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  • May 2023
  • Case

CMA CGM: Reducing the Carbon Footprint of Container Shipping
By: Willy C. Shih and Emilie Billaud
Marine transport is the most cost-effective way to move large volumes over long distances, and container shipping is the backbone of international trade in goods. Yet shipping contributed 3% of worldwide greenhouse gas emissions, and the deep-sea segment, which...  View Details
Keywords: Container Shipping; Logistic Regression; Supply Chain; Trade Links; Decarbonization; Environmental Strategies; Environmental Impact; Globalization; Trade; Environmental Regulation; Shipping Industry; European Union; Asia; North America
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  • 2023
  • Article

Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators
By: Benjamin Jakubowski, Siram Somanchi, Edward McFowland III and Daniel B. Neill
Regression discontinuity (RD) designs are widely used to estimate causal effects in the absence of a randomized experiment. However, standard approaches to RD analysis face two significant limitations. First, they require a priori knowledge of discontinuities in...  View Details
Keywords: Regression Discontinuity Design; Analytics and Data Science; AI and Machine Learning
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  • March–April 2023
  • Article

Market Segmentation Trees
By: Ali Aouad, Adam Elmachtoub, Kris J. Ferreira and Ryan McNellis
Problem definition: We seek to provide an interpretable framework for segmenting users in a population for personalized decision making. Methodology/results: We propose a general methodology, market segmentation trees (MSTs), for learning market...  View Details
Keywords: Decision Trees; Computational Advertising; Market Segmentation; Analytics and Data Science; E-commerce; Consumer Behavior; Marketplace Matching; Marketing Channels; Digital Marketing
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  • 2022
  • Article

Becoming a Learning Organization While Enhancing Performance: The Case of LEGO
By: Thomas Borup Kristensen, Henrik Saabye and Amy Edmondson
Purpose - The purpose of this study is to empirically test how problem-solving lean practices, along with leaders as learning facilitators in an action learning approach, can be transferred from a production context to a knowledge work context for the purpose...  View Details
Keywords: Performance Efficiency; Learning; Organizational Change and Adaptation
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  • 2022
  • Working Paper

Coordination and Incumbency Advantage in Multi-Party Systems: Evidence from French Elections
By: Kevin Dano, Francesco Ferlenga, Vincenzo Galasso, Caroline Le Pennec and Vincent Pons
In theory, free and fair elections can improve the selection of politicians and incentivize them to exert effort. In practice, incumbency advantage and coordination issues may lead to the (re)election of bad politicians. We ask whether these two forces compound each...  View Details
Keywords: Political Parties; Incumbent Politicians; Democracy; Political Elections; Competitive Advantage
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  • September 2022
  • Article

The Impact of Financial Assistance Programs on Health Care Utilization: Evidence from Kaiser Permanente
By: Alyce S. Adams, Raymond Kluender, Neale Mahoney, Jinglin Wang, Francis Wong and Wesley Yin
Most hospitals have financial assistance programs for low-income patients. We use administrative data from Kaiser Permanente to study the effects of financial assistance on health care utilization. Using a regression discontinuity design based on an income threshold...  View Details
Keywords: Healthcare; Utilization; Financial Assistance; Health Care and Treatment; Social Issues; Poverty; Health Industry
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  • 2022
  • Article

Nonparametric Subset Scanning for Detection of Heteroscedasticity
By: Charles R. Doss and Edward McFowland III
We propose Heteroscedastic Subset Scan (HSS), a novel method for identifying covariates that are responsible for violations of the homoscedasticity assumption in regression settings. Viewing the problem as one of anomalous pattern detection, we use subset scanning...  View Details
Keywords: Scan Statistics; Anomaly Detection; Regression; Model Diagnostics
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  • 2022
  • Working Paper

Innovation on Wings: Nonstop Flights and Firm Innovation in the Global Context
By: Dany Bahar, Prithwiraj Choudhury, Do Yoon Kim and Wesley W. Koo
We study whether, when, and how better connectivity through nonstop flights leads to positive innovation outcomes for firms in the global context. Using unique data of all flights emanating from 5,015 airports around the globe from 2005 to 2015 and exploiting a...  View Details
Keywords: Nonstop Flights; Collaborative Innovation and Invention; Patents; Research and Development; Air Transportation Industry
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  • 2022
  • Working Paper

Machine Learning Models for Prediction of Scope 3 Carbon Emissions
By: George Serafeim and Gladys Vélez Caicedo
For most organizations, the vast amount of carbon emissions occur in their supply chain and in the post-sale processing, usage, and end of life treatment of a product, collectively labelled scope 3 emissions. In this paper, we train machine learning algorithms on 15...  View Details
Keywords: Carbon Emissions; Climate Change; Environment; Carbon Accounting; Machine Learning; Artificial Intelligence; Digital; Data Science; Environmental Sustainability; Environmental Management; Environmental Accounting
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  • May 2022
  • Supplement

Regression Exercises
By: David E. Bell
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  • May 2022
  • Exercise

Regression Exercises
By: David E. Bell
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  • May 2022
  • Article

Complex Disclosure
By: Ginger Zhe Jin, Michael Luca and Daniel Martin
We present evidence that unnecessarily complex disclosure can result from strategic incentives to shroud information. In our lab experiment, senders are required to report their private information truthfully, but can choose how complex to make their reports. We find...  View Details
Keywords: Disclosure; Experiments; Naiveté; Overconfidence; Corporate Disclosure; Policy; Information; Complexity; Strategy; Consumer Behavior
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  • Article

How Much Should We Trust Staggered Difference-In-Differences Estimates?
By: Andrew C. Baker, David F. Larcker and Charles C.Y. Wang
We explain when and how staggered difference-in-differences regression estimators, commonly applied to assess the impact of policy changes, are biased. These biases are likely to be relevant for a large portion of research settings in finance, accounting, and law that...  View Details
Keywords: Difference In Differences; Staggered Difference-in-differences Designs; Generalized Difference-in-differences; Dynamic Treatment Effects; Mathematical Methods
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  • March 2022 (Revised July 2022)
  • Module 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
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  • March 2022 (Revised July 2022)
  • Module Note

Prediction & Machine Learning
By: Iavor I. Bojinov, Michael Parzen and Paul Hamilton
This note provides an introduction to machine learning for an introductory data science course. The note begins with a description of supervised, unsupervised, and reinforcement learning. Then, the note provides a brief explanation of the difference between traditional...  View Details
Keywords: Machine Learning; Data Science; Learning; Analytics and Data Science; Performance Evaluation
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  • March 2022
  • Article

Assessing the Impact of the COVID-19 Pandemic on Clinician Ambulatory Electronic Health Record Use
By: A Jay Holmgren, Lance Downing, Mitchell Tang, Christopher Sharp, Christopher Longhurst and Robert S. Huckman
Objective: The COVID-19 pandemic changed clinician electronic health record (EHR) work in a multitude of ways. To evaluate how, we measure ambulatory clinician EHR use in the United States throughout the COVID-19 pandemic.

Materials and Methods: We use EHR...  View Details
Keywords: Health Care; Electronic Health Records; Productivity; COVID-19 Pandemic; Health Care and Treatment; Health Pandemics; Information Technology; Performance Productivity; United States
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  • 2022
  • Working Paper

Electoral Turnovers
By: Benjamin Marx, Vincent Pons and Vincent Rollet
In most national elections, voters face a key choice between continuity and change. Electoral turnovers occur when the incumbent candidate or party fails to win reelection. To understand how turnovers affect national outcomes, we study the universe of presidential and...  View Details
Keywords: Election Outcomes; Regression Discontinuity Design; Political Elections; Change; Global Range; Outcome or Result; Economy; Governance; Performance Improvement
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  • February 2022
  • Article

Sugar-sweetened Beverage Purchases and Intake at Event Arenas with and without a Portion Size Cap
By: Sheri Volger, James Scott Parrott, Brian Elbel, Leslie K. John, Jason P. Block, Pamela Rothpletz-Puglia and Christina A. Roberto
This is the first real-world study to examine the association between a voluntary 16-ounce (oz.) portion-size cap on sugar-sweetened beverages (SSB) at a sporting arena on volume of SSBs and food calories purchased and consumed during basketball games. Cross-sectional...  View Details
Keywords: Sugar-sweetened Beverages; Nutrition Policy; Obesity Prevention; Portion Sizes; Nutrition; Policy; Health; Behavior
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  • 2022
  • Working Paper

The Impact of Campaign Finance Rules on Candidate Selection and Electoral Outcomes: Evidence from France
By: Nikolaj Broberg, Vincent Pons and Clémence Tricaud
This paper investigates the effects of campaign finance rules on electoral outcomes. In French departmental and municipal elections, candidates competing in districts above 9,000 inhabitants face spending limits and are eligible for public reimbursement if they obtain...  View Details
Keywords: Political Elections; Finance; Governing Rules, Regulations, and Reforms; Outcome or Result; France
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  • January–February 2022
  • Article

Operational Disruptions, Firm Risk, and Control Systems
By: William Schmidt and Ananth Raman
Operational disruptions can impact a firm's risk, which manifests in a host of operational issues, including a higher holding cost for inventory, a higher financing cost for capacity expansion, and a higher perception of the firm's risk among its supply chain partners....  View Details
Keywords: Operational Risk; Operational Disruptions; Information Asymmetry; Control Systems; Operations; Disruption; Risk Management
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