Publications
Publications
Show Results For
- All HBS Web
(12,522)
- Faculty Publications (1,670)
- July 2024
- Article
Acceptance of Automated Vehicles Is Lower for Self than Others
By: Stuti Agarwal, Julian De Freitas, Anya Ragnhildstveit and Carey K. Morewedge
Road traffic accidents are the leading cause of death worldwide for people aged 2–59. Nearly all deaths are due to human error. Automated vehicles could reduce mortality risks, traffic congestion, and air pollution of human-driven vehicles. However, their adoption... View Details
- July 2024
- Article
Chatbots and Mental Health: Insights into the Safety of Generative AI
By: Julian De Freitas, Ahmet Kaan Uğuralp, Zeliha Uğuralp and Stefano Puntoni
Chatbots are now able to engage in sophisticated conversations with consumers. Due to the ‘black box’ nature of the algorithms, it is impossible to predict in advance how these conversations will unfold. Behavioral research provides little insight into potential safety... View Details
- July, 2024
- Article
Consumer Protection in an Online World: An Analysis of Occupational Licensing
By: Chiara Farronato, Andrey Fradkin, Bradley Larsen and Erik Brynjolfsson
We study the demand and supply implications of occupational licensing using transaction-level data from a large online platform for home improvement services. We find that demand is more responsive to a professional's reviews than to the professional's... View Details
- July 2024
- Article
Demographic 'Stickiness': The Demographic Identity of Departing Group Members Influences Who Is Chosen to Replace Them
By: Edward H. Chang and Erika Kirgios
People tasked with replacing a departing group member are disproportionately likely to choose a replacement with the same demographic identity, leading to demographic “stickiness” in group composition. We examine this effect in 2,163 U.S. federal judge appointments... View Details
- July–August 2024
- Article
Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals
By: Ta-Wei Huang and Eva Ascarza
Firms are increasingly interested in developing targeted interventions for customers with the best response,
which requires identifying differences in customer sensitivity, typically through the conditional average treatment
effect (CATE) estimation. In theory, to... View Details
- July 2024
- Article
How Artificial Intelligence Constrains Human Experience
By: A. Valenzuela, S. Puntoni, D. Hoffman, N. Castelo, J. De Freitas, B. Dietvorst, C. Hildebrand, Y.E. Huh, R. Meyer, M. Sweeney, S. Talaifar, G. Tomaino and K. Wertenbroch
Many consumption decisions and experiences are digitally mediated. As a consequence, consumer behavior is increasingly the joint product of human psychology and ubiquitous algorithms (Braun et al. 2024; cf. Melumad et al. 2020). The coming of age of Large Language... View Details
- 2024
- Working Paper
How Inflation Expectations De-Anchor: The Role of Selective Memory Cues
By: Nicola Gennaioli, Marta Leva, Raphael Schoenle and Andrei Shleifer
In a model of memory and selective recall, household inflation expectations remain rigid when inflation is anchored but exhibit sharp instability during inflation surges, as similarity prompts retrieval of forgotten high-inflation experiences. Using data from the New... View Details
- 2024
- Working Paper
The Golden Revolving Door
By: Ling Cen, Lauren Cohen, Jing Wu and Fan Zhang
Using both the onset of the US-China trade war in 2018 and the most recent Russia-Ukraine war and associated trade tensions, we show a counterintuitive pattern in global trade. Namely, while the average firm trading with these nations significantly decreases their... View Details
- 2024
- Working Paper
Webmunk: A New Tool for Studying Online Behavior and Digital Platforms
By: Chiara Farronato, Andrey Fradkin and Chris Karr
Understanding the behavior of users online is important for researchers, policymakers, and private companies alike. But observing online behavior and conducting experiments is difficult without direct access to the user base and software of technology companies. We... View Details
- July 2024
- Article
Whether to Apply
By: Katherine B. Coffman, Manuela Collis and Leena Kulkarni
Labor market outcomes depend, in part, upon an individual’s willingness to put herself forward for different opportunities. We use a series of experiments to explore gender differences in willingness to apply for higher return, more challenging work. We find that, in... View Details
- June 2024
- Teaching Note
Skills-First Hiring at IBM
By: Boris Groysberg and Sarah Mehta
Teaching note for “Skills-First Hiring at IBM,” case no. 422-013. View Details
Keywords: Competency and Skills; Experience and Expertise; Talent and Talent Management; Human Resources; Human Capital; Employees; Recruitment; Retention; Selection and Staffing; Jobs and Positions; Job Design and Levels; Job Interviews; Society; Societal Protocols; Technology Industry; United States; New York (state, US)
- July 2024
- Article
Mass General Brigham’s Patient-Reported Outcomes Measurement System: A Decade of Learnings
By: Jason B. Liu, Robert S. Kaplan, David W. Bates, Mario O. Edelen, Rachel C. Sisodia and Andrea L. Pusic
This article describes the strategies that leaders at the Mass General Brigham (MGB) health system have used in launching a standardized patient-reported outcome measure (PROM) collection program in 2012, a major step in the value-based transformation of health care.... View Details
- 2024
- Working Paper
Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization
This paper introduces Incrementality Representation Learning (IRL), a novel multitask representation learning framework that predicts heterogeneous causal effects of marketing interventions. By leveraging past experiments, IRL efficiently designs and targets... View Details
- 2025
- Working Paper
Evaluations Amid Measurement Error: Determining the Optimal Timing for Workplace Interventions
By: Matthew DosSantos DiSorbo, Iavor I. Bojinov and Fiammetta Menchetti
Researchers have embraced factorial experiments to simultaneously evaluate multiple treatments, each with different levels. Typically, in large-scale factorial experiments, the primary objective is identifying the treatment with the largest causal effect, especially... View Details
- 2024
- Working Paper
Advancing Personalization: How to Experiment, Learn & Optimize
By: Aurelie Lemmens, Jason M.T. Roos, Sebastian Gabel, Eva Ascarza, Hernan Bruno, Elea McDonnell Feit, Brett Gordon, Ayelet Israeli, Carl F. Mela and Oded Netzer
Personalization has become the heartbeat of modern marketing. Advances in causal inference and machine learning enable companies to understand how the same marketing action can impact the choices of individual customers differently. This article provides an academic... View Details
- June 2024
- Article
Defining Who You Are by Whom You Serve? Strategies for Prosocial–Professional Identity Integration with Clients
By: Lakshmi Ramarajan and Julie Yen
Many professionals want to both achieve professional success and contribute to society. Yet, in some professional contexts, these aims are in tension because serving elite clients is considered the pinnacle of professional success, but professionals themselves may view... View Details
- June 2024 (Revised August 2024)
- Case
Hospital for Special Surgery: Returning to a New Normal? (A)
By: Robert S. Huckman, Michael Lingzhi Li and Camille Gregory
Early on the morning of April 27, 2020, Justin Oppenheimer stood outside the entrance to the lobby of the Hospital for Special Surgery (HSS) Pavilion Building with mixed emotions. On one hand, Oppenheimer, HSS’ Enterprise Chief Operating Officer and Chief Strategy... View Details
- June 2024
- Article
Information Spillovers in Experience Goods Competition
By: Zhuoqiong Charlie Chen, Christopher Stanton and Catherine Thomas
When experience goods compete, consuming one product can be informative about value for similar untried products. We study a two-period model of duopoly competition in markets that have this feature and where firms can price discriminate between consumers based on... View Details
- June 2024
- Article
Oral History and Business History in Emerging Markets
By: Geoffrey Jones
This article describes the motivation, structure and use of the Creating Emerging Markets (CEM) oral history-based project at the Harvard Business School. The project consists of lengthy interviews with business leaders from emerging markets. By June 2024 183... View Details
- June 2024
- Article
Stereotypes and Belief Updating
By: Katherine B. Coffman, Manuela Collis and Leena Kulkarni
We explore how feedback shapes, and perpetuates, gender gaps in self-assessments. Participants in our experiment take tests of their ability across different domains. We elicit their beliefs of their performance before and after feedback. We find that, even after the... View Details