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The primary objectives of this article are to systematically explore whether and how certain WeChat use motives could lead to bridging social capital, bonding social capital and civic engagement among young people.

The data was collected from a large-scale online survey of 1208 young people in mainland China. Zero-order correlation analyses and structural equation modeling were carried out to examine the corresponding hypotheses.

Obtained findings show that WeChat use for informational and social motivations are positively associated with bonding and bridging social capital. Moreover, bonding social capital could mediate the relationship between WeChat usage for informational and relational motivations and civic engagement.

Theoretically, this article underlines the unique social and technological affordances of WeChat by exploring mobile social media use and how it would contribute to the quality of democracy by fostering young people's engagement in civic life. Practically, bridging and bonding social capital play significant roles in enhancing young people's civic engagement, which could be the meaningful resource for mobile social media designers, managers and government officials.

These obtained outcomes underlined the vital role of these newly emerging communication technologies in fostering democratic involvement and production of social capital in contemporary socially networked society.

By building and examining an integral model, the principal objectives of this research are to systematically explore how indirect and direct network externalities lead to user loyalty toward WeChat through the mediating effect of perceived gratifications.

The data were collected through an online survey of 688 young people in Mainland China. To empirically assess the conceptual model, zero-order correlation analyses and structural equation modeling were carried out utilizing web-based data.

Path analysis results demonstrate that indirect network externalities and direct network externalities exert a significant impact on users' hedonic gratifications and utilitarian gratifications. Moreover, the study discovers the significant mediating influences of utilitarian gratifications on the association between indirect network externalities and user loyalty.

Theoretically, this article may extend the scope of diverse studies on the association between network externalities and perceived gratifications and offer fresh insights into how mobile social media could actually improve user loyalty through enhancing perceived values among younger generation. Practically, this research assists mobile social media practitioners in retaining users and gaining competitive advantages over rival applications.

Although the extraordinary growth of WeChat has successfully become the dominant media by which individuals develop interpersonal network and contact with others, the roles of perceived gratifications between network externalities and user loyalty toward WeChat have not yet been investigated in depth. These obtained outcomes not only enrich the existing literature regarding the relationship between network externalities and affective response, but also offer fresh insights to mobile social media designers, marketers and users.

Building upon uses and gratifications (UG) theory and social exchange theory, the current study establishes a theoretical model to examine the underlying relationship between customer motivations, active participation and electronic word-of-mouth (e-WOM) and purchase intentions on WeChat.

The data were gathered in a web-based survey of 301 WeChat users in mainland China. To empirically verify the proposed hypotheses, confirmatory factor analysis (CFA) and structural equation modeling (SEM) were employed using online data.

Path analysis outcomes demonstrate that functional, hedonic and social motivations positively affect WeChat users' active participation. In addition, active participation significantly influences e-WOM intention while showing no correlation with purchase intention.

Theoretically, this article can enrich the extant system of relevant theories and offer a fresh perspective for further research on the generation of consumers' e-WOM intention and purchase intention in the WeChat context. Practically, the research outcomes provide insight for companies on how to motivate customers to participate in online activities, which subsequently improve WeChat users' willingness in conducting e-WOM communication and making purchase decisions.

Although mobile social media could serve as an influential marketing vehicle for individuals' engagement in social and commercial activities in today's mobile-matured environment, the substantial impact of active engagement on the relationship between customer motivation and purchase intention remains insufficiently explored. The outcomes not only contribute to the current body of knowledge, but also offer several managerial guidance for companies that pay attention to mobile social media marketing in a contemporary mobile media-saturated society.

Building upon social capital theoretical foundation, the principal purpose of present research is to construct a conceptual research model and uncover the intricate relationships between WeChat usage, social capital and civic participation behaviors among young people.

A large cross-sectional valid data from 1,238 young people in mainland China were gathered to examine the hypothesized research model. Descriptive analyses, correlation analysis and structural equation modeling (SEM) were sequentially undertaken to determine dynamic interrelationships among main constructs.

The empirical findings demonstrate that WeChat usage positively impacts young people's social interaction ties, the guanxi network and shared goals. Moreover, social interaction ties and shared goals are positively associated with their online civic engagement. Furthermore, the guanxi network is positively associated with both online and offline civic engagement.

Theoretically, this research is the first to explicitly explore the influence mechanism of WeChat use intensity on different dimensions of individual-level social capital and civic engagement. Practically, these obtained results can be beneficial to the comprehending of whether and how WeChat is a resource for social capital and civic involvement.

Despite mobile social media, especially WeChat, has achieved immense popularity in contemporary mainland China, the potential influence of this emerging technology use on individuals' differential dimensions of social capital and civic engagement has not been systematically investigated. The study may not only offer fresh insight into innovative features of WeChat but also contribute to broader controversies regarding the impact of mobile-mediated communication on individuals' daily civic lives.

In light of the stimulus-organism-response (SOR) theoretical paradigm, this paper explores how information relevance and media richness affect social network exhaustion and, moreover, how social network exhaustion ultimately leads to health anxiety and COVID-19-related stress.

The conceptual model is explicitly analyzed and estimated by using data from 309 individuals of different ages in mainland China. Confirmatory factor analysis (CFA) and structural equation modeling (SEM) were utilized to validate the proposed hypotheses through the use of online data.

The findings suggest that information relevance is negatively associated with social network exhaustion. In addition, social network exhaustion is a significant predictor of health anxiety and stress. Furthermore, information relevance and media richness can indirectly influence health anxiety and stress through the mediating effect of social network exhaustion.

Theoretically, this paper verifies the causes and consequences of social network exhaustion during COVID-19, thus making a significant contribution to the theoretical construction and refinement of this emerging research area. Practically, the conceptual research model in this paper may provide inspiration for more investigators and scholars who are inclined to further explore the different dimensions of social network exhaustion by utilizing other variables.

Although social network exhaustion and its adverse consequences have become prevalent, relatively few empirical studies have addressed the deleterious effects of social network exhaustion on mobile social media users’ psychosocial well-being and mental health during the prolonged COVID-19. These findings have important theoretical and practical implications for the rational development and construction of mobile social technologies to cultivate proper health awareness and mindset during the ongoing worldwide COVID-19 epidemic.

Public-private partnership (PPP) projects for construction waste recycling have become the main approach to construction waste treatment in China. Risk sharing and income distribution of PPP projects play a vital role in achieving project success. This paper is aimed at building a practical and effective risk sharing and income distribution model to achieve win–win situation among different stakeholders, thereby providing a systematic framework for governments to promote construction waste recycling.

Stakeholders of construction waste recycling PPP projects were reclassified according to the stakeholder theory. Best-worst multi–criteria decision-making method and comprehensive fuzzy evaluation method (BWM–FCE) risk assessment model was constructed to optimize the risk assessment of core stakeholders in construction waste recycling PPP projects. Based on the proposed risk evaluation model for construction waste recycling PPP projects, the Shapley value income distribution model was modified in combination with capital investment, contribution and project participation to obtain a more equitable and reasonable income distribution system.

The income distribution model showed that PPP Project Companies gained more transaction benefits, which proved that PPP Project Companies played an important role in the actual operation of PPP projects. The policy change risk, investment and financing risk and income risk were the most important risks and key factors for project success. Therefore, it is of great significance to strengthen the management of PPP Project Companies, and in the process of PPP implementation, the government should focus on preventing the risk of policy changes, investment and financing risks and income risks.

The findings from this study have advanced the application methods of risk sharing and income distribution for PPP projects and further improved PPP project-related theories. It helps to promote and rationalize fairness in construction waste recycling PPP projects and to achieve mutual benefits and win–win situation in risk sharing. It has also provided a reference for resource management of construction waste and laid a solid foundation for long-term development of construction waste resources.

PPP mode is an effective tool for construction waste recycling. How to allocate risks and distribute benefits has become the most important issue of waste recycling PPP projects, and also the key to project success. The originality of this study resides in its provision of a holistic approach of risk allocation and benefit distribution on construction waste PPP projects in China as a developing country. Accordingly, this study adds its value by promoting resource development of construction waste, extending an innovative risk allocation and benefit distribution method in PPP projects, and providing a valuable reference for policymakers and private investors who are planning to invest in PPP projects in China.

The application of circular economy (CE) has received wide coverage in the built environment, including public-private partnership (PPP) infrastructure projects, in recent times. However, current studies and practical implementation of CE are largely associated with construction demolition, waste and recycling management. Few studies exist on circular models and success factors of public infrastructures developed within the PPP contracts. Thus, the main objective of this article is to identify the models and key success factors associated with CE implementation in PPP infrastructure projects.

A systematic review of the literature was undertaken in this study using forty-two (42) peer-reviewed journal articles from Scopus, Web of Science, Google Scholar and PubMed.

The results show that environmental factors, sustainable economic growth, effective stakeholder management, sufficient funding, utilization of low-carbon materials, effective supply chain and procurement strategies facilitate the implementation of CE in PPP infrastructure projects. Key CE business models are centered around the extension of project life cycle value, circular inputs and recycling and reuse of projects.

Although the study presents relevant findings and gaps for further investigations, it has a limited sample size of 42 papers, which is expected to increase as CE gain more prominence in PPP infrastructure management in future.

The findings are relevant for decision-making by PPP practitioners to attain the social, economic and environmental benefits of transitioning to circular infrastructure management.

This study contributes to articulating the key models and measures toward sustainable CE in public infrastructure development.

Building a smart city is a necessary path to achieve sustainable urban development. Smart city public–private partnership (PPP) project is a necessary measure to build a smart city. Since there are many participants in smart city PPP projects, there are problems such as uneven distribution of risks; therefore, in order to ensure the normal construction and operation of the project, the reasonable sharing of risks among the participants becomes an urgent problem to be solved. In order to make each participant clearly understand the risk sharing of smart city PPP projects, this paper aims to establish a scientific and practical risk sharing model.

This paper uses the literature review method and the Delphi method to construct a risk index system for smart city PPP projects and then calculates the objective and subjective weights of each risk index through the Entropy Weight (EW) and G1 methods, respectively, and uses the combined assignment method to find the comprehensive weights. Considering the nature of the risk sharing problem, this paper constructs a risk sharing model for smart city PPP projects by initially sharing the risks of smart city PPP projects through Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to determine the independently borne risks and the jointly borne risks and then determines the sharing ratio of the jointly borne risks based on utility theory.

Finally, this paper verifies the applicability and feasibility of the risk-sharing model through empirical analysis, using the smart city of Suzhou Industrial Park as a research case. It is hoped that this study can provide a useful reference for the risk sharing of PPP projects in smart cities.

In this paper, the authors calculate the portfolio assignment by EW-G1 and construct a risk-sharing model by TOPSIS-Utility Theory (UT), which is applied for the first time in the study of risk sharing in smart cities.

The optimal payment in the whole operation and maintenance period of water environment treatment PPP projects has become the main approach to realize sustainable development of projects. This study is aimed at constructing an effective payment model for the whole life period of projects to achieve win-win among all stakeholders, so as to provide a theoretical reference and managerial implications for the public sector in the whole operation and maintenance period.

In the whole operation and maintenance period of water environment treatment PPP projects, this article investigates how the public sector optimizes the payment in the whole operation and maintenance period of projects. Firstly, the projects' whole operation and maintenance period is divided into several stages according to the performance appraisal period. And then, the multi-stage dynamic programming model is constructed to design the payment construct model for the public sector in each performance appraisal stage. The payment from the public sector is the decision variable, and the deduction from the private sector is a random variable.

The optimal payment model showed that the relatively less objective weight of public sector leaded to its relatively more total payment and vice versa. Therefore, the sustainable development of the projects can only be ensured when the objective weights both of them should be balanced. Additionally, the deduction from the performance appraisal of private sector plays an important role in the model construction. The larger deduction the private sector undertakes, the smaller profits private sector has. Since the deduction at each stage is a random variable, the deduction varies with the different probability distributions obeyed by the practical deduction in each stage.

The findings from this study have provided theoretical and application references, and some managerial implications are also given. First, the improvement of the pricing system of public sector should be accelerated. Second, the reasonable profit of the private sector must be guaranteed. While pursuing the maximization of social benefits, the public sector should make full use of the price sharing mechanism in the market and supervise the real income situation of the private sector. Third is increasing the public to participate in pricing. Additionally, it is a limitation that the deduction is assumed to conform to a uniform distribution in this study. Other probability distributions on deduction can be essentially further sought, so as to be more line with the actual situation of the projects.

The optimal payment in whole operation and maintenance period of the projects has become an important issue, which is a key to project success. This study constructs a multi-stage dynamic programming model to optimize payment in the whole period of projects. Additionally, this study adds its value through deeply developing the new theories of optimal payment to more suitable for the practical problems, so that to optimize the design of payment mechanism. Meanwhile, a valuable reference for public and private sectors is provided to ensure the sustainable development of the projects.

This paper aims to study the agent learning from expert demonstration data while incorporating reinforcement learning (RL), which enables the agent to break through the limitations of expert demonstration data and reduces the dimensionality of the agent’s exploration space to speed up the training convergence rate.

Firstly, the decay weight function is set in the objective function of the agent’s training to combine both types of methods, and both RL and imitation learning (IL) are considered to guide the agent's behavior when updating the policy. Second, this study designs a coupling utilization method between the demonstration trajectory and the training experience, so that samples from both aspects can be combined during the agent’s learning process, and the utilization rate of the data and the agent’s learning speed can be improved.

The method is superior to other algorithms in terms of convergence speed and decision stability, avoiding training from scratch for reward values, and breaking through the restrictions brought by demonstration data.

The agent can adapt to dynamic scenes through exploration and trial-and-error mechanisms based on the experience of demonstrating trajectories. The demonstration data set used in IL and the experience samples obtained in the process of RL are coupled and used to improve the data utilization efficiency and the generalization ability of the agent.