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Show Results For
- All HBS Web
(5,256)
- People (9)
- News (1,165)
- Research (2,876)
- Events (31)
- Multimedia (20)
- Faculty Publications (1,514)
Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem
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,... View Details
- Web
Ways to Give Today - Alumni
Fund There are two ways you can make a gift through your donor-advised fund: Support HBS now by recommending a grant to Harvard Business School (legal name: “President and Fellows of Harvard College”). Support HBS in the future View Details
- Research Summary
Research Summary
By: Ranjay Gulati
My research focuses on how to unlock organizational potential and unleash human potential.
Unlocking organizational potential involves a deep dive into how enterprises can achieve enduring success. This includes applying strategic frameworks to drive... View Details
- 2008
- Working Paper
Finding Missing Markets (and a disturbing epilogue): Evidence from an Export Crop Adoption and Marketing Intervention in Kenya
By: Nava Ashraf, Xavier Gine and Dean Karlan
In much of the developing world, many farmers grow crops for local or personal consumption despite export options which appear to be more profitable. Thus many conjecture that one or several markets are missing. We report here on a randomized controlled trial conducted... View Details
Keywords: Agribusiness; Developing Countries and Economies; Trade; Profit; Product Marketing; Standards; Failure; Risk and Uncertainty; Non-Governmental Organizations; Agriculture and Agribusiness Industry; Service Industry; Kenya; Europe
Ashraf, Nava, Xavier Gine, and Dean Karlan. "Finding Missing Markets (and a disturbing epilogue): Evidence from an Export Crop Adoption and Marketing Intervention in Kenya." Harvard Business School Working Paper, No. 08-065, February 2008. (forthcoming, American Journal of Agricultural Economics.)
- 20 Aug 2013
- First Look
First Look: August 20
challenge to centuries-long traditions in design and construction that green building represents. The contributors consider the changes associated with green building through a sociological and organizational lens. They discuss shifts in... View Details
Keywords: Anna Secino
- 07 Oct 2014
- First Look
First Look: October 7
Experiment in Computational Biology By: Boudreau, Kevin J., and Karim Lakhani Abstract—Most of society's innovation systems―academic science, the patent system, open source, etc.―are "open" in the sense that they are designed to... View Details
Keywords: Sean Silverthorne
- September 2020
- Case
Uber at a Crossroads (2017)
By: Ramon Casadesus-Masanell and Karen Elterman
This case describes the history of Uber, its business model—including the ways it differed from that of the traditional taxi industry—and its competition with Lyft. The case is set in 2017, a year in which Uber was plagued by even more scandals than usual, though its... View Details
Keywords: Business Startups; Business Model; Customer Satisfaction; Fairness; Values and Beliefs; Price; Profit; Revenue; Investment; Government Legislation; Business History; Compensation and Benefits; Resignation and Termination; Employment; Wages; Lawfulness; Leadership Style; Leading Change; Management Style; Market Entry and Exit; Digital Platforms; Product Design; Organizational Culture; Problems and Challenges; Attitudes; Strategy; Competitive Strategy; Expansion; Transportation Networks; Mobile and Wireless Technology; Valuation; Transportation Industry; Technology Industry; United States
Casadesus-Masanell, Ramon, and Karen Elterman. "Uber at a Crossroads (2017)." Harvard Business School Case 721-376, September 2020.
- 11 Jan 2011
- First Look
First Look: Jan. 11
painful, difficult journey. It's trial and error, endless effort, and slowly acquired personal insight. Many managers never complete the journey. At best, they just learn to get by. At worst, they become terrible bosses. This new book explains how to avoid that fate... View Details
Keywords: Sean Silverthorne
- October 2023
- Case
CornerUp: Digitizing the Corner Store
By: Álvaro Rodríguez Arregui, Stacy Straaberg and Diego Zainos De La Sota Riva
In July 2023, Jason Diaz, co-founder and CEO of CornerUp, assessed the progress of his business-to-business e-procurement software application (app) startup, founded in January 2022. CornerUp began as a fast-moving consumer packaged goods (FMCG) distributor in New York... View Details
Keywords: Business Growth and Maturation; Business Startups; Small Business; Transition; Decisions; Social Entrepreneurship; Geographic Location; Disruptive Innovation; Market Participation; Digital Platforms; Trust; Business Strategy; Expansion; Information Infrastructure; Internet and the Web; Technology Adoption; Value Creation; Technology Industry; United States
The Execution Premium: Linking Strategy to Operations for Competitive Advantage
From HBSP: " In a world of stiffening competition, business strategy is more crucial than ever. Yet most organizations struggle in this area--not with formulating strategy but with executing it, or putting their... View Details
- Program
Compensation Committees
Summary Executive compensation has become a flashpoint issue for board members, institutional investors, regulators, and the media. Examining critical market and regulatory issues, this board leadership program enables compensation committee chairs and members to View Details
- 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.
Warnings and Endorsements: Improving Human-AI Collaboration in the Presence of Outliers
1. Problem definition: While artificial intelligence (AI) algorithms may perform well on data that are representative of the training set (inliers), they may err when extrapolating on non-representative data (outliers). How can humans and algorithms work together to... View Details
- Web
Leadership Initiative - Leadership
to Watch.” She was named by Thinkers50 as one of the top ten management thinkers in the world in 2013 and 2021 and received the Thinkers50 Innovation Award in 2015. Hill’s Collective Genius has also been named to the inaugural Thinkers50... View Details
- Program
Audit Committees in a New Era of Governance
Education program on the HBS campus, you enter an immersive experience where every aspect of the learning model has been carefully designed to facilitate your growth. Your learning will take place on your own, in your living group, and in... View Details
- 30 Mar 2021
- Blog Post
Africa Rising: Understanding Business, Entrepreneurship, and the Complexities of a Continent with Professor Hakeem Belo-Osagie
a faculty member’s area of expertise or passion. We caught up with Professor Hakeem Belo-Osagie, who taught the Africa Rising: Understanding Business, Entrepreneurship, and the Complexities of a Continent. This course was designed to... View Details
Accuracy Obsession: Humans Prioritize Immaterial AI Accuracy Over Their Own Compensation — Unless We Educate Them
1. Problem definition: Accuracy isn't everything. In many contexts, high or low sensitivity is more important than overall correctness — and yet, we find that humans prefer accurate algorithms, even to their detriment. Specifically, we identify and address an... View Details
- 2024
- Working Paper
Social Movements and Public Opinion in the United States
By: Amory Gethin and Vincent Pons
Recent social movements stand out by their spontaneous nature and lack of stable leadership, raising doubts on their ability to generate political change. This article provides systematic evidence on the effects of protests on public opinion and political attitudes.... View Details
Gethin, Amory, and Vincent Pons. "Social Movements and Public Opinion in the United States." NBER Working Paper Series, No. 32342, April 2024.
- July 2024
- Article
Chatbots and Mental Health: Insights into the Safety of Generative AI
By: Julian De Freitas, Ahmet Kaan Uğuralp, Zeliha Uğuralp and Stefano Puntoni
Chatbots are now able to engage in sophisticated conversations with consumers. Due to the ‘black box’ nature of the algorithms, it is impossible to predict in advance how these conversations will unfold. Behavioral research provides little insight into potential safety... View Details
Keywords: Autonomy; Chatbots; New Technology; Brand Crises; Mental Health; Large Language Model; AI and Machine Learning; Behavior; Well-being; Technological Innovation; Ethics
De Freitas, Julian, Ahmet Kaan Uğuralp, Zeliha Uğuralp, and Stefano Puntoni. "Chatbots and Mental Health: Insights into the Safety of Generative AI." Journal of Consumer Psychology 34, no. 3 (July 2024): 481–491.
- 2021
- Working Paper
Population Interference in Panel Experiments
By: Iavor I Bojinov, Kevin Wu Han and Guillaume Basse
The phenomenon of population interference, where a treatment assigned to one experimental unit affects another experimental unit's outcome, has received considerable attention in standard randomized experiments. The complications produced by population interference in... View Details
Bojinov, Iavor I., Kevin Wu Han, and Guillaume Basse. "Population Interference in Panel Experiments." Harvard Business School Working Paper, No. 21-100, March 2021.