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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

February 2021
Tutorial

T-tests: Theory and Practice

By: Michael Parzen, Natalie Epstein, Chiara Farronato and Michael Toffel

This video provides an introduction to hypothesis testing, sampling, t-tests, and p-values. It provides examples of A/B testing and t-testing to assess whether difference between two groups are statistically significant. This video can be assigned in conjunction with... View Details

Keywords: Data Analysis; Data Analytics; Experiment Design; Experimentation; Analytics and Data Science; Analysis

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

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

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February 2024
Module Note

Data-Driven Marketing in Retail Markets

By: Ayelet Israeli

This note describes an eight-class sessions module on data-driven marketing in retail markets. The module aims to familiarize students with core concepts of data-driven marketing in retail, including exploring the opportunities and challenges, adopting best practices,... View Details

September 2020 (Revised July 2022)
Exercise

Artea (D): Discrimination through Algorithmic Bias in Targeting

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

November 2016 (Revised April 2017)
Case

Basecamp: Pricing

By: Frank Cespedes and Robb Fitzsimmons

A data analyst at Basecamp is evaluating the results of pricing research and its potential implications for the venture’s latest version of its project management software product. View Details

Keywords: Pricing; Entrepreneurial Management; Data Analysis; Marketing; Customer Acquisition; Customer Retention; Value Proposition; Sales Management; Product Management; Market Research; Life Time Value; Testing; Entrepreneurship; Analytics and Data Science; Customers; Value; Sales; Product Marketing; United States

August 2020 (Revised September 2020)
Technical Note

Assessing Prediction Accuracy of Machine Learning Models

By: Michael W. Toffel, Natalie Epstein, Kris Ferreira and Yael Grushka-Cockayne

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... View Details

Keywords: Machine Learning; Statistics; Econometric Analyses; Experimental Methods; Data Analysis; Data Analytics; Forecasting and Prediction; Analytics and Data Science; Analysis; Mathematical Methods

16 Apr 2019
Working Paper Summaries

Can Biometric Tracking Improve Healthcare Provision and Data Quality? Experimental Evidence from Tuberculosis Control in India

Keywords: by Thomas Bossuroy, Clara Delavallade, and Vincent Pons; Health; Medical Devices & Supplies

2020
Working Paper

Is Accounting Useful for Forecasting GDP Growth? A Machine Learning Perspective

By: Srikant Datar, Apurv Jain, Charles C.Y. Wang and Siyu Zhang

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... View Details

Keywords: Big Data; Elastic Net; GDP Growth; Machine Learning; Macro Forecasting; Short Fat Data; Accounting; Economic Growth; Forecasting and Prediction; Analytics and Data Science

Article

Evaluating and Managing Tramp Shipping Lines Performances: A New Methodology Combining Balanced Scorecard and Network DEA

By: Ying-Chen Hsu, Cheng-Chi Chung, Hsuan-Shih Lee and H. David Sherman

The shipping industry is essential for the economic development of nations like Taiwan as a means delivering and receiving cargo. Shipping has been depressed since 2008 as a result of the financial crisis increasing pressure for the shipping lines to operate more... View Details

Keywords: Network Data Envelopment Analysis; Shipping Line; Centralized Approach; Cross-efficiency; Balanced Scorecard; Performance Evaluation

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April 2018
Article

Scope versus Speed: Team Diversity, Leader Experience, and Patenting Outcomes for Firms

By: Prithwiraj Choudhury and Martine R. Haas

How does the organization of patenting activity affect a firm’s patenting outcomes? We investigate how the composition of patenting teams relates to both the scope of their patent applications and the speed of their patent approvals by examining the main effects of... View Details

Keywords: Leader Experience; Micro-foundations Of Innovation; Scope; Speed; Team Diversity; Within-firm Data; Groups and Teams; Diversity; Patents; Leadership; Experience and Expertise; Outcome or Result

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November 2021
Article

Panel Experiments and Dynamic Causal Effects: A Finite Population Perspective

By: Iavor Bojinov, Ashesh Rambachan and Neil Shephard

In panel experiments, we randomly assign units to different interventions, measuring their outcomes, and repeating the procedure in several periods. Using the potential outcomes framework, we define finite population dynamic causal effects that capture the relative... View Details

Keywords: Panel Data; Dynamic Causal Effects; Potential Outcomes; Finite Population; Nonparametric; Mathematical Methods

April 2015 (Revised March 2017)
Case

Instacart and the New Wave of Grocery Startups

By: John Deighton and Leora Kornfeld

Instacart is testing an Uber-style solution to the challenge of building a home-delivered grocery business. It is backed by $220 million of venture funding. Will this model succeed where businessses like Webvan failed? What are the questions that this exploratory... View Details

Keywords: Food Retailing; Outsourced Grocery Delivery; Online Ordering; Dynamic Pricing; Data Analytics; Marketing Strategy; Food; Distribution Channels; Business Startups; Food and Beverage Industry; California

August 2018 (Revised October 2019)
Case

C3.ai—Driven to Succeed

By: Robert Simons and George Gonzalez

CEO Tom Siebel navigates his artificial intelligence (ai) startup through a series of pivots, market expansions, and even an elephant attack to become a leading platform ad service provider. The case describes his unusual management approach emphasizing employee... View Details

June 2017
Article

When Novel Rituals Lead to Intergroup Bias: Evidence from Economic Games and Neurophysiology

By: Nicholas M. Hobson, Francesca Gino, Michael I. Norton and Michael Inzlicht

Long-established rituals in pre-existing cultural groups have been linked to the cultural evolution of large-scale group cooperation. Here we test the prediction that novel rituals—arbitrary hand and body gestures enacted in a stereotypical and repeated fashion—can... View Details

Keywords: Ritual; Intergroup Dynamics; Intergroup Bias; Neural Reward Processing; Open Data; Open Materials; Preregistered; Groups and Teams; Behavior; Prejudice and Bias; Cooperation

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October 2016 (Revised February 2019)
Module Note

Strategy Execution Module 5: Building a Profit Plan

By: Robert Simons

This module reading describes how to build a profit plan to reflect the strategy of a business in economic terms. After introducing the profit wheel, cash wheel, and ROE wheel, the module illustrates how to use a profit plan to assess the viability of different... View Details

Keywords: Management Control Systems; Implementing Strategy; Execution; Profit Planning; Cash Flow Analysis; Asset Utilization; Return On Equity; Business Planning; Testing Strategy; Analyzing Strategic Alternative; Strategy; Asset Management; Cash Flow; Investment Return; Management Systems; Profit

16 Feb 2016
News

Is your child taking a test? When is the right time?

May 2013
Teaching Note

Launching Krispy Natural: Cracking the Product Management Code (Brief Case)

By: Frank V. Cespedes and Heather Beckham

This case study concerns a review and interpretation of test market results for a new packaged good product. The purpose of the case is to provide students with practice and guidelines in the analysis of quantitative test market data while illustrating the roles of... View Details

Keywords: Analytics and Data Science; Analysis; Product Marketing

20 Jul 2015
News

Better innovation

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