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      • 2020
      • Working Paper

      Fresh Fruit and Vegetable Consumption: The Impact of Access and Value

      By: Retsef Levi, Elisabeth Paulson and Georgia Perakis
      The goal of this paper is to leverage household-level data to improve food-related policies aimed at increasing the consumption of fruits and vegetables (FVs) among low-income households. Currently, several interventions target areas where residents have limited... View Details
      Keywords: Food Deserts; Food Access; Food Policy; Causal Inference; Food; Nutrition; Poverty; Government Administration
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      Levi, Retsef, Elisabeth Paulson, and Georgia Perakis. "Fresh Fruit and Vegetable Consumption: The Impact of Access and Value." MIT Sloan Research Paper, No. 5389-18, October 2020.
      • 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
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      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
      Keywords: Targeted Advertising; Targeting; Race; Gender; Diversity; Marketing; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
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      Ascarza, Eva, and Ayelet Israeli. "Artea (A), (B), (C), and (D): Designing Targeting Strategies." Harvard Business School Teaching Note 521-041, September 2020. (Revised February 2024.)
      • September 2020 (Revised July 2022)
      • Exercise

      Artea (B): Including Customer-Level Demographic Data

      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: Targeting; Algorithmic Bias; Race; Gender; Marketing; Diversity; Customer Relationship Management; Demographics; Prejudice and Bias; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
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      Ascarza, Eva, and Ayelet Israeli. "Artea (B): Including Customer-Level Demographic Data." Harvard Business School Exercise 521-022, September 2020. (Revised July 2022.)
      • September 2020 (Revised July 2022)
      • Exercise

      Artea (C): Potential Discrimination through Algorithmic 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: Targeting; Algorithmic Bias; Race; Gender; Marketing; Diversity; Customer Relationship Management; Prejudice and Bias; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
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      Ascarza, Eva, and Ayelet Israeli. "Artea (C): Potential Discrimination through Algorithmic Targeting." Harvard Business School Exercise 521-037, September 2020. (Revised July 2022.)
      • 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; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
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      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; Retail Industry; Apparel and Accessories Industry; United States
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      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; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
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      Ascarza, Eva, and Ayelet Israeli. "Spreadsheet Supplement to Artea Teaching Note." Harvard Business School Spreadsheet Supplement 521-705, September 2020. (Revised June 2023.)
      • 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
      Keywords: Cloud Computing; Location Strategies; Data Centers; Information Infrastructure
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      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.)
      • August 2020 (Revised September 2020)
      • Technical Note

      Assessing Prediction Accuracy of Machine Learning Models

      By: Michael W. Toffel, Natalie Epstein, Kris Ferreira and Yael Grushka-Cockayne
      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
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      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

      By: Iavor I Bojinov, Chiara Farronato, Yael Grushka-Cockayne, Willy C. Shih and Michael W. Toffel
      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
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      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
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      Datar, Srikant M., Sarah Mehta, and Paul Hamilton. "Applying Data Science and Analytics at P&G." Harvard Business School Case 121-006, July 2020.
      • 2020
      • Working Paper

      EMEs and COVID-19: Shutting Down in a World of Informal and Tiny Firms

      By: Laura Alfaro, Oscar Becerra and Marcela Eslava
      Emerging economies are characterized by an extremely high prevalence of informality, small-firm employment and jobs not fit for working from home. These features factor into how the COVID-19 crisis has affected the economy. We develop a framework that, based on... View Details
      Keywords: COVID-19; Emerging Economies; Informality; Firm-size Distribution; Health Pandemics; Developing Countries and Economies; Economy; System Shocks; Latin America
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      Alfaro, Laura, Oscar Becerra, and Marcela Eslava. "EMEs and COVID-19: Shutting Down in a World of Informal and Tiny Firms." Harvard Business School Working Paper, No. 20-125, June 2020. (See application of the methodology to Latin American Countries in the IMF Regional Economic Outlook: Western Hemisphere 2020, Chapter 3. https://www.imf.org/en/Publications/REO/WH/Issues/2020/10/13/regional-economic-outlook-western-hemisphere.)
      • June 2020
      • Teaching Note

      Understanding the Brand Equity of Nestlé Crunch Bar

      By: Jill Avery and Gerald Zaltman
      Teaching Note for HBS Case Nos. 519-061 and 519-062. In early 2018, Nestlé announced the sale of its U.S. candy-making division and a select collection of twenty of its confectionery brands, including the Nestlé Crunch Bar, to Ferrero SpA for $2.8 billion. Under the... View Details
      Keywords: Brand Management; Brand Storytelling; Brand Equity; Market Research; Qualitative Methods; Marketing; Brands and Branding; Marketing Communications; Consumer Behavior; Marketing Strategy; Food and Beverage Industry
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      Avery, Jill, and Gerald Zaltman. "Understanding the Brand Equity of Nestlé Crunch Bar." Harvard Business School Teaching Note 520-124, June 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
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      Ofek, Elie, Barak Libai, and Eitan Muller. "Customer Management Dynamics and Cohort Analysis." Harvard Business School Background Note 520-122, June 2020.
      • 2021
      • Working Paper

      The Project on Impact Investments' Impact Investment Database

      By: M. Diane Burton, Shawn Cole, Abhishek Dev, Christina Jarymowycz, Leslie Jeng, Josh Lerner, Fanele Mashwama, Yue (Cynthia) Xu and T. Robert Zochowski
      Impact investing has grown significantly over the past 15 years. From a niche investing segment with only $25 billion AUM in 2013 (WEF 2013), it experienced double-digit growth and developed into a market with an estimated $502 billion AUM (Mudaliapar and Dithrich... View Details
      Keywords: Impact Investing; Investment; Analytics and Data Science; Analysis
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      Burton, M. Diane, Shawn Cole, Abhishek Dev, Christina Jarymowycz, Leslie Jeng, Josh Lerner, Fanele Mashwama, Yue (Cynthia) Xu, and T. Robert Zochowski. "The Project on Impact Investments' Impact Investment Database." Harvard Business School Working Paper, No. 20-117, May 2020. (Revised August 2021.)
      • May 2020
      • Article

      Inventory Auditing and Replenishment Using Point-of-Sales Data

      By: Achal Bassamboo, Antonio Moreno and Ioannis Stamatopoulos
      Spoilage, expiration, damage due to employee/customer handling, employee theft, and customer shoplifting usually are not reflected in inventory records. As a result, records often report phantom inventory, i.e., units of good not available for sale. We derive an... View Details
      Keywords: Shelf Availability; Inventory Record Inaccuracy; Optimal Replenishment; Retail Analytics; Performance Effectiveness; Analysis; Mathematical Methods
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      Bassamboo, Achal, Antonio Moreno, and Ioannis Stamatopoulos. "Inventory Auditing and Replenishment Using Point-of-Sales Data." Production and Operations Management 29, no. 5 (May 2020): 1219–1231.
      • April 2020
      • Article

      CEO Behavior and Firm Performance

      By: Oriana Bandiera, Stephen Hansen, Andrea Prat and Raffaella Sadun
      We measure the behavior of 1,114 CEOs in six countries parsing granular CEO diary data through an unsupervised machine learning algorithm. The algorithm uncovers two distinct behavioral types: "leaders" and "managers." Leaders focus on multi-function, high-level... View Details
      Keywords: CEOs; Management; Behavior; Organizations; Performance; Analysis
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      Bandiera, Oriana, Stephen Hansen, Andrea Prat, and Raffaella Sadun. "CEO Behavior and Firm Performance." Journal of Political Economy 128, no. 4 (April 2020): 1325–1369.
      • 2021
      • Working Paper

      Hunting for Talent: Firm-Driven Labor Market Search in the United States

      By: Ines Black, Sharique Hasan and Rembrand Koning
      This article analyzes the phenomenon of firm-driven labor market search—or outbound recruiting—where recruiters are increasingly “hunting for talent” rather than passively relying on workers to search for and apply to job vacancies. Our research methodology leverages... View Details
      Keywords: Hiring; Referrals; Outbound Recruiting; Labor Markets; Selection and Staffing; Networks; Recruitment; Strategy; United States
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      Black, Ines, Sharique Hasan, and Rembrand Koning. "Hunting for Talent: Firm-Driven Labor Market Search in the United States." SSRN Working Paper Series, No. 3576498, September 2021.
      • April 2020
      • Article

      Technological Leadership (de)Concentration: Causes in Information and Communication Technology Equipment

      By: Yasin Ozcan and Shane Greenstein
      Using patent data from 1976 to 2010 as indicators of inventive activity, we determine the concentration level of where inventive ideas originate and then examine how and why those concentrations change over time. The analysis finds pervasive deconcentration in every... View Details
      Keywords: Deconcentration; Technological Innovation; Innovation Leadership; Patents; Market Entry and Exit; Telecommunications Industry
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      Ozcan, Yasin, and Shane Greenstein. "Technological Leadership (de)Concentration: Causes in Information and Communication Technology Equipment." Industrial and Corporate Change 29, no. 2 (April 2020): 241–263. (Winner of the Industry Studies Association 2021 Ralph Gomory Award for Best Paper.)
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