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Spring 2016
Article

The Billion Prices Project: Using Online Prices for Inflation Measurement and Research

By: Alberto Cavallo and Roberto Rigobon

New data-gathering techniques, often referred to as “Big Data” have the potential to improve statistics and empirical research in economics. In this paper we describe our work with online data at the Billion Prices Project at MIT and discuss key lessons for both... View Details

Keywords: Billion Prices Project; Online Scraped Data; Online Price Index; Economics; Research; Price; Analytics and Data Science

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July 2023 (Revised July 2023)
Background Note

Generative AI Value Chain

By: Andy Wu and Matt Higgins

Generative AI refers to a type of artificial intelligence (AI) that can create new content (e.g., text, image, or audio) in response to a prompt from a user. ChatGPT, Bard, and Claude are examples of text generating AIs, and DALL-E, Midjourney, and Stable Diffusion are... View Details

Keywords: AI; Artificial Intelligence; Model; Hardware; Data Centers; AI and Machine Learning; Applications and Software; Analytics and Data Science; Value

January 2022
Article

Artificial Intelligence, Data-Driven Learning, and the Decentralized Structure of Platform Ecosystems

By: David R. Clough and Andy Wu

Gregory, Henfridsson, Kaganer, and Kyriakou (2020) highlight the important role of data and AI as strategic resources that platforms may use to enhance user value. However, their article overlooks a significant conceptual distinction: the installed base of... View Details

Keywords: Artificial Intelligence; Data Strategy; Ecosystem; Value Capture; Digital Platforms; Analytics and Data Science; Strategy; Learning; Value Creation; AI and Machine Learning; Technology Industry; Information Technology Industry; Video Game Industry; Advertising Industry

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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

Research Summary

Overview

By: Kris Johnson Ferreira

Professor Ferreira's research primarily focuses on how retailers can use algorithms to make better revenue management decisions, including pricing, product display, and assortment planning. In the retail industry, anticipating consumer demand is arguably one of the... View Details

Keywords: E-commerce; Analytics; Revenue Management; Pricing; Assortment Planning; Field Experiments; Operations; Supply Chain; Supply Chain Management; Retail Industry

August 2018 (Revised April 2019)
Supplement

Chateau Winery (B): Supervised Learning

By: Srikant M. Datar and Caitlin N. Bowler

This case builds directly on “Chateau Winery (A).” In this case, Bill Booth, marketing manager of a regional wine distributor, shifts to supervised learning techniques to try to predict which deals he should offer to customers based on the purchasing behavior of those... View Details

Keywords: Data Science; Clustering; Analytics and Data Science; Customers; Marketing; Analysis

Article

Uninformed Consent

By: Leslie K. John

Companies want access to more and more of your personal data—from where you are to what’s in your DNA. Can they unlock its value while respecting consumers’ privacy? View Details

Keywords: Personal Data; Privacy; Customers; Analytics and Data Science; Ethics; Governing Rules, Regulations, and Reforms

July 16, 2015
Article

How Small Businesses Can Fend Off Hackers

By: Lou Shipley

If you wanted to hack a business, which one would you pick: A Fortune 500 company with a large digital-security budget and a team dedicated to protecting its cyberassets? Or a small enterprise that doesn’t employ a single IT security specialist? Security breaches at... View Details

Keywords: Hack; Data Security; Small Business; Analytics and Data Science; Safety; Information Technology; Cybersecurity

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March 2022 (Revised July 2022)
Technical Note

Linear Regression

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

This note provides an overview of linear regression for an introductory data science course. It begins with a discussion of correlation, and explains why correlation does not necessarily imply causation. The note then describes the method of least squares, and how to... View Details

Keywords: Data Science; Linear Regression; Mathematical Modeling; Mathematical Methods; Analytics and Data Science

March 2019
Case

HOPI: Turkey's Shopping Companion

By: Sunil Gupta, Donald Ngwe and Gamze Yucaoglu

The case opens in 2017 as Onur Erbay, CEO of HOPI, a multi-vendor loyalty platform, is contemplating a critical decision. The case chronicles the origins of Boyner Group, the parent company of HOPI and a major retailer in Turkey, and development of retail and customer... View Details

Keywords: Loyalty Programs; Multi-vendor Platform; Retail; Big Data; Customer Relationship Management; Mobile and Wireless Technology; Business Model; Analytics and Data Science; Competitive Strategy; Decision Making; Applications and Software; Digital Platforms; Technology Industry; Retail Industry; Turkey

June 2022 (Revised July 2022)
Technical Note

Causal Inference

By: Iavor I Bojinov, Michael Parzen and Paul Hamilton

This note provides an overview of causal inference for an introductory data science course. First, the note discusses observational studies and confounding variables. Next the note describes how randomized experiments can be used to account for the effect of... View Details

Keywords: Causal Inference; Causality; Experiment; Experimental Design; Data Science; Analytics and Data Science

March 2019 (Revised July 2020)
Case

MoviePass: The 'Get Big Fast' Strategy

By: Benjamin C. Esty and Daniel W. Fisher

In August 2017, MoviePass dramatically lowered its subscription price from $50 per month to just $10 for up to one movie per day. The idea was to rapidly scale the business to the point where they could generate incremental revenue streams from related businesses... View Details

Keywords: Market Entry; Growth Strategy; Profit Vs. Growth; Subscription Business; Cash Burn; Data Analytics; Get-big-fast; Buyer Power; Strategy Implementation; Movie Industry; Racing; Entrepreneurship; Market Entry and Exit; Growth and Development Strategy; Business Strategy; Value Creation; Disruption; Motion Pictures and Video Industry; United States

August 2013 (Revised August 2014)
Case

Catalina In the Digital Age

By: Robert J. Dolan and Uma R. Karmarkar

Catalina in the Digital Age considers how a company with a dominant market position should evolve its established product lines given the rise of novel digital technologies. Since its founding in 1983, Catalina had enjoyed a distinct position in the world of consumer... View Details

Keywords: Big Data; Digital Technologies; Marketing; Customer Relationship Management; Consumer Behavior; Analytics and Data Science

April 2014 (Revised March 2015)
Case

GE and the Industrial Internet

By: Karim R. Lakhani, Marco Iansiti and Kerry Herman

CEO Jeff Immelt considers whether GE is moving fast enough on its new Industrial Internet initiative. The undertaking includes building out an Industrial Internet, connecting machines and devices, collecting their data and operations, and providing services to clients... View Details

November 2018
Case

Komatsu Komtrax: Asset Tracking Meets Demand Forecasting

By: Willy Shih, Paul Hong and YoungWon Park

Komatsu's Komtrax system started as a way of remotely monitoring and tracking equipment for the purpose of improving operational efficiency. This case follows its evolution towards other uses including demand forecasting for its sales, marketing, and production... View Details

Keywords: Big Data; Manufacturing; Manufacturing Industry; Data Strategy; Internet Of Things; Construction; Production; Analytics and Data Science; Strategy; Performance Efficiency; Forecasting and Prediction; Industrial Products Industry; Construction Industry; Japan

October 2017
Case

Quantopian: A New Model for Active Management

By: Sara Fleiss, Adi Sunderam, Luis M. Viceira and Caitlin Carmichael

Keywords: Big Data; Hedge Fund; Crowdsourcing; Investment Fund; Quantitative Hedge Fun; Algorithmic Data; Analytics and Data Science

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... View Details

Keywords: Satellite Images; Store-level Performance; Institutional Investors; Local Advantage; Overweighting; Processing Costs; Alternative Data; Big Data; Emerging Technologies; Information; Quality; Institutional Investing; Decision Making; Behavioral Finance; Analytics and Data Science

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January 2014 (Revised January 2017)
Case

Nivea (A)

By: Karim R. Lakhani, Johann Fuller, Volker Bilgram and Greta Friar

The case describes the efforts of Beiersdorf, a worldwide leader in the cosmetics and skin care industries, to generate and commercialize new R&D through open innovation using external crowds and "netnographic" analysis. Beiersdorf, best known for its consumer brand... View Details

Keywords: Innovation; Innovation Management; Crowdsourcing; Big Data; Innovation Strategy; Innovation and Management; Knowledge Management; Knowledge Sharing; Research and Development; Social and Collaborative Networks; Collaborative Innovation and Invention; Analytics and Data Science; Beauty and Cosmetics Industry; Consumer Products Industry

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

01 Dec 1999
News

The Way You See It

vaunted analytical skills of HBS alumni prove to be on target? Stay tuned. What essentials shoiuld HBS stress for the future? Morals, ethics, values Globalization Entrepreneurship Technology, computers Leadership View Details

Keywords: Garry Emmons. Data collection by Ericka Webb.

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