Purpose: The purpose of this paper is to evaluate the role of handicraft production units within creative cultural clusters (CCCs) and their impact on urban regeneration, particularly within the historical fabric of Isfahan. It aims to identify the key factors contributing to the development of CCCs and how these clusters, in turn, influence tourism development. Design/methodology/approach: The research method of this study is based on a quantitative approach, using a researcher-devised questionnaire as the primary data collection instrument. The statistical population included 227 units of handicraft makers in the historical fabric of Isfahan. The data processing and analysis were performed using SPSS software. Findings: Statistical analysis confirms the creative industries, spatial and socio-cultural indices significantly impact tourism, with means of 14.19, 19.07 and 15.11. Clustering, cultural resources and tourism are key to CCCs growth, while innovation and cultural identity have less effect. CCCs enhance Isfahan’s historical fabric, improving urban space attractiveness and fostering social ties. Handicraft clusters around Naqsh-e Jahan square notably influence the economy and cultural identity, with shop placement reflecting the city’s character. Originality/value: The originality of this research lies in its analysis of how handicraft production within CCCs contributes to urban regeneration and tourism in Isfahan, with a novel focus on the socio-cultural and economic impacts of these clusters in a historical context.

This study investigates how artificial intelligence (AI) has transformed the epistemological foundations of urban planning over the past 30 years, a critical yet under-theorised area in planning scholarship. To address this gap, the study conducts a large-scale bibliometric analysis of 1353 peer-reviewed articles from Scopus, using VOSviewer and SciMAT for science mapping. ASReview, a machine learning–assisted tool, was employed to reduce selection bias during article screening, thereby enhancing methodological rigor. The findings reveal a shift from rational-comprehensive models to data-driven, algorithmic urbanism. More significantly, the study identifies a novel hybrid epistemological turn, wherein AI acts as a dynamic mediator between top-down infrastructures and bottom-up, using approaches such as citizen science. This challenges the view of AI as a purely technocratic tool and reframes it as a socio-technical system with the potential to enhance participatory and adaptive planning, while also fostering more authentic, faster, and reliable decision making. The originality of this study lies in critically linking AI’s technical evolution with its socio-political consequences. Its significance lies in showing how digital transformation is not merely altering planning tools but fundamentally reconfiguring planning itself in ways that are context-sensitive, inclusive, resilient, and ethically grounded.

Cities provide residents access to diverse amenities, services, and spaces, fostering dynamic and innovative creative economy (Taheri et al. 2024) and serving as hubs for interactive and evolving s...