Search Results (155)

This study explores the dissemination of Cantonese Opera on Bilibili, a social media platform popular among younger audiences in China, as traditional cultural forms struggle to captivate younger generations. Platforms like Bilibili present opportunities for revitalizing interest in intangible heritage. This research aims to uncover how user engagement metrics influence the visibility and spread of Cantonese Opera content, providing insights for enhancing heritage promotion. Data were collected from 1916 Cantonese Opera videos using Python-based web scraping, focusing on eight user engagement metrics: Likes, Shares, Coins, Comments, Bullet Comments, Fans, Collects, and Plays. In addition to descriptive statistics, exploratory data analyses—including distributional assessment, correlation analysis, and K-means clustering—were conducted to examine engagement heterogeneity and interaction patterns across videos. The structural equation modeling (SEM) was employed to analyze the relationships among these metrics and their impact on content dissemination. Results show that Coins and Likes significantly predict Comments and Shares, indicating the importance of both monetary and non-monetary support in fostering interaction. The clustering results revealed three distinct video groups—high, moderate, and low engagement—demonstrating a long-tail pattern typical of social media visibility. Collects and Shares notably increase Plays counts, underscoring the role of curation and social diffusion. However, the negative impact of Coins on Plays reveals complex user motivations. These multi-level analyses provide a comprehensive understanding of engagement mechanisms and heterogeneity. They contribute to understanding the promotion of traditional cultural content through youth-oriented social media and offer practical implications for content creators and cultural institutions leveraging digital media for cultural preservation. Full article

The sustainable preservation of cultural heritage, as articulated in Sustainable Development Goal (SDG) 11.4, requires strategies that not only safeguard tangible and intangible assets but also enhance their long-term cultural, social, and economic value. Artificial intelligence (AI) and digital technologies are increasingly applied in heritage conservation. However, most research emphasizes technical applications, such as improving data accuracy and increasing efficiency, while neglecting their integration into a broader framework of cultural sustainability and heritage tourism. This study addresses this gap by developing a set of practical guidelines for the sustainable use of AI in cultural heritage preservation. The guidelines highlight six dimensions: inclusive data governance, data authenticity protection, leveraging AI as a complementary tool, balancing innovation with cultural values, ensuring copyright and ethical compliance, long-term technical maintenance, and collaborative governance. To illustrate the feasibility of these guidelines, the paper analyses three representative case studies: AI-driven 3D reconstruction of the Old Summer Palace, educational dissemination via Google Arts & Culture, and intelligent restoration at E-Dunhuang. By situating AI-driven practices within the framework of cultural sustainability, this study makes both theoretical and practical contributions to heritage governance, to enhance cultural sustainability commitments and align digital innovation with the enduring preservation of humanity’s shared heritage, providing actionable insights for policymakers, institutions, and the tourism industry in designing resilient and culturally respectful heritage strategies. Full article

Small local museums play a crucial role in safeguarding cultural heritage, but often lack the necessary resources and digital capabilities to engage younger visitors effectively. This study examines whether a mobile serious game can enhance engagement, intrinsic motivation, and cultural knowledge among Generation Z museum visitors. This study introduces Thai-Craft-To-Go, a mobile serious game that mediates intangible cultural heritage—specifically Thai textiles and handicrafts—for Generation Z. Grounded in Self-Determination Theory (SDT) and Flow Theory and operationalized through the Mechanics–Dynamics–Aesthetics (MDA) framework, the game translates cultural content into interactive play. We conducted an exploratory evaluation with 30 Generation Z participants using the Game Engagement Questionnaire (GEQ), the Intrinsic Motivation Inventory (IMI), and a 10-item knowledge test administered before and after gameplay. Results indicated high engagement—particularly Presence and Absorption on the GEQ—strong intrinsic motivation on the IMI (notably perceived competence and value), and significant knowledge gains (mean scores increased from 4.40 to 8.03; t(29) = 8.39, p < 0.001, d = 1.53). These findings suggest that a well-designed serious game can align museum learning with the digital habits of younger audiences, enhancing engagement, motivation, and cultural understanding. For small local museums, serious games provide a feasible and cost-conscious pathway to revitalize visitor experiences and support the intergenerational transmission of intangible cultural heritage in the digital age. Full article

Digital platforms for intangible cultural heritage (ICH) function as vibrant electronic marketplaces, yet they grapple with content overload, high search costs, and under-leveraged social networks of heritage custodians. To address these electronic-commerce challenges, we present GCHS, a custodian-aware, graph-based deep learning model that enhances ICH recommendation by uniting three critical signals: custodians’ social relationships, user interest profiles, and content metadata. Leveraging an attention mechanism, GCHS dynamically prioritizes influential custodians and resharing behaviors to streamline user discovery and engagement. We first characterize ICH-specific propagation patterns, e.g., custodians’ social influence, heterogeneous user interests, and content co-consumption and then encode these factors within a collaborative graph framework. Evaluation on a real-world ICH dataset demonstrates that GCHS delivers improvements in Top-N recommendation accuracy over leading benchmarks and significantly outperforms in terms of next-N sequence prediction. By integrating social, cultural, and transactional dimensions, our approach not only drives more effective digital commerce interactions around heritage content but also supports sustainable cultural dissemination and stakeholder participation. This work advances electronic-commerce research by illustrating how graph-based deep learning can optimize content discovery, personalize user experience, and reinforce community networks in digital heritage ecosystems. Full article

Artificial intelligence (AI) is profoundly transforming heritage tourism through the incorporation of technological solutions that reconfigure the ways in which cultural heritage is conserved, interpreted, and experienced. This article presents a critical and systematic review of current AI applications in this field, with a special focus on their impact on destination management, the personalization of tourist experiences, universal accessibility, and the preservation of both tangible and intangible assets. Based on an analysis of the scientific literature and international use cases, key technologies such as machine learning, computer vision, generative models, and recommendation systems are identified. These tools enable everything from the virtual reconstruction of historical sites to the development of intelligent cultural assistants and adaptive tours, improving the visitor experience and promoting inclusion. This study also examines the main ethical, technical, and epistemological challenges associated with this transformation, including algorithmic surveillance, data protection, interoperability between platforms, the digital divide, and the reconfiguration of heritage knowledge production processes. In conclusion, this study argues that AI, when implemented in accordance with principles of responsibility, sustainability, and cultural sensitivity, can serve as a strategic instrument for ensuring the accessibility, representativeness, and social relevance of cultural heritage in the digital age. However, its effective integration necessitates the development of sector-specific ethical frameworks, inclusive governance models, and sustainable technological implementation strategies that promote equity, community participation, and long-term viability. Furthermore, this article highlights the need for empirical research to assess the actual impact of these technologies and for the creation of indicators to evaluate their effectiveness, fairness, and contribution to the Sustainable Development Goals. Full article

Cultural heritage is important for every group and society, as it represents a part of their identity and helps preserve traditions, along with significant tangible and intangible elements. These elements are not only passed on to future generations but also play a role in education today. Many studies have examined digital applications that promote cultural heritage, particularly those that use Augmented Reality (AR) technology. However, few have systematically examined the methodologies used in the design, development and evaluation of AR applications for cultural heritage. This narrative review addresses that gap by analyzing 45 papers published between 2008 and 2024 from the Scopus and Web of Science databases. The review identifies the main motivations for AR applications, such as enhancing the learning experience, promoting tourism and the use of gamification. The majority of these applications concentrate on tangible cultural heritage, such as historical buildings and cultural routes, while intangible heritage remains less explored. In most cases, AR applications were developed with a focus on user experience, using various development tools and showing different levels of technical complexity. Although many applications initiated evaluation processes, few completed them thoroughly. These evaluations vary widely, ranging from usability tests to pre-/post-tests. The results generally report positive impacts in terms of learning and user experience. This review offers a structured framework and useful insights for researchers regarding the design and evaluation of AR applications and helps identify research gaps and limitations for future work. Full article

Malay songket motifs are a vital component of Malaysia’s intangible cultural heritage, characterized by intricate visual designs and deep cultural symbolism. However, the practical digital preservation and retrieval of these motifs present challenges, particularly due to the rotational variations typical in textile imagery. This study introduces a novel Content-Based Image Retrieval (CBIR) model that integrates Principal Component Analysis (PCA) for feature extraction and Quadratic Geometric Distance (QGD) for measuring similarity. To evaluate the model’s performance, a curated dataset comprising 413 original images and 4956 synthetically rotated songket motif images was utilized. The retrieval system featured metadata-driven preprocessing, dimensionality reduction, and multi-angle similarity assessment to address the issue of rotational invariance comprehensively. Quantitative evaluations using precision, recall, and F-measure metrics demonstrated that the proposed PCAQGD + Rotation technique achieved a mean F-measure of 59.72%, surpassing four benchmark retrieval methods. These findings confirm the model’s capability to accurately retrieve relevant motifs across varying orientations, thus supporting cultural heritage preservation efforts. The integration of PCA and QGD techniques effectively narrows the semantic gap between machine perception and human interpretation of motif designs. Future research should focus on expanding motif datasets and incorporating deep learning approaches to enhance retrieval precision, scalability, and applicability within larger national heritage repositories. Full article

As a vital carrier of China’s intangible cultural heritage, restoring damaged embroidery fabrics is essential for the sustainable preservation of cultural relics. However, existing methods face persistent challenges, such as mask pattern mismatches and restoration size constraints. To address these gaps, this study proposes an embroidery image restoration framework based on enhanced generative adversarial networks (GANs). Specifically, the framework integrates a U-Net generator with a multi-scale discriminator augmented by an attention mechanism and dual-path residual blocks to significantly enhance texture generation. Furthermore, fabric damage was classified into three categories (hole-shaped, crease-shaped, and block-shaped), with complex patterns simulated through dynamic randomization. Grid-based overlapping segmentation and pixel fusion techniques enable arbitrary-dimensional restoration. Quantitative evaluations demonstrated exceptional performance in complex texture restoration, achieving a structural similarity index (SSIM) of 0.969 and a peak signal-to-noise ratio (PSNR) of 32.182 dB. Complementarily, eye-tracking experiments revealed no persistent visual fixation clusters in the restored regions, confirming perceptual reliability. This approach establishes an efficient digital conservation pathway that promotes resource-efficient and sustainable heritage conservation. Full article

McMahon Hall, an iconic Brutalist dormitory at the University of Washington, has become the site of an interdisciplinary experiment in cultural memory and machine-assisted storytelling. This article presents a method that combines remote sensing with AI-generated voices to produce a polyvocal narrative of architecture through the perspective of the building itself, its material (concrete), an architect, a journalist, and a bird. Drone photogrammetry and generated 3D models were combined with generative AI (text, image, and voice) to reconstruct the site digitally and imaginatively (AI-driven speculative narratives). Through speculative storytelling, the article and the project explore how cultural memory and perception of built heritage can be augmented by machines, offering plural perspectives that challenge singular historical narratives. The Introduction situates the work at the intersection of digital heritage documentation, AI storytelling, epistemology in machine learning, and spatial computing, emphasizing the perception of heritage through different actors. The Theoretical Framework draws on literature in photogrammetry for heritage preservation, polyvocal narrative, and knowledge frameworks of AI. The Materials and Methods detail the workflow: capturing McMahon Hall via UAV photogrammetry, producing a 3D model, and generating character-driven narratives with large language models and voice synthesis. The resulting multi-voiced narrative and its thematic insights are described. In the Discussion, the implications of this approach for architectural heritage interpretation are considered, including its capacity to amplify diverse voices and the risks of bias or hyperreality in AI-generated narratives. The study argues that this polyvocal, machine-augmented storytelling expands the toolkit of remote sensing and digital heritage by not only documenting the tangible form of the built environment but also speculating on its intangible cultural memory. The Conclusions reflect on how merging spatial computing techniques with AI narratives can support new modes of engagement with architecture, positioning this work as a building block toward richer human-machine co-created heritage experiences. Full article

This study investigates how Corporate Social Responsibility (CSR) influences financial performance in the Middle Eastern banking sector through the mediating roles of corporate reputation, employee engagement, and innovation orientation. Drawing on stakeholder theory and the resource-based view, a survey of 297 senior banking executives was analyzed using structural equation modeling. The results show that CSR has both a direct positive impact on financial performance and an indirect effect by strengthening intangible resources. Among the mediators, innovation orientation emerged as the strongest pathway, followed by employee engagement and reputation. Collectively, the model accounted for more than 60% of the variance in financial performance, confirming that socially responsible strategies are not symbolic but yield tangible economic value. In the Middle Eastern banking sector—characterized by regulatory turbulence, cultural expectations, and digital transformation—CSR initiatives such as financial inclusion programs, green financing, and Sharia-compliant services provide both legitimacy and resilience. These findings highlight the strategic importance of embedding CSR into banking practices, showing that socially responsible institutions not only secure reputational gains but also cultivate motivated employees, foster innovation, and achieve sustainable profitability. By situating CSR within the unique context of Middle Eastern banking, this study extends the literature on CSR—performance linkages in emerging markets and demonstrates how intangible capabilities can be mobilized to secure long-term financial sustainability. Full article

In the contemporary international context, the preventive conservation of cultural relics has become a widespread consensus. “Risk management” has emerged as a pivotal research focus at the present stage. However, the preventive protection of cultural relics is confronted with deficiencies in risk assessment and prediction. There is an urgent requirement for research to present a comprehensive and in-depth overview of the frontier technologies applicable to the preventive protection of cultural relics, with a particular emphasis on risk prevention and control. Additionally, it is essential to delineate the prospects for future investigations and developments in this domain. Consequently, this study employs bibliometric methods, applying CiteSpace (6.3.R1) and Biblioshiny (4.3.0) to perform comprehensive visual and analytical examinations of 392 publications sourced from the Web of Science (WoS) database covering the period 2010 to 2024. The results obtained from the research are summarized as follows: First, it is evident that scholars originating from China, Italy, and Spain have exhibited preponderant publication frequencies, contributing the largest quantity of articles. Second, augmented reality, digital technology, and risk-based analysis have been identified as the cardinal research frontiers. These areas have attracted significant scholarly attention and are at the forefront of innovation and exploration within the discipline. Third, the “Journal of Culture Heritage” and “Heritage Science” have been empirically determined to be the most frequently cited periodical within this particular field of study. Moreover, over the past decade, under the impetus and influence of the concept of Intangible Cultural Heritage, virtual reality, digital protection, and 3D models have progressively evolved into the central and crucial topics that have pervaded and shaped the research agenda. Finally, with respect to future research trajectories, there will be a pronounced focus on interdisciplinary design. This will be accompanied by an escalation in the requisites and standards for preventive conservation. Specifically, the spotlight will be cast upon aspects such as the air quality within the preservation environment of cultural relics held in collections, the implementation and efficacy of environmental real-time monitoring systems, the utilization and interpretation of big data analysis and early warning mechanisms, as well as the comprehensive and in-depth risk analysis of cultural relics. These multifaceted investigations will be essential for advancing understanding and safeguarding of cultural heritage. These findings deepen our grasp of how risk management in cultural heritage conservation has progressed and transformed between 2010 and 2024. Furthermore, the study provides novel insights and directions for subsequent investigations into risk assessment methodologies for heritage collections. Full article

The preservation of architectural heritage must extend beyond historic city centres to include the large-scale prefabricated housing stock that characterises many post-socialist urban environments. These structures, often overlooked, hold both material and social value. This study focuses on prefabricated residential buildings and proposes a scalable methodology for sustainable rehabilitation through a prototype tool: the building identity passport (BIP). The proposed approach integrates multi-layered diagnostics—combining building integrated modelling (BIM), thermographic surveys, occupant questionnaires, and expert interviews—into a replicable decision-support framework. Results demonstrate that the passport can synthesise tangible (physical) and intangible (perceptual, social) resources of prefabricated blocks into a coherent framework, highlighting both technical pathologies and lived experiences. Thermographic validation of BIM simulations confirms the feasibility of combining digital and on-site diagnostics, while community surveys and expert insights reveal the tensions between comfort, health, and energy efficiency. The resulting prototype provides a transparent overview of building identity, making rehabilitation strategies easier to compare, communicate, and adapt. Beyond its local application, the study underscores the broader replicability of the method: core diagnostic layers remain constant, while context-sensitive indicators can be tailored to different regions. The proposed framework thus offers municipalities and communities a practical tool to align rehabilitation with circular resource use and occupant well-being. Future work will focus on automating data processing and extending validation to diverse housing contexts, strengthening its potential as a platform for sustainable urban regeneration. Full article

This paper presents a flexible approach to a multipurpose, heterogeneous archive and data management system model that merges the robustness of legacy grid-based technologies with modern cloud and edge computing paradigms. It leverages innovations driven by big data, IoT, AI, and machine learning to create an adaptive data storage and processing framework. In today’s digital age, where data are the new intangible gold, the “gold rush” lies in managing and storing massive datasets effectively—especially when these data serve governmental or commercial purposes, raising concerns about privacy and data misuse by third-party aggregators. Astronomical data, in particular, require this same thoughtful approach. Scientific discovery increasingly depends on efficient extraction and processing of large datasets. Distributed archival models, unlike centralized warehouses, offer scalability by allowing data to be accessed and processed across locations via cloud services. Incorporating edge computing further enables real-time access with reduced latency. Major astronomical projects must also avoid common single points of failure (SPOFs), often resulting from suboptimal technological choices driven by collaboration politics or In-Kind Contributions (IKCs). These missteps can hinder innovation and long-term project success. The principal goal of this work is to outline best practices in archival and data management projects—from policy development and task planning to use-case definition and implementation. Only after these steps can a coherent selection of hardware, software, or virtual environments be made. The proposed model—CTAARCHS (Cloud-based Technologies for Astronomical Archiving Research Contents and Handling Systems)—is an open-source, multidisciplinary platform supporting big data needs in astronomy. It promotes broad institutional collaboration, offering code repositories and sample data for immediate use. Full article

Ethnic minority embroidery from Guizhou is an important part of Chinese culture, reflecting the history, beliefs, and artistic traditions of the region’s diverse ethnic groups. However, challenges in automatic recognition arise due to data scarcity, complex textures, and the flexibility of handmade designs. This study constructs the Guizhou Province Intangible Cultural Heritage Embroidery dataset and proposes an improved MobileViT-DDC model to address the issues of complex textures and data scarcity. The model integrates Dilatefomer, Deformable Dilatefomer (DefDilatefomer), and Context Broadcasting Module (CBM) to capture local details and global information in embroidery patterns. Experimental results show that the MobileViT-DDC model achieves an accuracy of 98.40% on the Guizhou embroidery dataset (a 2.17% improvement over the original baseline model) with a 14% reduction in computational load; on the Pakistani National Dress Dataset, it reaches an accuracy of 79.07%, representing a 2.63% increase compared to the original baseline model of the same scale. This study is the first to apply a CNN-ViT hybrid model to ethnic embroidery recognition, providing a new solution for the digital preservation of cultural heritage. The model’s cross-cultural adaptability was further validated through its application to the Pakistani National Dress dataset. Full article

Cultural ecosystem services (CES) represent the non-material relationships between people and nature, yet their intangible nature poses challenges for spatial planning and policy integration. This study examines CES in Gauja National Park, Latvia, focusing on symbolic, sacred, educational, and cultural heritage values—types often underrepresented in CES assessments. Using a Participatory Geographic Information Systems (PGIS) approach, a map-based public survey was conducted via ArcGIS Survey123, enabling respondents to mark and describe places of personal significance. While widely applied internationally, PGIS remains rarely used in Latvia, especially in planning and municipal decision-making. This study explores the use of the PGIS method for the assessment of CES, serving as a pilot application to test its suitability and potential for integration into spatial planning. Points of value were successfully georeferenced and reflect diverse associations. While well-known heritage sites were commonly mentioned, respondents also identified personally meaningful locations, sometimes situated outside the park’s formal boundaries. The findings highlight both the strengths and limitations of digital participatory methods, including issues related to response rates, accessibility, and digital literacy. The study demonstrates that mapping CES with PGIS can offer valuable insights for inclusive landscape governance and supports the incorporation of local perspectives into spatial planning. Full article