Towards a Taxonomy of Large Language Model based Business Model Transformations

Fuente: arXiv
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Main Authors: Wulf, Jochen, Meierhofer, Juerg
Format: Preprint
Published: 2023
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author Wulf, Jochen
Meierhofer, Juerg
author_facet Wulf, Jochen
Meierhofer, Juerg
contents Research on the role of Large Language Models (LLMs) in business models and services is limited. Previous studies have utilized econometric models, technical showcases, and literature reviews. However, this research is pioneering in its empirical examination of the influence of LLMs at the firm level. The study introduces a detailed taxonomy that can guide further research on the criteria for successful LLM-based business model implementation and deepen understanding of LLM-driven business transformations. Existing knowledge on this subject is sparse and general. This research offers a more detailed business model design framework based on LLM-driven transformations. This taxonomy is not only beneficial for academic research but also has practical implications. It can act as a strategic tool for businesses, offering insights and best practices. Businesses can lev-erage this taxonomy to make informed decisions about LLM initiatives, ensuring that technology in-vestments align with strategic goals.
format Preprint
id arxiv_https___arxiv_org_abs_2311_05288
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Towards a Taxonomy of Large Language Model based Business Model Transformations
Wulf, Jochen
Meierhofer, Juerg
General Economics
Economics
Research on the role of Large Language Models (LLMs) in business models and services is limited. Previous studies have utilized econometric models, technical showcases, and literature reviews. However, this research is pioneering in its empirical examination of the influence of LLMs at the firm level. The study introduces a detailed taxonomy that can guide further research on the criteria for successful LLM-based business model implementation and deepen understanding of LLM-driven business transformations. Existing knowledge on this subject is sparse and general. This research offers a more detailed business model design framework based on LLM-driven transformations. This taxonomy is not only beneficial for academic research but also has practical implications. It can act as a strategic tool for businesses, offering insights and best practices. Businesses can lev-erage this taxonomy to make informed decisions about LLM initiatives, ensuring that technology in-vestments align with strategic goals.
title Towards a Taxonomy of Large Language Model based Business Model Transformations
topic General Economics
Economics
url https://arxiv.org/abs/2311.05288