“Spatial Characteristics and Influencing Factors of Night Cultural and Tourism Consumption Agglomeration Areas in China”
This study explores the spatial distribution and influencing factors of night cultural and tourism consumption areas across China, with implications for economic development and urban renewal. The authors use spatial analysis methods to evaluate the distribution characteristics of these agglomeration areas, finding that the spatial distribution is unbalanced, with a combination of regional clusters and single nucleus aggregation points. The study identifies eight different types of night agglomeration areas, each with distinctive features and varying spatial densities, driven by factors such as resource endowment, economic level, transportation location, and policy environment. This research provides a foundation for future studies on the spatiotemporal evolution of China’s night tourism economy and offers insights for urban renewal efforts in other regions facing economic challenges, including implications for the Greater Bay Area.
“The ‘Chinese Path’: Uneven Development, Projectment, and Socialism”
This paper investigates the unique trajectory of China’s development, emphasizing the concepts of uneven development, projectment, and socialism as key factors that differentiate China’s growth path from other Asian economies like Japan and South Korea. The authors argue that China’s success cannot be solely attributed to catching up economically but must be understood within the context of its historical and socialist foundations. The study discusses how these factors have enabled China to move from being one of the poorest countries in 1949 to becoming a global competitor, particularly in technology. The paper suggests that these elements are crucial in explaining the robustness and resilience of China’s development process, offering a deeper understanding of the Chinese model of economic growth.
“How Does Industrial Intellectualization Affect Energy Intensity? Evidence from China”
This research examines the relationship between industrial intellectualization and energy intensity in China, particularly focusing on the impact of the digital economy and the Fourth Industrial Revolution. The study constructs an industrial intelligent system and analyzes data from 2006 to 2018, finding that industrial intellectualization significantly improves energy efficiency, thereby reducing energy intensity, albeit with a notable lag effect. The research also highlights the spatial autocorrelation and agglomeration of energy intensity in China, with a negative spatial spillover effect observed from industrial intellectualization. Additionally, the study considers the nonlinear effects of various economic factors, such as technological progress and environmental regulation, on energy intensity. The findings provide valuable insights for policymakers in regions like the GBA to enhance industrial efficiency and achieve sustainable economic growth through industrial intellectualization.