Spatial correlation and influencing factors of the urban land transaction market in the Yangtze River Delta urban agglomeration

Abstract

PurposeLand transactions are a key indicator of urban sustainable development and urban space expansion. Therefore, this paper aims to study the spatial correlation of different types of land transactions.Design/methodology/approachBased on the big data of land micro transactions in Yangtze River Delta urban agglomeration, this paper uses the generalized forecast error variance decomposition (GFEVD) method to measure the correlation level of urban land markets. Also, social network analysis (SNA) is used to describe spatial correlation network characteristics of an urban agglomeration land market. In the meantime, the factors that influence the spatial correlation of urban land markets are investigated through a quadratic assignment procedure (QAP).FindingsThe price growth rate of urban residential land was higher than that of industrial land and commercial land. The spatial relevance of urban residential land is the highest, while the spatial relevance of the urban commercial land market is the lowest. The urban industrial land market, commercial land market and residential land market all present a typical network structure. Population distance (POD) and Engel coefficient distance (EGD) are negatively correlated with the correlation degree of the urban residential land network; traffic distance (TRD) and economic distance (ECD) are negatively correlated with the correlation degree of the urban industrial land network and commercial land network.Originality/valueThis paper uses a systematically-integrated series of problem-solving models to better explain the development path of urban land markets and to realize the integration of the interdisciplinary methods of geography, statistics and big data analysis.

Scenario analysis on co-benefits of air pollution control and carbon reduction in Yangtze River Delta based on STIRPAT model

“…Based on the development reality of the Yangtze River Delta, the main economic and social development indicators of the 14 th Five-Year Plan and previous research results [30,31], selected population size, economic scale, industrialization level, urbanization level, and energy intensity as the influencing factors and constructed an extended STIRPAT model for air pollution control and carbon reduction in the Yangtze River Delta; On this basis, the forecast analysis is further carried out from the two dimensions of synergistic emission equivalent and synergy coefficient. The following conclusions are drawn:…”

“…This study retains the original variables (population size and economic scale) of STIRPAT model. Referring to the research conducted by Jiang Huiqin et al [30] and Li Zhiqing et al [31], Industrialization level, urbanization level and Energy intensity are vital factors affecting the Co-benefits in the Yangtze River Delta in recent trends. Therefore, the finally chosen five variables as shown in Table 3.…”

Assessing Urban Tourism Development Efficiency: Based on a DEA Approach

“…Zhang Xianxian et al focused on cities in the Yangtze River Delta region and used spatial analysis methods to study the differences in urban tourism development. The results showed that the overall tourism development trend in the Yangtze River Delta was good, but regional differences were significant [7,8,9,10]. In the study of combining tourism development efficiency with spatial analysis, Yu Tingting and Zuo Bing [11] used the DEA model to evaluate the comprehensive efficiency, pure technical efficiency, and scale efficiency of various prefecture level cities.…”