Evaluation of Methods for User Needs Extraction in Digital–Physical Product Ecosystems Using ChatGPT Text Categorization

Evaluation of Methods for User Needs Extraction in Digital–Physical Product Ecosystems Using ChatGPT Text Categorization

연구 분야: Analysis

학회: International Baltic Conference on Digital Business and Intelligent Systems

The identification and categorization of user needs in digital–physical product ecosystems are key starting point for developing user-centered products and improving user experiences in complex, interconnected environments. Utilizing ChatGPT for text categorization offers a new automated approach to simplify user need elicitation of a user generated content that can be applied to a traditional user needs elicitation method. The Kano model, user personas, the jobs to be done framework, and user journey mapping methods were used in this study to identify user needs in digital–physical product ecosystems. ChatGPT was used in this study to automate the process of identifying and analyzing consumer experiences using the selected methods. The findings of this study offer insights into product ecosystem user needs research and practical guidance in the use of ChatGPT to identify and categorize user needs.