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- Article
Multitasking While Driving: A Time Use Study of Commuting Knowledge Workers to Assess Current and Future Uses
By: Thomaz Teodorovicz, Andrew L. Kun, Raffaella Sadun and Orit Shaer
Commuting has enormous impact on individuals, families, organizations, and society. Advances in vehicle automation may help workers employ the time spent commuting in productive work-tasks or wellbeing activities. To achieve this goal, however, we need to develop a...
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- Article
Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)
By: Eva Ascarza and Ayelet Israeli
An inherent risk of algorithmic personalization is disproportionate targeting of individuals from certain groups (or demographic characteristics such as gender or race), even when the decision maker does not intend to discriminate based on those “protected”... View Details
- 2022
- Working Paper
Can a Website Bring Unemployment Down? Experimental Evidence from France
By: Aïcha Ben Dhia, Bruno Crépon, Esther Mbih, Louise Paul-Delvaux, Bertille Picard and Vincent Pons
We evaluate the impact of an online platform giving job seekers tips to improve their search and recommendations of new occupations and locations to target, based on their personal data and labor market data. Our experiment used an encouragement design and was...
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- March 2022
- Article
Learning to Rank an Assortment of Products
By: Kris Ferreira, Sunanda Parthasarathy and Shreyas Sekar
We consider the product ranking challenge that online retailers face when their customers typically behave as “window shoppers”: they form an impression of the assortment after browsing products ranked in the initial positions and then decide whether to continue...
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- 2022
- Working Paper
E-commerce During COVID: Stylized Facts from 47 Economies
By: Joel Alcedo, Alberto Cavallo, Bricklin Dwyer, Prachi Mishra and Antonio Spilimbergo
We study e-commerce across 47 economies and 26 industries during the COVID-19 pandemic using aggregated and anonymized transaction-level data from Mastercard, scaled to represent total consumer spending. The share of online transactions in total consumption increased...
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Keywords:
COVID-19 Pandemic;
E-commerce;
Health Pandemics;
Spending;
Online Technology;
Global Range;
Analysis
- November 2021 (Revised December 2021)
- Supplement
PittaRosso (B): Human and Machine Learning
By: Ayelet Israeli
This case supplements the "PittaRosso: Artificial Intelligence-Driven Pricing and Promotion" case, and provides major highlights on what happened at the company since the first case.
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Keywords:
Artificial Intelligence;
Pricing;
Pricing Algorithm;
Pricing Decisions;
Pricing Strategy;
Pricing Structure;
Promotion;
Promotions;
Online Marketing;
Data-driven Decision-making;
Data-driven Management;
Retail;
Retail Analytics;
Price;
Advertising Campaigns;
Analytics and Data Science;
Analysis;
Digital Marketing;
Budgets and Budgeting;
Marketing Strategy;
Marketing;
Transformation;
Decision Making;
AI and Machine Learning;
Retail Industry;
Italy
- 2021
- Working Paper
Who Benefits from Online Gig Economy Platforms?
By: Christopher Stanton and Catherine Thomas
This paper estimates the magnitude and distribution of surplus from the knowledge worker gig economy using data from an online labor market. Labor demand elasticities determine workers’ wages, and buyers’ past market experience shapes both their job posting frequency...
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- October 2021 (Revised March 2022)
- Supplement
PittaRosso: Artificial Intelligence-Driven Pricing and Promotion
By: Ayelet Israeli and Fabrizio Fantini
PittaRosso, a traditional Italian shoe retailer, is implementing an AI system to provide pricing and promotion recommendations. The system allows them to implement changes that would affect both the top of funnel and bottom of funnel activities for the company: once...
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Keywords:
Artificial Intelligence;
Pricing;
Pricing Algorithm;
Pricing Decisions;
Pricing Strategy;
Pricing Structure;
Promotion;
Promotions;
Online Marketing;
Data-driven Decision-making;
Data-driven Management;
Retail;
Retail Analytics;
Price;
Advertising Campaigns;
Analytics and Data Science;
Analysis;
Digital Marketing;
Budgets and Budgeting;
Marketing Strategy;
Marketing;
Transformation;
Decision Making;
Retail Industry;
Italy
- October 2021 (Revised March 2022)
- Case
PittaRosso: Artificial Intelligence-Driven Pricing and Promotion
By: Ayelet Israeli
PittaRosso, a traditional Italian shoe retailer, is implementing an AI system to provide pricing and promotion recommendations. The system allows them to implement changes that would affect both the top of funnel and bottom of funnel activities for the company: once...
View Details
Keywords:
Artificial Intelligence;
Pricing;
Pricing Algorithm;
Pricing Decisions;
Pricing Strategy;
Pricing Structure;
Promotion;
Promotions;
Online Marketing;
Data-driven Decision-making;
Data-driven Management;
Retail;
Retail Analytics;
AI;
Price;
Advertising Campaigns;
Analytics and Data Science;
Analysis;
Digital Marketing;
Budgets and Budgeting;
Marketing Strategy;
Marketing;
Transformation;
Decision Making;
AI and Machine Learning;
Retail Industry;
Italy
- 2021
- Working Paper
How Does Working from Home during COVID-19 Affect What Managers Do? Evidence from Time-Use Studies
By: Thomaz Teodorovicz, Raffaella Sadun, Andrew L. Kun and Orit Shaer
We assess how the sudden and widespread shift to working from home (WFH) during the pandemic impacted how managers allocate time throughout their working day. We analyze the results from an online time-use survey with data on 1,192 knowledge workers (out of which 973...
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- September 2021
- Article
Joint Problem-solving Orientation in Fluid Cross-boundary Teams
By: Michaela J. Kerrissey, Anna T. Mayo and Amy C. Edmondson
Using interviews, a national field survey, and an online laboratory study, we have examined teamwork in fluid cross-boundary teams. Across three studies, we qualitatively discovered and quantitatively explored "joint problem-solving orientation" as a new team factor....
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- 2022
- Working Paper
What Can Stockouts Tell Us About Inflation? Evidence from Online Micro Data
By: Alberto Cavallo and Oleksiy Kryvtsov
We use a detailed micro dataset on product availability to construct a direct high-frequency measure of consumer product shortages during the 2020–2022 pandemic. We document a widespread multi-fold rise in shortages in nearly all sectors early in the pandemic. Over...
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- 2021
- Working Paper
The Value of Data and Its Impact on Competition
By: Marco Iansiti
Common regulatory perspective on the relationship between data, value, and competition in online platforms has increasingly centered on the volume of data accumulated by incumbent firms. This view posits the existence of "data network effects," where more data leads to...
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- July 2021
- Article
Outsourcing Tasks Online: Matching Supply and Demand on Peer-to-Peer Internet Platforms
By: Zoë Cullen and Chiara Farronato
We study the growth of online peer-to-peer markets. Using data from TaskRabbit, an expanding marketplace for domestic tasks at the time of our study, we show that growth varies considerably across cities. To disentangle the potential drivers of growth, we look...
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- July 2021
- Article
The Effect of Price on Firm Reputation
By: Michael Luca and Oren Reshef
While a business's reputation can affect its pricing, prices can also affect its reputation. To explore the effect of prices on reputation, we investigate daily data on menu prices and online ratings from a large rating and ordering platform. We find that a price...
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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 February 2022)
- 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;
E-commerce;
E-Commerce Strategy;
Platform;
Platforms;
Big Data;
Preference Elicitation;
Predictive Analytics;
App Development;
＂Marketing Analytics＂;
Advertising;
Mobile App;
Mobile Marketing;
Apparel;
Online Advertising;
Referral Rewards;
Referrals;
Female Ceo;
Female Entrepreneur;
Female Protagonist;
Analytics and Data Science;
Analysis;
Creativity;
Marketing Strategy;
Brands and Branding;
Consumer Behavior;
Demand and Consumers;
Forecasting and Prediction;
Marketing Channels;
Digital Marketing;
Internet and the Web;
Mobile and Wireless Technology;
AI and Machine Learning;
Fashion Industry;
Retail Industry;
Apparel and Accessories Industry;
Consumer Products Industry;
United States
- 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;
Analytics and Data Science;
Market Design;
Digital 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
- April 2021
- Article
A Model of Multi-Pass Search: Price Search Across Stores and Time
By: Navid Mojir and K. Sudhir
In retail settings with price promotions, consumers often search across stores and time. However, the search literature typically only models one pass search across stores, ignoring revisits to stores; the choice literature using scanner data has modeled search across...
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- 2021
- Article
Does Fair Ranking Improve Minority Outcomes? Understanding the Interplay of Human and Algorithmic Biases in Online Hiring
By: Tom Sühr, Sophie Hilgard and Himabindu Lakkaraju
Ranking algorithms are being widely employed in various online hiring platforms including LinkedIn, TaskRabbit, and Fiverr. Prior research has demonstrated that ranking algorithms employed by these platforms are prone to a variety of undesirable biases, leading to the...
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