[ai]deation: GenAI-Based Collaborative Service Innovation
Files
Date
2025-01-07
Contributor
Advisor
Department
Instructor
Depositor
Speaker
Researcher
Consultant
Interviewer
Narrator
Transcriber
Annotator
Journal Title
Journal ISSN
Volume Title
Publisher
Volume
Number/Issue
Starting Page
1332
Ending Page
Alternative Title
Abstract
Many new services fail within the first year as businesses often launch services without a deep understanding of stakeholder needs. Recent advancements in generative AI, particularly Large Language Models (LLMs), have enabled the automation of creative tasks. In this work, we focus on the ideation phase of service development, aiming to integrate stakeholder perspectives early in the service development process through a novel human-AI collaborative role-based ideation method. Based on this method, we developed a software tool and an evaluation concept to support this approach. By tailoring the LLM’s roles to meet specific stakeholder needs and incorporating diverse perspectives from the start, we encourage a more effective service development process, reduce the risk of poorly designed services, and facilitate coordination and understanding among stakeholders.
Description
Keywords
Digital Service Innovation and Design, artificial intelligence, generative ai, human-ai collaboration, large language model, service innovation
Citation
Extent
10
Format
Geographic Location
Time Period
Related To
Proceedings of the 58th Hawaii International Conference on System Sciences
Related To (URI)
Table of Contents
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International
Rights Holder
Local Contexts
Collections
Email libraryada-l@lists.hawaii.edu if you need this content in ADA-compliant format.