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Show Results For
- All HBS Web
(4,020)
- People (2)
- News (556)
- Research (2,855)
- Events (51)
- Multimedia (21)
- Faculty Publications (2,057)
- November 1975
- Article
Theory of Finance from the Perspective of Continuous Time
By: Robert C. Merton
Merton, Robert C. "Theory of Finance from the Perspective of Continuous Time." Journal of Financial and Quantitative Analysis 10 (November 1975): 659–674.
- 1983
- Working Paper
A Theory of Bargaining with Monetary Transfers
By: Jerry R. Green
Green, Jerry R. "A Theory of Bargaining with Monetary Transfers." Harvard Institute of Economic Research Discussion Paper, No. 966, February 1983.
- July 1975
- Article
An Asymptotic Theory of Growth Under Uncertainty
By: Robert C. Merton
Merton, Robert C. "An Asymptotic Theory of Growth Under Uncertainty." Review of Economic Studies 42, no. 3 (July 1975): 375–393. (Chapter 17 in Continuous-Time Finance.)
- TeachingInterests
Interpretability and Explainability in Machine Learning
As machine learning models are increasingly being employed to aid decision makers in high-stakes settings such as healthcare and criminal justice, it is important to ensure that the decision makers correctly understand and consequent trust the functionality of these... View Details
- 2013
- Working Paper
Imprinting: Toward A Multilevel Theory
By: Christopher Marquis and Andras Tilcsik
The concept of imprinting has attracted considerable interest in numerous fields—including organizational ecology, institutional theory, network analysis, and career research—and has been applied at several levels of analysis, from the industry to the individual. This... View Details
Marquis, Christopher, and Andras Tilcsik. "Imprinting: Toward A Multilevel Theory." Harvard Business School Working Paper, No. 13-061, January 2013. (Forthcoming in Academy of Management Annals.)
Imprinting: Toward A Multilevel Theory
The concept of imprinting has attracted considerable interest in numerous fields—including organizational ecology, institutional theory, network analysis, and career research—and has been applied at several levels of analysis, from the industry to the individual.... View Details
- April 2016 (Revised April 2017)
- Case
Reimagining Capitalism: Towards a Theory of Change
By: Rebecca Henderson, Tony L. He and Brian Tomlinson
Henderson, Rebecca, Tony L. He, and Brian Tomlinson. "Reimagining Capitalism: Towards a Theory of Change." Harvard Business School Case 316-162, April 2016. (Revised April 2017.)
- 1998
- Chapter
A Theory of the Firm's Knowledge-Creation Dynamics
By: Ikujiro Nonaka and Hirotaka Takeuchi
- January 2006
- Article
The Ongoing Process of Building a Theory of Disruption
By: Clayton M. Christensen
Christensen, Clayton M. "The Ongoing Process of Building a Theory of Disruption." Journal of Product Innovation Management 23 (January 2006): 39–55.
- 2010
- Book
Government and Markets: Toward a New Theory of Regulation
By: Edward J. Balleisen and David A. Moss
After two generations of emphasis on governmental inefficiency and the need for deregulation, we now see growing interest in the possibility of constructive governance, alongside public calls for new, smarter regulation. Yet there is a real danger that regulatory... View Details
Keywords: Governing Rules, Regulations, and Reforms; Government and Politics; Markets; Business and Government Relations; Research
Balleisen, Edward J., and David A. Moss, eds. Government and Markets: Toward a New Theory of Regulation. Cambridge: Cambridge University Press, 2010.
- 02–03 Dec 2022
- HBS Alumni Events
D^3 Catalyst: No Code Machine Learning and Artificial Intelligence
Do you want to delve into Machine Learning and Artificial Intelligence, but you feel overwhelmed and intimidated? Do you want to leverage the power of Machine Learning and Artificial Intelligence without writing any code? Do you want to leverage Machine Learning and... View Details
Government and Markets: Toward a New Theory of Regulation
As the financial crisis has shown, neither traditional market failure models nor public choice theory, by themselves, sufficiently inform or explain our current regulatory challenges, nor point us toward the best solutions. Regulatory studies, long neglected in an... View Details
- 2021
- Working Paper
Time and the Value of Data
By: Ehsan Valavi, Joel Hestness, Newsha Ardalani and Marco Iansiti
Managers often believe that collecting more data will continually improve the accuracy of their machine learning models. However, we argue in this paper that when data lose relevance over time, it may be optimal to collect a limited amount of recent data instead of... View Details
Keywords: Economics Of AI; Machine Learning; Non-stationarity; Perishability; Value Depreciation; Analytics and Data Science; Value
Valavi, Ehsan, Joel Hestness, Newsha Ardalani, and Marco Iansiti. "Time and the Value of Data." Harvard Business School Working Paper, No. 21-016, August 2020. (Revised November 2021.)
- 01 Oct 1997
- News
Theory & Practice
analyses of competitive interaction to explore the uses and limits of game theory as a tool for students of business strategy. As a basis for... View Details
- August 2023 (Revised December 2023)
- Case
Automating Morality: Ethics for Intelligent Machines
By: Joseph L. Badaracco Jr. and Tom Quinn
As autonomy became a more significant part of modern life – most notably in autonomous vehicles (AVs), such as Teslas – ethical debates about whether and how to impart ethics to machines heated up. Utilitarians pointed out that autonomous vehicles crashed much less... View Details
Keywords: Cost vs Benefits; Judgments; Fairness; Moral Sensibility; Values and Beliefs; Cross-Cultural and Cross-Border Issues; Disruptive Innovation; Technology Adoption; Risk and Uncertainty; Cognition and Thinking; Technological Innovation; Auto Industry; Technology Industry; Africa; Asia; Europe; North and Central America; Oceania; South America
Badaracco, Joseph L., Jr., and Tom Quinn. "Automating Morality: Ethics for Intelligent Machines." Harvard Business School Case 324-007, August 2023. (Revised December 2023.)
- April 2020
- Article
A Theory of Experimenters: Robustness, Randomization, and Balance
By: Abhijit Banerjee, Sylvain Chassang, Sergio Montero and Erik Snowberg
This paper studies the problem of experiment design by an ambiguity-averse decisionmaker who trades off subjective expected performance against robust performance guarantees. This framework accounts for real-world experimenters’ preference for randomization. It also... View Details
Banerjee, Abhijit, Sylvain Chassang, Sergio Montero, and Erik Snowberg. "A Theory of Experimenters: Robustness, Randomization, and Balance." American Economic Review 110, no. 4 (April 2020): 1206–1230.
- November 2023
- Case
Open Source Machine Learning at Google
Set in early 2023, the case exposes students to the challenges of managing open source software at Google. The case focuses on the challenges for Alex Spinelli, Vice President of Product Management for Core Machine Learning. He must set priorities for Google’s efforts... View Details
Keywords: Decision Choices and Conditions; Technological Innovation; Open Source Distribution; Strategy; AI and Machine Learning; Applications and Software; Technology Industry; United States
Greenstein, Shane, Martin Wattenberg, Fernanda B. Viégas, Daniel Yue, and James Barnett. "Open Source Machine Learning at Google." Harvard Business School Case 624-015, November 2023.
- Article
How Actors Change Institutions: Towards a Theory of Institutional Entrepreneurship
By: Julie Battilana, Bernard Leca and Eva Boxenbaum
As well as review the literature on the notion of institutional entrepreneurship introduced by Paul DiMaggio in 1988, we propose a model of the process of institutional entrepreneurship. We first present theoretical and definitional issues associated with the concept... View Details
Keywords: Change; Corporate Entrepreneurship; Framework; Research; Theory; Organizations; Management Practices and Processes
Battilana, Julie, Bernard Leca, and Eva Boxenbaum. "How Actors Change Institutions: Towards a Theory of Institutional Entrepreneurship." Academy of Management Annals 3 (2009): 65–107.
- Article
Productivity and Selection of Human Capital with Machine Learning
By: Aaron Chalfin, Oren Danieli, Andrew Hillis, Zubin Jelveh, Michael Luca, Jens Ludwig and Sendhil Mullainathan
Keywords: Analytics and Data Science; Selection and Staffing; Performance Productivity; Mathematical Methods; Policy
Chalfin, Aaron, Oren Danieli, Andrew Hillis, Zubin Jelveh, Michael Luca, Jens Ludwig, and Sendhil Mullainathan. "Productivity and Selection of Human Capital with Machine Learning." American Economic Review: Papers and Proceedings 106, no. 5 (May 2016): 124–127.