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      • November 2020 (Revised July 2022)
      • Case

      Dell Technologies: Bringing the Cloud to the Ground

      By: Navid Mojir and V. Kasturi Rangan
      The case tells the story of Dell Technologies and its efforts to revitalize its value proposition and escape a commodity trap by acquiring EMC for $67 billion—the largest tech acquisition in history. It also shows the deeply intertwined connections between a company’s... View Details
      Keywords: Value Proposition; Go-to-market; Strategic Positioning; Mergers and Acquisitions; Business Strategy; Marketing Strategy; Technological Innovation; Business Divisions; Information Technology Industry; Computer Industry
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      Mojir, Navid, and V. Kasturi Rangan. "Dell Technologies: Bringing the Cloud to the Ground." Harvard Business School Case 521-036, November 2020. (Revised July 2022.)
      • November 3, 2020
      • Article

      Gender Differences in COVID-19 Attitudes and Behavior: Panel Evidence from Eight Countries

      By: Vincenzo Galasso, Vincent Pons, Paola Profeta, Michael Becher, Sylvain Brouard and Martial Foucault
      Using original data from two waves of a survey conducted in March and April 2020 in eight OECD countries (N = 21,649), we show that women are more likely to see COVID-19 as a very serious health problem, to agree with restraining public policy measures adopted in... View Details
      Keywords: COVID-19; Health Pandemics; Attitudes; Behavior; Gender; Policy; Governance Compliance
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      Galasso, Vincenzo, Vincent Pons, Paola Profeta, Michael Becher, Sylvain Brouard, and Martial Foucault. "Gender Differences in COVID-19 Attitudes and Behavior: Panel Evidence from Eight Countries." Proceedings of the National Academy of Sciences 117, no. 44 (November 3, 2020).
      • November 2020
      • Article

      Casting Conference Calls

      By: Lauren Cohen, Dong Lou and Christopher J. Malloy
      We explore a subtle but important mechanism through which firms can control information flow to the markets. We find that firms that “cast” their conference calls by disproportionately calling on bullish analysts tend to underperform in the future. Firms that call on... View Details
      Keywords: Strategic Release; Firms; Conference Calls; Information; Strategy; Asset Pricing
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      Cohen, Lauren, Dong Lou, and Christopher J. Malloy. "Casting Conference Calls." Management Science 66, no. 11 (November 2020): 5015–5039. (Winner of the First Prize, Crowell Memorial Award for Best Paper in Quantitative Investments, PanAgora Asset Management, 2014.)
      • 2020
      • Working Paper

      Designing, Not Checking, for Policy Robustness: An Example with Optimal Taxation

      By: Benjami Lockwood, Afras Y. Sial and Matthew C. Weinzierl
      Economists typically check the robustness of their results by comparing them across plausible ranges of parameter values and model structures. A preferable approach to robustness—for the purposes of policymaking and evaluation—is to design policy that takes these... View Details
      Keywords: Optimal Taxation; Robust Optimization; Taxation; Income; Policy; Design
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      Lockwood, Benjami, Afras Y. Sial, and Matthew C. Weinzierl. "Designing, Not Checking, for Policy Robustness: An Example with Optimal Taxation." NBER Working Paper Series, No. 28098, November 2020.
      • 2022
      • Working Paper

      Intertemporal Altruism

      By: Felix Chopra, Armin Falk and Thomas Graeber
      Most prosocial decisions involve intertemporal tradeoffs. Yet, the timing of prosocial utility flows is ambiguous and bypassed by most models of other-regarding preferences. We study the behavioral implications of the time structure of prosocial utility,... View Details
      Keywords: Altruism; Donation; Intertemporal Decision-making; Time Inconsistency
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      Chopra, Felix, Armin Falk, and Thomas Graeber. "Intertemporal Altruism." Working Paper, August 2022. (R&R at American Economic Journal Microeconomics.)
      • Article

      Nudging: Progress to Date and Future Directions

      By: John Beshears and Harry Kosowsky
      Nudges influence behavior by changing the environment in which decisions are made, without restricting the menu of options and without altering financial incentives. This paper assesses past empirical research on nudging and provides recommendations for future work in... View Details
      Keywords: Nudge; Choice Architecture; Behavioral Economics; Behavioral Science; Behavior; Change; Situation or Environment; Decision Choices and Conditions; Decision Making
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      Beshears, John, and Harry Kosowsky. "Nudging: Progress to Date and Future Directions." Organizational Behavior and Human Decision Processes 161, Supplement (November 2020): 3–19.
      • November 2020
      • Article

      Taxation in Matching Markets

      By: Arnaud Dupuy, Alfred Galichon, Sonia Jaffe and Scott Duke Kominers
      We analyze the effects of taxation in two-sided matching markets, i.e., markets in which all agents have heterogeneous preferences over potential partners. In matching markets, taxes can generate inefficiency on the allocative margin by changing who is matched to whom,... View Details
      Keywords: Matching Markets; Labor Markets; Taxation; Labor; Markets
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      Dupuy, Arnaud, Alfred Galichon, Sonia Jaffe, and Scott Duke Kominers. "Taxation in Matching Markets." International Economic Review 61, no. 4 (November 2020): 1591–1634.
      • October 2020 (Revised May 2023)
      • Exercise

      SenseAim Technologies: Pricing to Win

      By: Elie Ofek, Eyal Biyalogorsky, Marco Bertini and Oded Koenigsberg
      This exercise serves to help students understand the proper role and use of costs in a firm’s pricing decisions. The exercise is designed such that the learning of students evolves across a classroom session, starting from understanding which costs are relevant when... View Details
      Keywords: Pricing Decisions; Cost; Information; Price; Decision Making
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      Ofek, Elie, Eyal Biyalogorsky, Marco Bertini, and Oded Koenigsberg. "SenseAim Technologies: Pricing to Win." Harvard Business School Exercise 521-049, October 2020. (Revised May 2023.)
      • 2020
      • Working Paper

      Short-Termism, Shareholder Payouts, and Investment in the EU

      By: Jesse M. Fried and Charles C.Y. Wang
      Investor-driven “short-termism” is said to harm EU public firms' ability to invest for the long term, prompting calls for the EU to better insulate managers from shareholder pressure. But the evidence offered—in the form of rising levels of repurchases and dividends—is... View Details
      Keywords: Short-termism; Quarterly Capitalism; EU; Dividends; Equity Issuances; Equity Compensastion; Capital Flows; Capital Distribution; R&D; Innovation; Investment; Corporate Governance; Investment Return; Acquisition; European Union
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      Fried, Jesse M., and Charles C.Y. Wang. "Short-Termism, Shareholder Payouts, and Investment in the EU." Harvard Business School Working Paper, No. 21-054, October 2020.
      • October 2020 (Revised March 2024)
      • Case

      Experimentation at Yelp

      By: Iavor Bojinov and Karim R. Lakhani
      Over the last decade, experimentation has become integral to the research and development processes of technology companies—including Yelp—for understanding customer preferences and mitigating innovation risks. The case describes Yelp's journey with experimentation,... View Details
      Keywords: Customer Relationship Management; Collaborative Innovation and Invention; Risk Management; Advertising; Research and Development; Technology Industry
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      Bojinov, Iavor, and Karim R. Lakhani. "Experimentation at Yelp." Harvard Business School Case 621-064, October 2020. (Revised March 2024.)
      • 2022
      • Working Paper

      Flight to Safety: How Economic Downturns Affect Talent Flows to Startups

      By: Shai Bernstein, Richard Townsend and Ting Xu
      Using proprietary data from AngelList Talent, we study how individuals’ job search and application behavior changed during the COVID-19 downturn. We find that job seekers shifted their searches toward more established firms and away from early-stage startups, even... View Details
      Keywords: Startup Labor Market; Flight To Safety; COVID-19; Recession; Business Startups; Human Capital; Business Cycles; Health Pandemics
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      Bernstein, Shai, Richard Townsend, and Ting Xu. "Flight to Safety: How Economic Downturns Affect Talent Flows to Startups." Harvard Business School Working Paper, No. 21-045, September 2020. (Revised March 2022.)
      • 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.
      • October 2020
      • Article

      The Elasticity of Science

      By: Kyle Myers
      This paper identifies the degree to which scientists are willing to change the direction of their work in exchange for resources. Data from the National Institutes of Health are used to estimate how scientists respond to targeted funding opportunities. Inducing a... View Details
      Keywords: Scientists; Funding; Research; Change
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      Myers, Kyle. "The Elasticity of Science." American Economic Journal: Applied Economics 12, no. 4 (October 2020): 103–134.
      • 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.)
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