Toward Adaptive Degrees of Freedom: an Exploratory Study of User Preference Heterogeneity in Mass Customization Toolkits

Document Type : Original Article

Author

Department of Industrial Design, College of Fine Arts, University of Tehran, Tehran, Iran.

Abstract

Mass Customization (MC) toolkits function as the primary interface between consumer heterogeneity and flexible manufacturing systems, facilitating the iterative configuration of personalized products. While widespread across industries, contemporary toolkit designs often rely on static "one-size-fits-all" frameworks that often struggle to account for the dynamic cognitive load imposed by varying solution spaces. This exploratory pilot study investigates user preferences regarding Degrees of Freedom (DoF) within MC interfaces. User interaction with a parametric lightshade configurator was examined across three distinct DoF levels (Low: 18, Medium: 23, and High: 28). The pilot observations suggest preliminary variation in user preference, and within the small exploratory sample (N=10), 4 participants showed differing preferences for the structured guidance of restricted options, while 6 participants preferred the granular control associated with high configurability. In addition, descriptive trends suggested that participants tended to prefer higher DoF levels for products perceived as more complex. The results argue the notion of a universally optimal option count and instead suggest the concept of Adaptive Degrees of Freedom (ADoF), in which toolkit complexity dynamically responds to differences in user expertise and product context. Given the small exploratory sample (N=10), these observations are descriptive and intended to generate hypotheses about adaptive interface design rather than to support statistical generalization. The primary contribution of this work is the clear illustration of user preference heterogeneity, which supports the foundational argument for developing and testing adaptive, context-aware DoF systems in future large-scale studies.

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References

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Journal of Design Thinking
Volume 7, Issue 1
June 2026
Pages 1-11

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