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Show Results For
- All HBS Web
(1,111)
- People (1)
- News (206)
- Research (821)
- Events (14)
- Multimedia (1)
- Faculty Publications (240)
- 22 Nov 2023
- Research & Ideas
Humans vs. Machines: Untangling the Tasks AI Can (and Can't) Handle
Knowing when to use artificial intelligence and when to rely on the human mind is a shifting fine line, one delineated by new research that shows considerable benefit and speed from generative AI—if it’s applied to the right tasks. What businesses need to know from a... View Details
- 21 Feb 2018
- News
Study: Use of EHRs Does Not Reduce Administrative Costs
- 2021
- Working Paper
Time Dependence and Preference: Implications for Compensation Structure and Shift Scheduling
By: Doug J. Chung, Byungyeon Kim and Byoung G. Park
This study jointly examines agents’ time dependence—period effects within instantaneous utility—and time preference—behavior on discounting future utility. The study considers the start- and end-of-period effects for time dependence and exponential and hyperbolic... View Details
Keywords: Time Preferences; Present Bias; Hyperbolic Discounting; Compensation; Dynamic Structural Models; Identification; Time Management; Motivation and Incentives; Behavior; Performance; Compensation and Benefits
Chung, Doug J., Byungyeon Kim, and Byoung G. Park. "Time Dependence and Preference: Implications for Compensation Structure and Shift Scheduling." Harvard Business School Working Paper, No. 21-121, April 2021.
- Mar 2021
- Conference Presentation
Descent-to-Delete: Gradient-Based Methods for Machine Unlearning
By: Seth Neel, Aaron Leon Roth and Saeed Sharifi-Malvajerdi
We study the data deletion problem for convex models. By leveraging techniques from convex optimization and reservoir sampling, we give the first data deletion algorithms that are able to handle an arbitrarily long sequence of adversarial updates while promising both... View Details
Neel, Seth, Aaron Leon Roth, and Saeed Sharifi-Malvajerdi. "Descent-to-Delete: Gradient-Based Methods for Machine Unlearning." Paper presented at the 32nd Algorithmic Learning Theory Conference, March 2021.
- 2010
- Working Paper
On the Descriptive Value of Loss Aversion in Decisions under Risk
By: Eyal Ert and Ido Erev
Five studies are presented that explore the assertion that losses loom larger than gains. The first two studies reveal equal sensitivity to gains and losses. For example, half of the participants preferred the gamble "1000 with probability 0.5; -1000 otherwise"... View Details
Ert, Eyal, and Ido Erev. "On the Descriptive Value of Loss Aversion in Decisions under Risk." Harvard Business School Working Paper, No. 10-056, January 2010.
- April 2011
- Article
What Can We Learn from 'Great Negotiations'?
What can one legitimately learn-analytically and/or prescriptively-from detailed historical case studies of "great negotiations," chosen more for their salience than their analytic characteristics or comparability? Taking a number of such cases compiled by Stanton... View Details
Keywords: Learning; International Relations; History; Agreements and Arrangements; Negotiation Process; Conflict and Resolution
Sebenius, James K. "What Can We Learn from 'Great Negotiations'?" Negotiation Journal 27, no. 2 (April 2011).
- September–October 2019
- Article
How Purchase Probability Scales Can Shed Light on Consumer Purchase Intentions
By: Rene Befurt and Alvin J. Silk
Market researchers generally, and survey experts specifically, study consumers to learn about their behavior: What are consumers’ opinions, attitudes, thoughts, and actions at the various stages of the buying process? Especially in litigation cases, these and other... View Details
Befurt, Rene, and Alvin J. Silk. "How Purchase Probability Scales Can Shed Light on Consumer Purchase Intentions." Landslide: Advancing Intellectual Property Law 12, no. 1 (September–October 2019): 51–54.
- 09 Oct 2014
- News
One in four Americans think poor people don’t work hard enough
- 07 Sep 2017
- HBS Seminar
Martin Dimitrov, Tulane
- 2006
- Dissertation
Enterprise Risk Management in Action
By: Anette Mikes
The new Basel regulatory initiatives and a burgeoning risk management literature signify the rise of enterprise risk management (ERM) in the financial services sector. However, very little is known of the roles that risk management plays in organizations and how it... View Details
- Article
Olfactory Cues from Romantic Partners and Strangers Moderate Women's Responses to Stress
By: Marlise Hofer, Hanne Collins, Ashley V. Whillans and Frances Chen
The scent of another person can activate memories, trigger emotions, and spark romantic attraction; however, almost nothing is known about whether and how human scents influence responses to stress. In the current study, 96 women were randomly assigned to smell one of... View Details
Hofer, Marlise, Hanne Collins, Ashley V. Whillans, and Frances Chen. "Olfactory Cues from Romantic Partners and Strangers Moderate Women's Responses to Stress." Journal of Personality and Social Psychology 114, no. 1 (January 2018): 1–9. (Lead Article.)
The International Price of Remote Work
We use data from a large web-based job platform to study how the price of remote work is determined in a globalized labor market. In the platform, workers located around the world compete for jobs that can be done... View Details
- 2018
- Chapter
Behavioral Empirics and Field Experiments
By: Maria Ibanez and Bradley R. Staats
As the study of behavioral operations has continued to grow, an increasing number of researchers are turning to the field (e.g., conducting observational studies or natural or field experiments) to push deeper in order to find the answers to relevant behavioral... View Details
Keywords: Behavioral Operations; Empirical Operations; Empirical Operations Management; Field Experiments; Behavior; Operations; Management; Research
Ibanez, Maria, and Bradley R. Staats. "Behavioral Empirics and Field Experiments." In The Handbook of Behavioral Operations, edited by Karen Donohue, Elena Katok, and Stephen Leider, 121–148. Hoboken, NJ: John Wiley & Sons, 2018.
- 2010
- Article
I May Not Agree With You, but I Trust You: Caring About Social Issues Signals Integrity
By: Julian Zlatev
What characteristics of an individual signal trustworthiness to other people? I propose that individuals who care about contentious social issues signal to observers that they have integrity and thus can be trusted. Critically, this signal conveys trustworthiness... View Details
Zlatev, Julian. "I May Not Agree With You, but I Trust You: Caring About Social Issues Signals Integrity." Psychological Science 30, no. 6 (June 2019): 880–892.
- 2021
- Working Paper
Soliciting Advice Rather Than Feedback Yields More Developmental, Critical, and Actionable Input
By: Hayley Blunden, Jaewon Yoon, Ariella S. Kristal and Ashley V. Whillans
Asking for feedback is a popular way to solicit third-party input at work. However, feedback seeking is only weakly related to performance, and employees often report that the feedback that they receive is unhelpful. Addressing this discrepancy, across six studies... View Details
Extraverts Reap Greater Social Rewards From Passion Because They Express Passion More Frequently and More Diversely
Passion is stereotypically expressed through animated facial expressions, energetic body movements, varied tone, and pitch—and met with interpersonal benefits. However, these capture only a subset of passion expressions that are more common for extraverts.... View Details
- 2018
- Working Paper
Survival of the Fittest: The Impact of the Minimum Wage on Firm Exit
By: Dara Lee Luca and Michael Luca
We study the impact of the minimum wage on firm exit in the restaurant industry, exploiting recent changes in the minimum wage at the city level. We find that the impact of the minimum wage depends on whether a restaurant was already close to the margin of exit.... View Details
Luca, Dara Lee, and Michael Luca. "Survival of the Fittest: The Impact of the Minimum Wage on Firm Exit." Harvard Business School Working Paper, No. 17-088, April 2017. (Revised August 2018.)
- 2022
- Working Paper
Product2Vec: Leveraging Representation Learning to Model Consumer Product Choice in Large Assortments
By: Fanglin Chen, Xiao Liu, Davide Proserpio and Isamar Troncoso
We propose a method, Product2Vec, based on representation learning, that can automatically learn latent product attributes that drive consumer choices, to study product-level competition when the number of products is large. We demonstrate Product2Vec’s... View Details
Chen, Fanglin, Xiao Liu, Davide Proserpio, and Isamar Troncoso. "Product2Vec: Leveraging Representation Learning to Model Consumer Product Choice in Large Assortments." NYU Stern School of Business Research Paper Series, July 2022.
- August 2006
- Article
Predicting Returns with Managerial Decision Variables: Is There a Small-Sample Bias?
By: Malcolm Baker, Ryan Taliaferro and Jeffrey Wurgler
Many studies find that aggregate managerial decision variables, such as aggregate equity issuance, predict stock or bond market returns. Recent research argues that these findings may be driven by an aggregate time-series version of Schultz's (2003, Journal of Finance... View Details
Keywords: Prejudice and Bias; Fairness; Managerial Roles; Management Analysis, Tools, and Techniques; Equity; Bonds; Financial Markets; Investment; Capital Markets; Borrowing and Debt; Investment Return
Baker, Malcolm, Ryan Taliaferro, and Jeffrey Wurgler. "Predicting Returns with Managerial Decision Variables: Is There a Small-Sample Bias?" Journal of Finance 61, no. 4 (August 2006): 1711–1730. (Section V of "Pseudo Market Timing and Predictive Regressions, NBER Working Paper Series, No. 10823, contains additional analyses.)