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- Faculty Publications (347)
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- All HBS Web (1,026)
- Faculty Publications (347)
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- January–February 2012
- Article
A Simple Model Relating Accruals to Risk, and its Implications for the Accrual Anomaly
By: Mozaffar N. Khan
This paper models systematic risk as a function of mean-reverting accruals. When the true abnormal returns are zero, but the true betas are empirically unobserved, the model predicts the anomalous pattern of empirical results on the accrual anomaly: (i) CAPM abnormal... View Details
Khan, Mozaffar N. "A Simple Model Relating Accruals to Risk, and its Implications for the Accrual Anomaly." Journal of Business Finance & Accounting 39, nos. 1-2 (January–February 2012): 35–59.
- Article
Applying Random Coefficient Models to Strategy Research: Identifying and Exploring Firm Heterogeneous Effects
By: Juan Alcácer, Wilbur Chung, Ashton Hawk and Gonçalo Pacheco-de-Almeida
Strategy aims at understanding the differential effects of firms’ actions on performance. However, standard regression models estimate only the average effects of these actions across firms. Our paper discusses how random coefficient models (RCMs) may generate new... View Details
Alcácer, Juan, Wilbur Chung, Ashton Hawk, and Gonçalo Pacheco-de-Almeida. "Applying Random Coefficient Models to Strategy Research: Identifying and Exploring Firm Heterogeneous Effects." Strategy Science 3, no. 3 (September 2018): 481–553.
- 2008
- Article
Warmth and Competence As Universal Dimensions of Social Perception: The Stereotype Content Model and the BIAS Map
By: A. J.C. Cuddy, S. T. Fiske and P. Glick
The stereotype content model (SCM) defines two fundamental dimensions of social perception, warmth and competence, predicted respectively by perceived competition and status. Combinations of warmth and competence generate distinct emotions of admiration, contempt,... View Details
Keywords: Perception; Competency and Skills; Prejudice and Bias; Emotions; Business Model; Behavior; Research; Competition; Status and Position; Cognition and Thinking; Groups and Teams
Cuddy, A. J.C., S. T. Fiske, and P. Glick. "Warmth and Competence As Universal Dimensions of Social Perception: The Stereotype Content Model and the BIAS Map." Advances in Experimental Social Psychology 40 (2008): 61–149.
- Article
Valuing Time Over Money Predicts Happiness After a Major Life Transition: A Preregistered Longitudinal Study of Graduating Students
By: A.V. Whillans, Lucia Macchia and Elizabeth Dunn
How does prioritizing time or money shape major life decisions and subsequent well-being? In a preregistered longitudinal study of approximately 1000 graduating university students, respondents who valued time over money chose more intrinsically rewarding activities... View Details
Keywords: Time Use; Trade-offs; Career Decisions; Time Management; Money; Happiness; Values and Beliefs; Personal Development and Career
Whillans, A.V., Lucia Macchia, and Elizabeth Dunn. "Valuing Time Over Money Predicts Happiness After a Major Life Transition: A Preregistered Longitudinal Study of Graduating Students." Science Advances 5, no. 9 (September 2019).
- Research Summary
Manager Specific Human Capital Investment: A Model of Block Trading and Firm Stability
I develop a model in which workers can undertake specific human capital investments in the firm and in the manager employed by the firm. If the manager leaves the firm, a worker has to decide whether to join her in the new firm or stay in the old firm. In case of... View Details
- February 2025
- Tutorial
Preparing Business Leaders for an Era of Climate Instability: Understanding and Managing Physical Climate Risk
By: Michael W. Toffel and Spencer Glendon
In this compelling video, Spencer Glendon, founder of Probable Futures and Executive Fellow at Harvard Business School, describes the profound implications of climate change for businesses, the economy, and societies around the world. Drawing from his background in... View Details
- 2010
- Working Paper
A New Model of Leadership (PDF File of Keynote Slides)
By: Michael C. Jensen and Allan L. Scherr
In this paper we provide a new definition of leadership that gives organizations and individuals access to new power, performance and accomplishment. In our model leadership consists of four critical elements The creation of a vision for the future that represents a... View Details
- 2021
- Working Paper
Real Credit Cycles
By: Pedro Bordalo, Nicola Gennaioli, Andrei Shleifer and Stephen J. Terry
We incorporate diagnostic expectations, a psychologically founded model of overreaction to news, into a workhorse business cycle model with heterogeneous firms and risky debt. A realistic degree of diagnosticity, estimated from the forecast errors of managers of U.S.... View Details
Bordalo, Pedro, Nicola Gennaioli, Andrei Shleifer, and Stephen J. Terry. "Real Credit Cycles." NBER Working Paper Series, No. 28416, January 2021.
- 2019
- Working Paper
Managing Churn to Maximize Profits
By: Aurelie Lemmens and Sunil Gupta
Customer defection threatens many industries, prompting companies to deploy targeted, proactive customer retention programs and offers. A conventional approach has been to target customers either based on their predicted churn probability, or their responsiveness to a... View Details
Keywords: Churn Management; Defection Prediction; Loss Function; Stochastic Gradient Boosting; Customer Relationship Management; Consumer Behavior; Profit
Lemmens, Aurelie, and Sunil Gupta. "Managing Churn to Maximize Profits." Harvard Business School Working Paper, No. 14-020, September 2013. (Revised December 2019. Forthcoming at Marketing Science.)
- September–October 2020
- Article
Managing Churn to Maximize Profits
By: Aurelie Lemmens and Sunil Gupta
Customer defection threatens many industries, prompting companies to deploy targeted, proactive customer retention programs and offers. A conventional approach has been to target customers either based on their predicted churn probability or their responsiveness to a... View Details
Keywords: Churn Management; Defection Prediction; Loss Function; Stochastic Gradient Boosting; Customer Relationship Management; Consumer Behavior; Profit
Lemmens, Aurelie, and Sunil Gupta. "Managing Churn to Maximize Profits." Marketing Science 39, no. 5 (September–October 2020): 956–973.
- Article
Towards Robust and Reliable Algorithmic Recourse
By: Sohini Upadhyay, Shalmali Joshi and Himabindu Lakkaraju
As predictive models are increasingly being deployed in high-stakes decision making (e.g., loan
approvals), there has been growing interest in post-hoc techniques which provide recourse to affected
individuals. These techniques generate recourses under the assumption... View Details
Keywords: Machine Learning Models; Algorithmic Recourse; Decision Making; Forecasting and Prediction
Upadhyay, Sohini, Shalmali Joshi, and Himabindu Lakkaraju. "Towards Robust and Reliable Algorithmic Recourse." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
- 19 Oct 2010
- Working Paper Summaries
The Impact of Supply Learning on Customer Demand: Model and Estimation Methodology
- April 2014
- Article
The Emergence of 'Us and Them' in 80 Lines of Code: Modeling Group Genesis in Homogeneous Populations
By: Kurt Gray, David G. Rand, Eyal Ert, Kevin Lewis, Steve Hershman and Michael I. Norton
Psychological explanations of group genesis often require population heterogeneity in identity or other characteristics, whether deep (e.g., religion) or superficial (e.g., eye color). We use game-theoretical agent-based models to explore group genesis in homogeneous... View Details
Keywords: Groups and Teams
Gray, Kurt, David G. Rand, Eyal Ert, Kevin Lewis, Steve Hershman, and Michael I. Norton. "The Emergence of 'Us and Them' in 80 Lines of Code: Modeling Group Genesis in Homogeneous Populations." Psychological Science 25, no. 4 (April 2014): 982–990.
- 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).
- March 2020
- Supplement
People Analytics at Teach For America (B)
By: Jeffrey T. Polzer and Julia Kelley
This is a supplement to the People Analytics at Teach For America (A) case. In this supplement, situated one year after the A case, Managing Director Michael Metzger must decide how to apply his team's predictive models generated from the previous year’s data. View Details
Keywords: Analytics; Human Resource Management; Data; Workforce; Hiring; Talent Management; Forecasting; Predictive Analytics; Organizational Behavior; Recruiting; Analytics and Data Science; Forecasting and Prediction; Recruitment; Selection and Staffing; Talent and Talent Management
Polzer, Jeffrey T., and Julia Kelley. "People Analytics at Teach For America (B)." Harvard Business School Supplement 420-086, March 2020.
- July 2023 (Revised July 2023)
- Background Note
Generative AI Value Chain
By: Andy Wu and Matt Higgins
Generative AI refers to a type of artificial intelligence (AI) that can create new content (e.g., text, image, or audio) in response to a prompt from a user. ChatGPT, Bard, and Claude are examples of text generating AIs, and DALL-E, Midjourney, and Stable Diffusion are... View Details
Keywords: AI; Artificial Intelligence; Model; Hardware; Data Centers; AI and Machine Learning; Applications and Software; Analytics and Data Science; Value
Wu, Andy, and Matt Higgins. "Generative AI Value Chain." Harvard Business School Background Note 724-355, July 2023. (Revised July 2023.)
- March 2021
- Article
Bayesian Signatures of Confidence and Central Tendency in Perceptual Judgment
By: Yang Xiang, Thomas Graeber, Benjamin Enke and Samuel Gershman
This paper theoretically and empirically investigates the role of Bayesian noisy cognition in perceptual judgment, focusing on the central tendency effect: the well-known empirical regularity that perceptual judgments are biased towards the center of the... View Details
Xiang, Yang, Thomas Graeber, Benjamin Enke, and Samuel Gershman. "Bayesian Signatures of Confidence and Central Tendency in Perceptual Judgment." Attention, Perception, & Psychophysics (March 2021): 1–11.
- Article
Counterfactual Explanations Can Be Manipulated
By: Dylan Slack, Sophie Hilgard, Himabindu Lakkaraju and Sameer Singh
Counterfactual explanations are useful for both generating recourse and auditing fairness between groups. We seek to understand whether adversaries can manipulate counterfactual explanations in an algorithmic recourse setting: if counterfactual explanations indicate... View Details
Slack, Dylan, Sophie Hilgard, Himabindu Lakkaraju, and Sameer Singh. "Counterfactual Explanations Can Be Manipulated." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
- January 1996
- Article
Real Business Cycle Models and the Forecastable Movements in Output, Hours and Consumption
By: J. J. Rotemberg and Michael Woodford
Keywords: Forecasting and Prediction
Rotemberg, J. J., and Michael Woodford. "Real Business Cycle Models and the Forecastable Movements in Output, Hours and Consumption." American Economic Review 86, no. 1 (January 1996): 71–89.
- 2018
- Working Paper
Bayesian Ensembles of Binary-Event Forecasts: When Is It Appropriate to Extremize or Anti-Extremize?
By: Kenneth C. Lichtendahl Jr., Yael Grushka-Cockayne, Victor Richmond R. Jose and Robert L. Winkler
Many organizations face critical decisions that rely on forecasts of binary events. In these situations, organizations often gather forecasts from multiple experts or models and average those forecasts to produce a single aggregate forecast. Because the average... View Details
Keywords: Forecast Aggregation; Linear Opinion Pool; Generalized Additive Model; Generalized Linear Model; Stacking.; Forecasting and Prediction
Lichtendahl, Kenneth C., Jr., Yael Grushka-Cockayne, Victor Richmond R. Jose, and Robert L. Winkler. "Bayesian Ensembles of Binary-Event Forecasts: When Is It Appropriate to Extremize or Anti-Extremize?" Harvard Business School Working Paper, No. 19-041, October 2018.