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Global climate change speeds up ice melting and increases flooding incidents. China launched a sponge city policy as a holistic nature-based solution combined with urban planning and development to address flooding due to climate change. Using Weibo analytics, this paper aims to study public perceptions of sponge city.

This study collected 53,586 sponge city contents from Sina Weibo via Python. Various artificial intelligence tools, such as CX Data Science of Simply Sentiment, KH Coder and Tableau, were applied in the study.

76.8% of public opinion on sponge city were positive, confirming its positive contribution to flooding management and city branding. 17 out of 31 pilot sponge cities recorded the largest number of sponge cities related posts. Other cities with more Weibo posts suffered from rainwater and flooding hazards, such as Xi'an and Zhengzhou.

To the best of the authors’ knowledge, this study is the first to explore the public perception of sponge city in Sina Weibo.

The purpose of this study is to identify key factors that facilitate knowledge sharing in collectivistic cultures and further help better understand knowledge management in the international context.

Using a survey method, this study collected data from over 200 managerial employees in knowledge management-based project teams from China. Regression analysis was then conducted to analyze the impact of individual differences and environmental factors on the willingness to share knowledge among team members to identify key factors for successful knowledge retention in the constantly changing organizational environment in a collectivistic context.

The results show that incentives are very important in individual’s decision to share knowledge in project teams even in a collectivistic culture like China and both intrinsically and extrinsically motivated individuals tend to share more knowledge with their team members. Individuals with high altruism are also found more likely to share knowledge with others. Moreover, a trusting environment and explicit knowledge will facilitate knowledge sharing for better retention.

More studies should be conducted in other collectivistic cultures to explore cultural barriers in knowledge management in the international context and comparative studies using samples from different cultural backgrounds are also encouraged to help extend the theories on knowledge management.

While it is well-known that knowledge sharing is essential for organization to maintain competitive advantage, relatively few studies have examined knowledge sharing in collectivistic cultures, and even fewer have done so in China. This study adds values to the literature by identifying key factors for knowledge sharing in China, and thus helps refine the knowledge management theories and provides insights for multinationals on knowledge management in the Chinese market.

The purpose of this paper is to explore knowledge sharing in a Chinese context and to examine the impact of some key contextual factors that affect knowledge sharing within project teams in the Chinese construction sector.

Self‐administered questionnaires were used in this study. Data were collected by surveying 222 managerial employees from different project teams in the construction sector in China. Regression analysis was then used to explore the relationship between different factors and the willingness to share knowledge. The potential influence of Chinese traditional cultures on this relationship was also explored.

This paper shows that within the Chinese context, explicit knowledge promotes knowledge sharing while tacit knowledge creates barriers to knowledge sharing in project teams. Moreover, trust is positively related to knowledge sharing but justice, leadership style, and empowerment do not influence whether employees will share knowledge among themselves in project teams.

While it is well known that knowledge management is critical to success, few studies have examined knowledge management in a Chinese context and little is known how the Chinese generate, codify, and transfer knowledge. This paper tries to bridge this gap by examining what affects knowledge sharing in project teams in China so as to help better understand knowledge management in this important emerging market and whether China can sustain its success in economic growth with effective knowledge management.

In modern society, considering the multi-channel of public opinion information (public opinion) propagation and its strong influence on social development, it is necessary to study its propagation law and discuss the intervention strategy in online social networks (OSN).

First, a conceptual model of double-layer OSN was constructed according to their structural characteristics. Then, a cross-network propagation model of public opinion in double-layer OSN was proposed and discussed its spreading characteristics through numerical simulations. Finally, the control strategy of public opinion, especially the timing and intensity of intervention were discussed.

The results show that the double-layer OSN promotes the propagation of public opinion, and the propagation of public opinion in double-layer OSN has the characteristics of that in two single-layer OSN. Compared with the intervention intensity, the regulator should give the priority to the timing of intervention and try to intervene in the early stage of public opinion propagation.

This study may help the regulators to respond to the propagation of public opinion in OSN more actively and reasonably.

This research has a deep comprehension of the cross-network propagation rules of public opinion and manages the propagation of public opinion.

Under the new media environment, while enjoying the convenience brought by the propagation of public opinion information (referred to as public opinion), learning the evolution process of public opinion and strengthening the governance of the spreading of public opinion are of great significance to promoting economic development and maintaining social stability as well as effectively resisting the negative impact of its propagation.

Thinking about the results of empirical research and bibliometric analysis, this paper focused on introducing key factors such as information content, social strengthening effects, etc., from both internal and external levels, dynamically designed public opinion spreading rules and netizens' state transition probability. Subsequently, simulation experiments were conducted to discuss the spreading law of public opinion in two types of online social networks and to identify the key factors which influencing its evolution process. Based on the experimental results, the governance strategies for the propagation of negative public opinion were proposed finally.

The results show that compared with other factors, the propagation of public opinion depends more on the attributes of the information content itself. For the propagation of negative public opinion, on the one hand, the regulators should adopt flexible guidance strategy to establish a public opinion supervision mechanism and autonomous system with universal participation. On the other hand, they still need to adopt rigid governance strategy, focusing on the governance timing and netizens with higher network status to forestall the wide-diffusion of public opinion.

The research conclusions put forward the enlightenment for the governance of public opinion in management practice, and also provided decision-making reference for the regulators to reasonably respond to the propagation of public opinion.

Our research proposed a research framework for the discussion of public opinion propagation process and had important practical guiding significance for the governance of public opinion propagation.