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- All HBS Web
(1,154)
- Faculty Publications (360)
- October 2018
- Article
The Operational Value of Social Media Information
By: Ruomeng Cui, Santiago Gallino, Antonio Moreno and Dennis J. Zhang
While the value of using social media information has been established in multiple business contexts, the field of operations and supply chain management have not yet explored the possibilities it offers in improving firms' operational decisions. This study attempts to... View Details
Cui, Ruomeng, Santiago Gallino, Antonio Moreno, and Dennis J. Zhang. "The Operational Value of Social Media Information." Special Issue on Big Data in Supply Chain Management. Production and Operations Management 27, no. 10 (October 2018): 1749–1774.
- September 2018 (Revised December 2019)
- Case
Zebra Medical Vision
By: Shane Greenstein and Sarah Gulick
An Israeli startup founded in 2014, Zebra Medical Vision developed algorithms that produced diagnoses from X-rays, mammograms, and CT-scans. The algorithms used deep learning and digitized radiology scans to create software that could assist doctors in making... View Details
Keywords: Radiology; Machine Learning; X-ray; CT Scan; Medical Technology; Probability; FDA 510(k); Diagnosis; Business Startups; Health Care and Treatment; Information Technology; Applications and Software; Competitive Strategy; Product Development; Commercialization; Decision Choices and Conditions; Medical Devices and Supplies Industry; Medical Devices and Supplies Industry; Medical Devices and Supplies Industry; Israel
Greenstein, Shane, and Sarah Gulick. "Zebra Medical Vision." Harvard Business School Case 619-014, September 2018. (Revised December 2019.)
- 2020
- Working Paper
Machine Learning for Pattern Discovery in Management Research
Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used as an observation for further inductive or abductive research, but should not be treated as the result of a... View Details
Keywords: Machine Learning; Theory Building; Induction; Decision Trees; Random Forests; K-nearest Neighbors; Neural Network; P-hacking; Analytics and Data Science; Analysis
Choudhury, Prithwiraj, Ryan Allen, and Michael G. Endres. "Machine Learning for Pattern Discovery in Management Research." Harvard Business School Working Paper, No. 19-032, September 2018. (Revised June 2020.)
- August 2018 (Revised October 2019)
- Case
C3.ai—Driven to Succeed
By: Robert Simons and George Gonzalez
CEO Tom Siebel navigates his artificial intelligence (ai) startup through a series of pivots, market expansions, and even an elephant attack to become a leading platform ad service provider. The case describes his unusual management approach emphasizing employee... View Details
Keywords: Strategy Execution; Performance Measurement; Critical Performance Variables; Strategic Boundaries; Internet Of Things; Artificial Intelligence; Software Development; Big Data; Machine Learning; Business Startups; Management Style; Business Strategy; Performance; Measurement and Metrics; Organizational Culture; AI and Machine Learning; Digital Transformation; Applications and Software; Digital Marketing; Analytics and Data Science; Technology Industry; United States; California
Simons, Robert, and George Gonzalez. "C3.ai—Driven to Succeed." Harvard Business School Case 119-004, August 2018. (Revised October 2019.)
- August 2018 (Revised October 2020)
- Case
Tailor Brands: Artificial Intelligence-Driven Branding
By: Jill Avery
Using proprietary artificial intelligence technology, startup Tailor Brands set out to democratize branding by allowing small businesses to create their brand identities by automatically generating logos in just minutes at minimal cost with no branding or design skills... View Details
Keywords: Startup; Services; Artificial Intelligence; Machine Learning; Digital Marketing; Brand Management; Big Data; Internet Marketing; Analytics; Marketing; Marketing Strategy; Brands and Branding; Information Technology; Entrepreneurship; Venture Capital; Business Model; Consumer Behavior; AI and Machine Learning; Analytics and Data Science; Advertising Industry; Service Industry; Technology Industry; United States; North America; Israel
Avery, Jill. "Tailor Brands: Artificial Intelligence-Driven Branding." Harvard Business School Case 519-017, August 2018. (Revised October 2020.)
- 2018
- Working Paper
Some Facts of High-Tech Patenting
By: Michael Webb, Nick Short, Nicholas Bloom and Josh Lerner
Patenting in software, cloud computing, and artificial intelligence has grown rapidly in recent years. Such patents are acquired primarily by large U.S. technology firms such as IBM, Microsoft, Google, and HP, as well as by Japanese multinationals such as Sony, Canon,... View Details
Webb, Michael, Nick Short, Nicholas Bloom, and Josh Lerner. "Some Facts of High-Tech Patenting." Harvard Business School Working Paper, No. 19-014, August 2018. (NBER Working Paper Series, No. 24793, July 2018.)
- April 2018 (Revised February 2019)
- Supplement
Improving Worker Safety in the Era of Machine Learning (B)
By: Michael W. Toffel, Dan Levy, Astrid Camille Pineda, Jose Ramon Morales Arilla and Matthew S. Johnson
Supplements the (A) case. View Details
Toffel, Michael W., Dan Levy, Astrid Camille Pineda, Jose Ramon Morales Arilla, and Matthew S. Johnson. "Improving Worker Safety in the Era of Machine Learning (B)." Harvard Business School Supplement 618-064, April 2018. (Revised February 2019.)
- March 2018
- Case
IBM: Watson and the Internet of Things
By: Rajiv Lal and Scott Johnson
IBM has recently launched a business unit devoted to the Internet of Things. The group's leadership team needs to figure out the best way to quickly scale its business in a fragmented and nascent market. View Details
- February 2018
- Case
Vodafone: Managing Advanced Technologies and Artificial Intelligence
By: William R. Kerr and Emer Moloney
Vodafone was operating in the fast-moving telecommunications market where innovation and scale were key. Faced with an onslaught of technological advances—big data, automation, and artificial intelligence—CEO Vittorio Colao reflected on how he should change the... View Details
Keywords: Technological Innovation; Management; Organizational Change and Adaptation; Corporate Social Responsibility and Impact; Opportunities; Telecommunications Industry
Kerr, William R., and Emer Moloney. "Vodafone: Managing Advanced Technologies and Artificial Intelligence." Harvard Business School Case 318-109, February 2018.
- February 2018
- Case
Amazon, Google, and Apple: Smart Speakers and the Battle for the Connected Home
By: Rajiv Lal and Scott Johnson
Amazon, Google, and Apple all offer their own smart speaker. The devices represent each firm's entry point into the connected home market. All three companies come into the space with their own strengths and weaknesses. Who will win? View Details
Keywords: Apple; Apple Inc.; Google; Amazon; Amazon.com; Google Home; Homepod; Echo; Smart Home; Connected Home; Voice; Artificial Intelligence; Machine Learning; Internet Of Things; Smart Speaker; Connected Speaker; Intelligent Assistants; Virtual Assistants; Voice Assistants; Alexa; Google Assistant; Siri; Technological Innovation; Disruptive Innovation; Competitive Strategy; Business Strategy; Adoption; Information Infrastructure; Information Technology; Internet and the Web; Mobile and Wireless Technology; Applications and Software; Technology Adoption; Digital Platforms; Household; AI and Machine Learning; Electronics Industry; Technology Industry; United States
Lal, Rajiv, and Scott Johnson. "Amazon, Google, and Apple: Smart Speakers and the Battle for the Connected Home." Harvard Business School Case 518-035, February 2018.
- February 2018 (Revised March 2018)
- Case
Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP)
By: Lauren Cohen, Christopher Malloy and William Powley
This case examines the intersection of two firms (Cogent Labs—a machine learning software firm in Tokyo; and Google, the technology infrastructure giant) attempting to exploit the benefits of artificial intelligence and machine learning in the financial services... View Details
Keywords: Technological Innovation; Finance; Growth and Development Strategy; Business Model; Applications and Software; Infrastructure; Technology Industry; Financial Services Industry
Cohen, Lauren, Christopher Malloy, and William Powley. "Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP)." Harvard Business School Case 218-080, February 2018. (Revised March 2018.)
- February 2018 (Revised October 2019)
- Case
HubSpot and Motion AI: Chatbot-Enabled CRM
By: Jill Avery and Thomas Steenburgh
HubSpot, an inbound marketing, sales, and customer relationship management (CRM) software provider, announced that it had acquired Motion AI, a software platform that enabled companies to easily build and deploy chatbots, fueled by artificial intelligence, to interact... View Details
Keywords: CRM; Sales Management; Customer Service; Artificial Intelligence; B2B Vs. B2C; Business Marketing; SaaS; Marketing; Marketing Strategy; Brands and Branding; Customer Focus and Relationships; Sales; Salesforce Management; Technological Innovation; Applications and Software; Customer Relationship Management; AI and Machine Learning; Technology Industry; Service Industry; United States; North America
Avery, Jill, and Thomas Steenburgh. "HubSpot and Motion AI: Chatbot-Enabled CRM." Harvard Business School Case 518-067, February 2018. (Revised October 2019.)
- February 2018 (Revised June 2021)
- Case
New Constructs: Disrupting Fundamental Analysis with Robo-Analysts
By: Charles C.Y. Wang and Kyle Thomas
This case highlights the business challenges associated with a financial technology firm, New Constructs, that created a technology that can quickly parse complicated public firm financials to paint a clearer economic picture of firms, remove accounting distortions,... View Details
Keywords: Fundamental Analysis; Machine Learning; Robo-analysts; Financial Statements; Financial Reporting; Analysis; Information Technology; Accounting Industry; Financial Services Industry; Information Technology Industry; North America; Tennessee
Wang, Charles C.Y., and Kyle Thomas. "New Constructs: Disrupting Fundamental Analysis with Robo-Analysts." Harvard Business School Case 118-068, February 2018. (Revised June 2021.)
- February 2018
- Article
Retention Futility: Targeting High-Risk Customers Might Be Ineffective.
By: Eva Ascarza
Companies in a variety of sectors are increasingly managing customer churn proactively, generally by detecting customers at the highest risk of churning and targeting retention efforts towards them. While there is a vast literature on developing churn prediction models... View Details
Keywords: Retention/churn; Proactive Churn Management; Field Experiments; Heterogeneous Treatment Effect; Machine Learning; Customer Relationship Management; Risk Management
Ascarza, Eva. "Retention Futility: Targeting High-Risk Customers Might Be Ineffective." Journal of Marketing Research (JMR) 55, no. 1 (February 2018): 80–98.
- January 2018 (Revised February 2023)
- Teaching Note
The Future of Patent Examination at the USPTO
This teaching note pairs with the case entitled: “The Future of Patent Examination at the USPTO” (case no. 617-027). View Details
- 2019
- Working Paper
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
Choudhury, Prithwiraj, Dan Wang, Natalie A. Carlson, and Tarun Khanna. "Machine Learning Approaches to Facial and Text Analysis: Discovering CEO Oral Communication Styles." Harvard Business School Working Paper, No. 18-064, January 2018. (Revised May 2019.)
- January 2018 (Revised March 2019)
- Case
Autonomous Vehicles: The Rubber Hits the Road...but When?
By: William Kerr, Allison Ciechanover, Jeff Huizinga and James Palano
The rise of autonomous vehicles has enormous implications for business and society. Despite the many headlines and significant investment in the technology by early 2019, it was still unclear when truly autonomous vehicles would be a commercial reality. Students will... View Details
Keywords: Technology Management; Artificial Intelligence; General Management; Robotics; Technological Innovation; Transportation; Disruption; Information Technology; Decision Making; AI and Machine Learning; Auto Industry; Technology Industry
Kerr, William, Allison Ciechanover, Jeff Huizinga, and James Palano. "Autonomous Vehicles: The Rubber Hits the Road...but When?" Harvard Business School Case 818-088, January 2018. (Revised March 2019.)
- Article
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness
By: Michael J Kearns, Seth Neel, Aaron Leon Roth and Zhiwei Steven Wu
The most prevalent notions of fairness in machine learning are statistical definitions: they fix a small collection of pre-defined groups, and then ask for parity of some statistic of the classifier (like classification rate or false positive rate) across these groups.... View Details
Kearns, Michael J., Seth Neel, Aaron Leon Roth, and Zhiwei Steven Wu. "Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness." Proceedings of the International Conference on Machine Learning (ICML) 35th (2018).
- October 2017 (Revised April 2018)
- Case
Improving Worker Safety in the Era of Machine Learning (A)
By: Michael W. Toffel, Dan Levy, Jose Ramon Morales Arilla and Matthew S. Johnson
Managers make predictions all the time: How fast will my markets grow? How much inventory do I need? How intensively should I monitor my suppliers? Which potential customers will be most responsive to a particular marketing campaign? Which job candidates should I... View Details
Keywords: Machine Learning; Policy Implementation; Empirical Research; Inspection; Occupational Safety; Occupational Health; Regulation; Analysis; Forecasting and Prediction; Policy; Operations; Supply Chain Management; Safety; Manufacturing Industry; Construction Industry; United States
Toffel, Michael W., Dan Levy, Jose Ramon Morales Arilla, and Matthew S. Johnson. "Improving Worker Safety in the Era of Machine Learning (A)." Harvard Business School Case 618-019, October 2017. (Revised April 2018.)
- August 2017 (Revised July 2019)
- Case
GROW: Using Artificial Intelligence to Screen Human Intelligence
By: Ethan Bernstein, Paul McKinnon and Paul Yarabe
Over 10% of all 2017 university graduates in Japan used GROW, an artificial intelligence platform and mobile app developed by Tokyo-based people analytics startup IGS, to recruit for a job. This case puts participants in the shoes of IGS founder and CEO Masahiro... View Details
Keywords: Big Data; Artificial Intelligence; Talent and Talent Management; Recruitment; Selection and Staffing; Human Resources; Information Technology; AI and Machine Learning; Analytics and Data Science; Financial Services Industry; Air Transportation Industry; Advertising Industry; Manufacturing Industry; Technology Industry; Japan
Bernstein, Ethan, Paul McKinnon, and Paul Yarabe. "GROW: Using Artificial Intelligence to Screen Human Intelligence." Harvard Business School Case 418-020, August 2017. (Revised July 2019.)