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March 2022 (Revised May 2022)
Case

Winning Business at Russell Reynolds (A)

By: Ethan Bernstein and Cara Mazzucco

In an effort to make compensation drive collaboration, Russell Reynolds Associates’ (RRA) CEO Clarke Murphy sought to re-engineer the bonus system for his executive search consultants in 2016. As his HR analytics guru, Kelly Smith, points out, that risks upsetting–and... View Details

March 2022
Supplement

Winning Business at Russell Reynolds (B)

By: Ethan Bernstein and Cara Mazzucco

In an effort to make compensation drive collaboration, Russell Reynolds Associates’ (RRA) CEO Clarke Murphy sought to re-engineer the bonus system for his executive search consultants in 2016. As his HR analytics guru, Kelly Smith, points out, that risks upsetting–and... View Details

March 2022
Article

Where to Locate COVID-19 Mass Vaccination Facilities?

By: Dimitris Bertsimas, Vassilis Digalakis Jr, Alexander Jacquillat, Michael Lingzhi Li and Alessandro Previero

The outbreak of COVID-19 led to a record-breaking race to develop a vaccine. However, the limited vaccine capacity creates another massive challenge: how to distribute vaccines to mitigate the near-end impact of the pandemic? In the United States in particular, the new... View Details

Keywords: Vaccines; COVID-19; Health Care and Treatment; Health Pandemics; Performance Effectiveness; Analytics and Data Science; Mathematical Methods

February 2022 (Revised January 2024)
Supplement

Winning Business at Russell Reynolds (C)

By: Ethan Bernstein and Cara Mazzucco

In an effort to make compensation drive collaboration, Russell Reynolds Associates’ (RRA) CEO Clarke Murphy sought to re-engineer the bonus system for his executive search consultants in 2016. As his HR analytics guru, Kelly Smith, points out, that risks upsetting—and... View Details

Keywords: Restructuring; Talent and Talent Management; Compensation and Benefits; Growth and Development Strategy; Organizational Change and Adaptation; Organizational Culture; Performance Evaluation; Motivation and Incentives; Consulting Industry

October 1, 2021
Article

An Evaluation of Cross-efficiency Methods: With an Application to Warehouse Performance.

By: B.M. Balk, M.R. De Koster, Christian Kaps and J.L. Zofio

Cross-efficiency measurement is an extension of Data Envelopment Analysis that allows for tie-breaking ranking of the Decision Making Units (DMUs) using all the peer evaluations. In this article we examine the theory of cross-efficiency measurement by comparing a... View Details

Keywords: Efficiency Analysis; Performance Benchmarking; Warehousing; Analytics and Data Science; Performance Evaluation; Measurement and Metrics; Mathematical Methods

October 2021
Article

Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach

By: Nicolas Padilla and Eva Ascarza

The success of Customer Relationship Management (CRM) programs ultimately depends on the firm's ability to understand consumers' preferences and precisely capture how these preferences may differ across customers. Only by understanding customer heterogeneity, firms can... View Details

Keywords: Customer Management; Targeting; Deep Exponential Families; Probabilistic Machine Learning; Cold Start Problem; Customer Relationship Management; Programs; Consumer Behavior; Analysis

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August 2021
Article

Multiple Imputation Using Gaussian Copulas

By: F.M. Hollenbach, I. Bojinov, S. Minhas, N.W. Metternich, M.D. Ward and A. Volfovsky

Missing observations are pervasive throughout empirical research, especially in the social sciences. Despite multiple approaches to dealing adequately with missing data, many scholars still fail to address this vital issue. In this paper, we present a simple-to-use... View Details

Keywords: Missing Data; Bayesian Statistics; Imputation; Categorical Data; Estimation

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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

March 2021
Article

Bayesian Signatures of Confidence and Central Tendency in Perceptual Judgment

By: Yang Xiang, Thomas Graeber, Benjamin Enke and Samuel Gershman

This paper theoretically and empirically investigates the role of Bayesian noisy cognition in perceptual judgment, focusing on the central tendency effect: the well-known empirical regularity that perceptual judgments are biased towards the center of the... View Details

Keywords: Visual Perception; Bayesian Modeling; Perception; Judgments

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February 2021
Case

Digital Manufacturing at Amgen

By: Shane Greenstein, Kyle R. Myers and Sarah Mehta

This case discusses efforts made by biotechnology (biotech) company Amgen to introduce digital technologies into its manufacturing processes. Doing so is complicated by the fact that the process for manufacturing biologics—or therapeutics made from living cells—is... View Details

January 2021
Article

Machine Learning for Pattern Discovery in Management Research

By: Prithwiraj Choudhury, Ryan Allen and Michael G. Endres

Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used for exploratory inductive or abductive research, or for post-hoc analysis of regression results to detect... View Details

Keywords: Machine Learning; Supervised Machine Learning; Induction; Abduction; Exploratory Data Analysis; Pattern Discovery; Decision Trees; Random Forests; Neural Networks; ROC Curve; Confusion Matrix; Partial Dependence Plots; AI and Machine Learning

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November 2020
Article

Disrupting the Disruptors or Enhancing Them? How Blockchain Re‐Shapes Two‐Sided Platforms

By: Daniel Trabucchi, Antonella Moretto, Tommaso Buganza and Alan MacCormack

The importance of platform‐based businesses in the modern economy is growing continuously and becoming increasingly relevant. Specifically, the deployment of digital technologies has enhanced the applicability of two‐sided business models, enabling companies to act not... View Details

Keywords: Blockchain; Two-Sided Platforms; Business Model; Innovation and Invention; Technological Innovation

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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

June 2020 (Revised May 2022)
Case

Vanguard Retail Operations (A)

By: Willy C. Shih and Antonio Moreno

The first two cases in this series are set in the financial services industry, and explore whether it is better for back-office workers to be generalists who provide the flexibility of being able to handle the complete range of transactions that the company faces or... View Details

Keywords: Pooling; Generalist Model; Specialist Model; Operations; Service Operations; Management; Job Design and Levels; Financial Services Industry; United States

June 2020 (Revised August 2020)
Supplement

Vanguard Retail Operations (B)

By: Willy C. Shih and Antonio Moreno

The first two cases in this series are set in the financial services industry, and explore whether it is better for back-office workers to be generalists who provide the flexibility of being able to handle the complete range of transactions that the company faces or... View Details

Keywords: Pooling; Generalist Model; Specialist Model; Service Operations; Management; Financial Services Industry; United States

26 Apr 2020
Other Presentation

Towards Modeling the Variability of Human Attention

By: Kuno Kim, Megumi Sano, Julian De Freitas, Daniel Yamins and Nick Haber

Children exhibit extraordinary exploratory behaviors hypothesized to contribute to the building of models of their world. Harnessing this capacity in artificial systems promises not only more flexible technology but also cognitive models of the developmental processes... View Details

Keywords: Exploratory Learning Behaviors; Modeling; Artificial Intelligence; AI and Machine Learning

2020
Conference Presentation

Towards Modeling the Developmental Variability of Human Attention

By: K-H Kim, M. Sano, J. De Freitas, N. Haber and D. L. K. Yamins

March 2020
Article

Diagnosing Missing Always at Random in Multivariate Data

By: Iavor I. Bojinov, Natesh S. Pillai and Donald B. Rubin

Models for analyzing multivariate data sets with missing values require strong, often assessable, assumptions. The most common of these is that the mechanism that created the missing data is ignorable—a twofold assumption dependent on the mode of inference. The first... View Details

Keywords: Missing Data; Diagnostic Tools; Sensitivity Analysis; Hypothesis Testing; Missing At Random; Row Exchangeability; Analytics and Data Science; Mathematical Methods

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2020
Working Paper

Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach

By: Eva Ascarza

The success of Customer Relationship Management (CRM) programs ultimately depends on the firm's ability to understand consumers' preferences and precisely capture how these preferences may differ across customers. Only by understanding customer heterogeneity, firms can... View Details

Keywords: Customer Management; Targeting; Deep Exponential Families; Probabilistic Machine Learning; Cold Start Problem; Customer Relationship Management; Customer Value and Value Chain; Consumer Behavior; Analytics and Data Science; Mathematical Methods; Retail Industry

2020
Working Paper

Machine Learning for Pattern Discovery in Management Research

By: Prithwiraj Choudhury

Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used as an observation for further inductive or abductive research, but should not be treated as the result of a... View Details

Keywords: Machine Learning; Theory Building; Induction; Decision Trees; Random Forests; K-nearest Neighbors; Neural Network; P-hacking; Analytics and Data Science; Analysis

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