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- 2021
- Working Paper
Auditor Independence and Outsourcing: Aligning Incentives to Mitigate Shilling and Shirking
By: Ashley Palmarozzo, Jodi L. Short and Michael W. Toffel
Multinational corporations (MNCs) hire auditors to assess their business partners’ compliance with quality, working conditions, and environmental standards. Independent third-party auditors are widely assumed to outperform second-party auditors employed and thus...
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- January 2021
- Case
Amazon Shopper Panel: Paying Customers for Their Data
By: Eva Ascarza and Ayelet Israeli
This case introduces a new Amazon program that has consumers upload their receipts from transactions outside of Amazon, in exchange for money. Through the discussion, the case aims to exlpore issues in customers’ privacy in the digital age, the value of customers’ own...
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Keywords:
Data Analytics;
Data Privacy;
Data Management;
Marketing;
＂marketing Analytics＂;
Marketing Communication;
Marketing Research;
Data-driven Management;
E-commerce;
E-commerce Strategy;
Ethical Decision Making;
Customer Relationship Management;
Crm;
Consumer Protection;
Targeted Advertising;
Targeted Policies;
Data Ownership;
Marketing;
retail industry;
Technology industry;
United States
- January 2021
- Case
Arçelik: From a Dealer Network to an Omnichannel Experience
By: Ayelet Israeli and Fares Khrais
Arçelik Turkey, the country’s market leader in household appliances, was at an omnichannel crossroads in January 2020. Arçelik was a B2B player utilizing a dealership network with an umbrella of brands and had one of the largest brick-and-mortar store networks in...
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Keywords:
Digital Transformation;
Digital Marketing;
Disruption;
Bricks And Mortar;
Franchise Management;
Franchising;
Dealer Network;
Dealers;
Sales;
B2b;
B2b2c;
Tradition;
Culture Change;
Cultural Adaptation;
Omnichannel;
Omnichannel Retail;
Omni-channel;
Omnichannel Retailing;
Sales Channels;
Sales Channel Development;
Channel Management;
Channels Of Distribution;
Marketplace;
Consumer Behavior;
Conflict Management;
Platforms;
Collaboration;
Partners And Partnerships;
Marketing Strategy;
Online Channel;
Online Data;
Online Sales;
Online Shopping;
Online;
retail;
Retailing;
Disruption;
Transformation;
Franchise Ownership;
Change Management;
Partners And Partnerships;
Consumer Behavior;
Online Technology;
Marketing Strategy;
Conflict And Resolution;
Conflict Management;
Electronics industry;
retail industry;
Consumer Products industry;
Turkey
- January 2021
- Article
The Effects of Menu Costs on Retail Performance: Evidence from Adoption of the Electronic Shelf Label Technology
By: Ioannis Stamatopoulos, Achal Bassamboo and Antonio Moreno
We use the adoption of electronic shelf labels (ESLs) by an international grocery retailer in 2015 to identify the effects of physical menu costs (i.e., labor and material costs of price adjustment) on retail performance. We find that the installation of ESLs increased...
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- 2020
- Working Paper
The Value of Descriptive Analytics: Evidence from Online Retailers
By: Ron Berman and Ayelet Israeli
Does the adoption of descriptive analytics impact online retailer performance, and if so, how? We use the synthetic control method to analyze the staggered adoption of a retail analytics dashboard by more than 1,000 e-commerce websites, and find an increase of 13–20%...
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- November 2020
- Case
Amazon: Cult or Culture?
By: Boris Groysberg, Sarah L. Abbott and Tricia Gregg
Amazon was one of the first entrants in e-commerce. Under the leadership of founder Jeff Bezos, Amazon had expanded beyond books to manufacturing and selling a wide range of products and services globally. Bezos had built a customer-centric culture that permeated all...
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- October 2020
- Case
Surviving Venezuela's Hyperinflation: Automercados Plaza's
By: Alberto Cavallo, Mariana Cal and Carla Larangeira
Under the rule of presidents Hugo Chávez and Nicolas Maduro, Venezuela experienced one of the worst economic and political meltdowns in modern history, culminating with a massive hyperinflation. Remarkably, during this dramatic times Automercados Plaza's had grown to...
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- September 2020
- Supplement
Spreadsheet Supplement to Artea (B) and (C)
By: Eva Ascarza and Ayelet Israeli
Spreadsheet Supplement to "Artea (B): Including Customer-level Demographic Data" and "Artea (C): Potential Discrimination through Algorithmic Targeting"
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- September 2020 (Revised December 2020)
- 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...
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- September 2020 (Revised December 2020)
- 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...
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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;
E-commerce Strategy;
Discrimination;
Targeted Advertising;
Targeted Policies;
Targeting;
Pricing Algorithms;
A/b Testing;
Ethical Decision Making;
Customer Base Analysis;
Customer Heterogeneity;
Coupons;
Marketing;
Race;
Gender;
Diversity;
Customer Relationship Management;
Marketing Communications;
Advertising;
Decision Making;
Ethics;
retail industry;
Apparel And Accessories industry;
United States
- September 2020 (Revised December 2020)
- 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...
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- September 2020
- 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...
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- September 2020
- 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...
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- September 2020
- 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...
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- September 2020
- Supplement
Spreadsheet Supplement to "Artea: Designing Targeting Strategies"
By: Eva Ascarza and Ayelet Israeli
Spreadsheet Supplement to "Artea: Designing Targeting Strategies" (521-021).
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- September 2020
- 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...
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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;
E-commerce;
Discrimination;
Targeting;
Targeted Advertising;
Pricing Algorithms;
Ethical Decision Making;
Customer Heterogeneity;
Marketing;
Race;
Ethnicity;
Gender;
Diversity;
Prejudice And Bias;
Marketing Communications;
Data And Data Sets;
Analysis;
Decision Making;
Ethics;
Customer Relationship Management;
retail industry;
Apparel And Accessories industry;
United States
- September 2020
- Teaching Note
Algorithmic Bias in Marketing
By: Ayelet Israeli and Eva Ascarza
Teaching Note for HBS No. 521-020. 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...
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- September 2020
- Supplement
Commonwealth Joe: January 2020 Update from CEO Robert Peck
At the end of 2016, the leadership team of Commonwealth Joe Coffee Roasters—Robert Peck, Chase Damiano, and Jeremy Martin—had begun an ambitious retail expansion strategy in the Washington, D.C. metropolitan area for their specialty coffee business. That October, they...
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- September 2020
- Case
Lojas Americanas: Project DNA and the 'People Machine'
By: Boris Groysberg, Eric Lin and Sarah L. Abbott
Lojas Americanas (“Americanas”) was one of the largest retailers in Brazil. Via its stores, digital platform and Innovation Engine, the company served more than 38 million people. In recent years, Americanas had enjoyed rapid growth; growing from 98 stores in 2001 to...
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- September 2020
- Case
JOANN: Joannalytics Inventory Allocation Tool
By: Kris Ferreira and Srikanth Jagabathula
Michael Joyce, Vice President of Inventory Management at JOANN, championed an effort to develop and implement an inventory allocation analytics tool that used advanced analytics to predict in-season demand of seasonal items for each of JOANN’s nearly 900 stores and...
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Keywords:
Analytics;
Machine Learning;
Optimization;
Inventory Management;
Mathematical Methods;
Decision Making;
Operations;
Supply Chain Management;
Resource Allocation;
Distribution;
Technology Adoption;
Software;
Change Management;
Fashion industry;
Consumer Products industry;
retail industry;
United States;
Ohio