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  • 2014
  • Book

Own Your Future: How to Think Like an Entrepreneur and Thrive in an Unpredictable Economy

By: Paul B. Brown, Charles F. Kiefer and Leonard A. Schlesinger
It used to be that if you studied and worked hard, you could be assured of an extremely satisfying career. But in a world of constant layoffs and dying industries, it has become increasingly difficult to "plan" your way to success. So what is the solution? Well, when... View Details
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Brown, Paul B., Charles F. Kiefer, and Leonard A. Schlesinger. Own Your Future: How to Think Like an Entrepreneur and Thrive in an Unpredictable Economy. New York, NY: AMACOM, 2014.
  • 2022
  • Chapter

Of Learning and Forgetting: Centrism, Populism, and the Legitimacy Crisis of Globalization

By: Rawi Abdelal
Every order is a bargain with disappointments and trade-offs. Thus is every order an unstable equilibrium. The first era of globalization, circa 1870–1914, created both international prosperity and domestic instability. That instability was fully realized during the... View Details
Keywords: Globalization; Policy; Economic Systems; Balance and Stability; Europe; European Union; United States
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Abdelal, Rawi. "Of Learning and Forgetting: Centrism, Populism, and the Legitimacy Crisis of Globalization." In The Downfall of the American Order? edited by Peter J. Katzenstein and Jonathan Kirshner, 105–123. Ithaca, NY: Cornell University Press, 2022.
  • August 2023
  • Article

Explaining Machine Learning Models with Interactive Natural Language Conversations Using TalkToModel

By: Dylan Slack, Satyapriya Krishna, Himabindu Lakkaraju and Sameer Singh
Practitioners increasingly use machine learning (ML) models, yet models have become more complex and harder to understand. To understand complex models, researchers have proposed techniques to explain model predictions. However, practitioners struggle to use... View Details
Keywords: AI and Machine Learning; Technological Innovation; Technology Adoption
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Slack, Dylan, Satyapriya Krishna, Himabindu Lakkaraju, and Sameer Singh. "Explaining Machine Learning Models with Interactive Natural Language Conversations Using TalkToModel." Nature Machine Intelligence 5, no. 8 (August 2023): 873–883.
  • 2021
  • Chapter

Towards a Unified Framework for Fair and Stable Graph Representation Learning

By: Chirag Agarwal, Himabindu Lakkaraju and Marinka Zitnik
As the representations output by Graph Neural Networks (GNNs) are increasingly employed in real-world applications, it becomes important to ensure that these representations are fair and stable. In this work, we establish a key connection between counterfactual... View Details
Keywords: Graph Neural Networks; AI and Machine Learning; Prejudice and Bias
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Agarwal, Chirag, Himabindu Lakkaraju, and Marinka Zitnik. "Towards a Unified Framework for Fair and Stable Graph Representation Learning." In Proceedings of the 37th Conference on Uncertainty in Artificial Intelligence, edited by Cassio de Campos and Marloes H. Maathuis, 2114–2124. AUAI Press, 2021.
  • 2021
  • Working Paper

Once Bitten, Twice Shy: Learning from Corporate Fraud and Corporate Governance Spillovers

By: Trung Nguyen
This paper finds that investors learn from their experience with corporate fraud and financial misconduct and modify their investment behavior to avoid suspicious firms and increase corporate governance efforts. More specially, mutual funds that experienced corporate... View Details
Keywords: Institutional Investors; Investor Experience; Shareholder Voting; Corporate Fraud; Corporate Governance; Institutional Investing; Behavior; Change; Learning
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Nguyen, Trung. "Once Bitten, Twice Shy: Learning from Corporate Fraud and Corporate Governance Spillovers." Harvard Business School Working Paper, No. 21-135, June 2021.
  • 29 Jul 2014
  • Working Paper Summaries

Learning from the Kursk Submarine Rescue Failure: The Case for Pluralistic Risk Management

Keywords: by Anette Mikes & Amram Migdal
  • 2024
  • Working Paper

Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization

By: Ta-Wei Huang, Eva Ascarza and Ayelet Israeli
This paper introduces Incrementality Representation Learning (IRL), a novel multitask representation learning framework that predicts heterogeneous causal effects of marketing interventions. By leveraging past experiments, IRL efficiently designs and targets... View Details
Keywords: Heterogeneous Treatment Effect; Multi-task Learning; Representation Learning; Personalization; Promotion; Deep Learning; Field Experiments; Customer Focus and Relationships; Customization and Personalization
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Huang, Ta-Wei, Eva Ascarza, and Ayelet Israeli. "Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization." Harvard Business School Working Paper, No. 24-076, June 2024.
  • July 2024
  • Article

Mass General Brigham’s Patient-Reported Outcomes Measurement System: A Decade of Learnings

By: Jason B. Liu, Robert S. Kaplan, David W. Bates, Mario O. Edelen, Rachel C. Sisodia and Andrea L. Pusic
This article describes the strategies that leaders at the Mass General Brigham (MGB) health system have used in launching a standardized patient-reported outcome measure (PROM) collection program in 2012, a major step in the value-based transformation of health care.... View Details
Keywords: Patient-reported Outcomes; Value Based Health Care; Health Care and Treatment; Transformation; Outcome or Result; Organizational Change and Adaptation; Performance Improvement; Health Industry
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Liu, Jason B., Robert S. Kaplan, David W. Bates, Mario O. Edelen, Rachel C. Sisodia, and Andrea L. Pusic. "Mass General Brigham’s Patient-Reported Outcomes Measurement System: A Decade of Learnings." NEJM Catalyst Innovations in Care Delivery 5, no. 7 (July 2024).
  • Article

Learning from Potentially Biased Statistics: Household Inflation Perceptions and Expectations in Argentina

By: Alberto Cavallo, Guillermo Cruces and Ricardo Perez-Truglia
When forming expectations, households may be influenced by perceived bias in the information they receive. In this paper, we study how individuals learn from potentially biased statistics using data from both a natural experiment and a survey experiment during a... View Details
Keywords: Inflation Expectations; Bayesian Estimation; Inflation and Deflation; Information; Household; Behavior; Argentina
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Cavallo, Alberto, Guillermo Cruces, and Ricardo Perez-Truglia. "Learning from Potentially Biased Statistics: Household Inflation Perceptions and Expectations in Argentina." Brookings Papers on Economic Activity (Spring 2016): 59–108.
  • 2023
  • Book

How the Harvard Business School Changed the Way We View Organizations

By: Jay W. Lorsch
The story of the field of organizational behavior (which overlaps considerably with the origin story of Harvard Business School) and how it created the “medical model” of systems thinking—anchored in the practices of listening, observing, testing, and only then... View Details
Keywords: Organizational Behavior; Systems Thinking; Medical Model; Organizations; Behavior; System; History
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Lorsch, Jay W. How the Harvard Business School Changed the Way We View Organizations. Business Expert Press, 2023.
  • January 2010
  • Case

Pratham - Every Child in School and Learning Well

By: Srikant M. Datar, Stacey M. Childress, Rachna Tahilyani and Anjali Raina
The case focuses on how Pratham, a non-governmental organization, provided quality education to underprivileged children in India by collaborating with the government. It focuses on the problem Madhav Chavan, the founder, is trying to solve, the contributing factors... View Details
Keywords: Non-Governmental Organizations; Collaborative Innovation and Invention; Social and Collaborative Networks; Performance Evaluation; Change Management; Organizational Design; Early Childhood Education; Management Systems; Strategy; Quality; Education Industry; India
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Datar, Srikant M., Stacey M. Childress, Rachna Tahilyani, and Anjali Raina. "Pratham - Every Child in School and Learning Well." Harvard Business School Case 110-001, January 2010.
  • 2007
  • Working Paper

Acting Globally but Thinking Locally? The Influence of Local Communities on Organizations

By: Christopher Marquis and Julie Battilana
We develop an institutional theory of how local communities continue to matter for organizations, and why community factors are particularly important in a global age. Since globalization has taken center stage in both practitioner and academic circles, research has... View Details
Keywords: Geographic Location; Local Range; Globalization; Organizational Change and Adaptation; Business and Community Relations; Power and Influence
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Marquis, Christopher, and Julie Battilana. "Acting Globally but Thinking Locally? The Influence of Local Communities on Organizations." Harvard Business School Working Paper, No. 08-034, November 2007.
  • July 2008
  • Exercise

Information Use by Managers in Decision Making: A Team Exercise

By: Amy C. Edmondson and Ann Cullen
The purpose of this exercise is to explore the challenges of information collection and analysis. Students will, experientially, gain insights into how information is used and be exposed to a framework for identifying and evaluating information. In addition, the... View Details
Keywords: Competency and Skills; Decision Making; Knowledge Use and Leverage; Managerial Roles; Business Processes; Groups and Teams
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Edmondson, Amy C., and Ann Cullen. "Information Use by Managers in Decision Making: A Team Exercise." Harvard Business School Exercise 609-027, July 2008.
  • 2004
  • Article

Teaching Students How to Reason Well by Analogy

By: Giovanni Gavetti and Jan Rivkin
Keywords: Teaching; Cognition and Thinking
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Gavetti, Giovanni, and Jan Rivkin. "Teaching Students How to Reason Well by Analogy." Journal of Strategic Management Education 1, no. 2 (2004).
  • 2018
  • Working Paper

Forecasting Airport Transfer Passenger Flow Using Real-Time Data and Machine Learning

By: Xiaojia Guo, Yael Grushka-Cockayne and Bert De Reyck
Problem definition: In collaboration with Heathrow Airport, we develop a predictive system that generates quantile forecasts of transfer passengers’ connection times. Sampling from the distribution of individual passengers’ connection times, the system also produces... View Details
Keywords: Quantile Forecasts; Regression Tree; Copula; Passenger Flow Management; Data-driven Operations; Forecasting and Prediction; Data and Data Sets
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Guo, Xiaojia, Yael Grushka-Cockayne, and Bert De Reyck. "Forecasting Airport Transfer Passenger Flow Using Real-Time Data and Machine Learning." Harvard Business School Working Paper, No. 19-040, October 2018.
  • June 2011
  • Article

Stepping into the Unknown: How Companies Learn through Risk Management

By: Anette Mikes
Risk management can add value through the continuous questioning of existing controls, strategies, and scenarios. The article outlines a new framework for risk management predicated on the notion of organizational learning, and illustrates it by a case study of a... View Details
Keywords: Learning; Framework; Governance Controls; Risk Management; Organizational Change and Adaptation
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Mikes, Anette. "Stepping into the Unknown: How Companies Learn through Risk Management." FS Focus 50 (June 2011): 22–25.
  • August 2021
  • Article

Crowdsourcing Memories: Mixed Methods Research by Cultural Insiders-Epistemological Outsiders

By: Tarun Khanna, Karim R. Lakhani, Shubhangi Bhadada, Nabil Khan, Saba Kohli Davé, Rasim Alam and Meena Hewett
This paper examines the role that the two lead authors’ personal connections played in the research methodology and data collection for the Partition Stories Project—a mixed-methods approach to revisiting the much-studied historical trauma of the Partition of British... View Details
Keywords: Mixed Methods; Insider-outsiders; Myth Of Informed Objectivity; Hybrid Research; Oral Narratives; Research; Analysis; India
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Khanna, Tarun, Karim R. Lakhani, Shubhangi Bhadada, Nabil Khan, Saba Kohli Davé, Rasim Alam, and Meena Hewett. "Crowdsourcing Memories: Mixed Methods Research by Cultural Insiders-Epistemological Outsiders." Academy of Management Perspectives 35, no. 3 (August 2021): 384–399.
  • March 1, 2022
  • Article

Widespread Use of National Academies Consensus Reports by the American Public

By: Diana Hicks, Matteo Zullo, Ameet Doshi and Omar Isaac Asensio
In seeking to understand how to protect the public information sphere from corruption, researchers understandably focus on dysfunction. However, parts of the public information ecosystem function very well, and understanding this as well will help in protecting and... View Details
Keywords: Reports; Surveys; AI and Machine Learning; Knowledge Dissemination; Knowledge Use and Leverage
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Hicks, Diana, Matteo Zullo, Ameet Doshi, and Omar Isaac Asensio. "Widespread Use of National Academies Consensus Reports by the American Public." e2107760119. Proceedings of the National Academy of Sciences 119, no. 9 (March 1, 2022).
  • December 2015
  • Case

IDEO: Human-Centered Service Design

By: Ryan W. Buell and Andrew Otazo
The case describes IDEO, one of the world's leading design firms, and its human-centered innovation culture and processes. It is an example of what managers can do to make their own organizations more innovative. In reaction to a rapidly changing competitive landscape,... View Details
Keywords: Design Thinking; Innovation; Service Management; Service; Design; Service Delivery; Innovation and Management; Entertainment and Recreation Industry; Peru
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Buell, Ryan W., and Andrew Otazo. "IDEO: Human-Centered Service Design." Harvard Business School Multimedia/Video Case 615-703, December 2015.
  • Working Paper

Visual Uniqueness in Peer-to-Peer Marketplaces: Machine Learning Model Development, Validation, and Application

By: Flora Feng, Charis Li and Shunyuan Zhang
Peer-to-peer (P2P) marketplaces have seen exponential growth in recent years featured by unique offerings from individual providers. Despite the perceived value of uniqueness, scalable quantification of visual uniqueness in P2P platforms like Airbnb has been largely... View Details
Keywords: Peer-to-peer Markets; Marketplace Matching; AI and Machine Learning; Demand and Consumers; Digital Platforms; Marketing
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Feng, Flora, Charis Li, and Shunyuan Zhang. "Visual Uniqueness in Peer-to-Peer Marketplaces: Machine Learning Model Development, Validation, and Application." SSRN Working Paper Series, No. 4665286, February 2024.
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