Publications
Publications
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(9,269)
- Faculty Publications (893)
- June 2023
- Article
When Does Uncertainty Matter? Understanding the Impact of Predictive Uncertainty in ML Assisted Decision Making
By: Sean McGrath, Parth Mehta, Alexandra Zytek, Isaac Lage and Himabindu Lakkaraju
As machine learning (ML) models are increasingly being employed to assist human decision
makers, it becomes critical to provide these decision makers with relevant inputs which can
help them decide if and how to incorporate model predictions into their decision... View Details
- 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
- May 9, 2023
- Article
8 Questions About Using AI Responsibly, Answered
By: Tsedal Neeley
Generative AI tools are poised to change the way every business operates. As your own organization begins strategizing which to use, and how, operational and ethical considerations are inevitable. This article delves into eight of them, including how your organization... View Details
- May 2023
- Article
Do Internal Control Weaknesses Affect Firms' Demand for Financial Skills? Evidence from U.S. Job Postings
By: Janet Gao, Kenneth J. Merkley, Joseph Pacelli and Joseph H. Schroeder
Ineffective internal controls over financial reporting often relates to a lack of qualified personnel with sufficient accounting and technical expertise. In this study, we examine whether firms respond to internal control failures by increasing their demand for... View Details
- April 12, 2023
- Article
Using AI to Adjust Your Marketing and Sales in a Volatile World
By: Das Narayandas and Arijit Sengupta
Why are some firms better and faster than others at adapting their use of customer data to respond to changing or uncertain marketing conditions? A common thread across faster-acting firms is the use of AI models to predict outcomes at various stages of the customer... View Details
- 2024
- Working Paper
Using LLMs for Market Research
By: James Brand, Ayelet Israeli and Donald Ngwe
Large language models (LLMs) have rapidly gained popularity as labor-augmenting
tools for programming, writing, and many other processes that benefit from quick text
generation. In this paper we explore the uses and benefits of LLMs for researchers and
practitioners... View Details
- April 2023 (Revised February 2024)
- Case
AI Wars
By: Andy Wu, Matt Higgins, Miaomiao Zhang and Hang Jiang
In February 2024, the world was looking to Google to see what the search giant and long-time putative technical leader in artificial intelligence (AI) would do to compete in the massively hyped technology of generative AI. Over a year ago, OpenAI released ChatGPT, a... View Details
- April 2023
- Case
Burning the Sails to Save the Ship: The Pilati Family Dilemma
By: Lauren Cohen, Hao Gao, Jiawei Ye and Grace Headinger
Octavian Graf Pilati, rising generation member of an Austrian princely family, prepared to sell the palace his family had held for over three hundred years. In recent years, the Pilati family lands had been leveraged as loan collateral for an international venture that... View Details
- 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
- 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
- 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
- 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
- March 2023 (Revised January 2024)
- Case
Nigeria: Africa's Giant
"Nigeria: Africa’s Giant" delves into the economic development and state building record of Africa’s most populous country. Despite being one of the continent’s largest oil-exporters, Nigeria’s economy has been struggling, and poverty is widespread. The country’s... View Details
- March 2023 (Revised June 2023)
- Case
Pratham 2.0: Sustaining Innovation
By: Brian Trelstad, Samantha Webster and Malini Sen
Pratham is a Mumbai-based nonprofit, which focuses on high-quality, low-cost, and replicable interventions to address gaps in India’s education system. From inception, it has pioneered innovation, from early childhood learning centers to adaptive literacy programs, to... View Details
- 2023
- Chapter
Marketing Through the Machine’s Eyes: Image Analytics and Interpretability
By: Shunyuan Zhang, Flora Feng and Kannan Srinivasan
he growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured data and can inform recommendations for increasing profits and consumer utility—if only the... View Details
- February 2023
- Case
Success Academy Charter Schools
By: Robin Greenwood, Joshua D. Coval, Denise Han, Ruth Page and Dave Habeeb
This stand-alone multimedia case follows the story of Eva Moskowitz and Success Academy, a network of high-performing charter schools in New York City. As a New York City councilor between 1999 and 2006, Moskowitz became frustrated over the inertia and dysfunction in... View Details
- February 2023 (Revised November 2024)
- Case
Ronald Reagan: Changing the World
By: Robert Simons and Shirley Sun
This case traces the rise of Ronald Reagan from small town Illinois to two-term president of the United States. An unlikely candidate for the world’s most powerful job, the case describes the different roles that Reagan filled over his life: radio announcer, Hollywood... View Details
- 2023
- Working Paper
Distributionally Robust Causal Inference with Observational Data
By: Dimitris Bertsimas, Kosuke Imai and Michael Lingzhi Li
We consider the estimation of average treatment effects in observational studies and propose a new framework of robust causal inference with unobserved confounders. Our approach is based on distributionally robust optimization and proceeds in two steps. We first... View Details
- 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
- 2023
- Working Paper
Networking Frictions: Evidence from Entrepreneurial Networking Events in Lomé
By: Stefan Dimitiadis and Rembrand Koning
Spatial proximity between firms plays a crucial role in entrepreneurship by creating knowledge spillovers, enabling resource sharing, and sparking productivity gains. Building on these insights, research has explored whether institutions and organizations can engineer... View Details