Abstract

This paper presents a literature review on modularity and creativity in terms of design variants for generative adversarial networks for image creation. The objective is to lay the foundation for providing a suitable tool to support product design, as this area is considered a potential beneficiary of this concept. Based on the literature, a new model will be developed as an IT artifact in future research. Current approaches that allow the user to control certain features of GAN outputs are explored and commonly used metrics are investigated. Finally, limitations and future research directions are reflected upon.

Recommended Citation

Gaikwad, S., Daase, C., Haertel, C., Staegemann, D. & Turowski, K. (2025). Modular Generative Adversarial Networks for Support in Product DesignIn I. Luković, S. Bjeladinović, B. Delibašić, D. Barać, N. Iivari, E. Insfran, M. Lang, H. Linger, & C. Schneider (Eds.), Empowering the Interdisciplinary Role of ISD in Addressing Contemporary Issues in Digital Transformation: How Data Science and Generative AI Contributes to ISD (ISD2025 Proceedings). Belgrade, Serbia: University of Gdańsk, Department of Business Informatics & University of Belgrade, Faculty of Organizational Sciences. ISBN: 978-83-972632-1-5. https://doi.org/10.62036/ISD.2025.154

Paper Type

Poster

DOI

10.62036/ISD.2025.154

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Modular Generative Adversarial Networks for Support in Product Design

This paper presents a literature review on modularity and creativity in terms of design variants for generative adversarial networks for image creation. The objective is to lay the foundation for providing a suitable tool to support product design, as this area is considered a potential beneficiary of this concept. Based on the literature, a new model will be developed as an IT artifact in future research. Current approaches that allow the user to control certain features of GAN outputs are explored and commonly used metrics are investigated. Finally, limitations and future research directions are reflected upon.