Future applications of generative large language models: A data-driven case study on ChatGPT

IF 11.1 1区 管理学 Q1 ENGINEERING, INDUSTRIAL Technovation Pub Date : 2024-03-29 DOI:10.1016/j.technovation.2024.103002
Chiarello Filippo , Giordano Vito , Spada Irene , Barandoni Simone , Fantoni Gualtiero
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Abstract

This study delves into the evolving role of generative Large Language Models (LLMs). We develop a data-driven approach to collect and analyse tasks that users are asking to generative LLMs. Thanks to the focus on tasks this paper contributes to give a quantitative and granular understanding of the potential influence of LLMs in different business areas. Utilizing a dataset comprising over 3.8 million tweets, we identify and cluster 31,747 unique tasks, with a specific case study on ChatGPT. To reach this goal, the proposed method combines two Natural Language Processing (NLP) Techniques, Named Entity Recognition (NER) and BERTopic. The combination makes it possible to collect granular tasks of LLMs (NER) and clusters them in business areas (BERTopic). Our findings reveal a wide spectrum of applications, from programming assistance to creative content generation, highlighting LLM's versatility. The analysis highlighted six emerging areas of application for ChatGPT: human resources, programming, social media, office automation, search engines, education. The study also examines the implications of these findings for innovation management, proposing a research agenda to explore the intersection of the identified areas, with four stages of the innovation process: idea generation, screening/idea selection, development, and diffusion/sales/marketing.

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生成式大型语言模型的未来应用:关于 ChatGPT 的数据驱动案例研究
本研究深入探讨了生成式大型语言模型(LLM)不断演变的作用。我们开发了一种数据驱动方法,用于收集和分析用户向生成式大型语言模型提出的任务。得益于对任务的关注,本文有助于对 LLM 在不同业务领域的潜在影响有一个量化和细化的了解。利用由 380 多万条推文组成的数据集,我们识别并聚类了 31747 个独特的任务,并对 ChatGPT 进行了具体的案例研究。为了实现这一目标,我们提出的方法结合了两种自然语言处理(NLP)技术:命名实体识别(NER)和 BERTopic。这两种技术的结合可以收集 LLM 的细粒度任务(NER),并将它们按业务领域(BERTopic)进行聚类。我们的研究结果揭示了从编程辅助到创意内容生成等广泛的应用领域,凸显了 LLM 的多功能性。分析强调了 ChatGPT 的六个新兴应用领域:人力资源、编程、社交媒体、办公自动化、搜索引擎和教育。本研究还探讨了这些发现对创新管理的影响,提出了一个研究议程,以探索已确定领域与创新过程四个阶段的交叉点:创意生成、筛选/创意选择、开发和传播/销售/营销。
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来源期刊
Technovation
Technovation 管理科学-工程:工业
CiteScore
15.10
自引率
11.20%
发文量
208
审稿时长
91 days
期刊介绍: The interdisciplinary journal Technovation covers various aspects of technological innovation, exploring processes, products, and social impacts. It examines innovation in both process and product realms, including social innovations like regulatory frameworks and non-economic benefits. Topics range from emerging trends and capital for development to managing technology-intensive ventures and innovation in organizations of different sizes. It also discusses organizational structures, investment strategies for science and technology enterprises, and the roles of technological innovators. Additionally, it addresses technology transfer between developing countries and innovation across enterprise, political, and economic systems.
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