The rapid progress of information technology has made public online participation in policy formulation an inevitable product of modern government reshaping and reconstruction. However, compared with developed countries, citizens’ online participation in policy formulation in China started relatively late. Thus, in order to explore an effective and efficient method for Chinese citizens’ participation in policy formulation, this research made a brief review of the experiences from the typical developed country of United States of America at first, followed by some other developed countries such as Singapore, South Korea, and Japan in Asia with similar situations. Still, combined with the current situation of the China itself into consideration, this research further proposes targeted recommendations. It is expected that the findings in this research could provide some references for the Chinese government to form more effective and efficient theoretical frameworks targeted at the future development trends of the Chinese society and accordingly, to improve the construction of democracy in China.

The article considers an actual problem of organizing a safe and sustainable urban transport system. We have examined the existing positive global experience in both infrastructural and managerial decisions. Then to assess possible solutions at the stage of infrastructure design, we have developed the simulation micromodels of transport network sections of the medium-sized city (Naberezhnye Chelny) with a rectangular building type. The models make it possible to determine the optimal parameters of the traffic flow, under which pollutant emissions from cars would not lead to high concentrations of pollutants. Also, the model allows to obtain the calculated values of the volume of emissions of pollutants and the parameters of the traffic flow (speed, time of passage of the section, etc.). On specific examples, the proposed method’s effectiveness is shown. Case studies of cities of different sizes and layouts are implementation examples and possible uses proposed by the models. This study has shown the rationality of the suggested solution at the stage of assessing infrastructure projects and choosing the best option for sustainable transport development. The proposed research method is universal and can be applied in any city.

Fire hazard is often mapped as a static conditional probability of fire characteristics’ occurrence. We developed a dynamic product for operational risk management to forecast the probability of occurrence of fire radiative power in the locally possible near-maximum fire intensity range. We applied standard machine learning techniques to remotely sensed data. We used a block maxima approach to sample the most extreme fire radiative power (FRP) MODIS retrievals in free-burning fuels for each fire season between 2001 and 2020 and associated weather, fuel, and topography features in northwestern south America. We used the random forest algorithm for both classification and regression, implementing the backward stepwise repression procedure. We solved the classification problem predicting the probability of occurrence of near-maximum wildfire intensity with 75% recall out-of-sample in ten annual test sets running time series cross validation, and 77% recall and 85% ROC-AUC out-of-sample in a twenty-fold cross-validation to gauge a realistic expectation of model performance in production. We solved the regression problem predicting FRP with 86% r² in-sample, but out-of-sample performance was unsatisfactory. Our model predicts well fatal and near-fatal incidents reported in Peru and Colombia out-of-sample in mountainous areas and unimodal fire regimes, the signal decays in bimodal fire regimes.

In light of the metaverse’s vast expansion, it’s a crucial intellectual platform that’s transforming the video game industry and spurring creative innovation and technological advancement. Considering the distinctive niche that Taiwan occupies within the realm of the video game industry, this study uses a total of 11 video game companies in Taiwan as samples. The study spans a period of 16 years, from 2007 to 2022, and utilizes the random effect regression model for analysis. The study results illustrate that intellectual capital efficiency exerts varying contributions to the creation of value across different corporate value indicators within the video game industry. Among the factors, HCE, SCE, and CEE demonstrate the highest explanatory power for ROE, reaching up to 82.23%. Following this, they account for 73.57% of the variance in market share, but only a meager 13.67% for Tobin’s Q. This study is the empirical evidence that different methods of measuring intellectual capital and various definitions of value creation in an industry may lead to divergent results and managerial implications in intellectual capital research. Hence, it is worthwhile for subsequent studies to continue clarifying and delving deeper into these aspects.

After the pandemic (COVID-19), there is a dire need to gain a competitive advantage for tourism organizations which can be accomplished by implementing new technologies to facilitate sustainable healthier services. Given that, the study aims to shed light on the importance of digital leadership to improve sustainable business performance considering the parallel mediation of digital technology and digital technology support in the tourism sector of Pakistan. The sample population consists of technology-based tourism organizations in Pakistan. Cochran’s formula was chosen for sampling, in which 37 organizations with 792 employees were selected for data through a random sampling technique. The collected data were analyzed through structural equation modeling, and findings reveal that digital leadership positively influences sustainable business performance. Furthermore, the mediating role of technological leadership support and digital technologies partially mediates the association between digital leadership and sustainable performance.