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- Faculty Publications (65)
Accuracy
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- October 2018
- Article
The Operational Value of Social Media Information
By: Ruomeng Cui, Santiago Gallino, Antonio Moreno and Dennis J. Zhang
While the value of using social media information has been established in multiple business contexts, the field of operations and supply chain management have not yet explored the possibilities it offers in improving firms' operational decisions. This study attempts to... View Details
- September 2018 (Revised December 2019)
- Case
Zebra Medical Vision
By: Shane Greenstein and Sarah Gulick
An Israeli startup founded in 2014, Zebra Medical Vision developed algorithms that produced diagnoses from X-rays, mammograms, and CT-scans. The algorithms used deep learning and digitized radiology scans to create software that could assist doctors in making... View Details
Keywords: Radiology; Machine Learning; X-ray; CT Scan; Medical Technology; Probability; FDA 510(k); Diagnosis; Business Startups; Health Care and Treatment; Information Technology; Applications and Software; Competitive Strategy; Product Development; Commercialization; Decision Choices and Conditions; Health Industry; Medical Devices and Supplies Industry; Technology Industry; Israel
- September 2018
- Article
Do Experts or Crowd-Based Models Produce More Bias? Evidence from Encyclopædia Britannica and Wikipedia
By: Shane Greenstein and Feng Zhu
Organizations today can use both crowds and experts to produce knowledge. While prior work compares the accuracy of crowd-produced and expert-produced knowledge, we compare bias in these two models in the context of contested knowledge, which involves subjective,... View Details
- 2021
- Working Paper
Government Shareholdings in Brokerage Firms and Analyst Research Quality
By: Sheng Cao, Xianjie He, Charles C.Y. Wang and Huifang Yin
During times when the Chinese government wished to prop up the market, sell-side analysts from brokerages with significant government ownership issued relatively less pessimistic (or more optimistic) earnings forecasts, earnings-forecast revisions, and stock... View Details
- 2018
- Working Paper
How Scheduling Can Bias Quality Assessment: Evidence from Food Safety Inspections
By: Maria Ibanez and Michael W. Toffel
Many production processes are subject to inspection to ensure they meet quality, safety, and environmental standards imposed by companies and regulators. Inspection accuracy is critical to inspections being a useful input to assessing risks, allocating quality... View Details
- 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
- 2016
- Article
Penalized Fast Subset Scanning
By: Skyler Speakman, Sriram Somanchi, Edward McFowland III and Daniel B. Neill
We present the penalized fast subset scan (PFSS), a new and general framework for scalable and accurate pattern detection. PFSS enables exact and efficient identification of the most anomalous subsets of the data, as measured by a likelihood ratio scan statistic.... View Details
- 2015
- Working Paper
The Wisdom of Crowds in Operations: Forecasting Using Prediction Markets
By: Achal Bassamboo, Ruomeng Cui and Antonio Moreno
Prediction is an important activity in various business processes, but it becomes difficult when historical information is not available, such as forecasting demand of a new product. One approach that can be applied in such situations is to crowdsource opinions from... View Details
- 2015
- Article
Scalable Detection of Anomalous Patterns With Connectivity Constraints
By: Skyler Speakman, Edward McFowland III and Daniel B. Neill
We present GraphScan, a novel method for detecting arbitrarily shaped connected clusters in graph or network data. Given a graph structure, data observed at each node, and a score function defining the anomalousness of a set of nodes, GraphScan can efficiently and... View Details
- October 2014 (Revised June 2015)
- Case
Quiet Logistics (A)
By: Robert Simons and Natalie Kindred
This two-part case focuses on how to identify and manage strategic uncertainties in an innovative, entrepreneurial start-up company. In the (A) case, students learn about Quiet Logistics, an e-commerce fulfillment company working with high-end apparel retailers such as... View Details
Keywords: Strategy Execution; Strategic Uncertainty; Disruptive Change; Managing Growth; Robotics; Disruptive Technology; Managing Start-ups; Management Control Systems; Performance Measurement; Business Growth and Maturation; Disruption; Entrepreneurship; Disruptive Innovation; Crisis Management; Risk Management; Organizational Change and Adaptation; Business Strategy; Competitive Strategy; E-commerce; Distribution Industry; Technology Industry; United States
- October 2014
- Supplement
Quiet Logistics (B)
By: Robert Simons and Natalie Kindred
This two-part case focuses on how to identify and manage strategic uncertainties in an innovative, entrepreneurial start-up company. In the (A) case, students learn about Quiet Logistics, an e-commerce fulfillment company working with high-end apparel retailers such as... View Details
Keywords: Strategy Execution; Strategic Uncertainties; Managing Growth; Disruptive Change; Robotics; Disruptive Technologies; Managing Start-ups; Management Control Systems; Performance Measurement; Business Growth and Maturation; Disruption; Entrepreneurship; Disruptive Innovation; Crisis Management; Risk Management; Organizational Change and Adaptation; Business Strategy; Competitive Strategy; E-commerce; Distribution Industry; Technology Industry; United States
- Article
Economics at the FTC: Physician Acquisitions, Standard Essential Patents, and Accuracy of Credit Reporting
By: Julie Carlson, Leemore S. Dafny, Beth Freeborn, Pauline Ippolito and Brett Wendling
- 2011
- Article
Scalable Detection of Anomalous Patterns With Connectivity Constraints
By: Skyler Speakman, Edward McFowland III and Daniel B. Neill
We present GraphScan, a novel method for detecting arbitrarily shaped connected clusters in graph or network data. Given a graph structure, data observed at each node, and a score function defining the anomalousness of a set of nodes, GraphScan can efficiently and... View Details
- 2010
- Working Paper
When Do Analysts Add Value? Evidence from Corporate Spinoffs
By: Emilie Rose Feldman, Stuart Gilson and Belen Villalonga
We investigate the information content and forecast accuracy of 1,793 analyst reports written around 62 spinoffs—a setting in which analysts' ability to inform investors is potentially very high. We find that analysts pay little attention to subsidiaries about to be... View Details
- June 2009 (Revised April 2019)
- Case
Crosley
By: Tom Nicholas and David Chen
In October 1941, a top secret envoy from the U.S. military was sent to Crosley Corporation in Cincinnati, Ohio to request their assistance to construct a weapon that would drastically strengthen the defenses of U.S. troops: the proximity fuze. Such a fuze would allow... View Details
- Article
From Wealth to Well-Being? Money Matters, but Less than People Think
By: Lara B. Aknin, Michael I. Norton and Elizabeth W. Dunn
While numerous studies have documented the modest (though reliable) link between household income and well-being, we examined the accuracy of laypeople's intuitions about this relationship by asking people from across the income spectrum to report their own... View Details
- January 2008 (Revised July 2009)
- Case
Forecasting the Great Depression
What is proper role of professional economic forecasting in financial decision making? The case presents excerpts from three leading economic forecasters on the eve of, and just after, the stock market crash of October 1929. The first set of excerpts is from Roger... View Details
- Article
Learning and Equilibrium as Useful Approximations: Accuracy of Prediction on Randomly Selected Constant Sum Games
By: Ido Erev, Alvin E. Roth, R. Slonim and Greg Barron
- 2007
- Chapter
Team Emotion Recognition Accuracy and Team Performance
By: H. A. Elfenbein, J. T. Polzer and N. Ambady
- 2006
- Working Paper
Learning and Equilibrium As Useful Approximations: Accuracy of Prediction on Randomly Selected Constant Sum Games
By: Ido Erev, Alvin E. Roth, Robert L. Slonim and Greg Barron