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- All HBS Web
(3,053)
- Faculty Publications (599)
- December 16, 2019
- Article
Why Your Startup Won't Last
By: Ranjay Gulati and Vasundhara Sawhney
Why do some startups that have crossed the threshold of “product-market fit” and have a viable business model still fail? This article begins by exploring the argument that most startups need more professionalization to thrive. Founders resist putting in place... View Details
Gulati, Ranjay, and Vasundhara Sawhney. "Why Your Startup Won't Last." HBR Ascend (December 16, 2019).
- Article
How to Use Heuristics for Differential Privacy
By: Seth Neel, Aaron Leon Roth and Zhiwei Steven Wu
We develop theory for using heuristics to solve computationally hard problems in differential privacy. Heuristic approaches have enjoyed tremendous success in machine learning, for which performance can be empirically evaluated. However, privacy guarantees cannot be... View Details
Neel, Seth, Aaron Leon Roth, and Zhiwei Steven Wu. "How to Use Heuristics for Differential Privacy." Proceedings of the IEEE Annual Symposium on Foundations of Computer Science (FOCS) 60th (2019).
- October 2019
- Case
Feeling Machines: Emotion AI at Affectiva
By: Shane Greenstein and John Masko
In 2016, Affectiva—a Boston-based emotion AI software company with a long track record of building emotion-sensing software for market research—had attempted to expand into new verticals by releasing a mobile software development kit (SDK) that downloaders could adapt... View Details
Keywords: Artificial Intelligence; Market Research; Business Model; Finance; Revenue; Decision Making; Risk and Uncertainty; Market Entry and Exit; Applications and Software; AI and Machine Learning; Information Technology Industry; Auto Industry; United States
Greenstein, Shane, and John Masko. "Feeling Machines: Emotion AI at Affectiva." Harvard Business School Case 620-058, October 2019.
- Article
Machine Learning Approaches to Facial and Text Analysis: Discovering CEO Oral Communication Styles
By: Prithwiraj Choudhury, Dan Wang, Natalie A. Carlson and Tarun Khanna
We demonstrate how a novel synthesis of three methods—(1) unsupervised topic modeling of text data to generate new measures of textual variance, (2) sentiment analysis of text data, and (3) supervised ML coding of facial images with a cutting-edge convolutional neural... View Details
Keywords: CEOs; Communication Style; Machine Learning; Spoken Communication; Nonverbal Communication; Personal Characteristics; Analysis; Performance
Choudhury, Prithwiraj, Dan Wang, Natalie A. Carlson, and Tarun Khanna. "Machine Learning Approaches to Facial and Text Analysis: Discovering CEO Oral Communication Styles." Strategic Management Journal 40, no. 11 (November 2019): 1705–1732.
- October 2019
- Case
Leading Bank Leumi into the Future
By: Joshua D. Margolis, Allison M. Ciechanover, Nicole Keller and Danielle Golan
An unlikely but highly effective leader of a traditional bank, Rakefet Russak-Aminoach, simultaneously leads a classic change effort and an unconventional effort to innovate. She focuses her initial energy on making the bank more efficient in the face of industry... View Details
Keywords: Mobile Banking; Digital Banking; Fintech; Startup; Financial Services; Artificial Intelligence; Innovation; Efficiency; Organizational Change; Personal Development; Female Ceo; Banks and Banking; Mobile and Wireless Technology; Leadership; Organizational Change and Adaptation; Innovation and Invention; Disruption; Information Technology; Opportunities; Performance Effectiveness; Personal Development and Career; AI and Machine Learning; Financial Services Industry; Banking Industry; Israel
Margolis, Joshua D., Allison M. Ciechanover, Nicole Keller, and Danielle Golan. "Leading Bank Leumi into the Future." Harvard Business School Case 420-063, October 2019.
- October 2019 (Revised March 2021)
- Background Note
Modern Automation (B): Robotics
By: William R. Kerr and James Palano
Driven largely by advances in perception and situational awareness, robots in the 2010s were gaining functionality that allowed them to be applied to fundamentally new types of work. The expanding range of new tasks that could be completed by machines had significant... View Details
Keywords: Robotics; Artificial Intelligence; Future Of Work; Technology Commercialization; Information Technology; Commercialization; Employment; AI and Machine Learning
Kerr, William R., and James Palano. "Modern Automation (B): Robotics." Harvard Business School Background Note 820-069, October 2019. (Revised March 2021.)
- 2019
- Working Paper
Soul and Machine (Learning)
By: Davide Proserpio, John R. Hauser, Xiao Liu, Tomomichi Amano, Alex Burnap, Tong Guo, Dokyun Lee, Randall Lewis, Kanishka Misra, Eric Schwarz, Artem Timoshenko, Lilei Xu and Hema Yoganarasimhan
Machine learning is bringing us self-driving cars, improved medical diagnostics, and machine translation, but can it improve marketing decisions? It can. Machine learning models predict extremely well, are scalable to “big data,” and are a natural fit to rich media... View Details
Proserpio, Davide, John R. Hauser, Xiao Liu, Tomomichi Amano, Alex Burnap, Tong Guo, Dokyun Lee, Randall Lewis, Kanishka Misra, Eric Schwarz, Artem Timoshenko, Lilei Xu, and Hema Yoganarasimhan. "Soul and Machine (Learning)." Harvard Business School Working Paper, No. 20-036, September 2019.
- 2020
- Working Paper
Improving Regulatory Effectiveness Through Better Targeting: Evidence from OSHA
By: Matthew S. Johnson, David I. Levine and Michael W. Toffel
We study how a regulator can best target inspections. Our case study is a US Occupational Safety and Health Administration (OSHA) program that randomly allocated some inspections. On average, each inspection averted 2.4 serious injuries (9%) over the next five years.... View Details
Keywords: Government Administration; Working Conditions; Safety; Quality; Production; Analysis; Resource Allocation; Manufacturing Industry; United States
Johnson, Matthew S., David I. Levine, and Michael W. Toffel. "Improving Regulatory Effectiveness Through Better Targeting: Evidence from OSHA." Harvard Business School Working Paper, No. 20-019, August 2019. (Revised February 2020.)
- July 2019
- Case
Christmas Inc. (A)
By: Susanna Gallani, Gregory Sabin, Lexor Adams and Nicholas Haberling
Santa Claus is facing increasing pressures to contain costs. The economic model that has worked for centuries is starting to show some cracks, to the point that he is considering outsourcing part of its toy production. Evaluating the bids his team collected from... View Details
Gallani, Susanna, Gregory Sabin, Lexor Adams, and Nicholas Haberling. "Christmas Inc. (A)." Harvard Business School Case 120-009, July 2019.
- July 2019 (Revised November 2019)
- Case
Osaro: Picking the Best Path
By: William R. Kerr, James Palano and Bastiane Huang
The founder of Osaro saw the potential of deep reinforcement learning to allow robots to be applied to new applications. Osaro targeted warehousing, already a dynamic industry for robotics and automation, for its initial product—a system which would allow robotic arms... View Details
Keywords: Artificial Intelligence; Machine Learning; Robotics; Robots; Ecommerce; Fulfillment; Warehousing; AI; Startup; Technology Commercialization; Business Startups; Entrepreneurship; Logistics; Order Taking and Fulfillment; Information Technology; Commercialization; Learning; Complexity; Competition; E-commerce
Kerr, William R., James Palano, and Bastiane Huang. "Osaro: Picking the Best Path." Harvard Business School Case 820-012, July 2019. (Revised November 2019.)
- July 2019
- Teaching Note
Miroglio Fashion
By: Sunil Gupta
Teaching Note for HBS Nos. 519-053, 519-070, and 519-072. View Details
- June 2019
- Teaching Note
Zebra Medical Vision
By: Shane Greenstein and Sarah Gulick
Teaching note is meant to accompany Zebra Medical Vision case, which offers a look at a company’s decisions as a small startup competing with other startups and major technology companies. It also demonstrates the challenges faced by a machine learning company working... View Details
- Article
Use of Crowd Innovation to Develop an Artificial Intelligence-Based Solution for Radiation Therapy Targeting
By: Raymond H. Mak, Michael G. Endres, Jin Hyun Paik, Rinat A. Sergeev, Hugo Aerts, Christopher L. Williams, Karim R. Lakhani and Eva C. Guinan
Importance: Radiation therapy (RT) is a critical cancer treatment, but the existing radiation oncologist work force does not meet growing global demand. One key physician task in RT planning involves tumor segmentation for targeting, which requires substantial... View Details
Keywords: Crowdsourcing; AI Algorithms; Health Care and Treatment; Collaborative Innovation and Invention; AI and Machine Learning
Mak, Raymond H., Michael G. Endres, Jin Hyun Paik, Rinat A. Sergeev, Hugo Aerts, Christopher L. Williams, Karim R. Lakhani, and Eva C. Guinan. "Use of Crowd Innovation to Develop an Artificial Intelligence-Based Solution for Radiation Therapy Targeting." JAMA Oncology 5, no. 5 (May 2019): 654–661.
- April 2019 (Revised June 2019)
- Case
From Globalization to Dual Digital Transformation: CEO Thierry Breton Leading Atos Into 'Digital Shockwaves' (A)
By: Tsedal Neeley, JT Keller and James Barnett
Thierry Breton, chairman and CEO of IT company Atos, faced a pivotal juncture. After spending eight intense years scaling the company globally to over 100,000 employees in 70 countries, he was ready to take the next crucial step. Breton was convinced that rapid digital... View Details
Keywords: Dual Digital Transformation; Transformation; Disruption; Employees; Competency and Skills; Training; Decision Making; Digital Transformation
Neeley, Tsedal, JT Keller, and James Barnett. "From Globalization to Dual Digital Transformation: CEO Thierry Breton Leading Atos Into 'Digital Shockwaves' (A)." Harvard Business School Case 419-027, April 2019. (Revised June 2019.)
- April 2019 (Revised February 2020)
- Case
Ripple: The Business of Crypto
By: David B. Yoffie and George Gonzalez
The case explores Ripple CEO Brad Garlinghouse’s mission to disrupt the global payments industry by leveraging the cryptocurrency XRP. Students will learn about Bitcoin and the blockchain industry, as well as Ripple’s unique crypto business model. The case provides an... View Details
Keywords: Payment Systems; Cryptocurrency; Bitcoin; Blockchain; Fintech; Business Startups; Business Model; Disruption; Strategy; Banking Industry; Technology Industry
Yoffie, David B., and George Gonzalez. "Ripple: The Business of Crypto." Harvard Business School Case 719-506, April 2019. (Revised February 2020.)
- April 2019 (Revised June 2019)
- Case
Western Governors University: 10x Vision
By: William R. Kerr and Susie L. Ma
Western Governors University (WGU) was a nonprofit institution of higher education whose online learning model served more than 100,000 students in 2019 and was scaling rapidly. President Scott Pulsipher wanted to expand WGU’s reach to millions more with a plan called... View Details
Keywords: Online Education; Enrollment; Scaling; Higher Education; Internet and the Web; Business Model; Expansion; Growth and Development Strategy; Education Industry; United States
Kerr, William R., and Susie L. Ma. "Western Governors University: 10x Vision." Harvard Business School Case 819-093, April 2019. (Revised June 2019.)
- March 2019
- Teaching Note
Numenta: Inventing and (or) Commercializing AI
By: David B. Yoffie
This teaching notes accompanies the Numenta case, HBS No. 716-469. The focus is how to scale a new artificial intelligence technology, how to build a platform and overcome chicken-or-the-egg problems, and how to utilize open source software and licensing. View Details
- March 2019
- Case
Wattpad
By: John Deighton and Leora Kornfeld
How to run a platform to match four million writers of stories to 75 million readers? Use data science. Make money by doing deals with television and filmmakers and book publishers. The case describes the challenges of matching readers to stories and of helping writers... View Details
Keywords: Platform Businesses; Creative Industries; Publishing; Data Science; Machine Learning; Collaborative Filtering; Women And Leadership; Managing Data Scientists; Big Data; Recommender Systems; Digital Platforms; Information Technology; Intellectual Property; Analytics and Data Science; Publishing Industry; Entertainment and Recreation Industry; Canada; United States; Philippines; Viet Nam; Turkey; Indonesia; Brazil
Deighton, John, and Leora Kornfeld. "Wattpad." Harvard Business School Case 919-413, March 2019.
- 2023
- Working Paper
When Does Gamified Training Improve Performance? The Roles of Office and Leader Engagement
By: Ryan W. Buell, Wei Cai and Tatiana Sandino
Gamified training is a novel management control system in which companies use gamification
techniques to engage and motivate employees to learn. This study empirically examines the
performance consequences of gamified training using data from a natural field... View Details
Keywords: Gamified Training; Management Control Systems; Employee Engagement; Employees; Learning; Training; Motivation and Incentives; Performance
Buell, Ryan W., Wei Cai, and Tatiana Sandino. "When Does Gamified Training Improve Performance? The Roles of Office and Leader Engagement." Harvard Business School Working Paper, No. 19-101, March 2019. (Revised October 2023.)
- March 2019
- Article
A Structural Analysis of the Role of Superstars in Crowdsourcing Contests
By: Shunyuan Zhang, Param Singh and Anindya Ghose
We investigate the long-term impact of competing against superstars in crowdsourcing contests. Using a unique 50-month longitudinal panel data set on 1677 software design crowdsourcing contests, we illustrate a learning effect where participants are able to improve... View Details
Keywords: Crowdsourcing Contests; Superstar Effect; Bayesian Learning; Utility; Economics Of Information System; Dynamic Structural Model; Dynamic Programming; Markov Chain; Monte Carlo; Learning; Competition; Performance Improvement
Zhang, Shunyuan, Param Singh, and Anindya Ghose. "A Structural Analysis of the Role of Superstars in Crowdsourcing Contests." Information Systems Research 30, no. 1 (March 2019): 15–33.