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      • 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
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      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.
      • November 2020
      • Case

      Axis My India

      By: Ananth Raman, Ann Winslow and Kairavi Dey
      Pradeep Gupta founded Axis My India (AMI) as a printing and publishing company in 1998. In 2013, AMI expanded into consumer research and election forecasting. Although a relatively unknown entity, AMI predicted several election results accurately. Gupta describes AMI’s... View Details
      Keywords: Market Research; Operations; Management; Infrastructure; Logistics; Service Operations; Political Elections; Forecasting and Prediction; Asia; India
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      Raman, Ananth, Ann Winslow, and Kairavi Dey. "Axis My India." Harvard Business School Case 621-075, November 2020.
      • 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.)
      • 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.)
      • 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; Financial Services Industry; Chemical Industry; Technology Industry; Consumer Products Industry; Pharmaceutical Industry; North America; Europe; Japan; Australia
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      Serafeim, George. "Social-Impact Efforts That Create Real Value." Harvard Business Review 98, no. 5 (September–October 2020): 38–48.
      • September–October 2020
      • Article

      The Past, Present, and (Near) Future of Gene Therapy and Gene Editing

      By: Julia Pian, Amitabh Chandra and Ariel Dora Stern
      Emerging gene therapy and gene-editing technologies will have a growing impact on patient lives and health-care delivery. We analyzed a decade of data on clinical trials and venture capital investments to understand the likely trajectory of genetically focused... View Details
      Keywords: Gene Therapy; Gene Editing; Impact; Health Care and Treatment; Technological Innovation; Health Testing and Trials; Venture Capital; Change
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      Pian, Julia, Amitabh Chandra, and Ariel Dora Stern. "The Past, Present, and (Near) Future of Gene Therapy and Gene Editing." NEJM Catalyst Innovations in Care Delivery 1, no. 5 (September–October 2020).
      • 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

      Keywords: Economics Of AI; Machine Learning; Non-stationarity; Perishability; Value Depreciation; Analytics and Data Science; Value
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      Valavi, Ehsan, Joel Hestness, Newsha Ardalani, and Marco Iansiti. "Time and the Value of Data." Harvard Business School Working Paper, No. 21-016, August 2020. (Revised November 2021.)
      • August 2020 (Revised March 2021)
      • Supplement

      Migros Turkey: Scaling Online Operations (B)

      By: Antonio Moreno and Gamze Yucaoglu
      The case opens in February 2020 as Ozgur Tort and Mustafa Bartin, CEO and chief large-format and online retail officer of Migros Ticaret A.S. (Migros), Turkey’s oldest and one of its largest supermarket chains, are looking over the results of the fulfillment pilot the... View Details
      Keywords: Grocery; Business Model; Strategy; Digital Platforms; Information Technology; Technology Adoption; Value Creation; Globalization; Competition; Expansion; Logistics; Profit; Resource Allocation; Corporate Strategy; Retail Industry; Turkey
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      Moreno, Antonio, and Gamze Yucaoglu. "Migros Turkey: Scaling Online Operations (B)." Harvard Business School Supplement 621-027, August 2020. (Revised March 2021.)
      • July 2020
      • Case

      Amanda and Kristen: Mented Cosmetics

      By: Steven Rogers, Jeffrey J. Bussgang and Alterrell Mills
      The co-founders (Black HBS alumnae) of an e-commerce beauty startup explore the unmet needs within the beauty industry. This case study examines the entrepreneurial opportunities that come from identifying an underserved market, specifically within the Black community... View Details
      Keywords: Brands and Branding; Competition; Customers; Disruption; Disruptive Innovation; Distribution Channels; Entrepreneurship; Finance; Macroeconomics; Marketing; Marketing Channels; Marketing Communications; Marketing Strategy; Mission and Purpose; Organizational Culture; Product Design; Product Development; Product Positioning; Sales; Social Issues; Social Marketing; Business Startups; Strategic Planning; Strategy; Supply Chain Management; Venture Capital; Beauty and Cosmetics Industry; Advertising Industry; Public Relations Industry; Chemical Industry; Manufacturing Industry; Retail Industry; North and Central America; United States; New York (city, NY); New York (state, US)
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      Rogers, Steven, Jeffrey J. Bussgang, and Alterrell Mills. "Amanda and Kristen: Mented Cosmetics." Harvard Business School Case 321-002, July 2020.
      • July 2020 (Revised September 2020)
      • Case

      MobSquad

      By: Prithwiraj Choudhury, William R. Kerr and Susie L. Ma
      Irfhan Rawji (MBA 2004) launched MobSquad in October 2018 to help American tech start-ups retain hard-to-find talent, many of whom struggled with U.S. work visa issues, such as software engineers with experience in artificial intelligence, machine learning, or data... View Details
      Keywords: Work Visas; H1-B; Business Ventures; Business Startups; Labor; Human Capital; Human Resources; Crisis Management; Employment Industry; Canada; United States
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      Choudhury, Prithwiraj, William R. Kerr, and Susie L. Ma. "MobSquad." Harvard Business School Case 821-010, July 2020. (Revised September 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.
      • 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.
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