Publications
Publications
Show Results For
- All HBS Web
(1,959)
- Faculty Publications (567)
- Article
Innovation Contests for High-Tech Procurement
By: Jin Hyun Paik, Martin Scholl, Rinat A. Sergeev, Steven Randazzo and Karim R. Lakhani
Innovation managers rarely use crowdsourcing as an innovative instrument despite extensive academic and theoretical research. The lack of tools available to compare and measure crowdsourcing, specifically contests, against traditional methods of procuring goods and... View Details
- 2021
- Working Paper
Impact Investing: A Theory of Financing Social Enterprises
By: Benjamin N. Roth
I present a model of financing social enterprises to delineate the role of impact investors relative to “pure” philanthropists. I characterize the optimal scale and structure of a social enterprise when financed by grants, and when financed by investments. Impact... View Details
- January 22, 2020
- Article
Making Honest Conversations the Norm
By: Michael Beer
Much admired companies like Boeing and Wells Fargo sacrifice their competitive advantage. Some make huge ethical blunders. As a result, shareholders suffer huge losses in value while employees, customers, and society lose trust and confidence in the institution. Based... View Details
- Article
Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error
By: Celia Cintas, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan and Edward McFowland III
Reliably detecting attacks in a given set of inputs is of high practical relevance because of the vulnerability of neural networks to adversarial examples. These altered inputs create a security risk in applications with real-world consequences, such as self-driving... View Details
- 2020
- Article
Fast Exact Matrix Completion: A Unified Optimization Framework for Matrix Completion
By: Dimitris Bertsimas and Michael Lingzhi Li
We formulate the problem of matrix completion with and without side information as a non-convex optimization problem. We design fastImpute based on non-convex gradient descent and show it converges to a global minimum that is guaranteed to recover closely the... View Details
Keywords: Mathematical Methods
- May 2020
- Article
Scalable Holistic Linear Regression
By: Dimitris Bertsimas and Michael Lingzhi Li
We propose a new scalable algorithm for holistic linear regression building on Bertsimas & King (2016). Specifically, we develop new theory to model significance and multicollinearity as lazy constraints rather than checking the conditions iteratively. The resulting... View Details
- December 2019
- Technical Note
Technical Note on Bayesian Statistics and Frequentist Power Calculations
By: Amitabh Chandra and Ariel Dora Stern
This Technical Note provides an introduction to Bayes’ Rule and the statistical intuition that stems from it. In this note, we review the concepts that underlie Bayesian statistics, and we offer several simple mathematical examples to illustrate applications of Bayes’... View Details
- 2019
- Article
Configurations of Extremal Type II Codes via Harmonic Weight Enumerators
By: Noam D. Elkies and Scott Duke Kominers
We prove configuration results for extremal Type II codes, analogous to the configuration results of Ozeki and of the second author for extremal Type II lattices. Specifically, we show that for n ∈{8,24,32,48,56,72,96} every extremal Type II code of length n is... View Details
Keywords: Mathematical Methods
- December 2019
- Article
Costly Concessions: An Empirical Framework for Matching with Imperfectly Transferable Utility
By: Alfred Galichon, Scott Duke Kominers and Simon Weber
We introduce an empirical framework for models of matching with imperfectly transferable utility and unobserved heterogeneity in tastes. Our framework allows us to characterize matching equilibrium in a flexible way that includes as special cases the classic fully- and... View Details
- 2019
- Article
Overcoming Cultural Resistance to Open Source Innovation
By: John Winsor, Jin Hyun Paik, Michael Tushman and Karim R. Lakhani
Purpose: This article offers insight on how to effectively help incumbent organizations prepare for global business shifts to open source and digital business models.
Design/methodology/approach: Discussion related to observation, experience and case studies... View Details
Design/methodology/approach: Discussion related to observation, experience and case studies... View Details
- 2019
- Article
Time Series Experiments and Causal Estimands: Exact Randomization Tests and Trading
By: Iavor I Bojinov and Neil Shephard
We define causal estimands for experiments on single time series, extending the potential outcome framework to dealing with temporal data. Our approach allows the estimation of a broad class of these estimands and exact randomization based p-values for testing causal... View Details
- 2020
- Working Paper
Recognition Incentives for Internal Crowdsourcing: A Field Experiment at NASA
By: Jana Gallus, Olivia S. Jung and Karim R. Lakhani
What might motivate employees to participate in internal crowdsourcing, a peer-based approach to innovation? Should organizations use incentives that are congruent with their established hierarchical structures, or should they use incentives that are aligned with the... View Details
- November 2019
- Article
Full Substitutability
By: John William Hatfield, Scott Duke Kominers, Alexandru Nichifor, Michael Ostrovsky and Alexander Westkamp
Various forms of substitutability are essential for establishing the existence of equilibria and other useful properties in diverse settings such as matching, auctions, and exchange economies with indivisible goods. We extend earlier models’ definitions of... View Details
- 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
- Article
From Words to Pixels: Text and Image Mining Methods for Service Research
By: Francisco Villarroel Ordenes and Shunyuan Zhang
- September 2019
- Article
Optimizing Reserves in School Choice: A Dynamic Programming Approach
By: Franklyn Wang, Ravi Jagadeesan and Scott Duke Kominers
We introduce a new model of school choice with reserves in which a social planner is constrained by a limited supply of reserve seats and tries to find an optimal matching according to a social welfare function. We construct the optimal distribution of reserves via a... View Details
- 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
- August 2019
- Article
When and How to Diversify—A Multicategory Utility Model for Personalized Content Recommendation
By: Yicheng Song, Nachiketa Sahoo and Elie Ofek
Sometimes we desire change, a break from the same or an opportunity to fulfill different aspects of our needs. Noting that consumers seek variety, several approaches have been developed to diversify items recommended by personalized recommender systems. However,... View Details
- July 2019
- Article
Optimal Capital Structure and Bankruptcy Choice: Dynamic Bargaining vs Liquidation
By: Samuel Antill and Steven R. Grenadier
We model a firm’s optimal capital structure decision in a framework in which it may later choose to enter either Chapter 11 reorganization or Chapter 7 liquidation. Creditors anticipate equityholders’ ex-post reorganization incentives and price them into the ex-ante... View Details
- 2019
- Article
Ridesharing with Driver Location Preferences
By: Duncan Rheingans-Yoo, Scott Duke Kominers, Hongyao Ma and David C. Parkes
We study revenue-optimal pricing and driver compensation in ridesharing platforms when drivers have heterogeneous preferences over locations. If a platform ignores drivers' location preferences, it may make inefficient trip dispatches; moreover, drivers may strategize... View Details