Start Date
6-10-2025 9:00 AM
End Date
8-10-2025 7:00 PM
Description
As an interdisciplinary approach, service design (SD) has integrated multidisciplinary perspectives to extend its capability and reinforce its transformative role in addressing service (eco)system transformations. However, as both external and internal ecosystem dynamics introduce growing complexity and uncertainty, SD must continue to evolve its frameworks. This paper proposes a double-cone spiralling interpretive model for SD, outlining a potential spiralling trajectory of system transformation by bridging ancestral elements with future possibilities. The interpretive model draws on emerging SD frameworks that integrate transdisciplinary knowledge and case study analyses of illustrative examples. It highlights the importance of systemically considering ancestrality, long-term temporality, and dynamic adaptation, contributing to ongoing discourse on the evolution of SD.
Citation
Lin, Z., Torta, R.,and Villari, B.(2025) Double-Cone Spiralling Model: Integrating Ancestral Elements and Future Possibilities in Service Design.. https://dl.designresearchsociety.org/servdes/servdes2025/researchpapers/17
Double-Cone Spiralling Model: Integrating Ancestral Elements and Future Possibilities in Service Design
As an interdisciplinary approach, service design (SD) has integrated multidisciplinary perspectives to extend its capability and reinforce its transformative role in addressing service (eco)system transformations. However, as both external and internal ecosystem dynamics introduce growing complexity and uncertainty, SD must continue to evolve its frameworks. This paper proposes a double-cone spiralling interpretive model for SD, outlining a potential spiralling trajectory of system transformation by bridging ancestral elements with future possibilities. The interpretive model draws on emerging SD frameworks that integrate transdisciplinary knowledge and case study analyses of illustrative examples. It highlights the importance of systemically considering ancestrality, long-term temporality, and dynamic adaptation, contributing to ongoing discourse on the evolution of SD.