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- 2024
- Working Paper
Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization
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
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
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
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
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
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
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
- 01 Oct 2000
- News
Willoughby G. Walling II: A Learning Experience
two grown children, both of whom are involved in the arts, have been supportive, notes Walling. Influenced by van Gogh, Horace Pippin, Basquiat, and Henri Rousseau, among others, Walling aspires to a style that is "between realistic View Details
Keywords: Deborah Blagg
- Web
10 Things I Learned During My First Month in the MS/MBA: Engineering Sciences Program - MBA
Blog Blog MBA Voices Filter Results Arrow Down Arrow Up Read posts from Author Alumni Author Career and Professional Development Staff Author HBS Community Author HBS Faculty Author MBA Admissions Author MBA Students Topics Topics 1st Year (RC) 2+2 Program 2nd Year... View Details
- 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
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.)
- 01 Dec 2013
- News
HBX: Expanding Our Reach
In the last few years, the landscape for online learning has changed dramatically. Using new and ever more powerful technologies, the market is shifting rapidly, with many dozens of organizations, aggregators, and educational institutions... View Details
Isamar Troncoso
Isamar Troncoso is an Assistant Professor of Business Administration in the Marketing Unit at HBS. She teaches the Marketing course in the MBA required curriculum.
Professor Troncoso studies problems related to digital marketplaces and new technologies. She... View Details
- 12 Jun 2023
- Blog Post
What Does PRIDE at HBS Mean to You?
that last long after they have graduated. Together they work to build community, foster professional development, and encourage advocacy for LGBTQ+ representation at our school and in business. Check out some current student and alum... View Details
- 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
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.
- 25 Sep 2023
- Blog Post
HBS Latino Student Association Spotlight: Ana Barrera (MBA 2024)
individuals holding an MBA identify as Latinas, and we have among the lowest representation in senior business positions and corporate boards. In part, the strong desire to challenge these statistics fueled my path to apply to HBS. With... View Details
- 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
Wu, Andy, and Matt Higgins. "Generative AI Value Chain." Harvard Business School Background Note 724-355, July 2023. (Revised July 2023.)
- 12 Mar 2018
- Blog Post
Applying to HBS in Round 3?
decide last minute to give the business school application a try. For the most part, the schools will never know the reason you are applying in round 3. They will only know who you are based on what you submit which should be the absolute best View Details
- 07 Oct 2020
- Blog Post
7 Coming Out Stories from the HBS PRIDE Club
many, anxiety and loneliness – our visibility and representation matter more than ever. Here, students share their personal stories through the National Coming Out Day student storyboard series organized by the PRIDE club. Visit our... View Details
- 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
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.