A new quality management system of admittance indicators to improve industrial land use efficiency in the Beijing−Tianjin−Hebei region

Abstract

Given China’s rapid urbanization, the continual adjustment of industrial land admittance indicators (ILAIs) to promote the optimal allocation and utilization of industrial land is critical for urban land use optimization and sustainable urban development. Unlike previous studies that have focused on qualitative analysis and traditional economic and statistical methods to modify ILAIs via sample survey data, this paper proposes a new theoretical framework for determining the optimal regulation of ILAIs to improve land use efficiency from a quality management perspective, analyses the differences in ILAIs in industrial space and types at multiple scales and sets and modifies the diverse function values of ILAIs by sub-region and sub-industrial sector via a probability model based on big data for 2007–2016 for the Beijing−Tianjin−Hebei (BTH) region. The findings were as follows: (1) The floor area ratio (FAR), greening ratio (GR), building density (BD) and fixed asset investment intensity (FAII) of industrial land in BTH were found to be low within national standards and exhibited great excavation potential. (2) The ILAIs exhibited spatial heterogeneity, with a significant multicore circular structure of peaks and fluctuations and with FAR, BD and FAII values higher in the Jing-Jin region and in the southern and northeastern regions of Hebei Province but lower in northwestern BTH, while the GR’s spatial pattern showed the opposite trend. (3) Both the five classified sub-regions and industry sub-types displayed marked variations in ILAIs, indicating that it was necessary to modify ILAIs by sub-region and sub-industrial sector. (4) Industrial land use efficiency in BTH was further revealed at the general, non-intensive and extensive levels and was found to vary considerable by sub-type. The land use mode of the service industry was the most efficient and intensive, followed by that of the high-tech industry. The land intensiveness of various light industry sectors was clearly distinct, while the chemical, metallurgy and equipment manufacturing industries were of moderate to non-intensive levels. The lowest values were found for the mining and coking industry. (5) The probability model is suggested to be an effective method for modifying the multifunctional values of ILAIs. Relative to national standards, the improved control values of ILAIs were higher at the regional level, and for different sub-regions not fully proportional to their development levels, they were higher or lower than their regional counterparts, even deviating from national standards. The revised FAR of each industry was also found to be higher and directly proportional to existing national standards; however, their improvement exhibited the opposite trend. ILAIs performance was bifurcated in terms of industry sub-types and economic-geographic regions. This study suggests establishing twofold ILAIs of “land use efficiency and industrial development”, developing gradient path guidance for ILAIs threshold values and enhancing ILAIs implementation flexibility to realize the precise matching of industry transfer and acceptance and the coordinated and balanced development of the entire region and constructing a sound “access-adjustment-exit” circulation system for applying ILAIs throughout the life cycle of industrial land.