Exploratory Learning Behaviors - Publications - Faculty & Research - Harvard Business School

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January 2021 (Revised March 2021)
Case

THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)

By: Jill Avery, Ayelet Israeli and Emma von Maur

THE YES, a multi-brand shopping app launched in May 2020 offered a new type of buying experience for women’s fashion, driven by a sophisticated algorithm that used data science and machine learning to create and deliver a personalized store for every shopper, based on... View Details

Keywords: Data; Data Analytics; Artificial Intelligence; AI; AI Algorithms; AI Creativity; Fashion; Retail; Retail Analytics; E-Commerce Strategy; Platform; Platforms; Big Data; Preference Elicitation; Preference Prediction; Predictive Analytics; App Development; ＂Marketing Analytics＂; Advertising; Mobile App; Mobile Marketing; Apparel; Online Advertising; Referral Rewards; Referrals; Female Ceo; Female Entrepreneur; Female Protagonist; Analytics and Data Science; Analysis; Creativity; Marketing Strategy; Brands and Branding; Consumer Behavior; Demand and Consumers; Forecasting and Prediction; Marketing Channels; Digital Marketing; Internet and the Web; Mobile and Wireless Technology; AI and Machine Learning; E-commerce; Digital Platforms; Fashion Industry; Retail Industry; Apparel and Accessories Industry; Consumer Products Industry; United States

January 2021 (Revised March 2022)
Case

Arçelik: From a Dealer Network to an Omnichannel Experience

By: Ayelet Israeli and Fares Khrais

Arçelik Turkey, the country’s market leader in household appliances, was at an omnichannel crossroads in January 2020. Arçelik was a B2B player utilizing a dealership network with an umbrella of brands and had one of the largest brick-and-mortar store networks in... 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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December 2020
Supplement

France Télécom (C): An Unprecedented Trial

By: Cynthia A. Montgomery and Ashley V. Whillans

In the C case we learn that former CEO Didier Lombard, Deputy Chief Executive Louis-Pierre Wenes, Human Resources Head Olivier Barberot and France Telecom itself were charged for institutional harassment by French authorities, a first for a CAC 40 company. In December... View Details

Article

Robust and Stable Black Box Explanations

By: Himabindu Lakkaraju, Nino Arsov and Osbert Bastani

As machine learning black boxes are increasingly being deployed in real-world applications, there has been a growing interest in developing post hoc explanations that summarize the behaviors of these black boxes. However, existing algorithms for generating such... View Details

Keywords: Machine Learning; Black Box Models; Framework

October 2020
Article

Task Selection and Workload: A Focus on Completing Easy Tasks Hurts Long-Term Performance

By: Diwas S. KC, Bradley R. Staats, Maryam Kouchaki and Francesca Gino

How individuals manage, organize, and complete their tasks is central to operations management. Recent research in operations focuses on how under conditions of increasing workload individuals can decrease their service time, up to a point, in order to complete work... View Details

Keywords: Healthcare; Knowledge Work; Discretion; Workload; Employees; Health Care and Treatment; Decision Making; Performance Effectiveness; Performance Productivity

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2020
Working Paper

(When) Does Appearance Matter? Evidence from a Randomized Controlled Trial

By: Prithwiraj Choudhury, Tarun Khanna, Christos A. Makridis and Subhradip Sarker

While there is evidence about labor market discrimination based on race, religion, and gender, we know little about whether physical appearance leads to discrimination in labor market outcomes. We deploy a randomized experiment on 1,000 respondents in India between... View Details

Keywords: Behavioral Economics; Coronavirus; Discrimination; Homophily; Labor Market Mobility; Limited Attention; Resumes; Personal Characteristics; Prejudice and Bias

September 2020
Article

Creativity, Artificial Intelligence, and a World of Surprises

By: Teresa M. Amabile

In recent years, progress has been made toward AI Creativity, which I define as the production of highly novel, yet appropriate, ideas, problem solutions, or other outputs by autonomous machines. I argue that organizational researchers of creativity and innovation... View Details

Keywords: Artificial Intelligence; AI Creativity; Computer Science; Organizational Behavior; Psychology; Creativity; Technological Innovation; AI and Machine Learning

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August 2020
Article

Machine Learning and Human Capital Complementarities: Experimental Evidence on Bias Mitigation

By: Prithwiraj Choudhury, Evan Starr and Rajshree Agarwal

The use of machine learning (ML) for productivity in the knowledge economy requires considerations of important biases that may arise from ML predictions. We define a new source of bias related to incompleteness in real time inputs, which may result from strategic... View Details

Keywords: Machine Learning; Bias; Human Capital; Management; Strategy

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July 2020
Teaching Plan

Girls Who Code

By: Brian Trelstad and Amy Klopfenstein

This teaching plan serves as a supplement to HBS Case No. 320-055, “Girls Who Code.” Founded 2012 by former lawyer Reshma Saujani, Girls Who Code (GWC) offered coding education programs to middle- and high school-aged girls. The organization also sought to alter... View Details

July 2020
Case

Amanda and Kristen: Mented Cosmetics

By: Steven Rogers, Jeffrey J. Bussgang and Alterrell Mills

The co-founders (Black HBS alumnae) of an e-commerce beauty startup explore the unmet needs within the beauty industry. This case study examines the entrepreneurial opportunities that come from identifying an underserved market, specifically within the Black community... View Details

July 2020 (Revised January 2021)
Case

Vineet Nayar and Sampark Foundation: Frugal Innovation at Scale (A)

By: Linda A. Hill and Emily Tedards

In 2005, Vineet Nayar, the former CEO and Vice Chairman of HCL Technologies, and his wife, Anupama Nayar, committed $100 million of their personal wealth to found Sampark Foundation — a grant-making philanthropy with a mission to transform learning outcomes for 20... View Details

July 2020 (Revised January 2021)
Case

Vineet Nayar and Sampark Foundation: Frugal Innovation at Scale (A) (Abridged)

By: Linda A. Hill and Emily Tedards

In 2005, Vineet Nayar, the former CEO and Vice Chairman of HCL Technologies, and his wife, Anupama Nayar, committed $100 million of their personal wealth to found Sampark Foundation—a grant-making philanthropy with a mission to transform learning outcomes for 20... View Details

Summer 2020
Article

Accelerating Innovation Through a Network of Ecosystems: What Companies Can Learn from One of the World's Largest Networks of Accelerator Labs

By: Elizabeth J. Altman and Frank Nagle

A United Nations agency with a sweeping mission and sprawling global presence may not appear to be the most likely place where companies can learn new techniques for accelerating innovation — but appearances can be deceiving. The United Nations Development Programme... View Details

Keywords: Accelerator Labs; Business Ecosystems; Networks; Innovation and Invention

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Article

Active World Model Learning with Progress Curiosity

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

World models are self-supervised predictive models of how the world evolves. Humans learn world models by curiously exploring their environment, in the process acquiring compact abstractions of high bandwidth sensory inputs, the ability to plan across long temporal... View Details

Keywords: World Models; Mathematical Methods

June 2020
Case

Agile Consumer Product Innovation with Alibaba's Tmall Innovation Center

By: William R. Kerr, Daniel O'Connor and James Palano

Consumer products companies were beset by changes on all sides during the 2010s. Customers were increasingly turning to ecommerce platforms rather than shopping in-store. Meanwhile, nimble, digitally-savvy competitors were gaining market share by capitalizing on the... View Details

Keywords: Future Of Work; Retail; Ecommerce; Alibaba; Consumer Products; Innovation; Innovation and Invention; Product Development; Consumer Behavior; E-commerce; Consumer Products Industry; Retail Industry; China

2021
Conference Presentation

An Algorithmic Framework for Fairness Elicitation

By: Christopher Jung, Michael J. Kearns, Seth Neel, Aaron Leon Roth, Logan Stapleton and Zhiwei Steven Wu

We consider settings in which the right notion of fairness is not captured by simple mathematical definitions (such as equality of error rates across groups), but might be more complex and nuanced and thus require elicitation from individual or collective stakeholders.... View Details

Keywords: Algorithmic Fairness; Machine Learning; Fairness; Framework; Mathematical Methods

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

April 2020
Article

CEO Behavior and Firm Performance

By: Oriana Bandiera, Stephen Hansen, Andrea Prat and Raffaella Sadun

We measure the behavior of 1,114 CEOs in six countries parsing granular CEO diary data through an unsupervised machine learning algorithm. The algorithm uncovers two distinct behavioral types: "leaders" and "managers." Leaders focus on multi-function, high-level... View Details

Keywords: CEOs; Management; Behavior; Organizations; Performance; Analysis

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Article

What We Can Learn from Five Naturalistic Field Experiments That Failed to Shift Commuter Behaviour

By: Ariella S. Kristal and A.V. Whillans

Across five field experiments with employees of a large organization (n = 68,915), we examined whether standard behavioural interventions (“nudges”) successfully reduced single-occupancy vehicle commutes. In Studies 1 and 2, we sent letters and emails with nudges... View Details

Keywords: Commuting; Field Experiments; Nudges; Behavior; Change

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