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- 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...
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Keywords:
User-generated Content;
Operations;
Tournaments;
Policy-making;
Machine Learning;
Online Platforms;
Analytics and Data Science;
Mathematical Methods;
City;
Infrastructure;
Business Processes;
Government and Politics
Glaeser, Edward, Andrew Hillis, Scott Duke Kominers, and Michael Luca. "Crowdsourcing City Government: Using Tournaments to Improve Inspection Accuracy." American Economic Review: Papers and Proceedings 106, no. 5 (May 2016): 114–118.
- 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...
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Boudreau, Kevin J., Karim R. Lakhani, and Michael E. Menietti. "Performance Responses to Competition Across Skill-Levels in Rank Order Tournaments: Field Evidence and Implications for Tournament Design." RAND Journal of Economics 47, no. 1 (Spring 2016): 140–165.
- Article
Algorithms Need Managers, Too
By: Michael Luca, Jon Kleinberg and Sendhil Mullainathan
Algorithms are powerful predictive tools, but they can run amok when not applied properly. Consider what often happens with social media sites. Today many use algorithms to decide which ads and links to show users. But when these algorithms focus too narrowly on...
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Keywords:
Machine Learning;
Algorithms;
Predictive Analytics;
Management;
Big Data;
Analytics and Data Science
Luca, Michael, Jon Kleinberg, and Sendhil Mullainathan. "Algorithms Need Managers, Too." Harvard Business Review 94, nos. 1/2 (January–February 2016): 96–101.
- 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...
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Ferreira, Kris J., Bin Hong Alex Lee, and David Simchi-Levi. "Analytics for an Online Retailer: Demand Forecasting and Price Optimization." Manufacturing & Service Operations Management 18, no. 1 (Winter 2016): 69–88.
- 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
Kho, Abel, John Cashy, Kathryn Jackson, Adam Pah, Satyender Goel, Jorn Boehnke, John Eric Humphries, Scott Duke Kominers, and et al. "Design and Implementation of a Privacy Preserving Electronic Health Record Linkage Tool in Chicago." Journal of the American Medical Informatics Association 22, no. 5 (September 2015): 1072–1080.
- 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...
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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
Hamermesh, Richard G., and Matthew G. Preble. "Medalogix." Harvard Business School Case 815-116, March 2015. (Revised June 2015.)
- 2015
- Working Paper
Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud
By: Michael Luca and Georgios Zervas
Consumer reviews are now part of everyday decision-making. Yet, the credibility of these reviews is fundamentally undermined when businesses commit review fraud, creating fake reviews for themselves or their competitors. We investigate the economic incentives to commit...
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Keywords:
Information;
Competition;
Internet and the Web;
Ethics;
Reputation;
Social and Collaborative Networks;
Retail Industry;
Food and Beverage Industry
Luca, Michael, and Georgios Zervas. "Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud." Working Paper. (May 2015. Revise and resubmit, Management Science.)
- Article
Fast Subset Scan for Multivariate Spatial Biosurveillance
By: Daniel B. Neill, Edward McFowland III and Huanian Zheng
We present new subset scan methods for multivariate event detection in massive space-time datasets. We extend the recently proposed 'fast subset scan' framework from univariate to multivariate data, enabling computationally efficient detection of irregular space-time...
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Neill, Daniel B., Edward McFowland III, and Huanian Zheng. "Fast Subset Scan for Multivariate Spatial Biosurveillance." Statistics in Medicine 32, no. 13 (June 15, 2013): 2185–2208.
- Article
Assent-maximizing Social Choice
By: Katherine A. Baldiga and Jerry R. Green
We take a decision theoretic approach to the classic social choice problem, using data on the frequency of choice problems to compute social choice functions. We define a family of social choice rules that depend on the population's preferences and on the probability...
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Keywords:
Decision Choices and Conditions;
Theory;
Measurement and Metrics;
Mathematical Methods;
Society
Baldiga, Katherine A., and Jerry R. Green. "Assent-maximizing Social Choice." Social Choice and Welfare 40, no. 2 (February 2013): 439–460.
- 2014
- Working Paper
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 web-site, 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...
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Keywords:
Peer Firm;
EDGAR Search Traffic;
Revealed Preference;
Co-search;
Industry Classification;
Analytics and Data Science;
Internet and the Web;
Mathematical Methods;
Corporate Finance
Lee, Charles M.C., Paul Ma, and Charles C.Y. Wang. "Search-Based Peer Firms: Aggregating Investor Perceptions Through Internet Co-Searches." Harvard Business School Working Paper, No. 13-048, November 2012. (Revised September 2013, March 2014, June 2014, July 2014.)
- September 2011 (Revised July 2012)
- Case
Building Watson: Not So Elementary, My Dear!
By: Willy Shih
This case is set inside IBM Research's efforts to build a computer that can successfully take on human challengers playing the game show Jeopardy! It opens with the machine named Watson offering the incorrect answer "Toronto" to a seemingly simple question during the...
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Keywords:
Technological Innovation;
Standards;
Product Development;
Organizational Change and Adaptation;
Mathematical Methods;
Research and Development;
Information Technology
Shih, Willy. "Building Watson: Not So Elementary, My Dear!" Harvard Business School Case 612-017, September 2011. (Revised July 2012.)
- Article
Fast Subset Scan for Multivariate Spatial Biosurveillance
By: Daniel B. Neill, Edward McFowland III and Huanian Zheng
We extend the recently proposed ‘fast subset scan’ framework from univariate to multivariate data, enabling computationally efficient detection of irregular space-time clusters even when the numbers of spatial locations and data streams are large. These fast algorithms...
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- April 2008
- Article
The Survey of Industrial R&D—Patent Database Link Project
By: William R. Kerr and Shihe Fu
This paper details the construction of a firm-year panel dataset combining the NBER Patent Dataset with the Survey of Industrial R&D conducted by the Census Bureau and National Science Foundation. The dataset constitutes a platform that offers an unprecedented view of...
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Keywords:
Analytics and Data Science;
Patents;
Surveys;
Research and Development;
Innovation and Invention;
Performance Productivity;
Projects;
Management Practices and Processes;
Management Analysis, Tools, and Techniques
Kerr, William R., and Shihe Fu. "The Survey of Industrial R&D—Patent Database Link Project." Journal of Technology Transfer 33, no. 2 (April 2008): 173–186.
- Forthcoming
- Article
A Machine Learning Algorithm Predicting Risk of Dilating VUR among Infants with Hydronephrosis Using UTD Classification
By: Hsin-Hsiao Scott Wang, Michael Lingzhi Li, Dylan Cahill, John Panagides, Tanya Logvinenko, Jeanne Chow and Caleb Nelson
Backgrounds: Urinary Tract Dilation (UTD) classification has been designed to be a more objective grading system to evaluate antenatal and post-natal UTD. Due to unclear association between UTD classifications to specific anomalies such as vesico-ureteral reflux (VUR),...
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Wang, Hsin-Hsiao Scott, Michael Lingzhi Li, Dylan Cahill, John Panagides, Tanya Logvinenko, Jeanne Chow, and Caleb Nelson. "A Machine Learning Algorithm Predicting Risk of Dilating VUR among Infants with Hydronephrosis Using UTD Classification." Journal of Pediatric Urology (forthcoming). (Pre-published online November 9, 2023.)
- 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...
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Zhang, Shunyuan, Flora Feng, and Kannan Srinivasan. "Marketing Through the Machine’s Eyes: Image Analytics and Interpretability." Chap. 8 in Artificial Intelligence in Marketing. 20, edited by Naresh K. Malhotra, K. Sudhir, and Olivier Toubia. Review of Marketing Research. Emerald Publishing Limited, forthcoming.
- Research Summary
Overview
By: Iavor I. Bojinov
My research focuses on overcoming the methodological and operational challenges of developing data science capabilities, what I call data science operations. Today, within leading digital companies, data science is no longer confined to technical teams but is pervasive...
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- Research Summary
Overview
By: Roberto Verganti
Roberto’s research focuses on how to create innovations that are meaningful for people, for society, and for their creators. He explores how leaders and organizations generate radically new visions, and make those visions come real. His studies lie at the intersection...
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- Research Summary
Overview
Professor Ferreira's research primarily focuses on how retailers can use algorithms to make better revenue management decisions, including pricing, product display, and assortment planning. In the retail industry, anticipating consumer demand is arguably one of the...
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- Research Summary
Overview
By: Ayelet Israeli
Professor Israeli utilizes econometric methods and field experiments to study data driven decision making in marketing context. Her research focuses on data-driven marketing, with an emphasis on how businesses can leverage their own data, customer data, and market data...
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