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Publications
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(4,926)
- Faculty Publications (1,003)
- 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
- 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
- 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
- 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
- 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
- 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
- September 2020
- Article
How Multimedia Shape Crowdfunding Outcomes: The Overshadowing Effect of Images and Videos on Text in Campaign Information
By: J Yang, Y Li, Goran Calic and Anton Shevchenko
This study aims to explore the moderating effect of the number of images and videos on the relationship between text length in crowdfunding campaign descriptions and crowdfunding outcomes. We use data from 13,622 technology campaigns on the Kickstarter website to test... View Details
- 2020
- Article
Research on Corporate Sustainability: Review and Directions for Future Research
By: Jody Grewal and George Serafeim
We review the literature on corporate sustainability and provide directions for future research. Our review focuses on three actions: measuring, managing and communicating corporate sustainability performance. Measurement is the least developed of the three and... View Details
Keywords: Sustainability; Sustainability Reporting; Sustainability Management; Nonfinancial Disclosure; Nonfinancial Information; Nonfinancial Performance; Materiality; ESG; ESG (Environmental, Social, Governance) Performance; ESG Disclosure; ESG Disclosure Metrics; ESG Ratings; ESG Reporting; Inequality; Corporate Social Responsibility; Accounting; Finance; Management; Strategy; Environmental Sustainability; Climate Change; Diversity; Equality and Inequality; Corporate Disclosure; Measurement and Metrics; Corporate Governance; Corporate Accountability; Corporate Social Responsibility and Impact
- September–October 2020
- Article
Social-Impact Efforts That Create Real Value
By: George Serafeim
Until the mid-2010s few investors paid attention to environmental, social, and governance (ESG) data—information about companies’ carbon footprints, labor policies, board makeup, and so forth. Today the data is widely used by investors. How can organizations create... View Details
Keywords: Sustainability; Sustainability Management; ESG; ESG (Environmental, Social, Governance) Performance; ESG Disclosure; ESG Disclosure Metrics; ESG Ratings; ESG Reporting; Social Impact; Impact Measurement; Social Innovation; Purpose; Corporate Purpose; Corporate Social Responsibility; Strategy; Social Enterprise; Society; Accounting; Investment; Environmental Sustainability; Climate Change; Corporate Strategy; Mission and Purpose; Corporate Social Responsibility and Impact; Technology Industry; Technology Industry; Technology Industry; Technology Industry; Technology Industry; North America; Europe; Japan; Australia
- August 2020 (Revised September 2020)
- Technical Note
Assessing Prediction Accuracy of Machine Learning Models
The note introduces a variety of methods to assess the accuracy of machine learning prediction models. The note begins by briefly introducing machine learning, overfitting, training versus test datasets, and cross validation. The following accuracy metrics and tools... View Details
- 2021
- Working Paper
Time and the Value of Data
By: Ehsan Valavi, Joel Hestness, Newsha Ardalani and Marco Iansiti
Managers often believe that collecting more data will continually improve the accuracy of their machine learning models. However, we argue in this paper that when data lose relevance over time, it may be optimal to collect a limited amount of recent data instead of... View Details
- August 2020
- Technical Note
Comparing Two Groups: Sampling and t-Testing
This note describes sampling and t-tests, two fundamental statistical concepts. View Details
- Article
Common Variants of the Oxytocin Receptor Gene Do Not Predict the Positive Mood Benefits of Prosocial Spending
By: Ashley V. Whillans, Lara B. Aknin, Colin Ross, Lihan Chen and Frances S. Chen
Who benefits most from helping others? Previous research suggests that common polymorphisms of the oxytocin receptor gene (OXTR) predict whether people behave generously and experience increases in positive mood in response to socially-focused experiences in daily... View Details
- Article
The Importance of Being Causal
By: Iavor I Bojinov, Albert Chen and Min Liu
Causal inference is the study of how actions, interventions, or treatments affect outcomes of interest. The methods that have received the lion’s share of attention in the data science literature for establishing causation are variations of randomized experiments.... View Details
- July 2020
- Case
Applying Data Science and Analytics at P&G
By: Srikant M. Datar, Sarah Mehta and Paul Hamilton
Set in December 2019, this case explores how P&G has applied data science and analytics to cut costs and improve outcomes across its business units. The case provides an overview of P&G’s approach to data management and governance, and reviews the challenges associated... View Details
- June 2020
- Case
Breakthroughs at Blueprint Medicines
By: Richard G. Hamermesh, Kathy Giusti and Susie L. Ma
Precision medicine company Blueprint Medicines was building a successful track record for bringing drug therapies to market 40% faster than average. The company had spent $40 million dollars and two years building a compound library that became its drug development... View Details
- June 2020
- Background Note
Customer Management Dynamics and Cohort Analysis
By: Elie Ofek, Barak Libai and Eitan Muller
The digital revolution has allowed companies to amass considerable amounts of data on their customers. Using this information to generate actionable insights is fast becoming a critical skill that firms must master if they wish to effectively compete and win in today’s... View Details
- June 2020
- Article
Frenemies in Platform Markets: Heterogeneous Profit Foci as Drivers of Compatibility Decisions
By: Ron Adner, Jianqing Chen and Feng Zhu
We study compatibility decisions of two competing platform owners that generate profits through both hardware sales and royalties from content sales. We consider a game-theoretic model in which two platforms offer different standalone utilities to users. We find that... View Details