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The aging and deterioration of engineering building structures present significant risks to both life and property. Fiber Bragg grating (FBG) sensors, acclaimed for their outstanding reusability, compact form factor, lightweight construction, heightened sensitivity, immunity to electromagnetic interference and exceptional precision, are increasingly being adopted for structural health monitoring in engineering buildings. This research paper aims to evaluate the current challenges faced by FBG sensors in the engineering building industry. It also anticipates future advancements and trends in their development within this field.

This study centers on five pivotal sectors within the field of structural engineering: bridges, tunnels, pipelines, highways and housing construction. The research delves into the challenges encountered and synthesizes the prospective advancements in each of these areas.

The exceptional performance of FBG sensors provides an ideal solution for comprehensive monitoring of potential structural damages, deformations and settlements in engineering buildings. However, FBG sensors are challenged by issues such as limited monitoring accuracy, underdeveloped packaging techniques, intricate and time-intensive embedding processes, low survival rates and an indeterminate lifespan.

This introduces an entirely novel perspective. Addressing the current limitations of FBG sensors, this paper envisions their future evolution. FBG sensors are anticipated to advance into sophisticated multi-layer fiber optic sensing networks, each layer encompassing numerous channels. Data integration technologies will consolidate the acquired information, while big data analytics will identify intricate correlations within the datasets. Concurrently, the combination of finite element modeling and neural networks will enable a comprehensive simulation of the adaptability and longevity of FBG sensors in their operational environments.

Posting and sharing about food on social media has surged in popularity amongst younger generations such as Millennials and Generation Z. This study aims to analyse and compare food-tourism sharing behaviour on social media across generations. First, this study specifically investigates the factors influencing the intention to share food experiences on social media; second, it examines the impact of sharing intention on actual behaviour and loyalty; and third, it determines whether Millennials and Generation Z differ in these relationships.

A survey was carried out of Millennial and Generation Z travellers who shared food experiences on social media. Structural equation modelling (SEM) and multi-group analysis were performed to examine the cause-and-effect relationship in both generations.

The findings reveal differences in motivation, satisfaction, sharing intention, sharing behaviour and loyalty between generations (Millennials and Generation Z).

This study contributes to the literature on the antecedents of food-sharing behaviour in online communities by indicating factors that influence the sharing of culinary experiences and brand or destination loyalty across generations. Suggestions for future research include exploring online food-sharing behaviour through cross-cultural comparisons in various regions.

As Millennials and Generation Z will expand their market share in the coming years, the findings of this study can help improve marketing strategies for culinary tourism and generate more intense food experiences for both generations.

The outcome of the research provides new insights to develop a conceptual model of food-sharing behaviour and tourism on social media by drawing comparisons across generations.

Microblogs are communication platforms for companies and consumers that challenge companies' brand marketing strategies. This paper provides a theoretical basis for expanding microblog applications and a practical basis for improving the effectiveness of brand marketing.

The authors use factor analysis to extract the factors of microblog user influence and construct a structural equation model to reveal the interaction mechanism of the influencing factors. Additionally, the authors clarify the promotion and enhancement effects of these factors.

Microblog user influence can be converted into richness, interaction and value factors. The richness factor significantly affects the latter two, whereas the interaction factor does not affect the value factor.

First, the sample used is limited to media industry practitioners. To increase generalizability, diverse groups should be included in future studies. Second, this model's theoretical explanatory ability can be further developed by adding other meaningful factors beyond the existing ones.

This study analyzes the factors of microblog user influence in China and validates the relevant elements. As a result, it improves the influence research on social media users and benefits the practice of information recommendation and microblog marketing.

To systematically characterize and objectively evaluate basic railway safety management capability, creating a closed-loop management approach which allows continuous improvement and optimization.

A basic railway safety management capability evaluation index system based on a comprehensive analysis of national safety management standards, railway safety rules and regulations and existing safety data from railway transport enterprises is presented. The system comprises a guideline layer including safety committee formation, work safety responsibility, safety management organization and safety rules and regulations as its components, along with an index layer consisting of 12 quantifiable indexes. Game theory combination weighting is utilized to integrate subjective and objective weight values derived using AHP and CRITIC methods and further combined using the TOPSIS method in order to construct a comprehensive basic railway safety management capability evaluation model.

The case study presented demonstrates that this evaluation index system and comprehensive evaluation model are capable of effectively characterizing and evaluating basic railway safety management capability and providing directional guidance for its sustained improvement.

Construction of an evaluation index system that is quantifiable, generalizable and accessible, accurately reflects the main aspects of railway transportation enterprises’ basic safety management capability and provides interoperability across various railway transportation enterprises. The application of the game theoretic combination weighting method to derive composite weights which combine experts’ subjective evaluations with the objectivity of data.

Supply chain management (SCM) has evolved to fulfill the demands of the dynamic global business environment. The development of the Internet of Things (IoT), which offers unmatched connectivity and real-time data insights, has further transformed SCM. This chapter provides an overview of SCM development and its integration with IoTs. This integration led to improved inventory control, supply chain optimization (SCO), and visibility which further enhances the conventional SCM and provides benefits, such as more accurate real-time tracking and monitoring, improved data analytics, more efficient logistics and transportation management, and reduced costs and wastages. However, despite these benefits, there are various associated challenges and concerns, like privacy and data security, compatibility and interoperability, implementation costs, returns on investment, trained workforce, and training requirements, which are required to be addressed. Additionally, the outcomes of this study and managerial implications are provided along with the future research scope. Overall, this chapter provides valuable insight into the transformative potential of IoT in SCM and practical suggestions on how managers can successfully navigate difficulties and get benefits from the IoT-SCM integration. Organizations can enhance their supply chain operations, efficiency, and innovation by actively confronting challenges and taking advantage of the opportunities provided by IoT technologies. This will ultimately result in the delivery of greater value to both stakeholders and customers.

This chapter examines the significant role of non-fungible tokens (NFTs) and blockchain technology in fostering a sustainable economy in the metaverse. Blockchain allows the saving and transfer of decentralized and secure data. As a primary component of the metaverse economy, NFTs are distinct and secure virtual assets saved on the blockchain. These assets facilitate possessing, trading, and monetizing digital assets. These advancing technologies have also revolutionized the method by which creators and artists test and exchange their digital work, introducing a novel period of ownership and value in the digital realm. However, the negative environmental effects of some blockchain technologies constitute a considerable constraint, pushing a shift to a sustainable economy. Platforms like The Sandbox have implemented initiatives to address environmental concerns. As a case study, The Sandbox play-to-earn model with tokenized assets showcases its ability to create value and encourage user participation. It shows the ability of NFTs and blockchain to support a sustainable economy.

Artificial intelligence (AI) carries the risk of widening gender inequalities due to the digital divide, while simultaneously promising to equalise the situation for women through the gender digital dividend. The conflicting findings from previous studies justify the need to investigate the gendered aspects of Artificial Intelligence (AI) diffusion. Specifically, the aim of this chapter is to understand the relationship between female entrepreneurship and the adoption of AI technologies within business contexts at the macroeconomic level. To achieve this, cluster analyses are conducted for the European Union (EU) countries. The results indicate an inverted U-shaped pattern in the relationship between the level of female entrepreneurship and the diffusion of AI technology in business. In the EU countries belonging to clusters with the highest level of AI diffusion, female entrepreneurship is at a moderate level, while in the EU countries with the lowest level of intelligent transformation, both extremes are observed: the highest and the lowest levels of female entrepreneurship. The variety of patterns in female entrepreneurship and AI technology spread in the EU countries implies the complex and multidimensional nature of the interrelationship, and, thus, it indicates the need for diverse, country-specific policies and practices to reach the intelligent transformation with respect to more equal society.

With burgeoning interest in the low-altitude economy, applications of long-endurance unmanned aerial vehicles (LE-UAVs) have increased in remote logistics distribution. Given LE-UAVs’ advantages of wide coverage, strong versatility and low cost, in addition to logistics distribution, they are widely used in military reconnaissance, communication relay, disaster monitoring and other activities. With limited autonomous intelligence, LE-UAVs require regular periodic and non-periodic control from ground control resources (GCRs) during flights and mission execution. However, the lack of GCRs significantly restricts the applications of LE-UAVs in parallel.

We consider the constraints of GCRs, investigating an integrated optimization problem of multi-LE-UAV mission planning and GCR allocation (Multi-U&G IOP). The problem integrates GCR allocation into traditional multi-UAV cooperative mission planning. The coupling decision of mission planning and GCR allocation enlarges the decision space and adds complexities to the problem’s structure. Through characterizing the problem, this study establishes a mixed integer linear programming (MILP) model for the integrated optimization problem. To solve the problem, we develop a three-stage iterative optimization algorithm combining a hybrid genetic algorithm with local search-variable neighborhood decent, heuristic conflict elimination and post-optimization of GCR allocation.

Numerical experimental results show that our developed algorithm can solve the problem efficiently and exceeds the solution performance of the solver CPLEX. For small-scale instances, our algorithm can obtain optimal solutions in less time than CPLEX. For large-scale instances, our algorithm produces better results in one hour than CPLEX does. Implementing our approach allows efficient coordination of multiple UAVs, enabling faster mission completion with a minimal number of GCRs.

Drawing on the interplay between LE-UAVs and GCRs and considering the practical applications of LE-UAVs, we propose the Multi-U&G IOP problem. We formulate this problem as a MILP model aiming to minimize the maximum task completion time (makespan). Furthermore, we present a relaxation model for this problem. To efficiently address the MILP model, we develop a three-stage iterative optimization algorithm. Subsequently, we verify the efficacy of our algorithm through extensive experimentation across various scenarios.

Turnover intention (TOI) has become a severe issue in Saudi Arabia’s health-care system as health professionals leave their organizations. Saudi Arabia’s health-care professionals’ TOI affects the organizations and the patients’ human rights. Therefore, this study aims to assess the factors that affected Saudi Arabia’s health-care professionals’ TOI.

This study based its findings on quantitative cross-sectional data. This study’s respondents were health-care professionals working in Saudi Arabia’s public and private health-care institutions.

By using path analysis, this study’s findings reveal that, on the one hand, job stress (JS), psychological distress (PD) and perceived work exhaustion (PWE) have positive and significant effects on TOI. On the other hand, perceived organizational support (POS) is a positive and significant predictor of TOI.

This study’s findings will help the Saudi Arabian Ministry and policymakers develop policies to encourage health professionals’ perseverance through reducing their JS, PD and PWE and by enhancing POS for health-care staff. Moreover, by controlling the increasing turnover ratio among Saudi Arabia’s health-care professionals, this study’s findings assist in overcoming the violations of human rights.

This study’s findings empirically confirm the development of TOI through JS, PD and PWE among Saudi Arabia’s health-care professionals.

In the context of green development in China, the circumstance in which Environmental, Social and Governance (ESG) ratings function has changed. As an important external governance mechanism of sustainable development, ESG ratings can also be a two-edged sword for the implementation of carbon emission reduction. This research examines the connection of ESG ratings and corporate carbon emission reduction in the context of green development. This present study postulates that the impact of ESG ratings on carbon emission reduction performance in the context of green development is inverted U-shaped.

To obtain empirical evidence for the hypotheses proposed, this study makes an empirical test based on the two-way fixed effects model. The data is taken from listed Chinese manufacturing firms between 2012 and 2021.

The study reveals that there is a significant inverted U-shape relationship between ESG ratings and carbon emission reduction performance in the context of green development. Managerial myopic behaviour plays a positive moderating role in the above relationship. In addition, it makes the inflection point of inverted U-shaped curve move to left. Heterogeneity analyses show that the above inverted U-shaped relationship is more significant for firms that don’t hire CEO with environmental protection background or big four accounting firms.

In the background of green development, this study helps to understand dual influence of ESG ratings on corporate carbon emission reduction deeply. It is beneficial to guide enterprises to utilize ESG ratings mechanism reasonably, thus enhancing the effectiveness of carbon emission reduction. This study provides decision-making reference for government to accelerate low-carbon transformation in microcosmic field.