Suchergebnisse

Abstract
The 20th National Congress of the Communist Party of China proposed accelerating the promotion of Chinese-style modernization, placing higher requirements on regional economic development. In this context, interregional industrial convergence has become a new driving force for achieving high-quality economic development and regional industrial transformation and upgrading. Using the 2017 interregional input-output table provided by Carbon Emission Accounts and Datasets (CEADs), this study constructs a directed weighted network from both the supply side and the demand side, with "province-industry" as the node and the real flow between industries as the edge weight. Network analysis is used to investigate the overall status of industrial convergence in China, as well as differences according to industry and region. Finally, an exponential random graph model (ERGM) is used to examine the influencing factors and effects of network formation. The results show the following: (1) the industrial convergence relationship between regions in China is transitive and reciprocal, and the overall tendency of the network is one in which output capacity is greater than absorption capacity. (2) The marginal flow of manufacturing and services occupies an absolute advantage in China's industrial convergence network, in which mid-end manufacturing and producer services are the most prominent. (3) Industrial convergence between provinces has formed a hierarchical spatial layout of "output-conduction-absorption". In the absorption layer, the breadth and depth of Beijing's industrial integration are characterized by absorption-dominant development. In the output layer, Shanghai's capital-intensive industries have a strong external radiation capacity and generally show open-led development. (4) Interregional industrial convergence tends to occur in areas with similar economic levels and output value levels, showing a coordinated development trend of high-level output and low-level absorption, which is also affected by location proximity relationships, regional technology gaps, and employment population gaps. This research shows that China's inter-provincial industrial convergence network generally shows the characteristics of spatial hierarchy, significant industry differences and multi-factor drivers.

AbstractThis article examines social deprivation at a regional scale using the case of Guangdong province, China. Counties, county‐level cities, and districts of prefecture cities are selected as the units of analysis. At the provincial level, a significant variation is found in terms of the social deprivation index, showing a pattern of increasing deprivation from the core of the Pearl River Delta (PRD) to the peripheral areas of Guangdong province. In the PRD, social development conditions are significantly different among these units, whereas the level of economic development is less differentiated. Social deprivation in urban areas is considerably lower than in rural areas. The differences between cities are significant, showing a bifurcation trend, whereas rural areas seem to be similar. Social disparities in Guangdong province are derived from unequal economic growth as well as social and regional policies.

According to the Chinese government' commitments while entering the WTO, now China has cancelled many restrictions for foreign banks including the restriction of foreign exchange business, the geographic restriction of RMB business and the restriction of the establishment form of foreign banks. Foreign banks are now permitted to offer services to all Chinese clients and to set up the same city services points to make cross‐region business. It means that nowadays foreign commercial banks and Chinese commercial banks are standing at the same start line to compete with each other. The innovation of this paper is mainly reflected in the following three aspects. First, we made a complete and systematic summary about the latest achievements on the competitiveness of commercial banks, including the foreign and domestic authoritative method of the evaluation of international competitiveness of commercial banks, in order to build a solid theoretical foundation for the empirical analysis. The second is the multilevel empirical method. In addition to the innovation on the selected indicators of the traditional factor analysis, we also made a cointegration analysis on the macro‐level variables which further strengthened the content of the international competitiveness of commercial banks. Thirdly, the data used in the empirical analysis are the latest ones released by the official website of the commercial banks, statistical agencies, regulatory bodies and related database by 2010, in order to ensure the validity and the timeliness of the empirical results.

AbstractThe formation of an industrial network is inevitable because an industrial structure evolves to a higher level. The continuous material exchange among sectors creates a path for the embodied carbon in products to flow freely among industries. With the gradual complication of industrial networks, however, the emission reduction behavior of sectors not only becomes rooted in individual conduct, but also originates from the interaction forces between individuals. Therefore, carbon management in industries in the real economy needs to be explored from the perspective of these complex networks. On the basis of these considerations, this study utilized a hybrid model, the Economic Input–Output Life Cycle Assessment model, to construct the carbon footprint network of China's industries in 2002, 2007, 2012, and 2017. We also applied social network analysis to quantify the structural characteristics and evolutionary patterns of the network. Results showed that the transmission efficiency of resources and the subgroup‐integrated degree of the actors within the carbon footprint network were excellent, which was conducive to coordinated carbon emission reduction of these sectors from a network perspective. Agriculture and services were the engines driving sector‐wide carbon emission reduction through links within the network. Furthermore, some sectors, such as transportation and the warehousing industry, basic chemicals and chemical products manufacturing, and metal smelting and rolling processing industry, act as bridges and brokers. These sectors are keys to ensuring network cohesion and reducing the risk of network fragmentation. Finally, the industrial block network presented a hierarchical structure of a core–edge network. The network followed a trend of structural changes in which the network core became increasingly clear, and the network distribution pattern gradually concentrated on a single block. This finding revealed a new pathway for collaborative carbon mitigation in the industry from the perspective of the industrial community.