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In this chapter, we will review the history, deregulation, policy reforms, and airline consolidations and mergers of the Chinese airline industry. The measurement of airline competition in China’s domestic market will also be discussed. Although air deregulation is still ongoing, the Chinese airline industry has become a market-driven business subject to some mild regulations. Then, we will review the impressive development of the high-speed rail (HSR) network in China and its effects on the domestic civil aviation market. In general, previous studies have found that the introduction of HSR services has a significant negative impact on airfare and air travel demand in China. The rapidly expanding network of HSR has important policy implications for Chinese airlines.

This chapter reviews three main issues in the interactions between air transport and high-speed rail (HSR) in China, namely the interaction between low-cost carriers (LCCs) and HSR, HSR speed effect on airlines, and airline–HSR integration. Studies on these three aspects of airline–HSR interactions have yet been well reviewed, and our chapter aims to fill in this gap. In this chapter, we comprehensively survey literature on the topics, especially studies on Chinese markets that have recently witnessed major HSR developments (and have planned further large-scale HSR expansion in the coming years). Our review shows that, first, compared to full-service carriers, LCCs face fiercer competition from HSR. However, the expansion of HSR network in China can be better coordinated with LCC development. Second, HSR speed exerts two countervailing effects on airline demand and price (the “travel-time” effect and “safety” effect, respectively). Specifically, an HSR speed reduction can have a positive effect on airlines due to longer HSR travel time, but a negative effect on airlines due to improved perception on HSR safety. Third, airline–HSR integration can be implemented through cooperation between airlines and HSR operators and through co-location of airports and HSR stations and can have important implications for intermodal transport and social welfare.

Most poverty research has explored monetary poverty. This chapter presents and analyzes the global multidimensional poverty index (MPI) estimations for China. Using China Family Panel Studies (CFPS), we find China’s global MPI was 0.035 in 2010 and decreased significantly to 0.017 in 2014. The dimensional composition of MPI suggests that nutrition, education, safe drinking water, and cooking fuel contribute most to overall non-monetary poverty in China. Such analysis is also applied to subgroups, including geographic areas (rural/urban, east/central/west, provinces), as well as social characteristics such as gender of the household heads, age, education level, marital status, household size, migration status, ethnicity, and religion. We find the level and composition of poverty differs significantly across certain subgroups. We also find high levels of mismatch between monetary and multidimensional poverty at the household level, which highlights the importance of using both complementary measures to track progress in eradicating poverty.

With the rapid development of China’s urbanisation and market economy, municipal solid waste (MSW) generation is increasing dramatically. In response to the threat of environmental pollution and the potential value of converting waste into energy, both the government and the public are now paying more attention to MSW treatment and disposal methods. In 2014, 178.6 million tonnes of MSW was collected at a safe treatment rate of 84.8%. However, the treatment methods and the composition of MSW are influenced by the collection area, its gross domestic product, population, rainfall and living conditions. This chapter analysed the MSW composition properties of Lhasa, Tibet, compared with other cities, such as Beijing, Guangzhou and so forth. The research showed that the moisture content of MSW in Lhasa approaches 31%, which is much lower than the other cities mentioned previously. The proportion of paper and plastics (rubbers) collected was 25.67% and 19.1%, respectively. This was 1.00–3.17 times and 0.75–2.44 times more than those found in Beijing and Guangzhou, respectively. Non-combustibles can reach up to 22.5%, which was 4.03–9.11 times that of Beijing and Guangzhou, respectively. The net heating values could reach up to 6,616 kilojoule/kilogram. The food residue was only half the proportion found in other cities. Moreover, the disposal method applied in each city has also been studied and compared.

Online social networks are increasingly important venues for businesses to promote their products and image. However, information propagation in online social networks is significantly more complicated compared to traditional transmission media such as newspaper, radio, and television. In this chapter, we will discuss research on modeling and forecasting diffusion of virally marketed content in social networks. Important aspects include the content and its presentation, the network topology, and transmission dynamics. Theoretical models, algorithms, and case studies of viral marketing will be explored.

This study investigated four different economic level areas of China (Shanghai, Shandong, Shaanxi, and Guizhou) to analyze the eastern and western urban and rural media service status at different development stages. This set of data comes from the comparison of regional urban and rural areas and indicates the various aspects of differences in the survey area, including the media use habits, media resources, media consumer demand, evaluation of media services, the role of media in public life, public knowledge level, and so on. On analyzing data comprehensively, one thing can be found that there is a positive correlation between the public media contact degree and the public knowledge level. The media plays an extremely important role in public life and regional public knowledge gap between urban and rural areas exists. Furthermore, this gap is positively correlated to the media resources and media exposure. The trend of media using on mobile phone and computer in urban areas increases significantly greater than in rural areas. Then, how to narrow the urban–rural and regional public knowledge gap and reduce the negative impact of the digital divide will be an important urgent task.