eric Budish, Piotr Dworczak, and Scott Duke Kominers. "An Economic Framework for Vaccine Prioritization." Quarterly Journal of Economics 139, no. 1 (February 2024): 359–417. (Authors' names are in certified random order.)
- 2023
- Working Paper
Advances in Power-to-Gas Technologies: Cost and Conversion Efficiency
By: Gunther Glenk, Philip Holler and Stefan Reichelstein
Widespread adoption of hydrogen as an energy carrier is widely believed to require continued advances in Power-to-Gas (PtG) technologies. Here we provide a comprehensive assessment of the dynamics of system prices and conversion efficiency for three currently prevalent...
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Keywords:
Clean Tech;
Decarbonization;
Carbon Emissions;
Learning By Doing;
Environment;
Energy;
Environmental Management;
Sustainable Cities;
Price;
Energy Industry;
Utilities Industry;
Industrial Products Industry;
Manufacturing Industry;
Transportation Industry;
Europe;
North America;
South America;
Africa;
Asia
Glenk, Gunther, Philip Holler, and Stefan Reichelstein. "Advances in Power-to-Gas Technologies: Cost and Conversion Efficiency." TRR 266 Accounting for Transparency Working Paper Series, No. 109, December 2022.
- 2022
- Article
Becoming a Learning Organization While Enhancing Performance: The Case of LEGO
By: Thomas Borup Kristensen, Henrik Saabye and Amy Edmondson
Purpose - The purpose of this study is to empirically test how problem-solving lean practices, along with
leaders as learning facilitators in an action learning approach, can be transferred from a production context to a
knowledge work context for the purpose...
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Kristensen, Thomas Borup, Henrik Saabye, and Amy Edmondson. "Becoming a Learning Organization While Enhancing Performance: The Case of LEGO." International Journal of Operations & Production Management 42, no. 13 (2022): 438–481.
- 2022
- Article
Efficiently Training Low-Curvature Neural Networks
By: Suraj Srinivas, Kyle Matoba, Himabindu Lakkaraju and Francois Fleuret
Standard deep neural networks often have excess non-linearity, making them susceptible to issues such as low adversarial robustness and gradient instability. Common methods to address these downstream issues, such as adversarial training, are expensive and often...
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Keywords:
AI and Machine Learning
Srinivas, Suraj, Kyle Matoba, Himabindu Lakkaraju, and Francois Fleuret. "Efficiently Training Low-Curvature Neural Networks." Advances in Neural Information Processing Systems (NeurIPS) (2022).