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- Teaching Interest
Data Science for Managers
By: Dennis Campbell
Data science has become the new language of business. Many roles across the enterprise in finance, marketing, human resources, operations, innovation, and strategy now rely heavily on data science for important managerial decisions. Given the increasing ubiquity and... View Details
- Teaching Interest
Data Science for Managers
By: Chiara Farronato
This new course is taught as a required course in the first year MBA curriculum as of a.y. 2023-2024. It provides students with the foundations of data science to become effective data-driven managers. The course covers the basics of visualization, statistical and... View Details
- Teaching Interest
Harvard Business Analytics Program
The Harvard Business Analytics Program is offered through a collaboration between Harvard Business School (HBS), the John A. Paulson School of Engineering and Applied Sciences (SEAS), and the Faculty of Arts and Sciences (FAS).
Designed for... View Details
- Teaching Interest
Harvard Business Analytics Program: Operations and Supply Chain Management
By: Dennis Campbell
Digital technologies and data analytics are radically changing the operating model of an organization and how it connects to its broader supply chain and ecosystem. This course emphasizes managing product availability, especially in a context of rapid product... View Details
- Forthcoming
- Article
Human-Algorithm Collaboration with Private Information: Naïve Advice Weighting Behavior and Mitigation
By: Maya Balakrishnan, Kris Ferreira and Jordan Tong
Even if algorithms make better predictions than humans on average, humans may sometimes have private information which an algorithm does not have access to that can improve performance. How can we help humans effectively use and adjust recommendations made by... View Details
Keywords: AI and Machine Learning; Analytics and Data Science; Forecasting and Prediction; Digital Marketing
Balakrishnan, Maya, Kris Ferreira, and Jordan Tong. "Human-Algorithm Collaboration with Private Information: Naïve Advice Weighting Behavior and Mitigation." Management Science (forthcoming).
- Teaching Interest
Overview
By: John A. Deighton
I teach about the ecosystem of big data, the role of data in advertising and creative industries, and customer management and personal privacy in an era of individual addressability. View Details
Keywords: Digital Marketing; Database Marketing; Social Media; Data Analytics; Information; Advertising; Marketing; Media; Technology; Entertainment and Recreation Industry; Entertainment and Recreation Industry; Entertainment and Recreation Industry; Entertainment and Recreation Industry; Entertainment and Recreation Industry
- Research Summary
Overview
I have spent my career studying novel talent management practices and their effect on collaboration and performance. My core research focuses on two interrelated organizational trends that have become salient in the 21st century: workplace transparency (who gets to... View Details
Keywords: Privacy; Transparency; Productivity; Field Experiments; Communication; Design; Human Resources; Leadership; Management; Organizational Design; Organizational Structure; Performance; Groups and Teams; Networks; Behavior; Social and Collaborative Networks; Satisfaction; North America; Europe; Asia; China; Japan; Latin America
- Research Summary
Overview
By: Iavor I. Bojinov
Over the last decade, technology companies like Amazon, Google, and Netflix have pioneered data-driven research and development processes centered on massive experimentation. However, as companies increase the breadth and scale of their experiments to millions of... View Details
- Research Summary
Overview
Professor Ferreira's research primarily focuses on how retailers can use algorithms to make better revenue management decisions, including pricing, product display, and assortment planning. In the retail industry, anticipating consumer demand is arguably one of the... View Details
- Research Summary
Overview
By: Ayelet Israeli
Professor Israeli utilizes econometric methods and field experiments to study data driven decision making in marketing context. Her research focuses on data-driven marketing, with an emphasis on how businesses can leverage their own data, customer data, and market data... View Details
- Article
Paradise Lost (and Restored?): A Study of Psychological Safety over Time
By: Derrick P. Bransby, Michaela Kerrissey and Amy C. Edmondson
Although prior research indicates that psychological safety can fluctuate, questions about when and why remain. To gain insights into the emergence and temporal dynamics of psychological safety, we explored longitudinal data representing more than 10,000 health care... View Details
Keywords: Analytics and Data Science; Research; Attitudes; Working Conditions; Well-being; Health Industry
Bransby, Derrick P., Michaela Kerrissey, and Amy C. Edmondson. "Paradise Lost (and Restored?): A Study of Psychological Safety over Time." Academy of Management Discoveries (in press). (Pre-published online March 14, 2024.)
- Research Summary
Performance Impact of Continuous Replenishment Systems
Janice H. Hammond has conducted (with Ted Clark of Hong Kong University of Science and Technology) a survey of U.S. retailers to determine how the implementation of continuous replenishment programs between manufacturers and retailers affects supply channel... View Details
- Research Summary
Reforming Social Science
By: Max H. Bazerman
Social science research affects all of us. When researchers learned organ donation rates are higher in countries where human organs are automatically available for donation unless you specifically “opt-out” of the system, as opposed to countries like the U.S., where... View Details
- Forthcoming
- Article
Slowly Varying Regression Under Sparsity
By: Dimitris Bertsimas, Vassilis Digalakis Jr, Michael Lingzhi Li and Omar Skali Lami
We consider the problem of parameter estimation in slowly varying regression models with sparsity constraints. We formulate the problem as a mixed integer optimization problem and demonstrate that it can be reformulated exactly as a binary convex optimization problem... View Details
Bertsimas, Dimitris, Vassilis Digalakis Jr, Michael Lingzhi Li, and Omar Skali Lami. "Slowly Varying Regression Under Sparsity." Operations Research (forthcoming). (Pre-published online March 27, 2024.)
- Forthcoming
- Article
The Double-Edged Sword of Exemplar Similarity
By: Majid Majzoubi, Eric Zhao, Tiona Zuzul and Greg Fisher
We investigate how a firm’s positioning relative to category exemplars shapes security analysts’ evaluations. Using a two-stage model of evaluation (initial screening and subsequent assessment), we propose that exemplar similarity enhances a firm’s recognizability and... View Details
Majzoubi, Majid, Eric Zhao, Tiona Zuzul, and Greg Fisher. "The Double-Edged Sword of Exemplar Similarity." Organization Science (forthcoming). (Pre-published online May 7, 2024.)
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