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Purpose This study analyzes sustainable fashion consumption and capsule wardrobe adoption in the Czech Republic (CZ). It explores motivations, barriers and decision-making processes, filling a gap in regional research and contributing to a broader understanding of cultural and social influences on sustainable fashion consumption. Design/methodology/approach A mixed-methods approach was used. A nationwide survey (n = 1,100) ensured demographic representativeness. Qualitative data were collected through two focus groups and 23 in-depth interviews. Term frequency-inverse document frequency (TF-IDF) analysis identified significant themes, and K-means clustering segmented consumers by key purchase drivers. Findings The study identified four consumer segments: (1) Unpretentious-practical and price-conscious, (2) Bargainers-discount-driven with minimal environmental concerns, (3) Meticulous-quality-oriented and emotionally attached to clothing and (4) Conservatives-valuing durability, skeptical of sustainable trends. While sustainable behaviors (e.g. upcycling, second-hand) are emerging, fast fashion remains dominant. A pronounced attitude–behavior gap persists, primarily driven by price sensitivity, limited knowledge, and perceived behavioral constraints across segments. Practical implications The segment-specific results support the implementation of targeted policies, educational initiatives, and retail strategies (e.g. offering repair incentives to price-conscious consumers and providing standardized information tools to quality-conscious consumers) to promote textile circularity. Social implications The study highlights the importance of raising awareness of circular fashion practices and tailoring interventions to different consumer values and behaviors. Originality/value This study advances sustainable fashion segmentation in three ways. First, it presents the first representative, mixed-methods, data-driven consumer segmentation analysis in the Czech context. Second, it explicitly links capsule wardrobe adoption to sufficiency and circularity perspectives, as well as to empirically observed purchase drivers and barriers. Third, it uses K-means clustering combined with TF-IDF-based qualitative validation to reveal the motivational and cognitive mechanisms (e.g. knowledge gaps and emotional attachment) behind the attitude-behavior gap in each segment.