中国陆海统筹绩效时空分异及影响因素——基于脆弱性视角的分析
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摘要
基于脆弱性视角,从敏感性和应对性两方面构建评价指标体系,运用熵权-TOPSIS模型测度1996—2015年中国陆海统筹绩效,结合核密度估计、多元线性回归和障碍度模型揭示其演化的时空分异及影响因素。结果表明:(1)中国陆海统筹绩效整体呈缓慢提升态势,两极分化趋势减弱,区域差距逐渐缩小。(2)空间演化上,陆海统筹绩效低值区空间范围不断缩小,中高值区空间范围不断扩大。其中,辽宁、河北、浙江、江苏、广西呈向好发展趋势,天津、山东、广东、上海呈减缓发展趋势,福建、海南呈波动变化。(3)回归分析表明,应对性对陆海统筹绩效的影响发挥主导作用,陆海经济协调发展度、陆海第二产业及第三产业贡献率、涉海就业结构专业化指数、科研经费投入力度、高层次人才储备率是制约其应对能力提升的主要障碍因子。
Based on the perspective of vulnerability, the paper constructed the performance evaluation index system from the aspects of sensitivity and response capacity. The entropy-TOPSIS model was used to evaluate the performance of land-sea coordination from 1996 to 2015, while the kernel density estimation was used to reveal its temporal and spatial differentiation. And the multiple linear regression and obstacle model was used to explore the key factors affecting the performance of land-sea coordination. The results show that:(1)China's land-sea performance shows a slow increase. The polarization trend of land-sea coordination performance of China's coastal areas shows weakened, and the regional differences significantly reduce.(2)The low-level performance of land-sea coordination regional space are gradually narrow, the intermediate performance area gradually expand. Among them, the land-sea coordination performance in Liaoning, Hebei, Zhejiang, Jiangsu, Guangxi shows a good development trend.The trend in Tianjin, Shandong, Guangdong, Shanghai is slowing down, and the performance in Fujian, Hainan is volatile change.(3)The regression analysis indicates that the impact of response capacity on the overall performance of land-sea coordination plays a leading role. The coordinated development of land-sea economy, the land-sea second and tertiary industry contribution rate, the professional structure of the sea-related employment, research funding and high-level talent reserve rate are the main obstacle factors.
Based on the perspective of vulnerability, the paper constructed the performance evaluation index system from the aspects of sensitivity and response capacity. The entropy-TOPSIS model was used to evaluate the performance of land-sea coordination from 1996 to 2015, while the kernel density estimation was used to reveal its temporal and spatial differentiation. And the multiple linear regression and obstacle model was used to explore the key factors affecting the performance of land-sea coordination. The results show that:(1)China's land-sea performance shows a slow increase. The polarization trend of land-sea coordination performance of China's coastal areas shows weakened, and the regional differences significantly reduce.(2)The low-level performance of land-sea coordination regional space are gradually narrow, the intermediate performance area gradually expand. Among them, the land-sea coordination performance in Liaoning, Hebei, Zhejiang, Jiangsu, Guangxi shows a good development trend.The trend in Tianjin, Shandong, Guangdong, Shanghai is slowing down, and the performance in Fujian, Hainan is volatile change.(3)The regression analysis indicates that the impact of response capacity on the overall performance of land-sea coordination plays a leading role. The coordinated development of land-sea economy, the land-sea second and tertiary industry contribution rate, the professional structure of the sea-related employment, research funding and high-level talent reserve rate are the main obstacle factors.
引文
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[27] 孙才志,李欣.基于核密度估计的中国海洋经济发展动态演变[J].经济地理,2015,35(1):96-103.
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[29] 王泽宇,张震,韩增林,等.区域海洋经济对国家海洋战略的响应测度[J].资源科学,2016,38(10):1832-1845.
[30] 鲁春阳,文枫,杨庆媛,等.基于改进TOPSIS法的城市土地利用绩效评价及障碍因子诊断:以重庆市为例[J].资源科学,2011,33(3):535-541.
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[2] 曹忠祥,高国力.我国陆海统筹发展的战略内涵、思路与对策[J].中国软科学,2015(2):1-12.
[3] BALLINGER R,PICKAVER A,LYMBERY G,et al.An Evaluation of the Implementation of the European ICZM Principles[J].Ocean & Coastal Management,2010,53(12):738-749.
[4] AREIZAGA J,SANO M,MEDINA R,et al.A Methodological Approach to Evaluate Progress and Public Participation in ICZM:The Case of the Cantabria Region,Spain[J].Ocean and Coastal Management,2012,59(4):63-76.
[5] LEECH S,WIENSCZYK A,TURNER J.Ecosystem Management:A Practitioners’ Guide[J].Journal of Ecosystems and Management,2009,12(10):1-12.
[6] GARRIGA M,INIGO J,LOSADA.Education and Training for Integrated Coastal Zone Management in Europe[J].Ocean & Coastal Management,2010,53(3):89-98.
[7] 韩增林,狄乾斌,周乐萍.陆海统筹的内涵与目标解析[J].海洋经济,2012,2(1):10-15.
[8] 杨荫凯.陆海统筹发展的理论、实践与对策[J].区域经济评论,2013(5):31-34.
[9] 曹忠祥,宋建军,刘岩,等.我国陆海统筹发展的重点战略任务[J].中国发展观察,2014(9):42-45.
[10] 于丽丽,孟德友.中国海陆经济一体化的时空分异研究[J].经济经纬,2017,34(2):7-12.
[11] 范斐,孙才志.辽宁省海洋经济与陆域经济协同发展研究[J].地域研究与开发,2011,30(2):59-63.
[12] 赵亚萍,曹广忠.山东省海陆产业协同发展研究[J].地域研究与开发,2014,33(3):21-26,48.
[13] 王莉莉,肖雯雯.基于投入产出模型的中国海洋产业关联及海陆产业联动发展分析[J].经济地理,2016,36(1):113-119.
[14] 杨阳,王玉良,高伟明.河北省陆域经济发展与海洋环境耦合关系研究[J].生态科学,2015,34(3):146-152.
[15] 孙才志,高扬,韩建.基于能力结构关系模型的环渤海地区海陆一体化评价[J].地域研究与开发,2012,31(6):28-33.
[16] 杨羽頔,孙才志.环渤海地区陆海统筹度评价与时空差异分析[J].资源科学,2014,36(4):691-701.
[17] 苏飞,陈媛,张平宇.基于集对分析的旅游城市经济系统脆弱性评价:以舟山市为例[J].地理科学,2013,33(5):538-544.
[18] 李鹤,张平宇.东北地区矿业城市社会就业脆弱性分析[J].地理研究,2009,28(3):751-760.
[19] 李博,苏飞,杨智,等.脆弱性视角下辽宁沿海地区人海关系地域系统特征演化及可持续发展模式[J].地域研究与开发,2017,36(4):32-36.
[20] 彭飞,韩增林,杨俊,等.基于BP神经网络的中国沿海地区海洋经济系统脆弱性时空分异研究[J].资源科学,2015,37(12):2441-2450.
[21] 李博,韩增林,孙才志,等.环渤海地区人海资源环境系统脆弱性的时空分析[J].资源科学,2012,34(11):2214-2221.
[22] 王坤,黄震方,曹芳东,等.泛长江三角洲城市旅游绩效空间格局演变及其影响因素[J].自然资源学报,2016,31(7):1149-1163.
[23] 何丹,高鹏.长江中游港口腹地演变及港口-腹地经济协调发展研究[J].地理科学,2016,36(12):1811-1821.
[24] WANGC L,YOON K S.Multiple Attribute Decision Making[M].Berlin:Spring-verlig,1981.
[25] 虞虎,陆林,朱冬芳.长江三角洲城市旅游与城市发展协调性及影响因素[J].自然资源学报,2012,27(10):1746-1757.
[26] 马雪莹,邵景安,徐新良.基于熵权-TOPSIS的山区乡镇通达性研究——以重庆市石柱县为例[J].地理科学进展,2016,35(9):1144-1154.
[27] 孙才志,李欣.基于核密度估计的中国海洋经济发展动态演变[J].经济地理,2015,35(1):96-103.
[28] 孙才志,覃雄合,李博,等.基于WSBM模型的环渤海地区海洋经济脆弱性研究[J].地理科学,2016,36(5):705-714.
[29] 王泽宇,张震,韩增林,等.区域海洋经济对国家海洋战略的响应测度[J].资源科学,2016,38(10):1832-1845.
[30] 鲁春阳,文枫,杨庆媛,等.基于改进TOPSIS法的城市土地利用绩效评价及障碍因子诊断:以重庆市为例[J].资源科学,2011,33(3):535-541.
[31] 王泽宇,卢函,孙才志,等.中国海洋经济系统稳定性评价与空间分异[J].资源科学,2017,39(3):566-576.