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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.

The purpose of this paper is to investigate the underlying mechanisms through which social media use for vertical and horizontal communication enhance employee performance.

To test the research model, the authors conducted a questionnaire survey in China. The authors used a customer panel database provided by a marketing research firm in China to identify appropriate respondents. Finally, the authors received 243 valid responses.

The authors find that social media use for vertical communication (SMUVC) is positively related to leader-member exchange (LMX) and social media use for horizontal communication (SMUHC) is positively related to team-member exchange (TMX). LMX and TMX are positively related to employee performance. LMX is positively associated with TMX. Besides, task complexity positively moderates the relationship between LMX and employee performance, while it negatively moderates the relationship between TMX and employee performance.

First, it adds to the literature by investigating the underlying mechanisms of how social media use for communication influences job performance. By identifying LMX and TMX as the underlying mechanisms, the authors make comprehensive considerations of how the vertical and horizontal relationships link the effect of social media use for communication on employee performance. Second, despite the growing evidence demonstrates that high-quality LMX and TMX can individually contribute to employee job performance, little research has considered both LMX and TMX relationships simultaneously and their effects on job performance. Finally, by establishing task complexity as a key moderator on the relationships between LMX and TMX and job performance, the study could explain the inconsistent findings in the literature that the effects of LMX and TMX are significant in some studies yet not significant in other studies.

The authors develop a conceptual model to examine how three basic psychological needs (i.e. needs for competence, autonomy and relatedness) affect employee social media use (i.e. work- and social-related use). The authors propose that the need for autonomy positively moderates the relationship between need for competence and work-related use, whereas it negatively moderates that between need for relatedness and social-related use.

To test the proposed model, 332 internal and 271 external social media users in the workplace were recruited.

The results indicate that needs for competence and autonomy and needs for relatedness and autonomy positively affect the work- and social-related use, respectively, of internal and external social media. Need for autonomy positively moderates the relationship between need for competence and work-related use of internal social media, and it negatively moderates that between need for relatedness and the social-related use of internal social media. Need for autonomy has no moderating effect on the relationship between need for competence and work-related use, whereas it negatively moderates the relationship between need for relatedness and the social-related use of external social media.

First, the authors’ findings offer significant empirical support for the different social media uses, namely work and social related. Second, this study highlights the importance of psychological needs of employees in determining the form of social media use. Third, this study empirically demonstrates the differences in psychological needs and social media use between two different social media contexts.

Smartphone multitasking behavior has become prevalent in our daily lives, yet factors influencing smartphone multitasking behavior have not been fully investigated. This study aimed to examine the roles of a set of demographic, personality and motivational factors on smartphone multitasking behavior, and how these factors were related to general and application-specific types of smartphone multitasking behavior.

A cross-sectional study was conducted in which 2,659 smartphone users were invited to complete an online survey on smartphone multitasking behavior. Hierarchical multiple regression analyses were used to examine the roles of demographic, personality and motivational factors on smartphone multitasking behavior.

The results showed that, in general, demographic factors, such as gender, age, occupation status, education and smartphone usage time significantly predicted smartphone multitasking behavior. People characterized by agreeableness, extraversion, neuroticism and openness to experience were more likely to multitask with smartphones. Information seeking, efficiency and habit motivations were identified as major motivational factors for smartphone multitasking behavior. The roles of demographic, personality and motivational factors differed much across varied types of application-specific smartphone multitasking behavior.

This study extends and advances the literature on media multitasking, smartphone multitasking in particular, by identifying a set of demographic, personality and motivational factors as antecedents of smartphone multitasking behavior. In addition, this study revealed the differentiated roles of the above-mentioned factors across varied types of smartphone application usages. The findings provide important implications for practitioners to tailor smartphone applications and services to different target smartphone users and use situations.

The purpose of this paper is to present a sliding mode attitude controller for reusable launch vehicle (RLV) which is nonlinear, coupling, and includes uncertain parameters and external disturbances.

A smooth second-order nonsingular terminal sliding mode (NTSM) controller is proposed for RLV in reentry phase. First, a NTSM manifold is proposed for finite-time convergence. Then a smooth second sliding mode controller is designed to establish the sliding mode. An observer is utilized to estimate the lumped disturbance and the estimation result is used for feedforward compensation in the controller.

It is mathematically proved that the proposed sliding mode technique makes the attitude tracking errors converge to zero in finite time and the convergence time is estimated. Simulations are made for RLV through the assumption that aerodynamic parameters and atmospheric density are perturbed. Simulation results demonstrate that the proposed control strategy is effective, leading to promising performance and robustness.

By the proposed controller, the second-order sliding mode is established. The attitude tracking error converges to zero in a finite time. Meanwhile, the chattering is alleviated and a smooth control input is obtained.

The purpose of this paper is to address the urgent need for guiding the construction of information systems for disease surveillance and early warning, given the latest efforts of the report system of public health information over China.

A system framework for disease surveillance and early warning, based on disease clustering test and cluster detection techniques, geographical information system, network and communication is conceived. Through geographical surveillance analysis of severe acute respiratory syndrome occurring in Beijing in 2003, an application example of the framework is illustrated.

Through approaches such as integrating spatial‐time clustering test and cluster detection algorithms, spatial visualization, computer network, wireless communication, it is feasible to build a systematic, automatic, real‐time surveillance and early warning system for prevention and control of disease.

The present study provides an underlying framework for the development of disease surveillance and early warning system enabling data acquisition, data analysis and alarm publishing.

The framework integrates report system of public health information, GIS and disease clustering test and cluster detection techniques into an application, which will significantly enhance the resilience of healthcare facilities. It is supposed to be implemented in near future and provides fundamental support for nation‐wide disease surveillance and early warning.

Based on the knowledge-based view, this study investigates how firms' information technology (IT) capability broadens and deepens their knowledge base, which consequently improves digital innovation. By further drawing on the institutional theory perspective, this study examines how the relationships between IT capability and knowledge base are moderated by the institutional environments in which the firm operates.

This paper uses 170 samples of Chinese firms and an empirical test conducted by the authors following a hierarchical moderated regression analysis.

The results find that IT capability positively affects knowledge breadth and knowledge depth, which consequently improves digital innovation. Furthermore, the study reveals the negative moderating effects of enforcement inefficiency on IT capability–knowledge breadth relationship, and the negative moderating effects of government support on IT capability–knowledge depth relationship.

This research is one of the earliest attempts to explore the impact of the institutional environment of emerging economies on IT capability. It also clarifies the impact of knowledge breadth and knowledge depth on digital innovation.

Innovative use of enterprise systems (ES) by employees is essential for organisations to benefit from huge investments in such systems. Drawing on job demands-resources (JDR) theory, this study explores how stressors (i.e. challenge and hindrance stressors) influence employees' innovative use of ES, as well as considering the moderating effects of IT mindfulness.

Data were collected from a longitudinal survey of 152 employees in a large financial service company in China. Hierarchical multiple regression was used to test the research model.

Results showed that challenge stressors exerted a positive effect and hindrance stressors had no significant effect on innovative use of ES. Furthermore, we found that IT mindfulness weakened the positive effect of challenge stressors and the negative effect of hindrance stressors on innovative use of ES.

This study is among the first to extend the research of innovative use of ES by considering two types of stressors based on the JDR theory. Besides, new insights are provided on how to promote employees' innovative use of ES in the post-acceptance stage according to the different levels of IT mindfulness of employees.

The coal bed methane resources distribution of Handan - Fengfeng Mining area has the features of "richness in the midland and north while poorness in the south, and richness in the east while poorness in the west. Through the analysis of the geological factors causing the above phenomena, we get that: the coal metamorphism and hydrogeological condition are the major controlling factors, the former controls the north and south difference of coal bed methane resources distribution from the two aspects covering gas-generated quantity and adsorption capacity, while the latter controls the east and west difference of coal bed methane resources distribution; syncline and good cap rock conditions are necessary conditions for coal bed methane enrichment, but not the reason for causing the difference of coal bed methane resources distribution.

The purpose of this paper is to perform a systematic review of articles that have used the unified theory of acceptance and use of technology (UTAUT).

The results produced in this research are based on the literature analysis of 174 existing articles on the UTAUT model. This has been performed by collecting data including demographic details, methodological details, limitations, and significance of relationships between the constructs from the available articles based on the UTAUT.

The findings indicated that general purpose systems and specialized business systems were examined in the majority of the articles using the UTAUT. The analysis also indicated that cross-sectional approach, survey methods, and structural equation modelling analysis techniques were the most explored research methodologies whereas SPSS was found to be the largely used analysis tools. Moreover, the weight analysis of independent variables indicates that variables such as performance expectancy and behavioural intention qualified for the best predictor category. Moreover, the analysis also suggested that single subject or biased sample as the most explored limitation across all studies.

The search activities were centered on occurrences of keywords to avoid tracing a large number of publications where these keywords might have been used as casual words in the main text. However, we acknowledge that there may be a number of studies, which lack keywords in the title, but still focus upon UTAUT in some form.

This is the first research of its type which has extensively examined the literature on the UTAUT and provided the researchers with the accumulative knowledge about the model.