Search results

This paper reports on a project looking at consumer perceptions of terroir in the UK, using cheese as a stimulus for the data collection.

Data collection was based on a consumer survey using a discrete choice experiment which included a number of cues to, and stories about, terroir. Analysis of preferences produced three latent classes with varying attitudes towards terroir cues for cheese. There was also an open-ended question giving rise to a qualitative analysis of respondents understanding of the work “terroir”.

When faced with the terroir cues most used some positively to make their choices. A PDO label and stories about the production region and method and business structure all generally offered positive utility.

Terroir is a widely used term in the marketing of (especially) wine, particularly in Europe, offering a form of authenticity and has been very important in policies to sustain the economies of otherwise declining rural areas. It has been adopted by producers in the English-speaking world but is less widely recognised, by consumers. The significance of this study is that it is the first large-scale survey of British consumer perceptions around a key tool for rural businesses – terroir – and one of the first around a non-wine product, and it explores the stories which resonate most effectively with consumers.

Reflexivity supports research teams in developing and implementing interdisciplinarity perspectives, but there is still limited literature on this topic. To fill this gap, we explore how reflexivity can support a research team in its interdisciplinary efforts to create new knowledge for disaster risk reduction.

We present the reflexive journey of our interdisciplinary research team consisting of Ecuador- and UK-based researchers from the social sciences, physical sciences and the arts and humanities and conducting multi-hazard research on Quito. By triangulating data obtained from different material collected during the reflexive journey, we discuss examples of how our team employed reflexivity towards interdisciplinarity.

The reflexive journey allowed our interdisciplinary team to acknowledge and give value to its diversity; to discuss disciplinary language differences, and to gradually develop interdisciplinary working practices and conversations. The journey demonstrates how reflexive practices within research teams allow researchers to overcome disciplinary differences and promote interdisciplinarity to reach research outcomes.

Our reflexive experience shows that adopting reflexivity can be effective in both enhancing interdisciplinarity and addressing the complex nature of risk.

This study aims to investigate the performance analysis, science mapping and future direction of artificial intelligence (AI) technology, applications, tools and software used to preserve, curate and predict the historical value of cultural heritage.

This study uses the bibliometric research method and utilizes the Scopus database to gather data. The keywords used are “artificial intelligence” and “cultural heritage,” resulting in 718 data sets spanning from 2001 to 2023. The data is restricted to the years 2001−2023, is in English language and encompasses all types of documents, including conference papers, articles, book chapters, lecture notes, reviews and editorials.

The performance analysis of research on the use of AI to aid in the preservation of cultural heritage has been ongoing since 2001, and research in this area continues to grow. The countries contributing to this research include Italy, China, Greece, Spain and the UK, with Italy being the most prolific in terms of authored works. The research primarily falls under the disciplines of computer science, mathematics, engineering, social sciences and arts and humanities, respectively. Document types mainly consist of articles and proceedings. In the science mapping process, five clusters have been identified. These clusters are labeled according to the contributions of AI tools, software, apps and technology to cultural heritage preservation. The clusters include “conservation assessment,” “exhibition and visualization,” “software solutions,” “virtual exhibition” and “metadata and database.” The future direction of research lies in extended reality, which integrates virtual reality (VR), augmented reality (AR) and mixed reality (MR); virtual restoration and preservation; 3D printing; as well as the utilization of robotics, drones and the Internet of Things (IoT) for mapping, conserving and monitoring historical sites and cultural heritage sites.

The cultural heritage institution can use this result as a source to develop AI-based strategic planning for curating, preservation, preventing and presenting cultural heritages. Researchers and academicians will get insight and deeper understanding on the research trend and use the interdisciplinary of AI and cultural heritage for expanding collaboration.

This study will help to reveal the trend and evolution of AI and cultural heritage. The finding also will fill the knowledge gap on the research on AI and cultural heritage.

Some similar bibliometric studies have been conducted; however, there are still limited studies on contribution of AI to preserve cultural heritage in wider view. The value of this study is the cluster in which AI is used to preserve, curate, present and assess cultural heritages.

This study aims to develop and apply a process model for prioritizing and selecting basic research projects in developing countries.

Basic research is mainly funded by governments and since, unlike technological research, it does not have clear business goals, its prioritization is one of the complicated issues in formulating science and technology policy. Adopting a design science research methodology, the authors chose a general framework for project portfolio selection as an appropriate artifact for solving this problem. By customizing it for two specific features of this study, i.e. national scale of the problem and the basic nature of research proposals, the authors developed the proposed framework for solving the problem of priority setting.

The process for selecting basic research proposals consists of several steps, which can be categorized into eight steps including strategic decisions, preparation, pre-screening, evaluating individual proposals, screening, portfolio selection and monitoring. This study emphasizes the necessity of defining goals that can be evaluated for the national basic research portfolio, as a key strategic decision. Evaluating individual proposals is a peer-review-based process. In contrast, portfolio selection is done through a zero-one linear programming model. The validity of the proposed framework has been confirmed based on the data obtained from the Iran National Science Foundation.

To the best of the authors’ knowledge, in this research, for the first time, a mathematical model for prioritizing basic research at the national level has been presented, which effectively contributes to policymaking regarding the development of an optimum national research portfolio.

Increased competition and the constant need for companies to differentiate make markets more competitive and consumers more demanding when making purchasing decisions. Consequently, companies recognized the importance of marketing and economics, which has gradually replaced its transactional practices, focused essentially on a single transaction, with relational practices, in which the customer is considered an integral part of the process. Creating long and profitable relationships has become a business priority and the use of tools such as customer relationship marketing (CRM) has become crucial. With the increasing importance of health and wellness tourism, thermalism has become a very competitive product wanted by tourists who need treatments that are not available in their country due to lack of availability or because they are quite expensive. Since tourism is integrated in the services sector, a set of relational marketing strategies can be applied to establish and maintain relationships with tourists. Therefore, it is important to understand how relational marketing can improve health and wellness tourism. Based on a combination of theoretical and practical research, this chapter explores the dynamic system and mechanism of innovation and development of relational marketing strategies in specific contexts of tourism (i.e. health and wellness tourism) considering cross-border (i.e. Northern Euroregion of Portugal and Galicia). From an interdisciplinary perspective, the chapter presents insights for marketing and tourism (health and well-being) and for the economic development of territories (i.e. cross-border regions).

Divers were contracted to carry out a detailed baseline survey which will form the Environmental Impact Assessment. This report presents information about the biodiversity of Cawsand Bay and the impact of installing a subsea tidal energy module. Subsequently, this addresses some of the SDG14 targets: 14.5, conserve coastal and marine areas; 14.7, increase the economic benefits from the sustainable use of marine resources to small island developing states and less developed countries; and 14.8, increase scientific knowledge, research and technology for ocean health. Contracted from November to December 2021 over a four-week period, five SCUBA divers conducted baseline transects over regular intervals of five meters at Cawsand Bay in each cardinal direction. Water and sediment samples were analysed to better understand the habitat and benthos at Cawsand Bay. Sediment samples established the biotope by identifying the benthos: sublittoral seagrass beds (SS.SMp.SSgr.Zmar). The data also revealed Zostera marina, commonly known as eelgrass (seagrass), is the most abundant species in the area, resulting in a high oxygen content within the water samples. In turn, this helps establish an environment capable of sustaining high levels of biodiversity for this time of year and is a more efficient support ecosystem.

The mega railway infrastructure projects are faced with complex environments and multi-level management challenges. Thus, the mega railway infrastructure project management system not only needs to focus on its composition, but also needs to consider changes and impacts of internal and external environment.

This study attempts to introduce the concept of dissipative structure from the perspective of complexity theory and constructs a positive entropy and negentropy flow index system for mega railway infrastructure project management system in order to analyze the factors of management system more deeply. The Brusselator model is used to construct the structure of the mega railway infrastructure project management system, and the entropy method is used to calculate the positive entropy and negentropy values to verify whether the management system is a dissipative structure.

A plateau railway project in China was used as an example for an empirical study, not only its own characteristics are analyzed, but also the role of constraints and facilitation of the internal and external environment. Based on the research results, several effective suggestions are put forward to improve the stability and work efficiency of mega railway infrastructure project management system.

This study demonstrates that mega railway infrastructure project management system has the characteristics of dissipative structure. It can provide theoretical support for the development of mega railway infrastructure project management system from disorderly state to orderly state.

The purpose of this study is to identify the causative factors of metro construction safety accidents, analyze the correlation between accidents and causative factors and assist in developing safety management strategies for improving safety performance in the context of the Chinese construction industry.

To achieve these objectives, 13 types and 48 causations were determined based on 274 construction safety accidents in China. Then, 204 cause-and-effect relationships among accidents and causations were identified based on data mining. Next, network theory was employed to develop and analyze the metro construction accident causation network (MCACN).

The topological characteristics of MCACN were obtained, it is both a small-world network and a scale-free network. Controlling critical causative factors can effectively control the occurrence of metro construction accidents. Degree centrality strategy is better than closeness centrality strategy and betweenness centrality strategy.

In practice, it is very difficult to quantitatively identify and determine the importance of different accidents and causative factors. The weights of nodes and edges are failed to be assigned when constructing MCACN.

This study provides a theoretical basis and feasible management reference for construction enterprises in China to control construction risks and reduce safety accidents. More safety resources should be allocated to control critical risks. It is recommended that safety managers implement degree centrality strategy when making safety-related decisions.

This paper establishes the MCACN model based on data mining and network theory, identifies the properties and clarifies the mechanism of metro construction accidents and causations.

The purpose of this paper is to propose a new combined finite-discrete element method (FDEM) to analyze the mechanical properties, failure behavior and slope stability of soil rock mixtures (SRM), in which the rocks within the SRM model have shape randomness, size randomness and spatial distribution randomness.

Based on the modeling method of heterogeneous rocks, the SRM numerical model can be built and by adjusting the boundary between soil and rock, an SRM numerical model with any rock content can be obtained. The reliability and robustness of the new modeling method can be verified by uniaxial compression simulation. In addition, this paper investigates the effects of rock topology, rock content, slope height and slope inclination on the stability of SRM slopes.

Investigations of the influences of rock content, slope height and slope inclination of SRM slopes showed that the slope height had little effect on the failure mode. The influences of rock content and slope inclination on the slope failure mode were significant. With increasing rock content and slope dip angle, SRM slopes gradually transitioned from a single shear failure mode to a multi-shear fracture failure mode, and shear fractures showed irregular and bifurcated characteristics in which the cut-off values of rock content and slope inclination were 20% and 80°, respectively.

This paper proposed a new modeling method for SRMs based on FDEM, with rocks having random shapes, sizes and spatial distributions.