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(2,816)
- News (443)
- Research (2,159)
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- Faculty Publications (1,378)
Show Results For
-
All HBS Web
(2,816)
- News (443)
- Research (2,159)
- Events (39)
- Multimedia (14)
- Faculty Publications (1,378)
- 27 Feb 2019
- Working Paper Summaries
Judgment Aggregation in Creative Production: Evidence from the Movie Industry
- Research Summary
Working Hard and Investing for an Early Retirement
I examine consumption, leisure, and portfolio choices made over the life-cycle using a model allowing for semi-flexible leisure and an endogenously chosen retirement date. Under a Cobb-Douglas utility specification, I present closed-form expressions for optimal...
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- 2007
- Working Paper
Evidence from Goodwill Non-impairments on the Effects of Unverifiable Fair-Value Accounting
By: Karthik Ramanna and Ross L. Watts
SFAS 142 requires firms to use unverifiable fair-value estimates to determine goodwill impairments. Standard setters suggest managers will use the discretion given by such estimates to convey private information on future cash flows, while agency theory predicts...
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Ramanna, Karthik, and Ross L. Watts. "Evidence from Goodwill Non-impairments on the Effects of Unverifiable Fair-Value Accounting." Harvard Business School Working Paper, No. 08-014, August 2007.
- 04 Oct 2019
- Working Paper Summaries
Soul and Machine (Learning)
- February 2013
- Case
Recorded Future: Analyzing Internet Ideas About What Comes Next
Recorded Future is a "big data" startup company that uses Internet data to make predictions about events, people, and entities. The company primarily serves government intelligence agencies, but has some private sector clients and is considering taking on more. The...
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Keywords:
Big Data;
Analytics;
Internet;
Analytics and Data Science;
Internet and the Web;
Entrepreneurship;
Forecasting and Prediction;
Business Startups;
Information Technology Industry
Davenport, Thomas H. "Recorded Future: Analyzing Internet Ideas About What Comes Next." Harvard Business School Case 613-083, February 2013.
- 11 Dec 2017
- Working Paper Summaries
The Use and Misuse of Patent Data: Issues for Corporate Finance and Beyond
Keywords:
by Josh Lerner and Amit Seru
Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem
Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data,...
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- 2007
- Working Paper
The Ethical Mirage: A Temporal Explanation as to Why We Aren't as Ethical as We Think We Are
By: Ann E. Tenbrunsel, Kristina A. Diekmann, Kimberly A. Wade-Benzoni and Max H. Bazerman
This paper explores the biased perceptions that people hold of their own ethicality. We argue that the temporal trichotomy of prediction, action and evaluation is central to these misperceptions: People predict that they will behave more ethically than they actually...
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Keywords:
Forecasting and Prediction;
Ethics;
Behavior;
Cognition and Thinking;
Perception;
Prejudice and Bias
Tenbrunsel, Ann E., Kristina A. Diekmann, Kimberly A. Wade-Benzoni, and Max H. Bazerman. "The Ethical Mirage: A Temporal Explanation as to Why We Aren't as Ethical as We Think We Are." Harvard Business School Working Paper, No. 08-012, August 2007. (revised January 2009, previously titled "Why We Aren't as Ethical as We Think We Are: A Temporal Explanation.")
- 12 Jan 2009
- Research & Ideas
The Value of a ‘Portable’ Career
Stellar teamwork and star talent will be on display February 1 at the National Football League's annual Super Bowl, in Tampa Bay, Florida. For football fans, the much-awaited Super Bowl is the highlight of the year. Minus the dramatic interceptions and exciting...
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- 2024
- Working Paper
Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization
This paper introduces Incrementality Representation Learning (IRL), a novel multitask representation learning framework that predicts heterogeneous causal effects of marketing interventions. By leveraging past experiments, IRL efficiently designs and targets...
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Keywords:
Heterogeneous Treatment Effect;
Multi-task Learning;
Representation Learning;
Personalization;
Promotion;
Deep Learning;
Field Experiments;
Customer Focus and Relationships;
Customization and Personalization
Huang, Ta-Wei, Eva Ascarza, and Ayelet Israeli. "Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization." Harvard Business School Working Paper, No. 24-076, June 2024.
- January 2010
- Article
The Role of Experience in the Gambler's Fallacy
By: Greg Barron and Stephen Leider
Recent papers have demonstrated that the way people acquire information about a decision problem, by experience or by abstract description, can affect their behavior. We examined the role of experience over time in the emergence of the Gambler's Fallacy in binary...
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Keywords:
Experience and Expertise;
Decision Making;
Forecasting and Prediction;
Knowledge Acquisition;
Outcome or Result;
Game Theory;
Prejudice and Bias
Barron, Greg, and Stephen Leider. "The Role of Experience in the Gambler's Fallacy." Special Issue on Decisions from Experience. Journal of Behavioral Decision Making 23, no. 1 (January 2010).
- 2016
- Working Paper
Through the Grapevine: Network Effects on the Design of Executive Compensation Contracts
By: Susanna Gallani
Effective design of executive compensation contracts involves choosing and weighting performance measures, as well as defining the mix between fixed and incentive-based pay components, with a view to fostering talent retention and goal congruence. The variability in...
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Keywords:
Compensation Design;
Board Interlocks;
Compensation Consultants;
Network Centrality;
Homophily;
Quadratic Assignment Procedure;
Blockholders;
Executive Compensation
Gallani, Susanna. "Through the Grapevine: Network Effects on the Design of Executive Compensation Contracts." Harvard Business School Working Paper, No. 16-019, August 2015. (Revised December, 2016.)
- 02 Jun 2013
- News
On the Job: Don't let shiny job blind you to realities
- 06 Jun 2016
- News
Your Investment Tool Is Failing You
- 03 Oct 2014
- News
Is the Apple Watch the Next Huge, Medium, or Mini Hit?
- 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).
- 05 Jun 2018
- News
HBS Scaling Expert On Finding The Next Bezos, Zuckerberg
- November 2000 (Revised April 2004)
- Case
Airbus A3XX: Developing the World's Largest Commercial Jet (A)
By: Benjamin C. Esty and Michael Kane
In July 2000, Airbus Industries' supervisory board is on the verge of approving a $13 billion investment for the development of a new super jumbo jet known as the A3XX that would seat from 550 to 1,000 passengers. Having secured approximately 20 orders for the new jet,...
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Keywords:
Risk and Uncertainty;
Investment;
Forecasting and Prediction;
Capital Budgeting;
Valuation;
Government and Politics;
Demand and Consumers;
Product Development;
Product Positioning;
Air Transportation Industry;
Manufacturing Industry
Esty, Benjamin C., and Michael Kane. "Airbus A3XX: Developing the World's Largest Commercial Jet (A)." Harvard Business School Case 201-028, November 2000. (Revised April 2004.)
- 2021
- Book
Why Startups Fail: A New Roadmap for Entrepreneurial Success
Why Startups Fail explores entrepreneurial failure, examining its predictable patterns, how to avoid them, and how to cope when failure does occur. Part I looks at three common failure patterns for early-stage startups, illustrating each with an anchor case...
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Eisenmann, Thomas R. Why Startups Fail: A New Roadmap for Entrepreneurial Success. New York: Currency, 2021.