Publications

2021
Working Paper

An Empirical Study of Time Allotment and Delays in E-commerce Delivery

By: M. Balakrishnan, MoonSoo Choi and Natalie Epstein

Problem definition: We study how having more time allotted to deliver an order affects the speed of the delivery process. Furthermore, we seek to predict orders that are likely to be delayed early in the delivery process so that actions can be taken to avoid delays.... View Details

Keywords: Logistics; E-commerce; Mathematical Methods; AI and Machine Learning; Performance Productivity

SSRN

2024
Working Paper

Igniting Innovation: Evidence from PyTorch on Technology Control in Open Collaboration

By: Daniel Yue and Frank Nagle

Many companies offer free access to their technology to encourage outside addon innovation, hoping to later profit by raising prices or harnessing the power of the crowd while continuing to steer the direction of innovation. They can achieve this balance by opening... View Details

Keywords: Technological Innovation; Power and Influence; Collaborative Innovation and Invention; Corporate Governance

An emerging form of remote work allows employees to work‐from‐anywhere, so that the worker can choose to live in a preferred geographic location. While traditional work‐from‐home (WFH) programs offer the worker temporal flexibility,... View Details

June 2024
Article

Oral History and Business History in Emerging Markets

By: Geoffrey Jones

This article describes the motivation, structure and use of the Creating Emerging Markets (CEM) oral history-based project at the Harvard Business School. The project consists of lengthy interviews with business leaders from emerging markets. By June 2024 183... View Details

Keywords: Emerging Economies; Oral History; Emerging Markets; Business History; Research

September–October 2023
Article

Reskilling in the Age of AI

By: Jorge Tamayo, Leila Doumi, Sagar Goel, Orsolya Kovács-Ondrejkovic and Raffaella Sadun

In the coming decades, as the pace of technological change continues to increase, millions of workers may need to be not just upskilled but reskilled—a profoundly complex societal challenge that will sometimes require workers to both acquire new skills and... View Details

Keywords: Competency and Skills; AI and Machine Learning; Training; Adaptation; Employees; Digital Transformation

Register to Read

2020
Working Paper

Design in the Age of Artificial Intelligence

By: Roberto Verganti, Luca Vendraminelli and Marco Iansiti

Artificial Intelligence (AI) is affecting the scenario in which innovation takes place. What are the implications for our understanding of design? Is AI just another digital technology that, akin to many others, will not significantly question what we know about... View Details

Keywords: Artificial Intelligence; Design Thinking; Technological Innovation; Design; Change; Theory; AI and Machine Learning

22 Oct 2007
Research & Ideas

Bringing ‘Lean’ Principles to Service Industries

own." Unfortunately, lean's prevalence has led to some misconceptions. "Some people think lean means 'not fat,' as in laying people off," Upton says, noting that in their paper they propose that the difference in a lean operating system comes from how it... View Details

Keywords: by Julia Hanna; Computer

Program

Competing in the Age of AI—Virtual

will delve into diverse applications of AI, machine learning, predictive modeling, and data science; explore network effects and platform strategies; and learn how to build an AI factory that enables your... View Details

2020
Book

Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World

By: Marco Iansiti and Karim R. Lakhani

In industry after industry, data, analytics, and AI-driven processes are transforming the nature of work. While we often still treat AI as the domain of a specific skill, business function, or sector, we have entered a new era in which AI is challenging the very... View Details

Keywords: Artificial Intelligence; Technological Innovation; Change; Competition; Strategy; Leadership; Business Processes; Organizational Change and Adaptation; AI and Machine Learning

Purchase

An inherent risk of algorithmic personalization is disproportionate targeting of individuals from certain groups (or demographic characteristics such as gender or race), even when the decision maker does not intend to discriminate based on those... View Details

2023
Other Article

The Harvard USPTO Patent Dataset: A Large-Scale, Well-Structured, and Multi-Purpose Corpus of Patent Applications

By: Mirac Suzgun, Luke Melas-Kyriazi, Suproteem K. Sarkar, Scott Duke Kominers and Stuart Shieber

Innovation is a major driver of economic and social development, and information about many kinds of innovation is embedded in semi-structured data from patents and patent applications. Though the impact and novelty of innovations expressed in patent data are difficult... View Details

Keywords: USPTO; Natural Language Processing; Classification; Summarization; Patent Novelty; Patent Trolls; Patent Enforceability; Patents; Innovation and Invention; Intellectual Property; AI and Machine Learning; Analytics and Data Science

08 Mar 2011
First Look

First Look: March 8

relocate to Japan and compete with other world-class international business schools. Purchase this case:http://cb.hbsp.harvard.edu/cb/product/811061-PDF-ENG The Wright Brothers and Their Flying Machines Tom Nicholas and David ChenHarvard... View Details

Keywords: Sean Silverthorne

Article

Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)

By: Eva Ascarza and Ayelet Israeli

An inherent risk of algorithmic personalization is disproportionate targeting of individuals from certain groups (or demographic characteristics such as gender or race), even when the decision maker does not intend to discriminate based on those “protected”... View Details

Keywords: Algorithm Bias; Personalization; Targeting; Generalized Random Forests (GRF); Discrimination; Customization and Personalization; Decision Making; Fairness; Mathematical Methods

September 2023 (Revised April 2024)
Case

Atomwise: Strategic Opportunities in AI for Pharma

By: Satish Tadikonda

Abraham Heifets and his co-founder, Izhar Wallach, had founded Atomwise to develop i) an AI engine to transform drug discovery by creating better medicines faster, and ii) a machine learning-based discovery engine that combined the power of convolutional neural... View Details

Keywords: Business Model; Business Startups; AI and Machine Learning; Science-Based Business; Technological Innovation; Biotechnology Industry; Pharmaceutical Industry

Educators

Purchase

Winter 2016
Article

Analytics for an Online Retailer: Demand Forecasting and Price Optimization

By: Kris J. Ferreira, Bin Hong Alex Lee and David Simchi-Levi

We present our work with an online retailer, Rue La La, as an example of how a retailer can use its wealth of data to optimize pricing decisions on a daily basis. Rue La La is in the online fashion sample sales industry, where they offer extremely limited-time... View Details

Keywords: Internet and the Web; Price; Forecasting and Prediction; Revenue; Sales; Retail Industry

Web

Publications - Faculty & Research

Semiconductors ; Change Management ; Transformation ; Decision Making ; Globalized Markets and Industries ; Government and Politics ; AI and Machine Learning ; Innovation and Management ; Innovation Strategy... View Details

2019
Book

Fintech, Small Business & the American Dream: How Technology Is Transforming Lending and Shaping a New Era of Small Business Opportunity

By: Karen G. Mills

Fintech, Small Business & the American Dream describes the needs of small businesses for capital and demonstrates how technology—novel data sources, artificial intelligence, machine learning—will transform the small business lending market. This market has been... View Details