Publications

22 May 2008
Working Paper Summaries

Testing Strategy with Multiple Performance Measures Evidence from a Balanced Scorecard at Store24

Keywords: by Dennis Campbell, Srikant M. Datar, Susan L. Kulp & V.G. Narayanan; Food & Beverage

2017
Working Paper

Nowcasting the Local Economy: Using Yelp Data to Measure Economic Activity

By: Edward L. Glaeser, Hyunjin Kim and Michael Luca

Can new data sources from online platforms help to measure local economic activity? Government datasets from agencies such as the U.S. Census Bureau provide the standard measures of economic activity at the local level. However, these statistics typically appear only... View Details

Keywords: Economy; Analytics and Data Science; Local Range; Social and Collaborative Networks

SSRN

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15 Aug 2024
Op-Ed

Post-CrowdStrike, Six Questions to Test Your Company's Operational Resilience

team. They will be responsible for designing and maintaining the business continuity and disaster recovery management plan, ensuring a robust and effective response to potential disasters. Process: Maintaining the plan iteratively and conducting View Details

Keywords: by Hise Gibson and Anita Lynch

2016
Working Paper

Experimental Evidence on Policies Aimed at Closing the Gender Gap in Willingness to Guess on Multiple-Choice Tests

By: Katherine Baldiga Coffman

Research has shown that women skip more questions than men on multiple-choice tests with penalties for wrong answers. We propose and test five policy changes aimed at eliminating this source of gender bias in test scores. Our data show that simply removing the penalty... View Details

Keywords: Competition; Behavior; Decision Choices and Conditions; Gender

January–February 2025
Article

Want Your Company to Get Better at Experimentation?: Learn Fast by Democratizing Testing

By: Iavor Bojinov, David Holtz, Ramesh Johari, Sven Schmit and Martin Tingley

For years, online experimentation has fueled the innovations of leading tech companies, enabling them to rapidly test and refine new ideas, optimize product features, personalize user experiences, and maintain a competitive edge. The widespread availability and lower... View Details

Keywords: Technological Innovation; AI and Machine Learning; Analytics and Data Science; Product Development; Competitive Advantage

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February 2025
Article

Variation in Batch Ordering of Imaging Tests in the Emergency Department and the Impact on Care Delivery

By: Jacob C. Jameson, Soroush Saghafian, Robert S. Huckman and Nicole Hodgson

Objectives: To examine heterogeneity in physician batch ordering practices and measure the impact of a physician's tendency to batch order imaging tests on patient outcomes and resource utilization.
Study Setting and Design: In this retrospective study, we used... View Details

Keywords: Health Care; Operations Management; Productivity; Health Care and Treatment; Operations; Outcome or Result; Resource Allocation; Health Industry; United States

May–June 2018
Article

Data Uncertainty in Markov Chains: Application to Cost-Effectiveness Analyses of Medical Innovations

By: Joel Goh, Mohsen Bayati, Stefanos A. Zenios, Sundeep Singh and David Moore

Cost-effectiveness studies of medical innovations often suffer from data inadequacy. When Markov chains are used as a modeling framework for such studies, this data inadequacy can manifest itself as imprecision in the elements of the transition matrix. In this paper,... View Details

Keywords: Markov Chains; Cost Effectiveness; Medical Innovations; Colorectal Cancer; Health Care and Treatment; Cost vs Benefits; Innovation and Invention; Mathematical Methods; Health Industry

12 Apr 2022
Research & Ideas

Swiping Right: How Data Helped This Online Dating Site Make More Matches

them with a premium “who likes you” feature. The control group couldn’t see their potential paramours, only their number of swipes. However, the test group would enjoy a reveal after one month, unblurring the photo of each user who... View Details

Keywords: by Kara Baskin

August 2005 (Revised December 2006)
Case

Procter & Gamble: Electronic Data Capture and Clinical Trial Management

By: Robert S. Huckman and Mark J. Cotteleer

Considers whether the management of Procter & Gamble (P&G) Pharmaceuticals should adopt Web-based electronic data capture (EDC) as the default standard for the management of its clinical drug trials. Provides a detailed description of the existing paper-based process... View Details

Keywords: Health Testing and Trials; Internet and the Web; Information Technology; Adoption; Business Processes; Industry Structures; Technological Innovation; Service Operations; Pharmaceutical Industry; United States

Educators

June 2023
Simulation

Artea Dashboard and Targeting Policy Evaluation

By: Ayelet Israeli and Eva Ascarza

Companies deploy A/B experiments to gain valuable insights about their customers in order to answer strategic business problems. In marketing, A/B tests are often used to evaluate marketing interventions intended to generate incremental outcomes for the firm. The Artea... View Details

21 Jan 2010
Working Paper Summaries

Going Through the Motions: An Empirical Test of Management Involvement in Process Improvement

Keywords: by Anita L. Tucker; Health

27 Feb 2024
Research & Ideas

Why Companies Should Share Their DEI Data (Even When It’s Unflattering)

products. “At the moment, many companies aren’t disclosing data on their workforce diversity,” Nam explains. “Simply disclosing this information is enough to improve customer attitudes.” The research comes amid mounting concern that DEI... View Details

Keywords: by Shalene Gupta

September 2020 (Revised June 2023)
Exercise

Artea: Designing Targeting Strategies

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

This paper evaluates the short- and long-term value of sales representatives’ detailing visits to different types of physicians. By understanding the dynamic effect of sales calls across heterogeneous physicians, we provide guidance on the design of optimal call... View Details

Teaching Interest

Overview

Paul is primarily interested in teaching data science to management students through the case method. This includes technical topics (programming and statistics) as well as higher-level management issues (digital transformation, data governance, etc.) As a research... View Details

Keywords: A/B Testing; AI; AI Algorithms; AI Creativity; Algorithm; Algorithm Bias; Algorithmic Bias; Algorithmic Fairness; Algorithms; Analytics; Application Program Interface; Artificial Intelligence; Causality; Causal Inference; Computing; Computers; Data Analysis; Data Analytics; Data Architecture; Data As A Service; Data Centers; Data Governance; Data Labeling; Data Management; Data Manipulation; Data Mining; Data Ownership; Data Privacy; Data Protection; Data Science; Data Science And Analytics Management; Data Scientists; Data Security; Data Sharing; Data Strategy; Data Visualization; Database; Data-driven Decision-making; Data-driven Management; Data-driven Operations; Datathon; Economics Of AI; Economics Of Innovation; Economics Of Information System; Economics Of Science; Forecast; Forecast Accuracy; Forecasting; Forecasting And Prediction; Information Technology; Machine Learning; Machine Learning Models; Prediction; Prediction Error; Predictive Analytics; Predictive Models; Analysis; AI and Machine Learning; Analytics and Data Science; Applications and Software; Digital Transformation; Information Management; Digital Strategy; Technology Adoption

Article

Online Experimentation: Benefits, Operational and Methodological Challenges, and Scaling Guide

By: Iavor Bojinov and Somit Gupta

In the past decade, online controlled experimentation, or A/B testing, at scale has proved to be a significant driver of business innovation. The practice was first pioneered by the technology sector and, more recently, has been adopted by traditional companies... View Details

Keywords: A/B Testing; Experimentation; Data-driven Culture; Product Development; Innovation and Invention; Digital Transformation

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March 2022 (Revised January 2025)
Technical Note

Statistical Inference

By: Iavor I. Bojinov, Michael Parzen and Paul Hamilton

This note provides an overview of statistical inference for an introductory data science course. First, the note discusses samples and populations. Next the note describes how to calculate confidence intervals for means and proportions. Then it walks through the logic... View Details

Keywords: Data Science; Statistics; Mathematical Modeling; Mathematical Methods; Analytics and Data Science

Educators