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- June 2024
- Article
Real Growth in Space Manufacturing Output Substantially Exceeds Growth in the Overall Space Economy
By: Tina Highfill and Matthew Weinzierl
Accurately measuring real economic output in the space economy is made difficult by the rapid increase in capabilities and decrease in prices of launch and satellite technologies achieved over the past two decades. Nominal measures of output in space will tend to...
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Highfill, Tina, and Matthew Weinzierl. "Real Growth in Space Manufacturing Output Substantially Exceeds Growth in the Overall Space Economy." Acta Astronautica 219 (June 2024): 236–242.
- 2024
- Working Paper
Anytime-Valid Inference in Linear Models and Regression-Adjusted Causal Inference
By: Michael Lindon, Dae Woong Ham, Martin Tingley and Iavor I. Bojinov
Linear regression adjustment is commonly used to analyze randomized controlled experiments due to its efficiency and robustness against model misspecification. Current testing and interval estimation procedures leverage the asymptotic distribution of such estimators to...
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Lindon, Michael, Dae Woong Ham, Martin Tingley, and Iavor I. Bojinov. "Anytime-Valid Inference in Linear Models and Regression-Adjusted Causal Inference." Harvard Business School Working Paper, No. 24-060, March 2024.
- 2024
- Working Paper
Contributing to Growth? The Role of Open Source Software for Global Startups
By: Nataliya Langburd Wright, Frank Nagle and Shane Greenstein
Does participating in open source software (OSS) communities spur entrepreneurial growth? More
efficiently developing shared code, learning from what the OSS community has developed, and
shaping the direction of massive projects, such as those linked to frameworks...
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Keywords:
Applications and Software;
Open Source Distribution;
Entrepreneurship;
Business Growth and Maturation;
Human Capital;
Valuation;
Corporate Strategy
Wright, Nataliya Langburd, Frank Nagle, and Shane Greenstein. "Contributing to Growth? The Role of Open Source Software for Global Startups." Harvard Business School Working Paper, No. 24-040, January 2024.
- January 2024 (Revised February 2024)
- Case
Data-Driven Denim: Financial Forecasting at Levi Strauss
By: Mark Egan
The case examines Levi Strauss’ journey in implementing machine learning and AI into its financial forecasting process. The apparel company partnered with the IT company Wipro in 2017 to develop a machine learning algorithm that could help Levi Strauss forecast its...
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Keywords:
Investor Relations;
Forecasting;
Machine Learning;
Artificial Intelligence;
Apparel;
Corporate Finance;
Forecasting and Prediction;
AI and Machine Learning;
Apparel and Accessories Industry;
United States
Egan, Mark. "Data-Driven Denim: Financial Forecasting at Levi Strauss." Harvard Business School Case 224-029, January 2024. (Revised February 2024.)
- December 2023 (Revised December 2023)
- Case
Research In Motion: Launching and Scaling the World's First Smartphone Empire (A)
By: Tatiana Sandino and Samuel Grad
In 2005, Research In Motion’s (RIM) BlackBerry smartphone was a sensation. After its launch in 1999, the groundbreaking BlackBerry had captured the hearts and minds of corporate America through its secure wireless email service. The device was so addictive and...
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Keywords:
Business Growth and Maturation;
Decision Choices and Conditions;
Mobile and Wireless Technology;
Technology Adoption;
Innovation and Management;
Technological Innovation;
Business or Company Management;
Management Style;
Product Development;
Sales;
Technology Industry;
United States;
Canada
- December 2023
- Article
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 Technology;
Green Hydrogen;
Carbon Emissions;
Decarbonization;
Learning By Doing;
Environment;
Energy;
Environmental Accounting;
Environmental Management;
Sustainable Cities;
Cost Accounting;
Innovation and Management;
Technology Adoption;
Energy Policy;
Engineering;
Green Technology;
Energy Industry;
Utilities Industry;
Industrial Products Industry;
Manufacturing Industry;
Transportation Industry;
North America;
South America;
Africa;
Europe;
Asia
Glenk, Gunther, Philip Holler, and Stefan Reichelstein. "Advances in Power-to-Gas Technologies: Cost and Conversion Efficiency." Energy & Environmental Science 16, no. 12 (December 2023): 6058–6070.
- 2023
- Working Paper
Can Digitalization Improve Public Services? Evidence from Innovation in Energy Management
By: Robyn C. Meeks, Jacquelyn Pless and Zhenxuan Wang
This paper examines how digitalization impacts public service provision through a study of the U.S. power sector. We exploit the staggered timing of electric utilities’ investments in “smart” meters and find that electricity losses per unit sold decrease by 3.6%. This...
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Keywords:
Electric Utility;
Energy Management;
Smart Meters;
Energy;
Climate Change;
State Ownership;
Private Ownership;
Technology Adoption;
Energy Industry;
Utilities Industry;
United States
Meeks, Robyn C., Jacquelyn Pless, and Zhenxuan Wang. "Can Digitalization Improve Public Services? Evidence from Innovation in Energy Management." MIT CEEPR Working Paper Series, No. 2023-22, December 2023.
- October 2023 (Revised November 2023)
- Case
Recycle & Re-Match: The Future of Soccer Turfs
By: George Serafeim, Lena Duchene and Carlota Moniz
By August 2023, Re-Match, an artificial turf waste-to-value company, had operations in Denmark and the Netherlands and had recycled over 160,000 tons of waste and plastic fiber. With recent capital injection from the VC firm Verdane and a dual revenue business model,...
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Keywords:
Carbon Emissions;
Carbon Abatement;
Sustainability;
Recycling;
Waste Management;
Technology;
Entrepreneurial Management;
Business Growth and Maturation;
Business Model;
Decisions;
Energy Conservation;
Investment Return;
Profit;
Technological Innovation;
Patents;
Growth and Development Strategy;
Market Entry and Exit;
Digital Platforms;
Wastes and Waste Processing;
Business Strategy;
Competition;
Expansion;
Technology Adoption;
Sports;
Environmental Sustainability;
Entrepreneurship;
Green Technology Industry;
Service Industry;
Manufacturing Industry;
Rubber Industry;
Sports Industry;
Denmark;
Netherlands;
France;
United States;
Pennsylvania;
Europe
- 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.
- 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).
- 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).
- November–December 2022
- Article
Can AI Really Help You Sell?: It Can, Depending on When and How You Implement It
By: Jim Dickie, Boris Groysberg, Benson P. Shapiro and Barry Trailer
Many salespeople today are struggling; only 57% of them make their annual quotas, surveys show. One problem is that buying processes have evolved faster than selling processes, and buyers today can access a wide range of online resources that let them evaluate products...
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Dickie, Jim, Boris Groysberg, Benson P. Shapiro, and Barry Trailer. "Can AI Really Help You Sell? It Can, Depending on When and How You Implement It." Harvard Business Review (November–December 2022): 120–129.
- September 2022
- Technical Note
Addressing Social Determinants of Health in the American Landscape
By: Susanna Gallani and Jacob Riegler
Social determinants of health (SDOH) have gained significant attention in recent years. A growing body of research shows that a person’s health is influenced by a large number of non-genetic factors, most of which operate outside the realm of health care and are...
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Keywords:
Socioeconomic Determinants Of Health;
Social Determinants Of Health;
Population Health;
Health;
Health Care and Treatment;
Social Issues;
Health Industry;
Insurance Industry;
Medical Devices and Supplies Industry;
United States
Gallani, Susanna, and Jacob Riegler. "Addressing Social Determinants of Health in the American Landscape." Harvard Business School Technical Note 123-023, September 2022.
- 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...
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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.
- 2023
- Working Paper
Dynamic Pricing, Intertemporal Spillovers, and Efficiency
By: Alexander J. MacKay, Dennis Svartbäck and Anders G. Ekholm
Pricing technology that allows firms to rapidly adjust prices has two potential benefits.
Time-varying prices can respond to high-frequency demand shocks to generate greater revenues,
and they can also be used to smooth out demand to reduce costs. Using data...
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MacKay, Alexander J., Dennis Svartbäck, and Anders G. Ekholm. "Dynamic Pricing, Intertemporal Spillovers, and Efficiency." Harvard Business School Working Paper, No. 23-007, July 2022. (Revised December 2023.)
- March 2022
- Case
Unilever: Remote Work in Manufacturing
By: Prithwiraj Choudhury and Susie L. Ma
In December 2021, Unilever—one of the world’s largest producers of consumer goods—was in the midst of a pilot project to digitize its manufacturing facilities and enable remote work for factory employees. This was possible because of an earlier project to retrofit a...
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Keywords:
Change;
Globalization;
Information Technology;
Technology Adoption;
Human Resources;
Jobs and Positions;
Operations;
Education;
Training;
Manufacturing Industry
Choudhury, Prithwiraj, and Susie L. Ma. "Unilever: Remote Work in Manufacturing." Harvard Business School Case 622-030, March 2022.
- February 2022 (Revised January 2023)
- Case
Huazhu: A Chinese Hotel Giant's Journey of Digital Transformation
By: Feng Zhu, Yulin Fang, Bonnie Yining Cao and Duan Yang
Based in Shanghai, China, Huazhu Group, the world’s third-largest hotel operator, was known for its standardized IT system. It helped the company boost efficiency during the COVID-19 pandemic. Chief Digital Officer Xinxin Liu also faced some longer-term challenges:...
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Keywords:
Hotel Industry;
COVID-19 Pandemic;
Labor;
Business or Company Management;
Emerging Markets;
Information Technology;
Operations;
Strategy;
Digital Transformation;
Accommodations Industry;
China;
United States;
Singapore;
Germany;
Hong Kong
Zhu, Feng, Yulin Fang, Bonnie Yining Cao, and Duan Yang. "Huazhu: A Chinese Hotel Giant's Journey of Digital Transformation." Harvard Business School Case 622-071, February 2022. (Revised January 2023.)