Publications
Publications
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- All HBS Web
(4,045)
- Faculty Publications (1,261)
- October 2021 (Revised June 2022)
- Case
PittaRosso: Artificial Intelligence-Driven Pricing and Promotion
By: Ayelet Israeli
PittaRosso, a traditional Italian shoe retailer, is implementing an AI system to provide pricing and promotion recommendations. The system allows them to implement changes that would affect both the top of funnel and bottom of funnel activities for the company: once... View Details
Keywords: Artificial Intelligence; Pricing; Pricing Algorithm; Pricing Decisions; Pricing Strategy; Pricing Structure; Promotion; Promotions; Online Marketing; Data-driven Decision-making; Data-driven Management; Retail; Retail Analytics; AI; Price; Advertising Campaigns; Analytics and Data Science; Analysis; Digital Marketing; Budgets and Budgeting; Marketing Strategy; Marketing; Transformation; Decision Making; AI and Machine Learning; Retail Industry; Italy
- October 1, 2021
- Article
An Evaluation of Cross-efficiency Methods: With an Application to Warehouse Performance.
By: B.M. Balk, M.R. De Koster, Christian Kaps and J.L. Zofio
Cross-efficiency measurement is an extension of Data Envelopment Analysis that allows for tie-breaking ranking of the Decision Making Units (DMUs) using all the peer evaluations. In this article we examine the theory of cross-efficiency measurement by comparing a... View Details
- 2021
- Chapter
Building Small Business Utopia: How Artificial Intelligence and Big Data Can Increase Small Business Success
By: Karen G. Mills and Annie Dang
Small business lending has remained unchanged for decades, laden with frictions and barriers that prevent many small businesses from accessing the capital they need to succeed. Financial technology, or “fintech,” promises to change this trajectory. In 2010, new fintech... View Details
- September–October 2021
- Article
Frontiers: Can an AI Algorithm Mitigate Racial Economic Inequality? An Analysis in the Context of Airbnb
By: Shunyuan Zhang, Nitin Mehta, Param Singh and Kannan Srinivasan
We study the effect of Airbnb’s smart-pricing algorithm on the racial disparity in the daily revenue earned by Airbnb hosts. Our empirical strategy exploits Airbnb’s introduction of the algorithm and its voluntary adoption by hosts as a quasi-natural experiment. Among... View Details
- October 2021
- Article
Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach
By: Nicolas Padilla and Eva Ascarza
The success of Customer Relationship Management (CRM) programs ultimately depends on the firm's ability to understand consumers' preferences and precisely capture how these preferences may differ across customers. Only by understanding customer heterogeneity, firms can... View Details
- October 2021 (Revised September 2022)
- Case
SmartOne: Building an AI Data Business
By: Karim R. Lakhani, Pippa Armerding, Gamze Yucaoglu and Fares Khrais
The case opens in August 2021, as Habib and Shahysta Hassim, husband and wife co-founders of the data labeling company SmartOne, contemplate the strategy of the high growth company. Between 2016 and 2021, SmartOne had kept doubling its size every two years and now,... View Details
- September 17, 2021
- Article
AI Can Help Address Inequity—If Companies Earn Users' Trust
By: Shunyuan Zhang, Kannan Srinivasan, Param Singh and Nitin Mehta
While companies may spend a lot of time testing models before launch, many spend too little time considering how they will work in the wild. In particular, they fail to fully consider how rates of adoption can warp developers’ intent. For instance, Airbnb launched a... View Details
- September 15, 2021
- Article
Improving Deconvolution Methods in Biology Through Open Innovation Competitions: An Application to the Connectivity Map
By: Andrea Blasco, Ted Natoli, Michael G. Endres, Rinat A. Sergeev, Steven Randazzo, Jin Hyun Paik, N.J. Maximilian Macaluso, Rajiv Narayan, Xiaodong Lu, David Peck, Karim R. Lakhani and Aravind Subramanian
A recurring problem in biomedical research is how to isolate signals of distinct populations (cell types, tissues, and genes) from composite measures obtained by a single analyte or sensor. Existing computational deconvolution approaches work well in many specific... View Details
- September 2021 (Revised March 2024)
- Case
Bühler: Mobilizing Industry around a Common Purpose
By: Ranjay Gulati, Franz Wohlgezogen and Malini Sen
Bühler Group, a Swiss multinational processing technology provider, started by selling machines for processing grains and later transitioned into selling food processing solutions. A family-owned business in the fifth generation, Bühler’s high-end milling, grinding,... View Details
- 2021
- Working Paper
Expanding the Entrepreneurial Cultural Toolkit: The Temporal Interplay of the Substantive and the Symbolic
By: Rebecca Karp and Siobhan O'Mahony
Much research shows how entrepreneurs leverage symbolic toolkits via storytelling and narratives to convince resource providers of their venture’s legitimacy. Although investors’ legitimacy concerns may be initially met with symbolic actions, it is unclear whether... View Details
- September 2021
- Article
Shaking Things Up: Disruptive Events and Inequality
By: Letian Zhang
This paper develops a theory of how disruptive events could reduce racial and gender inequality in organizations. Despite pressure from regulators and advocates, racial and gender inequality in the workplace remains high. I theorize that because such inequality is... View Details
- 2017
- Working Paper
Does Financial Misconduct Affect the Future Compensation of Alumni Managers?
By: Boris Groysberg, Eric Lin and Georgios Serafeim
We explore how an organization’s financial misconduct may affect pay for former employees not implicated in wrongdoing. Drawing on stigma theory we hypothesize that although such alumni did not participate in the financial misconduct and they had left the organization... View Details
- 2021
- Working Paper
'Just Letting You Know…': Underestimating Others' Desire for Constructive Feedback
By: Nicole Abi-Esber, Jennifer Abel, Juliana Schroeder and Francesca Gino
People often avoid giving feedback to others even when it would help fix a problem immediately. Indeed, in a pilot field study (N=155), only 2.6% of individuals provided feedback to survey administrators that the administrators had food or marker on their faces.... View Details
Keywords: Feedback; Helping; Prosocial Behavior; Relationships; Social Psychology; Theory; Perception
- August 2021 (Revised November 2024)
- Case
Intenseye: Powering Workplace Health and Safety with AI (A)
By: Michael W. Toffel and Youssef Abdel Aal
Intenseye was a Turkey-based technology startup that deployed machine learning algorithms to workplace camera feeds in order to identify unsafe worker actions and unsafe working conditions, in order to help improve worker safety. The case describes how Intenseye’s... View Details
- July 2021
- Article
Big Data for Social Benefits: Innovation as a Mediator of the Relationship between Big Data and Corporate Social Performance
By: Goran Calic and Maryam Ghasemaghaei
Over the last decade, the use big data in firms has seen a rapid increase. Whilst scholars have begun to unpack the relationship between big data utilisation and financial performance, significant uncertainty exists about the ethical uses of this new asset. Whether... View Details
- July 2021
- Article
Discovering Auctions: Contributions of Paul Milgrom and Robert Wilson
By: Alex Teytelboym, Shengwu Li, Scott Duke Kominers, Mohammad Akbarpour and Piotr Dworczak
The 2020 Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel was awarded to Paul R. Milgrom and Robert B. Wilson for “improvements to auction theory and inventions of new auction formats.” In this survey article, we review the contributions of the... View Details
- Article
Learning Models for Actionable Recourse
By: Alexis Ross, Himabindu Lakkaraju and Osbert Bastani
As machine learning models are increasingly deployed in high-stakes domains such as legal and financial decision-making, there has been growing interest in post-hoc methods for generating counterfactual explanations. Such explanations provide individuals adversely... View Details
- 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
- Article
Towards the Unification and Robustness of Perturbation and Gradient Based Explanations
By: Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu and Himabindu Lakkaraju
As machine learning black boxes are increasingly being deployed in critical domains such as healthcare and criminal justice, there has been a growing emphasis on developing techniques for explaining these black boxes in a post hoc manner. In this work, we analyze two... View Details
- June 2021
- Technical Note
Introduction to Linear Regression
By: Michael Parzen and Paul Hamilton
This technical note introduces (from an applied point of view) the theory and application of simple and multiple linear regression. The motivation for the model is introduced, as well as how to interpret the summary output with regard to prediction and statistical... View Details