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- All HBS Web
(2,916)
- Faculty Publications (966)
- 2024
- Working Paper
Warnings and Endorsements: Improving Human-AI Collaboration Under Covariate Shift
By: Matthew DosSantos DiSorbo and Kris Ferreira
Problem definition: While artificial intelligence (AI) algorithms may perform well on data that are representative of the training set (inliers), they may err when extrapolating on non-representative data (outliers). These outliers often originate from covariate shift,... View Details
DosSantos DiSorbo, Matthew, and Kris Ferreira. "Warnings and Endorsements: Improving Human-AI Collaboration Under Covariate Shift." Working Paper, February 2024.
- 2024
- Article
Financial Constraints and Short-Term Planning Are Linked to Flood Risk Adaptation Gaps in U.S. Cities
By: Shirley Lu and Anya Nakhmurina
Adaptation is critical in reducing the inevitable impact of climate change. Here we study cities’ adaptation to elevated flood risk by introducing a linguistic measure of adaptation extracted from financial disclosures of 431 US cities over 2013–2020. While cities with... View Details
Keywords: City; Natural Disasters; Climate Change; Adaptation; Risk and Uncertainty; Strategic Planning
Lu, Shirley, and Anya Nakhmurina. "Financial Constraints and Short-Term Planning Are Linked to Flood Risk Adaptation Gaps in U.S. Cities." Art. 43. Communications Earth & Environment 5 (2024).
- January 2024 (Revised May 2024)
- Case
Uncle Nearest: Creating a Legacy
By: Hise Gibson, Archie L. Jones, Nicole Gilmore and Ai-Ling Jamila Malone
Fawn Weaver, as a Black woman and industry outsider in a capital-intensive, highly regulated, competitive and male-dominated spirits industry, successfully overcame numerous obstacles to launch a premium American whiskey brand, Uncle Nearest in 2017, which became the... View Details
Keywords: Advertising; Business Startups; Customer Focus and Relationships; Decisions; Forecasting and Prediction; Age; Ethnicity; Gender; Entrepreneurship; Working Capital; Innovation Leadership; Innovation Strategy; Intellectual Property; Trademarks; Leadership Style; Growth and Development; Growth and Development Strategy; Product Marketing; Product Launch; Marketing Strategy; Mission and Purpose; Organizational Culture; Private Ownership; Performance Effectiveness; Strategic Planning; Problems and Challenges; Prejudice and Bias; Social Issues; Competition; Competitive Strategy; Expansion; Entrepreneurial Finance; Food and Beverage Industry; Tourism Industry; United States; Tennessee; France
Gibson, Hise, Archie L. Jones, Nicole Gilmore, and Ai-Ling Jamila Malone. "Uncle Nearest: Creating a Legacy." Harvard Business School Case 824-047, January 2024. (Revised May 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... View Details
Keywords: Investor Relations; Forecasting; Machine Learning; Artificial Intelligence; Apparel; Corporate Finance; Forecasting and Prediction; AI and Machine Learning; Digital Transformation; 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.)
- 2024
- Working Paper
Lost in Transmission
By: Thomas Graeber, Shakked Noy and Christopher Roth
For many decisions, people rely on information received from others by word of mouth. How does the process of verbal transmission distort economic information? In our experiments, participants listen to audio recordings containing economic forecasts and are paid to... View Details
Keywords: Information Trnasmission; Word Of Mouth; Word-of-Mouth; Narratives; Reliability; Knowledge Sharing; Spoken Communication; Cognition and Thinking
Graeber, Thomas, Shakked Noy, and Christopher Roth. "Lost in Transmission." Harvard Business School Working Paper, No. 24-047, January 2024.
- 2024
- Chapter
Managing, Preserving, and Unlocking Wealth through FinTech
By: Grace Headinger, Lauren Cohen and Zhaoheng Gong
In nearly every generation, a sentiment like Einstein’s has been expressed as a cautionary tale to constrain the development and application of technology. In spite of these calls, technology has time and again proven its utility and ability to improve across and upon... View Details
Headinger, Grace, Lauren Cohen, and Zhaoheng Gong. "Managing, Preserving, and Unlocking Wealth through FinTech." Chap. 11 in Research Handbook on Alternative Finance, edited by Franklin Allen and Meijun Qian, 250–281. Northampton, MA: Edward Elgar Publishing, 2024.
- January–February 2024
- Article
The Challenge of Maintaining Passion for Work over Time: A Daily Perspective on Passion and Emotional Exhaustion
By: Joy Bredehorst, Kai Krautter, Jirs Meuris and Jon M. Jachimowicz
Passion for work is highly coveted, but many employees report struggling to maintain their passion over time. In the current research, we explain the challenge of pursuing passion by conceptualizing passion as an attribute with temporal variation. Viewed through a... View Details
Bredehorst, Joy, Kai Krautter, Jirs Meuris, and Jon M. Jachimowicz. "The Challenge of Maintaining Passion for Work over Time: A Daily Perspective on Passion and Emotional Exhaustion." Organization Science 35, no. 1 (January–February 2024): 364–386.
- 2024
- Working Paper
The Impact of Culture Consistency on Subunit Outcomes
By: Jasmijn Bol, Robert Grasser, Serena Loftus and Tatiana Sandino
We examine the association between subunit culture consistency—defined as the congruence between the organizational values espoused by top management and those perceived and practiced by subunit employees—and subunit outcomes. Using data from 235 subunits of a... View Details
Bol, Jasmijn, Robert Grasser, Serena Loftus, and Tatiana Sandino. "The Impact of Culture Consistency on Subunit Outcomes." Working Paper, December 2024.
- 2023
- Working Paper
New Facts and Data about Professors and Their Research
By: Kyle Myers, Wei Yang Tham, Jerry Thursby, Marie Thursby, Nina Cohodes, Karim R. Lakhani, Rachel Mural and Yilun Xu
We introduce a new survey of professors at roughly 150 of the most research-intensive institutions of higher education in the US. We document seven new features of how research-active professors are compensated, how they spend their time, and how they perceive their... View Details
Keywords: Research; Higher Education; Compensation and Benefits; Measurement and Metrics; Equality and Inequality; Performance Productivity
Myers, Kyle, Wei Yang Tham, Jerry Thursby, Marie Thursby, Nina Cohodes, Karim R. Lakhani, Rachel Mural, and Yilun Xu. "New Facts and Data about Professors and Their Research." Harvard Business School Working Paper, No. 24-036, December 2023.
- 2023
- Working Paper
Debiasing Treatment Effect Estimation for Privacy-Protected Data: A Model Auditing and Calibration Approach
By: Ta-Wei Huang and Eva Ascarza
Data-driven targeted interventions have become a powerful tool for organizations to optimize business outcomes
by utilizing individual-level data from experiments. A key element of this process is the estimation
of Conditional Average Treatment Effects (CATE), which... View Details
Huang, Ta-Wei, and Eva Ascarza. "Debiasing Treatment Effect Estimation for Privacy-Protected Data: A Model Auditing and Calibration Approach." Harvard Business School Working Paper, No. 24-034, December 2023.
- December 2023
- Supplement
Accounting for Loan Losses at JPMorgan Chase: Predicting Credit Costs
By: Jonas Heese and Jung Koo Kang
- 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... View Details
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.
- 2023
- Working Paper
Complexity and Hyperbolic Discounting
By: Benjamin Enke, Thomas Graeber and Ryan Oprea
A large literature shows that people discount financial rewards hyperbolically instead of exponentially. While discounting of money has been questioned as a measure of time preferences, it continues to be highly relevant in empirical practice and predicts a wide range... View Details
Keywords: Hyperbolic Discounting; Present Bias; Bounded Rationality; Cognitive Uncertainty; Behavioral Finance
Enke, Benjamin, Thomas Graeber, and Ryan Oprea. "Complexity and Hyperbolic Discounting." Harvard Business School Working Paper, No. 24-048, February 2024.
- December 2023
- Other Article
Introduction to the Special Section on Business and Climate Change
By: Rajesh Chandy, Glen Dowell, Colin Mayer, Erica Plambeck, George Serafeim, Michael W. Toffel, L. Beril Toktay and Elke Weber
Keywords: Climate Change; Adaptation; Policy; Corporate Social Responsibility and Impact; Innovation and Invention; Forecasting and Prediction
Chandy, Rajesh, Glen Dowell, Colin Mayer, Erica Plambeck, George Serafeim, Michael W. Toffel, L. Beril Toktay, and Elke Weber. "Introduction to the Special Section on Business and Climate Change." Management Science 69, no. 12 (December 2023): 7347–7351.
- November 2023
- Article
Knowledge About the Source of Emotion Predicts Emotion-Regulation Attempts, Strategies, and Perceived Emotion-Regulation Success
By: Yael Millgram, Matthew K. Nock, David D. Bailey and Amit Goldenberg
People’s ability to regulate emotions is crucial to healthy emotional functioning. One overlooked aspect in emotion-regulation research is that knowledge about the source of emotions can vary across situations and individuals, which could impact people’s ability to... View Details
Millgram, Yael, Matthew K. Nock, David D. Bailey, and Amit Goldenberg. "Knowledge About the Source of Emotion Predicts Emotion-Regulation Attempts, Strategies, and Perceived Emotion-Regulation Success." Psychological Science 34, no. 11 (November 2023): 1244–1255.
- 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... View Details
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
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... View Details
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
Save More Today or Tomorrow: The Role of Urgency in Precommitment Design
By: Joseph Reiff, Hengchen Dai, John Beshears, Katherine L. Milkman and Shlomo Benartzi
To encourage farsighted behaviors, past research suggests that marketers may be wise to invite consumers to pre-commit to adopt them “later.” However, the authors propose that people will draw different inferences from different types of pre-commitment offers, and that... View Details
Reiff, Joseph, Hengchen Dai, John Beshears, Katherine L. Milkman, and Shlomo Benartzi. "Save More Today or Tomorrow: The Role of Urgency in Precommitment Design." Journal of Marketing Research (JMR) 60, no. 6 (December 2023): 1095–1113.
- 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... View Details
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... View Details
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).