Publications

21 Sep 2020
Working Paper Summaries

The Targeting and Impact of Paycheck Protection Program Loans to Small Businesses

Keywords: by Alexander Bartik, Zoë B. Cullen, Edward L. Glaeser, Michael Luca, Christopher Stanton, and Adi Sunderam

11 May 2020
Working Paper Summaries

Targeting High Ability Entrepreneurs Using Community Information: Mechanism Design in the Field

Keywords: by Reshmaan Hussam, Natalia Rigol, and Benjamin N. Roth

May 2019
Supplement

Did You Decide to Proceed by Targeting Three or Six New Products?

By: Michael W. Toffel

Forthcoming
Article

When Should Public Programs Be Privately Administered? Theory and Evidence from the Paycheck Protection Program

By: Alexander W. Bartik, Zoë Cullen, Edward L. Glaeser, Michael Luca, Christopher Stanton and Adi Sunderam

What happens when public resources are allocated by private companies whose objectives may be imperfectly aligned with policy goals? We study this question in the context of the Paycheck Protection Program (PPP), which relied on private banks to disburse aid to small... View Details

Keywords: Paycheck Protection Program; Targeting; Impact; Entrepreneurship; Health Pandemics; Small Business; Financing and Loans; Outcome or Result; United States

SSRN

December 1988 (Revised November 1989)
Case

Provigo, Inc. (B): Issues Surrounding Target Setting and Use of Discretion in Performance Evaluations

2023
Working Paper

When Should Public Programs Be Privately Administered? Theory and Evidence from the Paycheck Protection Program

By: Alexander Bartik, Zoë B. Cullen, Edward L. Glaeser, Michael Luca, Christopher Stanton and Adi Sunderam

What happens when public resources are allocated by private companies whose objectives may be imperfectly aligned with policy goals? We study this question in the context of the Paycheck Protection Program (PPP), which relied on private banks to disburse aid to small... View Details

Keywords: Paycheck Protection Program; Targeting; Impact; Entrepreneurship; Health Pandemics; Small Business; Financing and Loans; Outcome or Result; United States

SSRN

September 2020 (Revised July 2022)
Exercise

Artea (B): Including Customer-Level Demographic Data

By: Eva Ascarza and Ayelet Israeli

This collection of exercises aims to teach students about 1)Targeting Policies; and 2)Algorithmic bias in marketing—implications, causes, and possible solutions. Part (A) focuses on A/B testing analysis and targeting. Parts (B),(C),(D) Introduce algorithmic bias. The... View Details

Keywords: Targeting; Algorithmic Bias; Race; Gender; Marketing; Diversity; Customer Relationship Management; Demographics; Prejudice and Bias; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States

October 2024
Article

Sampling Bias in Entrepreneurial Experiments

By: Ruiqing Cao, Rembrand Koning and Ramana Nanda

Using data from a prominent online platform for launching new digital products, we document that ‘sampling bias’—defined as the difference between a startup’s target customer base and the actual sample on which early ‘beta tests’ are conducted—has a systematic and... View Details

Keywords: Target Market; Sampling Biases; Beta Testing; Product Launch; Entrepreneurship; Gender

September 2019 (Revised June 2020)
Case

Othellonia: Growing a Mobile Game

By: Eva Ascarza, Tomomichi Amano and Sunil Gupta

In the summer of 2019, Yu Sasaki, Head of the Game Division of DeNA, a Japanese mobile gaming company, is evaluating various growth strategies for its recent game Othellonia. Sasaki needs to decide if he should focus on customer acquisition, retention, or monetization. View Details

Keywords: Targeting; Retention/churn; Freemium; Monetization; Customer Relationship Management; Games, Gaming, and Gambling; Mobile and Wireless Technology; Growth and Development Strategy; Marketing; Customers; Marketing Strategy; Retention; Acquisition; Entertainment and Recreation Industry; Japan

Educators

June 23, 2021
Article

Research: When A/B Testing Doesn't Tell You the Whole Story

By: Eva Ascarza

When it comes to churn prevention, marketers traditionally start by identifying which customers are most likely to churn, and then running A/B tests to determine whether a proposed retention intervention will be effective at retaining those high-risk customers. While... View Details

Keywords: Customer Retention; Churn; Targeting; Market Research; Marketing; Investment Return; Customers; Retention; Research

Register to Read

December 2016
Article

Through the Mud or in the Boardroom: Examining Activist Types and Their Strategies in Targeting Firms for Social Change

By: Charles Eesley, K. A. DeCelles and Michael Lenox

We examine the variety of activist groups and their tactics in demanding firms’ social change. While extant work does not usually distinguish among activist types or their variety of tactics, we show that different activists (e.g., social movement organizations vs.... View Details

Keywords: Negotiation Tactics; Investment Activism

April 2021
Background Note

HEAD vs. LEAD: Disruptions Originating at the High- vs. Low-End of the Market

By: Elie Ofek, Olivier Toubia and Didier Toubia

Twenty five years after it was initially proposed, Clay Christensen’s theory of disruptive innovation continues to be a major reference for entrepreneurs, corporate innovators, and investors. However, the term “disruptive innovation” is often used in ways and contexts... View Details

Keywords: Market Entry; New Product Management; Targeting; Disruptive Innovation; Market Entry and Exit; Entrepreneurship; Product; Management; Innovation Strategy; Technology

Educators

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

Keywords: Algorithm Bias; Personalization; Targeting; Generalized Random Forests (GRF); Discrimination; Customization and Personalization; Decision Making; Fairness; Mathematical Methods

Article

The Perils of Proactive Churn Prevention Using Plan Recommendations: Evidence from a Field Experiment

By: Eva Ascarza, Raghuram Iyengar and Martin Schleicher

Facing the issue of increasing customer churn, many service firms have begun recommending pricing plans to their customers. One reason behind this type of retention campaign is that customers who subscribe to a plan suitable for them should be less likely to churn... View Details

Keywords: Churn/retention; Field Experiment; Pricing; Tariff/plan Choice; Targeting; Customer Relationship Management; Price; Performance Effectiveness

June 2002
Article

If You View the Customer's World in Terms of Products and Features Rather Than Jobs That Need to Be Done, You'll Miss the Target

By: Clayton Christensen and Tara Donovan

Keywords: Customers; Product

September 2020 (Revised June 2023)
Supplement

Spreadsheet Supplement to Artea Teaching Note

By: Eva Ascarza and Ayelet Israeli

Spreadsheet Supplement to Artea Teaching Note 521-041. This collection of exercises aims to teach students about 1)Targeting Policies; and 2)Algorithmic bias in marketing—implications, causes, and possible solutions. Part (A) focuses on A/B testing analysis and... View Details

Keywords: Targeted Advertising; Algorithmic Data; Bias; Advertising; Race; Gender; Diversity; Marketing; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States