Publications

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April 12, 2023
Article

Using AI to Adjust Your Marketing and Sales in a Volatile World

By: Das Narayandas and Arijit Sengupta

Why are some firms better and faster than others at adapting their use of customer data to respond to changing or uncertain marketing conditions? A common thread across faster-acting firms is the use of AI models to predict outcomes at various stages of the customer... View Details

Keywords: Forecasting and Prediction; AI and Machine Learning; Consumer Behavior; Technology Adoption; Competitive Advantage

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23 Apr 2024
In Practice

Getting to Net Zero: The Climate Standards and Ecosystem the World Needs Now

With each month clocking record-breaking temperatures across the planet, this Earth Day reflected the renewed urgency of regulators and businesses to find climate-change solutions. The US Securities and Exchange Commission recently adopted new rules that will mandate... View Details

Keywords: by Rachel Layne

November 2020
Case

Axis My India

By: Ananth Raman, Ann Winslow and Kairavi Dey

Pradeep Gupta founded Axis My India (AMI) as a printing and publishing company in 1998. In 2013, AMI expanded into consumer research and election forecasting. Although a relatively unknown entity, AMI predicted several election results accurately. Gupta describes AMI’s... View Details

Keywords: Market Research; Operations; Management; Infrastructure; Logistics; Service Operations; Political Elections; Forecasting and Prediction; Asia; India

2023
Working Paper

Debiasing Treatment Effect Estimation for Privacy-Protected Data: A Model Auditing and Calibration Approach

By: Ta-Wei Huang and Eva Ascarza

Data-driven targeted interventions have become a powerful tool for organizations to optimize business outcomes by utilizing individual-level data from experiments. A key element of this process is the estimation of Conditional Average Treatment Effects (CATE), which... View Details

Keywords: Analytics and Data Science; Consumer Behavior; Marketing

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

SSRN

Forthcoming
Article

Human-Algorithm Collaboration with Private Information: Naïve Advice Weighting Behavior and Mitigation

By: Maya Balakrishnan, Kris Ferreira and Jordan Tong

Even if algorithms make better predictions than humans on average, humans may sometimes have private information which an algorithm does not have access to that can improve performance. How can we help humans effectively use and adjust recommendations made by... View Details

Keywords: AI and Machine Learning; Analytics and Data Science; Forecasting and Prediction; Digital Marketing

October 2017 (Revised April 2018)
Case

Improving Worker Safety in the Era of Machine Learning (A)

By: Michael W. Toffel, Dan Levy, Jose Ramon Morales Arilla and Matthew S. Johnson

Managers make predictions all the time: How fast will my markets grow? How much inventory do I need? How intensively should I monitor my suppliers? Which potential customers will be most responsive to a particular marketing campaign? Which job candidates should I... View Details

Keywords: Machine Learning; Policy Implementation; Empirical Research; Inspection; Occupational Safety; Occupational Health; Regulation; Analysis; Forecasting and Prediction; Policy; Operations; Supply Chain Management; Safety; Manufacturing Industry; Construction Industry; United States

December 2011
Article

Stock Price Fragility

By: Robin Greenwood and David Thesmar

We investigate the relationship between ownership structure of financial assets and non-fundamental risk. We define an asset to be fragile if it is susceptible to non-fundamental trading shocks. An asset can be fragile because of concentrated ownership or because its... View Details

Keywords: Stocks; Price; Ownership; Risk and Uncertainty; Assets; System Shocks; Financial Liquidity; Forecasting and Prediction; Investment Return; Volatility; Relationships; United States

09 Dec 2019
News

Identify Great Customers from Their First Purchase

20 Mar 2017
Working Paper Summaries

Bubbles for Fama

Keywords: by Robin Greenwood, Andrei Shleifer, and Yang You

23 Sep 2017
Working Paper Summaries

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

Keywords: by Edward L. Glaeser, Hyunjin Kim, and Michael Luca

2023
Working Paper

The Limits of Algorithmic Measures of Race in Studies of Outcome Disparities

By: David S. Scharfstein and Sergey Chernenko

We show that the use of algorithms to predict race has significant limitations in measuring and understanding the sources of racial disparities in finance, economics, and other contexts. First, we derive theoretically the direction and magnitude of measurement bias in... View Details

Keywords: Racial Disparity; Paycheck Protection Program; Measurement Error; AI and Machine Learning; Race; Measurement and Metrics; Equality and Inequality; Prejudice and Bias; Forecasting and Prediction; Outcome or Result

SSRN

2008
Article

Warmth and Competence As Universal Dimensions of Social Perception: The Stereotype Content Model and the BIAS Map

By: A. J.C. Cuddy, S. T. Fiske and P. Glick

The stereotype content model (SCM) defines two fundamental dimensions of social perception, warmth and competence, predicted respectively by perceived competition and status. Combinations of warmth and competence generate distinct emotions of admiration, contempt,... View Details

Keywords: Perception; Competency and Skills; Prejudice and Bias; Emotions; Business Model; Behavior; Research; Competition; Status and Position; Cognition and Thinking; Groups and Teams

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June 2023
Case

Tractor Supply Co

By: David L. Ager and Michael A. Roberto

In February 2023, Hal Lawton, CEO of Tractor Supply Co, the largest farm and ranch retailer in the United States reflected on the company’s 70% growth between 2019 and 2022. Economists had begun to predict an economic downturn and experts were predicting softening... View Details

Keywords: COVID-19 Pandemic; Demand and Consumers; Economic Slowdown and Stagnation; Organizational Change and Adaptation; Retail Industry

22 Dec 2015
News

Algorithms Need Managers, Too

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

We show that the use of algorithms to predict race has significant limitations in measuring and understanding the sources of racial disparities in finance, economics, and other contexts. First, we derive theoretically the direction and magnitude of measurement... View Details

February 2018 (Revised December 2020)
Case

People Analytics at Teach For America (A)

By: Jeffrey T. Polzer and Julia Kelley

As of mid-2016, national nonprofit Teach For America (TFA) had struggled with three consecutive years of declining application totals, and senior management was re-examining the organization's strategy, including recruitment and selection. A few months earlier, former... View Details

Keywords: Recruitment; Selection and Staffing; Analysis; Forecasting and Prediction

April 2003 (Revised December 2006)
Case

ZARA: Fast Fashion

By: Pankaj Ghemawat and Jose Luis Nueno

Focuses on Inditex, an apparel retailer from Spain, which has set up an extremely quick response system for its ZARA chain. Instead of predicting months before a season starts what women will want to wear, ZARA observes what's selling and what's not and continuously... View Details

Keywords: Organizational Change and Adaptation; Multinational Firms and Management; Competitive Advantage; Manufacturing Industry; Apparel and Accessories Industry; Retail Industry; Spain