This article focuses on private art collections that play a relevant role on the art market while reducing its information asymmetry. Knowledge of how art consumers such as private art collectors show preferences for specific artworks may allow to identify collecting patterns based on the preference of some artworks’ signs. Understanding these patterns is essential for evaluating the impact of art collectors on the art market. The evolution of the art market shows complex consumption systems that shape the cognition and behavior of actors such as private art collectors. Consequently, to be a key art collector and to progress as such in today’s art world implies a constant reinterpretation about what it means to consume and to collect art. This paper explores the collection of one of the most important art collectors in the world, the French tycoon François Pinault. More precisely, his background as a key collector was examined, and a number of preferences toward particular signs which connote his collected artworks were identified. All the collected artworks were observed through a descriptive data analysis of the Pinault Collection’s exhibition catalogues, published from 2006 to 2015, enforced by the statistical decision tree classifier. Results show how the Pinault Collection is shaped by collecting preferences that can be described as collecting patterns. As a preeminent collector and owner of one of the two major auction houses in the world, Pinault’s consumption preferences and decisions may impact the art market, for instance through signals and by influencing other art market players or the artists’ careers.

Today’s contemporary art world has to come to terms with a highly unstable socioeconomic context that is evolving rapidly and constantly, with the result that any analysis to establish the state of the demand and supply of artistic goods and services in a global scenario is quite complex. The supply of contemporary art is renewed and must continue to be renewed, in line with the recent requirements of demand and with economic and technological changes.

The topic of creativity and culture in relation to urban value creation and global competitiveness becomes all the more relevant when it allows us to understand the development or the enhancement of cultural and creative industries clusters alongside with the subsequent new geographies shaping cities. In an enclosed area such as a city, the cultural and creative potential is closely related to the scale of innovation and knowledge, let alone to the kind of tourism or cultural occasions that the city provides. This article identifies specific cultural and creative sectors that are concentrated and coexist in the city of Milan. This article suggests that these markets may mutually enhance their paths of value creation whilst positively impacting on the city's tourist image. In this way, Milan will have the opportunity to become a global capital of culture and creativity.

Recent advances in artificial intelligence (AI) have accelerated organizational experimentation with new forms of value creation across cultural and creative industries. While prior research has examined AI adoption, creative augmentation, and ethical concerns, limited attention has been paid to how AI contributes to regenerative forms of value creation. Addressing this gap, this study investigates how regenerative practices emerge from different configurations of AI-enabled organizational capabilities in cultural and creative industries. Drawing on survey data from 110 European creative organizations and applying fuzzy-set qualitative comparative analysis (fsQCA), the study identifies one dominant pathway to regenerative practices, centered on the joint presence of adaptive learning and collaborative engagement, alongside supplementary configurations with limited empirical coverage. The findings reveal that regenerative practices do not arise from AI adoption or human-centric design alone, but from specific combinations of resource efficiency, environmental impact reduction, adaptive learning, and collaborative engagement. The results further outline causal asymmetry, indicating that the absence of regeneration cannot be explained as the simple inverse of its presence. This study contributes to research on AI, regenerative business models in cultural and creative industries, offering theoretical insights into AI-enabled regeneration and practical guidance for managing human–AI collaboration toward regenerative outcomes.

The preservation and evaluation of cultural heritage increasingly demand methodologies capable of navigating complexity, expert subjectivity, and participatory foresight. This study examines the Delphi method as a robust tool for cultural heritage research, particularly for contexts marked by plural values, limited empirical data, and evolving stakeholder constellations. Drawing from the method’s philosophical foundations and recent evolutions (including fuzzy, policy, and e-Delphi variants) we propose a narrative framework for Delphi-based heritage assessments. Based on a review of eleven Delphi studies across the arts and heritage fields, we identify common methodological patterns, design innovations, and challenges related to expert selection, consensus-building, and transparency. We also highlight the method’s potential to engage diverse knowledge systems and to map dissensus rather than enforce artificial agreement. The paper concludes by discussing the implications of Delphi for interdisciplinary research, inclusive governance, and the co-construction of knowledge in sustainable cultural development.