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All HBS Web
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- Faculty Publications (134)
- October 2022 (Revised August 2023)
- Case
Founders First Capital Partners: An Approach to Capital Access Equity
By: Brian Trelstad, Mel Martin and Amy Klopfenstein
In June 2021, Kim T. Folsom, the founder and CEO of revenue-based financing firm Founders First Capital Partners (FFCP), must decide whether to issue another loan to OnShore Technology Group, an up-and-coming software validation company. FFCP provided revenue-based...
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Keywords:
Finance;
Financial Instruments;
Financing and Loans;
Interest Rates;
Investment Return;
Revenue;
Capital;
Financial Services Industry;
North and Central America;
United States
Trelstad, Brian, Mel Martin, and Amy Klopfenstein. "Founders First Capital Partners: An Approach to Capital Access Equity." Harvard Business School Case 323-013, October 2022. (Revised August 2023.)
- October–December 2022
- Article
Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem
By: Mochen Yang, Edward McFowland III, Gordon Burtch and Gediminas Adomavicius
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, followed...
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Keywords:
Machine Learning;
Econometric Analysis;
Instrumental Variable;
Random Forest;
Causal Inference;
AI and Machine Learning;
Forecasting and Prediction
Yang, Mochen, Edward McFowland III, Gordon Burtch, and Gediminas Adomavicius. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem." INFORMS Journal on Data Science 1, no. 2 (October–December 2022): 138–155.
- September 2022
- Article
Health Externalities and Policy: The Role of Social Preferences
By: Laura Alfaro, Ester Faia, Nora Lamersdorf and Farzad Saidi
Social preferences facilitate the internalization of health externalities, for example by reducing mobility during a pandemic. We test this hypothesis using mobility data from 258 cities worldwide alongside experimentally validated measures of social preferences....
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Keywords:
Social Preferences;
Pandemics;
Mobility;
Health Externalities;
Mitigation Policies;
Health Pandemics;
Cooperation;
Behavior;
Policy
Alfaro, Laura, Ester Faia, Nora Lamersdorf, and Farzad Saidi. "Health Externalities and Policy: The Role of Social Preferences." Management Science 68, no. 9 (September 2022): 6751–6761.
- September–October 2022
- Article
Seeking Purity, Avoiding Pollution: Strategies for Moral Career Building
By: Erin Reid and Lakshmi Ramarajan
This study builds theory on how people construct moral careers. Analyzing interviews with 102 journalists, we show how people build moral careers by seeking jobs that allow them to fulfill both the institution’s moral obligations and their own material aims. We...
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Reid, Erin, and Lakshmi Ramarajan. "Seeking Purity, Avoiding Pollution: Strategies for Moral Career Building." Organization Science 33, no. 5 (September–October 2022): 1909–1937.
- June 2022
- Teaching Note
Bespoken Spirits: Disrupting Distilling
By: Benjamin C. Esty and Daniel Fisher
Teaching Note for HBS Case No. 721-419. On October 7, 2020, Bespoken Spirits publicly announced it had received $2.6 million of seed funding for its “sustainable maturation process,” a process that could produce award-winning whiskeys in just days rather than years...
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- 2022
- Conference Presentation
Towards the Unification and Robustness of Post hoc Explanation Methods
By: Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu and Himabindu Lakkaraju
As machine learning black boxes are increasingly being deployed in critical domains such as healthcare and criminal justice, there has been a growing emphasis on developing techniques for explaining these black boxes in a post hoc manner. In this work, we analyze two...
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Keywords:
AI and Machine Learning
Agarwal, Sushant, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu, and Himabindu Lakkaraju. "Towards the Unification and Robustness of Post hoc Explanation Methods." Paper presented at the 3rd Symposium on Foundations of Responsible Computing (FORC), 2022.
- May 2022
- Article
Embracing Field Studies as a Tool for Learning
Field studies in social psychology tend to focus on validating existing insights. In addition to learning from the laboratory and bringing those insights to the field—which researchers currently favour—we should also conduct field studies that aim to learn in the field...
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Jachimowicz, Jon M. "Embracing Field Studies as a Tool for Learning." Nature Reviews Psychology 1, no. 5 (May 2022): 249–250.
- 2022
- Article
Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis.
By: Martin Pawelczyk, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay and Himabindu Lakkaraju
As machine learning (ML) models become more widely deployed in high-stakes applications, counterfactual explanations have emerged as key tools for providing actionable model explanations in practice. Despite the growing popularity of counterfactual explanations, a...
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Keywords:
Machine Learning Models;
Counterfactual Explanations;
Adversarial Examples;
Mathematical Methods
Pawelczyk, Martin, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay, and Himabindu Lakkaraju. "Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis." Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) 25th (2022).
- Article
Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)
By: Eva Ascarza and Ayelet Israeli
An inherent risk of algorithmic personalization is disproportionate targeting of individuals from certain groups (or demographic characteristics such as gender or race), even when the decision maker does not intend to discriminate based on those “protected”... View Details
Keywords:
Algorithm Bias;
Personalization;
Targeting;
Generalized Random Forests (GRF);
Discrimination;
Customization and Personalization;
Decision Making;
Fairness;
Mathematical Methods
Ascarza, Eva, and Ayelet Israeli. "Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)." e2115126119. Proceedings of the National Academy of Sciences 119, no. 11 (March 8, 2022).
- 2022
- Working Paper
Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments
By: Kosuke Imai and Michael Lingzhi Li
Researchers are increasingly turning to machine learning (ML) algorithms to investigate causal heterogeneity in randomized experiments. Despite their promise, ML algorithms may fail to accurately ascertain heterogeneous treatment effects under practical settings with...
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Imai, Kosuke, and Michael Lingzhi Li. "Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments." Working Paper, March 2022.
- February 2022 (Revised February 2023)
- Case
TikTok in 2020: Super App or Supernova? (Abridged)
By: Jeffrey F. Rayport, Dan Maher and Dan O'Brien
TikTok’s parent company, ByteDance, was launched in 2012 around a simple idea—helping users entertain themselves on their smartphones while on the Beijing Subway. In less than a decade, it had become one of the world’s most valuable private companies, with investors...
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Keywords:
Digital Platform;
Artificial Intelligence;
AI;
Mobile App;
Mobile App Industry;
Mobile and Wireless Technology;
Market Entry and Exit;
Brands and Branding;
Growth and Development Strategy;
China
Rayport, Jeffrey F., Dan Maher, and Dan O'Brien. "TikTok in 2020: Super App or Supernova? (Abridged)." Harvard Business School Case 822-112, February 2022. (Revised February 2023.)
- 2022
- Working Paper
Measuring Time Use in Rural India: Design and Validation of a Low-Cost Survey Module
By: Erica Field, Rohini Pande, Natalia Rigol, Simone Schaner, Elena Stacy and Charity Troyer Moore
Time use data can help us understand individual labor supply choices, especially
for women who often provide unpaid care and home production. Although
enumerator-assisted diary-based time use data collection is suitable for
low-literacy populations, it is costly and...
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Keywords:
Time Use;
Household;
Rural Scope;
Developing Countries and Economies;
Time Management;
Analytics and Data Science;
Surveys
Field, Erica, Rohini Pande, Natalia Rigol, Simone Schaner, Elena Stacy, and Charity Troyer Moore. "Measuring Time Use in Rural India: Design and Validation of a Low-Cost Survey Module." NBER Working Paper Series, No. 29671, January 2022. (Revised September 2022.)
- Article
Adaptive Machine Unlearning
By: Varun Gupta, Christopher Jung, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi and Chris Waites
Data deletion algorithms aim to remove the influence of deleted data points from trained models at a cheaper computational cost than fully retraining those models. However, for sequences of deletions, most prior work in the non-convex setting gives valid guarantees...
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Gupta, Varun, Christopher Jung, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi, and Chris Waites. "Adaptive Machine Unlearning." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
- October 15, 2021
- Article
Virtuous Victims
By: Jillian J. Jordan and Maryam Kouchaki
How do people perceive the moral character of victims? We find, across a range of transgressions, that people frequently see victims of wrongdoing as more moral than non-victims who have behaved identically. Across 15 experiments (total n = 9,355), we document this...
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Keywords:
Moral Judgment;
Restorative Justice;
Punishment;
Compensation;
Person Perception;
Moral Sensibility;
Judgments;
Perception
Jordan, Jillian J., and Maryam Kouchaki. "Virtuous Victims." Science Advances 7, no. 42 (October 15, 2021).
- October 2021
- Case
Sparking Growth at Consumer Reports
Consumer Reports (CR) is a nonprofit organization that traditionally provided independent testing and research on consumer goods. With the need to diversify its audience and revenue streams CR partnered with market research firm Spark No. 9 to identify potential...
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Keywords:
Nonprofit Management;
Innovation;
Entrepreneurship;
Marketing;
Social Media;
Innovation and Management;
Nonprofit Organizations
Wallace, Christina. "Sparking Growth at Consumer Reports." Harvard Business School Case 822-035, October 2021.
- October 2021
- Article
Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach
By: Nicolas Padilla and Eva Ascarza
The success of Customer Relationship Management (CRM) programs ultimately depends on the firm's ability to understand consumers' preferences and precisely capture how these preferences may differ across customers. Only by understanding customer heterogeneity, firms can...
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Keywords:
Customer Management;
Targeting;
Deep Exponential Families;
Probabilistic Machine Learning;
Cold Start Problem;
Customer Relationship Management;
Programs;
Consumer Behavior;
Analysis
Padilla, Nicolas, and Eva Ascarza. "Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach." Journal of Marketing Research (JMR) 58, no. 5 (October 2021): 981–1006.
- September 2021
- Article
Joint Problem-solving Orientation in Fluid Cross-boundary Teams
By: Michaela J. Kerrissey, Anna T. Mayo and Amy C. Edmondson
Using interviews, a national field survey, and an online laboratory study, we have examined teamwork in fluid cross-boundary teams. Across three studies, we qualitatively discovered and quantitatively explored "joint problem-solving orientation" as a new team factor....
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Keywords:
Problem Solving;
Cross-boundary Teams;
Groups and Teams;
Problems and Challenges;
Performance
Kerrissey, Michaela J., Anna T. Mayo, and Amy C. Edmondson. "Joint Problem-solving Orientation in Fluid Cross-boundary Teams." Academy of Management Discoveries 7, no. 3 (September 2021): 381–405.
- August 2021
- Article
Anger Damns the Innocent
By: Katherine DeCelles, Gabrielle Adams, Holly S. Howe and Leslie K. John
False accusations of wrongdoing are common and can have grave consequences. In six studies, we document a worrisome paradox in perceivers’ subjective judgments of a suspect’s guilt. Specifically, we find that laypeople (online panelists; N = 4,983) use suspects’ angry...
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Keywords:
Morality;
Accusations;
Deception;
Guilt;
Affect;
Emotions;
Behavior;
Perception;
Judgments;
Decision Making
DeCelles, Katherine, Gabrielle Adams, Holly S. Howe, and Leslie K. John. "Anger Damns the Innocent." Psychological Science 32, no. 8 (August 2021): 1214–1226.
- August 2021
- Article
Multiple Imputation Using Gaussian Copulas
By: F.M. Hollenbach, I. Bojinov, S. Minhas, N.W. Metternich, M.D. Ward and A. Volfovsky
Missing observations are pervasive throughout empirical research, especially in the social sciences. Despite multiple approaches to dealing adequately with missing data, many scholars still fail to address this vital issue. In this paper, we present a simple-to-use...
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Hollenbach, F.M., I. Bojinov, S. Minhas, N.W. Metternich, M.D. Ward, and A. Volfovsky. "Multiple Imputation Using Gaussian Copulas." Special Issue on New Quantitative Approaches to Studying Social Inequality. Sociological Methods & Research 50, no. 3 (August 2021): 1259–1283. (0049124118799381.)
- August 2021
- Article
Rate-Amplifying Demand and the Excess Sensitivity of Long-Term Rates
By: Samuel G. Hanson, David O. Lucca and Jonathan H. Wright
Long-term nominal interest rates are surprisingly sensitive to high-frequency (daily or monthly) movements in short-term rates. Since 2000, this high-frequency sensitivity has grown even stronger in U.S. data. By contrast, the association between low-frequency changes...
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Hanson, Samuel G., David O. Lucca, and Jonathan H. Wright. "Rate-Amplifying Demand and the Excess Sensitivity of Long-Term Rates." Quarterly Journal of Economics 136, no. 3 (August 2021): 1719–1781.