Filter Results
:
(169)
Show Results For
-
All HBS Web
(465)
- Faculty Publications (169)
Show Results For
-
All HBS Web
(465)
- Faculty Publications (169)
←
Page 9 of
169
Results
- Teaching Interest
Interpretability and Explainability in Machine Learning
As machine learning models are increasingly being employed to aid decision makers in high-stakes settings such as healthcare and criminal justice, it is important to ensure that the decision makers correctly understand and consequent trust the functionality of these... View Details
- Forthcoming
- Article
Is Hybrid Work the Best of Both Worlds? Evidence from a Field Experiment
This paper reports causal evidence on how the extent of hybrid work—the number of days worked from home relative to days worked from office—affects employee attitudes and performance. Workers who spent around two days in the office each week on average self-reported...
View Details
Choudhury, Prithwiraj, Tarun Khanna, Christos A. Makridis, and Kyle Schirmann. "Is Hybrid Work the Best of Both Worlds? Evidence from a Field Experiment." Review of Economics and Statistics (forthcoming). (Pre-published online February 9, 2024.)
- Forthcoming
- Article
On the Origins of Restricting Women's Promiscuity
By: Anke Becker
This paper studies the origins and function of customs and norms that intend to keep women from being promiscuous. Using large-scale survey data from more than 100 countries, I test the anthropological theory that a particular form of preindustrial...
View Details
- Research Summary
Overview
By: Isamar Troncoso
Professor Troncoso's research explores problems related to digital marketplaces and AI applications in marketing, and combines toolkits from econometrics, causal inference, and machine learning. She has studied how different platform design choices can lead to...
View Details
- Research Summary
Overview
By: Iavor I. Bojinov
My research focuses on overcoming the methodological and operational challenges of developing data science capabilities, what I call data science operations. Today, within leading digital companies, data science is no longer confined to technical teams but is pervasive...
View Details
- Research Summary
Overview
By: Eva Ascarza
Professor Ascarza’s research primarily focuses on providing researchers and marketers a better understanding of how to manage customer retention so as to reduce churn and increase firm’s profitability. She addresses these issues by building empirical models of customer...
View Details
- Research Summary
Overview
Engaged with field work in East Africa, South Asia, and in several large hybrid organizations in the United States, Professor Whillans places a focus on exploring questions with strong theoretical motivation in the social psychological literature and relevant...
View Details
- Article
Relational Attributions for One’s Own Resilience Predict Compassion for Others
By: Rachel Ruttan, Ting Zhang, Sivahn Barli and Katherine DeCelles
Existing work on attribution theory distinguishes between external and internal attributions (i.e., “I overcame adversity due to luck” vs. “my own effort”). We introduce the construct of relational resilience attributions (i.e., “due to help from other people”) as a...
View Details
Ruttan, Rachel, Ting Zhang, Sivahn Barli, and Katherine DeCelles. "Relational Attributions for One’s Own Resilience Predict Compassion for Others." Journal of Personality and Social Psychology (in press). (Pre-published online January 11, 2024.)
- Research Summary
Why Doesn't Capital Flow from Rich to Poor Countries? An Empirical Investigation (joint with Sebnem Kalemli-Ozcan and Vadym Volosovych)
By: Laura Alfaro
We examine the role of different explanations for the lack of
flows of capital from rich to poor countries -- the Lucas paradox
-- in an empirical framework. Broadly, the theoretical
explanations for this paradox include differences in fundamentals
affecting the...
View Details
- ←
- 9