Abstract
Mariculture areas are an important non-renewable natural resource and continuously improving their efficiency is important for increasing mariculture output and adjusting its structure. The aim of this study was to measure the mariculture area production efficiency (MAPE) considering undesirable outputs, further analyze its spatiotemporal disparities, and analyze the reasons for the differences observed during the period from 2008 to 2019. The super-efficiency Engel–Blackwell–Miniard (S-EBM) model and global Malmquist–Luenberger (GML) index was selected to analyze the technical efficiency and productivity of MAPE from both the static and dynamic aspects, and the Theil index was used to decompose the regional differences. The results showed that the MAPE showed fluctuation and an increasing trend overall; the production efficiency and technical progress showed a fluctuating rising trend, and technical progress had a significant driving effect on the production efficiency; and intra-regional differences were the main factors that cause the differences in MAPE. The findings suggest the increase of scientific and technological investment in mariculture, changes in mariculture methods, the establishment of environmental monitoring centers in mariculture areas, and the sharing of information technology between regions to achieve sustainable development.
Highlights
The ocean is a major component of the global life support system and a valuable resource that helps to achieve the sustainable development of human society [1]
Model is a non-parametric method that calculates the relative efficiency of a decisionmaking unit (DMU) by constructing the production frontier of the data and is the most commonly used among the two methods [55]
The traditional data envelope analysis (DEA) model considers only the radial distance and ignores the influence of slack variables; it cannot measure efficiency by considering undesirable outputs accurately [56]. In response to this problem, Tone [57] proposed the slacks-based measure (SBM) model, which takes into account the effects of slack variables on efficiency measurements, while avoiding the deviation caused by the difference in radial and angle distances and solving the high efficiency problem of the traditional DEA estimation approach
Summary
The ocean is a major component of the global life support system and a valuable resource that helps to achieve the sustainable development of human society [1]. With the rapid increase of the global population, environmental pollution, and shortages of resources, food problems are becoming increasingly serious [2,3]. Due to economic development and the improvement of living standards, people are not satisfied with merely solving the problem of food quantity, but are paying more attention to the pursuit of highquality food [4,5]. The mariculture production in China ranks first in the world and is developing rapidly, increasing from 10 kilotons in 1950 to 36,403.631 kilotons in 2019, accounting for 3.17% and 62.9% of the world’s mariculture production, respectively
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