Data-Driven Service Innovation in Used Clothing Collection: Integrating User-Centered Drop-off Point Layout with Low-Carbon Inventory Management

Abstract

Fast fashion and linear consumption models have led to rapid growth in the volume of used clothing globally, presenting severe environmental and social challenges for local governments, charitable organizations, and social enterprises. Although the field of operations research has proposed various complex models for optimizing collection networks and supply chains, these models are rarely truly integrated into user-facing service design and circular business models. This paper constructs a service-oriented used clothing collection framework that combines front-end user-centered collection bin placement and layout with back-end low-carbon inventory management in the resale stage of secondhand clothing. The paper synthesizes core findings from two recent analytical studies: first, an optimal location and recommendation simulation model for used clothing collection bins based on multi-dimensional user preferences and location-based social networks; second, a two-echelon supply chain low-carbon inventory decision optimization model for secondhand clothing resale scenarios under carbon tax and carbon labeling policy constraints. Building on this foundation, the paper proposes an integrated service system architecture that coordinates and unifies user-level service recommendations, environmental impact visualization, and the effects of policy instruments through collaborative design. This framework distills key design principles for service innovation in used clothing collection systems: (1) achieving personalization in collection service access methods by mining user preferences and travel behavior patterns; (2) managing inventory-related carbon emissions in secondhand clothing resale operations through policy-sensitive decision rules; (3) embedding data flows and analytical modules into the service value proposition; (4) achieving synergistic alignment among user experience, operational efficiency, and environmental performance. Finally, the paper discusses the management and policy implications of this framework for local governments, charitable organizations, social enterprises, and platform-based service providers in building data-driven, user-centered, and low-carbon used clothing collection services, and looks ahead to future research directions for service innovation in circular textile systems.