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- 2024
- Working Paper
Climate Solutions, Transition Risk, and Stock Returns
By: Shirley Lu, Edward J. Riedl, Simon Xu and George Serafeim
Using large language models to measure firms' climate solution products and services, we find that high-climate solution firms exhibit lower stock returns and higher market valuation multiples. Their stock prices respond positively to events signaling increased demand... View Details
- 2024
- Working Paper
Catalysts for Climate Solutions: Corporate Responses to Venture Capital Financing of Climate-tech Startups
By: Shirley Lu, George Serafeim and Simon Xu
We study whether incumbent firms increase their product focus on climate solutions in response to venture capital (VC) financing of climate-tech startups. Using large language models to measure a firm's focus on climate solutions, we find that incumbents in similar... 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
- 2024
- Working Paper
The Financial Anatomy of Climate Solutions: A Large Language Model Approach to Company Classification and Analysis
By: Shirley Lu and George Serafeim
Leveraging advancements in large language models (LLM), we study the financial characteristics of firms offering climate solutions-products and services aimed at fostering a transition to a low-carbon economy. We use a new measure that applies LLM to 10-K Item 1... 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
- July 2024
- Article
Chatbots and Mental Health: Insights into the Safety of Generative AI
By: Julian De Freitas, Ahmet Kaan Uğuralp, Zeliha Uğuralp and Stefano Puntoni
Chatbots are now able to engage in sophisticated conversations with consumers. Due to the ‘black box’ nature of the algorithms, it is impossible to predict in advance how these conversations will unfold. Behavioral research provides little insight into potential safety... View Details
- July 2024
- Article
How Artificial Intelligence Constrains Human Experience
By: A. Valenzuela, S. Puntoni, D. Hoffman, N. Castelo, J. De Freitas, B. Dietvorst, C. Hildebrand, Y.E. Huh, R. Meyer, M. Sweeney, S. Talaifar, G. Tomaino and K. Wertenbroch
Many consumption decisions and experiences are digitally mediated. As a consequence, consumer behavior is increasingly the joint product of human psychology and ubiquitous algorithms (Braun et al. 2024; cf. Melumad et al. 2020). The coming of age of Large Language... View Details
- 2024
- Working Paper
AI Companions Reduce Loneliness
By: Julian De Freitas, Ahmet K Uguralp, Zeliha O Uguralp and Puntoni Stefano
Chatbots are now able to engage in sophisticated conversations with consumers in the domain of relationships, providing a potential coping solution to widescale societal loneliness. Behavioral research provides little insight into whether these applications are... View Details
- June 2024 (Revised September 2024)
- Case
Driving Scale with Otto
By: Rebecca Karp, David Allen and Annelena Lobb
This case asks how startup founders make scaling decisions in light of their priorities for their business and for themselves. Otto was a technology company that applied artificial intelligence technology to sales. It deployed natural language processing to find sales... View Details
Keywords: Artificial Intelligence; Natural Language Processing; B2B; B2B Innovation; Scaling; Scaling Tech Ventures; Business Startups; AI and Machine Learning; Finance; Sales; Business Strategy; Growth and Development Strategy; Entrepreneurship; Information Technology Industry; United States; Cambridge; New York (city, NY); Spain
- 2024
- Book
The Ritual Effect: From Habit to Ritual, Harness the Surprising Power of Everyday Actions
By: Michael Norton
Our lives are filled with repetitive tasks meant to keep us on track—what we come to know as habits. Over time, these routines (for example, brushing your teeth or putting on your right sock first) tend to be performed automatically. But when we’re more mindful about... View Details
- February 2024
- Teaching Note
TimeCredit
By: Emanuele Colonnelli, Raymond Kluender and Shai Benjamin Bernstein
Teaching Note for HBS Case No. 824-139. TimeCredit is an artificial intelligence (AI) startup that is developing large language models (LLMs) to generate accounting memos. The case follows Ndonga Sagnia, a Gambian Harvard Business School MBA student with an accounting... View Details
- February 2024 (Revised September 2024)
- Case
TimeCredit
By: Emanuele Colonnelli, Raymond Kluender and Shai Benjamin Bernstein
TimeCredit is an artificial intelligence (AI) startup that is developing large language models (LLMs) to generate accounting memos. The case follows Ndonga Sagnia, a Gambian Harvard Business School MBA student with an accounting background, as she decides how much... View Details
- February 2024
- Case
More than Optics: Olympus's Vision to Become a Leading Global MedTech Company
By: David J. Collis and Haisley Wert
In August 2022, CEO Yasuo Takeuchi reflected on Olympus Corporation’s recent transformation from being known as a Japanese consumer camera company to becoming a leading global medical technology (MedTech) company. Over the past dozen years, Takeuchi and prior... View Details
- 2024
- Working Paper
Age at Immigrant Arrival and Career Mobility: Evidence from Vietnamese Refugee Migration and the Amerasian Homecoming Act
By: Sari Pekkala Kerr, William R. Kerr and Kendall Smith
We study the long-run career mobility of young immigrants, mostly refugees, from Vietnam who moved to the United States during 1989-1995. This third and final migration wave of young Vietnamese immigrants was sparked by unexpected events that culminated in the... View Details
- 2024
- Working Paper
The Value of Open Source Software
By: Manuel Hoffmann, Frank Nagle and Yanuo Zhou
The value of a non-pecuniary (free) product is inherently difficult to assess. A pervasive
example is open source software (OSS), a global public good that plays a vital role in the economy
and is foundational for most technology we use today. However, it is... View Details
- 2024
- Conference Paper
Quantifying Uncertainty in Natural Language Explanations of Large Language Models
By: Himabindu Lakkaraju, Sree Harsha Tanneru and Chirag Agarwal
Large Language Models (LLMs) are increasingly used as powerful tools for several
high-stakes natural language processing (NLP) applications. Recent prompting
works claim to elicit intermediate reasoning steps and key tokens that serve as
proxy explanations for LLM... View Details
- 2023
- Article
Benchmarking Large Language Models on CMExam—A Comprehensive Chinese Medical Exam Dataset
By: Junling Liu, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Lei Zhu and Michael Lingzhi Li
Recent advancements in large language models (LLMs) have transformed the field of question answering (QA). However, evaluating LLMs in the medical field is challenging due to the lack of standardized and comprehensive datasets. To address this gap, we introduce CMExam,... View Details
- November 2023
- Article
Knowledge About the Source of Emotion Predicts Emotion-Regulation Attempts, Strategies, and Perceived Emotion-Regulation Success
By: Yael Millgram, Matthew K. Nock, David D. Bailey and Amit Goldenberg
People’s ability to regulate emotions is crucial to healthy emotional functioning. One overlooked aspect in emotion-regulation research is that knowledge about the source of emotions can vary across situations and individuals, which could impact people’s ability to... View Details
- 2023
- Article
MoPe: Model Perturbation-based Privacy Attacks on Language Models
By: Marvin Li, Jason Wang, Jeffrey Wang and Seth Neel
Recent work has shown that Large Language Models (LLMs) can unintentionally leak sensitive information present in their training data. In this paper, we present Model Perturbations (MoPe), a new method to identify with high confidence if a given text is in the training... View Details
- 2023
- Article
Post Hoc Explanations of Language Models Can Improve Language Models
By: Satyapriya Krishna, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh and Himabindu Lakkaraju
Large Language Models (LLMs) have demonstrated remarkable capabilities in performing complex tasks. Moreover, recent research has shown that incorporating human-annotated rationales (e.g., Chain-of-Thought prompting) during in-context learning can significantly enhance... View Details