The complexity of urban street vitality is reflected in the interaction of multiple factors. A deep understanding of the multi-dimensional driving mechanisms behind it is crucial to enhancing urban street vitality. However, existing studies lack comprehensive interpretative analyses of urban multi-source data, making it difficult to uncover these drivers’ nonlinear relationships and interaction effects fully. This study introduces an interpretable machine learning framework, using Nanchang, China as a case study. It utilizes urban multi-source data to explore how these variables influence different dimensions of street vitality. This study’s innovation lies in employing an integrated measurement approach which reveals the complex nonlinearities and interaction effects between data, providing a more comprehensive explanation. The results not only demonstrate the strong explanatory power of the measurement approach but also reveal that (1) built environment indicators play a key role in influencing street vitality, showing significant spatial positive correlations; (2) different dimensions of street vitality exhibit nonlinear characteristics, with transit station density being the most influential one; and (3) cluster analysis revealed distinct built environment and socioeconomic characteristics across various street vitality types. This study provides urban planners with a data-driven quantitative tool to help formulate more effective strategies for enhancing street vitality.

Consumer experiences with cultural fashion for special events often involve heightened expectations, with satisfied customers typically demonstrating increased brand engagement and loyalty. Traditional cultural attire, such as the Chinese Qipao, is widely recognized as quintessential for expressing cultural identity and fashion sensibility, particularly for weddings and other significant life events. Understanding these consumer experiences is crucial for cultural fashion brands seeking to expand their customer base by strategically enhancing consumer satisfaction through providing innovative features. This study, which examines customer experiences with hybrid customized high-end Qipaos for weddings using the integrated customer value framework, seeks to identify value dimensions that lead to satisfied customers. LDA and thematic analyses reveal three predominant themes. Specifically, the theme of “style”, reflecting esthetic values, emerged as the most influential factor and drives customer satisfaction, favorable word of mouth, and referrals. The theme of “fit”, representing performance values, was identified as a basic product feature and functions as a dissatisfier that customers take for granted when customizing high-end traditional cultural attire. This study used a dictionary-based analysis to examine consumers’ price, service, and traditional element preferences. This study proposes a five-dimensional value framework for assessing the high-end expressive fashion customization processes and experiences from a customer value perspective. The findings theoretically expand consumer value theory within customized consumption and offer practical recommendations for e-commerce brands and customization enterprises, aiming to enhance customer satisfaction.