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This paper aims to study the characteristics and evolution rules of tagging knowledge network for users with different activity levels in question-and-answer (Q&A) community represented by Zhihu.

A random sample of issue tag data generated by topics in the Zhihu network environment is selected. By defining user quality and selecting the top 20% and bottom 20% of users to focus on, i.e. top users and bot users, the authors apply time slicing for both types of data to construct label knowledge networks, use Q-Q diagrams and ARIMA models to analyze network indicators and introduce the theory and methods of network motif.

This study shows that when the power index of degree distribution is less than or equal to 3.1, the ARIMA model with rank index of label network has a higher fitting degree. With the development of the community, the correlation between tags in the tagging knowledge network is very weak.

It is not comprehensive and sufficient to classify users only according to their activity levels. And traditional statistical analysis is not applicable to large data sets. In the follow-up work, the authors will further explore the characteristics of the network at a larger scale and longer timescale and consider adding more node features, including some edge features. Then, users are statistically classified according to the attributes of nodes and edges to construct complex networks, and algorithms such as machine learning and deep learning are used to calculate large-scale data sets to deeply study the evolution of knowledge networks.

This paper uses the real data of the Zhihu community to divide users according to user activity and combines the theoretical methods of statistical testing, time series and network motifs to carry out the time series evolution of the knowledge network of the Q&A community. And these research methods provide other network problems with some new ideas. Research has found that user activity has a certain impact on the evolution of the tagging network. The tagging network followed by users with high activity level tends to be stable, and the tagging network followed by users with low activity level gradually fluctuates.

Research has found that user activity has a certain impact on the evolution of the tagging network. The tagging network followed by users with high activity level tends to be stable, and the tagging network followed by users with low activity level gradually fluctuates. For the community, understanding the formation mechanism of its network structure and key nodes in the network is conducive to improving the knowledge system of the content, finding user behavior preferences and improving user experience. Future research work will focus on identifying outbreak points from a large number of topics, predicting topical trends and conducting timely public opinion guidance and control.

In terms of data selection, the user quality is defined; the Zhihu tags are divided into two categories for time slicing; and network indicators and network motifs are compared and analyzed. In addition, statistical tests, time series analysis and network modality theory are used to analyze the tags.

The emergence of a coronavirus disease 2019 (COVID-19) epidemic has had a tremendous impact on the world, and the characteristics of its evolution need to be better understood.

To explore the changes of cases and control them effectively, this paper analyzes and models the fluctuation and dynamic characteristics of the daily growth rate based on the data of newly confirmed cases around the world. Based on the data, the authors identify the inflection points and analyze the causes of the new daily confirmed cases and deaths worldwide.

The study found that the growth sequence of the number of new confirmed COVID-19 cases per day has a significant cluster of fluctuations. The impact of previous fluctuations in the future is gradually attenuated and shows a relatively gentle long-term downward trend. There are four inflection points in the global time series of new confirmed cases and the number of deaths per day. And these inflection points show the state of an accelerated rise, a slowdown in the rate of decline, a slowdown in the rate of growth and an accelerated decline in turn.

This paper has a certain guiding and innovative significance for the dynamic research of COVID-19 cases in the world.

This paper aims to explore the development trend of OA articles and their advantages and disadvantages in the process of fighting the pandemic, and conduct a multi-level and multi-angle analysis of the relationship between publishing costs and the influence of OA articles.

This study first compares the total number of articles in Web of Science with the number of OA articles, and the total number of COVID-19 related articles with the total number of OA articles. Subsequently, using the methods of institutional cooperation co-occurrence network, keyword co-occurrence and multidimensional scale analysis, and using the literature on the topic of COVID-19 in CNKI (Chinese National Knowledge Infrastructure) as the data set, we generate visualized maps of research results distribution and keyword co-occurrence network with the help of the Statistical Analysis Toolkit for Infometrics (SATI)

The research results show that the citation frequency and use frequency of OA articles related to COVID-19 are significantly higher than that of non-OA articles. OA articles dominate in the anti-pandemic process, with a series of advantages such as short review cycle, timeliness, high social benefit, high participation and fast dissemination playing an important role. Under the model of author's non-payment for OA article, the degree of institutional cooperation and author cooperation is enhanced, which improves the fluidity of knowledge, strengthens close links between keywords and enhances significant academic influence; OA articles will continue to promote research in the field of COVID-19, but the lack of quality of some OA articles may hinder their development. Then OA articles will further focus on clinical medicine, and related results will continue to promote the development and communication of OA articles in this field.

Corresponding measures are also proposed for the existing problems of OA articles, to provide a reference for the publication and dissemination of OA articles in public health emergencies in the future.

From a more general point of view the initiatives and novel practices of farmers represent ‘seeds of transition’. They are the ‘sprouts’ out of which new socio-technical modes for organizing production and marketing emerge – ‘sprouts’ that, taken together can be described under the term ‘rural development’. The examples are, on the whole, well-known; they include agro-ecological production, on-farm processing, agro-tourism, new credit associations and cooperative forms of commercialization. But it remains important to develop a more sociological interpretation of these new forms: since they are produced by social actors and are constantly redefined and modified through the relations and interactions implied by these new forms. This chapter defines the outline on actors and practices that will be discussed in later chapters of the book.

The purpose of this study is to explore how digital transformation helps enterprises achieve high-quality development, including the mediating mechanism of information transparency, innovation capacity and financial stability, the moderating role of financing constraints and government subsidies, and the heterogeneous effects of property rights, size and growth.

This study conducts two-way fixed-effect model using 780 samples of China's Shanghai-Shenzhen A-share listed companies from 2012 to 2019.

The results show that digital transformation can effectively improve the total factor productivity (TFP) of enterprises through the triple channels of information transparency, innovation capability and financial stability. Meanwhile, financing constraints significantly inhibited the contribution of digital transformation to TFP, while government subsidies significantly increased the contribution of digital transformation to TFP. In addition, state-owned enterprises (SOEs), large enterprises and high-growth enterprises are more able to achieve high-quality development by increasing their digital transformation.

In the process of implementing digital transformation, companies should actively improve information transparency, financial stability and innovation capabilities, and choose differentiated paths based on intrinsic characteristics such as property rights, scale and growth. At the same time, the government should actively improve not only the digital institutional environment but also the financial policy and credit system.

This study enriches the theoretical research framework of digital transformation and high-quality development by identifying the channel mechanisms and boundary conditions through which digital transformation affects high-quality development and expands the consequences of digital transformation and the antecedents of high-quality development.

The paper aims to study the relationship between corporate social responsibility, green supply chain management, and operational performance and the moderating effects of relational capital on these relationships.

The authors conduct an empirical study with a structural equation modeling approach to investigate the relationship between corporate social responsibility—constructed by the quality and environmental responsibility, green supply chain management—including green supplier and customer management and operational performance—manifested by quality, cost, flexibility, and delivery performance using data from 308 manufacturers in China. Besides, the authors explore the moderating effect of supplier and customer relational capital on these relationships.

The findings indicate that a company's quality and environmental responsibility significantly impacts its green supply chain management practices, which further improve its operational performance in quality, cost, flexibility, and delivery. In addition, supplier and customer relational capital strengthens the influence of environmental responsibility on green supply chain management. While supplier relational capital reinforces the impact of green supplier management on flexibility and delivery performance, customer relational capital only strengthens the influence of green customer management on flexibility performance.

The study enriches the extant literature by developing a holistic framework integrating corporate social responsibility, green supply chain management, relational capital, and operational performance and unraveling their intricate relationships. The authors’ findings help practitioners prioritize proactive steps in environmental conservation more than achieving operational performance.

This study aims to examine the joint effect of internal quality integration and product innovation on financial performance by considering the mediating roles of incremental and radical product innovation.

A theoretical framework was developed using the organizational capability view. Based on empirical survey data collected from 209 Chinese manufacturing firms, this research uses structural equation modeling and the bootstrapping method to test hypotheses.

The results show that internal quality integration positively impacts incremental and radical product innovation and financial performance. Further, incremental product innovation can promote radical product innovation. Both incremental and radical product innovation partially mediate the relationship between internal quality integration and financial performance.

The findings provide practical guidance for manufacturing companies to engage in quality integration and product innovation. Managers should encourage the internal functional departments to coordinate quality integration while promoting incremental and radical product innovation to occupy a larger market and achieve higher performance.

This research contributes to the literature in two ways. First, this study expands the theoretical research framework of the joint effects of quality integration and product innovation on financial performance. Second, through testing the mediating role of product innovation, this study provides empirical evidence for the intermediate role of internal quality integration for improving financial performance.

To solve the problem of oil film thinning when hydrostatic thrust bearings are overloaded or rotating at high speed, the dynamic pressure formed by tiny oil wedges is used to compensate, and the optimum height of oil wedges is determined by the compensation rate to improve the bearing capacity of hydrostatic thrust bearings.

This research method is aimed at the new type of double rectangular cavity static bearing with microbevel surface of q1-205. The wedge parameters of oil film were defined. The oil film lubrication performance of the bearing with the wedge parameters of 0, 0.02, 0.04, 0.06, 0.08 and 0.10 mm was simulated by the finite volume method, the comprehensive influence law of the wedge-shaped parameters on the vorticity and flow rate of the oil cavity pressure fluid was revealed. Finally, the oil cavity pressure changes of oil films with different wedge parameters under certain load and speed were tested by design experiments, and the theoretical analysis and simulation were verified.

This study found that the oil film wedge shape can well compensate the static pressure loss caused by the high-speed or heavy-duty operation of the bearing, but the dynamic pressure effect of the wedge shape does not always increase with the increase of the wedge height. The oil film exhibits superior lubrication performance in the range of 0.06–0.08 mm.

The original hydrostatic oil pad was designed as a microinclined plane, and the dynamic pressure caused by the microwedge of the oil pad was used to compensate the static pressure loss of the bearing. The lubrication performance of the oil film under the condition of varying viscosity was obtained by using the simulation method.

Economic fundamentals are recognized as determining factors for housing on the city level, but the relationship between housing price and land supply has been disputed. This study aims to examine what kind of impact housing prices have on land supply and whether there is heterogeneity in different regional spaces.

This study collects the relevant data of land supply and housing prices in Nanchang from 2010 to 2018, constructs a vector autoregression (VAR) model, including one external factor and four internal factors of land supply to explore the dynamic effects and spatial heterogeneity of land supply on housing prices through regression analysis. Also, the authors use the geographic detector to analyze the spatial heterogeneity of housing prices in Nanchang.

This study found that the interaction between land supply and housing price is extremely complex because of the significant differences in the study area; the variables of land supply have both positive and negative effects on housing price, and the actual effect varies with the region; and residential land and GDP are the two major factors leading to the spatial heterogeneity in housing price.

The dynamic effects of land supply on housing price are mainly reflected in the center and edge of the city, the new development area, and the old town, which is consistent with the spatial pattern of the double core, three circles and five groups in Nanchang.

This is a novel work to analyze the dynamic effects of land supply on house prices, instead of a single amount of land supply or land prices. Furthermore, the authors also explore the spatial heterogeneity according to the regional characteristics, which is conducive to targeted policymaking.

In this contribution, we systematically review the extant global leadership literature to identify important bibliometric and thematic patterns in evidence in this evolving field of scholarship. Conceptualizing the phenomenon to include leaders/managers/supervisors who hold global, expatriate, or international positions, we draw out insights accumulated from a total of 327 published articles in key management and organizational behavior journals listed in Scopus. Our analysis proceeds in two sequential phases. Our bibliometric analysis first identifies the most cited articles, most published first authors, country bases of first authors, and frequently publishing journals in this field. This characterizes both the diversity and innovative nature of scholarship in the field. Our thematic content analysis, generated through Nvivo 11, isolates two dominant overarching themes that represent the wellspring for the body of literature, namely global leader development and global leader effectiveness. These themes of development and effectiveness are further explicated through six distinct lenses namely cultural, cognitive, learning, personality trait, social/relational, and political. These lenses are underpinned by a suite of theoretical perspectives encompassing individual, system, and contextual considerations. In combination, these sets of analyses bring added systematics to the field and serve as a point of departure for future inquiry.