Publications
Publications
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- All HBS Web
(1,542)
- Faculty Publications (263)
- 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
- 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
- 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
- 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
- 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 (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
- 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
- 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
- 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
- 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
- September 2020
- Article
Customer Supercharging in Experience-Centric Channels
By: David R. Bell, Santiago Gallino and Antonio Moreno
We conjecture that for online retailers, experience-centric offline store formats do not simply expand market coverage, but rather, serve to significantly amplify future positive customer behaviors, both online and offline. We term this phenomenon “supercharging” and... View Details
- 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)
- June 2020
- Case
Agile Consumer Product Innovation with Alibaba's Tmall Innovation Center
By: William R. Kerr, Daniel O'Connor and James Palano
Consumer products companies were beset by changes on all sides during the 2010s. Customers were increasingly turning to ecommerce platforms rather than shopping in-store. Meanwhile, nimble, digitally-savvy competitors were gaining market share by capitalizing on the... 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
- 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
- March–April 2020
- Article
Building A Culture of Experimentation
By: Stefan Thomke
Why don’t organizations test more? After examining this question for several years, I can tell you that the central reason is culture. As companies try to scale up their experimentation capacity, they often find that the obstacles are not tools and technology but... View Details
- 2020
- Book
Experimentation Works: The Surprising Power of Business Experiments
By: Stefan Thomke
Don’t fly blind. See how the power of experiments works for you. When it comes to improving customer experiences, trying out new business models, or developing new products, even the most experienced managers often get it wrong. They discover that intuition,... View Details
- January 2020
- Case
Banorte Móvil: Data-Driven Mobile Growth
By: Ayelet Israeli, Carla Larangeira and Mariana Cal
In mid-2019, Carlos Hank was deliberating over the results for Banorte Móvil—the mobile application for Banorte, Mexico’s most profitable and second-largest financial institution. Hank, who had been appointed as Banorte´s Chairman of the Board in January 2015, had... View Details
- 2020
- Article
Assessing the Impact of Big Data on Firm Innovation Performance: Big Data is not Always Better Data
By: Maryam Ghasemaghaei and Goran Calic
In this study, we explore the impacts of big data’s main characteristics (i.e., volume, variety, and velocity) on innovation performance (i.e., innovation efficacy and efficiency), which eventually impacts firm performance (i.e., customer perspective, financial... View Details
- November 2019 (Revised May 2020)
- Case
Collibra
By: Lynda M. Applegate, Jeffrey F. Rayport and Julia Kelley
Founded in 2008 at Vrije Universiteit Brussels, Collibra was a data intelligence company that found product-market fit in the years after the global financial crisis when many companies were under pressure from consumers and governments to improve their data management... View Details
Keywords: Entrepreneurship; Governance; Innovation and Invention; Technological Innovation; Markets; Information Technology; Applications and Software; Technology Adoption; Digital Platforms; Internet and the Web; Customer Focus and Relationships; Customer Satisfaction; Expansion; Information Technology Industry; Technology Industry; Europe; Belgium; Brussels; North and Central America; United States; New York (city, NY); New York (state, US)