Skip to Main Content
HBS Home
  • About
  • Academic Programs
  • Alumni
  • Faculty & Research
  • Baker Library
  • Giving
  • Harvard Business Review
  • Initiatives
  • News
  • Recruit
  • Map / Directions
Faculty & Research
  • Faculty
  • Research
  • Featured Topics
  • Academic Units
  • …→
  • Harvard Business School→
  • Faculty & Research→
  • Research
    • Research
    • Publications
    • Global Research Centers
    • Case Development
    • Initiatives & Projects
    • Research Services
    • Seminars & Conferences
    →
  • Publications→

Publications

Publications

Filter Results: (1,553) Arrow Down
Filter Results: (1,553) Arrow Down Arrow Up

Show Results For

  • All HBS Web  (3,013)
    • People  (14)
    • News  (648)
    • Research  (1,553)
    • Events  (19)
    • Multimedia  (9)
  • Faculty Publications  (830)

Show Results For

  • All HBS Web  (3,013)
    • People  (14)
    • News  (648)
    • Research  (1,553)
    • Events  (19)
    • Multimedia  (9)
  • Faculty Publications  (830)
← Page 11 of 1,553 Results →
Sort by

Are you looking for?

→Search All HBS Web
  • 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
Citation
SSRN
Read Now
Related
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.
  • 09 May 2014
  • Working Paper Summaries

‘My Bad!’ How Internal Attribution and Ambiguity of Responsibility Affect Learning from Failure

Keywords: by Christopher G. Myers, Bradley R. Staats & Francesca Gino
  • February 2021
  • Article

Topic Classification of Electric Vehicle Consumer Experiences with Transformer-Based Deep Learning

By: Sooji Ha, Daniel J Marchetto, Sameer Dharur and Omar Isaac Asensio
The transportation sector is a major contributor to greenhouse gas (GHG) emissions and is a driver of adverse health effects globally. Increasingly, government policies have promoted the adoption of electric vehicles (EVs) as a solution to mitigate GHG emissions.... View Details
Keywords: Natural Language Processing; Analytics and Data Science; Environmental Sustainability; Infrastructure; Transportation; Policy
Citation
Read Now
Related
Ha, Sooji, Daniel J Marchetto, Sameer Dharur, and Omar Isaac Asensio. "Topic Classification of Electric Vehicle Consumer Experiences with Transformer-Based Deep Learning." Art. 100195. Patterns 2, no. 2 (February 2021).
  • March 2003
  • Background Note

A Short Note on the AccuFlow Excel Model

By: Jay O. Light
Describes an Excel spreadsheet workbook that facilitates the analysis of AccuFlow, Inc. View Details
Keywords: History; Analytics and Data Science; Cost of Capital; Negotiation; Capital; Business Model; Economic Systems; Machinery and Machining; Leveraged Buyouts; Business Startups; Equity
Citation
Educators
Purchase
Related
Light, Jay O. "A Short Note on the AccuFlow Excel Model." Harvard Business School Background Note 203-089, March 2003.
  • 14 Nov 2016
  • Op-Ed

5 Lessons I Hope Marketers Don’t Learn from Donald Trump

marketer ranks on size of the lie is a matter of opinion, but someone who hoped to learn ethical practice from his marketing manual would be well advised not to follow him in the matter of frequency. The Washington Post scored 64 percent... View Details
Keywords: by John A. Deighton
  • April 2025
  • Article

Serving with a Smile on Airbnb: Analyzing the Economic Returns and Behavioral Underpinnings of the Host’s Smile

By: Shunyuan Zhang, Elizabeth Friedman, Kannan Srinivasan, Ravi Dhar and Xupin Zhang
Non-informational cues, such as facial expressions, can significantly influence judgments and interpersonal impressions. While past research has explored how smiling affects business outcomes in offline or in-store contexts, relatively less is known about how smiling... View Details
Keywords: Sharing Economy; Airbnb; Image Feature Extraction; Machine Learning; Facial Expressions; Prejudice and Bias; Nonverbal Communication; E-commerce; Consumer Behavior; Perception
Citation
Read Now
Related
Zhang, Shunyuan, Elizabeth Friedman, Kannan Srinivasan, Ravi Dhar, and Xupin Zhang. "Serving with a Smile on Airbnb: Analyzing the Economic Returns and Behavioral Underpinnings of the Host’s Smile." Journal of Consumer Research 51, no. 6 (April 2025): 1073–1097.
  • 01 Jun 2020
  • What Do You Think?

Will Challenged Amazon Tweak Its Retail Model Post-Pandemic?

asked, “Is this a good time to begin thinking about prudential limits so that the brick-and-mortar stores will continue to be around when the next lockdown happens?” Perhaps the most basic question was one raised by NickC when he said, “The question for me is whether... View Details
Keywords: by James Heskett; Retail
  • 10 Apr 2013
  • Research & Ideas

Learning Curve: Making the Most of Outsourcing

model fits the practice of teleradiology. The article, titled "Learning from Customers: Individual and Organizational Effects in Outsourced Radiological Services," was written by Huckman; Jonathan R. Clark (HBS PhDHP '10), Pennsylvania... View Details
Keywords: by Paul Guttry; Health
  • Article

A Prescriptive Analytics Framework for Optimal Policy Deployment Using Heterogeneous Treatment Effects

By: Edward McFowland III, Sandeep Gangarapu, Ravi Bapna and Tianshu Sun
We define a prescriptive analytics framework that addresses the needs of a constrained decision-maker facing, ex ante, unknown costs and benefits of multiple policy levers. The framework is general in nature and can be deployed in any utility maximizing context, public... View Details
Keywords: Prescriptive Analytics; Heterogeneous Treatment Effects; Optimization; Observed Rank Utility Condition (OUR); Between-treatment Heterogeneity; Machine Learning; Decision Making; Analysis; Mathematical Methods
Citation
Find at Harvard
Purchase
Related
McFowland III, Edward, Sandeep Gangarapu, Ravi Bapna, and Tianshu Sun. "A Prescriptive Analytics Framework for Optimal Policy Deployment Using Heterogeneous Treatment Effects." MIS Quarterly 45, no. 4 (December 2021): 1807–1832.
  • 07 Oct 2015
  • What Do You Think?

What is the Best Immigration Model for the US?

On Immigration Does the US Have Anything to Learn from Europe? We should not confuse the potential economic benefits of immigration for the United States with what is happening in Europe and specifically Germany. While the benefits can be... View Details
Keywords: by James Heskett
  • October 2018
  • Case

American Family Insurance and the Artificial Intelligence Opportunity

By: Rajiv Lal and Scott Johnson
Keywords: Artificial Intelligence; Machine Learning; Automation; Analytics; American Family; American Family Insurance; Insurance; Business Organization; Transformation; Talent and Talent Management; Employee Relationship Management; Innovation Strategy; Job Cuts and Outsourcing; Risk and Uncertainty; Mobile and Wireless Technology; Technology Adoption; Internet and the Web; Applications and Software; Corporate Strategy; AI and Machine Learning; Digital Transformation; Insurance Industry; Technology Industry; Wisconsin
Citation
Educators
Related
Lal, Rajiv, and Scott Johnson. "American Family Insurance and the Artificial Intelligence Opportunity." Harvard Business School Case 519-028, October 2018.
  • Research Summary

Team, Individual, and Organizational Learning From Experience in Two High-Hazard Industries

High-hazard industries such as nuclear power and chemical process plants must learn and improve without sole reliance on trial-and-error. Considerable attention and resources are placed on learning from operating experience, including exchange of best practices, peer... View Details
  • Article

Why Hospitals Don't Learn from Failures: Organizational and Psychological Dynamics That Inhibit System Change

By: A. Tucker and A. Edmondson
The importance of hospitals learning from their failures hardly needs to be stated. Not only are matters of life and death at stake on a daily basis, but also an increasing number of U.S. hospitals are operating in the red. This article reports on in-depth qualitative... View Details
Keywords: Health Care and Treatment; Health Industry
Citation
Find at Harvard
Related
Tucker, A., and A. Edmondson. "Why Hospitals Don't Learn from Failures: Organizational and Psychological Dynamics That Inhibit System Change." California Management Review 45, no. 2 (Winter 2003). (Winner of Accenture Award For the article published in the California Management Review that has made the most important contribution to improving the practice of management​.)
  • December 2018
  • Case

Choosy

By: Jeffrey J. Bussgang and Julia Kelley
Founded in 2017, Choosy is a data-driven fashion startup that uses algorithms to identify styles trending on social media. After manufacturing similar items using a China-based supply chain, Choosy sells them to consumers through its website and social media pages.... View Details
Keywords: Artificial Intelligence; Algorithms; Machine Learning; Neural Networks; Instagram; Influencer; Fast Fashion; Design; Customer Satisfaction; Customer Focus and Relationships; Decision Making; Cost vs Benefits; Innovation and Invention; Brands and Branding; Product Positioning; Demand and Consumers; Supply Chain; Production; Logistics; Business Model; Expansion; Internet and the Web; Mobile and Wireless Technology; Digital Platforms; Social Media; Technology Industry; Fashion Industry; North and Central America; United States; New York (state, US); New York (city, NY)
Citation
Educators
Purchase
Related
Bussgang, Jeffrey J., and Julia Kelley. "Choosy." Harvard Business School Case 819-054, December 2018.
  • 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
Citation
Educators
Purchase
Related
Wu, Andy, and Matt Higgins. "Generative AI Value Chain." Harvard Business School Background Note 724-355, July 2023. (Revised July 2023.)
  • 2020
  • Article

A Practical Approach to Sales Compensation: What Do We Know Now? What Should We Know in the Future?

By: Doug J. Chung, Byungyeon Kim and Niladri B. Syam
Personal selling represents one of the most important elements in the marketing mix, and appropriate management of the sales force is vital to achieving the organization’s objectives. Among the various instruments of sales management, compensation plays a pivotal role... View Details
Keywords: Sales Compensation; Sales Management; Sales Strategy; Principal-agent Theory; Structural Econometrics; Field Experiments; Machine Learning; Artificial Intelligence; Salesforce Management; Compensation and Benefits; Motivation and Incentives; AI and Machine Learning
Citation
Find at Harvard
Read Now
Related
Chung, Doug J., Byungyeon Kim, and Niladri B. Syam. "A Practical Approach to Sales Compensation: What Do We Know Now? What Should We Know in the Future?" Foundations and Trends® in Marketing 14, no. 1 (2020): 1–52.
  • 1990
  • Chapter

Measurement, Coordination and Learning in a Multi-plant Network

By: W. B. Chew, K. B. Clark and T. Bresnahan
Keywords: Factories, Labs, and Plants; Organizational Structure; Networks; Business Model; Measurement and Metrics; Cooperation
Citation
Related
Chew, W. B., K. B. Clark, and T. Bresnahan. "Measurement, Coordination and Learning in a Multi-plant Network." In Measures for Manufacturing Excellence, edited by Robert S. Kaplan. Boston: Harvard Business School Press, 1990.
  • 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
Citation
Read Now
Related
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.
  • January–February 2022
  • Article

Algorithm-Augmented Work and Domain Experience: The Countervailing Forces of Ability and Aversion

By: Ryan Allen and Prithwiraj Choudhury
How does a knowledge worker’s level of domain experience affect their algorithm-augmented work performance? We propose and test theoretical predictions that domain experience has countervailing effects on algorithm-augmented performance: on one hand, domain experience... View Details
Keywords: Automation; Domain Experience; Algorithmic Aversion; Experts; Algorithms; Machine Learning; Future Of Work; Employees; Experience and Expertise; Decision Making; Performance
Citation
Find at Harvard
Read Now
Related
Allen, Ryan, and Prithwiraj Choudhury. "Algorithm-Augmented Work and Domain Experience: The Countervailing Forces of Ability and Aversion." Organization Science 33, no. 1 (January–February 2022): 149–169. ("Best PhD Student Paper" at SMS conference 2020.)
  • 04 Apr 2011
  • Research & Ideas

Attention Medical Shoppers: What Health Care Can Learn from Walmart and Amazon

In order to get its financial and management woes under control, the health care industry might want to peek at the playbooks of retail giants like Walmart, Google, and Amazon.com. This was a key conversation point at "Perspectives on Health Care as a Management... View Details
Keywords: by Carmen Nobel; Health
  • ←
  • 11
  • 12
  • …
  • 77
  • 78
  • →

Are you looking for?

→Search All HBS Web
ǁ
Campus Map
Harvard Business School
Soldiers Field
Boston, MA 02163
→Map & Directions
→More Contact Information
  • Make a Gift
  • Site Map
  • Jobs
  • Harvard University
  • Trademarks
  • Policies
  • Accessibility
  • Digital Accessibility
Copyright © President & Fellows of Harvard College.