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Show Results For
- All HBS Web
(2,246)
- People (22)
- News (636)
- Research (1,024)
- Events (32)
- Multimedia (17)
- Faculty Publications (519)
- April 2019
- Article
Incentives for Public Goods Inside Organizations: Field Experimental Evidence
By: Andrea Blasco, Olivia S. Jung, Karim R. Lakhani and Michael Menietti
Understanding why employees go the extra mile at work is a key problem for many organizations. We conduct a field experiment at a medical organization to study motivations for employees to submit project proposals for organizational improvement. In total, we analyze... View Details
Keywords: Field Experiment; Innovation; Contest; Incentives; Free-rider Problem; Healthcare Organizations; Employees; Motivation and Incentives; Innovation and Invention; Organizations; Performance Improvement; Perspective
Blasco, Andrea, Olivia S. Jung, Karim R. Lakhani, and Michael Menietti. "Incentives for Public Goods Inside Organizations: Field Experimental Evidence." Journal of Economic Behavior & Organization 160 (April 2019): 214–229.
- 01 Jun 2012
- News
FIELD 3 Tests Students
successful ventures go through this ‘pivoting’ process multiple times as they probe and test their ideas. FIELD 3 uniquely challenged students to experience that process and learn from it.” Beginning January... View Details
Keywords: FIELD program
- March 2022
- Article
Targeting High Ability Entrepreneurs Using Community Information: Mechanism Design in the Field
Identifying high-growth microentrepreneurs in low-income countries remains a challenge due to a scarcity of verifiable information. With a cash grant experiment in India we demonstrate that community knowledge can help target high-growth microentrepreneurs; while the... View Details
Keywords: Microentrepreneurs; Community Information; Field Experiment; Loans; Entrepreneurship; Developing Countries and Economies; Financing and Loans; Information; Mathematical Methods; India
Hussam, Reshmaan, Natalia Rigol, and Benjamin N. Roth. "Targeting High Ability Entrepreneurs Using Community Information: Mechanism Design in the Field." American Economic Review 112, no. 3 (March 2022): 861–898.
(Online Appendix with Corrigendum—Thanks to Isabella Masetto, Diego Ubfal, and The Institute for Replication for identifying a minor coding error in the production of Table 4.)
(Online Appendix with Corrigendum—Thanks to Isabella Masetto, Diego Ubfal, and The Institute for Replication for identifying a minor coding error in the production of Table 4.)
- 13 Jan 2020
- Working Paper Summaries
Recognition Incentives for Internal Crowdsourcing: A Field Experiment at NASA
Time Series Experiments and Causal Estimands: Exact Randomization Tests and Trading
We define causal estimands for experiments on single time series, extending the potential outcome framework to dealing with temporal data. Our approach allows the estimation of a broad class of these estimands and exact... View Details
- 01 Apr 2002
- News
Q&A - Mark Fields
Concluding a successful tenure at Mazda, Mark Fields was appointed on April 19 to head the Premier group, a London-based unit of Ford Motor Company, which controls Mazda. The Premier group, a $23 billion company, includes brands such as... View Details
- 2020
- Working Paper
Design and Analysis of Switchback Experiments
By: Iavor I Bojinov, David Simchi-Levi and Jinglong Zhao
In switchback experiments, a firm sequentially exposes an experimental unit to a random treatment, measures its response, and repeats the procedure for several periods to determine which treatment leads to the best outcome. Although practitioners have widely adopted... View Details
Bojinov, Iavor I., David Simchi-Levi, and Jinglong Zhao. "Design and Analysis of Switchback Experiments." Harvard Business School Working Paper, No. 21-034, September 2020.
- 01 Dec 2012
- News
FIELD Updates Greet Class of 2014
transforming a set of blueprints into a stunning new Executive Education facility. Tata Hall is scheduled to open in December 2013. As the second class to experience the new, yearlong required curriculum of View Details
- 2023
- Working Paper
Efficient Discovery of Heterogeneous Quantile Treatment Effects in Randomized Experiments via Anomalous Pattern Detection
By: Edward McFowland III, Sriram Somanchi and Daniel B. Neill
In the recent literature on estimating heterogeneous treatment effects, each proposed method makes its own set of restrictive assumptions about the intervention’s effects and which subpopulations to explicitly estimate. Moreover, the majority of the literature provides... View Details
Keywords: Causal Inference; Program Evaluation; Algorithms; Distributional Average Treatment Effect; Treatment Effect Subset Scan; Heterogeneous Treatment Effects
McFowland III, Edward, Sriram Somanchi, and Daniel B. Neill. "Efficient Discovery of Heterogeneous Quantile Treatment Effects in Randomized Experiments via Anomalous Pattern Detection." Working Paper, 2023.
- July 2023
- Article
Design and Analysis of Switchback Experiments
By: Iavor I Bojinov, David Simchi-Levi and Jinglong Zhao
In switchback experiments, a firm sequentially exposes an experimental unit to a random treatment, measures its response, and repeats the procedure for several periods to determine which treatment leads to the best outcome. Although practitioners have widely adopted... View Details
Bojinov, Iavor I., David Simchi-Levi, and Jinglong Zhao. "Design and Analysis of Switchback Experiments." Management Science 69, no. 7 (July 2023): 3759–3777.
- Article
Learning Through Noticing: Theory and Evidence from a Field Experiment
By: Rema Hanna, Sendhil Mullainathan and Joshua Schwartzstein
We consider a model of technological learning under which people "learn through noticing": they choose which input dimensions to attend to and subsequently learn about from available data. Using this model, we show how people with a great deal of experience may... View Details
Hanna, Rema, Sendhil Mullainathan, and Joshua Schwartzstein. "Learning Through Noticing: Theory and Evidence from a Field Experiment." Quarterly Journal of Economics 129, no. 3 (August 2014): 1311–1353. (Online Appendix.)
- 25 Sep 2012
- Working Paper Summaries
Colocation and Scientific Collaboration: Evidence from a Field Experiment
- January 2024
- Article
Investing with the Government: A Field Experiment in China
By: Emanuele Colonnelli, Bo Li and Ernest Liu
We study the demand for government participation in China’s venture capital and private equity market. We conduct a large-scale, non-deceptive field experiment in collaboration with the leading industry service provider, through which we survey both capital investors... View Details
Keywords: Venture Capital; Private Equity; Business and Government Relations; Entrepreneurship; China
Colonnelli, Emanuele, Bo Li, and Ernest Liu. "Investing with the Government: A Field Experiment in China." Journal of Political Economy 132, no. 1 (January 2024): 248–294.
- 2025
- Article
Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments
By: Kosuke Imai and Michael Lingzhi Li
Researchers are increasingly turning to machine learning (ML) algorithms to investigate causal heterogeneity in randomized experiments. Despite their promise, ML algorithms may fail to accurately ascertain heterogeneous treatment effects under practical settings with... View Details
Imai, Kosuke, and Michael Lingzhi Li. "Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments." Journal of Business & Economic Statistics 43, no. 1 (2025): 256–268.
- 2023
- Working Paper
Culture as a Signal: Evidence from a Natural Field Experiment
By: Wei Cai, Dennis Campbell and Jiehang Yu
The importance of culture as an informal management control system is increasingly acknowledged in academia. While prior research mainly focuses on the value of culture on internal stakeholders (e.g., employees), we examine whether culture serves as a credible signal... View Details
Cai, Wei, Dennis Campbell, and Jiehang Yu. "Culture as a Signal: Evidence from a Natural Field Experiment." SSRN Working Paper Series, No. 4447603, May 2023.
- 2020
- Working Paper
Recognition Incentives for Internal Crowdsourcing: A Field Experiment at NASA
By: Jana Gallus, Olivia S. Jung and Karim R. Lakhani
What might motivate employees to participate in internal crowdsourcing, a peer-based approach to innovation? Should organizations use incentives that are congruent with their established hierarchical structures, or should they use incentives that are aligned with the... View Details
Keywords: Online Platforms; Employee Engagement; Managerial Recognition; Innovation and Management; Employees; Motivation and Incentives
Gallus, Jana, Olivia S. Jung, and Karim R. Lakhani. "Recognition Incentives for Internal Crowdsourcing: A Field Experiment at NASA." Harvard Business School Working Paper, No. 20-059, November 2019. (Revised May 2020.)
- January 2008
- Article
Nonemployment Stigma as Rational Herding: A Field Experiment
Long spells of unemployment are known to reduce the likelihood of re-employment, but it is difficult to discern the reasons for this observation. Using an experimental method that controls for search intensity and possible discouragement of job applicants, I document... View Details
Keywords: Job Search; Job Cuts and Outsourcing; Employment; Cognition and Thinking; Perception; Creativity; Human Needs; Job Interviews; Selection and Staffing; Recruitment; Managerial Roles; Judgments; Employment Industry
Oberholzer-Gee, Felix. "Nonemployment Stigma as Rational Herding: A Field Experiment." Journal of Economic Behavior & Organization 65, no. 1 (January 2008): 30–40.
- October–December 2022
- Article
Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem
By: Mochen Yang, Edward McFowland III, Gordon Burtch and Gediminas Adomavicius
Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data, followed... View Details
Keywords: Machine Learning; Econometric Analysis; Instrumental Variable; Random Forest; Causal Inference; AI and Machine Learning; Forecasting and Prediction
Yang, Mochen, Edward McFowland III, Gordon Burtch, and Gediminas Adomavicius. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem." INFORMS Journal on Data Science 1, no. 2 (October–December 2022): 138–155.
- 2020
- Book
The Power of Experiments: Decision-Making in a Data-Driven World
By: Michael Luca and Max H. Bazerman
Have you logged into Facebook recently? Searched for something on Google? Chosen a movie on Netflix? If so, you've probably been an unwitting participant in a variety of experiments—also known as randomized controlled trials—designed to test the impact of changes to an... View Details
Keywords: Experiments; Randomized Controlled Trials; Organizations; Decision Making; Analytics and Data Science; Management Analysis, Tools, and Techniques
Luca, Michael, and Max H. Bazerman. The Power of Experiments: Decision-Making in a Data-Driven World. Cambridge, MA: MIT Press, 2020.