Publications

Educators

Purchase

27 Nov 2023
Research & Ideas

Voting Democrat or Republican? The Critical Childhood Influence That's Tough to Shake

American political candidates are forecast to spend as much as $12 billion by next November to put ads on airwaves, texts on phones, and signs on lawns. Yet new research from Harvard Business School finds that no amount of money can undo... View Details

Keywords: by Ben Rand

2008
Chapter

Allocating Marketing Resources

By: Sunil Gupta and Thomas J. Steenburgh

Companies spend billions of dollars on marketing every year because it is essential to organic growth. Given these large investments, marketing managers have the responsibility to optimally allocate resources and to demonstrate that their investments generate... View Details

Keywords: Investment Return; Resource Allocation; Marketing; Demand and Consumers; Mathematical Methods

Research Summary

Compensatory Transfers in Collective Decision Making

By: Jerry R. Green

Jerry R. Green is studying mechanisms that can be employed to promote efficient collective decisions while providing justifiable compensation to participants who favor different, less efficient alternatives. This type of decision problem is pervasive in business,... View Details

2021
Working Paper

How Much Should We Trust Staggered Difference-In-Differences Estimates?

By: Andrew C. Baker, David F. Larcker and Charles C.Y. Wang

Difference-in-differences analysis with staggered treatment timing is frequently used to assess the impact of policy changes on corporate outcomes in academic research. However, recent advances in econometric theory show that such designs are likely to be biased in the... View Details

Keywords: Difference In Differences; Staggered Difference-in-differences Designs; Generalized Difference-in-differences; Dynamic Treatment Effects; Mathematical Methods

SSRN

2017
Chapter

Toward Transparent Reporting of Psychological Science

By: Etienne P. LeBel and Leslie K. John

In this chapter we make a case for increased transparency of the methods used to obtain research findings. Although comprehensive reporting facilitates accurate assessment of a paper’s claims, the current reporting norm is secrecy, not openness. We begin by putting... View Details

Keywords: Research; Problems and Challenges

Research Summary

Overview

Professor Goh’s primary research interest is applying mathematical models to real-world problems in health care in order to inform, improve, and enhance medical decision making and health policy. His recent work in this domain focuses on developing new methods for... View Details

Keywords: Uncertainty; Optimization; Inventory Management; Health; Decision Making; Supply Chain

Article

Machine Learning Approaches to Facial and Text Analysis: Discovering CEO Oral Communication Styles

By: Prithwiraj Choudhury, Dan Wang, Natalie A. Carlson and Tarun Khanna

We demonstrate how a novel synthesis of three methods—(1) unsupervised topic modeling of text data to generate new measures of textual variance, (2) sentiment analysis of text data, and (3) supervised ML coding of facial images with a cutting-edge convolutional neural... View Details

Keywords: CEOs; Communication Style; Machine Learning; Spoken Communication; Nonverbal Communication; Personal Characteristics; Analysis; Performance

2008
Working Paper

Allocating Marketing Resources

By: Sunil Gupta and Thomas J. Steenburgh

Marketing is essential for the organic growth of a company. Not surprisingly, firms spend billions of dollars on marketing. Given these large investments, marketing managers have the responsibility to optimally allocate these resources and demonstrate that these... View Details

Keywords: Investment Return; Resource Allocation; Marketing; Demand and Consumers; Mathematical Methods

2019
Working Paper

The Impact of Professionals' Contributions to Online Knowledge Communities on Their Workplace Knowledge Work

By: Hila Lifshitz - Assaf and Frank Nagle

Knowledge work is becoming increasingly challenging as pace of change in the knowledge frontier is increasing. Organizations have created multiple mechanisms to minimize knowledge gaps and increase learning such internal training, mentorship programs as well as... View Details

Keywords: Open Source; Future Of Work; Software Development; Knowledge Work; Online Community; Learning; Knowledge Sharing; Applications and Software; Open Source Distribution; Performance Productivity

2016
Chapter

User-Generated Content and Social Media

By: Michael Luca

This paper documents what economists have learned about user-generated content (UGC) and social media. A growing body of evidence suggests that UGC on platforms ranging from Yelp to Facebook has a large causal impact on economic and social outcomes ranging from... View Details

Keywords: User-generated Content; Crowdsourcing; Design Economics; Internet and the Web; Marketing; Economics; Media; Social Media

2010 - 2010
Conference Presentation

Teams at the Top: Revisiting the Structure and Effects of Strategic Work in Top Management

By: James R. Dillon

This paper examines the usage and effects of small work groups by top management in the course of guiding an organization's strategy process. Reviewing evidence from research literatures on strategy process, strategic leadership, and small groups, I propose that a... View Details

Keywords: Management Teams; Strategy; Leadership; Practice; Management Analysis, Tools, and Techniques

September 2023
Module Note

Live Case Exercise for Financial Reporting

By: Tatiana Sandino and Marshal Herrmann

Harvard Business School employs the case method as a cornerstone of its pedagogy, providing students with opportunities to engage in discussions related to difficult or contentious decisions confronted by real-world organizations. In this “live case,” we depart from... View Details

Keywords: Financial Reporting; Research; Corporate Disclosure

March 2022
Article

Sensitivity Analysis of Agent-based Models: A New Protocol

By: Emanuele Borgonovo, Marco Pangallo, Jan Rivkin, Leonardo Rizzo and Nicolaj Siggelkow

Agent-based models (ABMs) are increasingly used in the management sciences. Though useful, ABMs are often critiqued: it is hard to discern why they produce the results they do and whether other assumptions would yield similar results. To help researchers address such... View Details

Keywords: Agent-based Modeling; Sensitivity Analysis; Design Of Experiments; Total Order Sensitivity Indices; Organizations; Behavior; Decision Making; Mathematical Methods

August 2023
Article

Explaining Machine Learning Models with Interactive Natural Language Conversations Using TalkToModel

By: Dylan Slack, Satyapriya Krishna, Himabindu Lakkaraju and Sameer Singh

Practitioners increasingly use machine learning (ML) models, yet models have become more complex and harder to understand. To understand complex models, researchers have proposed techniques to explain model predictions. However, practitioners struggle to use... View Details

Keywords: AI and Machine Learning; Technological Innovation; Technology Adoption

05 Jul 2006
Working Paper Summaries

Measuring Consumer and Competitive Impact with Elasticity Decompositions

Keywords: by Thomas J. Steenburgh; Advertising

September 2022
Article

In Search of Scholarly Impact

By: Usha C.V Haley, Cary L. Cooper, Andrew J. Hoffman, Tyrone S. Pitsis and Danna Greenberg

This is an introduction to a special issue on the importance and the methods of scholarly impact in real world issues. View Details

Keywords: Research; Higher Education

Purchase

17 Apr 2017
HBS Case

This Turkish Debt Collector Is Customer-friendly

of both their consumers and regulators. “Usually, with debt collection, the object is to dial for dollars—collect as much as you can in the first phone call, and then outsource the work to the legal system,” says Campbell, whose research... View Details

Keywords: by Michael Blanding; Financial Services

November 2021
Article

Gaussian Process Subset Scanning for Anomalous Pattern Detection in Non-iid Data

By: William Herlands, Edward McFowland III, Andrew Gordon Wilson and Daniel B. Neill

Identifying anomalous patterns in real-world data is essential for understanding where, when, and how systems deviate from their expected dynamics. Yet methods that separately consider the anomalousness of each individual data point have low detection power for subtle,... View Details

Keywords: Pattern Detection; Subset Scanning; Gaussian Processes; Mathematical Methods