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Although governments have used social media platforms to interact with the public in an attempt to minimize anxiety and provide a forum for public discussion during the pandemic, governments require sufficient crisis communication skills to engage citizens in taking appropriate action effectively. This study aims to examine how the National Health Commission of China (NHCC) has used TikTok, the leading short video–based platform, to facilitate public engagement during COVID-19.

Building upon dual process theories, this study integrates the activation of information exposure, prosocial interaction theory and social sharing of emotion theory to explore how public engagement is related to message sensation value (MSV), media character, content theme and emotional valence. A total of 354 TikTok videos posted by NHCC were collected during the pandemic to explore the determinants of public engagement in crises.

The findings demonstrate that MSV negatively predicts public engagement with government TikTok, but that instructional information increases engagement. The presence of celebrities and health-care professionals negatively affects public engagement with government TikTok accounts. In addition, emotional valence serves a moderating role between MSV, media characters and public engagement.

Government agencies must be fully aware of the different combinations of MSV and emotion use in the video title when releasing crisis-related videos. Government agencies can also leverage media characters – health professionals in particular – to enhance public engagement. Government agencies are encouraged to solicit public demand for the specific content of instructing information through data mining techniques.

This study aims to examine how the knowledge breadth and depth of a patent affect its likelihood of being pledged. It also seeks to explore whether these relationships change diversely in different technological environments.

A complementary log-log model with random effects was conducted to test the hypotheses using a unique data set consisting of 348,927 invention patents granted by the China National Intellectual Property Administration from 1985 to 2015 belonging to 74,996 firms.

The findings reveal that both knowledge breadth and depth of a patent positively affect its likelihood of being pledged. Furthermore, the knowledge breadth and depth entail different degrees of superiority in different technological environments.

This study focuses on the effect of an individual patent’s knowledge base on its likelihood of being selected as collateral. It does not consider the influence of the overall knowledge characteristics of the selected patent portfolio.

Managers need to pay attention to patents’ knowledge characteristics and the changes in technological environments to select the most suitable patents as collateral and thus improve the success rate of pledge financing.

This study explores the impact of multidimensional characteristics of knowledge base on patent pledge financing within a systematic theoretical framework and incorporates technological environments into this framework.

Coal is the basic energy and essential resource in China, which is crucial to the economic lifeline and energy security of the country. Coal mining has been ever exposed to potential safety risks owing to the complex geologic environment. Effective safety supervision is a vital guarantee for safe production in coal mines. This paper aims to explore the impacts of the internet+ coal mine safety supervision (CMSS) mode that is being emerged in China.

In this study, the key factors influencing CMSS are identified by social network analysis. They are used to develop a multiple linear regression model of law enforcement frequency for conventional CMSS mode, which is then modified by an analytical hierarchy process to predict the law enforcement frequency of internet+ CMSS mode.

The regression model demonstrated high accuracy and reliability in predicting law enforcement frequency. Comparative analysis revealed that the law enforcement frequency in the internet+ mode was approximately 40% lower than the conventional mode. This reduction suggests a potential improvement in cost-efficiency, and the difference is expected to become even more significant with an increase in law enforcement frequency.

To the best of the authors’ knowledge, this is one of the few available pieces of research which explore the cost-efficiency of CMSS by forecasting law enforcement frequency. The study results provide a theoretical basis for promoting the internet+ CMSS mode to realize the healthy and sustainable development of the coal mining industry.

Drawing upon work-home resources model, this study aims to investigate how and when humble leadership influences followers’ work–family enrichment. Specifically, this study focuses on the mediating role of thriving at work and moderating role of promotion focus.

Data were collected from 292 employees of science and technology enterprises in China through a three-wave questionnaire survey. Hierarchical regression analysis and bootstrapping approach were employed to test hypotheses.

This study found that thriving at work significantly mediated the relationship between humble leadership and work–family enrichment. Promotion focus strengthened the positive relationship between humble leadership and thriving at work and the indirect effect of humble leadership on work–family enrichment through thriving at work.

The findings of this study offer guidance for managers to enhance thriving at work and improve employees’ work–family experiences.

First, this study explores the work-to family spillover effects of humble leadership by examining the family outcomes of humble leadership. Second, this study further uncovers the underlying mechanism between humble leadership and work–family enrichment by demonstrating the mediating role of thriving at work. Third, by exploring the moderating role of promotion focus, this study provides insight into the boundary conditions of the impact of humble leadership.

This study aims to investigate the effects of interaction in agricultural product live rooms, including personalization, responsiveness, and entertainment, on consumers’ purchase intention.

The SOR model has been applied to formulate hypotheses. This study is based on an online survey conducted with a sample of 433 valid questionnaires from Chinese consumers on the TikTok agricultural products live platform. A partial least squares structural equation modeling (PLS-SEM) is used to test the hypotheses.

The findings indicate that (1) interactions (personalization, responsiveness, and entertainment) in the agricultural products live room have a positive effect on perceived values (utilitarian value, symbolic value, and entertainment value); (2) utilitarian value positively affects purchase intention and mediates the effects of personalization and entertainment interactions on purchase intention, respectively; (3) entertainment value positively influences purchase intention and mediates the influence of entertainment interaction on purchase intention.

This study offers theoretical insights into live marketing of agricultural products and practical implications for practitioners of agricultural products in live streaming commerce.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

Given their interrelationship, international market selection (IMS) and entry mode selection (EMS) must be considered jointly if an optimal entry strategy is to be realized. However, researchers in the field of international construction have the tendency to consider IMS and EMS independently or sequentially. Therefore, this paper aims to explore a holistic framework that can accommodate IMS and EMS concurrently and test it using empirical data.

his study includes theoretical and empirical research. In theoretical part, an integrated decision model of IMS and EMS is proposed adopting literature review and theoretical derivation, then hypotheses are developed for the impact of decision-making factors. In the latter part, the IMS and EMS of 54 Chinese contractors in 67 countries were investigated, empirical data are collected according to hypotheses, an ordinal logistic regression model is established for statistics analysis. Finally, findings are drawn by comparing literature-based hypotheses with data-based analysis results.

Results show that empirical data fit theoretical model well. Findings are: IMS and EMS can be integrated into a holistic decision-making framework when be properly sequenced. When IMS and EMS are determined simultaneously, the decision can benefit from a sharing of common information. And the roles of at least 13 common factors are empirically demonstrated in this study.

The integrated decision sequence proposed in this study is applicable for a specific market, and cannot compare multiple alternative markets directly. The decision-making factors identified in this paper do not cover the enterprise strategic objectives and some other factors. Empirical data and some theoretical assumptions are based on the international market entry strategy of Chinese contractors. Therefore, the conclusions may not be completely applicable to global contractors though have certain reference value.

Based on the idea of holistic decision-making of IMS and EMS, this study proposes an international market entry strategy (IMES) sequence and an explicit model for determinants, then tests them with empirical data. This paper provides a new idea to manage IMS and EMS concurrently, which can improve the efficiency of IMES decision-making and avoid missing optimal alternatives. This study paves the way for a practical model and provides reference for contractors' international market entry strategy.

Polyaniline (PANI) has garnered attention for its potential applications in anticorrosion fields because of its unique properties. Satisfactory outcomes have been achieved when using PANI as a functional filler in organic coatings. More recently, research has extensively explored PANI-based organic coatings with self-healing properties. The purpose of this paper is to provide a summary of the active agents, methods and mechanisms involved in the self-healing of organic coatings.

This study uses specific doped acids and metal corrosion inhibitors as active and self-healing agents to modify PANI using the methods of oxidation polymerization, template synthesis, nanosheet carrier and nanocontainer loading methods. The anticorrosion performance of the coatings is evaluated using EIS, LEIS and salt spray tests.

Specific doped acids and metal corrosion inhibitors are used as active agents to modify PANI and confer self-healing properties to the coatings. The coatings’ active protection mechanism encompasses PANI’s own passivation ability, the adsorption of active agents and the creation of insoluble compounds or complexes.

This paper summarizes the active agents used to modify PANI, the procedures used for modification and the self-healing mechanism of the composite coatings. It also proposes future directions for developing PANI organic coatings with self-healing capabilities. The summaries and proposals presented may facilitate large-scale production of the PANI organic coatings, which exhibit outstanding anticorrosion competence and self-healing properties.

Based on person-job fit and self-determination theory, this paper examined the effects of (in)congruence between autonomy expectation and perceived autonomy on proactive behaviour, and the moderating role of humble leadership in this relationship among Chinese public employees.

Data were collected from a two-wave survey, and the research model was tested using polynomial regression and response surface methodology.

Results suggested that employees' proactive behaviour will be highest when autonomy congruence was achieved, while autonomy incongruence led to different levels of proactive behaviour based on the specific situations. Furthermore, the moderating effect of humble leadership was proved such that it accentuated the positive influence of autonomy congruence on proactive behaviour.

Managers should be fully aware of the benefits and importance of person-job fit and strive to reduce autonomy incongruence. Meanwhile, humble leadership should be considered in the context of granting autonomy to boost proactivity.

This paper re-emphasises the importance of autonomy by utilising a congruence perspective to understand the effects of autonomy on proactive behaviour. Meanwhile, it incorporates an important boundary condition, humble leadership, on the effects of autonomy congruence and thus offers a more nuanced understanding. Further, this paper not only highlights the significance of underexplored concepts among public employees, but also extends autonomy (in)congruence study to a new context and culture.

The purpose of this study is to ensure the successful implementation of a landing cushion for the new generation armored vehicles with significantly enhanced quality. Furthermore, to introduce a high-precision landing cushioning analysis model.

To accurately analyze the cushioning performance of the new generation armored vehicles, a nonlinear finite element dynamics model considering the complex travel system was established. The model considered the influence of various nonlinear factors to measure the dynamic response difference between the proposed and traditional models. The cushioning performance of airbags under different landing conditions and their various influence factors were analyzed.

The travel system has a large influence on the key points of the vehicle, whose rear end of the upper deck has a larger acceleration fluctuation compared with the traditional model. The increase in the body material stiffness is helpful to reduce this fluctuation. The established nonlinear finite element model can effectively analyze the landing cushioning performance of airborne armored vehicles. The area of the external airbag vent has a large influence on the cushioning performance, and the cushioning system has excellent cushioning performance under various operating conditions.

This study introduces the travel system, which is ignored by traditional analytical models. The interactions between various types of complex structures are included in the analysis process in its entirety, leading to valuable new conclusions. Quantitatively reveals the analytical errors of traditional simulation models in multiple dimensions and the reasons for their formation. Based on a high-precision simulation model, it is verified that the designed airbag cushioning system has an excellent cushioning effect for the new generation of heavy airborne armored vehicles.

The novelty of this work comes from the need for smooth landing with low overload for a new type of large-load airborne armored vehicle and provides a high-precision model that quantifies the traditional analytical modeling errors and error principle.