Construction resource allocation for industrial solid waste treatment centers in cities of Anhui Province, China

Abstract

Purpose The purpose of this paper is to study where to place industrial solid waste treatment centers among the 16 prefecture-level cities under its jurisdiction. Design/methodology/approach This paper adopts the cross-efficiency data envelopment analysis (DEA) model, with the industrial land price and average annual salary per capita as inputs, while coverage, total transportation distance, number of industrial enterprises and total amount of industrial solid waste are used as outputs. Findings Based on the spatial efficiency scores calculated by using the new presented models, the authors find that the most efficient construction site are Chizhou, Chuzhou, Suzhou and Bengbu. That is quite different from the results obtained by using traditional approach. Originality/value This paper evaluates the spatial efficiency by using combinations of the four locations as the decision-making units of the DEA model, which could be used as an objective way to allocate limited resource. In addition to the resource allocation of the industrial solid waste treatment center, the method in this paper can also be applied to other spatial aspects of resource allocation.

Ranking Canadian waste management system efficiencies using three waste performance indicators

“…In the future, the proposed ranking framework can include waste from non-residential sector to provide a more comprehensive assessment of the WMS. Other operation research techniques such as data envelopment analysis (DEA) models can also be used to study waste management system efficiency (Wu et al 2019 ; Molinos-Senante et al 2022 ; Ye et al 2022 ). WMS is complex, and multiple factors and metrics should be considered when evaluating WMS efficiency.…”

Environmental Protection, Industrial Structure and Urbanization: Spatiotemporal Evidence from Beijing–Tianjin–Hebei, China

“…For example, the layout and construction of urban industries are the same, leading to a serious waste of resources and the failure to adapt to the characteristics of the city, as well as causing the phenomenon of urban industry in regions having the same structure and overcapacity. According to relevant calculations, the similarity rate of the industrial structure in various provinces is over 90%, and the traditional industries of Hebei Province remain dominant; these similarities in industrial development have triggered homogeneous competition between cities [49], and the loose spatial structure leads to insufficient urban land use intensiveness [50,51]. When the circular model of urban construction is insufficient, the surrounding areas will be developed from a low starting point at the same time, and it will be difficult to support high-level, fast-running and intensive urban facilities, resulting in low efficiency of urbanization.…”

Influencing Factors Analysis and Optimization of Land Use Allocation: Combining MAS with MOPSO Procedure

“…There have been various past studies on optimal land-use allocation. These include several studies on the optimal allocation of urban land use [14] or single rural land-use types, such as agricultural land [15,16], rural residential land [17,18], industrial land [19,20], and tourist land [21]. However, there have been relatively few past studies on the simultaneous optimization of the allocation of several rural land-use types.…”