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(645)
- News (145)
- Research (421)
- Events (15)
- Multimedia (11)
- Faculty Publications (295)
Show Results For
- All HBS Web
(645)
- News (145)
- Research (421)
- Events (15)
- Multimedia (11)
- Faculty Publications (295)
- 05 Jul 2006
- Working Paper Summaries
Time-Driven Activity-Based Costing
- 2023
- Article
On Minimizing the Impact of Dataset Shifts on Actionable Explanations
By: Anna P. Meyer, Dan Ley, Suraj Srinivas and Himabindu Lakkaraju
The Right to Explanation is an important regulatory principle that allows individuals to request actionable explanations for algorithmic decisions. However, several technical challenges arise when providing such actionable explanations in practice. For instance, models... View Details
Meyer, Anna P., Dan Ley, Suraj Srinivas, and Himabindu Lakkaraju. "On Minimizing the Impact of Dataset Shifts on Actionable Explanations." Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI) 39th (2023): 1434–1444.
- 2023
- Working Paper
Dynamic Pricing, Intertemporal Spillovers, and Efficiency
By: Alexander J. MacKay, Dennis Svartbäck and Anders G. Ekholm
Pricing technology that allows firms to rapidly adjust prices has two potential benefits.
Time-varying prices can respond to high-frequency demand shocks to generate greater revenues,
and they can also be used to smooth out demand to reduce costs. Using data... View Details
MacKay, Alexander J., Dennis Svartbäck, and Anders G. Ekholm. "Dynamic Pricing, Intertemporal Spillovers, and Efficiency." Harvard Business School Working Paper, No. 23-007, July 2022. (Revised December 2023.)
- 2019
- Working Paper
Managing Churn to Maximize Profits
By: Aurelie Lemmens and Sunil Gupta
Customer defection threatens many industries, prompting companies to deploy targeted, proactive customer retention programs and offers. A conventional approach has been to target customers either based on their predicted churn probability, or their responsiveness to a... View Details
Keywords: Churn Management; Defection Prediction; Loss Function; Stochastic Gradient Boosting; Customer Relationship Management; Consumer Behavior; Profit
Lemmens, Aurelie, and Sunil Gupta. "Managing Churn to Maximize Profits." Harvard Business School Working Paper, No. 14-020, September 2013. (Revised December 2019. Forthcoming at Marketing Science.)
- Article
Assent-maximizing Social Choice
By: Katherine A. Baldiga and Jerry R. Green
We take a decision theoretic approach to the classic social choice problem, using data on the frequency of choice problems to compute social choice functions. We define a family of social choice rules that depend on the population's preferences and on the probability... View Details
Keywords: Decision Choices and Conditions; Theory; Measurement and Metrics; Mathematical Methods; Society
Baldiga, Katherine A., and Jerry R. Green. "Assent-maximizing Social Choice." Social Choice and Welfare 40, no. 2 (February 2013): 439–460.
- Article
Soul and Machine (Learning)
By: Davide Proserpio, John R. Hauser, Xiao Liu, Tomomichi Amano, Burnap Alex, Tong Guo, Dokyun (DK) Lee, Randall Lewis, Kanishka Misra, Eric Schwarz, Artem Timoshenko, Lilei Xu and Hema Yoganarasimhan
Machine learning is bringing us self-driving cars, medical diagnoses, and language translation, but how can machine learning help marketers improve marketing decisions? Machine learning models predict extremely well, are scalable to “big data,” and are a natural fit to... View Details
Keywords: Machine Learning; Marketing Applications; Knowledge; Technological Innovation; Core Relationships; Marketing; Applications and Software
Proserpio, Davide, John R. Hauser, Xiao Liu, Tomomichi Amano, Burnap Alex, Tong Guo, Dokyun (DK) Lee, Randall Lewis, Kanishka Misra, Eric Schwarz, Artem Timoshenko, Lilei Xu, and Hema Yoganarasimhan. "Soul and Machine (Learning)." Marketing Letters 31, no. 4 (December 2020): 393–404.
- 19 Oct 2021
- HBS Seminar
Cynthia Rudin, Duke University
- 10 Jul 2023
- In Practice
The Harvard Business School Faculty Summer Reader 2023
fascinating realm of design and human interaction with everyday objects. Norman provides thought-provoking insights on usability and human-centered design. The book is relevant to my own research on visual analytics. Picture this: designing an View Details
Keywords: by Dina Gerdeman
- March 2023
- Teaching Note
VideaHealth: Building the AI Factory
By: Karim R. Lakhani
Teaching Note for HBS Case No. 621-021. The case “VideaHealth: Building the AI Factory” examines the creation of dental startup VideaHealth (Videa) and the development of its artificial intelligence (AI)-led business strategy through the eyes of founder and CEO Florian... View Details
- 2015
- Chapter
Optimal Process Control of Symbolic Transfer Functions
By: Christopher Griffin and Elisabeth Paulson
Transfer function modeling is a standard technique in classical Linear Time Invariant and Statistical Process Control. The work of Box and Jenkins was seminal in developing methods for identifying parameters associated with classical (r, s, k) transfer functions.... View Details
Keywords: Transfer Functions; Markov Processes; Stochastic Models; Process Control; Research; Information Technology
Griffin, Christopher, and Elisabeth Paulson. "Optimal Process Control of Symbolic Transfer Functions." In Proceedings of the 10th International Workshop on Feedback Computing. IEEE, 2015.
- 06 Oct 2015
- First Look
October 6, 2015
upon the Thompson sampling algorithm used for multi-armed bandit problems by incorporating inventory constraints into the pricing decisions. Our algorithm proves to have both strong theoretical performance... View Details
Keywords: Sean Silverthorne
- 2021
- Book
The Future of Executive Development
By: Mihnea C Moldoveanu and Das Narayandas
Executive development programs have entered a period of rapid transformation, driven by digital disruption and a widening gap between the skills that participants and their organizations demand and those provided by their executive programs. This work delves into the... View Details
Moldoveanu, Mihnea C., and Das Narayandas. The Future of Executive Development. Stanford, CA: Stanford Business Books, 2021.
- September–October 2020
- Article
Managing Churn to Maximize Profits
By: Aurelie Lemmens and Sunil Gupta
Customer defection threatens many industries, prompting companies to deploy targeted, proactive customer retention programs and offers. A conventional approach has been to target customers either based on their predicted churn probability or their responsiveness to a... View Details
Keywords: Churn Management; Defection Prediction; Loss Function; Stochastic Gradient Boosting; Customer Relationship Management; Consumer Behavior; Profit
Lemmens, Aurelie, and Sunil Gupta. "Managing Churn to Maximize Profits." Marketing Science 39, no. 5 (September–October 2020): 956–973.
- 26 Mar 2024
- Research & Ideas
How Humans Outshine AI in Adapting to Change
the flexibility of AI versus humans in adjusting to new situations, the authors set up four video games, outlining certain tasks for humans and several popular game-playing AI algorithms to complete. The tasks tested the players’ ability... View Details
- August 2020 (Revised March 2021)
- Supplement
Migros Turkey: Scaling Online Operations (B)
By: Antonio Moreno and Gamze Yucaoglu
The case opens in February 2020 as Ozgur Tort and Mustafa Bartin, CEO and chief large-format and online retail officer of Migros Ticaret A.S. (Migros), Turkey’s oldest and one of its largest supermarket chains, are looking over the results of the fulfillment pilot the... View Details
Keywords: Grocery; Business Model; Strategy; Digital Platforms; Information Technology; Technology Adoption; Value Creation; Globalization; Competition; Expansion; Logistics; Profit; Resource Allocation; Corporate Strategy; Retail Industry; Turkey
Moreno, Antonio, and Gamze Yucaoglu. "Migros Turkey: Scaling Online Operations (B)." Harvard Business School Supplement 621-027, August 2020. (Revised March 2021.)
- 09 Jan 2024
- In Practice
Harnessing AI: What Businesses Need to Know in ChatGPT’s Second Year
includes addressing algorithmic biases, safeguarding privacy, ensuring security and copyright protection, as well as promoting transparency, fairness, and interpretability. Deploying mechanisms for responsible AI will be central to these... View Details
- 2024
- Article
Neyman Meets Causal Machine Learning: Experimental Evaluation of Individualized Treatment Rules
By: Michael Lingzhi Li and Kosuke Imai
A century ago, Neyman showed how to evaluate the efficacy of treatment using a randomized experiment under a minimal set of assumptions. This classical repeated sampling framework serves as a basis of routine experimental analyses conducted by today’s scientists across... View Details
Li, Michael Lingzhi, and Kosuke Imai. "Neyman Meets Causal Machine Learning: Experimental Evaluation of Individualized Treatment Rules." Journal of Causal Inference 12, no. 1 (2024).
- June 2024
- Case
Aidoc: Building a Hospital-Centric AI Platform
By: Ariel D. Stern and Susan Pinckney
In 2023, Israel-based AI health care company Aidoc evaluated its future. The company, founded in 2016, had grown from commercializing a single AI product for radiologists to a software platform that could detect 20 conditions and immediately notify care teams of... View Details
Keywords: Business Growth and Maturation; Business Model; Business Organization; Business Startups; Disruption; Cost vs Benefits; Decision Choices and Conditions; Decisions; Private Sector; Entrepreneurial Finance; Global Range; Global Strategy; Globalized Markets and Industries; Governance Compliance; Governance Controls; Governing and Advisory Boards; Policy; Medical Specialties; AI and Machine Learning; Digital Platforms; Digital Transformation; Technology Adoption; Disruptive Innovation; Innovation and Management; Innovation Strategy; Laws and Statutes; Growth and Development Strategy; Growth Management; Distribution; Product Development; Success; Performance Efficiency; Strategic Planning; Research and Development; Risk and Uncertainty; Business Strategy; Competitive Advantage; Value Creation; Health Industry; Israel
Stern, Ariel D., and Susan Pinckney. "Aidoc: Building a Hospital-Centric AI Platform." Harvard Business School Case 624-046, June 2024.
- Article
Counterfactual Explanations Can Be Manipulated
By: Dylan Slack, Sophie Hilgard, Himabindu Lakkaraju and Sameer Singh
Counterfactual explanations are useful for both generating recourse and auditing fairness between groups. We seek to understand whether adversaries can manipulate counterfactual explanations in an algorithmic recourse setting: if counterfactual explanations indicate... View Details
Slack, Dylan, Sophie Hilgard, Himabindu Lakkaraju, and Sameer Singh. "Counterfactual Explanations Can Be Manipulated." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
- 2020
- Working Paper
Topic Preference Detection: A Novel Approach to Understand Perspective Taking in Conversation
By: Michael Yeomans and Alison Wood Brooks
Although most humans engage in conversations constantly throughout their lives, conversational mistakes are commonplace— interacting with others is difficult, and conversation re-quires quick, relentless perspective-taking and decision making. For example: during every... View Details
Keywords: Natural Language Processing; Interpersonal Communication; Perspective; Decision Making; Perception
Yeomans, Michael, and Alison Wood Brooks. "Topic Preference Detection: A Novel Approach to Understand Perspective Taking in Conversation." Harvard Business School Working Paper, No. 20-077, February 2020.