Xianzhu Wang's research while affiliated with Anhui University of Technology and other places

... Years of rapid growth have, however, resulted in several drawbacks [3], such as the short history of marketization of China's real estate industry, the lack of a functioning market mechanism and the prevalence of speculative activity [4]. To this end, the government has implemented a series of regulation measures in the real estate industry with the prohibition of housing speculation as a guideline, such as restricting the purchase of second and third homes as well as the resale of housing within five years, thus prompting the real estate industry to make supply-side reforms and enter an adjustment period; however, this will also destroy the growth of the construction industry to a certain extent, leading to bottlenecks in the development of some real estate enterprises [3,5]. ...

... Energy is a basic element for human survival and development, and residential energy consumption is an important part of China's energy demand [1]. Demand for energy has increased with the development of the Chinese economy [2]. On the one hand, traditional energy is nonrenewable. ...

... For policy-based financial support, only HPF participants are eligible to apply, so the coverage and fairness of the HPF program have been widely questioned by scholars [7,40]. Low-income families find it difficult to not only afford housing but also receive support from HPF [41,42]. ...

... Huang et al. [24] categorised urban renewal projects in Taipei into three dimensions of environmental, economic, and social, by classifying them into decision units, and evaluated the efciency of renewal projects based on DEA. Tang et al. [25] combined energy analysis and SBM-DEA to construct an eco-efciency model and illustrated the applicability of this eco-model in urban regeneration using the questionnaire statistics of Chongqing, China, as an example. Numerous studies have shown that DEA treats the study area as a grey system in a complex urban system, focusing on the relationship between its "input" and "output," instead of studying the interaction of various factors, similar to "black box operation," which can avoid the bias caused by the interaction of the internal links of the complex urban system and thus obtain more realistic performance evaluation results. ...

... In addition, the positive marginal effect of HPF on homeownership was shown to be rising from 2014. This finding echoes the existing literatures that housing finance accessibility matters for homeownership tendency [31,40,73] and supports a recent finding that HPF plays an active role in China's housing finance system [43,74]. Moreover, the marginal effect of city-level HPF participation rate on migrants' homeownership acquisition (e.g., 0.241 for CMDS 2016) was more than four times that of individual-level HPF participation (0.057 for CMDS 2016). ...

... Under the background of green and sustainable development, clean energy has become an ideal substitute for traditional fossil energy [5]. In addition, the Chinese government promised in the "Paris Climate Summit" to achieve peak carbon emissions by 2030 and carbon neutrality by 2060 [6]. In order to fulfill its commitments, reducing the use of traditional energy and increasing clean energy consumption are important measures taken by the Chinese government to reduce carbon dioxide emissions [7]. ...

... In the second stage, as shown in Table 2, empirical findings for control variables (micro-level characteristics of rural migrants, city-level attributes of host city, and geographic factor of migration) were in line with theoretic forecasts and consistent with the previous empirical literature [8,9,48,71,72]. It is important to note that the city-level indicator of rural migrants' accessibilities to HPF was shown to have a significantly positive effect on migrants' homeownership propensity. In addition, the positive marginal effect of HPF on homeownership was shown to be rising from 2014. ...

... Many scholars have proven that CEE is spatially clustered and dependent (Li et al. 2019a, b;Chuai and Feng 2019). In exploring regional CEE, ignoring spatial spillover effect may lead to biased estimates (Hong et al. 2020). Our study, therefore, assumed that there was a spatial effect of CEE. ...