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This paper introduces a methodology to identify, analyse and represent heritage site attributes, emphasizing their impact on value, authenticity, integrity and management, with a case study on Ghadames, Libya. Inscribed in 1986 and moved to the In-Danger List in 2016 due to conflict, this work seeks to update the site's attributes and values for improved management.

This methodology, focusing on Ghadames, leverages recent heritage management advancements to monitor conflict-induced changes, aiming to enhance decision-making through a detailed analysis of the site's natural and cultural attributes.

Our findings highlight the need for systematic and holistic assessments of heritage site attributes and values, crucial for managing sites of both local and global significance. This approach is a key to understanding their identity, guiding interpretation, management and preserving cultural significance.

Developed for Ghadames, the methodology requires adaptation for other sites, underscoring the importance of identifying core tangible and intangible attributes that define a site's uniqueness.

Our developed methodology offers a replicable framework that can be modified by local heritage professionals to map attributes and assess the direct and indirect impact of conflict on heritage sites.

The detailed assessment provides a foundation for crafting informed policies and effective management strategies. It specifically targets minimizing the adverse effects of conflict on heritage sites' attributes. This effort is instrumental in preparing the necessary documentation to support the delisting of these sites from the UNESCO World Heritage Site In-Danger List, promoting their preservation and recovery.

The ancient town of Lijiang is a representative place of ethnic minorities in China’s southwest border area jointly built by many ethnic groups. Its rich and diversified history, culture and architecture as well as its artistic and spiritual values need to be better retained and explored.

The protection and inheritance of Lijiang’s cultural heritage will be improved through the construction of digital memory resources. To guide Lijiang’s digital memory construction, this study explores strategies of digital memory construction by analyzing four case studies of well-known memory projects from China and America.

From the case studies analysis, factors of digital memory construction were identified and compared. Factors led to the discussion of strategies for constructing the digital memory of Lijiang within its design, construction and service phases.

The ancient town of Lijiang is a famous historical and cultural city in China, and it is also a representative place of ethnic minorities in the border area jointly built by many ethnic groups. The rich culture should be preserved and digitalized to offer better use for the whole nation.

This paper argues that cultures with the same climate have similar handicrafts as they have similar cultivation and identical raw materials. This study focuses on how mountainous, coastal and hot regions partaking in similar crafts and cultural heritage use palm leaves and analyses the resulting handicrafts' similarities.

A review of mapping these samples establishes this similarity in the traditional industries of some civilizations' cultural heritage from countries sharing similar climates.

The handwoven crafts using palm leaves were significant patrimonial artifacts in different societies' and communities' cultural heritage. Our studies revealed that climate plays an active role in influencing all aspects of humanity’s life. It affects the construction methods and style, agriculture and lifestyles.

Traditional handwoven palm leaf product models, especially plates and baskets, are studied from South America, Africa, Gulf Countries and Asia.

Additionally, this paper focuses on preserving these treasures as an essential part of interior elements as accessories for most inhabitants of these areas.

Cultural heritage also embraces intangible aspects such as skills passed down through generations within a particular society. The tangible and intangible elements complement each other and contribute to an overall legacy.

Cultural heritage reflects a society’s way of life carried down through the years across lands, items, customs and aesthetic concepts. People are the gatekeepers of society, as they preserve their way of life for future generations to emulate. Tangible artistic and cultural heritage comprises artifacts. It comprises all human evidence and expressions, such as traditional handicrafts, pictures, documents, books and manuscripts.

The main objective of this research is to analyze satisfaction with tourist services linked to the concept of sustainability in the context of a visit to the so-called equestrian show. The equestrian show adds values from the cultures that passed through the city. Specifically, the study focuses on tourist loyalty based on satisfaction with tourist services, satisfaction with the equestrian show and its overall quality. The fieldwork has been conducted in Córdoba, Spain. There are few studies on the relationship between tourist services linked to the concepts of sustainability and loyalty from the perspective of equestrian show management, making this a novel contribution to research.

The methodology used is based on a partial least squares structural equation modeling (PLS-SEM) approach.

To achieve the proposed objective, a structured questionnaire was used, and the results obtained confirm that satisfaction with tourist services linked to the concept of sustainability and the assessment of quality positively influence tourist loyalty. Consequently, they recommend returning to the destination and repeating the visit.

Heritage in Córdoba, Spain, is internationally recognized. Its uniqueness, with four world inscriptions along with the cultures that inhabited it, left a material heritage legacy in the city. Over time, this legacy has made it a magnet for visitors, making it essential to delve into its management and how concepts such as satisfaction with tourist services, combined with sustainability, impact the improvement of the visit.

This article examines curatorial practices, both traditional and digital, in the Guizhou Provincial Museum’s ethnic exhibition to assess their effectiveness in representing ethnic minority cultures, fostering learning and inspiring curiosity about ethnic textiles and costumes and associated cultures. It also explores audience expectations concerning digital technology use in future exhibitions.

A mixed-methods approach was employed, where visitor data were collected through questionnaires, together with interviews with expert, museum professionals and ethnic minority textile practitioners. Their expertise proved instrumental in shaping the design of the study and enhancing the overall visitor experience, and thus fostering a deeper appreciation and understanding of ethnic minority cultures.

Visitors were generally satisfied with the exhibition, valuing their educational experience on ethnic textiles and cultures. There is a notable demand for more immersive digital technologies in museum exhibitions. The study underscores the importance of participatory design with stakeholders, especially ethnic minority groups, for genuine and compelling cultural representation.

This study delves into the potentials of digital technologies in the curation of ethnic minority textiles, particularly for enhancing education and cultural communication. Ethnic textiles and costumes provide rich sensory experience, and they carry deep cultural significance, especially during festive occasions. Our findings bridge this gap; they offer insights for museums aiming to deepen the visitor experiences and understanding of ethnic cultures through the use of digital technologies.

Faced with the growing need to find new viable water supply models for urban areas, this article studies and maps the strategies and identifies the key criteria of sustainable development present in pioneering water supply systems in the medieval period. The main aim is to determine which of its innovative principles could be applied in present-day cities.

From a methodological perspective, two types of cases were established, such as water supply models for human consumption and pre-industrial hydraulic systems, all of which are located in Italy. For the first group, the cases of Venice and Siena were analysed, while for the second, in the context of the cities along the Aemilian Way, the case of Bologna was selected.

Five key criteria resulted from the analysis of the cases: exploitation, self-sufficiency, maintenance, rationalisation and reuse. The said concepts were defined and contextualised within the framework of the Sustainable Development Goals.

The Middle Ages were a historic moment in technological reinvention, before the development of modern systems of sanitation. With very limited resources, these traditional systems focused on rational use and deep cultural and geographical knowledge. This is why its recognition is of great importance today, in a time full of instabilities, with a view to the work that needs to be done for the development of more sustainable communities.

This paper provides practical advice for archaeologists and heritage specialists wishing to use ML approaches to identify archaeological features in high-resolution satellite imagery (or other remotely sensed data sources). We seek to balance the disproportionately optimistic literature related to the application of ML to archaeological prospection through a discussion of limitations, challenges and other difficulties. We further seek to raise awareness among researchers of the time, effort, expertise and resources necessary to implement ML successfully, so that they can make an informed choice between ML and manual inspection approaches.

Automated object detection has been the holy grail of archaeological remote sensing for the last two decades. Machine learning (ML) models have proven able to detect uniform features across a consistent background, but more variegated imagery remains a challenge. We set out to detect burial mounds in satellite imagery from a diverse landscape in Central Bulgaria using a pre-trained Convolutional Neural Network (CNN) plus additional but low-touch training to improve performance. Training was accomplished using MOUND/NOT MOUND cutouts, and the model assessed arbitrary tiles of the same size from the image. Results were assessed using field data.

Validation of results against field data showed that self-reported success rates were misleadingly high, and that the model was misidentifying most features. Setting an identification threshold at 60% probability, and noting that we used an approach where the CNN assessed tiles of a fixed size, tile-based false negative rates were 95–96%, false positive rates were 87–95% of tagged tiles, while true positives were only 5–13%. Counterintuitively, the model provided with training data selected for highly visible mounds (rather than all mounds) performed worse. Development of the model, meanwhile, required approximately 135 person-hours of work.

Our attempt to deploy a pre-trained CNN demonstrates the limitations of this approach when it is used to detect varied features of different sizes within a heterogeneous landscape that contains confounding natural and modern features, such as roads, forests and field boundaries. The model has detected incidental features rather than the mounds themselves, making external validation with field data an essential part of CNN workflows. Correcting the model would require refining the training data as well as adopting different approaches to model choice and execution, raising the computational requirements beyond the level of most cultural heritage practitioners.

Improving the pre-trained model’s performance would require considerable time and resources, on top of the time already invested. The degree of manual intervention required – particularly around the subsetting and annotation of training data – is so significant that it raises the question of whether it would be more efficient to identify all of the mounds manually, either through brute-force inspection by experts or by crowdsourcing the analysis to trained – or even untrained – volunteers. Researchers and heritage specialists seeking efficient methods for extracting features from remotely sensed data should weigh the costs and benefits of ML versus manual approaches carefully.

Our literature review indicates that use of artificial intelligence (AI) and ML approaches to archaeological prospection have grown exponentially in the past decade, approaching adoption levels associated with “crossing the chasm” from innovators and early adopters to the majority of researchers. The literature itself, however, is overwhelmingly positive, reflecting some combination of publication bias and a rhetoric of unconditional success. This paper presents the failure of a good-faith attempt to utilise these approaches as a counterbalance and cautionary tale to potential adopters of the technology. Early-majority adopters may find ML difficult to implement effectively in real-life scenarios.

Unlike many high-profile reports from well-funded projects, our paper represents a serious but modestly resourced attempt to apply an ML approach to archaeological remote sensing, using techniques like transfer learning that are promoted as solutions to time and cost problems associated with, e.g. annotating and manipulating training data. While the majority of articles uncritically promote ML, or only discuss how challenges were overcome, our paper investigates how – despite reasonable self-reported scores – the model failed to locate the target features when compared to field data. We also present time, expertise and resourcing requirements, a rarity in ML-for-archaeology publications.

This study aims to identify the attitudes of Chinese residents towards tourists and tourism development. Based on periods of observation, temporary residency and several visits for more than a decade, and supplemented by data collected from 478 residents, the study examines to what extent the rural villagers identify the tourism induced changes as being an outcome of official Chinese policies. The villages, Xidi, Hongcun and Nanping, are three heritage villages in Anhui Province and represent appropriate case studies for such an examination due to their differing histories of tourism administrative procedures. Findings contribute to scholarly knowledge by putting pro-poor tourism and community participation under scrutiny in Chinese context. A change of residents’ perceptions towards tourism could potentially be consequential for tourists’ experience and the sustainability of tourism development, particularly in emerging rural destinations.

This research delves into the realm of Business Model Innovation (BMI), integrating it with the human-centric, sustainable, and resilient principles of Industry 5.0, proposing a new theoretical framework.

An abductive approach has been chosen to expand existing knowledge developing new ideas based on emerging phenomena. Data were gathered via semi-structured interviews with directors, managers and curators of public institutions in Italy, Switzerland, Germany and Spain encompassing Galleries, Libraries, Archives, and Museums (GLAM). These data were subsequently subjected to thematic analysis.

The findings indicate that the main enablers for Business Model Innovation (BMI) in combination with Industry 5.0 encompassed stakeholder, customer and organizational engagement, collaborative environment, knowledge and innovation management, and sustainability. These drivers were effectively leveraged through three pivotal facilitators-inhibitors: technology, resources, and leadership.

The principal constraints are rooted in the narrow contextual focus and the limited participants number. However, upcoming research efforts may broaden the horizons of this multifaceted and extensive investigation.

This study is groundbreaking as it fills a significant gap in the existing literature by integrating Business Model Innovation (BMI) with the Industry 5.0 paradigm, a novel approach that has not been explored previously. Additionally, the inclusion of GLAM institutions in this research adds a unique dimension, as they have been largely overlooked in both research domains.

This study seeks to provide a greater understanding of the variables that influence travellers’ intention to participate in social media, paying special attention to (1) the direct impact of perceived usefulness (PU) of social media and (2) the moderating impact of tourists’ altruism and self-interest.

The proposed conceptual model was empirically tested using an online questionnaire distributed to a sample of 394 tourists visiting a World Heritage city.

The findings show that perceived social media usefulness has a significant effect on users’ intention to share experiences. Additionally, self-interest appears to moderate the relationship between perceived social media usefulness and users’ sharing intention, but the results do not support the moderating effect of altruism.

Despite scholars’ growing interest in social networks as sources of tourist information, little is known about the aspects that encourage users’ participation in these platforms. This paper offers key contributions to the relevant literature in this field and offers compelling recommendations for tour operators' management of social networks.

本研究擬讓我們更清楚了解驅使旅行人士參與社交媒體上的交流活動的變數;為求達至這研究目的，研究人員特別對以下兩方面加以注意和研究：(一) 、旅行人士對社交媒體的感知效用所帶來的直接影響;(二) 、旅行人士的利他主義，以及其對個人利益的考慮所帶來的緩和影響。

研究人員對其提出之概念模型進行實證測試，方法乃透過收集一個包含394名曾參觀世界遺產城市的旅行人士的樣本所回應的網上問卷數據，並進行數據分析。

研究結果顯示，旅行人士若覺得社交媒體是有用的話，則他們會更願意在那裡分享旅行經歷;而且，他們對自己個人利益的考慮，似會緩和他們對社交媒體的感知效用與其分享經歷的願意程度之間的關係;唯研究結果沒有證實利他主義會帶來緩和的影響。

雖然學者對社交網絡作為提供資訊的來源感到興趣，而且這興趣不斷增加，但我們對促進旅行人士參與社交網絡平台活動之因素的了解仍然淺薄，就此而言，本研究於有關的文獻提供了重要的貢獻;研究亦為旅遊經營者就應如何管理社交網絡提供了具說服力的建議。