Publications
Publications
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- All HBS Web
(68)
- Faculty Publications (20)
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- 2024
- Working Paper
Charting (and Updating) the Path: A Bayesian Perspective on Entrepreneurial Learning
This chapter explores two distinct modes of entrepreneurial learning: assessing
venture viability and choosing between alternative development paths. It introduces
a framework for decomposing venture viability into technological feasibility, commercial
potential and... View Details
- December 2023
- Article
When Should the Off-Grid Sun Shine at Night? Optimum Renewable Generation and Energy Storage Investments
By: Christian Kaps, Simone Marinesi and Serguei Netessine
Globally, 1.5 billion people live off the grid, their only access to electricity often limited to operationally-expensive fossil fuel generators. Solar power has risen as a sustainable and less costly option, but its generation is variable during the day and... View Details
- 2023
- Working Paper
How People Use Statistics
By: Pedro Bordalo, John J. Conlon, Nicola Gennaioli, Spencer Yongwook Kwon and Andrei Shleifer
We document two new facts about the distributions of answers in famous statistical problems: they are i) multi-modal and ii) unstable with respect to irrelevant changes in the problem. We offer a model in which, when solving a problem, people represent each hypothesis... View Details
- 2021
- Working Paper
Cognitive Biases: Mistakes or Missing Stakes?
By: Benjamin Enke, Uri Gneezy, Brian Hall, David Martin, Vadim Nelidov, Theo Offerman and Jeroen van de Ven
Despite decades of research on heuristics and biases, empirical evidence on the effect of large incentives—as present in relevant economic decisions—on cognitive biases is scant. This paper tests the effect of incentives on four widely documented biases: base rate... View Details
- Article
Memory and Representativeness
By: Pedro Bordalo, Katherine Baldiga Coffman, Nicola Gennaioli, Frederik Schwerter and Andrei Shleifer
We explore the idea that judgment by representativeness reflects the workings of episodic memory, especially interference. In a new laboratory experiment on cued recall, participants are shown two groups of images with different distributions of colors. We find that i)... View Details
- October 2020 (Revised May 2023)
- Exercise
SenseAim Technologies: Pricing to Win
By: Elie Ofek, Eyal Biyalogorsky, Marco Bertini and Oded Koenigsberg
This exercise serves to help students understand the proper role and use of costs in a firm’s pricing decisions. The exercise is designed such that the learning of students evolves across a classroom session, starting from understanding which costs are relevant when... View Details
- Article
Signaling When Nobody Is Watching: A Reputation Heuristics Account of Outrage and Punishment in One-shot Anonymous Interactions
By: Jillian J. Jordan and David G. Rand
Moralistic punishment can confer reputation benefits by signaling trustworthiness to observers. However, why do people punish even when nobody is watching? We argue that people often rely on the heuristic that reputation is typically at stake, such that reputation... View Details
Keywords: Signaling; Morality; Trustworthiness; Anger; Third-party Punishment; Moral Sensibility; Behavior; Trust; Reputation
- Article
How to Use Heuristics for Differential Privacy
By: Seth Neel, Aaron Leon Roth and Zhiwei Steven Wu
We develop theory for using heuristics to solve computationally hard problems in differential privacy. Heuristic approaches have enjoyed tremendous success in machine learning, for which performance can be empirically evaluated. However, privacy guarantees cannot be... View Details
- 2024
- Working Paper
The Revised-Is-Quality Heuristic: Why Consumers Prefer Products Labeled as Revised
By: Ximena Garcia-Rada, Leslie K. John, Ed O’Brien and Michael I. Norton
From downloading never-ending updates to tracking ever-newer releases, consumers
today are surrounded by revised products that purport to have improved upon their predecessors.
Seven experiments examine when and why consumers rely on a “revised-is-quality”... View Details
- 2019
- Article
An Empirical Study of Rich Subgroup Fairness for Machine Learning
By: Michael J Kearns, Seth Neel, Aaron Leon Roth and Zhiwei Steven Wu
Kearns et al. [2018] recently proposed a notion of rich subgroup fairness intended to bridge the gap between statistical and individual notions of fairness. Rich subgroup fairness picks a statistical fairness constraint (say, equalizing false positive rates across... View Details
- November 2018
- Case
frog design
By: Srikant M. Datar and Caitlin N. Bowler
The case follows the genesis and development of Palo, a radical urban communications hub designed to replace payphone booths on Manhattan’s city streets, through a joint venture between frog design and a venture-backed firm LQD WiFi. The case explores the complexity of... View Details
- Article
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness
By: Michael J Kearns, Seth Neel, Aaron Leon Roth and Zhiwei Steven Wu
The most prevalent notions of fairness in machine learning are statistical definitions: they fix a small collection of pre-defined groups, and then ask for parity of some statistic of the classifier (like classification rate or false positive rate) across these groups.... View Details
- 2016
- Other Teaching and Training Material
Organizational Behavior Reading: Decision Making
By: Francesca Gino, Max Bazerman and Katherine Shonk
This Reading argues that decision making is systematically flawed and introduces methods to improve decision-making effectiveness. The Essential Reading section covers the rational decision-making model and three important ideas that challenge it: Herbert Simon's... View Details
- Article
Heuristics Guide the Implementation of Social Preferences in One-Shot Prisoner's Dilemma Experiments
By: Jillian J. Jordan, Valerio Capraro and David G. Rand
Cooperation in one-shot anonymous interactions is a widely documented aspect of human behavior. Here we shed light on the motivations behind this behavior by experimentally exploring cooperation in a one-shot continuous-strategy Prisoner’s Dilemma (i.e. one-shot... View Details
- May 2013
- Article
From Russia with Love: The Impact of Relocated Firms on Incumbent Survival
By: Oliver Falck, Christina Guenther, Stephan Heblich and William R. Kerr
We identify the impact of local firm concentration on incumbent performance with a quasi-natural experiment. When Germany was divided after World War II, many firms in the machine tool industry fled the Soviet occupied zone to prevent expropriation. We show that the... View Details
- August 2011
- Article
Coming Clean and Cleaning Up: Does Voluntary Self-Reporting Indicate Effective Self-Policing
By: Michael W. Toffel and Jodi L. Short
Regulatory agencies are increasingly establishing voluntary self-reporting programs both as an investigative tool and to encourage regulated firms to commit to policing themselves. We investigate whether voluntary self-reporting can reliably indicate effective... View Details
- Article
From Thinking Too Little to Thinking Too Much: A Continuum of Decision Making.
By: Dan Ariely and Michael I. Norton
Due to the sheer number and variety of decisions that people make in their everyday lives-from choosing yogurts to choosing religions to choosing spouses-research in judgment and decision making has taken many forms. We suggest, however, that much of this research has... View Details
- Article
A Learning Perspective on Intraorganizational Knowledge Spill-Ins
By: James Oldroyd and Ranjay Gulati
This exploratory study examines the role of intraorganizational knowledge spill-ins in the process of inferential learning. Drawing on the notions of knowledge reliability (the creation of shared meanings) and validity (understandings of cause and effect), we explore... View Details
- 1999
- Article
Effects of Instructional Style on Problem-Solving Creativity
By: A. M. Ruscio and T. M. Amabile
This study sought to determine the impact of 2 differing instructional approaches on creative problem-solving performance. Eighty-two college students completed a novel structure-building task after receiving algorithmic instruction (providing a rote, step-by-step... View Details
- Forthcoming
- Article
Slowly Varying Regression Under Sparsity
By: Dimitris Bertsimas, Vassilis Digalakis Jr, Michael Lingzhi Li and Omar Skali Lami
We consider the problem of parameter estimation in slowly varying regression models with sparsity constraints. We formulate the problem as a mixed integer optimization problem and demonstrate that it can be reformulated exactly as a binary convex optimization problem... View Details