Redefining fashion through disruption: Technological advances in the Industry 5.0 paradigm

Resumen

This research examines the integration of disruptive technologies (Artificial Intelligence (AI), blockchain, and Internet of Things (IoT) in the fashion industry's transition to Industry 5.0, employing a mixed-methods approach that combines quantitative analysis of global enterprises, qualitative interviews with stakeholders, and geographical mapping. The main results show that AI's operational benefits (22.7% error reduction, p<0.01) are best when humans and AI work together (28% faster design cycles with "augmented ideation" models). On the other hand, blockchain demonstrates a consumer trust premium (a 67% willingness-to-pay) despite a significant transparency gap (82% demand for ethical sourcing versus 38% recognition of verification, χ2(4) = 38.72, p < 0.001). Geospatial research reveals regional inequalities, indicating that Latin America's adoption lag (38% behind standards) is associated with infrastructure deficiencies (92/100 severity) and colonial legacies (r=0.71, p<0.001). The research enhances theoretical frameworks by augmenting the Technology Acceptance Model with Ethical Perceived Usefulness (β=0.29, p<0.01), which surpasses conventional ease-of-use indicators, and introduces a practical adoption inequality index that contests linear diffusion theories. The results indicate that Small and Medium-sized Enterprises (SMEs) possess an unforeseen edge in agile integration, achieving 24.3% cost savings compared to 17.2% for big enterprises, hence establishing a phase-gated implementation strategy. These results change the definition of Industry 5.0 to mean a human-centered model that needs a balanced mix of technological efficiency (AI's 19.8% cost savings), ethical transparency (blockchain's verification systems), and fair access (targeted policy interventions for emerging markets). This leads to a new framework for sustainable, fair innovation in fashion technology.