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- 2024
- Working Paper
AI Companions Reduce Loneliness
By: Julian De Freitas, Ahmet K Uguralp, Zeliha O Uguralp and Puntoni Stefano
Chatbots are now able to engage in sophisticated conversations with consumers in the domain of relationships, providing a potential coping solution to widescale societal loneliness. Behavioral research provides little insight into whether these applications are... View Details
De Freitas, Julian, Ahmet K Uguralp, Zeliha O Uguralp, and Puntoni Stefano. "AI Companions Reduce Loneliness." Harvard Business School Working Paper, No. 24-078, June 2024.
- April 2024
- Article
Detecting Routines: Applications to Ridesharing CRM
By: Ryan Dew, Eva Ascarza, Oded Netzer and Nachum Sicherman
Routines shape many aspects of day-to-day consumption. While prior work has established the importance of habits in consumer behavior, little work has been done to understand the implications of routines—which we define as repeated behaviors with recurring, temporal... View Details
Keywords: Ride-sharing; Routine; Machine Learning; Customer Relationship Management; Consumer Behavior; Segmentation
Dew, Ryan, Eva Ascarza, Oded Netzer, and Nachum Sicherman. "Detecting Routines: Applications to Ridesharing CRM." Journal of Marketing Research (JMR) 61, no. 2 (April 2024): 368–392.
- 2024
- Working Paper
Greenlighting Innovative Projects: How Evaluation Format Shapes the Perceived Feasibility of Novel Ideas
By: Jacqueline N. Lane, Tianxi Cai, Michael Menietti, Griffin Weber and Eva C. Guinan
Evaluation of novel projects is essential for scientific and technological advancement. However,
evaluator bias toward a project’s potential can obscure its limitations. This study investigates
evaluation formats by contrasting combined assessments of novelty and... View Details
Lane, Jacqueline N., Tianxi Cai, Michael Menietti, Griffin Weber, and Eva C. Guinan. "Greenlighting Innovative Projects: How Evaluation Format Shapes the Perceived Feasibility of Novel Ideas." Harvard Business School Working Paper, No. 24-064, March 2024.
- March 2024
- Case
Unintended Consequences of Algorithmic Personalization
By: Eva Ascarza and Ayelet Israeli
“Unintended Consequences of Algorithmic Personalization” (HBS No. 524-052) investigates algorithmic bias in marketing through four case studies featuring Apple, Uber, Facebook, and Amazon. Each study presents scenarios where these companies faced public criticism for... View Details
Keywords: Race; Gender; Marketing; Diversity; Customer Relationship Management; Prejudice and Bias; Customization and Personalization; Technology Industry; Retail Industry; United States
Ascarza, Eva, and Ayelet Israeli. "Unintended Consequences of Algorithmic Personalization." Harvard Business School Case 524-052, March 2024.
- February 2024
- Course Overview Note
The Anatomy of Fraud
By: Jonas Heese
Corporate fraud remains a serious problem. Learning how to detect and prevent it, and make better investment decisions, has broad applicability for private and public market investors, as well as for people joining or running companies. This course note describes a... View Details
Heese, Jonas. "The Anatomy of Fraud." Harvard Business School Course Overview Note 124-076, February 2024.
- February 2024
- Article
Conveying and Detecting Listening in Live Conversation
By: Hanne Collins, Julia A. Minson, Ariella S. Kristal and Alison Wood Brooks
Across all domains of human social life, positive perceptions of conversational listening (i.e., feeling heard) predict well-being, professional success, and interpersonal flourishing. But a fundamental question remains: Are perceptions of listening accurate? Prior... View Details
Collins, Hanne, Julia A. Minson, Ariella S. Kristal, and Alison Wood Brooks. "Conveying and Detecting Listening in Live Conversation." Journal of Experimental Psychology: General 153, no. 2 (February 2024): 473–494.
- January 2024
- Case
Post-Wirecard: BaFin under Mark Branson
By: Jonas Heese, Carlota Moniz and Daniela Beyersdorfer
In November 2023, Mark Branson, the head of Germany's Federal Financial Supervisory Authority (BaFin), reflected on the efficacy of the reforms initiated since the Wirecard scandal. BaFin had been discredited after Wirecard’s downfall in 2020. The press had derided it... View Details
Keywords: Accounting; Crime and Corruption; Governing Rules, Regulations, and Reforms; Government Administration; Failure; Trust; Financial Services Industry; Public Administration Industry; Germany
Heese, Jonas, Carlota Moniz, and Daniela Beyersdorfer. "Post-Wirecard: BaFin under Mark Branson." Harvard Business School Case 124-078, January 2024.
- December 2023
- Case
The Valuation Multiple Detective
By: Jonas Heese, Paul M. Healy and Pietro Bonetti
Heese, Jonas, Paul M. Healy, and Pietro Bonetti. "The Valuation Multiple Detective." Harvard Business School Case 124-049, December 2023.
- 2023
- Working Paper
Black-box Training Data Identification in GANs via Detector Networks
By: Lukman Olagoke, Salil Vadhan and Seth Neel
Since their inception Generative Adversarial Networks (GANs) have been popular generative models across images, audio, video, and tabular data. In this paper we study whether given access to a trained GAN, as well as fresh samples from the underlying distribution, if... View Details
Olagoke, Lukman, Salil Vadhan, and Seth Neel. "Black-box Training Data Identification in GANs via Detector Networks." Working Paper, October 2023.
- 2023
- Working Paper
Much Ado About Nothing? Overreaction to Random Regulatory Audits
By: Samuel Antill and Joseph Kalmenovitz
Regulators often audit firms to detect non-compliance. Exploiting a natural experiment in the lobbying industry, we show that firms overreact to audits and this response distorts prices and reduces welfare. Each year, federal regulators audit a random sample of... View Details
Antill, Samuel, and Joseph Kalmenovitz. "Much Ado About Nothing? Overreaction to Random Regulatory Audits." Working Paper, August 2023.
- 2023
- Working Paper
Learning to Use: Stack Overflow and Technology Adoption
By: Daniel Jay Brown and Maria P. Roche
In this paper, we examine the potential impact of Q&A websites on the adoption of technologies.
Using data from Stack Overflow – one of the most popular Q&A websites worldwide
– and implementing an instrumental-variable approach, we find that users whose questions... View Details
Brown, Daniel Jay, and Maria P. Roche. "Learning to Use: Stack Overflow and Technology Adoption." Harvard Business School Working Paper, No. 24-001, July 2023.
- 2024
- Working Paper
Managing Remote Work Quality: Evidence from Auditing Management Systems Standards
By: Ashley Palmarozzo and Michael W. Toffel
Remote work has become more common, providing operational flexibility and productivity
benefits, but questions remain about whether and how it affects work quality. We investigate the
quality effects of remote work in a context in which remote work separates workers... View Details
Keywords: Audit; Auditing; Remote Work; Compliance; Assessment; Environment; Management Systems; Quality Management; Quality Management System; Quality; Operations; Supply Chain Management; Environmental Management; Safety
Palmarozzo, Ashley, and Michael W. Toffel. "Managing Remote Work Quality: Evidence from Auditing Management Systems Standards." Harvard Business School Working Paper, No. 24-002, July 2023. (Revised August 2024.)
- 2023
- Working Paper
Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness
By: Neil Menghani, Edward McFowland III and Daniel B. Neill
In this paper, we develop a new criterion, "insufficiently justified disparate impact" (IJDI), for assessing whether recommendations (binarized predictions) made by an algorithmic decision support tool are fair. Our novel, utility-based IJDI criterion evaluates false... View Details
Menghani, Neil, Edward McFowland III, and Daniel B. Neill. "Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness." Working Paper, June 2023.
- 2023
- Working Paper
Auditing Predictive Models for Intersectional Biases
By: Kate S. Boxer, Edward McFowland III and Daniel B. Neill
Predictive models that satisfy group fairness criteria in aggregate for members of a protected class, but do not guarantee subgroup fairness, could produce biased predictions for individuals at the intersection of two or more protected classes. To address this risk, we... View Details
Boxer, Kate S., Edward McFowland III, and Daniel B. Neill. "Auditing Predictive Models for Intersectional Biases." Working Paper, June 2023.
- 2023
- Article
Provable Detection of Propagating Sampling Bias in Prediction Models
By: Pavan Ravishankar, Qingyu Mo, Edward McFowland III and Daniel B. Neill
With an increased focus on incorporating fairness in machine learning models, it becomes imperative not only to assess and mitigate bias at each stage of the machine learning pipeline but also to understand the downstream impacts of bias across stages. Here we consider... View Details
Ravishankar, Pavan, Qingyu Mo, Edward McFowland III, and Daniel B. Neill. "Provable Detection of Propagating Sampling Bias in Prediction Models." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 8 (2023): 9562–9569. (Presented at the 37th AAAI Conference on Artificial Intelligence (2/7/23-2/14/23) in Washington, DC.)
- 2023
- Article
Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators
By: Benjamin Jakubowski, Siram Somanchi, Edward McFowland III and Daniel B. Neill
Regression discontinuity (RD) designs are widely used to estimate causal effects in the absence of a randomized experiment. However, standard approaches to RD analysis face two significant limitations. First, they require a priori knowledge of discontinuities in... View Details
Jakubowski, Benjamin, Siram Somanchi, Edward McFowland III, and Daniel B. Neill. "Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators." Journal of Machine Learning Research 24, no. 133 (2023): 1–57.
- 2023
- Working Paper
Detecting Structural Breaks in Inflation Trends: A High-Frequency Approach
By: Alberto Cavallo and Gaston Garcia Zavaleta
We combine standard structural-break methods with high-frequency data to identify shifts in inflation trends. We use this approach to study the inflation dynamics of 25 countries from January 2022 to April 2023 and find evidence of a broad-based slowdown in about half... View Details
Cavallo, Alberto, and Gaston Garcia Zavaleta. "Detecting Structural Breaks in Inflation Trends: A High-Frequency Approach." Working Paper, May 2023. (Preliminary draft.)
- March, 2023
- Article
Academic Entrepreneurship: Entrepreneurial Advisors and Their Advisees' Outcomes
By: Maria P. Roche
The transfer of complex knowledge and skills is difficult, often requiring intensive interaction and extensive periods of co-working between a mentor and mentee, which is particularly true in apprenticeship-like settings and on-the-job training. This paper studies a... View Details
Keywords: Entrepreneurship; Higher Education; Training; Personal Development and Career; Knowledge Dissemination
Roche, Maria P. "Academic Entrepreneurship: Entrepreneurial Advisors and Their Advisees' Outcomes." Organization Science 34, no. 2 (March, 2023): 959–986.
- January–February 2023
- Article
Forecasting COVID-19 and Analyzing the Effect of Government Interventions
By: Michael Lingzhi Li, Hamza Tazi Bouardi, Omar Skali Lami, Thomas Trikalinos, Nikolaos Trichakis and Dimitris Bertsimas
We developed DELPHI, a novel epidemiological model for predicting detected cases and deaths in the prevaccination era of the COVID-19 pandemic. The model allows for underdetection of infections and effects of government interventions. We have applied DELPHI across more... View Details
Keywords: COVID-19 Pandemic; Epidemics; Analytics and Data Science; Health Pandemics; AI and Machine Learning; Forecasting and Prediction
Li, Michael Lingzhi, Hamza Tazi Bouardi, Omar Skali Lami, Thomas Trikalinos, Nikolaos Trichakis, and Dimitris Bertsimas. "Forecasting COVID-19 and Analyzing the Effect of Government Interventions." Operations Research 71, no. 1 (January–February 2023): 184–201.
- November–December 2022
- Article
Your Company Needs a Space Strategy. Now.
By: Matthew Weinzierl, Prithwiraj (Raj) Choudhury, Tarun Khanna, Alan MacCormack and Brendan Rosseau
Space is becoming a potential source of value for businesses across a range of sectors, including agriculture, pharmaceuticals, consumer goods, and tourism. To understand what the opportunities are for your company, the authors advise you to consider the four ways in... View Details
Keywords: Space Strategy; Emerging Markets; Natural Resources; Analytics and Data Science; Organizational Change and Adaptation; Adaptation; Competition; Aerospace Industry
Weinzierl, Matthew, Prithwiraj (Raj) Choudhury, Tarun Khanna, Alan MacCormack, and Brendan Rosseau. "Your Company Needs a Space Strategy. Now." Harvard Business Review (November–December 2022): 80–91.