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Based on social exchange theory and self-determination theory, this study explores the influence mechanism of empowering leadership on employees’ creative deviance and innovation performance.

The data were collected from 312 employees on Internet and other high-tech corporation in China. Hierarchical linear regression models and bootstrapping analysis outlined by Hayes were used to test the hypotheses.

Empowering leadership is positively correlated with employees’ innovation performance (EIP), and employees’ creative deviance plays an intermediary role in the above relationship. Power distance positively moderates the relationship between empowering leadership and employees’ creative deviance. Time pressure moderates the moderating effect of power distance on empowering leadership and employees’ creative deviance.

This study advances the empowering leadership and employees’ innovation performance by establishing creative deviance as the mediator. This study is also helpful to clarify the role of time press and power distance as boundary condition in the relationship between empowering leadership and employees’ creative deviance, which have certain reference significance for organization practices.

Prefabricated building (PB) has high technical requirements and is susceptible to safety accidents, and its construction occupational health and safety (OHS) problems should not be ignored. To promote the better development of PB, this study aims to measure their construction safety management level and propose corresponding countermeasures.

By systematically combing the relevant literature, this study extracts the influencing factors that appear frequently in several studies and categorizes them according to six dimensions: people, materials and components, technology, mechanical equipment, environment and system. Combining expert opinions, the measurement index system, including 6 primary indexes and 24 secondary indexes, is constructed. The structural entropy weight (SEW) method is applied to calculate the index weights. The cloud matter element (CME) model based on the weights is constructed to determine the level of construction occupational health and safety management (COHSM). A project case of a training building is used to verify it. The results obtained from the model are compared with those from other measurement models to verify the feasibility of the model in measuring the level of COHSM for PB.

The calculated weights show that technology is the most important for the COHSM of PB. The management level of the project in terms of people, materials and components, technology, machinery and equipment, environment and system is Level II good. The overall safety management level is also Level II, which is good. The model of this study is consistent with other model measurements. The methodology of this study yields reasonable and realistic results.

This study is the first to include occupational health dimensions in the research on the construction safety management of PB, which not only covers the key elements in traditional construction safety management but also considers the impact of the construction process, material use and technology of PB on safety management, making the measurement index system more scientific. Meanwhile, the introduction of the CME model based on the SEW method effectively solves the deficiencies of the traditional method in dealing with ambiguity and uncertainty and provides practitioners with more accurate and comprehensive measurement results. It helps practitioners formulate a more scientific management plan in combination with the actual situation and provides a guiding idea and practical path for the COHSM of similar projects.

The purpose of this research is to address the existing gap in the study of construction and demolition waste (C&DW) by focusing on its impact on human health throughout the entire life cycle. And this research provides a comprehensive assessment model that incorporates the release of gaseous pollutants and particulate matter during the whole life cycle of C&DW, thereby contributing to a more holistic understanding of its impact on human health.

The research was conducted in two stages. Firstly, the quantitative model framework of pollutants emitted by C&DW was established. Three types of pollutants were considered, namely nitrogen dioxide (NO₂), sulfur dioxide (SO₂) and inhalable particulate matter (PM10). Second, disability-adjusted life year (DALY) and willingness to pay (WTP) assessments were used to provide a monetary quantified health impact for pollutants released by C&DW.

The results show that the WTP value of PM10 is the highest among all pollutants and 8.68E+07 dollars/a, while the WTP value in the disposal stage accounts for the largest proportion compared to the generation and transportation stage. These findings emphasize the importance of PM10 and C&DW treatment stage for pollutant treatment.

The results of this study are of great significance for the management department to optimize the construction management scheme to reduce the total amount of pollutants produced by C&DW and its harm to human health. Meanwhile, this study fills the gap in existing research on the impact assessment of C&DW on human health throughout the whole life cycle, and provides reference and basis for future research and policy formulation.

The purpose of this study is to explore the interfacial adhesion between superhydrophobic coatings FC-X (X = 1%, 2%, 3%, 4% and 5%) and the concrete substrate, along with the impact of FC-X on the water repellency characteristics of the concrete substrate.

One synthetic step was adopted to prepare novel F-SiO₂ NP hybrid fluororesin coating. The impact of varying mass fractions of F-SiO₂ NPs on the superhydrophobicity of FC-X was analyzed and subsequently confirmed through water contact angle (WCA) measurements. Superhydrophobic coatings were simply applied to the concrete substrate using a one-step spraying method. The interfacial adhesion between FC-X and the concrete substrate was analyzed using tape pasting tests and abrasion resistance measurements. The influence of FC-X on the water repellency of the concrete substrate was investigated through measurements of water absorption, impermeability and electric flux.

FC-4% exhibits excellent superhydrophobicity, with a WCA of 157.5° and a sliding angle of 2.3°. Compared to control sample, FC-X exhibits better properties, including chemical durability, wear resistance, adhesion strength, abrasion resistance, water resistance and impermeability.

This study offers a thorough investigation into the practical implications of enhancing the durability and water repellency of concrete substrates by using superhydrophobic coatings, particularly FC-4%, which demonstrates exceptional superhydrophobicity alongside remarkable chemical durability, wear resistance, adhesion strength, abrasion resistance, water resistance and impermeability.

Through the examination of the interfacial adhesion between FC-X and the concrete substrate, along with an assessment of FC-X’s impact on the water repellency of the concrete, this paper provides valuable insights into the practical application of superhydrophobic coatings in enhancing the durability and performance of concrete materials.

In recent years, the incidence of cardiovascular disease has continued to rise, and early screening and prevention are especially critical. Phonocardiography (PCG) and electrocardiography (ECG), as simple, cost-effective and non-invasive tests, are important tools for clinical analysis. However, it is difficult to fully reflect the complexity of the cardiovascular system using PCG or ECG tests alone. Combining the multimodal signals of PCG and ECG can provide complementary information to improve the detection accuracy. Therefore, the purpose of this paper is to propose a multimodal signal classification method based on continuous wavelet transform and improved ResNet18.

The classification method is based on the ResNet18 backbone, and the ResNet18 network is improved by embedding the global grouped coordinate attention mechanism module and the improved bidirectional feature pyramid network. Firstly, a data acquisition system was built using a MEMS-integrated PCG-ECG sensor to construct a private data set. Second is the time-frequency transformation of PCG and ECG synchronized signals on public and private data sets using continuous wavelet transform. Finally, the time-frequency images are categorized.

The global grouped coordinate attention mechanism and bidirectional feature pyramid network modules proposed in this paper significantly enhance the model’s performance. On public data sets, the method achieves precision, sensitivity, specificity, accuracy and F1 score of 97.96%, 98.51%, 97.58%, 98.08% and 98.23%, respectively, which represent improvements of 3.54%, 3.92%, 4.18%, 4.03% and 3.72% compared to ResNet18. Additionally, it demonstrates a clear advantage over existing mainstream algorithms. On private data sets, the method’s five metrics are 98.15%, 98.76%, 98.08%, 98.42% and 98.45%, further validating the model’s generalization ability.

The method proposed in this paper not only improves the accuracy and efficiency of the test but also provides an effective solution for early screening and prevention of cardiovascular diseases.

Drawing on the stakeholder theory, this study aims to empirically analyse the impact of platform enterprises’ corporate social responsibility (CSR) announcements on corporate stock market value. This study also estimates the moderating effect of stakeholder orientation and responsibility categories of CSR announcements, the platform enterprise type and the degree of CSR disclosure.

The event study method is used to analyse the change in stock market value of 191 CSR announcements from 137 Chinese platform enterprises. In addition, a case analysis is presented for two platform enterprises with the best practices to validate and complement study findings.

CSR announcements improve platform enterprises’ stock market value. Specifically, CSR announcements responding to platform enterprises’ external stakeholders, and CSR announcements with economic responsibility, have obvious positive impacts on stock market value. Furthermore, the maker platform’s CSR announcement has a more positive impact on stock market value than the exchange platform.

To the best of the authors’ knowledge, this study is the first attempt to identify the link between platform enterprises’ CSR announcements and stock market performance by empirical evidence, and it contributes to new knowledge of operating and evaluating platform enterprises’ CSR.

Artificial intelligence (AI) services are vital in enhancing customer experience and purchase intentions in the international online fashion retail sector. This study explores customers’ intentions to use AI-enabled services, focusing on transaction utility, trust and product uniqueness across the customer journey in the context of international online fashion stores. This study also assesses how privacy moderates customer intentions.

This study adopted a longitudinal research design and purposive sampling technique to collect a total of 566 participants. The final data were analyzed using IBM SPSS Amos version 21 software.

The study highlights the significance of transaction utility, trust and product uniqueness in AI integration across the customer journey (pre-purchase, during purchase and post-purchase stages). Most of the direct relationships are significant, except the relationship between the during purchase and post-purchase stages. With a few exceptions, AI integration commonly does not mediate the relationship between antecedents and intention to use AI-enabled services. Privacy moderates AI integration in post-purchase, during purchase and intention to use AI-enabled services, except in the pre-purchase stage.

This study bridges important gaps in the literature by integrating AI-enabled services and customer behavior, contributing to a broader knowledge of customer interactions in global e-commerce fashion stores. The study examines multiple attributes that impact intention, such as transaction utility, trust, product uniqueness, AI integration in three stages of purchases (pre-purchase, during purchase and post-purchase) and privacy, using three major theories: mental accounting theory, trust commitment theory and commodity theory.

Interorganizational knowledge sharing (IKS) is an important strategy for organizations to obtain exterior knowledge resources to enhance innovation and value co-creation in megaprojects. However, little research has deeply investigated multiple attributes of organizational motivations and the combinatorial effects of these motivations on facilitating IKS. Based on resource dependency theory, this study examined the net and combinatorial effects of four types of motivations (i.e. image motivations, reactive motivations, project-based co-creative economic motivations and cross-project co-creative economic motivations).

Questionnaire surveys were administered to 244 practitioners with over 10 years of experience in construction megaprojects. The collected data were analyzed using a partial least square-structural equation model (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA).

The findings of PLS-SEM support that image and project-based co-creative economic motivations positively drive IKS. The results of fsQCA reveal three types of efficacious configurations, including comprehensive benefits-integrated driven, short-term benefits-dominated driven and long-term benefits-dominated driven configurations.

This study provides insight into broadening the understanding of multidimensional organizational motivations for IKS and fostering the configurational perspective to their effects with the idea that one size does not fit all. Managers should develop effective interventions considering the combination of various motivations and use multi-layered incentive structures that reward both immediate project-specific outcomes and long-term relationship-building efforts.

While the impact of digitalization on businesses has been extensively studied, the influence of digitalization on marketing outcomes in private enterprises has not received sufficient attention. The current study aims to examine how and when digitalization affects international marketing decisions in the context of private enterprises.

This study employs data from a survey of Chinese private enterprises conducted in 2020, which constitutes the world's largest dataset of its kind. Nearly 19,000 samples were included in the study. Additionally, we also incorporate supplementary data on digitalization in the Chinese region. Employing various methods, this study empirically and robustly examines the proposed research framework within the context of Chinese private enterprises.

Based on the resource-based view and agency theory, this paper found that digitalization can positively impact private enterprises’ direct and indirect international marketing decisions. Furthermore, we introduce the inclusion of innovation capacity and board governance as moderators in the model and find that board governance attenuates the influence of digitalization on international marketing decisions, while innovation capacity enhances the impact of digitalization on direct international marketing but diminishes its effect on indirect international marketing.

This study advances the understanding of the impact of digitalization on international marketing in private enterprises, thereby addressing the gap in the limited focus on digitalization in private enterprises. It also demonstrates how private enterprises effectively utilize digitalization to gain marketing advantages in the international market.

This study aims to provide a timely review of hospitality and tourism live streaming (HTLS) research, aiming to understand the intellectual foundation in the past and identify opportunities for future research.

This study collected 56 papers from journals in the Social Science Citation Index database or the Australian Business Deans Council journal quality list and adopted a hybrid systematic literature review combining bibliometric analysis and the theory-context-characteristics-method framework-based approach. Additionally, a cross-tabulation analysis was conducted to compare the research on two specific forms of HTLS – tourism e-commerce live streaming (TEcLS) and travel live streaming.

The study found that the current research lacks in-depth theoretical insights, focuses on China as the national context and viewers as the research subject, mainly uses online surveys and lacks first-order knowledge. Moreover, it identified five research themes, including the impact of HTLS on viewer behavior, purchase behavior in HTLS and introduction of HTLS, within which eight categories of research constructs, such as viewer-related, streamer-related and relationship-related, are applied.

In terms of research, the study reveals various gaps in the existing literature and provides potential research directions to advance the field. As for practice, it offers valuable strategies for practitioners to optimize their marketing efforts using HTLS.

This study provides an up-to-date review of the HTLS field through a systematic and reproducible method. It offers critical discussions and suggestions for academic research and industry practices.