Digital Business Model Analysis Using a Large Language Model

TL;DR

This paper proposes an LLM-based method to compare and analyze companies across different domains, aiding digital business model design and supporting idea generation amidst digital transformation challenges.

Contribution

It introduces a novel approach using large language models for cross-domain company analysis to assist in digital business model development.

Findings

The method effectively compares companies from different domains.

It supports idea generation for digital business models.

The approach demonstrates potential in digital transformation contexts.

Abstract

Digital transformation (DX) has recently become a pressing issue for many companies as the latest digital technologies, such as artificial intelligence and the Internet of Things, can be easily utilized. However, devising new business models is not easy for compa-nies, though they can improve their operations through digital technologies. Thus, business model design support methods are needed by people who lack digital tech-nology expertise. In contrast, large language models (LLMs) represented by ChatGPT and natural language processing utilizing LLMs have been developed revolutionarily. A business model design support system that utilizes these technologies has great potential. However, research on this area is scant. Accordingly, this study proposes an LLM-based method for comparing and analyzing similar companies from different business do-mains as a first step toward business model design support utilizing LLMs. This method can support idea generation in digital business model design.