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- All HBS Web
(117,451)
- Faculty Publications (37,517)
- April 2023 (Revised September 2023)
- Case
Levels: The Remote, Asynchronous, Deep Work Management System
By: Joseph B. Fuller and George Gonzalez
Levels is a highly innovative startup in the health care space. They intend to revolutionize health by linking behavior—eating, exercise, sleeping, etc.—to changes in metabolism. They believe metabolic health can be managed through careful monitoring of changes in... View Details
Keywords: Applications and Software; Business Startups; Organizational Culture; Management Style; Technology Industry; United States
Fuller, Joseph B., and George Gonzalez. "Levels: The Remote, Asynchronous, Deep Work Management System." Harvard Business School Case 323-069, April 2023. (Revised September 2023.)
- April 2023 (Revised May 2024)
- Case
The Venice Biennale
By: Rohit Deshpandé and Elena Corsi
La Biennale of Venice, which organized festivals in different disciplines, pondered how to remain relevant in front of fading boundaries across arts. View Details
Deshpandé, Rohit, and Elena Corsi. "The Venice Biennale." Harvard Business School Case 523-097, April 2023. (Revised May 2024.)
- April 2023
- Article
A Field Experiment on Subgoal Framing to Boost Volunteering: The Trade-off Between Goal Granularity and Flexibility
By: Aneesh Rai, Marissa A. Sharif, Edward H. Chang, Katherine L. Milkman and Angela L. Duckworth
Research suggests that breaking overarching goals into more granular subgoals is beneficial for goal progress. However, making goals more granular often involves reducing the flexibility provided to complete them, and recent work shows that flexibility can also be... View Details
Rai, Aneesh, Marissa A. Sharif, Edward H. Chang, Katherine L. Milkman, and Angela L. Duckworth. "A Field Experiment on Subgoal Framing to Boost Volunteering: The Trade-off Between Goal Granularity and Flexibility." Journal of Applied Psychology 108, no. 4 (April 2023): 621–634.
- 2023
- Working Paper
Applications or Approvals: What Drives Racial Disparities in the Paycheck Protection Program?
By: Sergey Chernenko, Nathan Kaplan, Asani Sarkar and David S. Scharfstein
We use the 2020 Small Business Credit Survey to study the sources of racial disparities in use of the Paycheck Protection Program (PPP). Black-owned firms are 8.9 percentage points less likely than observably similar white-owned firms to receive PPP loans. About 55% of... View Details
Chernenko, Sergey, Nathan Kaplan, Asani Sarkar, and David S. Scharfstein. "Applications or Approvals: What Drives Racial Disparities in the Paycheck Protection Program?" NBER Working Paper Series, No. 31172, April 2023.
- April 2023
- Article
Are Intermediary Constraints Priced?
By: Wenxin Du, Benjamin Hebert and Amy Wang Huber
Violations of no-arbitrage conditions measure the shadow cost of intermediary constraints. Intermediary asset pricing and intertemporal hedging together imply that the risk of these constraints tightening is priced. We describe a “forward CIP trading strategy” that... View Details
Du, Wenxin, Benjamin Hebert, and Amy Wang Huber. "Are Intermediary Constraints Priced?" Review of Financial Studies 36, no. 4 (April 2023): 1464–1507.
- 2023
- Case
Christiana Figueres and the Collaborative Approach to Negotiating Climate Action
By: James K. Sebenius, Laurence A. Green, Hannah Riley-Bowles, Lara SanPietro and Mina Subramanian
This case study centers on Harvard’s Program on Negotiation 2022 Great Negotiator, Christiana Figueres, and her efforts as Executive Secretary of the United Nations Framework Convention on Climate Change (UNFCCC) to build momentum for, and ultimately pass, the 2015... View Details
Keywords: Climate Change; Negotiation; Environmental Regulation; International Relations; Leadership
Sebenius, James K., Laurence A. Green, Hannah Riley-Bowles, Lara SanPietro, and Mina Subramanian. "Christiana Figueres and the Collaborative Approach to Negotiating Climate Action." Program on Negotiation at Harvard Law School Case, 2023. Electronic.
- 2023
- Working Paper
Corporate Website-based Measures of Firms' Value Drivers
By: Wei Cai, Dennis Campbell and Patrick Ferguson
We develop and validate new text-based measures of firms’ financial and non-financial value drivers. Using the Wayback Machine to access public US firms’ archived websites from 1995-2020, we scrape text from corporate homepages. We use Kaplan and Norton’s (1992)... View Details
Cai, Wei, Dennis Campbell, and Patrick Ferguson. "Corporate Website-based Measures of Firms' Value Drivers." SSRN Working Paper Series, No. 4413808, April 2023.
- April 2023
- Case
Drive Capital: A New Road for Venture
By: Paul A. Gompers and Alicia Dadlani
Founded by two former Sequoia Capital partners, Columbus-Ohio-based Drive Capital’s mission was to build a world-class venture capital firm in the middle of the U.S., an area historically overlooked by VCs. Drive faced early challenges of attracting investors, sourcing... View Details
Keywords: Venture Capital; Business Startups; Entrepreneurship; Investment; Business Strategy; Financial Services Industry; Biotechnology Industry; United States; Ohio
Gompers, Paul A., and Alicia Dadlani. "Drive Capital: A New Road for Venture." Harvard Business School Case 823-056, April 2023.
- 2023
- Article
Estimating Causal Peer Influence in Homophilous Social Networks by Inferring Latent Locations.
By: Edward McFowland III and Cosma Rohilla Shalizi
Social influence cannot be identified from purely observational data on social networks, because such influence is generically confounded with latent homophily, that is, with a node’s network partners being informative about the node’s attributes and therefore its... View Details
Keywords: Causal Inference; Homophily; Social Networks; Peer Influence; Social and Collaborative Networks; Power and Influence; Mathematical Methods
McFowland III, Edward, and Cosma Rohilla Shalizi. "Estimating Causal Peer Influence in Homophilous Social Networks by Inferring Latent Locations." Journal of the American Statistical Association 118, no. 541 (2023): 707–718.
- 2023
- Working Paper
Feature Importance Disparities for Data Bias Investigations
By: Peter W. Chang, Leor Fishman and Seth Neel
It is widely held that one cause of downstream bias in classifiers is bias present in the training data. Rectifying such biases may involve context-dependent interventions such as training separate models on subgroups, removing features with bias in the collection... View Details
Chang, Peter W., Leor Fishman, and Seth Neel. "Feature Importance Disparities for Data Bias Investigations." Working Paper, March 2023.
- April 2023
- Article
Inattentive Inference
By: Thomas Graeber
This paper studies how people infer a state of the world from information structures that include additional, payoff-irrelevant states. For example, learning from a customer review about a product’s quality requires accounting for the reviewer’s otherwise irrelevant... View Details
Graeber, Thomas. "Inattentive Inference." Journal of the European Economic Association 21, no. 2 (April 2023): 560–592.
- Spring 2023
- Article
Incentive Contract Design and Employee-Initiated Innovation: Evidence from the Field
By: Wei Cai, Susanna Gallani and Jee-Eun Shin
This study examines how the design of incentive contracts for tasks defined as workers’ official responsibilities (i.e., standard tasks) influences workers’ propensity to engage in employee-initiated innovation (EII). EII corresponds to innovation activities that are... View Details
Keywords: Employee-initiated Innovation; Contract Design; Rank-and-file; Extra-role Behaviors; Compensation and Benefits; Motivation and Incentives; Innovation and Management
Cai, Wei, Susanna Gallani, and Jee-Eun Shin. "Incentive Contract Design and Employee-Initiated Innovation: Evidence from the Field." Contemporary Accounting Research 40, no. 1 (Spring 2023): 292–323.
- April 2023
- Article
Learning Down to Train Up: Mentors Are More Effective When They Value Insights from Below
By: Ting Zhang, Dan Wang and Adam D. Galinsky
Although mentorship is vital for individual success, potential mentors often view it as a costly burden. To understand what motivates mentors to overcome this barrier and more fully engage with their mentees, we introduce a new construct, learning direction, which... View Details
Keywords: Mentoring; Learning Direction; Interpersonal Communication; Learning; Leadership Development
Zhang, Ting, Dan Wang, and Adam D. Galinsky. "Learning Down to Train Up: Mentors Are More Effective When They Value Insights from Below." Academy of Management Journal 66, no. 2 (April 2023): 604–637.
- April 2023
- Article
On the Privacy Risks of Algorithmic Recourse
By: Martin Pawelczyk, Himabindu Lakkaraju and Seth Neel
As predictive models are increasingly being employed to make consequential decisions, there is a growing emphasis on developing techniques that can provide algorithmic recourse to affected individuals. While such recourses can be immensely beneficial to affected... View Details
Pawelczyk, Martin, Himabindu Lakkaraju, and Seth Neel. "On the Privacy Risks of Algorithmic Recourse." Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) 206 (April 2023).
- April 2023
- Article
Perceptions Related to Engaging in Non-driving Activities in an Automated Vehicle While Commuting: A Text Mining Approach
By: Yilun Xing, Linda Ng Boyle, Raffaella Sadun, John D. Lee, Orit Shaer and Andrew Kun
Automated vehicles (AVs) offer human operators the opportunity to participate in non-driving activities while on the move. In this study, we examined and compared drivers' perception of non-driving activities in two driving modes: highly AVs in the future and current... View Details
Xing, Yilun, Linda Ng Boyle, Raffaella Sadun, John D. Lee, Orit Shaer, and Andrew Kun. "Perceptions Related to Engaging in Non-driving Activities in an Automated Vehicle While Commuting: A Text Mining Approach." Transportation Research Part F: Traffic Psychology and Behaviour 94 (April 2023): 305–320.
- March–April 2023
- Article
Pricing for Heterogeneous Products: Analytics for Ticket Reselling
By: Michael Alley, Max Biggs, Rim Hariss, Charles Herrmann, Michael Lingzhi Li and Georgia Perakis
Problem definition: We present a data-driven study of the secondary ticket market. In particular, we are primarily concerned with accurately estimating price sensitivity for listed tickets. In this setting, there are many issues including endogeneity, heterogeneity in... View Details
Keywords: Price; Demand and Consumers; AI and Machine Learning; Investment Return; Entertainment and Recreation Industry; Sports Industry
Alley, Michael, Max Biggs, Rim Hariss, Charles Herrmann, Michael Lingzhi Li, and Georgia Perakis. "Pricing for Heterogeneous Products: Analytics for Ticket Reselling." Manufacturing & Service Operations Management 25, no. 2 (March–April 2023): 409–426.
- 2023
- Working Paper
PRIMO: Private Regression in Multiple Outcomes
By: Seth Neel
We introduce a new differentially private regression setting we call Private Regression in Multiple Outcomes (PRIMO), inspired the common situation where a data analyst wants to perform a set of l regressions while preserving privacy, where the covariates... View Details
Neel, Seth. "PRIMO: Private Regression in Multiple Outcomes." Working Paper, March 2023.
- April 2023
- Article
Racial Inequality in Work Environments
By: Letian Zhang
This article explores racial stratification in work environments. Inequality scholars have long identified racial disparities in wage and occupational attainment, but workers’ careers and well-being are also shaped by elements of their work environment, including firm... View Details
Keywords: Discrimination; Race; Equality and Inequality; Working Conditions; Personal Development and Career; Organizational Culture
Zhang, Letian. "Racial Inequality in Work Environments." American Sociological Review 88, no. 2 (April 2023): 252–283.
- 2023
- Working Paper
The Limits of Algorithmic Measures of Race in Studies of Outcome Disparities
By: David S. Scharfstein and Sergey Chernenko
We show that the use of algorithms to predict race has significant limitations in measuring and understanding the sources of racial disparities in finance, economics, and other contexts. First, we derive theoretically the direction and magnitude of measurement bias in... View Details
Keywords: Racial Disparity; Paycheck Protection Program; Measurement Error; AI and Machine Learning; Race; Measurement and Metrics; Equality and Inequality; Prejudice and Bias; Forecasting and Prediction; Outcome or Result
Scharfstein, David S., and Sergey Chernenko. "The Limits of Algorithmic Measures of Race in Studies of Outcome Disparities." Working Paper, April 2023.
- March–April 2023
- Article
The New-Collar Workforce
By: Colleen Ammerman, Boris Groysberg and Ginni Rometty
Many workers today are stuck in low-paying jobs, unable to advance simply because they don’t have a bachelor’s degree. At the same time, many companies are desperate for workers and not meeting the diversity goals that could help them perform better while also reducing... View Details
Ammerman, Colleen, Boris Groysberg, and Ginni Rometty. "The New-Collar Workforce." Harvard Business Review 101, no. 2 (March–April 2023): 96–103.