Machinery and Machining - Publications - Faculty & Research - Harvard Business School

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October–December 2022
Article

Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem

By: Mochen Yang, Edward McFowland III, Gordon Burtch and Gediminas Adomavicius

Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data, followed... View Details

Keywords: Machine Learning; Econometric Analysis; Instrumental Variable; Random Forest; Causal Inference; AI and Machine Learning; Forecasting and Prediction

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November 2022
Article

A Language-Based Method for Assessing Symbolic Boundary Maintenance between Social Groups

By: Anjali M. Bhatt, Amir Goldberg and Sameer B. Srivastava

When the social boundaries between groups are breached, the tendency for people to erect and maintain symbolic boundaries intensifies. Drawing on extant perspectives on boundary maintenance, we distinguish between two strategies that people pursue in maintaining... View Details

Keywords: Culture; Machine Learning; Natural Language Processing; Symbolic Boundaries; Organizations; Boundaries; Social Psychology; Interpersonal Communication; Organizational Culture

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October 2023 (Revised June 2024)
Case

ReUp Education: Can AI Help Learners Return to College?

By: Kris Ferreira, Christopher Thomas Ryan and Sarah Mehta

Founded in 2015, ReUp Education helps “stopped out students”—learners who have stopped making progress towards graduation—achieve their college completion goals. The company relies on a team of success coaches to engage with learners and help them reenroll. In 2019,... View Details

Keywords: AI; Algorithms; Machine Learning; Edtech; Education Technology; Analysis; Higher Education; AI and Machine Learning; Customization and Personalization; Failure; Education Industry; Technology Industry; United States

May 2007
Article

Capital Flows and Capital Goods

By: Laura Alfaro and Eliza Hammel

Studying the relation between equity market liberalization and imports of capital goods, we examine one channel through which international financial integration can promote growth. For the period 1980–1997, we find that after controlling for other policies and... View Details

Keywords: Cash Flow; Equity; Financial Markets; Economy; Distribution Channels; Machinery and Machining; Capital

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December 2020
Case

VIA Science (A)

By: Juan Alcácer, Rembrand Koning, Annelena Lobb and Kerry Herman

Via (a) captures the early days of the data analytics startup as founders Gounden and Ravanis considered which markets offer the right opportunities for their firm and what kinds of experiments will help them narrow their choice. Supplement Via (b) reveals the... View Details

Keywords: Data Analytics; Machine Learning; Artificial Intelligence; Strategy; Business Startups; Markets; AI and Machine Learning; Telecommunications Industry; Utilities Industry; United States; Japan

Teaching Interest

Empirical Technology and Operations Management Course

By: Himabindu Lakkaraju

I taught a set of lectures on "Introduction to Machine Learning for Social Scientists" as part of this required course for first year PhD students. This module familiarizes students with all the basic concepts in machine learning, their implementations, as well as the... View Details

July 2019 (Revised November 2019)
Case

Osaro: Picking the Best Path

By: William R. Kerr, James Palano and Bastiane Huang

The founder of Osaro saw the potential of deep reinforcement learning to allow robots to be applied to new applications. Osaro targeted warehousing, already a dynamic industry for robotics and automation, for its initial product—a system which would allow robotic arms... View Details

December 2020
Supplement

VIA Science (B)

By: Juan Alcácer, Rembrand Koning, Annelena Lobb and Kerry Herman

Via (a) captures the early days of the data analytics startup as founders Gounden and Ravanis considered which markets offer the right opportunities for their firm and what kinds of experiments will help them narrow their choice. Supplement Via (b) reveals the... View Details

Keywords: Data Analytics; Machine Learning; Artificial Intelligence; Strategy; Business Startups; AI and Machine Learning; Telecommunications Industry; Utilities Industry; United States; Japan

Article

Oracle Efficient Private Non-Convex Optimization

By: Seth Neel, Aaron Leon Roth, Giuseppe Vietri and Zhiwei Steven Wu

One of the most effective algorithms for differentially private learning and optimization is objective perturbation. This technique augments a given optimization problem (e.g. deriving from an ERM problem) with a random linear term, and then exactly solves it.... View Details

Keywords: Machine Learning; Algorithms; Objective Perturbation; Mathematical Methods

Article

Counterfactual Explanations Can Be Manipulated

By: Dylan Slack, Sophie Hilgard, Himabindu Lakkaraju and Sameer Singh

Counterfactual explanations are useful for both generating recourse and auditing fairness between groups. We seek to understand whether adversaries can manipulate counterfactual explanations in an algorithmic recourse setting: if counterfactual explanations indicate... View Details

Keywords: Machine Learning Models; Counterfactual Explanations

August 2018 (Revised October 2020)
Case

Tailor Brands: Artificial Intelligence-Driven Branding

Using proprietary artificial intelligence technology, startup Tailor Brands set out to democratize branding by allowing small businesses to create their brand identities by automatically generating logos in just minutes at minimal cost with no branding or design skills... View Details

September 2020 (Revised March 2022)
Case

JOANN: Joannalytics Inventory Allocation Tool

By: Kris Ferreira and Srikanth Jagabathula

Michael Joyce, Vice President of Inventory Management at JOANN, championed an effort to develop and implement an inventory allocation analytics tool that used advanced analytics to predict in-season demand of seasonal items for each of JOANN’s nearly 900 stores and... View Details

Keywords: Analytics; Machine Learning; Optimization; Inventory Management; Mathematical Methods; Decision Making; Operations; Supply Chain Management; Resource Allocation; Distribution; Technology Adoption; Applications and Software; Change Management; Fashion Industry; Consumer Products Industry; Retail Industry; United States; Ohio

March 1985 (Revised November 1985)
Case

Wilmington Tap and Die

By: Robert S. Kaplan

The general manager of a division manufacturing taps and dies must decide whether to continue a major capital investment program. The program was designed to replace aging mechanical machines with modern, electronically controlled equipment. A post-audit, after an... View Details

Keywords: Capital Budgeting; Investment; Accounting Audits; Cost Management; Technological Innovation; Information Technology; Performance Productivity; Production; Management Analysis, Tools, and Techniques; Manufacturing Industry

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2017
Working Paper

The Need for Speed: Effects of Uncertainty Reduction in Patenting

By: Mike Horia Teodorescu

Patents are essential in commerce to establish property rights for ideas and to give equal protection to firms that develop new technologies. Young firms especially depend on the protection of intellectual property to bring a product from concept to market. However,... View Details

Keywords: Startups; Natural Language Processing; Machine Learning; Patents; Business Startups; Risk and Uncertainty; Outcome or Result; Green Technology Industry

Spring 2021
Article

Corporate Resilience and Response During COVID-19

By: Alex Cheema-Fox, Bridget LaPerla, George Serafeim and Hui (Stacie) Wang

The coronavirus pandemic caused a sharp market decline while raising heterogeneous responses across companies related to their employees, supply chain, and repurposing of operations to provide needed products and services. We study whether during the 2020 COVID-19... View Details

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2021
Working Paper

First Law of Motion: Influencer Video Advertising on TikTok

By: Jeremy Yang, Juanjuan Zhang and Yuhan Zhang

This paper engineers an intuitive feature that is predictive of the causal effect of influencer video advertising on product sales. We propose the concept of m-score, a summary statistic that captures the extent to which a product is advertised in the most engaging... View Details

Keywords: Influencer Advertising; Video Advertising; Computer Vision; Machine Learning; Advertising; Online Technology

April 1996
Case

Southern Pulp and Paper

A paper mill's paper machines are a bottleneck in the operation. The causes include poor scheduling, lack of investment, and ineffective process control. The plant manager is charged with improving this situation fairly rapidly and has a number of proposals for change... View Details

Keywords: Information Infrastructure; Performance Improvement; Infrastructure; Pulp and Paper Industry

February 2018
Article

Retention Futility: Targeting High-Risk Customers Might Be Ineffective.

By: Eva Ascarza

Companies in a variety of sectors are increasingly managing customer churn proactively, generally by detecting customers at the highest risk of churning and targeting retention efforts towards them. While there is a vast literature on developing churn prediction models... View Details

Keywords: Retention/churn; Proactive Churn Management; Field Experiments; Heterogeneous Treatment Effect; Machine Learning; Customer Relationship Management; Risk Management

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February 2018
Case

Amazon, Google, and Apple: Smart Speakers and the Battle for the Connected Home

By: Rajiv Lal and Scott Johnson

Amazon, Google, and Apple all offer their own smart speaker. The devices represent each firm's entry point into the connected home market. All three companies come into the space with their own strengths and weaknesses. Who will win? View Details

January 2018 (Revised February 2023)
Teaching Note

The Future of Patent Examination at the USPTO

By: Prithwiraj Choudhury

This teaching note pairs with the case entitled: “The Future of Patent Examination at the USPTO” (case no. 617-027). View Details

Keywords: Machine Learning; Telework; Collaborating With Unions; Recruitment; Intellectual Property; Copyright; Patents; Trademarks; Knowledge Sharing; Technology Adoption; District of Columbia

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