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- Article
Financial Shame Spirals: How Shame Intensifies Financial Hardship
By: Joe J. Gladstone, Jon M. Jachimowicz, Adam Eric Greenberg and Adam D. Galinsky
Financial hardship is an established source of shame. This research explores whether shame is also a driver and exacerbator of financial hardship. Six experimental, archival, and correlational studies (N = 9,110)—including data from customer bank account histories and...
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- 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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- 2021
- Working Paper
Channeled Attention and Stable Errors
We develop a framework for assessing when a person will notice that a theory she has about the world is wrong, premised on the idea that people neglect information that they view (through the lens of their misconceptions) to be irrelevant. Focusing on the question of...
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- 2021
- Working Paper
BEAT Unintended Bias in Personalized Policies
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" attributes....
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- August 2021
- Case
Orchadio’s First Two Split Experiments
By: Iavor I. Bojinov, Marco Iansiti and David Lane
Orchadio, a direct-to-consumer grocery business, needs to conduct its first two A/B tests—one to evaluate the effectiveness and functioning of its newly redesigned website, and one to market-test four versions of a new banner for the website. To do so, it will rely on...
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- 2021
- Working Paper
Going to Extremes: Crucibles, Multiple Sensitive Periods, and Career Progression
By: Prithwiraj Choudhury, Sunasir Dutta, Hise O. Gibson and Eric Lin
We study the effects of crucible experiences along multiple sensitive periods on career progression. While prior literature has hinted that individuals can be imprinted during multiple sensitive periods, not just during the early career, there has been scant attention...
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- Article
Are They Useful? The Effects of Performance Incentives on the Prioritization of Work Versus Personal Ties
By: Julia Hur, Alice Lee-Yoon and Ashley V. Whillans
Most working adults report spending very little time with friends and family. The current research explores the aspects of work that encourage employees to spend less time with personal ties. We show that incentive systems play a critical role in shaping how people...
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- July–August 2021
- Article
Surfacing the Submerged State: Operational Transparency Increases Trust in and Engagement with Government
By: Ryan W. Buell, Ethan Porter and Michael I. Norton
Problem definition: As trust in government reaches historic lows, frustration with government performance approaches record highs.
Academic/practical relevance: We propose that in co-productive settings like government services, peoples’ trust and...
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- 2021
- Article
To Thine Own Self Be True? Incentive Problems in Personalized Law
By: Jordan M. Barry, John William Hatfield and Scott Duke Kominers
Recent years have seen an explosion of scholarship on “personalized law.” Commentators foresee a world in which regulators armed with big data and machine learning techniques determine the optimal legal rule for every regulated party, then instantaneously disseminate...
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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
- Article
A Multicountry Perspective on Gender Differences in Time Use During COVID-19
By: Ashley V. Whillans, Laura M. Giurge and Ayse Yemiscigil (shared authorship)
The COVID-19 pandemic has fundamentally altered how people spend time, with possible consequences for subjective well-being. Using diverse samples of remote workers from the United States, Canada, Denmark, Brazil, and Spain (n = 31,141), following a preregistered...
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- 2021
- Working Paper
Working from Home during COVID-19: 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 during the pandemic impacted how knowledge workers allocate time throughout their working day. We analyzed the results from an online time-use survey that collected data on 1,192 knowledge workers in...
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Keywords:
Time-use;
COVID;
Knowledge Workers;
Working-from-home;
Managers;
Health Pandemics;
Time Management
- March 2021
- Article
The Impact of the General Data Protection Regulation on Internet Interconnection
By: Ran Zhuo, Bradley Huffaker, KC Claffy and Shane Greenstein
The Internet comprises thousands of independently operated networks, where bilaterally negotiated interconnection agreements determine the flow of data between networks. The European Union’s General Data Protection Regulation (GDPR) imposes strict restrictions on...
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- 2021
- White Paper
Working to Learn: Despite a Growing Set of Innovators, America Struggles to Connect Education and Career
By: Joseph B. Fuller, Rachel Lipson, Jorge Encinas, Tessa Forshaw, Alexis Gable and J.B. Schramm
In the wake of COVID-19 and growing inequality, America needs more pathways that bridge education and career. New research from the Project on Workforce at Harvard draws on data from New Profit's Postsecondary Initiative for Equity to identify opportunities for the...
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- February 2021
- Supplement
Apple: Privacy vs. Safety (B)
By: Henry McGee, Nien-hê Hsieh and Christian Godwin
In 2020, as the COVID-19 pandemic swept across the globe, Apple and Google partnered to develop a contact tracing application that would collect information about users infected with the disease and notify those who they had been in contact with. While Apple/Google’s...
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Keywords:
Iphone;
Encryption;
Data Privacy;
Customers;
Customer Focus and Relationships;
Decision Making;
Ethics;
Values and Beliefs;
Globalized Firms and Management;
Government and Politics;
Health;
Health Pandemics;
Leadership;
Markets;
Safety;
Social Issues;
Technology;
Telecommunications Industry;
Technology Industry;
Consumer Products Industry;
Electronics Industry;
Health Industry;
United States;
Europe
- 2021
- Working Paper
Information Avoidance and Image Concerns
By: Christine L. Exley and Judd B. Kessler
A rich literature finds that individuals avoid information, even information that is instrumental to their choices. A common hypothesis posits that individuals strategically avoid information to hold particular beliefs or to take certain actions--such as behaving...
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- 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
- 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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- January 2021
- Article
How Personality and Policy Predict Pandemic Behavior: Understanding Sheltering-in-Place in 55 Countries at the Onset of COVID-19
By: Friedrich M. Götz, Andrés Gvirtz, Adam D. Galinsky and Jon M. Jachimowicz
The spread of COVID-19 within any given country or community at the onset of the pandemic depended in part on the sheltering-in-place rate of its citizens. The pandemic led us to revisit one of psychology’s most fundamental and most basic questions in a high-stakes...
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- Article
Credit and Punishment: Are Corporate Bankers Disciplined for Risk-Taking?
By: Janet Gao, Kristoph Kleiner and Joseph Pacelli
We examine whether bankers face disciplining consequences for structuring poorly performing corporate loans. We construct a novel data set containing the employment histories and loan portfolios of a large sample of corporate bankers and find that corporate credit...
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