Modeling User Requirement for Value-Oriented Design: A Multi-Dimensional Perception Evidence from the Automobile Market

Aligning system design with evolving user expectations remains a critical challenge in contemporary digital markets. While online reviews offer vast potential for informing product development, transforming unstructured feedback into actionable system intelligence requires rigorous analytical frameworks. This study proposes a unified framework that synthesizes topic-related text analysis, sentiment analysis, and time-series trends to model user requirements as indicators of multidimensional system value. Based on this framework, we introduce the Product Online User Perception Score to quantify user perception of product attributes through the integration of attention, discussion richness, and sentiment. Crucially, a User Requirement Value model is developed to assess the strategic priority of requirements. The model applies a discussion richness dimension to filter superficial noise and employs a reverse valuation mechanism to identify systematic gaps between high attention and low satisfaction. Comparative evidence from the Chinese automotive market highlights the evolution of user needs during the transition from fuel-powered to new energy vehicles. While manufacturers prioritize enterprise-centric intelligent features, user dissatisfaction is systematically concentrated on basic ergonomic deficits, revealing that foundational operational value remains a prerequisite for overall system success. This study shifts the analytical paradigm from descriptive monitoring to diagnostic system valuation, providing a measurable and diagnostic instrument for supporting evidence-based product iteration.