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Using the Pearl River Delta urban agglomeration as the research area, this study comprehensively uses an interlocking network model and social network analysis to construct a network based on the headquarters branch data of digital economy listed enterprises in 2005, 2010, 2015, and 2020 to analyze the digital economy correlation pattern of the Pearl River Delta urban agglomeration. The results show that from 2005 to 2020, the number of digital economy listed companies' headquarters and branches in the Pearl River Delta urban agglomeration has grown rapidly. The radiating influence of headquarters has gradually expanded, and cross-city connections among digital economy companies have strengthened. Shenzhen and Guangzhou have become the engines of digital economy development and the control centers of the correlation network. The overall correlation structure of the urban agglomeration transformed from a single triangle consisting of Guangzhou-Zhuhai-Shenzhen and the connecting cities in 2005 to a double triangle structure consisting of Guangzhou-Foshan-Shenzhen and Guangzhou-Zhuhai-Shenzhen and the connecting cities in 2020. The network density increased, the asymmetry weakened, and the agglomeration subgroups shifted from a single regional center to multiple regional centers. From an industrial perspective, there are significant disparities among the different sectors of the digital economy. Network connections were strongest in the information transmission, software, and information technology service industries, weakest in finance, and moderate in manufacturing. The dual-core status of Shenzhen and Guangzhou is prominent, whereas Zhaoqing and Jiangmen are on the network periphery. This study examines the formation and evolution of the digital economy network of the Pearl River Delta urban agglomeration from the perspective of corporate organizational connections, identifies the positions and roles of each city in the correlation network, analyzes the correlation pattern and evolution path of the digital economy, and expands the study of digital economy correlation from an industry perspective, revealing industry differences in the digital economy correlation of urban agglomerations. The characteristics of the regional digital economy correlation can be summarized based on the results of this study and the existing research. First, the degree of regional digital economy correlation continuously increases during the development of the digital economy, and the overall network connection is strengthened. Second, differentiation emerges in the digital economy correlation network, forming core and peripheral cities and displaying spatial distribution imbalances. This study also found that policy guidance may promote the formation of multiple centers in the region and contribute to the balanced development of the correlation network. Finally, the regional digital economy correlation exhibits industry differences due to industry foundations and development characteristics. To promote sustained and healthy development of the digital economy in the Pearl River Delta urban agglomeration, it is necessary to further enhance inter-city digital economy cooperation, better leverage the radiating driving effects of core cities, such as Shenzhen and Guangzhou, improve digital economy development policies and infrastructure in peripheral cities, and promote coordinated development of the overall digital economy in the urban agglomeration. Comprehensive planning of the industry layout is necessary in subdivided industries to promote balanced development across all sectors and form a concerted effort in digital economy development. These measures can also serve as a reference for other areas in developing digital economies.

Using the Pearl River Delta urban agglomeration as the research area, this study comprehensively uses an interlocking network model and social network analysis to construct a network based on the headquarters branch data of digital economy listed enterprises in 2005, 2010, 2015, and 2020 to analyze the digital economy correlation pattern of the Pearl River Delta urban agglomeration. The results show that from 2005 to 2020, the number of digital economy listed companies' headquarters and branches in the Pearl River Delta urban agglomeration has grown rapidly. The radiating influence of headquarters has gradually expanded, and cross-city connections among digital economy companies have strengthened. Shenzhen and Guangzhou have become the engines of digital economy development and the control centers of the correlation network. The overall correlation structure of the urban agglomeration transformed from a single triangle consisting of Guangzhou-Zhuhai-Shenzhen and the connecting cities in 2005 to a double triangle structure consisting of Guangzhou-Foshan-Shenzhen and Guangzhou-Zhuhai-Shenzhen and the connecting cities in 2020. The network density increased, the asymmetry weakened, and the agglomeration subgroups shifted from a single regional center to multiple regional centers. From an industrial perspective, there are significant disparities among the different sectors of the digital economy. Network connections were strongest in the information transmission, software, and information technology service industries, weakest in finance, and moderate in manufacturing. The dual-core status of Shenzhen and Guangzhou is prominent, whereas Zhaoqing and Jiangmen are on the network periphery. This study examines the formation and evolution of the digital economy network of the Pearl River Delta urban agglomeration from the perspective of corporate organizational connections, identifies the positions and roles of each city in the correlation network, analyzes the correlation pattern and evolution path of the digital economy, and expands the study of digital economy correlation from an industry perspective, revealing industry differences in the digital economy correlation of urban agglomerations. The characteristics of the regional digital economy correlation can be summarized based on the results of this study and the existing research. First, the degree of regional digital economy correlation continuously increases during the development of the digital economy, and the overall network connection is strengthened. Second, differentiation emerges in the digital economy correlation network, forming core and peripheral cities and displaying spatial distribution imbalances. This study also found that policy guidance may promote the formation of multiple centers in the region and contribute to the balanced development of the correlation network. Finally, the regional digital economy correlation exhibits industry differences due to industry foundations and development characteristics. To promote sustained and healthy development of the digital economy in the Pearl River Delta urban agglomeration, it is necessary to further enhance inter-city digital economy cooperation, better leverage the radiating driving effects of core cities, such as Shenzhen and Guangzhou, improve digital economy development policies and infrastructure in peripheral cities, and promote coordinated development of the overall digital economy in the urban agglomeration. Comprehensive planning of the industry layout is necessary in subdivided industries to promote balanced development across all sectors and form a concerted effort in digital economy development. These measures can also serve as a reference for other areas in developing digital economies. [ABSTRACT FROM AUTHOR]

The adoption and diffusion level of eXtensible Business Reporting Language (XBRL) technology among listed enterprises is an important indicator of the capital market's openness and efficiency degree. In this study, we established an evolutionary model between the government, listed enterprises, and institutional investors, analyzed the evolutionary path and evolutionary law of the model, and conducted numerical simulations. In the numerical simulations, we discussed the impact of different parameters change on the strategic choices of the three parties, and the results show that increasing government enforcement and subsidies intensity, reducing the adoption cost for listed enterprises, increasing the incremental benefits of adoption for enterprises, and increasing the participation level of institutional investors all promote the adoption of XBRL technology by listed enterprises. The adoption behavior of listed enterprises is driven by a combination of the government's policy guidance and institutional investors' XBRL engagement level. Therefore, this paper is an effective supplement to the innovative technology adoption and diffusion theory and provides policy recommendations and management insights for the government's efforts in promoting XBRL technology, which is conducive to solving the problem of insufficient motivation for XBRL technology adoption by listed enterprises. [ABSTRACT FROM AUTHOR]

The adoption and diffusion level of eXtensible Business Reporting Language (XBRL) technology among listed enterprises is an important indicator of the capital market‘s openness and efficiency degree. In this study, we established an evolutionary model between the government, listed enterprises, and institutional investors, analyzed the evolutionary path and evolutionary law of the model, and conducted numerical simulations. In the numerical simulations, we discussed the impact of different parameters change on the strategic choices of the three parties, and the results show that increasing government enforcement and subsidies intensity, reducing the adoption cost for listed enterprises, increasing the incremental benefits of adoption for enterprises, and increasing the participation level of institutional investors all promote the adoption of XBRL technology by listed enterprises. The adoption behavior of listed enterprises is driven by a combination of the government’s policy guidance and institutional investors’ XBRL engagement level. Therefore, this paper is an effective supplement to the innovative technology adoption and diffusion theory and provides policy recommendations and management insights for the government’s efforts in promoting XBRL technology, which is conducive to solving the problem of insufficient motivation for XBRL technology adoption by listed enterprises.

Letter of Credit (L/C) is currently a very popular international settlement method frequently used in international trade processes amongst countries around the globe. Compared with other international settlement methods, however, L/C has some obvious shortcomings. Firstly, it is not easy to use due to the sophisticated processes its usage involves. Secondly, it is sometimes accompanied by a few risks and some uncertainty. Thus, highly efficient methods need to be used to assess and control these risks. To begin with, FAHP and KMV methods are used to resolve the problem of incomplete information associated with L/C and then, on this basis, Bayesian game theory is used in order to make more scientific and reasonable decisions with respect to international trade. [ABSTRACT FROM AUTHOR]