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- All HBS Web
(2,896)
- Faculty Publications (959)
- 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).
- Working Paper
An AI Method to Score Celebrity Visual Potential from Human Faces
By: Flora Feng, Shunyuan Zhang, Xiao Liu, Kannan Srinivasan and Cait Lamberton
Celebrities have extraordinary abilities to attract and influence others. Predicting celebrity visual potential is important in the domains of business, politics, media, and entertainment. Can we use human faces to predict celebrity visual potential? If so, which... View Details
Feng, Flora, Shunyuan Zhang, Xiao Liu, Kannan Srinivasan, and Cait Lamberton. "An AI Method to Score Celebrity Visual Potential from Human Faces." SSRN Working Paper Series, No. 4071188, November 2023.
- 2023
- Working Paper
Do Active Funds Do Better in What They Trade?
By: Marco Sammon and John J. Shim
We develop two new, simple measures to quantify active fund decisions at the individual position level. The intuition is to separate passive rebalancing induced by flows and position changes from active rebalancing decisions. We find that additive active rebalancing --... View Details
Sammon, Marco, and John J. Shim. "Do Active Funds Do Better in What They Trade?" Working Paper, November 2023.
- 2023
- Working Paper
The Optimal Stock Valuation Ratio
By: Sebastian Hillenbrand and Odhrain McCarthy
Trailing price ratios, such as the price-dividend and the price-earnings ratio, scale prices by trailing cash flow measures. They theoretically contain expected returns, yet, their performance in predicting stock market returns is poor. This is because of an omitted... View Details
Keywords: Price; Investment Return; AI and Machine Learning; Valuation; Cash Flow; Forecasting and Prediction
Hillenbrand, Sebastian, and Odhrain McCarthy. "The Optimal Stock Valuation Ratio." Working Paper, November 2023.
- October 2023
- Teaching Note
Accounting for Loan Losses at JPMorgan Chase: Predicting Credit Costs
By: Jonas Heese and Jung Koo Kang
Teaching Note for HBS Case No. 123-042. View Details
- October 2023 (Revised January 2024)
- Case
Ball: EVA Driving the World's Leading Can Manufacturer (A)
By: Jonas Heese and Susan Pinckney
The case describes Ball’s multi decade history of using Economic Value Added to drive decision making and workforce compensation. In 2016, the company acquired Rexam PLC and became the world’s leading metal beverage container company. Consumer demand for varied... View Details
Keywords: Budgets and Budgeting; Cost Accounting; Financial Reporting; Financial Statements; Buildings and Facilities; Green Building; Mergers and Acquisitions; Customer Satisfaction; Decisions; Forecasting and Prediction; Machinery and Machining; Asset Pricing; Corporate Finance; Capital; Cost; Financial Management; Goods and Commodities; Compensation and Benefits; Executive Compensation; Employee Relationship Management; Goals and Objectives; Resource Allocation; Business Strategy; Corporate Strategy; Food and Beverage Industry; United States; Arizona; California; Texas
Heese, Jonas, and Susan Pinckney. "Ball: EVA Driving the World's Leading Can Manufacturer (A)." Harvard Business School Case 124-002, October 2023. (Revised January 2024.)
- 2023
- Working Paper
Deglobalization and Entrepreneurial Investment: The Natural Experiment of Brexit
By: Elisa Alvarez-Garrido and Juan Alcácer
We seek to gain insight into the consequences of deglobalization on entrepreneurial investment by
analyzing an instance of economic disintegration: the United Kingdom’s exit from the European Union.
Brexit is not only a unique empirical opportunity, a natural... View Details
Keywords: Entrepreneurial Finance; International Relations; Trade; Disruption; Globalized Economies and Regions; United Kingdom
Alvarez-Garrido, Elisa, and Juan Alcácer. "Deglobalization and Entrepreneurial Investment: The Natural Experiment of Brexit." Harvard Business School Working Paper, No. 24-017, August 2023.
- October 2023 (Revised February 2024)
- Technical Note
Design and Evaluation of Targeted Interventions
By: Eva Ascarza and Ta-Wei (David) Huang
Targeted interventions serve as a pivotal tool in business strategy, streamlining decisions for enhanced efficiency and effectiveness. This note delves into two central facets of such interventions: first, the design of potent decision guidelines, or targeting... View Details
Keywords: Marketing; Customer Relationship Management; Analysis; Design; Business Strategy; Retail Industry; Apparel and Accessories Industry; Technology Industry; Financial Services Industry; Telecommunications Industry
Ascarza, Eva, and Ta-Wei (David) Huang. "Design and Evaluation of Targeted Interventions." Harvard Business School Technical Note 524-034, October 2023. (Revised February 2024.)
- 2023
- Working Paper
Are Hospital Quality Indicators Causal?
By: Amitabh Chandra, Maurice Dalton and Douglas O. Staiger
Hospitals play a key role in patient outcomes and spending, but efforts to improve their quality are hindered because we do not know whether hospital quality indicators are causal or biased. We evaluate the validity of commonly used quality indicators, such as... View Details
Keywords: Quality; Health Care and Treatment; Measurement and Metrics; Outcome or Result; Health Industry
Chandra, Amitabh, Maurice Dalton, and Douglas O. Staiger. "Are Hospital Quality Indicators Causal?" NBER Working Paper Series, No. 31789, October 2023.
- October 2023
- Article
Improving Regulatory Effectiveness Through Better Targeting: Evidence from OSHA
By: Matthew S. Johnson, David I. Levine and Michael W. Toffel
We study how a regulator can best target inspections. Our case study is a U.S. Occupational Safety and Health Administration (OSHA) program that randomly allocated some inspections. On average, each inspection averted 2.4 serious injuries (9%) over the next five years.... View Details
Keywords: Safety Regulations; Regulations; Regulatory Enforcement; Machine Learning Models; Safety; Operations; Service Operations; Production; Forecasting and Prediction; Decisions; United States
Johnson, Matthew S., David I. Levine, and Michael W. Toffel. "Improving Regulatory Effectiveness Through Better Targeting: Evidence from OSHA." American Economic Journal: Applied Economics 15, no. 4 (October 2023): 30–67. (Profiled in the Regulatory Review.)
- 2023
- Working Paper
Interest-Rate Risk and Household Portfolios
By: Sylvain Catherine, Max Miller, James Paron and Natasha Sarin
How are households exposed to interest-rate risk? When rates fall, households face lower future expected returns but those holding long-term assets—disproportionately the wealthy and middle-aged—experience capital gains. We study the hedging demand for long-term assets... View Details
Keywords: Portfolio Choice; Social Security; Interest Rates; Investment Portfolio; Equality and Inequality; Welfare
Catherine, Sylvain, Max Miller, James Paron, and Natasha Sarin. "Interest-Rate Risk and Household Portfolios." Working Paper, October 2023. (Reject and Resubmit, American Economic Review.)
- 2023
- Working Paper
The Customer Journey as a Source of Information
By: Nicolas Padilla, Eva Ascarza and Oded Netzer
In the face of heightened data privacy concerns and diminishing third-party data access,
firms are placing increased emphasis on first-party data (1PD) for marketing decisions.
However, in environments with infrequent purchases, reliance on past purchases 1PD... View Details
Keywords: Customer Journey; Privacy; Consumer Behavior; Analytics and Data Science; AI and Machine Learning; Customer Focus and Relationships
Padilla, Nicolas, Eva Ascarza, and Oded Netzer. "The Customer Journey as a Source of Information." Harvard Business School Working Paper, No. 24-035, October 2023. (Revised October 2023.)
- 2023
- Working Paper
The Real Effects of Fair Workweek Laws on Work Schedules: Evidence from Chicago, Los Angeles, and Philadelphia
By: Caleb Kwon and Ananth Raman
Effective in eight jurisdictions and banned in four, Fair Workweek Laws (FWL) aim to increase the predictability and stability of work schedules. Among other requirements, these laws penalize employers for unilaterally adjusting work schedules without providing some... View Details
Kwon, Caleb, and Ananth Raman. "The Real Effects of Fair Workweek Laws on Work Schedules: Evidence from Chicago, Los Angeles, and Philadelphia." Working Paper, October 2023.