As China is transitioning from a planned economy to a market-based economy, over the past 30 years, China’s economy has experienced the same type of changes that led to amenity-driven housing and land markets in more developed countries. This paper examines the effect of different types of amenities on urban land and housing prices across Chinese cities in 2020. When firms and households value some amenities, the assumption is that the preference for these amenities will be valued and reflected in both land and housing markets. We conduct a cross-sectional analysis of urban land and housing prices in prefecture and higher-level cities in China. We extend the Roback model to explore the extent to which the different land rents and housing prices reflect the compensations for interregional amenity differences across Chinese cities. We include two types of amenities: natural amenities and locally produced amenities. We perform two-stage least squares (2SLS) estimations and compute the implicit prices of various amenities for households and firms. The empirical results show that a range of amenities is valued by both households and firms, resulting in higher housing and industrial prices.

Global value chains (GVCs) involve production and distribution cooperation as well as pollution redistribution. With the increasing frequency of global trade activities and the growing problem of environmental pollution, the impact of GVC participation on environmental pollution has attracted considerable academic attention. In this study, a dynamic panel Gaussian mixture model was constructed using data from several databases, including Chinese industrial enterprise pollution emission and customs data from 2005 to 2013. We found that the degree of GVC participation of enterprises and pollution emission show a non-linear inverted U-shaped relationship. This indicates that the pollution emissions of enterprises increased and then decreased as the degree of GVC participation increased. We constructed separate models for the effects of output upstreamness and input downstreamness on pollution emissions and found that upstreamness is negatively related to pollution emissions, with the upstream economic components of GVC (such as technology research and development, international marketing, and key component manufacturing) producing emission reduction effects. Downstreamness, on the other hand, is positively correlated with emissions, which means that the downstream economic components of the GVC (e.g., processing, assembly, and production of non-critical components) will increase emissions. Based on the second finding, we proposed that the inverted U-shaped relationship is the result of the combined influence of upstream and downstream participation and confirmed this hypothesis by constructing a multiple mediating effects model. This study will help enterprises consciously implement environmental protection measures and broaden the scope of research on the environmental impact of GVCs, providing a broader segmented research perspective on the degree of participation in GVCs and the environmental performance of exporting enterprises, and guiding governments to formulate more effective industrial policies for foreign trade and promote better environmental performance of enterprises.

Consensus in group decision-making has become a hotspot to ensure the agreement opinions of decision makers (DMs). The irrational behaviors of DMs, such as confidence, will impact the consensus results, which should be considered. In addition, the existing self-confidence level directly given by DMs rather than exacted from evaluation information may generate malicious manipulation. Furthermore, double-hierarchy hesitant fuzzy linguistic term set (DHHFLTS) is an effective tool to express the complex evaluations of DMs. In this paper, the endo-confidence of DHHFLTS to reflect confidence of DMs from the perspective of evaluation information is defined. Then, we propose a novel consensus model with endo-confidence of DMs based on DHHFLTSs. First, some improved operators of DHHFLTSs are developed. Second, the weight is determined based on both entropy and endo-confidence. Due to the fact that the consensus threshold should decrease as the endo-confidence increases, we give a novel method to obtain the consensus threshold considering endo-confidence level. Moreover, the two-stage adjustment mechanism is presented for non-consensus DMs and the selection process is constructed. Finally, an illustrative example is carried out to demonstrate the feasibility of the proposed model, and a series of comparative analysis is used to show its stability.