Publications
Publications
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- All HBS Web
(670)
- Faculty Publications (211)
- October 2017
- Case
Quantopian: A New Model for Active Management
- October 2017 (Revised April 2018)
- Case
Improving Worker Safety in the Era of Machine Learning (A)
By: Michael W. Toffel, Dan Levy, Jose Ramon Morales Arilla and Matthew S. Johnson
Managers make predictions all the time: How fast will my markets grow? How much inventory do I need? How intensively should I monitor my suppliers? Which potential customers will be most responsive to a particular marketing campaign? Which job candidates should I... View Details
- September 2017
- Article
It Doesn't Hurt to Ask: Question-asking Increases Liking
By: K. Huang, M. Yeomans, A.W. Brooks, J. Minson and F. Gino
Conversation is a fundamental human experience, one that is necessary to pursue intrapersonal and interpersonal goals across myriad contexts, relationships, and modes of communication. In the current research, we isolate the role of an understudied conversational... View Details
- Article
The Selective Labels Problem: Evaluating Algorithmic Predictions in the Presence of Unobservables
By: Himabindu Lakkaraju, Jon Kleinberg, Jure Leskovec, Jens Ludwig and Sendhil Mullainathan
- May 2017
- Other Article
Stepwise Distributed Open Innovation Contests for Software Development: Acceleration of Genome-Wide Association Analysis
By: Andrew Hill, Po-Ru Loh, Ragu B. Bharadwaj, Pascal Pons, Jingbo Shang, Eva C. Guinan, Karim R. Lakhani, Iain Kilty and Scott Jelinsky
BACKGROUND:
The association of differing genotypes with disease-related phenotypic traits offers great potential to both help identify new therapeutic targets and support stratification of patients who would gain the greatest benefit from specific drug classes.... View Details
- January 2017 (Revised January 2017)
- Case
Susan Cassidy at Bertram Gilman International
By: Jeffrey T. Polzer and Michael Norris
In 2016, Susan Cassidy, VP of sales and marketing for the packaged foods division at CPG firm Bertram Gilman International, has to make a promotion decision. Should she choose the person she has been grooming for the position or another candidate recommended by central... View Details
- Winter 2017
- Article
Why Big Data Isn't Enough
By: Sen Chai and Willy C. Shih
There is a growing belief that sophisticated algorithms can explore huge databases and find relationships independent of any preconceived hypotheses. But in businesses that involve scientific research and technological innovation, this approach is misguided and... View Details
- 2016
- Working Paper
Foreign Competition and Domestic Innovation: Evidence from U.S. Patents
By: David Autor, David Dorn, Gordon H. Hanson, Pian Shu and Gary Pisano
Manufacturing is the locus of U.S. innovation, accounting for more than three quarters of U.S. corporate patents. The rise of import competition from China has represented a major competitive shock to the sector, which in theory could benefit or stifle innovation. In... View Details
- 18 Nov 2016
- Conference Presentation
Rawlsian Fairness for Machine Learning
By: Matthew Joseph, Michael J. Kearns, Jamie Morgenstern, Seth Neel and Aaron Leon Roth
Motivated by concerns that automated decision-making procedures can unintentionally lead to discriminatory behavior, we study a technical definition of fairness modeled after John Rawls' notion of "fair equality of opportunity". In the context of a simple model of... View Details
- June 2016
- Teaching Note
HubSpot: Lower Churn through Greater CHI
By: Jill Avery, Asis Martinez Jerez and Thomas Steenburgh
HubSpot, a web marketing startup selling inbound marketing software to small- and medium-sized businesses, is under pressure from its venture capital partners to rapidly acquire new customers and to maintain a low level of customer churn. The B2B SaaS company is in the... View Details
- June 2016
- Article
Detecting Figures and Part Labels in Patents: Competition-based Development of Graphics Recognition Algorithms
By: Christoph Riedl, Richard Zanibbi, Marti A. Hearst, Siyu Zhu, Michael Menietti, Jason Crusan, Ivan Metelsky and Karim R. Lakhani
- Article
Crowdsourcing City Government: Using Tournaments to Improve Inspection Accuracy
By: Edward Glaeser, Andrew Hillis, Scott Duke Kominers and Michael Luca
The proliferation of big data makes it possible to better target city services like hygiene inspections, but city governments rarely have the in-house talent needed for developing prediction algorithms. Cities could hire consultants, but a cheaper alternative is to... View Details
- Spring 2016
- Article
Performance Responses to Competition Across Skill-Levels in Rank Order Tournaments: Field Evidence and Implications for Tournament Design
By: Kevin J. Boudreau, Karim R. Lakhani and Michael E. Menietti
Tournaments are widely used in the economy to organize production and innovation. We study individual contestant-level data from 2,796 contestants in 774 software algorithm design contests with random assignment. Precisely conforming to theory predictions, the... View Details
- Winter 2016
- Article
Analytics for an Online Retailer: Demand Forecasting and Price Optimization
By: Kris J. Ferreira, Bin Hong Alex Lee and David Simchi-Levi
We present our work with an online retailer, Rue La La, as an example of how a retailer can use its wealth of data to optimize pricing decisions on a daily basis. Rue La La is in the online fashion sample sales industry, where they offer extremely limited-time... View Details
- 2016
- Chapter
Deriving an Optimally Deceptive Policy in Two-Player Iterated Games
By: Elisabeth Paulson and Christopher Griffin
We formulate the problem of determining an optimally deceptive strategy in a repeated game framework. We assume that two players are engaged in repeated play. During an initial time period, Player 1 may deceptively train his opponent to expect a specific strategy. The... View Details
- November 2015 (Revised May 2016)
- Case
Aspiring Minds
By: Karim R. Lakhani, Marco Iansiti and Christine Snively
By 2015, India-based employment assessment and certification provider Aspiring Minds had helped facilitate over 300,000 job matches through its assessment tools. Aspiring Minds' flagship product, the Aspiring Minds Computer Adaptive Test (AMCAT), used machine learning... View Details
- September 2015
- Article
Design and Implementation of a Privacy Preserving Electronic Health Record Linkage Tool in Chicago
By: Abel Kho, John Cashy, Kathryn Jackson, Adam Pah, Satyender Goel, Jorn Boehnke, John Eric Humphries, Scott Duke Kominers and et al.
Objective
To design and implement a tool that creates a secure, privacy preserving linkage of electronic health record (EHR) data across multiple sites in a large metropolitan area in the United States (Chicago, IL), for use in clinical... View Details
To design and implement a tool that creates a secure, privacy preserving linkage of electronic health record (EHR) data across multiple sites in a large metropolitan area in the United States (Chicago, IL), for use in clinical... View Details
Keywords: Information; Customers; Safety; Rights; Ethics; Entrepreneurship; Health Care and Treatment; Health Industry; Chicago
- Article
Search-Based Peer Firms: Aggregating Investor Perceptions Through Internet Co-Searches
By: Charles M.C. Lee, Paul Ma and Charles C.Y. Wang
Applying a "co-search" algorithm to Internet traffic at the SEC's EDGAR website, we develop a novel method for identifying economically-related peer firms and for measuring their relative importance. Our results show that firms appearing in chronologically adjacent... View Details
- March 2015 (Revised June 2015)
- Case
Medalogix
By: Richard G. Hamermesh and Matthew G. Preble
This case examines an exciting new approach to health care that will help care providers identify when hospice services are the appropriate type of care for patients. The company, Medalogix, already has a product on the market that uses a proprietary algorithm to... View Details
Keywords: Health Care; Health Care Entrepreneurship; Health Care Services; Implementing Strategy; Dissemination; Innovation; Market Selection; Health; Health Care and Treatment; Analytics and Data Science; Marketing Strategy; Innovation and Management; Innovation Strategy; Health Industry; United States
- 2015
- Chapter
Optimal Process Control of Symbolic Transfer Functions
By: Christopher Griffin and Elisabeth Paulson
Transfer function modeling is a standard technique in classical Linear Time Invariant and Statistical Process Control. The work of Box and Jenkins was seminal in developing methods for identifying parameters associated with classical (r, s, k) transfer functions.... View Details