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Spatial autocorrelation analysis is essential for understanding the distribution patterns of spatial flow data. Existing methods focus mainly on the origins and destinations of flow units and the relationships between them. These methods measure the autocorrelation of gravity or the positional and directional autocorrelations of flow units that are treated as objects. However, the intrinsic complexity of actual flow data necessitates the consideration of not only gravity, positional, and directional autocorrelations but also the autocorrelations of the variables of interest. This study proposes a global spatial autocorrelation method to measure the variables of interest of flow data. This method mainly consists of three steps. First, the proximity constraints of the origin and destination of a flow unit are defined to ensure similarity of flow units in terms of direction, distance, and position. This undertaking aims to determine the neighborhood of flow units and generate their adjacent matrices. Second, a spatial autocorrelation measurement model for flow data is constructed on the basis of the adjacent matrix generated. Artificial data sets are also employed to test the validity of the model. Finally, the proposed method is applied to the flow data analysis of population migration in central and eastern China to prove the practical application value of the model. The proposed method is universal and can be generalized to the global spatial autocorrelation analysis of any type of flow data. [ABSTRACT FROM AUTHOR]

Prefabricated buildings (PBs) are vigorously promoted for their many advantages. However, obvious regional differences exist in the development of PBs in China, and underdeveloped areas significantly lag behind other areas. Regional "tactics" have a more direct effect on the development of PBs than national "strategies". A targeted analysis of PB policies in underdeveloped areas in China is lacking in current research. Therefore, the aim of this study was to construct a comprehensive policy framework to help underdeveloped areas improve PB policies to develop PBs. In this study, we constructed a three-dimensional policy framework based on the content analysis method and policy instrument theory. Through a comparative analysis of 137 PB policies in three representative regions, 547 policy content codes were obtained, and reliability and validity tests were completed. The results indicate that (1) underdeveloped areas should focus on improving the number of policies rather than the accuracy in the early stages of development of PBs; (2) underdeveloped areas should focus on mandatory policy instruments (MPIs) supplemented by incentive policy instruments (IPIs) and social policy instruments (SPIs) rather than a balanced use of various policy instruments; and (3) underdeveloped areas should adjust the policy layout of the whole life cycle, and stakeholders should pay attention to the construction willingness of developers and the demands of consumers and seek policy support in the operation and maintenance stages, as well as during the demolition and recovery stages. In this study, we systematically analyzed the focus of PB policies for different stages and stakeholders and proposed an application strategy of policy instruments, contributing to the improvement of the PB policy system and the narrowing of regional development gaps with respect to PBs. [ABSTRACT FROM AUTHOR]

Carbon emissions trading (CET) is now one of China's key policy tools for achieving the goals of carbon peak and carbon neutrality. To comprehensively explore the consequences of China's CET policy, the study first evaluated the content validity of CET policies across China's 31 provinces, autonomous regions, and municipalities falling directly under the central government using policy strengths, tools, and measures from 2011 to 2020. The spatiotemporal drivers of regional carbon efficiency improvements from aspects of actual policy effect, average policy content validity effect, and policy quantity effect were also evaluated via the logarithmic mean Divisia index. This analysis revealed that the policy content validity was increasing in general and was higher in pilot regions. On average, the policy quantity effect was the primary driver of carbon efficiency improvements in both pilot and non-pilot regions, but the actual policy effect failed to promote carbon efficiency in both regions. Beijing's carbon emissions reduction effect was superior to that of other pilot regions, and where actual policy effect and policy quantity effect were the primary and secondary drivers of local carbon efficiency improvements, respectively. These findings suggest that when formulating CET policies, each region should not only focus on improving policy content validity, but also pay attention to the actual carbon emissions reduction effects produced by policies as well. [ABSTRACT FROM AUTHOR]