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This study aims to develop a polymer cement-based waterproof coating with self-healing capability to efficiently and intelligently solve the building leakage caused by cracking of waterproof materials, along with excellent durability to prolong its service life.

Ion chelators are introduced into the composite system based on ethylene vinyl acetate copolymer emulsion and ordinary Portland cement to prepare self-healing polymer cement-based waterproof coating. Hydration, microstructure, wettability, mechanical properties, durability, self-healing performance and self-healing products of polymer cement-based waterproof coating with ion chelator are investigated systematically. Meanwhile, the chemical composition of self-healing products in the crack was examined.

The results showed that ion chelators could motivate the hydration of C₂S and C₃S, as well as the formation of hydration products (C-S-H gel) of the waterproof coating to improve its compactness. Compared with the control group, the waterproof coating with ion chelator had more excellent water resistance, alkali resistance, thermal and UV aging resistance. When the dosage of ion chelator was 2%, after 28 days of curing, cracks with a width of 0.29 mm in waterproof coating could fully heal and cracks with a width of 0.50 mm could achieve a self-healing efficiency of 72%. Furthermore, the results reveal that the self-healing product in the crack was calcite crystalline CaCO₃.

A novel ion chelator was introduced into the composite coating system to endow it with excellent self-healing ability to prolong its service life. It has huge application potential in the field of building waterproofing.

Motivated by the real-world practice that the boom of the online selling induces a higher product return as well, selecting which online channel mode indicates who takes ownership over the product and thus bears the loss of the product return. This paper aims to seek the optimal online channel modes for the two members in a platform supply chain in the presence of product returns.

This study aims to develop a platform supply chain that consists of one platform company and one supplier. Along with an offline distribution channel, the supplier can choose two alternative online selling modes (i.e. the reselling and agency modes) to sell its product through the online marketplace. This paper applies Stackelberg game to derive the equilibrium with different business scenarios and selects the optimal online channel modes for two parties, respectively. Moreover, this paper extends to a different supply chain with a reverse channel leadership and a different product return policy for testing the robustness.

Several interesting and important results are derived in this paper. Firstly, it is found that the relative pricing are largely relied on the costs of two channels. Secondly, the platform supply chain may benefit from a pure channel rather than the dual-channel when this channel enjoys a relatively low cost and/or a sufficiently high consumer preference. Then, the platform and the supplier act contradictorily when selecting their optimal online channel modes. To be specific, the platform motivates to choose the online reselling mode when both the commission rate and the slotting fee are relatively low, whereas the supplier is likely to select the online agency mode under this circumstance. Finally, a win-win situation in regards to the optimal online channel mode for two parties is achievable with numerical experiments.

Based on the analytical studies, the results derived in the authors’ work can provide managerial insights to assist the supplier and the platform company in determining the operational decision and selecting the optimal online channel mode to deal with consumer returns. In addition, appropriate commission rate along with slotting fee will make both parties achieve a win-win situation in determining their optimal online channel mode.

To the authors’ best knowledge, this paper makes the first move to determine the optimal online channel mode in the content of consumer returns and study how it is affected by different product return policies.

This study focuses on the self-organized cooperative consumption of platform participants on social media platform, and reveals how the brand owner cooperates with two-sided customers to achieve value co-creation.

The authors adopted a case study approach to explore how a Chinese beauty startup developed collaborative networks from 2013 to 2022, and tracked the the changes of network structure and cooperation mechanism.

The study finds that the brand owner cooperates with two-sided customers to integrate resources and establish diverse relational trust, which enhances the evolution of a heterogeneous collaborative network for value co-creation.

The study builds upon traditional dyadic actor-to-actor interactions between providers and customers, develops a novel interaction framework of actor-to-network to explain the value co-creation by collaborative networking, reveals the self-organized mechanism of cooperative consumption on social media.

This paper applies a volume-price probability wave differential equation to propose a conceptual theory and has innovative behavioral interpretations of intraday dynamic market equilibrium price, in which traders' momentum, reversal and interactive behaviors play roles.

The authors select intraday cumulative trading volume distribution over price as revealed preferences. An equilibrium price is a price at which the corresponding cumulative trading volume achieves the maximum value. Based on the existence of the equilibrium in social finance, the authors propose a testable interacting traders' preference hypothesis without imposing the invariance criterion of rational choices. Interactively coherent preferences signify the choices subject to interactive invariance over price.

The authors find that interactive trading choices generate a constant frequency over price and intraday dynamic market equilibrium in a tug-of-war between momentum and reversal traders. The authors explain the market equilibrium through interactive, momentum and reversal traders. The intelligent interactive trading preferences are coherent and account for local dynamic market equilibrium, holistic dynamic market disequilibrium and the nonlinear and non-monotone V-shaped probability of selling over profit (BH curves).

The authors will understand investors' behaviors and dynamic markets through more empirical execution in the future, suggesting a unified theory available in social finance.

The authors can apply the subjects' intelligent behaviors to artificial intelligence (AI), deep learning and financial technology.

Understanding the behavior of interacting individuals or units will help social risk management beyond the frontiers of the financial market, such as governance in an organization, social violence in a country and COVID-19 pandemics worldwide.

It uncovers subjects' intelligent interactively trading behaviors.

Hydro-viscous drive (HVD) clutches are widely used in equipment requiring soft start, such as fans and pumps, to transmit torque and adjust speed by changing the gap distance between friction pairs. This paper aims to propose a novel two-parameter evaluation method for HVD during the mixed lubrication stage. The objective is to develop an effective model that establishes the relationship between these parameters and the actual surface topography.

In the presented methods, the fractal features of the real manufacturing surface are calculated based on the power spectrum function by the ultra-depth three-dimensional microscope. After that, the hybrid friction model of the friction plate is established based on mixed elasto-hydrodynamic lubrication theory, boundary friction model and fractal theory. Then the torque and load bearing characteristics of the clutch are obtained, and the influences of the surface fractal features are investigated and discussed. Finally, the Weierstrass–Mandelbrot function is adopted for the surface topography characterization and evaluation.

The results indicate that the proposed method exhibits good accuracy, while the speed difference between the friction pair exceeds 2,500 rpm. It is concluded that this paper proposed a way to evaluate the torque and loading capacity of HVD considering the real manufacturing surface topography and is helpful for surface optimization.

The originality and value of this study lie in its development of a novel torque and load bearing capacity evaluation method for HVD in mixed lubrication stage, considering manufacturing surface topography and describing the real manufacturing surface.

A cross-domain intelligent software-defined network (SDN) routing method based on a proposed multiagent deep reinforcement learning (MDRL) method is developed.

First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between the root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to acquire global network state information in real time. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a network traffic state prediction mechanism is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time.

Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and open shortest path first (OSPF) routing methods.

Message transmission and message synchronization for multicontroller interdomain routing in SDN have long adaptation times and slow convergence speeds, coupled with the shortcomings of traditional interdomain routing methods, such as cumbersome configuration and inflexible acquisition of network state information. These drawbacks make it difficult to obtain global state information about the network, and the optimal routing decision cannot be made in real time, affecting network performance. This paper proposes a cross-domain intelligent SDN routing method based on a proposed MDRL method. First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to realize the real-time acquisition of global network state information. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a prediction mechanism for the network traffic state is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time. Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and OSPF routing methods.

With the rapid development of social media, many organizations have begun to attach importance to social media platforms. This research studies the management and the use of social media in academic music libraries, taking the Center for Chinese Music Studies of the Chinese University of Hong Kong (CCMS) as a case study.

We conducted a sentiment analysis of posts on Facebook’s public page to analyze the reaction to the posts with some exploratory analysis, including the communication trend and relevant factors that affect user interaction.

Our results show that the Facebook channel for the library has a good publicity effect and active interaction, but the number of posts and interactions has a downward trend. Therefore, the library needs to pay more attention to the management of the Facebook channel and take adequate measures to improve the quality of posts to increase interaction.

Few studies have analyzed existing data directly collected from social media by programming based on sentiment analysis and natural language processing technology to explore potential methods to promote music libraries, especially in East Asia, and about traditional music.

Urbanization is driving the growth of China’s carbon footprint. It’s important to investigate what factors, how and to what extent, affect carbon footprints embedded in various categories of rural and urban households’ consumption.

We employ an environmental extended input-output model to assess and compare the rural-urban household carbon footprints and perform a multivariant regression analysis to identify the varying relationships of the determinants on rural and urban household carbon footprints based on the panel data of Chinese households from 2012 to 2018.

The results show evidence of urbanity density effect on direct carbon footprints and countervailing effect on indirect carbon footprints. The old dependency ratio has no significant effect on rural family emissions but has a significantly negative effect on urban direct and indirect carbon footprints. A higher child dependency ratio is associated with less rural household carbon emissions while the opposite is true for urban households. Taking advantage of recycled fuel saves direct carbon emissions and this green lifestyle benefits urban households more by saving more carbon emissions. There is a positive relationship between consumption structure ratio and direct carbon footprints while a negative relationship with indirect carbon footprints and this impact is less significant for urban households. The higher the price level of water, electricity and fuel, the lower the rural household’s direct carbon footprints. Private car ownership consistently augments household carbon footprints across rural and urban areas.

This paper provides comprehensive findings to understand the relationships between an array of determinants and China’s rural-urban carbon emissions, empowering China’s contribution to the global effort on climate mitigation.

“Metaverse” has become a buzzword in the Chinese stock market. However, it remains unclear whether a firm's metaverse-related announcements will elicit positive stock market reactions. Whether and how stakeholder reactions are influenced by a firm's metaverse-related readiness also needs to be further explored. This study aims to discuss the aforementioned objective.

The authors derived a set of factors based on readiness theory and business ecosystem literature and extend them into the context of the metaverse. The authors used a sample of 642 Chinese listed firms in 2021 to investigate the hypotheses through the event study.

The study’s findings show that metaverse coverage induces a positive stock market reaction, but it is subject to three moderating effects. The authors introduce the novel concepts of IT readiness, ecosystem readiness and digital infrastructure readiness as the moderators. Stakeholders perceive metaverse announcements as overhyped, and stock prices do not fluctuate significantly after a metaverse announcement when the listed firms are not ready to embrace the metaverse.

This study is one of the first that introduces the event study method into the metaverse research, and it reveals that different levels of readiness influence stakeholders' evaluations and reactions to corporate metaverse coverage. This provides empirical evidence on metaverse development in China from the stock market's perspective.

As foreign direct investment (FDI) plays an important role in economic globalization. This paper examines the structural features of the global FDI network based on FDI flows data and changes in the position of countries within the network.

In order to study the structural characteristics of the global FDI network and the status and changes of countries in the global FDI network, the authors build the investment network and apply the QAP (Quadratic Assignment Procedure) analysis to examine the evolutionary characteristics of the network and its influencing factors.

The global FDI network becomes more interconnected and has a clear “core-periphery” structure. The network connections and volumes have increased dramatically and most countries spread their assets across multiple countries, while only a handful of countries have concentrated investments. The topological structure of the global FDI network has changed noticeably, although this process has been slow and stable and countries in the core position have remained largely intact. The authors find that trade relations between countries, geographic distance and differences in economic size, income levels and institutional environments all have a significant impact on the global FDI network.

Although we find some valuable results, some aspects need further investigation. For example, how a country uses the investment network to boost its economy and how the different industries in the investment network change over time. It is important to get the industry-level details to understand the impact of the global investment network from a government's perspective.

FDI affects the distribution of international capital and contributes to the development of the global economy. Therefore, it is important to study the characteristics of the global FDI network and its development patterns. With more understanding about the network as well as its evolutionary pattern, the government can possibly carry out some policies to promote direct investments as well as economic development.

All countries should actively engage in international direct investments and strengthen their economic ties. At the same time, they can put more emphasis on inward or outward FDI based on their own level of economic development to better establish the circulation channel for domestic and international capital.

This paper examines foreign direct investments through the lens of a global network. In contrast to traditional bilateral studies, this paper focuses on the network structure and evolution, reflecting the dynamics of the entire direct investment system as well as the changing positions of participating countries.