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作 者:关美 陈晓宇 李春林 GUAN Mei;CHEN Xiaoyu;LI Chunlin(Library,Zhejiang Ocean University.Zhoushan 361000,China;School of Business,Ningbo University,Ningbo 315211,China;School of Economics and Management,Zhejiang Ocean University,Zhoushan 361000,China)
机构地区:[1]浙江海洋大学图书馆,舟山361000 [2]宁波大学商学院,宁波315211 [3]浙江海洋大学经济与管理学院,舟山361000
出 处:《海洋开发与管理》2024年第8期90-100,共11页Ocean Development and Management
基 金:浙江省软科学研究计划重点项目(2023C25029);浙江省文化和旅游厅一般科研项目(2022KYY004);浙江省哲学社会科学规划高校思想政治工作专项课题(22GXSZ064YBM)。
摘 要:基于韧性理论,结合海洋渔业经济韧性内涵,构建中国海洋渔业经济韧性指标评价体系,文章采用基于CRITIC组合权重模型计算综合评价指数,利用变异系数法和熵权法确定各指标的权重,依托GIS空间分析技术探究海洋渔业经济韧性的时空分异特征,运用马尔科夫(Markov)链分析其动态演进特征。结果表明:(1)2001—2020年我国沿海省份海洋渔业经济韧性整体呈上升趋势;从不同维度来看,抵抗恢复能力和创新转型能力呈现波动上升的趋势,适应调整能力则显现下降态势。(2)海洋渔业经济韧性的高值区域呈现向南扩张的趋势,中值区和较高值区逐渐向南北两级扩展,而低值区的空间分布相对稳定。(3)Markov链的研究结果表明,研究期间中国海洋渔业经济韧性的发展状态相对稳定,同时呈现出俱乐部趋同的特征;各省区维持现有发展水平的概率逐渐减小,向更高发展水平发展的概率增加;趋势预测结果表明未来可能发生一种“跨越式”的阶段演变,高水平省区的数量有望不断增加。Based on resilience theory,combined with the connotation of marine fishery economic resilience,an evaluation index system for China's marine fishery economic resilience is established.This paper employs the CRITIC-based combined weight model to calculate the comprehensive evaluation index,utilizing both the Coefficient of Variation Method and the Entropy Weight Method to determine the weights of the indicators.Utilizing the GIS spatial analysis echnology,this paper explores the temporal and spatial characteristics of the economic resilienceof the marine fishery, and applies the Markov chain to analyze the characteristics of its dynamicevolution. The results indicate that: (1) The overall economic resilience of marine fisheries inChina's coastal provinces from 2001 to 2020 is on the rise;from different dimensions, the resistance-recoveryability and innovation-transformation ability exhibit a fluctuating upwardtrend, whereas the adaptive-adjustment ability shows a downward trend. (2) The high-valuearea of marine fisheries economic resilience exhibits a tendency to expand towards the south,while the medium-value and the higher-value areas gradually expand to both the north andsouth. Meanwhile, the spatial distribution of the low-value area remains relatively stable. (3)The results of Markov chain analysis reveal that the development state of marine fisheries economicresilience is relatively stable during the study period, and simultaneously, it displays thecharacteristics of club convergence. The probability of maintaining the current level of development in each province and region gradually decreases, while the probability of developing towardsa high level increases. The results of the trend forecast suggest that a “leapfrog” stage ofevolution is likely to occur in the future, with the number of high-level provinces and districtsanticipated to continue to rise.
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