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  • All HBS Web  (160)
    • News  (38)
    • Research  (60)
    • Events  (1)
  • Faculty Publications  (18)

Show Results For

  • All HBS Web  (160)
    • News  (38)
    • Research  (60)
    • Events  (1)
  • Faculty Publications  (18)
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  • 2025
  • Working Paper

Dynamic Personalization with Multiple Customer Signals: Multi-Response State Representation in Reinforcement Learning

By: Liangzong Ma, Ta-Wei Huang, Eva Ascarza and Ayelet Israeli
Reinforcement learning (RL) offers potential for optimizing sequences of customer interactions by modeling the relationships between customer states, company actions, and long-term value. However, its practical implementation often faces significant challenges.... View Details
Keywords: Dynamic Policy; Deep Reinforcement Learning; Representation Learning; Dynamic Difficulty Adjustment; Latent Variable Models; Customer Relationship Management; Customer Value and Value Chain; Foreign Direct Investment; Analytics and Data Science
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Ma, Liangzong, Ta-Wei Huang, Eva Ascarza, and Ayelet Israeli. "Dynamic Personalization with Multiple Customer Signals: Multi-Response State Representation in Reinforcement Learning." Harvard Business School Working Paper, No. 25-037, February 2025.
  • 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.
  • 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.
  • 2022
  • Working Paper

Product2Vec: Leveraging Representation Learning to Model Consumer Product Choice in Large Assortments

By: Fanglin Chen, Xiao Liu, Davide Proserpio and Isamar Troncoso
We propose a method, Product2Vec, based on representation learning, that can automatically learn latent product attributes that drive consumer choices, to study product-level competition when the number of products is large. We demonstrate Product2Vec’s... View Details
Keywords: Consumer Choice; Consumer Behavior; Competition; Product Marketing
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Chen, Fanglin, Xiao Liu, Davide Proserpio, and Isamar Troncoso. "Product2Vec: Leveraging Representation Learning to Model Consumer Product Choice in Large Assortments." NYU Stern School of Business Research Paper Series, July 2022.
  • December 2023
  • Article

Self-Orienting in Human and Machine Learning

By: Julian De Freitas, Ahmet Uğuralp, Zeliha Uğuralp, Laurie Paul, Joshua B. Tenenbaum and T. Ullman
A current proposal for a computational notion of self is a representation of one’s body in a specific time and place, which includes the recognition of that representation as the agent. This turns self-representation into a process of self-orientation, a challenging... View Details
Keywords: AI and Machine Learning; Behavior; Learning
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De Freitas, Julian, Ahmet Uğuralp, Zeliha Uğuralp, Laurie Paul, Joshua B. Tenenbaum, and T. Ullman. "Self-Orienting in Human and Machine Learning." Nature Human Behaviour 7, no. 12 (December 2023): 2126–2139.
  • June 2024
  • Article

Rationalizing Outcomes: Interdependent Learning in Competitive Markets

By: Anoop R. Menon and Dennis Yao
In this article we use simulation models to explore interdependent learning in competitive markets. Such interactions require attention to both the mental representations held by the management of the focal firm as well as the beliefs of that management about the... View Details
Keywords: Mental Models; Strategic Interactions; Rationalization; Explanation-based View; Competition
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Menon, Anoop R., and Dennis Yao. "Rationalizing Outcomes: Interdependent Learning in Competitive Markets." Strategy Science 9, no. 2 (June 2024): 97–117.
  • 2008
  • Chapter

Learning in Environmental Policymaking and Implementation

By: Alnoor Ebrahim
This paper explores how "learning" occurs in the context of environmental policy formulation and implementation. Rather than viewing policy learning as a rational and technocratic process, the emphasis here is on the political and institutional contexts within which... View Details
Keywords: Learning; Corporate Accountability; Policy; Government and Politics; Business and Stakeholder Relations; Natural Environment; Power and Influence; South Africa; Brazil
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Ebrahim, Alnoor. "Learning in Environmental Policymaking and Implementation." In Strategic Environmental Assessment for Policies: An Instrument for Good Governance, edited by Kulsum Ahmed and Ernesto Sanchez-Triana. Washington, D.C.: World Bank, 2008. (Was HBS Working Paper 08-071.)
  • 2008
  • Working Paper

Learning Processes in Environmental Policy Making and Implementation

By: Alnoor Ebrahim
This paper explores how "learning" occurs in the context of environmental policy formulation and implementation. Rather than viewing policy learning as a rational and technocratic process, the emphasis here is on the political and institutional contexts within which... View Details
Keywords: Policy; Business and Government Relations; Natural Environment; Power and Influence; South Africa; Brazil
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Ebrahim, Alnoor. "Learning Processes in Environmental Policy Making and Implementation." Harvard Business School Working Paper, No. 08-071, February 2008.
  • 2012
  • Working Paper

An Outside-Inside Evolution in Gender and Professional Work

By: Lakshmi Ramarajan, Kathleen McGinn and Deborah Kolb
We study the process by which a professional service firm reshaped its activities and beliefs over nearly two decades as it adapted to shifts in the social discourse regarding gender and work. Analyzing archival data from the firm over eighteen years and... View Details
Keywords: Professional Service Firms; Social Institutions; Organizational Learning; Organizational Change and Adaptation; Employment; Gender; Society; Service Industry
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Ramarajan, Lakshmi, Kathleen McGinn, and Deborah Kolb. "An Outside-Inside Evolution in Gender and Professional Work." Harvard Business School Working Paper, No. 13-051, November 2012. (Work in progress for requested submission, Research in Organizational Behavior.)
  • Article

Capabilities, Cognition and Inertia: Evidence from Digital Imaging

By: M. Tripsas and G. Gavetti
There is empirical evidence that established firms often have difficulty adapting to radical technological change. Although prior work in the evolutionary tradition emphasizes the inertial forces associated with the local nature of learning processes, little... View Details
Keywords: Business Offices; Organizations; Management Analysis, Tools, and Techniques
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Tripsas, M., and G. Gavetti. "Capabilities, Cognition and Inertia: Evidence from Digital Imaging." Strategic Management Journal 21, nos. 10-11 (October–November 2000): 1147–1161.
  • July 2023 (Revised July 2023)
  • Background Note

Generative AI Value Chain

By: Andy Wu and Matt Higgins
Generative AI refers to a type of artificial intelligence (AI) that can create new content (e.g., text, image, or audio) in response to a prompt from a user. ChatGPT, Bard, and Claude are examples of text generating AIs, and DALL-E, Midjourney, and Stable Diffusion are... View Details
Keywords: AI; Artificial Intelligence; Model; Hardware; Data Centers; AI and Machine Learning; Applications and Software; Analytics and Data Science; Value
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Wu, Andy, and Matt Higgins. "Generative AI Value Chain." Harvard Business School Background Note 724-355, July 2023. (Revised July 2023.)
  • 2019
  • Article

Can Big Data Improve Firm Decision Quality? The Role of Data Quality and Data Diagnosticity

By: Maryam Ghasemaghaei and Goran Calic
Anecdotal evidence suggests that, despite the large variety of data, the huge volume of generated data, and the fast velocity of obtaining data (i.e., big data), quality of big data is far from perfect. Therefore, many firms defer collecting and integrating big data as... View Details
Keywords: Big Data; Analytics and Data Science; Decisions; Quality
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Ghasemaghaei, Maryam, and Goran Calic. "Can Big Data Improve Firm Decision Quality? The Role of Data Quality and Data Diagnosticity." Decision Support Systems 120 (2019): 38–49.
  • December 2022
  • Article

Entry Points: Gaining Momentum in Early-Stage Cross-Boundary Collaborations

By: Eva Flavia Martínez Orbegozo, Jorrit de Jong, Hannah Riley Bowles, Amy Edmondson, Anahide Nahhal and Lisa Cox
To address complex social challenges, it is widely recognized that leaders from public, for-profit, and civic organizations should join forces. Yet, well-intended collaborators often struggle to achieve alignment and fail to gain traction in their joint efforts. This... View Details
Keywords: Groups and Teams; Social and Collaborative Networks; Goals and Objectives
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Orbegozo, Eva Flavia Martínez, Jorrit de Jong, Hannah Riley Bowles, Amy Edmondson, Anahide Nahhal, and Lisa Cox. "Entry Points: Gaining Momentum in Early-Stage Cross-Boundary Collaborations." Journal of Applied Behavioral Science 58, no. 4 (December 2022): 595–645.
  • March 2013
  • Case

NovaStar Financial: A Short Seller's Battle

By: Suraj Srinivasan and Amy Kaser
The NovaStar case describes the challenges faced by short seller Marc Cohodes of hedge fund Rocker Partners as he tried to expose what he thought was widespread fraud in mortgage lender NovaStar Financial. The case is set in the time period from 2001 to 2007 and tracks... View Details
Keywords: Short Selling; Financial Accounting; Financial Analysis; Financial Analysts; Valuation; Business Analysis; Financial Statement Analysis; Financial Statements; Securitization; Securities Analysis; Fraud; Accounting Quality; Accounting Red Flags; Accounting Restatements; Hedge Fund; Hedge Funds; Accounting Scandal; Accounting Fraud; Financial Crisis; Financial Intermediaries; Financial Firms; Corporate Accountability; Subprime Lending; Mortgage Lending; Accounting; Accrual Accounting; Fair Value Accounting; Governance; Governance Compliance; Corporate Governance; Governance Controls; Financial Services Industry; United States; California
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Srinivasan, Suraj, and Amy Kaser. "NovaStar Financial: A Short Seller's Battle." Harvard Business School Case 113-120, March 2013.
  • 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).
  • Teaching Interest

Investing: Risk, Return and Impact (MBA)

By: Shawn A. Cole

This is an investing/finance course, designed to build on skills introduced in the RC finance course, but with an emphasis on how and whether investors should incorporate what have traditionally been considered “non-financial” criteria in their decisions: for... View Details

  • 20 Apr 2009
  • Working Paper Summaries

Corporate Misgovernance at the World Bank

Keywords: by Ashwin Kaja & Eric Werker
  • 02 Jul 2013
  • First Look

First Look: July 2

candidates. We find that increasing the political representation of Muslims improves health and education outcomes in the district from which the legislator is elected. We find no evidence of religious favoritism: Muslim children do not... View Details
Keywords: Anna Secino
  • 31 Oct 2023
  • Research & Ideas

Beyond the 'Business Case' in DEI: 6 Steps Toward Meaningful Change

cites: Meta’s goal to raise the representation of people of color, including Black leadership, by 30 percent between 2020 and 2025; Hartford Prudential Financial’s goal to have 20 percent people of color in senior leadership roles by... View Details
Keywords: by Katherine Hutt Scott and Barbara DeLollis
  • 27 Feb 2024
  • Research & Ideas

Why Companies Should Share Their DEI Data (Even When It’s Unflattering)

diversity data—even if it shows a disparity in the representation of employees of color—doesn’t hurt consumer attitudes toward a company. And, when the numbers show that a company’s workforce is relatively diverse, consumers feel even... View Details
Keywords: by Shalene Gupta
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