基于三重底线理论的绿色服装评价指标体系构建OA

Against the backdrop of accelerating green consumption and the sustainable transformation of industry,apparel—as a high-frequency,fast-turnover consumer good—faces growing scrutiny for its resource use and environmental burdens.Existing evaluations mostly focus on environmental performance or process safety and lack a unified product-level approach that simultaneously covers social,environmental,and economic objectives across the full life cycle,making it difficult for enterprises to pursue targeted improvements and for consumers to identify genuinely green products.To remedy these deficiencies,this paper adopts the triple bottom line(people-planet-profit)as the overarching framework and,at the product level,constructs an evaluation indicator system for green apparel,aiming to deliver a measurement tool that is quantifiable,comparable,and auditable,and to provide reference for academic research and industry standards. Building on the triple bottom line framework,three first-level indicators were specified:social responsibility,environmental impact,and economic benefits.Drawing on a literature review and case analysis,the social responsibility dimension was subdivided,in line with stakeholder requirements,into wearability-related health and safety,information transparency,consumer education,and community collaboration;the environmental impact dimension was subdivided,from a life-cycle perspective,into raw materials,eco-design and innovation,production emissions,use and maintenance,and circular regeneration potential;and the economic benefits dimension was subdivided,based on circular-economy theory,into product market performance,resource cost efficiency,and circular returns.On this basis,with reference to national∕industry specifications and operable data definitions,quantifiable third-level observed items were further detailed.In validating the initial indicator system,expert scoring based on the necessity-identifiability-feasibility(N-I-F)rubric was employed;by using opinion concentration and feasibility as criteria,redundant or hard-to-quantify items were deleted,including the number of donation∕reuse projects(insufficient concentration),the participation rate in used-clothing recycling(insufficient identifiability),and the technology profit conversion rate(insufficient feasibility).A questionnaire survey was subsequently conducted.Exploratory factor analysis identified the latent structure;because the item-total correlation coefficients for investment in used-clothing recycling infrastructure,abrasion mass loss,and government subsidies were all below 0.30 and exhibited,respectively,conceptual deviation or level mismatch and insufficient measurability,these items were removed.At the same time,the green premium rate was adjusted to the negative review rate,which has higher discrimination.Confirmatory factor analysis was then performed;model-fit indices met commonly used thresholds,and the construct validity and scale stability were sound,resulting in a finalized official scale.Based on triple bottom line theory,this study constructed an evaluation indicator system for green apparel;unlike prior research centered on environmental performance or process compliance,the present study simultaneously covers social-environmental-economic objectives and the product's full life cycle within a single scale,forming a more comprehensive and quantifiable indicator framework.The results show that the green apparel evaluation system consists of three first-level indicators,12 second-level indicators,and 32 third-level measurement items.The third-level items cover supply-chain traceability and consumer feedback,chemical safety control;the share of recycled∕biobased fibers,carbon∕water footprints and energy consumption,wash durability and colorfastness,material recovery rate and design-for-disassembly ratio;as well as life-cycle cost,savings from circular materials,sell-out rate within the first 30 days of initial launch,defect return rate,and negative review rate. This system can provide enterprises with quantitative bases for improvement in raw-material selection,eco-design,manufacturing,and recycling,and it can offer consumers structured information to support rational choices and use.Subsequent work will center on key data sources and calculation boundaries,and further detail more specific and operable third-level indicators and evidence requirements(e.g.,test reports,certification numbers,platform-review scraping with harmonized definitions),and calibrating weights and thresholds across multiple categories and scenarios,so as to promote the system's adoption in enterprise practice and in standards development.