Designing Adaptive Digital Nudging Systems with LLM-Driven Reasoning
For software architects and designers of adaptive systems, this work provides reusable architectural patterns that balance nudge effectiveness with ethical constraints, bridging behavioral science and software architecture.
The paper addresses the lack of architectural guidance for translating behavioral science into digital nudging systems, proposing an architecture that integrates behavioral theory, ethics, and fairness as structural guardrails. Validation with 13 software architects confirmed requirements satisfaction, and an LLM-powered proof-of-concept in energy sustainability with 15 users achieved high perceived intervention quality and positive emotional impact.
Digital nudging systems lack architectural guidance for translating behavioral science into software design. While research identifies nudge strategies and quality attributes, existing architectures fail to integrate multi-dimensional user modeling with ethical compliance as architectural concerns. We present an architecture that uses behavioral theory through explicit architectural decisions, treating ethics and fairness as structural guardrails rather than implementation details. A literature review synthesized 68 nudging strategies, 11 quality attributes, and 3 user profiling dimensions into architectural requirements. The architecture implements sequential processing layers with cross-cutting evaluation modules enforcing regulatory compliance. Validation with 13 software architects confirmed requirements satisfaction and domain transferability. An LLM-powered proof-of-concept in residential energy sustainability demonstrated feasibility through evaluation with 15 users, achieving high perceived intervention quality and measurable positive emotional impact. This work bridges behavioral science and software architecture by providing reusable patterns for adaptive systems that balance effectiveness with ethical constraints.