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- October 2024
- Teaching Plan
Teamworks: Tackling a Forecasting Fumble
By: Lou Shipley and Stacy Straaberg
In late March 2018, Teamworks CEO Zach Maurides learned Q1 2018 sales were at risk for a large forecasting miss. Founded in 2004, Teamworks’s software application assisted support staff in messaging, scheduling, and sharing documents with collegiate and professional... View Details
Keywords: Acquisition; Business Growth and Maturation; Communication Strategy; Decisions; Forecasting and Prediction; Business Cycles; Technological Innovation; Sports; Growth and Development Strategy; Resource Allocation; Marketing; Sales; Business Strategy; Expansion; Sports Industry; Technology Industry; United States; North Carolina
- 2024
- Working Paper
Generative AI and the Nature of Work
By: Manuel Hoffmann, Sam Boysel, Frank Nagle, Sida Peng and Kevin Xu
Recent advances in artificial intelligence (AI) technology demonstrate considerable potential to
complement human capital intensive activities. While an emerging literature documents wide-ranging productivity
effects of AI, relatively little attention has been paid... View Details
- October 2024
- Case
Lanco Medical Group: Fostering Happiness for Growth
By: Susanna Gallani, Jenyfeer Martínez Buitrago and Katherine Sonnefeldt
This case describes how Lanco Medical Group, a fast-growing pharmaceutical distributor serving Latin America, approached the design of their employee benefits and incentives program. After learning about gaps between what leadership believed motivated employees and... View Details
- 2024
- Working Paper
Lessons from an App Update at Replika AI: Identity Discontinuity in Human-AI Relationships
By: Julian De Freitas, Noah Castelo, Ahmet Uğuralp and Zeliha Uğuralp
Can consumers form deep emotional bonds with AI and be vested in AI identities over time? We
leverage a natural app-update event at Replika AI, a popular US-based AI companion, to shed
light on these questions. We find that customers feel closer to their AI companion... View Details
- 2024
- Working Paper
Global Evidence on Gender Gaps and Generative AI
By: Nicholas G. Otis, Solène Delecourt, Katelynn Cranney and Rembrand Koning
Generative AI has the potential to transform productivity and reduce inequality, but only if used broadly. In this paper, we show that recently identified gender gaps in AI use are nearly universal. Synthesizing evidence from 16 studies that surveyed 100,000... View Details
- 2024
- Working Paper
Priors, Experiments, Learning and Persuasion in (Bayesian) Entrepreneurial Finance
By: Ramana Nanda
At the heart of entrepreneurial finance lies a persuasion challenge: regardless of
the strength of an entrepreneur’s belief in the potential of their idea, they typically
need to convince investors to provide the financial capital required for its... View Details
- September 2024
- Case
Xendit: Hiring for Growth
By: Jeffrey F. Rayport, Steve Castano, Quoc Anh Nguyen and Claire Wu
In 2019, Xendit, a growth-stage Southeast Asia (SEA) fintech venture based in Jakarta, was looking to hire a Head of Sales and Head of Product to lead its next phase of growth. Founded by Moses Lo and Tessa Wijaya, Xendit provided payment infrastructure, modeling... View Details
- September 2024
- Exercise
Finding Your 'Jagged Frontier': A Generative AI Exercise
By: Mitchell Weiss
In 2023 a set of scholars set out to study the effect of artificial intelligence (AI) on the quality and productivity of knowledge workers – in this specific instance, management consultants. They wanted to know across a range of tasks in a workflow, which, if any,... View Details
Keywords: AI and Machine Learning
- 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
- 2024
- Working Paper
Empirical Guidance: Data Processing and Analysis with Applications in Stata, R, and Python
By: Melissa Ouellet and Michael W. Toffel
This paper describes a range of best practices to compile and analyze datasets, and includes some examples in Stata, R, and Python. It is meant to serve as a reference for those getting started in econometrics, and especially those seeking to conduct data analyses in... View Details
- September 2024
- Exercise
Building an AI First Snack Company: A Hands-on Generative AI Exercise
By: Iavor I. Bojinov
Although the term 'Generative AI' (GenAI) is widely recognized, its practical application in daily workflows has yet to be understood. This exercise introduces students to GenAI tools, demonstrating how they can be seamlessly integrated into professional work practices... View Details
- September–October 2024
- Article
How AI Can Power Brand Management
By: Julian De Freitas and Elie Ofek
Marketers have begun experimenting with AI to improve their brand-management efforts. But unlike other marketing tasks, brand management involves more than just repeatedly executing one specialized function. Long considered the exclusive domain of creative talent, it... View Details
- 2024
- Article
Learning Under Random Distributional Shifts
By: Kirk Bansak, Elisabeth Paulson and Dominik Rothenhäusler
Algorithmic assignment of refugees and asylum seekers to locations within host
countries has gained attention in recent years, with implementations in the U.S.
and Switzerland. These approaches use data on past arrivals to generate machine
learning models that can... View Details
- 2024
- Working Paper
The Wade Test: Generative AI and CEO Communication
By: Prithwiraj Choudhury, Bart S. Vanneste and Amirhossein Zohrehvand
Can generative artificial intelligence (AI) transform the role of the CEO by effectively automating CEO
communication? This study investigates whether AI can mimic a human CEO and whether employees’
perception of the communication’s source matter. In a field... View Details
- August 2024
- Case
DBS' AI Journey
By: Feng Zhu, Harold Zhu and Adina Wong
Headquartered in Singapore, DBS Bank, one of Asia's leading financial services groups, embarked on a multi-year digital transformation under CEO Piyush Gupta in 2014. It was then that DBS also began experimenting with AI to drive value for the business and customers.... View Details
- August 2024
- Case
Oculii
By: Andy Wu and Lucas Defilippo
It was a bright June day in 2016. Steven Hong, co-founder and COO of Oculii had just signed a letter of intent agreeing to a 51% stake acquisition by Nexteer Automotive, a global steering and driveline supplier company that developed advanced driver assistance systems... View Details
- August 2024
- Background Note
Your True Moral Compass
This note explores the concept of a "moral compass" for making difficult decisions in leadership roles. It argues that the standard view of a moral compass as a simple, internal guide is inadequate for complex situations. Instead, it proposes that our true moral... View Details
- 2024
- Working Paper
The Narrative AI Advantage? A Field Experiment on Generative AI-Augmented Evaluations of Early-Stage Innovations
By: Jacqueline N. Lane, Léonard Boussioux, Charles Ayoubi, Ying Hao Chen, Camila Lin, Rebecca Spens, Pooja Wagh and Pei-Hsin Wang
The rise of generative artificial intelligence (AI) is transforming creative problem-solving, necessitating new approaches for evaluating innovative solutions. This study explores how human-AI collaboration can enhance early-stage evaluations, focusing on the interplay... View Details
- 2024
- 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
The second edition of Fintech, Small Business & the American Dream, builds on the groundbreaking 2019 book with new insights on how technology and artificial intelligence are transforming small business lending. This ambitious view covers the significance of... View Details
- 2024
- Article
Neyman Meets Causal Machine Learning: Experimental Evaluation of Individualized Treatment Rules
By: Michael Lingzhi Li and Kosuke Imai
A century ago, Neyman showed how to evaluate the efficacy of treatment using a randomized experiment under a minimal set of assumptions. This classical repeated sampling framework serves as a basis of routine experimental analyses conducted by today’s scientists across... View Details