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Skip to Main Content Cold Call A podcast featuring faculty discussing cases they've written and the lessons they impart. Subscribe on iTunes 29 Sep...
- January 2021
- Article
Using Models to Persuade
By: Joshua Schwartzstein and Adi Sunderam
We present a framework where "model persuaders" influence receivers’ beliefs by proposing models that organize past data to make predictions. Receivers are assumed to find models more compelling when they better explain the data, fixing receivers’ prior beliefs. Model...
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- December 2020
- Article
Taking Innovation to the Streets: Micro-geography, Physical Structure and Innovation
By: Maria P. Roche
In this paper, we analyze how the physical layout of cities affects innovation by influencing the organization of knowledge exchange. We exploit a novel data set covering all Census Block Groups in the contiguous United States with information on innovation outcomes,...
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- Article
Value of New Performance Information in Healthcare: Evidence from Japan
By: Susanna Gallani, Takehisa Kajiwara and Ranjani Krishnan
Mandatory measurement and disclosure of outcome measures are commonly used policy tools in
healthcare. The effectiveness of such disclosures relies on the extent to which the new information produced by the mandatory system is internalized by the healthcare...
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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 3, 2020
- Article
Gender Differences in COVID-19 Related Attitudes and Behavior: Evidence from a Panel Survey in Eight OECD Countries
By: Vincenzo Galasso, Vincent Pons, Paola Profeta, Michael Becher, Sylvain Brouard and Martial Foucault
Using original data from two waves of a survey conducted in March and April 2020 in eight OECD countries (N = 21,649), we show that women are more likely to see COVID-19 as a very serious health problem, to agree with restraining public policy measures adopted in...
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- October 2020
- Exercise
FirstSense Technologies: Pricing to Win
By: Elie Ofek, Eyal Biyalogorsky, Marco Bertini and Oded Koenigsberg
This exercise serves to help students understand the proper role and use of costs in a firm’s pricing decisions. The exercise is designed such that the learning of students evolves across a classroom session, starting from understanding which costs are relevant when...
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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
- 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
- Article
Customer Supercharging in Experience-Centric Channels
By: David R. Bell, Santiago Gallino and Antonio Moreno
We conjecture that for online retailers, experience-centric offline store formats do not simply expand market coverage, but rather, serve to significantly amplify future positive customer behaviors, both online and offline. We term this phenomenon “supercharging” and...
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- Article
Conversational Receptiveness: Expressing Engagement with Opposing Views
By: M. Yeomans, J. Minson, H. Collins, H. Chen and F. Gino
We examine “conversational receptiveness”—the use of language to communicate one’s willingness to thoughtfully engage with opposing views. We develop an interpretable machine-learning algorithm to identify the linguistic profile of receptiveness (Studies 1A-B). We then...
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- August 2020 (Revised September 2020)
- Technical Note
Assessing Prediction Accuracy of Machine Learning Models
The note introduces a variety of methods to assess the accuracy of machine learning prediction models. The note begins by briefly introducing machine learning, overfitting, training versus test datasets, and cross validation. The following accuracy metrics and tools...
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- August 2020
- Technical Note
Comparing Two Groups: Sampling and t-Testing
This note describes sampling and t-tests, two fundamental statistical concepts.
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- 2020
- Working Paper
A Little Help from My Friends: How Receiving Assistance Affects Participation in Online Knowledge-Sharing Communities
By: Eunkwang Seo, Frank Nagle and Sonali K. Shah
Online knowledge-sharing communities are important arenas for the development and exchange of knowledge; both firm participation and sponsorship in communities are increasing, as is scholarly interest in understanding how interactions between members shape subsequent...
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- Article
The Importance of Being Causal
By: Iavor I Bojinov, Albert Chen and Min Liu
Causal inference is the study of how actions, interventions, or treatments affect outcomes of interest. The methods that have received the lion’s share of attention in the data science literature for establishing causation are variations of randomized experiments....
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- July 2020
- Case
Applying Data Science and Analytics at P&G
By: Srikant M. Datar, Sarah Mehta and Paul Hamilton
Set in December 2019, this case explores how P&G has applied data science and analytics to cut costs and improve outcomes across its business units. The case provides an overview of P&G’s approach to data management and governance, and reviews the challenges associated...
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- Article
How to Make Remote Monitoring Tech Part of Everyday Health Care
By: Samantha F. Sanders, Ariel Dora Stern and William J. Gordon
Remote patient monitoring is a subset of telehealth that involves the collection, transmission, evaluation, and communication of patient health data from electronic devices. These devices include wearable sensors, implanted equipment, and handheld instruments. During...
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- July 2020
- Article
Lessons From The Impact of Price Regulation on The Pricing Of Anticancer Drugs in Germany
By: Victoria D. Lauenroth, Aaron S. Kesselheim, Ameet Sarpatwari and Ariel Dora Stern
Worldwide spending on prescription drugs has increased dramatically in recent years. Although this increase has been particularly pronounced in the U.S., it remains largely unaddressed there. In Europe, however, different approaches to regulating drug prices have been...
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- June 2020
- Background Note
Customer Management Dynamics and Cohort Analysis
By: Elie Ofek, Barak Libai and Eitan Muller
The digital revolution has allowed companies to amass considerable amounts of data on their customers. Using this information to generate actionable insights is fast becoming a critical skill that firms must master if they wish to effectively compete and win in today’s...
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- Article
Development of a Deep Learning Algorithm for Periapical Disease Detection in Dental Radiographs
By: Michael G. Endres, Florian Hillen, Marios Salloumis, Ahmad R. Sedaghat, Stefan M. Niehues, Olivia Quatela, Henning Hanken, Ralf Smeets, Benedicta Beck-Broichsitter, Carsten Rendenbach, Karim R. Lakhani, Max Helland and Robert A. Gaudin
Periapical radiolucencies, which can be detected on panoramic radiographs, are one of the most common radiographic findings in dentistry and have a differential diagnosis including infections, granuloma, cysts, and tumors. In this study, we seek to investigate the...
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