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- 2010
- Chapter
Deferred Acceptance Algorithms: History, Theory, Practice
By: Alvin E. Roth
The deferred acceptance algorithm proposed by Gale and Shapley (1962) has had a profound influence on market design, both directly, by being adapted into practical matching mechanisms, and indirectly, by raising new theoretical questions. Deferred acceptance 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.
- March 2008
- Article
Deferred Acceptance Algorithms: History, Theory, Practice, and Open Questions
By: Alvin E. Roth
The deferred acceptance algorithm proposed by Gale and Shapley (1962) has had a profound influence on market design, both directly, by being adapted into practical matching mechanisms, and, indirectly, by raising new theoretical questions. Deferred acceptance...
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Keywords:
History;
Market Design;
Labor;
System;
Practice;
Performance;
Theory;
Boston;
New York (city, NY)
Roth, Alvin E. "Deferred Acceptance Algorithms: History, Theory, Practice, and Open Questions." Prepared for Gale's Feast: A Day in Honor of the 85th Birthday of David Gale International Journal of Game Theory 36, nos. 3-4 (March 2008): 537–569.
- 2007
- Working Paper
Deferred Acceptance Algorithms: History, Theory, Practice, and Open Questions
By: Alvin E. Roth
The deferred acceptance algorithm proposed by Gale and Shapley (1962) has had a profound influence on market design, both directly, by being adapted into practical matching mechanisms, and, indirectly, by raising new theoretical questions. Deferred acceptance...
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- March 2007 (Revised April 2007)
- Case
The University of Utah and the Computer Graphics Revolution
By: H. Kent Bowen and Courtney Purrington
Computer science departments were new to universities in the 1960s, and the one created at the University of Utah by David Evans and Ivan Sutherland had a research mission to invent the field of computer graphics. Details the research process that led to many of the...
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Keywords:
Engineering;
Entrepreneurship;
Management Practices and Processes;
Mission and Purpose;
Research and Development;
Technology Adoption;
Computer Industry;
Education Industry;
Utah
Bowen, H. Kent, and Courtney Purrington. "The University of Utah and the Computer Graphics Revolution." Harvard Business School Case 607-036, March 2007. (Revised April 2007.)
- 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...
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Ruscio, A. M., and T. M. Amabile. "Effects of Instructional Style on Problem-Solving Creativity." Creativity Research Journal 12, no. 4 (1999): 251–266.
- Article
The Effects of the Change in the NRMP Matching Algorithm
By: A. E. Roth and Elliott Peranson
Roth, A. E., and Elliott Peranson. "The Effects of the Change in the NRMP Matching Algorithm." JAMA, the Journal of the American Medical Association 278, no. 9 (September 3, 1997): 729–732.
- 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.)
- Forthcoming
- Article
A Universal In-Place Reconfiguration Algorithm for Sliding Cube-Shaped Robots in Quadratic Time
By: Zachary Abel, Hugo A. Akitaya, Scott Duke Kominers, Matias Korman and Frederick Stock
In the modular robot reconfiguration problem we are given n cube-shaped modules (or "robots") as well as two configurations, i.e., placements of the n modules so that their union is face-connected. The goal is to find a sequence of moves that reconfigures the modules...
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- Forthcoming
- Article
Branch-and-Price for Prescriptive Contagion Analytics
By: Alexandre Jacquillat, Michael Lingzhi Li, Martin Ramé and Kai Wang
Contagion models are ubiquitous in epidemiology, social sciences, engineering, and management. This paper formulates a prescriptive contagion analytics model where a decision maker allocates shared resources across multiple segments of a population, each governed by...
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Jacquillat, Alexandre, Michael Lingzhi Li, Martin Ramé, and Kai Wang. "Branch-and-Price for Prescriptive Contagion Analytics." Operations Research (forthcoming). (Pre-published online March 13, 2024.)
- Forthcoming
- Article
How Artificial Intelligence Constrains Human Experience
By: A. Valenzuela, S. Puntoni, D. Hoffman, N. Castelo, J. De Freitas, B. Dietvorst, C. Hildebrand, Y.E. Huh, R. Meyer, M. Sweeney, S. Talaifar, G. Tomaino and K. Wertenbroch
Many consumption decisions and experiences are digitally mediated. As a consequence, consumer behavior is increasingly the joint product of human psychology and ubiquitous algorithms (Braun et al. 2024; cf. Melumad et al. 2020). The coming of age of Large Language...
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Keywords:
Large Language Model
Valenzuela, A., S. Puntoni, D. Hoffman, N. Castelo, J. De Freitas, B. Dietvorst, C. Hildebrand, Y.E. Huh, R. Meyer, M. Sweeney, S. Talaifar, G. Tomaino, and K. Wertenbroch. "How Artificial Intelligence Constrains Human Experience." Special Issue on Automation. Journal of the Association for Consumer Research (forthcoming).
- 2021
- Chapter
Leapfrog Leaders: Accelerating Systems Leadership Skills
By: Laura Cabrera, Derek Cabrera and Hise O. Gibson
We need leaders who can execute at the Strategic, Operational, and Tactical (SOT) levels. But, research shows it takes time for skills to develop at all three levels—too much time. Why does it take too much time? First, because expertise is borne of experience. An...
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Keywords:
DSRP;
VCML;
Strategy;
Operations;
Leadership Development;
Decision Making;
Organizational Structure
Cabrera, Laura, Derek Cabrera, and Hise O. Gibson. "Leapfrog Leaders: Accelerating Systems Leadership Skills." In The Routledge Handbook of Systems Thinking, edited by Derek Cabrera, Laura Cabrera, and Gordon Midgley. London: Routledge, forthcoming.
- 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
Professor MacKay combines theory and measurement to deliver new insights about price competition and consumer preferences. In current and published papers, his research addresses how strategic pricing decisions may be influenced by algorithms, long-term contracts,... View Details
- 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
I develop machine learning tools and techniques which enable human decision makers to make better decisions. More specifically, my research addresses the following fundamental questions pertaining to human and algorithmic decision-making:
1. How to build... View Details
1. How to build... View Details
- 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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- Research Summary
Understanding the Limitations of Model Explanations
The goal of this research is to understand how adversaries can exploit various algorithms used for explaining complex machine learning models with an intention to mislead end users. For instance, can adversaries trick these algorithms into masking their racial and...
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