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All HBS Web
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- Faculty Publications (1,984)
- December 2023
- Case
Microsoft Azure and the Cloud Wars (B)
By: Andy Wu and Matt Higgins
By 2023, the global market for cloud infrastructure had consolidated into a three-horse race. As of Q4 2022, Amazon, Microsoft, and Google collectively accounted for 66% of the global market. AWS had a market share of 33%, Microsoft Azure had 23%, and Google Cloud had...
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- 2023
- Working Paper
Accountability of Corporate Emissions Reduction Targets
By: Xiaoyan Jiang, Shawn Kim and Shirley Lu
Firms are increasingly announcing targets to reduce their carbon emissions, but it is unclear whether firms are held accountable for these targets. In this paper, we examine emissions targets that ended in 2020 to investigate the prevalence of missed targets, how firms...
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Keywords:
Carbon Emissions;
Corporate Disclosure;
Corporate Accountability;
Corporate Social Responsibility and Impact;
Climate Change
Jiang, Xiaoyan, Shawn Kim, and Shirley Lu. "Accountability of Corporate Emissions Reduction Targets." SSRN Working Paper Series, No. 4676649, December 2023.
- 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
- Book
Beyond AI: ChatGPT, Web3, and the Business Landscape of Tomorrow
By: Ken Huang, Yang Wang, Feng Zhu, Xi Chen and Chunxiao Xing
This book explores the transformative potential of ChatGPT, Web3, and their impact on productivity and various industries. It delves into Generative AI (GenAI) and its representative platform ChatGPT, their synergy with Web3, and how they can revolutionize business...
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Huang, Ken, Yang Wang, Feng Zhu, Xi Chen, and Chunxiao Xing, eds. Beyond AI: ChatGPT, Web3, and the Business Landscape of Tomorrow. Springer, 2023.
- December 2023
- Article
Brokerage Relationships and Analyst Forecasts: Evidence from the Protocol for Broker Recruiting
By: Braiden Coleman, Michael Drake, Joseph Pacelli and Brady Twedt
In this study, we offer novel evidence on how the nature of brokerage-client relationships can influence the quality of equity research. We exploit a unique setting provided by the Protocol for Broker Recruiting to examine whether relaxed broker non-compete agreement...
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Keywords:
Brokers;
Analysts;
Forecasts;
Bias;
Protocol;
Investment;
Research;
Forecasting and Prediction
Coleman, Braiden, Michael Drake, Joseph Pacelli, and Brady Twedt. "Brokerage Relationships and Analyst Forecasts: Evidence from the Protocol for Broker Recruiting." Review of Accounting Studies 28, no. 4 (December 2023): 2075–2103.
- December 2023
- Article
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work
By: Mijeong Kwon, Julia Lee Cunningham and Jon M. Jachimowicz
Intrinsic motivation has received widespread attention as a predictor of positive work outcomes, including employees’ prosocial behavior. In the current research, we offer a more nuanced view by proposing that intrinsic motivation does not uniformly increase prosocial...
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Kwon, Mijeong, Julia Lee Cunningham, and Jon M. Jachimowicz. "Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work." Academy of Management Journal 66, no. 6 (December 2023): 1625–1650.
- 2023
- Article
M4: A Unified XAI Benchmark for Faithfulness Evaluation of Feature Attribution Methods across Metrics, Modalities, and Models
By: Himabindu Lakkaraju, Xuhong Li, Mengnan Du, Jiamin Chen, Yekun Chai and Haoyi Xiong
While Explainable Artificial Intelligence (XAI) techniques have been widely studied to explain predictions made by deep neural networks, the way to evaluate the faithfulness of explanation results remains challenging, due to the heterogeneity of explanations for...
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Keywords:
AI and Machine Learning
Lakkaraju, Himabindu, Xuhong Li, Mengnan Du, Jiamin Chen, Yekun Chai, and Haoyi Xiong. "M4: A Unified XAI Benchmark for Faithfulness Evaluation of Feature Attribution Methods across Metrics, Modalities, and Models." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- 2023
- Article
MoPe: Model Perturbation-based Privacy Attacks on Language Models
By: Marvin Li, Jason Wang, Jeffrey Wang and Seth Neel
Recent work has shown that Large Language Models (LLMs) can unintentionally leak sensitive information present in their training data. In this paper, we present Model Perturbations (MoPe), a new method to identify with high confidence if a given text is in the training...
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Li, Marvin, Jason Wang, Jeffrey Wang, and Seth Neel. "MoPe: Model Perturbation-based Privacy Attacks on Language Models." Proceedings of the Conference on Empirical Methods in Natural Language Processing (2023): 13647–13660.
- 2023
- Article
Post Hoc Explanations of Language Models Can Improve Language Models
By: Satyapriya Krishna, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh and Himabindu Lakkaraju
Large Language Models (LLMs) have demonstrated remarkable capabilities in performing complex tasks. Moreover, recent research has shown that incorporating human-annotated rationales (e.g., Chain-of-Thought prompting) during in-context learning can significantly enhance...
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Krishna, Satyapriya, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh, and Himabindu Lakkaraju. "Post Hoc Explanations of Language Models Can Improve Language Models." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- December 2023
- Article
Self-Orienting in Human and Machine Learning
By: Julian De Freitas, Ahmet Uğuralp, Zeliha Uğuralp, Laurie Paul, Joshua B. Tenenbaum and T. Ullman
A current proposal for a computational notion of self is a representation of one’s body in a specific time and place, which includes the recognition of that representation as the agent. This turns self-representation into a process of self-orientation, a challenging...
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De Freitas, Julian, Ahmet Uğuralp, Zeliha Uğuralp, Laurie Paul, Joshua B. Tenenbaum, and T. Ullman. "Self-Orienting in Human and Machine Learning." Nature Human Behaviour 7, no. 12 (December 2023): 2126–2139.
- 2023
- Other Article
The Harvard USPTO Patent Dataset: A Large-Scale, Well-Structured, and Multi-Purpose Corpus of Patent Applications
By: Mirac Suzgun, Luke Melas-Kyriazi, Suproteem K. Sarkar, Scott Duke Kominers and Stuart Shieber
Innovation is a major driver of economic and social development, and information about many kinds of innovation is embedded in semi-structured data from patents and patent applications. Though the impact and novelty of innovations expressed in patent data are difficult...
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Keywords:
USPTO;
Natural Language Processing;
Classification;
Summarization;
Patent Novelty;
Patent Trolls;
Patent Enforceability;
Patents;
Innovation and Invention;
Intellectual Property;
AI and Machine Learning;
Analytics and Data Science
Suzgun, Mirac, Luke Melas-Kyriazi, Suproteem K. Sarkar, Scott Duke Kominers, and Stuart Shieber. "The Harvard USPTO Patent Dataset: A Large-Scale, Well-Structured, and Multi-Purpose Corpus of Patent Applications." Conference on Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track 36 (2023).
- 2023
- Article
Verifiable Feature Attributions: A Bridge between Post Hoc Explainability and Inherent Interpretability
By: Usha Bhalla, Suraj Srinivas and Himabindu Lakkaraju
With the increased deployment of machine learning models in various real-world applications, researchers and practitioners alike have emphasized the need for explanations of model behaviour. To this end, two broad strategies have been outlined in prior literature to...
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Bhalla, Usha, Suraj Srinivas, and Himabindu Lakkaraju. "Verifiable Feature Attributions: A Bridge between Post Hoc Explainability and Inherent Interpretability." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- December 2023
- Article
When Should the Off-Grid Sun Shine at Night? Optimum Renewable Generation and Energy Storage Investments
By: Christian Kaps, Simone Marinesi and Serguei Netessine
Globally, 1.5 billion people live off the grid, their only access to electricity often limited to operationally-expensive fossil fuel generators. Solar power has risen as a sustainable and less costly option, but its generation is variable during the day and...
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Kaps, Christian, Simone Marinesi, and Serguei Netessine. "When Should the Off-Grid Sun Shine at Night? Optimum Renewable Generation and Energy Storage Investments." Management Science 69, no. 12 (December 2023): 7633–7650.
- November 2023
- Case
From Imitation to Innovation: Zongshen Industrial Group (Abridged)
By: Willy Shih and Nancy Dai
Like other small shops based in Chongqing, China, Zongshen Industrial Group started by assembling motorcycles from "standard" parts. The quality of its early products was good enough for rural Chinese buyers, though wealthier consumers usually purchased premium...
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Keywords:
Disruptive Innovation;
Growth and Development Strategy;
Organizational Change and Adaptation;
Competitive Strategy;
Supply Chain;
Product Positioning;
Manufacturing Industry;
Motorcycle Industry;
China
Shih, Willy, and Nancy Dai. "From Imitation to Innovation: Zongshen Industrial Group (Abridged)." Harvard Business School Case 624-056, November 2023.
- November 2023
- Case
Aviva plc: Examining Net Zero
By: Peter Tufano, Brian Trelstad and Matteo Gasparini
The board of Aviva Plc, one of the world’s largest insurers, must review its climate risk exposures and evaluate next steps. Risk experts at the firm have conducted a robust set of analyses prepared for its regulator, the Bank of England, simulating how various climate...
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- 2023
- Working Paper
Coordinated R&D Programs and the Creation of New Industries
By: Daniel P. Gross and Maria P. Roche
Government R&D programs have a long history in supporting industry development, yet their impacts are often overlooked in strategy research. We examine how a large, coordinated, government-funded effort to develop radar in World War II spawned a new high-tech industry....
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Keywords:
Research and Development;
Policy;
Business and Government Relations;
Technological Innovation;
Collaborative Innovation and Invention
Gross, Daniel P., and Maria P. Roche. "Coordinated R&D Programs and the Creation of New Industries." Harvard Business School Working Paper, No. 24-027, April 2023.
- November 2023
- Case
Copilot(s): Generative AI at Microsoft and GitHub
This case tells the story of Microsoft’s 2018 acquisition of GitHub and the subsequent launch of GitHub Copilot, a tool that uses generative artificial intelligence to suggest snippets of code to software developers in real time. Set in late 2021, when Copilot was...
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Keywords:
Business Ventures;
Strategy;
AI and Machine Learning;
Applications and Software;
Product Launch;
Information Technology Industry;
Technology Industry;
Web Services Industry;
United States;
California
Nagle, Frank, Shane Greenstein, Maria P. Roche, Nataliya Langburd Wright, and Sarah Mehta. "Copilot(s): Generative AI at Microsoft and GitHub." Harvard Business School Case 624-010, November 2023.
- 2023
- Working Paper
Learning by Investing: Entrepreneurial Spillovers from Venture Capital
By: Josh Lerner, Jinlin Li and Tong Liu
This paper studies how investing in venture capital (VC) affects the entrepreneurial outcomes of individual limited partners (LPs). Using comprehensive administrative data on entrepreneurial activities and VC fundraising and investments in China, we first document that...
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Lerner, Josh, Jinlin Li, and Tong Liu. "Learning by Investing: Entrepreneurial Spillovers from Venture Capital." Harvard Business School Working Paper, No. 24-029, November 2023.
- November 2023
- Background Note
Corporate Climate Targets
By: Willy C. Shih, Michael W. Toffel and Kelsey Carter
Companies that are addressing climate change by mitigating their greenhouse gas emissions often set reduction targets. This note describes several types of widely used carbon reduction targets, including carbon neutral, science based, net zero, real zero, and carbon...
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Keywords:
Corporate Sustainability;
Environmental Strategy;
Climate Risk;
Target-setting;
Climate Change;
Environmental Sustainability;
Corporate Accountability;
Policy;
Measurement and Metrics;
Strategic Planning;
Social Issues;
Corporate Social Responsibility and Impact
Shih, Willy C., Michael W. Toffel, and Kelsey Carter. "Corporate Climate Targets." Harvard Business School Background Note 624-041, November 2023.
- 2023
- Working Paper
What Do Impact Investors Do Differently?
In recent years, impact investors – private investors who seek to generate simultaneously financial and social returns – have attracted intense interest and controversy. We analyze a novel, comprehensive data set of impact and traditional investors to assess how the...
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Keywords:
ESG;
Socially Responsible Investing;
Investment Decisions;
Public Goods;
Impact Investment;
Investment;
Private Equity;
Venture Capital
Cole, Shawn, Leslie Jeng, Josh Lerner, Natalia Rigol, and Benjamin N. Roth. "What Do Impact Investors Do Differently?" Harvard Business School Working Paper, No. 24-028, November 2023. (Reject and Resubmit, Journal of Financial Economics.)