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- Faculty Publications (209)
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- January 2021 (Revised March 2021)
- Case
THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)
By: Jill Avery, Ayelet Israeli and Emma von Maur
THE YES, a multi-brand shopping app launched in May 2020 offered a new type of buying experience for women’s fashion, driven by a sophisticated algorithm that used data science and machine learning to create and deliver a personalized store for every shopper, based on... View Details
Keywords: Data; Data Analytics; Artificial Intelligence; AI; AI Algorithms; AI Creativity; Fashion; Retail; Retail Analytics; E-Commerce Strategy; Platform; Platforms; Big Data; Preference Elicitation; Preference Prediction; Predictive Analytics; App Development; "Marketing Analytics"; Advertising; Mobile App; Mobile Marketing; Apparel; Online Advertising; Referral Rewards; Referrals; Female Ceo; Female Entrepreneur; Female Protagonist; Analytics and Data Science; Analysis; Creativity; Marketing Strategy; Brands and Branding; Consumer Behavior; Demand and Consumers; Forecasting and Prediction; Marketing Channels; Digital Marketing; Internet and the Web; Mobile and Wireless Technology; AI and Machine Learning; E-commerce; Digital Platforms; Fashion Industry; Retail Industry; Apparel and Accessories Industry; Consumer Products Industry; United States
Avery, Jill, Ayelet Israeli, and Emma von Maur. "THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)." Harvard Business School Case 521-070, January 2021. (Revised March 2021.)
- January 2021
- Case
The FIRE Savings Calculator
By: Michael Parzen and Paul Hamilton
This case follows Carol Muñoz, a member of the Financial Independence, Retire Early (FIRE) lifestyle movement. At the age of 45, Carol is considering retiring and living off the $1 million she has accumulated. Using Monte Carlo simulation, Carol forecasts the... View Details
- January 2021 (Revised March 2021)
- Supplement
E-Commerce Analytics for CPG Firms (A): Estimating Sales
By: Ayelet Israeli and Fedor (Ted) Lisitsyn
The E-Commerce Analytics group at the traditional CPG firm was in charge of compiling various online sales reports, as well as making data-driven recommendations for sales and marketing tactics. In a series of exercises, students address different data challenges for... View Details
Keywords: Data Analysis; Data Analytics; CPG; Consumer Packaged Goods (CPG); Estimation; Online Channel; Retail Analytics; Retail; Retailing Industry; Data; Data Sharing; Bricks And Mortar; Ecommerce; Analytics and Data Science; Analysis; Sales; Goods and Commodities; Retail Industry; Consumer Products Industry; United States
- January 2021
- Exercise
E-Commerce Analytics for CPG Firms (B): Optimizing Assortment for a New Retailer
By: Ayelet Israeli and Fedor (Ted) Lisitsyn
The E-Commerce Analytics group at the traditional CPG firm was in charge of compiling various online sales reports, as well as making data-driven recommendations for sales and marketing tactics. In a series of exercises, students address different data challenges for... View Details
Keywords: Data Analysis; Data Analytics; CPG; Consumer Packaged Goods (CPG); Online Channel; Retail Analytics; Retail; Retailing Industry; Data; Data Sharing; Ecommerce; CRM; Loyalty Management; Assortment Planning; Assortment Optimization; Lifetime Value (LTV); Analytics and Data Science; Analysis; Retention; E-commerce; Retail Industry; Consumer Products Industry; United States
Israeli, Ayelet, and Fedor (Ted) Lisitsyn. "E-Commerce Analytics for CPG Firms (B): Optimizing Assortment for a New Retailer." Harvard Business School Exercise 521-079, January 2021.
- January 2021 (Revised March 2021)
- Supplement
E-Commerce Analytics for CPG Firms (C): Free Delivery Terms
By: Ayelet Israeli and Fedor (Ted) Lisitsyn
The E-Commerce Analytics group at the traditional CPG firm was in charge of compiling various online sales reports, as well as making data-driven recommendations for sales and marketing tactics. In a series of exercises, students address different data challenges for... View Details
Keywords: Data; Data Analysis; Data Analytics; Data Sharing; CPG; Consumer Packaged Goods (CPG); Delivery Planning; Customer Lifetime Value; Online Channel; Retail; Retail Analytics; Retailing Industry; Ecommerce; Grocery; Grocery Delivery; Margins; Retention; Analytics and Data Science; Analysis; Retail Industry; Consumer Products Industry; United States
- January 2021 (Revised February 2021)
- Case
Tech with a Side of Pizza: How Domino's Rose to the Top
By: Boris Groysberg, Sarah L. Abbott and Susan Seligson
After hitting an all-time low in 2008, Domino’s Pizza underwent a vigorous rebranding, product development, and embraced innovative technologies to become the world’s leading international fast-food retailer. Domino’s considered itself as much a tech company as it was... View Details
Keywords: Digital Marketing; Digital Technology; Innovation; Scaling; Data Analytics; Turnaround; Technological Innovation; Information Technology; Strategy; Management; Marketing; Operations; Human Resources; Entrepreneurship; Change Management; Analysis; Performance; Customers; Growth and Development; Competitive Advantage; Employees; Training; Leadership Development; Food and Beverage Industry; Technology Industry; United States
Groysberg, Boris, Sarah L. Abbott, and Susan Seligson. "Tech with a Side of Pizza: How Domino's Rose to the Top." Harvard Business School Case 421-057, January 2021. (Revised February 2021.)
- December 2020
- Article
Different Founders, Different Firms: A Comparative Analysis of Academic and Non-academic Startups
By: Maria P. Roche, Annamaria Conti and Frank T. Rothaermel
What role do differences in founders' occupational backgrounds play in new venture performance? Analyzing a novel dataset of 2,998 founders creating 1,723 innovative startups in biomedicine, we find that the likelihood and hazard of achieving a liquidity event are... View Details
Keywords: Founders; Innovation; Occupational Imprinting; Academic Startups; Non-academic Startups; Founder Heterogeneity; Business Startups; Innovation and Invention; Performance; Demographics; Analysis
Roche, Maria P., Annamaria Conti, and Frank T. Rothaermel. "Different Founders, Different Firms: A Comparative Analysis of Academic and Non-academic Startups." Special Issue on Innovative Start-Ups and Policy Initiatives. Research Policy 49, no. 10 (December 2020).
- 2020
- Working Paper
Determinants of Early-Stage Startup Performance: Survey Results
To explore determinants of new venture performance, the CEOs of 470 early-stage startups were surveyed regarding a broad range of factors related to their venture’s customer value proposition, product management, marketing, technology and operations, financial... View Details
Keywords: Startups; Survey Research; Performance Analysis; Entrepreneurship; Performance; Analysis; Business Startups; Failure; Surveys
Eisenmann, Thomas R. "Determinants of Early-Stage Startup Performance: Survey Results." Harvard Business School Working Paper, No. 21-057, October 2020.
- 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 June 2021)
- Case
Francisco Partners Private Credit Opportunity Fund
By: Luis M. Viceira, John D. Dionne, Soracha Prathanrasnikorn and Ari Sunshine
In April 2020, Scott Einsenberg, the Head of Credit at the private equity firm Francisco Partners, is deciding whether to go ahead with extending a private lending agreement to Eventbrite, Inc. (NYSE: EB), a leading global event management and online ticketing... View Details
Viceira, Luis M., John D. Dionne, Soracha Prathanrasnikorn, and Ari Sunshine. "Francisco Partners Private Credit Opportunity Fund." Harvard Business School Case 221-002, October 2020. (Revised June 2021.)
- 2021
- Working Paper
Accounting for Organizational Employment Impact
By: David Freiberg, Katie Panella, George Serafeim and T. Robert Zochowski
Organizations create significant positive and negative impacts through their employment practices. This paper builds on the substantial body of research regarding job quality and impact measurement to present a framework for monetized analysis of employment impact. We... View Details
Keywords: Impact-Weighted Accounts; IWAI; Employment Impact; Employment; Jobs and Positions; Quality; Measurement and Metrics; Analysis; Framework
Freiberg, David, Katie Panella, George Serafeim, and T. Robert Zochowski. "Accounting for Organizational Employment Impact." Harvard Business School Working Paper, No. 21-050, October 2020. (Revised August 2021.)
- 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; Retail 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.)
- 2020
- Working Paper
Design and Analysis of Switchback Experiments
By: Iavor I Bojinov, David Simchi-Levi and Jinglong Zhao
In switchback experiments, a firm sequentially exposes an experimental unit to a random treatment, measures its response, and repeats the procedure for several periods to determine which treatment leads to the best outcome. Although practitioners have widely adopted... View Details
Bojinov, Iavor I., David Simchi-Levi, and Jinglong Zhao. "Design and Analysis of Switchback Experiments." Harvard Business School Working Paper, No. 21-034, September 2020.
- 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
Keywords: Machine Learning; Statistics; Econometric Analyses; Experimental Methods; Data Analysis; Data Analytics; Forecasting and Prediction; Analytics and Data Science; Analysis; Mathematical Methods
Toffel, Michael W., Natalie Epstein, Kris Ferreira, and Yael Grushka-Cockayne. "Assessing Prediction Accuracy of Machine Learning Models." Harvard Business School Technical Note 621-045, August 2020. (Revised September 2020.)
- August 2020
- Technical Note
Comparing Two Groups: Sampling and t-Testing
This note describes sampling and t-tests, two fundamental statistical concepts. View Details
Keywords: Statistics; Econometric Analyses; Experimental Methods; Data Analysis; Data Analytics; Analytics and Data Science; Analysis; Surveys; Mathematical Methods
Bojinov, Iavor I., Chiara Farronato, Yael Grushka-Cockayne, Willy C. Shih, and Michael W. Toffel. "Comparing Two Groups: Sampling and t-Testing." Harvard Business School Technical Note 621-044, August 2020.
- 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
Keywords: Data Science; Analytics; Analysis; Information; Information Management; Information Types; Innovation and Invention; Strategy; Analytics and Data Science; Consumer Products Industry; United States; Ohio
Datar, Srikant M., Sarah Mehta, and Paul Hamilton. "Applying Data Science and Analytics at P&G." Harvard Business School Case 121-006, July 2020.
- 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
Keywords: Cohort Analysis; Customers; Analytics and Data Science; Segmentation; Analysis; Customer Value and Value Chain
Ofek, Elie, Barak Libai, and Eitan Muller. "Customer Management Dynamics and Cohort Analysis." Harvard Business School Background Note 520-122, June 2020.
- June 2020
- Article
Air Pollution, State Anxiety, and Unethical Behavior: A Meta-Analytic Review
By: J Lu, J. Lee, F. Gino and A. Galinsky
Lu, Lee, Gino, and Galinsky (2018) reported four studies demonstrating that air pollution predicted unethical behavior and that one mediating mechanism was state anxiety. In contrast, Heck and colleagues reported two null-effect studies on air pollution, trait... View Details
Lu, J., J. Lee, F. Gino, and A. Galinsky. "Air Pollution, State Anxiety, and Unethical Behavior: A Meta-Analytic Review." Psychological Science 31, no. 6 (June 2020): 748–755.
- 2020
- Article
Inconvenient Truths: Interpreting the Origins of the Internet
By: Shane Greenstein
A conventional economic narrative provides intellectual underpinnings for governments to subsidize research and development ("R&D") that coordinates risky research to benefit many in society. This essay compares this narrative with the origins and invention of the... View Details
Keywords: Lead Users; Technology Transfer; Internet and the Web; History; Analysis; Research and Development; Governance; Information Technology; Policy
Greenstein, Shane. "Inconvenient Truths: Interpreting the Origins of the Internet." Journal of Law & Innovation 3 (2020): 36–68.
- June 2020
- Article
The Isolated Choice Effect and Its Implications for Gender Diversity in Organizations
By: Edward H. Chang, Erika L. Kirgios, Aneesh Rai and Katherine L. Milkman
We highlight a feature of personnel selection decisions that can influence the gender diversity of groups and teams. Specifically, we show that people are less likely to choose candidates whose gender would increase group diversity when making personnel selections in... View Details
Keywords: Behavior And Behavioral Decision Making; Organizational Studies; Decision Analysis; Economics; Decision Making; Behavior; Analysis; Organizations; Diversity; Gender
Chang, Edward H., Erika L. Kirgios, Aneesh Rai, and Katherine L. Milkman. "The Isolated Choice Effect and Its Implications for Gender Diversity in Organizations." Management Science 66, no. 6 (June 2020): 2752–2761.