Publications

2018
Working Paper

Forecasting Airport Transfer Passenger Flow Using Real-Time Data and Machine Learning

By: Xiaojia Guo, Yael Grushka-Cockayne and Bert De Reyck

Problem definition: In collaboration with Heathrow Airport, we develop a predictive system that generates quantile forecasts of transfer passengers’ connection times. Sampling from the distribution of individual passengers’ connection times, the system also produces... View Details

Keywords: Quantile Forecasts; Regression Tree; Copula; Passenger Flow Management; Data-driven Operations; Forecasting and Prediction; Data and Data Sets

SSRN

July–August 2018
Article

How CEOs Manage Time

By: Michael E. Porter and Nitin Nohria

In 2006 Harvard Business School’s Michael E. Porter and Nitin Nohria launched a study tracking how large companies’ CEOs spent their time, 24/7, for 13 weeks: where they were, with whom, what they did, and what they were focusing on. To date, Porter and Nohria have... View Details

Keywords: CEOs; Executives; Time Management; Attitudes; Managerial Roles; Leadership; Performance Effectiveness; Strategy; Decision Making; Organizational Culture

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21 Aug 2017
Lessons from the Classroom

Companies Love Big Data But Lack the Strategy To Use It Effectively

Source: peterhowell Big data has shifted the ground under every business, enough so that many managers are waking up to the fact that they are already behind in developing a smart View Details

Keywords: by Dina Gerdeman

2019
Article

Does Big Data Enhance Firm Innovation Competency? The Mediating Role of Data-driven Insights

By: Maryam Ghasemaghaei and Goran Calic

Grounded in gestalt insight learning theory and organizational learning theory, we collected data from 280 middle and top-level managers to investigate the impact of each big data characteristic (i.e., data volume, data velocity, data variety, and data veracity) on... View Details

Keywords: Analytics and Data Science; Innovation and Invention; Learning

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19 Dec 2023
Research & Ideas

$15 Billion in Five Years: What Data Tells Us About MacKenzie Scott’s Philanthropy

of gifts over time. So many in the nonprofit and philanthropy world wondered how Scott’s nonconforming principles would be expressed in her actual giving. Scott, whose net worth has been estimated to top $40 billion, established the organization Yield Giving in 2022 to... View Details

Keywords: by Matthew Lee, Brian Trelstad, and Ethan Tran

Article

Channel Integration, Sales Dispersion, and Inventory Management

By: Santiago Gallino, Antonio Moreno and Ioannis Stamatopoulos

We study the effects of the introduction of cross-channel functionalities on the overall sales dispersion of retailers and the implications of these effects for inventory management. To do that, we analyze data from a leading U.S. retailer who introduced a... View Details

Keywords: Retail Operations; Online Retail; Channel Integration; Sales Dispersion; Long Tail; Empirical Operations; Inventory Management; Omnichannel Retail; Marketing Channels; Integration; Sales; Logistics; Operations; Management; Retail Industry

01 Dec 1999
News

EMC's Ruettgers Finds Gold in Data Storage

noted, EMC has spent some $1 billion during the 1990s developing its own software for data storage and retrieval. Emphasis on R&D and quality control has been a key to EMC's success. But Ruettgers, often noted for making brilliant... View Details

Web

Statistical & Data Services - Research Computing Services

About Us Statistical & Data Services 3ms Research Computing Services (RCS) provides statistical and data services for the HBS research community, including consultations and expertise in: Advanced... View Details

Service Productivity Management

Here is an in-depth guide to the most powerful available benchmarking technique for improving service organization performance — Data Envelopment Analysis (DEA). The book outlines DEA as a benchmarking technique, identifies high cost service units, isolates... View Details

April 2015
Case

Carolinas HealthCare System: Consumer Analytics

By: John A. Quelch and Margaret L. Rodriguez

In 2014, Dr. Michael Dulin, chief clinical officer for analytics and outcomes research and head of the Dickson Advanced Analytics (DA2) group at Carolinas HealthCare System (CHS), successfully unified all analytics talent and resources into one group over a three year... View Details

Keywords: Consumer Segmentation; Big Data; Management Information Systems; Hospital Management; Health Care and Treatment; Marketing; Segmentation; Analytics and Data Science; Information Management; Information Technology; Health; Health Industry; United States

Educators

June 2020
Article

Real-time Data from Mobile Platforms to Evaluate Sustainable Transportation Infrastructure

By: Omar Isaac Asensio, Kevin Alvarez, Arielle Dror, Emerson Wenzel, Catharina Hollauer and Sooji Ha

By displacing gasoline and diesel fuels, electric cars and fleets reduce emissions from the transportation sector, thus offering important public health benefits. However, public confidence in the reliability of charging infrastructure remains a fundamental barrier to... View Details

Keywords: Environmental Sustainability; Transportation; Infrastructure; Behavior; AI and Machine Learning; Demand and Consumers

12 Apr 2022
Research & Ideas

Swiping Right: How Data Helped This Online Dating Site Make More Matches

Evidence from a Randomized Field Experiment. McFowland coauthored the paper with Jui Ramaprasad of the University of Maryland, Ravi Bapna of the University of Minnesota, Probal Mojumdar of Indian Institute of Management Udaipur, and... View Details

Keywords: by Kara Baskin

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

Teaching Interest

Overview

Paul is primarily interested in teaching data science to management students through the case method. This includes technical topics (programming and statistics) as well as higher-level management issues (digital transformation, data governance, etc.) As a research... View Details

Keywords: A/B Testing; AI; AI Algorithms; AI Creativity; Algorithm; Algorithm Bias; Algorithmic Bias; Algorithmic Fairness; Algorithms; Analytics; Application Program Interface; Artificial Intelligence; Causality; Causal Inference; Computing; Computers; Data Analysis; Data Analytics; Data Architecture; Data As A Service; Data Centers; Data Governance; Data Labeling; Data Management; Data Manipulation; Data Mining; Data Ownership; Data Privacy; Data Protection; Data Science; Data Science And Analytics Management; Data Scientists; Data Security; Data Sharing; Data Strategy; Data Visualization; Database; Data-driven Decision-making; Data-driven Management; Data-driven Operations; Datathon; Economics Of AI; Economics Of Innovation; Economics Of Information System; Economics Of Science; Forecast; Forecast Accuracy; Forecasting; Forecasting And Prediction; Information Technology; Machine Learning; Machine Learning Models; Prediction; Prediction Error; Predictive Analytics; Predictive Models; Analysis; AI and Machine Learning; Analytics and Data Science; Applications and Software; Digital Transformation; Information Management; Digital Strategy; Technology Adoption

2004
Teaching Note

Learning to Manage with Data in Duval County Public Schools: Lake Shore Middle School (A) and (B) Case Series, Teaching Note

By: Allen Grossman, James P. Honan and Caroline Joan King

Keywords: Middle School Education; Management Skills; Florida

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