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Tourism consumption as a typical representative of service consumption, has strong comprehensiveness and driving force, continuously expanding new consumption upgrade space. In the context of the digital economy, the development of the mobile internet has opened up new opportunities for the tourism industry acting as an important factor influencing the consumer behaviour of the residents. Based on 9007 resident survey data from the China General Social Survey (CGSS) in 2017, this paper explores the relationship between Internet use, access to information and residents' travel consumption behavior by means of probit model and mediating effect model. First, according to the findings, Internet use has a positive impact on residents' travel consumption behavior, increasing residents' tourism expenditure. Second, the mechanism suggests that access to information plays a partially mediating role between Internet use and travel consumption behavior. Third, further analysis revealed that, for the retired population, the more frequently they use the Internet, the more likely they are to spend on travel. Compared to those with lower incomes, those with higher incomes will spend less on travel after retirement. With this in mind, in order to promote residents' tourism consumption, speed and fee reduction should be continuously promoted, urban and rural information infrastructure should be strengthened, and accessibility of tourism information for residents should be improved. At the same time, there is a need to innovate the way tourism products are promoted, improve the types of tourism products and launch diversified tourism products. [ABSTRACT FROM AUTHOR]

Green technology innovation is an effective means to achieve high-quality economic development. The impact and mechanism of digital financial inclusion on regional green technology innovation are tested using a threshold regression model and the panel fixed effect model, based on China's provincial Panel data (provincial Panel data are regional annual report data) from 2011 to 2020. According to the study, there is a direct link between local green technology innovation and digital financial inclusion. This paper highlights the differences in their influence by location and usage depth and underscores the necessity of government engagement to improve these characteristics. Information infrastructure needs to be strengthened, especially in areas with gaps. Greater investment in research and development (R&D) indirectly supports regional green technology innovation since it is impacted by digital financial inclusion. Interestingly, a threshold effect becomes most noticeable when digital financial inclusion rises above a particular threshold. Promoting utilizing digital financial inclusion to lessen regional differences in green technology innovation is important. [ABSTRACT FROM AUTHOR]

The analysis of influencing factors serves as the cornerstone for the research on smart community construction. Drawing upon both field research and extensive literature study, this paper explores the influencing factors of China's smart community construction and its effective paths by taking 52 national pilot zones for community governance and service innovation in China as examples. In the constructed analytical framework of influencing factors, elements such as economic development, capital investment, information infrastructure, community governance, public support system, and smart platform are included. By the use of the qualitative comparative analysis (QCA) method, the results of the study show that community governance, public support system, and smart platform are necessary conditions for smart community construction, while economic development, capital investment and information infrastructure play a leading role in the four combined paths. Finally, this study provides a new perspective for theoretical research, a reference forgovernmental departments to make decisions, and experience for the construction of smart communities in other developing countries. [ABSTRACT FROM AUTHOR]

Triggering economic growth is a requirement to promote human welfare and realize sustainable development in many developing countries. However, place-based policies' impact on economic growth is debatable, and its underlying mechanism is unknown. China's Old Revolutionary Development Program (ORDP) is a large-scale and novel type of place-based policy targeted at undeveloped regions in China. We evaluate the effect of ORDP on economic growth by employing a time-varying difference-in-differences model and further explore the potential mechanisms and heterogeneity effects. VIIRS/DNB nightlight data is used to measure economic growth. We find that ORDP can significantly promote economic growth by 4.0% and the result is still robust after several tests. Mechanism analysis shows that ORDP can improve economic growth through government intervention, industrial structure optimization, and information infrastructure construction. Heterogeneity analysis indicates that the ORDP performs better on economic growth in central Chinese cities and high-economy cities. At the same time, our paper provides three practical suggestions for stimulating economic growth in ORDP, which can be enlightening for other developing countries. [ABSTRACT FROM AUTHOR]

Vehicle-tree collisions are the most common type of road crash with fixed obstacle in Czech Republic. Based on the literature review and using real world in-depth crash data, this paper aims to define factors, which significantly influence the injury severity of single vehicle-tree crashes. In-depth data provide a comprehensive view to the failure on the system infrastructure—human—vehicle related to crash, the in-depth crash database include very detailed information related to infrastructure, vehicle, human failure and crash participants characteristics and their medical condition and also crash reconstruction. Multinomial logistic regression and generalized linear mixed model were used to determine the individual effect of each predictor. The statistically significant variables were the day period, trunk diameter and impact speed. Using multinomial logistic regression shows also vehicle age as statistically significant. Obtained results can help to efficiently direct countermeasures not only on the road infrastructure—e.g. speed reduction in selected locations with specified tree character. However, the emphasis should be also focused on driver behaviour. [ABSTRACT FROM AUTHOR]

Containers have emerged as a more portable and efficient solution than virtual machines for cloud infrastructure providing both a flexible way to build and deploy applications. The quality of service, security, performance, energy consumption, among others, are essential aspects of their deployment, management, and orchestration. Inappropriate resource allocation can lead to resource contention, entailing reduced performance, poor energy efficiency, and other potentially damaging effects. In this paper, we present a set of online job allocation strategies to optimize quality of service, energy savings, and completion time, considering contention for shared on-chip resources. We consider the job allocation as the multilevel dynamic bin-packing problem that provides a lightweight runtime solution that minimizes contention and energy consumption while maximizing utilization. The proposed strategies are based on two and three levels of scheduling policies with container selection, capacity distribution, and contention-aware allocation. The energy model considers joint execution of applications of different types on shared resources generalized by the job concentration paradigm. We provide an experimental analysis of eighty-six scheduling heuristics with scientific workloads of memory and CPU-intensive jobs. The proposed techniques outperform classical solutions in terms of quality of service, energy savings, and completion time by 21.73–43.44%, 44.06–92.11%, and 16.38–24.17%, respectively, leading to a cost-efficient resource allocation for cloud infrastructures. [ABSTRACT FROM AUTHOR]

“The Belt and Road” initiative has been expected to facilitate interactions among numerous city centers. This initiative would generate a number of centers, both economic and political, which would facilitate greater interaction. To explore how information flows are merged and the specific opportunities that may be offered, Chinese cities along “the Belt and Road” are selected for a case study. Furthermore, urban networks in cyberspace have been characterized by their infrastructure orientation, which implies that there is a relative dearth of studies focusing on the investigation of urban hierarchies by capturing information flows between Chinese cities along “the Belt and Road”. This paper employs Baidu, the main web search engine in China, to examine urban hierarchies. The results show that urban networks become more balanced, shifting from a polycentric to a homogenized pattern. Furthermore, cities in networks tend to have both a hierarchical system and a spatial concentration primarily in regions such as Beijing-Tianjin-Hebei, Yangtze River Delta and the Pearl River Delta region. Urban hierarchy based on web search activity does not follow the existing hierarchical system based on geospatial and economic development in all cases. Moreover, urban networks, under the framework of “the Belt and Road”, show several significant corridors and more opportunities for more cities, particularly western cities. Furthermore, factors that may influence web search activity are explored. The results show that web search activity is significantly influenced by the economic gap, geographical proximity and administrative rank of the city. [ABSTRACT FROM AUTHOR]

In order to quantitatively analyze the influence of different traffic conditions on highway crash risk, a method of crash risk assessment based on traffic safety state division is proposed in this paper. Firstly, the highway crash data and corresponding traffic data of upstream and downstream are extracted and processed by using the matched case-control method to exclude the influence of other factors on the model. Secondly, considering the weight of traffic volume, speed and occupancy, a multi-parameter fusion cluster method is applied to divide traffic safety state. In addition, the quantitative relationship between different traffic states and highway crash risk is analyzed by using Bayesian conditional logistic regression model. Finally, the results of case study show that different traffic safety conditions are in different crash risk levels. The highway traffic management department can improve the safety risk management level by focusing on the prevention and control of high-risk traffic safety conditions. [ABSTRACT FROM AUTHOR]

Haze is a typical weather phenomena that has a significant negative impact on transportation safety, particularly in the port, highways, and airport runway areas. A multi-scale U-shaped dehazing network is proposed in this research, which is based on our multi-channel feature fusion attention structure. With the help of the feature fusion attention techniques, the model can focus on the intriguing locations with higher haze concentration area. In conjunction with UNet, it can achieve multi-scale feature reuse and residual learning, allowing it to fully utilize the feature information of each layer for image restoration. Experimental resulsts show that our technique performs well on a variety of test datasets. On highway data sets, the PSNR / SSIM / L∞ error performance over the novel technique is increased by 0.52% / 0.5% / 30.84%, 4.68% / 0.78% / 26.19% and 13.84% / 9.05% / 55.57% respectively, when compared to DehazeFormer, MIRNetv2, and FSDGN methods. The findings suggest that our proposed method performs better on image dehazing, especially in terms of L∞ error performance. [ABSTRACT FROM AUTHOR]

The Cold Supply Chain (CSC) is an integral part of the supply chain of perishable products. The aim of this research is to examine the inhibitors that have a major impact on the performance of CSC operations in the United Arab Emirates (UAE). This study provides a synthesis and suggests a hierarchical model among CSC inhibitors and their respective relevance. The hierarchical synthesis of twelve (12) primary CSC inhibitors is achieved through a comprehensive literature review and consultation with academics and CSC professionals. This study used semi-structured interviews, a fuzzy interpretive structural modeling (FISM) and a Fuzzy-MICMAC (FMICMAC) analysis to explore and establish the relationship between and among identified inhibitors. FISM is used to examine the interaction between inhibitors, while FMICMAC analysis is used to examine the nature of inhibitors on the basis of their dependence and driving power. The results of the FISM and FMICMAC analysis show the inter-relationships and relative dominance of identified inhibitors. The results show that some inhibitors are of high strategic importance due to their high driving power and low dependence. These inhibitors seek more management attention in order to improve their effectiveness. The result of a hierarchical model helps to understand the influence of a particular inhibitor on others. 'Higher capital and operating costs' occupy the highest level in the FISM model. The 'fragmented cold supply chains', 'lack of skilled labor', 'inadequate information system infrastructure' and 'lack of commitment by top level management' had strong driving power but weak dependence, which characterizes them as independent inhibitors. Management should be extra careful when dealing with these inhibitors as they influence the effects of other variables at the top of the FISM hierarchy in the overall management of the cold supply chain. The study also suggests a number of recommendations for addressing these inhibitors in cold supply chains operating in the UAE. With due attention and care for these inhibitors, the operation of the cold supply chains is likely to be even more successful. [ABSTRACT FROM AUTHOR]