Spatial Justice and Residents’ Policy Acceptance: Evidence from Construction Land Reduction in Shanghai, China

Nowadays, the contradiction between strict construction land supply restriction and excessive construction land demand is extremely prominent. Construction land reduction (CLR) is a policy innovation for economically developed regions designed to solve the tight constraints of the construction land quota as urban development continues in China, however, it leads to a lack of spatial justice. In this study, we address a gap in land use regulation literature regarding regional economic development in fast-developing nations by presenting a quantitative investigation of spatial justice in Shanghai, China. We theoretically analyze the connotation of spatial justice in CLR and its influence on residents’ policy acceptance of CLR. Based on theoretical analysis and using household questionnaires from JJ Town in W District, Shanghai, China, we investigate how spatial justice affects residents’ policy acceptance of CLR through an ordered probit model. The results show that (1) spatial justice strengthens residents’ policy acceptance of CLR; (2) both policy familiarity and participation are important influencing factors that contribute to residents’ policy acceptance of CLR; (3) age, education, household income, the contracting land scale and household population structure also affect residents’ policy acceptance of CLR. (4) Robustness tests support the above findings. Thus, in the process of CLR, it is essential to fully consider the realization of spatial justice to ensure the development of remote suburbs, especially the regions experiencing a net reduction in their construction land

Comprehensive Quality Assessment Algorithm for Smart Meters

With the improvement of operation monitoring and data acquisition levels of smart meters, mining data associated with smart meters becomes possible. Besides, precisely assessing the operation quality of smart meters plays an important role in purchasing metering equipment and improving the economic benefits of power utilities. First, seven indexes for assessing operation quality of smart meters are defined based on the metering data and the Gaussian mixture model (GMM) clustering algorithm is applied to extract the typical index data from the massive data of smart meters. Then, the combination optimization model of index’s weight is presented with the subject experience of experts and object difference of data considered; and the comprehensive assessment algorithm based on the revised technique for order preference by similarity to an ideal solution (TOPSIS) is proposed to evaluate the operation quality of smart meters. Finally, the proposed data-driven assessment algorithm is illustrated by the actual metering data from Zhejiang Ningbo power supply company of China and practical application is briefly introduced. The results show that the proposed algorithm is effective for assessing the operation quality of smart meters and could be helpful for energy measurement and asset management