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- May 2021
- Simulation
Customer Compatibility Exercise Application
By: Ryan W. Buell
Customers impose considerable variability on the operating systems of service organizations. They show up when they wish (arrival variability), they ask for different things (request variability), they vary in their willingness and ability to help themselves (effort...
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- May 2021 (Revised October 2021)
- Teaching Note
THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)
By: Ayelet Israeli and Jill Avery
THE YES, a multi-brand shopping app launched in May 2020 offered a new type of buying experience for women’s fashion, driven by a sophisticated algorithm that used data science and machine learning to create and deliver a personalized store for every shopper, based on...
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Keywords:
Data;
Data Analytics;
Artificial Intelligence;
AI;
AI Algorithms;
AI Creativity;
Fashion;
Retail;
Retail Analytics;
Digital Marketing;
E-commerce;
E-Commerce Strategy;
Platform;
Platforms;
Big Data;
Preference Elicitation;
Predictive Analytics;
App Development;
＂Marketing Analytics＂;
Advertising;
Mobile App;
Mobile Marketing;
Apparel;
Referral Rewards;
Referrals;
Female Ceo;
Female Entrepreneur;
Female Protagonist;
Data and Data Sets;
Analysis;
Creativity;
Marketing Strategy;
Brands and Branding;
Consumer Behavior;
Demand and Consumers;
Forecasting and Prediction;
Marketing Channels;
Online Advertising;
Online Technology;
Mobile Technology;
Fashion Industry;
Retail Industry;
Apparel and Accessories Industry;
Consumer Products Industry;
United States
- May 2021
- Article
Risk-Mitigating Technologies: The Case of Radiation Diagnostic Devices
By: Alberto Galasso and Hong Luo
We study the impact of consumers’ risk perception on firm innovation. Our analysis exploits a major surge in the perceived risk of radiation diagnostic devices following extensive media coverage of a set of over-radiation accidents involving CT scanners in late 2009....
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- April 2021 (Revised July 2021)
- Case
StockX: The Stock Market of Things (Abridged)
By: Chiara Farronato, John J. Horton, Annelena Lobb and Julia Kelley
Founded in 2015 by Dan Gilbert, Josh Luber, and Greg Schwartz, StockX was an online platform where users could buy and sell unworn luxury and limited-edition sneakers. Sneaker resale prices often fluctuated over time based on supply and demand, creating a robust...
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Keywords:
Markets;
Auctions;
Bids and Bidding;
Demand and Consumers;
Consumer Behavior;
Data and Data Sets;
Market Design;
Market Platforms;
Two-Sided Platforms;
Multi-Sided Platforms;
Market Transactions;
Marketplace Matching;
Supply and Industry;
Analysis;
Price;
Product Marketing;
Product Launch;
Apparel and Accessories Industry;
Fashion Industry;
North and Central America;
United States;
Michigan;
Detroit
- 2021
- Working Paper
How Much Should We Trust Staggered Difference-In-Differences Estimates?
By: Andrew C. Baker, David F. Larcker and Charles C.Y. Wang
Difference-in-differences analysis with staggered treatment timing is frequently used to assess the impact of policy changes on corporate outcomes in academic research. However, recent advances in econometric theory show that such designs are likely to be biased in the...
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- March 2021
- Article
The Customer May Not Always Be Right: Customer Compatibility and Service Performance
This paper investigates the impact of customer compatibility – the degree of fit between the needs of customers and the capabilities of the operations serving them – on customer experiences and firm performance. We use a variance decomposition analysis to quantify the...
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- February 2021 (Revised May 2021)
- Case
SafeGraph: Selling Data as a Service
By: Ramana Nanda, Abhishek Nagaraj and Allison Ciechanover
Set in January 2021, the CEO of SafeGraph, a four-year-old startup that sold Data as a Service, looked to the future. His aim was to become the most trusted source for data about a physical place. The company provided points of interest (POI) and foot traffic data on...
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- February 2021
- Tutorial
Getting Started in R Cloud Studio
By: Chiara Farronato and Caleb Kwon
This video provides an introduction to the free programming language R using an online cloud version of RStudio, which is the most popular editor and interface for writing and executing R code. The video begins by providing a brief background of R and RStudio and...
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- February 2021
- Tutorial
T-tests: Theory and Practice
This video provides an introduction to hypothesis testing, sampling, t-tests, and p-values. It provides examples of A/B testing and t-testing to assess whether difference between two groups are statistically significant. This video can be assigned in conjunction with...
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- February 2021 (Revised February 2021)
- Background Note
eGrocery and the Role of Data for CPG Firms
By: Ayelet Israeli, Fedor (Ted) Lisitsyn and Mark A. Irwin
This notes provides information about the eGrocery industry and how traditional CPG companies handle this channel and potential data. It is recommended to use together with a series of exercises entitled: "E-Commerce Analytics for CPG Firms (A), (B), and (C)."
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Keywords:
Data;
Data Analysis;
Data Analytics;
Data Sharing;
CPG;
Consumer Packaged Goods (CPG);
Delivery Planning;
Customer Lifetime Value;
Online Channel;
Retail;
Retail Analytics;
Retailing Industry;
Ecommerce;
Grocery;
Optimization;
Data and Data Sets;
Analysis;
Customer Value and Value Chain;
Marketing Channels;
Retail Industry;
Consumer Products Industry;
United States
- January 2021 (Revised March 2021)
- Case
THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)
By: Jill Avery, Ayelet Israeli and Emma von Maur
THE YES, a multi-brand shopping app launched in May 2020 offered a new type of buying experience for women’s fashion, driven by a sophisticated algorithm that used data science and machine learning to create and deliver a personalized store for every shopper, based on...
View Details
Keywords:
Data;
Data Analytics;
Artificial Intelligence;
AI;
AI Algorithms;
AI Creativity;
Fashion;
Retail;
Retail Analytics;
Digital Marketing;
E-commerce;
E-Commerce Strategy;
Platform;
Platforms;
Big Data;
Preference Elicitation;
Preference Prediction;
Predictive Analytics;
App Development;
＂Marketing Analytics＂;
Advertising;
Mobile App;
Mobile Marketing;
Apparel;
Referral Rewards;
Referrals;
Female Ceo;
Female Entrepreneur;
Female Protagonist;
Data and Data Sets;
Analysis;
Creativity;
Marketing Strategy;
Brands and Branding;
Consumer Behavior;
Demand and Consumers;
Forecasting and Prediction;
Marketing Channels;
Online Advertising;
Online Technology;
Mobile Technology;
Fashion Industry;
Retail Industry;
Apparel and Accessories Industry;
Consumer Products Industry;
United States
- 2021
- Working Paper
Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem
By: Mochen Yang, Edward McFowland III, Gordon Burtch and Gediminas Adomavicius
Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data, followed...
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- January 2021 (Revised March 2021)
- Supplement
E-Commerce Analytics for CPG Firms (A): Estimating Sales
By: Ayelet Israeli and Fedor (Ted) Lisitsyn
The E-Commerce Analytics group at the traditional CPG firm was in charge of compiling various online sales reports, as well as making data-driven recommendations for sales and marketing tactics. In a series of exercises, students address different data challenges for...
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Keywords:
Data Analysis;
Data Analytics;
CPG;
Consumer Packaged Goods (CPG);
Estimation;
Online Channel;
Retail Analytics;
Retail;
Retailing Industry;
Data;
Data Sharing;
Bricks And Mortar;
Ecommerce;
Data and Data Sets;
Analysis;
Sales;
Goods and Commodities;
Retail Industry;
Consumer Products Industry;
United States
- January 2021 (Revised March 2021)
- Exercise
E-Commerce Analytics for CPG Firms (A): Estimating Sales
By: Ayelet Israeli and Fedor (Ted) Lisitsyn
The E-Commerce Analytics group at the traditional CPG firm was in charge of compiling various online sales reports, as well as making data-driven recommendations for sales and marketing tactics. In a series of exercises, students address different data challenges for...
View Details
Keywords:
Data Analysis;
Data Analytics;
CPG;
Consumer Packaged Goods (CPG);
Estimation;
Online Channel;
Retail Analytics;
Retail;
Retailing Industry;
Data;
Data Sharing;
Bricks And Mortar;
Ecommerce;
Direct-to-consumer;
DTC;
Data and Data Sets;
Sales;
Marketing;
Retail Industry;
Consumer Products Industry;
United States
- January 2021
- Supplement
E-Commerce Analytics for CPG Firms (B): Optimizing Assortment for a New Retailer
By: Ayelet Israeli and Fedor (Ted) Lisitsyn
The E-Commerce Analytics group at the traditional CPG firm was in charge of compiling various online sales reports, as well as making data-driven recommendations for sales and marketing tactics. In a series of exercises, students address different data challenges for...
View Details
Keywords:
Data Analysis;
Data Analytics;
CPG;
Consumer Packaged Goods (CPG);
Online Channel;
Retail;
Retail Analytics;
Retailing Industry;
Data;
Data Sharing;
Ecommerce;
Assortment Optimization;
Assortment Planning;
Data and Data Sets;
Retention;
Retail Industry;
Consumer Products Industry;
United States
- January 2021
- Exercise
E-Commerce Analytics for CPG Firms (B): Optimizing Assortment for a New Retailer
By: Ayelet Israeli and Fedor (Ted) Lisitsyn
The E-Commerce Analytics group at the traditional CPG firm was in charge of compiling various online sales reports, as well as making data-driven recommendations for sales and marketing tactics. In a series of exercises, students address different data challenges for...
View Details
Keywords:
Data Analysis;
Data Analytics;
CPG;
Consumer Packaged Goods (CPG);
Online Channel;
Retail Analytics;
Retail;
Retailing Industry;
Data;
Data Sharing;
Ecommerce;
CRM;
Loyalty Management;
Assortment Planning;
Assortment Optimization;
Lifetime Value (LTV);
Data and Data Sets;
Analysis;
Retention;
Retail Industry;
Consumer Products Industry;
United States
- January 2021 (Revised March 2021)
- Supplement
E-Commerce Analytics for CPG Firms (C): Free Delivery Terms
By: Ayelet Israeli and Fedor (Ted) Lisitsyn
The E-Commerce Analytics group at the traditional CPG firm was in charge of compiling various online sales reports, as well as making data-driven recommendations for sales and marketing tactics. In a series of exercises, students address different data challenges for...
View Details
Keywords:
Data;
Data Analysis;
Data Analytics;
Data Sharing;
CPG;
Consumer Packaged Goods (CPG);
Delivery Planning;
Customer Lifetime Value;
Online Channel;
Retail;
Retail Analytics;
Retailing Industry;
Ecommerce;
Grocery;
Grocery Delivery;
Margins;
Retention;
Data and Data Sets;
Analysis;
Retail Industry;
Consumer Products Industry;
United States
- January 2021 (Revised March 2021)
- Exercise
E-Commerce Analytics for CPG Firms (C): Free Delivery Terms
By: Ayelet Israeli and Fedor (Ted) Lisitsyn
The E-Commerce Analytics group at the traditional CPG firm was in charge of compiling various online sales reports, as well as making data-driven recommendations for sales and marketing tactics. In a series of exercises, students address different data challenges for...
View Details
Keywords:
Data;
Data Analysis;
Data Analytics;
Data Sharing;
CPG;
Consumer Packaged Goods (CPG);
Delivery Planning;
Customer Lifetime Value;
Online Channel;
Retail;
Retail Analytics;
Retailing Industry;
Ecommerce;
Grocery;
Grocery Delivery;
Margins;
Data and Data Sets;
Retention;
Retail Industry;
Consumer Products Industry;
United States
- January 2021
- Case
Biobot Analytics
In 2017, Newsha Ghaeli and Mariana Matus were deciding whether to leave their labs at the Massachusetts Institute of Technology, put other job opportunities aside, and dive full-time into founding a wastewater analysis start-up, Biobot. Ghaeli, an architect, and Matus,...
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- 2021
- Article
Fair Algorithms for Infinite and Contextual Bandits
By: Matthew Joseph, Michael J Kearns, Jamie Morgenstern, Seth Neel and Aaron Leon Roth
We study fairness in linear bandit problems. Starting from the notion of meritocratic fairness introduced in Joseph et al. [2016], we carry out a more refined analysis of a more general problem, achieving better performance guarantees with fewer modelling assumptions...
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