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(5,032)
- Faculty Publications (980)
- December 2020 (Revised March 2022)
- Teaching Note
Forecasting ClimaCell
By: Joshua Lev Krieger, Christopher Stanton and James Barnett
A weather technology startup, ClimaCell considers the R&D trade-offs and financing implications of pursuing a proposed contract with a major automobile maker, rather than continuing its focus on building a scalable, all-purpose weather prediction engine. View Details
- December 2020
- Case
VIA Science (A)
By: Juan Alcácer, Rembrand Koning, Annelena Lobb and Kerry Herman
Via (a) captures the early days of the data analytics startup as founders Gounden and Ravanis considered which markets offer the right opportunities for their firm and what kinds of experiments will help them narrow their choice. Supplement Via (b) reveals the... View Details
Keywords: Data Analytics; Machine Learning; Artificial Intelligence; Strategy; Business Startups; Markets; AI and Machine Learning; Telecommunications Industry; Utilities Industry; United States; Japan
Alcácer, Juan, Rembrand Koning, Annelena Lobb, and Kerry Herman. "VIA Science (A)." Harvard Business School Case 721-367, December 2020.
- December 2020
- Supplement
VIA Science (B)
By: Juan Alcácer, Rembrand Koning, Annelena Lobb and Kerry Herman
Via (a) captures the early days of the data analytics startup as founders Gounden and Ravanis considered which markets offer the right opportunities for their firm and what kinds of experiments will help them narrow their choice. Supplement Via (b) reveals the... View Details
Keywords: Data Analytics; Machine Learning; Artificial Intelligence; Strategy; Business Startups; AI and Machine Learning; Telecommunications Industry; Utilities Industry; United States; Japan
Alcácer, Juan, Rembrand Koning, Annelena Lobb, and Kerry Herman. "VIA Science (B)." Harvard Business School Supplement 721-368, December 2020.
- 2020
- Working Paper
An Empirical Guide to Investor-Level Private Equity Data from Preqin
By: Juliane Begenau, Claudia Robles-Garcia, Emil Siriwardane and Lulu Wang
This note provides guidance on the use of investor-level private equity data from Preqin for empirical research. Preqin primarily sources its cash flow data through Freedom of Information Act (FOIA) requests with U.S. public pensions. Our focus is on the components of... View Details
Keywords: Private Equity Returns; Prequin Data; Private Equity; Analytics and Data Science; Investment Return
Begenau, Juliane, Claudia Robles-Garcia, Emil Siriwardane, and Lulu Wang. "An Empirical Guide to Investor-Level Private Equity Data from Preqin." Working Paper, December 2020.
- December 2020
- Other Article
Digital Health Care: Empowering Consumers: Q&A with Professor Regina Herzlinger
Regina Herzlinger, the Nancy R. McPherson Professor of Business Administration, has been studying the health care sector for nearly half a century. In that time, she has seen significant innovation in the field—and she has also seen the powerful sway of the status quo,... View Details
Keywords: Digital Health; Telemedicine; Wearable Sensors; Health Care and Treatment; Technological Innovation; Health Industry
Herzlinger, Regina E. "Digital Health Care: Empowering Consumers: Q&A with Professor Regina Herzlinger." HBS Alumni Bulletin (December 2020).
- November–December 2021
- Article
Does Gender Matter? The Effect of Management Responses on Reviewing Behavior
By: Davide Proserpio, Isamar Troncoso and Francesca Valsesia
We study the effect of management responses on the reviewing behavior of self-identified female and male reviewers. Using data from Tripadvisor, we show that after hotels begin to respond to reviews, the probability that a negative review comes from a self-identified... View Details
Keywords: Word Of Mouth; Online Reviews; Management Responses; E-commerce; Gender; Prejudice and Bias; Digital Platforms; Customers
Proserpio, Davide, Isamar Troncoso, and Francesca Valsesia. "Does Gender Matter? The Effect of Management Responses on Reviewing Behavior." Marketing Science 40, no. 6 (November–December 2021): 1199–1213.
- Article
Making a Difference: Developing Actionable Knowledge for Practice and Theory
By: Michael Beer
There is a widely acknowledged gap between academic research and practice. While the field of organizational studies and development has had an impact on management practice in some organizations, it has had only a modest impact on widely accepted management practice... View Details
Keywords: Actionable Knowledge; Actionable Practice; Normal Science; Scholar-consultant; Management Practices and Processes; Theory; Innovation Leadership; Organizations; Performance Effectiveness
Beer, Michael. "Making a Difference: Developing Actionable Knowledge for Practice and Theory." Journal of Applied Behavioral Science 56, no. 4 (December 2020): 506–520.
- 2021
- Working Paper
The Value of Descriptive Analytics: Evidence from Online Retailers
By: Ron Berman and Ayelet Israeli
Does the adoption of descriptive analytics impact online retailer performance, and if so, how? We use the synthetic difference-in-differences method to analyze the staggered adoption of a retail analytics dashboard by more than 1,500 e-commerce websites, and we find an... View Details
Keywords: Descriptive Analytics; Big Data; Synthetic Control; E-commerce; Online Retail; Difference-in-differences; Martech; Internet and the Web; Analytics and Data Science; Performance; Retail Industry
Berman, Ron, and Ayelet Israeli. "The Value of Descriptive Analytics: Evidence from Online Retailers." Harvard Business School Working Paper, No. 21-067, November 2020. (Revised December 2021. Accepted at Marketing Science.)
- 2020
- Working Paper
Dog Eat Dog: Balancing Network Effects and Differentiation in a Digital Platform Merger
By: Chiara Farronato, Jessica Fong and Andrey Fradkin
Digital platforms are increasingly the subject of regulatory scrutiny. In comparison to multiple competitors, a single platform may increase consumer welfare if network effects are large or may decrease welfare due to higher prices or reduction in platform variety. We... View Details
Keywords: Platform Differentiation; Digital Platforms; Network Effects; Measurement and Metrics; Mergers and Acquisitions; Outcome or Result
Farronato, Chiara, Jessica Fong, and Andrey Fradkin. "Dog Eat Dog: Balancing Network Effects and Differentiation in a Digital Platform Merger." NBER Working Paper Series, No. 28047, November 2020.
- November 2020
- Teaching Note
DayTwo: Going to Market with Gut Microbiome
By: Ayelet Israeli
Teaching Note for HBS Case No. 519-010. DayTwo is a young Israeli startup that applies research on the gut microbiome and machine learning algorithms to deliver personalized nutritional recommendations to its users in order to minimize blood sugar spikes after meals.... View Details
Keywords: Start-up Growth; Startup; Positioning; Targeting; Go To Market Strategy; B2B Vs. B2C; B2B2C; Health & Wellness; AI; Machine Learning; Female Ceo; Female Protagonist; Science-based; Science And Technology Studies; Ecommerce; Applications; DTC; Direct To Consumer Marketing; US Health Care; "USA,"; Innovation; Pricing; Business Growth; Segmentation; Distribution Channels; Growth and Development Strategy; Business Startups; Science-Based Business; Health; Innovation and Invention; Marketing; Information Technology; Business Growth and Maturation; E-commerce; Applications and Software; Technology Industry; Technology Industry; Technology Industry; Technology Industry; Technology Industry; Israel; United States
- 2020
- Working Paper
Hospital Allocation and Racial Disparities in Health Care
By: Amitabh Chandra, Pragya Kakani and Adam Sacarny
We develop a simple framework to measure the role of hospital allocation in racial disparities in health care and use it to study Black and white Medicare patients who are treated for heart attacks—a condition where virtually everyone receives care, hospital care is... View Details
Chandra, Amitabh, Pragya Kakani, and Adam Sacarny. "Hospital Allocation and Racial Disparities in Health Care." NBER Working Paper Series, No. 28018, November 2020.
- October 2020 (Revised November 2023)
- Case
COVID-19 Testing at Everlywell
By: Jeffrey J. Bussgang and Olivia Hull
In March 2020, as COVID-19 spreads rapidly across the U.S., Everlywell founder Julia Cheek considers how to respond as a small start-up specializing in at-home lab testing. After making dramatic budget cuts, she decides to pivot the organization to address the... View Details
Keywords: Entrepreneurship; Business Strategy; Venture Capital; Health Care and Treatment; Health Disorders; Leading Change; Technology Adoption; Digital Platforms; Competitive Strategy; Science; Adaptation; Corporate Social Responsibility and Impact; Crisis Management; Social Entrepreneurship; Ethics; Government Legislation; Health; Health Testing and Trials; Health Pandemics; Technology Industry; Technology Industry; Technology Industry; Texas; United States
Bussgang, Jeffrey J., and Olivia Hull. "COVID-19 Testing at Everlywell." Harvard Business School Case 821-001, October 2020. (Revised November 2023.)
- September 2020 (Revised July 2022)
- Technical Note
Algorithmic Bias in Marketing
By: Ayelet Israeli and Eva Ascarza
This note focuses on algorithmic bias in marketing. First, it presents a variety of marketing examples in which algorithmic bias may occur. The examples are organized around the 4 P’s of marketing – promotion, price, place and product—characterizing the marketing... View Details
Keywords: Algorithmic Data; Race And Ethnicity; Promotion; "Marketing Analytics"; Marketing And Society; Big Data; Privacy; Data-driven Management; Data Analysis; Data Analytics; E-Commerce Strategy; Discrimination; Targeting; Targeted Advertising; Pricing Algorithms; Ethical Decision Making; Customer Heterogeneity; Marketing; Race; Ethnicity; Gender; Diversity; Prejudice and Bias; Marketing Communications; Analytics and Data Science; Analysis; Decision Making; Ethics; Customer Relationship Management; E-commerce; Apparel and Accessories Industry; Apparel and Accessories Industry; United States
Israeli, Ayelet, and Eva Ascarza. "Algorithmic Bias in Marketing." Harvard Business School Technical Note 521-020, September 2020. (Revised July 2022.)
- September 2020 (Revised February 2024)
- Teaching Note
Artea (A), (B), (C), and (D): Designing Targeting Strategies
By: Eva Ascarza and Ayelet Israeli
Teaching Note for HBS No. 521-021,521-022,521-037,521-043. This collection of exercises aims to teach students about 1)Targeting Policies; and 2)Algorithmic bias in marketing—implications, causes, and possible solutions. Part (A) focuses on A/B testing analysis and... View Details
- September 2020 (Revised July 2022)
- Exercise
Artea (D): Discrimination through Algorithmic Bias in Targeting
By: Eva Ascarza and Ayelet Israeli
This collection of exercises aims to teach students about 1)Targeting Policies; and 2)Algorithmic bias in marketing—implications, causes, and possible solutions. Part (A) focuses on A/B testing analysis and targeting. Parts (B),(C),(D) Introduce algorithmic bias. The... View Details
Keywords: Targeted Advertising; Discrimination; Algorithmic Data; Bias; Advertising; Race; Gender; Marketing; Diversity; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Apparel and Accessories Industry; Apparel and Accessories Industry; Apparel and Accessories Industry; United States
Ascarza, Eva, and Ayelet Israeli. "Artea (D): Discrimination through Algorithmic Bias in Targeting." Harvard Business School Exercise 521-043, September 2020. (Revised July 2022.)
- September 2020 (Revised June 2023)
- Exercise
Artea: Designing Targeting Strategies
By: Eva Ascarza and Ayelet Israeli
This collection of exercises aims to teach students about 1)Targeting Policies; and 2)Algorithmic bias in marketing—implications, causes, and possible solutions. Part (A) focuses on A/B testing analysis and targeting. Parts (B),(C),(D) Introduce algorithmic bias. The... View Details
Keywords: Algorithmic Data; Race And Ethnicity; Experimentation; Promotion; "Marketing Analytics"; Marketing And Society; Big Data; Privacy; Data-driven Management; Data Analytics; Data Analysis; E-Commerce Strategy; Discrimination; Targeted Advertising; Targeted Policies; Targeting; Pricing Algorithms; A/B Testing; Ethical Decision Making; Customer Base Analysis; Customer Heterogeneity; Coupons; Algorithmic Bias; Marketing; Race; Gender; Diversity; Customer Relationship Management; Marketing Communications; Advertising; Decision Making; Ethics; E-commerce; Analytics and Data Science; Apparel and Accessories Industry; Apparel and Accessories Industry; United States
Ascarza, Eva, and Ayelet Israeli. "Artea: Designing Targeting Strategies." Harvard Business School Exercise 521-021, September 2020. (Revised June 2023.)
- September 2020 (Revised June 2023)
- Supplement
Spreadsheet Supplement to Artea Teaching Note
By: Eva Ascarza and Ayelet Israeli
Spreadsheet Supplement to Artea Teaching Note 521-041. This collection of exercises aims to teach students about 1)Targeting Policies; and 2)Algorithmic bias in marketing—implications, causes, and possible solutions. Part (A) focuses on A/B testing analysis and... View Details
Keywords: Targeted Advertising; Algorithmic Data; Bias; Advertising; Race; Gender; Diversity; Marketing; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Apparel and Accessories Industry; Apparel and Accessories Industry; Apparel and Accessories Industry; United States
- 2022
- Working Paper
Where the Cloud Rests: The Location Strategies of Data Centers
By: Shane Greenstein and Tommy Pan Fang
This study provides an analysis of the entry strategies of third-party data centers in the United States. We examine the market before the pandemic in 2018 and 2019, when supply and demand for data services were geographically stable. We compare with the entry... View Details
Greenstein, Shane, and Tommy Pan Fang. "Where the Cloud Rests: The Location Strategies of Data Centers." Harvard Business School Working Paper, No. 21-042, September 2020. (Revised June 2022.)
- 2020
- Working Paper
Design Rules, Volume 2: How Technology Shapes Organizations: Chapter 7 The Value Structure of Technologies, Part 2: Strategy without Numbers
Functional analysis as set forth in the last chapter decomposes a technical system into functional components that do things to advance the system’s purpose and the goals of its designers. Functional analysis in turn can be used to construct value structure maps... View Details
Keywords: Modularity; Value Structure Mapping; Value Capture; Information Technology; Organizations; Strategy; Value Creation
Baldwin, Carliss Y. "Design Rules, Volume 2: How Technology Shapes Organizations: Chapter 7 The Value Structure of Technologies, Part 2: Strategy without Numbers." Harvard Business School Working Paper, No. 21-040, September 2020.
- September 2020
- Article
Creativity, Artificial Intelligence, and a World of Surprises
In recent years, progress has been made toward AI Creativity, which I define as the production of highly novel, yet appropriate, ideas, problem solutions, or other outputs by autonomous machines. I argue that organizational researchers of creativity and innovation... View Details
Keywords: Artificial Intelligence; AI Creativity; Computer Science; Organizational Behavior; Psychology; Creativity; Technological Innovation; AI and Machine Learning
Amabile, Teresa M. "Creativity, Artificial Intelligence, and a World of Surprises." Academy of Management Discoveries 6, no. 3 (September 2020): 351–354.