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Show Results For
- All HBS Web
(249)
- People (1)
- News (73)
- Research (147)
- Events (5)
- Multimedia (2)
- Faculty Publications (23)
- 25 Mar 2021
- Research & Ideas
Steer Clear of the Blind Spots That Derail Experiments
Should companies let employees keep working remotely after the COVID-19 pandemic ends? Assessing the impact of remote work has involved a lot of guesswork for business leaders, but it doesn’t have to be that way. Consider the Chinese travel company Ctrip, now known as... View Details
Keywords: by Danielle Kost
- 2020
- Working Paper
Engineering Serendipity: When Does Knowledge Sharing Lead to Knowledge Production?
By: Jacqueline N. Lane, Ina Ganguli, Patrick Gaule, Eva C. Guinan and Karim R. Lakhani
We investigate how knowledge similarity between two individuals is systematically related to the likelihood that a serendipitous encounter results in knowledge production. We conduct a natural field experiment at a medical research symposium, where we exogenously... View Details
Keywords: Cognitive Similarity; Knowledge Creation; Knowledge Sharing; Knowledge Dissemination; Relationships
Lane, Jacqueline N., Ina Ganguli, Patrick Gaule, Eva C. Guinan, and Karim R. Lakhani. "Engineering Serendipity: When Does Knowledge Sharing Lead to Knowledge Production?" Harvard Business School Working Paper, No. 20-058, November 2019. (Revised July 2020.)
- 15 Jan 2019
- Blog Post
Interning in the Retail Sector
project, to a data scientist where he was able to learn to code in R and utilize SQL and Tableau to strengthen his strategic analysis and data skillset. Learn how Wayfair... View Details
Keywords: Consumer Products / Retail
Iavor I. Bojinov
Iavor Bojinov is an Assistant Professor of Business Administration and the Richard Hodgson Fellow at Harvard Business School. He is the co-PI of the AI and Data Science Operations Lab and a faculty affiliate in the Department of Statistics at Harvard University and... View Details
- February 2014
- Case
BGI: Data-driven Research
By: Willy Shih and Sen Chai
BGI has the largest installed gene-sequencing capacity in the world, and to Zhang Gengyun, general manager of the Life Sciences Division, this represented an opportunity to apply his training as a plant breeder and his early career work as a biochemist to improving... View Details
Keywords: Genomics; Gene Sequencing; Life Sciences; Plant Breeding; Human Genome Program; Beijing Genomics Institute; BGI; Rice Genome; Technological Innovation; Innovation Strategy; Research; Research and Development; Science; Genetics; Science-Based Business; Strategy; Commercialization; Corporate Strategy; Information Technology; Applications and Software; Agriculture and Agribusiness Industry; Biotechnology Industry; Food and Beverage Industry; China; United States
Shih, Willy, and Sen Chai. "BGI: Data-driven Research." Harvard Business School Case 614-056, February 2014.
- 15 Dec 2017
- News
Patient-Powered Precision
Katherine Wang
Katherine is a doctoral student in the Business Economics program. She is interested in labor, public, and development economics with a focus on issues of gender and gender-based violence. Prior to joining HBS, Katherine led field experiments as a data scientist on the... View Details
Edward H. Chang
Edward Chang (he/him/his) is an Assistant Professor of Business Administration in the Negotiation, Organizations & Markets Unit at Harvard Business School. He teaches Inclusion in the MBA required curriculum and Negotiations in the MBA elective curriculum.
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Siyu Zhang
Siyu Zhang is a second-year doctoral student at HBS. Zhang joined Harvard Business School in 2020 as a Research Associate and has been working on macroeconomic forecasting projects. Prior to joining HBS, he was a Data Scientist at John Hancock, where he utilized... View Details
- 13 Apr 2017
- News
What Precision Medicine Can Learn from the NFL
- June 2021
- Article
Engineering Serendipity: When Does Knowledge Sharing Lead to Knowledge Production?
By: Jacqueline N. Lane, Ina Ganguli, Patrick Gaule, Eva C. Guinan and Karim R. Lakhani
We investigate how knowledge similarity between two individuals is systematically related to the likelihood that a serendipitous encounter results in knowledge production. We conduct a natural field experiment at a medical research symposium, where we exogenously... View Details
Keywords: Cognitive Similarity; Innovation; Knowledge Production; Natural Field Experiment; Knowledge Acquisition; Knowledge Sharing; Relationships
Lane, Jacqueline N., Ina Ganguli, Patrick Gaule, Eva C. Guinan, and Karim R. Lakhani. "Engineering Serendipity: When Does Knowledge Sharing Lead to Knowledge Production?" Strategic Management Journal 42, no. 6 (June 2021).
- 28 Feb 2014
- HBS Seminar
Paula Stephan, Georgia State Univ and NBER
- 05 Nov 2007
- Research & Ideas
The Changing Face of American Innovation
A better understanding of these deeper relationships is the most important outcome of this work. Q: Your data shows the ethnic composition of U.S. scientists and engineers undergoing a significant... View Details
- 16 Sep 2015
- News
Faculty Q&A: The Working World
- 14 Sep 2011
- Working Paper Summaries
Ethnic Innovation and US Multinational Firm Activity
Keywords: by C. Fritz Foley & William R. Kerr
- 29 Nov 2004
- Research & Ideas
Caves, Clusters, and Weak Ties: The Six Degrees World of Inventors
about these ideas. We gathered thirty years of U.S. patent data and wrote up some code that identifies the inventors and links them to each other for three million patents and two million inventors. Our first cut was to look at the... View Details
- 29 Jun 2015
- News
High-Profile Study Turns Up the Antitrust Heat on Google
- Article
The Importance of Being Causal
By: Iavor I Bojinov, Albert Chen and Min Liu
Causal inference is the study of how actions, interventions, or treatments affect outcomes of interest. The methods that have received the lion’s share of attention in the data science literature for establishing causation are variations of randomized experiments.... View Details
Keywords: Causal Inference; Observational Studies; Cross-sectional Studies; Panel Studies; Interrupted Time-series; Instrumental Variables
Bojinov, Iavor I., Albert Chen, and Min Liu. "The Importance of Being Causal." Harvard Data Science Review 2.3 (July 30, 2020).
Importance of Being Causal
Causal inference is the study of how actions, interventions, or treatments affect outcomes of interest. The methods that have received the lion’s share of attention in the data science literature for establishing causation are variations of randomized... View Details