Publications
Publications
Show Results For
- All HBS Web
(575)
- Faculty Publications (109)
- March–April 2023
- Article
Market Segmentation Trees
By: Ali Aouad, Adam Elmachtoub, Kris J. Ferreira and Ryan McNellis
Problem definition: We seek to provide an interpretable framework for segmenting users in a population for personalized decision making. Methodology/results: We propose a general methodology, market segmentation trees (MSTs), for learning market... View Details
- February 10, 2023
- Article
The Case for Having a Boring CEO
CEOs who avoid the cameras and minimize drama offer valuable leadership lessons. Their lifestyles aren’t splashed on the pages of magazines. They don’t speak out on every public issue, and their pronouncements are balanced and cautious. Sometimes when I name them as my... View Details
Keywords: CEO; Leadership; Company Management; Personal Brand; Reliability; Humility; Public Opinion
- 2023
- Article
Evaluating Explainability for Graph Neural Networks
By: Chirag Agarwal, Owen Queen, Himabindu Lakkaraju and Marinka Zitnik
As explanations are increasingly used to understand the behavior of graph neural networks (GNNs), evaluating the quality and reliability of GNN explanations is crucial. However, assessing the quality of GNN explanations is challenging as existing graph datasets have no... View Details
Keywords: Analytics and Data Science
- October 25, 2022
- Article
Why Sharing Economic Growth with the Community Is Good Business
By: José A. Tiburcio, Lino Miguel Dias and Robert S. Kaplan
Subsistence dairy ranchers in Central America struggle to stay afloat during the dry season when grass is scarce. Global life sciences company Bayer has launched a program to enable them to produce their own corn silage feed. The results of this program are helping to... View Details
- October 2022 (Revised December 2022)
- Case
SMART: AI and Machine Learning for Wildlife Conservation
By: Brian Trelstad and Bonnie Yining Cao
Spatial Monitoring and Reporting Tool (SMART), a set of software and analytical tools designed for the purpose of wildlife conservation, had demonstrated significant improvements in patrol coverage, with some observed reductions in poaching and contributing to wildlife... View Details
- 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... View Details
- August 2022
- Supplement
Sweet Teez Bakery: Projecting the Dough’s Rise Financial Supplement
By: Emily R. McComb, Mel Martin and Amy Klopfenstein
Abstract: In 2021, the HBS Impact Investment Fund student team met with entrepreneur Teresa Maynard, who had applied for a $25,000 impact investment loan. The students thought the former Harvard Data Scientist’s bakery business, Sweet Teez Bakery, showed promise.... View Details
- August 2022 (Revised November 2024)
- Case
Sweet Teez Bakery: Projecting the Dough's Rise
By: Emily R. McComb, Mel Martin and Amy Klopfenstein
In 2021, the HBS Impact Investment Fund student team met with entrepreneur Teresa Maynard, who had applied for a $25,000 impact investment loan. The students thought the former Harvard Data Scientist’s bakery business, Sweet Teez Bakery, showed promise. Maynard had... View Details
- 2022
- Article
Data Poisoning Attacks on Off-Policy Evaluation Methods
By: Elita Lobo, Harvineet Singh, Marek Petrik, Cynthia Rudin and Himabindu Lakkaraju
Off-policy Evaluation (OPE) methods are a crucial tool for evaluating policies in high-stakes domains such as healthcare, where exploration is often infeasible, unethical, or expensive. However, the extent to which such methods can be trusted under adversarial threats... View Details
- 2022
- Article
Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods.
By: Chirag Agarwal, Marinka Zitnik and Himabindu Lakkaraju
As Graph Neural Networks (GNNs) are increasingly employed in real-world applications, it becomes critical to ensure that the stakeholders understand the rationale behind their predictions. While several GNN explanation methods have been proposed recently, there has... View Details
- 2023
- Working Paper
Uniform Rate Setting and the Deposit Channel
By: Juliane Begenau and Erik Stafford
U.S. banks predominantly use uniform deposit rate setting policies, particularly the largest banks. Uniform rate setting ignores local market concentration, and is therefore inconsistent with the identification strategy used to provide cross-sectional evidence of the... View Details
- March 2022 (Revised May 2022)
- Case
Reclaiming the Land of Purple: Purpl’s Mission to Unlock Finance in Lebanon
By: Lauren Cohen and Grace Headinger
Karl Naim, Co-Founder and CEO of Purpl, embarked on a venture to lower remittance costs for his native Lebanon. Since October 2019, the Lebanese economy had entered a free fall as its banking sector collapsed and large swathes of its population were plunged into... View Details
Keywords: Business Startup; Fintech; Inflation; Deflation; Cross-border Frictions; Remittances; Business Startups; Diasporas; Financial Crisis; Money; Entrepreneurship; Cross-Cultural and Cross-Border Issues; Poverty; Financial Institutions; Banking Industry; Financial Services Industry; Technology Industry; Lebanon
- 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
- Article
Reliable Post hoc Explanations: Modeling Uncertainty in Explainability
By: Dylan Slack, Sophie Hilgard, Sameer Singh and Himabindu Lakkaraju
As black box explanations are increasingly being employed to establish model credibility in high stakes settings, it is important to ensure that these explanations are accurate and reliable. However, prior work demonstrates that explanations generated by... View Details
- Article
Complementarity between Audited Financial Reporting and Voluntary Disclosure: The Case of Former Andersen Clients
By: Richard Frankel, Alon Kalay, Gil Sadka and Yuan Zou
Prior literature presents various perspectives on the role of financial reporting. One view is that mandatory periodic reporting disciplines managers and encourages timely voluntary disclosure. We examine this "confirmation hypothesis" using the shock to financial... View Details
- November 2021
- Article
Determining Variable Costs in the Acute Urolithiasis Cycle of Care Through Time-driven Activity-based Costing
By: Tyler R. McClintock, David F. Friedlander, Aiden Y. Feng, Mahek A. Shah, Daniel J. Pallin, Steven L. Chang, Angela M. Bader, Thomas W. Feeley, Robert S. Kaplan and George E. Haleblian
Objective. To characterize full cycle of care costs for managing an acute ureteral stone using time-driven activity-based costing.
Methods. We defined all phases of care for patients presenting with an acute ureteral stone and built an... View Details
Methods. We defined all phases of care for patients presenting with an acute ureteral stone and built an... View Details
- October 2021 (Revised December 2021)
- Case
Customer-Centric Design with Artificial Intelligence: Commonwealth Bank
By: Karim R. Lakhani, Yael Grushka-Cockayne, Jin Hyun Paik and Steven Randazzo
As Commonwealth Bank (CommBank) CEO Matt Comyn delivered the full financial year results in August 2021 over videoconference, it took less than two minutes for him to make his first mention of the organization's Customer Engagement Engine (CEE), the AI-driven customer... View Details
- September 2021
- Article
Income More Reliably Predicts Frequent Than Intense Happiness
By: Jon M. Jachimowicz, Ruo Mo, Adam Eric Greenberg, Bertus Jeronimus and Ashley V. Whillans
There is widespread consensus that income and subjective well-being are linked, but when and why they are connected is subject to ongoing debate. We draw on prior research that distinguishes between the frequency and intensity of happiness to suggest that higher income... View Details
- February 2021 (Revised March 2022)
- Case
Marvin: A Personalized Telehealth Approach to Mental Health
By: Regina E. Herzlinger, Eshani Sharma, Andrew Nguyen, Thomas Arsenault, Carin-Isabel Knoop and Julia Kelley
More than one third of Americans were said to suffer some type of behavioral health ailment at some point in their lifetime, with many people requiring chronic therapy or intervention. Despite significant clinical needs, access to reliable treatment has been difficult... View Details
- 2021
- Working Paper
Measuring Employment Impact: Applications and Cases
By: Katie Panella and George Serafeim
Applying the Impact-Weighted Accounts Initiative’s employment impact methodology on eight leading companies, we document wide variability in employment impacts as a percentage of salaries paid, ranging between 59 and 80 percent. We identify opportunities for... View Details