Redesigning the Apparel Ecosystem: An Integrated Intelligence Approach to Post-Growth Transition

The global apparel sector is defined by a pathology of structural unsustainability, where a volume-driven growth imperative has doubled production while halving garment utilisation. This linear trajectory generates 92 million tonnes of annual waste and relies on an extractive logic that compromises social sustainability. This paper argues that current Circular Business Models (CBMs) fail because they refuse to confront the growth paradox or the persistent ‘attitude-behaviour gap’ of consumers. To address these systemic failures, we propose a transition toward ‘sustainable maturity’ via a post-growth paradigm. Drawing on Multi-Level Perspective (MLP) theory, the study introduces an ‘Integrated Intelligence’ framework, synthesising Artificial Intelligence (AI) and Cognitive Intelligence (CI) to navigate the systemic paradoxes (such as the ‘longevity trap’ and ‘sunk cost fallacy’) inherent in industrial descaling. The research employs a three-stage mixed-methods approach: an online scenario-based experiment with 720 consumers to test AI-driven behavioural nudges; focus groups in the UK and Sri Lanka to validate operational feasibility; and semi-structured interviews with stakeholders in Turkey and Bangladesh. Preliminary findings suggest that AI-enabled ‘capability brokers’ and ‘defaulting to repair’ mechanisms can effectively overcome cognitive biases like visceral contamination and loss aversion. The paper culminates in the validation of the Post-Growth Ecosystem Model (PGEM). By advocating for an end-to-end (E2E) agency model, the study challenges adversarial procurement logics and introduces wealth redistribution mechanisms. This provides a ‘Minimum Viable Ecosystem’ that decouples revenue from volume, ensuring a ‘just transition’ for Global South manufacturers while respecting planetary boundaries and social floors.