Publications
Publications
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- Faculty Publications (335)
- March 2022 (Revised January 2024)
- Case
Moksha Data: Delivering Insights for Public Service
By: Ashish Nanda and Zack Kurtovich
Moksha Data, a boutique consulting firm specializing in public sector work, started in January 2017 with a handshake between friends and a shared commitment to the principles of egalitarianism, ownership, and collaboration. The Houston-based firm had built momentum... View Details
Keywords: Professional Service Firms; Professional Service Firm; Strategy Formulation; Data; Data As A Service; Government Contracting; Consulting; Consulting Firms; Consulting Services; Entrepreneurship; Public Sector; Analytics and Data Science; Growth and Development; Strategy; Consulting Industry; Texas
- March 2022
- Article
Where to Locate COVID-19 Mass Vaccination Facilities?
By: Dimitris Bertsimas, Vassilis Digalakis Jr, Alexander Jacquillat, Michael Lingzhi Li and Alessandro Previero
The outbreak of COVID-19 led to a record-breaking race to develop a vaccine. However, the limited vaccine capacity creates another massive challenge: how to distribute vaccines to mitigate the near-end impact of the pandemic? In the United States in particular, the new... View Details
- February 2022
- Case
CityScore: Big Data Comes to Boston
By: Boris Groysberg and Sarah L. Abbott
In 2016, Martin “Marty” Walsh, the Mayor of Boston, introduced CityScore, a data dashboard that measured the city’s progress across a range of metrics. The dashboard was updated daily and publicly available. The mayor frequently discussed the CityScore targets in... View Details
- February 2022
- Teaching Plan
Community Solutions
By: Brian Trelstad and Tom Quinn
Teaching Plan for HBS Case No. 322-021. Community Solutions was an anti-homelessness nonprofit founded in 2011 after protagonist Rosanne Haggerty grew frustrated with the limited impact of traditional housing and outreach strategies. It set an ambitious goal, reached... View Details
- 2022
- Working Paper
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective
By: Satyapriya Krishna, Tessa Han, Alex Gu, Javin Pombra, Shahin Jabbari, Steven Wu and Himabindu Lakkaraju
As various post hoc explanation methods are increasingly being leveraged to explain complex models in high-stakes settings, it becomes critical to develop a deeper understanding of if and when the explanations output by these methods disagree with each other, and how... View Details
- 2022
- Chapter
Measuring Compliance Risk and the Emergence of Analytics
By: Eugene F. Soltes
Corporate compliance manages a diverse set of regulatory and reputational concerns ranging from fraud to privacy to discrimination. However, effectively managing such risks has often been hampered by a lack of adequate information about when, where, and why misconduct... View Details
- January 2022 (Revised February 2022)
- Case
Introducing EVA at ISS: A Better Way to Evaluate CEO Performance and Compensation?
By: Jonas Heese, Charles C.Y. Wang and James Weber
In early 2019, Anthony Campagna, the global director of fundamental research at ISS EVA, a unit of the proxy advisory firm Institutional Shareholder Services (ISS), was preparing to release ISS's analyses of public company performance and CEO compensation ahead of Say... View Details
- January 2022
- Article
Artificial Intelligence, Data-Driven Learning, and the Decentralized Structure of Platform Ecosystems
By: David R. Clough and Andy Wu
Gregory, Henfridsson, Kaganer, and Kyriakou (2020) highlight the important role of data and AI as strategic resources that platforms may use to enhance user value. However, their article overlooks a significant conceptual distinction: the installed base of... View Details
- December 2021
- Case
Burning Glass Technologies: From Data to Product
By: Suraj Srinivasan and Amy Klopfenstein
In May 2021, Matt Sigelman, CEO of Burning Glass Technologies, a company that provided labor market analytics for a variety of markets, navigates his company’s transition from data company to product company. Burning Glass originated as a service that used artificial... View Details
Keywords: Information Technology; Applications and Software; Digital Platforms; Internet and the Web; Strategy; Expansion; Business Strategy; Labor; Employment; Human Capital; Jobs and Positions; Job Design and Levels; Job Search; Human Resources; Selection and Staffing; Recruitment; Employees; Retention; Competency and Skills; Experience and Expertise; Talent and Talent Management; Analytics and Data Science; Business Model; Technology Industry; North and Central America; United States
- Article
Core Earnings: New Data and Evidence
By: Ethan Rouen, Eric C. So and Charles C.Y. Wang
Using a novel dataset, we show that components of firms' GAAP earnings stemming from ancillary business activities or transitory shocks are significant in frequency and magnitude. These components have grown over time and are dispersed across various sections of the... View Details
- November 2021 (Revised December 2021)
- Supplement
PittaRosso (B): Human and Machine Learning
By: Ayelet Israeli
This case supplements the "PittaRosso: Artificial Intelligence-Driven Pricing and Promotion" case, and provides major highlights on what happened at the company since the first case. 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; 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 2021 (Revised February 2022)
- Case
Newsweek: Driving a Digital First Strategy
By: Lynda M. Applegate and Suraj Srinivasan
The case describes the transformation at Newsweek, the storied news magazine that had fallen from its commanding position as a premier print publication unable to find its footing in the fast changing digital media landscape. After buying Newsweek and taking over as... View Details
- October 2021 (Revised March 2022)
- Supplement
PittaRosso: Artificial Intelligence-Driven Pricing and Promotion
By: Ayelet Israeli and Fabrizio Fantini
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; Price; Advertising Campaigns; Analytics and Data Science; Analysis; Digital Marketing; Budgets and Budgeting; Marketing Strategy; Marketing; Transformation; Decision Making; Retail Industry; Italy
- 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
- 2021
- Working Paper
The Value of Data and Its Impact on Competition
By: Marco Iansiti
Common regulatory perspective on the relationship between data, value, and competition in online platforms has increasingly centered on the volume of data accumulated by incumbent firms. This view posits the existence of "data network effects," where more data leads to... 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
- June 2021 (Revised November 2024)
- Case
MicroStrategy: Accounting for Cryptocurrency
By: Jonas Heese and Annelena Lobb
On February 15, 2021, Alina Moss, an analyst who covered the technology company MicroStrategy, pondered a rise in MicroStrategy’s share price. Moss had dialed into the company earnings call. When it ended, Moss had more questions than answers. MicroStrategy had... 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