Decision-Making Based on Network Analyses of New Infrastructure Layouts

Abstract

New Infrastructure (NI) has gradually become a new driving force for regional economic growth and an important part of the construction of new urban infrastructure in many countries, including China. Compared with traditional infrastructures, these NIs have mutually supportive functions and complex interrelationships that create interconnected networks of resources, information, and other interactions during the construction of the NIs. Therefore, it is important to analyze such correlation networks and explore their formation mechanisms in order to develop more scientific and reasonable strategies for NI investment and construction. In this study, the interdependence between NIs in Chongqing was analyzed as an example. Social network analysis (SNA) was used for the overall characteristics of the interdependency network of the NIs and an exponential random graph model (ERGM) was used to reveal the formation mechanism of this network. The results showed that information infrastructure is the key node for enhancing the effectiveness of Chongqing’s NI needs and its government should play a coordinating role. The network of related relationships is characterized by “reciprocity” and “small group”. The aggregation of NIs with such characteristics can produce an agglomeration effect. So, in the planning of NIs, the coordination among management departments should be strengthened and project locations should be reasonably arranged according to the functional interactive characteristics of the projects.

Promoting the Integration of Elderly Healthcare and Elderly Nursing: Evidence from the Chinese Government

“…Furthermore, the collaboration content between different functional departments is mainly reflected in the relevant information, i.e., the information about the integration of elderly healthcare and elderly nursing. Therefore, in this paper, we conduct the whole study under the perspective of information collaboration between different government agencies, constructs a healthcare–nursing information collaboration network (HnICN) [ 18 , 19 ] based on the SOFPDCHE, and comprehensively explores the inner features of the HnICN by analyzing the global structure, calculating the attribute variables of the adjacency subgroups, and measuring the collaboration effects of the node-pairs. The main contributions and innovations of this study are highlighted as follows:…”