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- 2022
- Book
The Digital Mindset: What It Really Takes to Thrive in the Age of Data, Algorithms, and AI
By: Paul Leonardi and Tsedal Neeley
The pressure to "be digital" has never been greater, but you can meet the challenge.
The digital revolution is here, changing how work gets done, how industries are structured, and how people from all walks of life work, behave, and relate to each other. To thrive...
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- March 2022 (Revised July 2022)
- Case
Nexleaf Analytics: Saving the World Using the Internet of Things
By: Frank Nagle
In 2019, a decade after co-founding Nexleaf Analytics, CEO Nithya Ramanathan faced an important decision that would impact the ability of the small, but growing, not-for-profit organization to thrive for another decade. Their sensor technologies and big data analytics...
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- February 2022
- Case
CityScore: Big Data Comes to Boston
By: Boris Groysberg and Sarah L. Abbott
In 2016, Martin “Marty” Walsh, the Mayor of Boston, introduced CityScore, a data dashboard that measured the city’s progress across a range of metrics. The dashboard was updated daily and publicly available. The mayor frequently discussed the CityScore targets in...
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- 2022
- Working Paper
Gone with the Big Data: Institutional Lender Demand for Private Information
By: Jung Koo Kang
I explore whether the value of borrowers’ private information is an important determinant of institutional lender participation in syndicated loans. Institutional lenders have been shown to exploit their access to borrowers’ private information by trading on it in...
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- Article
Core Earnings: New Data and Evidence
By: Ethan Rouen, Eric C. So and Charles C.Y. Wang
Using a novel dataset, we show that components of firms' GAAP earnings stemming from ancillary business activities or transitory shocks are significant in frequency and magnitude. These components have grown over time and are dispersed across various sections of the...
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- October 18, 2021
- Article
To Regulate Network-Based Platforms, Look at Their Data
By: Chiara Farronato and Daniel Björkegren
Historically, antitrust authorities have taken a laissez-faire approach under the assumption that it is better to err on the side of not intervening when there is uncertainty. This has allowed companies like Google and Facebook to go on a shopping spree to acquire...
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- 2021
- Chapter
Building Small Business Utopia: How Artificial Intelligence and Big Data Can Increase Small Business Success
By: Karen G. Mills and Annie Dang
Small business lending has remained unchanged for decades, laden with frictions and barriers that prevent many small businesses from accessing the capital they need to succeed. Financial technology, or “fintech,” promises to change this trajectory. In 2010, new fintech...
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- 2021
- Working Paper
T-Shaped Managers—One Size Does Not Fit All: Exploratory Study from the Military
By: Hise O. Gibson
People are an organization’s most important resource. Managers who are collaborative and innovative ensure that organizations remain competitive. This type of manager has been referred to as a T-shaped manager. “T” given that the vertical portion represents the depth...
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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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Keywords:
Personalized Law;
Regulation;
Regulatory Avoidance;
Regulatory Arbitrage;
Law And Economics;
Law And Technology;
Law And Artificial Intelligence;
Futurism;
Moral Hazard;
Elicitation;
Signaling;
Privacy;
Law;
Governing Rules, Regulations, and Reforms;
Information Technology;
AI and Machine Learning
- 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 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;
E-commerce;
Digital Platforms;
Fashion Industry;
Retail Industry;
Apparel and Accessories Industry;
Consumer Products Industry;
United States
- May 2021
- Article
The Firm Next Door: Using Satellite Images to Study Local Information Advantage
By: Jung Koo Kang, Lorien Stice-Lawrence and Forester Wong
We use novel satellite data that track the number of cars in the parking lots of 92,668 stores for 71 publicly listed U.S. retailers to study the local information advantage of institutional investors. We establish car counts as a timely measure of store-level...
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- 2020
- Working Paper
Is Accounting Useful for Forecasting GDP Growth? A Machine Learning Perspective
We provide a comprehensive examination of whether, to what extent, and which accounting variables are useful for improving the predictive accuracy of GDP growth forecasts. We leverage statistical models that accommodate a broad set of (341) variables—outnumbering the...
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- Spring 2021
- Article
Corporate Resilience and Response During COVID-19
By: Alex Cheema-Fox, Bridget LaPerla, George Serafeim and Hui (Stacie) Wang
The coronavirus pandemic caused a sharp market decline while raising heterogeneous responses across companies related to their employees, supply chain, and repurposing of operations to provide needed products and services. We study whether during the 2020 COVID-19...
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Keywords:
ESG;
COVID-19;
Coronavirus;
Crisis Response Plans;
Crisis;
ESG (Environmental, Social, Governance) Performance;
ESG Ratings;
Leadership & Corporate Accountability;
Big Data;
Machine Learning;
Investor Behavior;
Institutional Investors;
Corporate Performance;
Health Pandemics;
Crisis Management;
Corporate Social Responsibility and Impact;
Human Capital;
Supply Chain;
Operations;
Leadership;
Corporate Accountability;
Institutional Investing;
Performance
- February 2021 (Revised June 2021)
- Case
Bairong and the Promise of Big Data
By: Lauren Cohen, Xiaoyan Zhang and Spencer C.N. Hagist
Bairong CEO Felix Zhang, in launching his credit scoring start-up that incorporates 74,000 variables per individual, found strong initial success. However, the shifting regulatory environment, growing breadth of competitors, difficulties in retaining top talent, and...
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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...
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Keywords:
Data;
Data Analytics;
Artificial Intelligence;
AI;
AI Algorithms;
AI Creativity;
Fashion;
Retail;
Retail Analytics;
E-Commerce Strategy;
Platform;
Platforms;
Big Data;
Preference Elicitation;
Preference Prediction;
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;
E-commerce;
Digital Platforms;
Fashion Industry;
Retail Industry;
Apparel and Accessories Industry;
Consumer Products Industry;
United States
- Winter 2021
- Editorial
Introduction
This issue of Negotiation Journal is dedicated to the theme of artificial intelligence, technology, and negotiation. It arose from a Program on Negotiation (PON) working conference on that important topic held virtually on May 17–18. The conference was not the...
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- Article
Healthy Buildings in 2070
By: John D. Macomber and Joseph G. Allen
Fifty years seems a very long time in the future for most industries. Not so in buildings and real estate; built structures routinely last decades if not hundreds of years, as long as they are economically competitive. Any discussion of the 50-year future has to...
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- 2021
- 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 difference-in-differences method to analyze the staggered adoption of a retail analytics dashboard by more than 1,500 e-commerce websites, and we find an...
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- Article
Cheating, Inequality Aversion, and Appealing to Social Norms
By: Clara Amato, Francesca Gino, Natalia Montinari and Pierluigi Sacco
We conduct a field experiment involving 143, 9-years old children in their classrooms. Children are requested to flip a coin in private and receive a big or a small prize depending on the outcome they report. Comparing the actual and theoretical distribution of...
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- 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...
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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;
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