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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.

In recent years, the frequency of emergencies, such as natural disasters and public health crises, has markedly increased globally. These occurrences have introduced new challenges to national public security systems and emergency management capabilities. Post-disaster humanitarian logistic operations involve the collection of emergency relief resources to mitigate the impact of disasters in affected areas. Effective coordination among governments, enterprises and charities is essential to enhance the efficiency of these operations. This study employs evolutionary game theory to explore the strategic interactions and behavioral patterns among these key stakeholders during the collection of emergency materials.

A tripartite evolutionary game model involving governments, enterprises and charities is developed. Subsequently, to validate the theoretical findings, a scale-free network is constructed for the purpose of numerical simulations. As this network evolves, both the edges between nodes and the strategy choices of the nodes also change. Numerical simulations are conducted using the network to examine the sensitivity of factors influencing strategic choices among game stakeholders.

According to the model simulation results, penalties significantly influence government regulation strength, while enterprise philanthropic behavior is mainly affected by penalties, profit transfer benefits and trust loss. For charities, strategic choices are primarily driven by penalties, tax subsidies, illegal operation benefits and charitable costs. The findings provide a theoretical basis for governments, enterprises and charities to select the sensible strategy.

Our study establishes a dynamic network of edges and nodes evolving over time to analyze the strategic evolutionary paths of governments, enterprises and charities from a micro perspective. The results assist governments, enterprises and charities in making more strategic decisions.

This study aims to address the lack of discrimination between fully efficient decision-making units in nonparametric efficiency analysis models by introducing a new ranking technique that incorporates contextual variables.

The proposed method combines Data Envelopment Analysis (DEA) and Ordinary Least Squares (OLS). First, DEA evaluates the partial efficiency of each unit, considering all inputs and only one output. Next, OLS removes the influence of contextual variables on the partial efficiencies. Finally, a ranking criterion based on modified partial efficiencies is formulated. The method is applied to data from 100 Chinese banks, including state-owned, commercial and industrial institutions, for the year 2020.

The ranking results show that the top six positions are assigned to highly esteemed banks in China, demonstrating strong alignment with real-world performance. The method provides a comprehensive ranking of all units, including nonextreme efficient ones, without excluding any. It resolves infeasibility issues that arise during the ranking of efficient units and ensures uniqueness in efficiency scores, leading to a more reliable and robust ranking process. Contextual variables exerted a greater influence on the first partial efficiency compared to the second. Notably, Total Capital Adequacy (TCA) significantly impact bank efficiency.

This study introduces a novel ranking method that effectively integrates contextual variables into DEA-based efficiency analysis, addressing limitations of existing methods. The practical application to Chinese banks demonstrates its utility and relevance.

With the uptake of prefabricated construction (PC) facing serious obstacles in China, networked innovation can break the technical constraints while also containing the risks in individual innovation. However, the construction community has paid little attention to PC innovation, especially networked innovation. This study aims to gain deep insights into what impacts the formation and dynamics of a prefabricated construction innovation network (PCIN). With the uptake of PC facing serious obstacles in China, networked innovation can break the technical constraints while also containing the risks in individual innovation.

The research design follows a sequential mixed methodology of qualitative and quantitative data collection and analysis. It first conceptualizes the PCIN based on the quadruple helix model and formulates a corresponding system dynamics model based on causality analysis. After validating the PCIN model using empirical data, simulations are carried out using Vensim PLE software. Finally, this study identifies key factors that promote the formation of PCIN in China through sensitivity analysis.

The results show that PC predicts a continuous increase in practice as of 2030. The tested drivers all positively influence the formation of the PCIN, with market demand and risk sharing having the greatest influence, followed by competitive pressure, profit government support, scientific and technological advancement and collaborative innovation strategy.

The study makes three major contributions. First, it provides a novel angle for a deeper understanding of the PC innovation. Second, it proposes a new approach for probing the formation and dynamics of the PCIN. Finally, it offers a theoretical reference for promoting the formation of innovation networks and the development of PC.

This study identifies benefits and challenges of PL partnerships, and recommendations to improve the PL partnership process.

Qualitative data was collected via semi-structured interviews (n = 8) with Irish PL retail buyers (n = 4) and producers (n = 4). Data was coded and thematically analysed.

Three key themes were identified. Theme 1 provides an overview of the benefits of PL partnerships for producers (e.g. volume driven orders, increased efficiencies) and for retailers (e.g. unique products, meeting consumer demand). Theme 2 presents challenges of PL partnerships specific to small and large producers (e.g. small producers may need significant investment to upgrade facilities, while larger producers may require significant volume to justify adaptation of production lines). Challenges common to both (e.g. risks related to short-term contracts, concerns about brand identity) are also discussed. Theme 3 summarised recommendations for successful PL partnerships generally (e.g. setting clear expectations and goals, building rapport and trust), and recommendations specific to producers and buyers specifically (e.g. producers should diversify customers to reduce risk, and retailers should communicate needs and direction).

There is currently limited research on PL partnerships between producers and retailers. This study addresses this gap by identifying key aspects for producers to consider when entering PL partnerships and key aspects for retailers to be aware of to help improve the attractiveness and success of these partnerships.

The purpose of this study is to examine how a hotel virtual reality photography (VRP) preview enhances customers’ immediate booking intention compared to a picture preview.

Data were collected using a one-factor between-subject experimental design and time-based systematic sampling. Respondents were asked to read a scenario on an iPad and assess a hotel preview (VRPs vs pictures) before answering the questionnaire.

The results show that a hotel VRP preview generates more mental imagery than a picture preview in terms of quantity, vividness, modality and valence. These four dimensions of mental imagery indirectly influence customers’ immediate booking intentions through perceived utilitarian value and hedonic value, among which modality has the greatest influence on utilitarian value and valence has the greatest influence on hedonic value. Moreover, utilitarian value has a stronger impact on customers’ immediate booking intentions than does hedonic value.

The results obtained in this study contribute to hospitality research by using cognitive consistency theory as the overarching framework, combining mental imagery theory, media richness theory and perceived value theory to explain the mechanism of tourists’ hotel booking decision-making from hotel previews. Comparing this study’s results with previous studies shows the difference in the effects of 360° (head-mounted) videos, VRPs and pictures on evoking mental imagery across tourism and hotel products, updating our knowledge of VR technology in tourism marketing.

本研究旨在探讨与图片预览相比, 酒店虚拟现实摄影（VRP）预览如何增强客户的即时预订意图。

本研究采用单因素被试间实验设计和时间系统抽样收集数据。受试者在 iPad 上阅读场景并评估酒店预览（VRP与图片）, 然后填写问卷。

结果表明, 酒店VRP预览在心理意象的数量、生动性、感官模式和情感效价方面比图片预览生成更多的心理意象。这四个维度的心理意象通过感知的工具价值和享乐价值间接影响客户的即时预订意图, 其中感官模式对工具价值的影响最大, 情感效价对享乐价值的影响最大。此外, 工具价值对客户的即时预订意图的影响强于享乐价值。

本研究利用认知一致性理论作为总体框架, 结合心理意象理论、媒介丰富度理论和感知价值理论, 解释了游客在酒店预览中做出预订决策的机制。本研究结果与以往研究相比, 展示了360°（头戴式）视频、VRP和图片在唤起旅游和酒店产品心理意象方面的差异, 更新了我们对旅游营销中VR技术的理解。

This study investigates the influence of the wisdom of the crowd (WSC), trust and perceived value on consumer purchase intentions within social commerce (s-commerce) platforms. By constructing a novel theoretical model, the research aims to delineate the interrelationships among these variables, addressing an emerging area in social interactions and information technology.

To empirically test and validate the proposed model, the study collected data from 442 Facebook users familiar with online shopping. The analysis employed Structural Equation Modeling – Partial Least Squares (SEM-PLS) to test the hypotheses and examine the relationships between WSC, trust, perceived value and purchase intentions.

The findings confirm that WSC significantly influences trust, perceived value and the intention to purchase on s-commerce platforms. Both perceived value and trust are substantial determinants of purchase intentions. Notably, the PLS analysis revealed that WSC accounts for 36.8% of the variance in trust and 33.1% of the variance in perceived value related to purchasing decisions on s-commerce platforms.

This research contributes uniquely to the ongoing discourse on s-commerce adoption by integrating WSC as a pivotal factor in understanding perceived value and consumer adoption intentions. It provides a fresh perspective on how collective intelligence affects consumer behavior in digital marketplaces, enriching the theoretical and practical understanding of s-commerce dynamics.

This study aimed to investigate whether information from reliable news sources such as medical experts and government officials, along with governmental and individual risk responses, influences consumers’ perceptions of news and intention to seek more information. Additionally, it aimed to explore the relationships between these perceptions and consumers’ intentions to seek information in a food safety risk event.

A survey design methodology was employed. A quasi-experimental approach divided 470 Taiwanese participants into three groups, each exposed to varying online news content about food safety news, designed according to the Internalization-Distribution-Explanation-Action (IDEA) model. This involved different combinations of reliable sources and risk response advice to examine the impact on news comprehension and behaviour intentions.

The results indicated that consumers perceived the news as highly credible when they read it with reliable news sources or risk response advice. Governmental and individual risk response advice significantly impacted consumers’ understanding of news. In addition, perceptions of news credibility and understanding of news can increase individuals’ information-seeking intentions to protect themselves from food safety risks.

This study introduced novel insights into the application of the source credibility theory (SCT) model within Taiwanese food safety incidents, identifying key factors that motivate consumer information-seeking behaviour. It marks an initial attempt to incorporate the IDEA model-based risk communication content into research design, aligning with existing literature while highlighting the critical role of reliable sources in enhancing news credibility and consumer response.

This study aims to analyse the relationship between a patent’s network position in a knowledge search network and the likelihood and speed of patent transactions. Additionally, it explores whether patent scope moderates these relationships.

In this empirical study, the authors collected a sample of patents in the artificial intelligence industry over the period of 1985–2018. Then, the authors examined the direct roles of degree centrality, betweenness centrality and closeness centrality on the likelihood and speed of patent transactions and the moderating role of patent scope in the knowledge search network using the logit and accelerated failure time models.

The findings reveal that degree centrality positively affects both the likelihood and speed of patent transactions, while betweenness centrality enhances the likelihood, and closeness centrality significantly boosts both. However, regarding the speed of patent transactions, closeness centrality is the most impactful, followed by degree centrality, with no significant influence of betweenness centrality. Additionally, the patent scope moderates how betweenness centrality affects the likelihood of transactions.

This study has limitations owing to its exclusive use of data from the Chinese Intellectual Property Office, lack of visibility of the confidential terms of most patent transactions, omission of transaction directionality and focus on a single industry, potentially restricting the breadth and applicability of the findings. In the future, expanding the data set and industries and combining qualitative research methods may be considered to further explore the content of this study.

This study has practical implications for developing a better understanding of how network structure in the knowledge search network affects the likelihood and speed of patent transactions as well as the identification of high-value patents. These findings suggest future directions for patent holders and policymakers to manage and optimise patent portfolios.

This study expands the application boundaries of social network theory and the knowledge-based view by conducting an in-depth analysis of how the position characteristics of patents within the knowledge search network influence their potential and speed of transactions in the technology market. Moreover, it provides a theoretical reference for evaluating patent value and identifying high-quality patents by quantifying network positions. Furthermore, the authors construct three centrality measures and explore the development of patent transactions, particularly within the context of the developing country.

A manufacturer with complex end-products can play the “hub firm” role in its supplier network and manage the relationship among its suppliers, but it mostly does not know how to manage suppliers’ coopetitive relationship for improving its innovation. This study aims to investigate the influence of horizontal supplier–supplier (S-S) competition and cooperation in the supplier network on the quantity and quality of manufacturer’s innovation, to unravel the manufacturers’ coopetitive strategic sourcing.

The study conducts negative binomial regression using the data from 130 listed Japanese manufacturers and their first-tier supplier networks as the analysis unit.

The results indicate that both S-S competition and cooperation have inverted U-shaped effects on manufacturers’ innovation. As to the interplay of S-S competition and cooperation in driving manufacturers’ innovation, the one weakens the other’s inverted U-shaped role. It also shows that simultaneously maintaining moderate cooperation and competition among suppliers is a good choice for manufacturer innovation, and when there is high S-S competition, motivating high cooperation among suppliers is also a way to enhance manufacturers’ innovation. All of the effects are more significant and robust on the innovation quality than the innovation quantity.

This study contributes to linking the dyadic analysis of vertical relationships to the network analysis of horizontal S-S relations and exploring the under-researched interplay between competition and cooperation in driving the ego firm’s innovation. It provides insights to manufacturers’ policymakers on how to strategically manage their supplier networks and S-S coopetition to improve their innovation performance.