中国海洋渔业经济韧性与效率协同演化研究

doi:10.11821/dlyj020210088

摘要/Abstract

摘要：

探索韧性和效率的相互作用关系和协同演化特征,对中国海洋渔业经济可持续发展研究具有科学参考价值。以2000—2019年中国沿海11个省份为研究区域,采用熵值-Topsis模型、超效率SBM模型分别测度中国海洋渔业经济韧性与效率,并通过哈肯模型刻画二者的协同演化特征。结果表明：① 海洋渔业经济效率作为协同演化的序参量,主导中国海洋渔业经济可持续发展,随着中国海洋经济向高质量转型,韧性作用愈加突显;② 海洋渔业经济韧性与效率协同演化时空差异显著,两极分化格局依旧存在,区域间合作不足,协同演化呈现由初级阶段向高级阶段、单极化向多极化格局演化的趋势;③ 整体上中国海洋渔业经济韧性与效率协同演化呈现正向效应,但政策选择、产业结构等因素使得天津、上海协同演化存在偏向效应,形成海洋渔业经济水平低但协同值高的错配发展;④ 研究期内协同演化呈现波动上升的特征,采用聚类分析将协同演化分为四类,高级协同阶段（0.824~0.964）为山东、福建,较高级协同阶段（0.784~0.823）为天津、上海、浙江及广西,中级协同阶段（0.502~0.771）为辽宁、江苏、广东和海南,初级协同阶段（0.411）为河北。韧性和效率的协同作用表明中国海洋渔业经济发展需培育内生动力,在既有产业基础、技术水平下构建多元化产业体系,在维持经济高效运转的前提下,加强经济韧性,推动海洋渔业经济可持续发展。

关键词: 海洋渔业, 经济韧性, 经济效率, 协同演化

Abstract:

Exploring the interaction and synergistic evolution characteristics of resilience and efficiency provides important reference for promoting the sustainable development of marine fishery economy. Taking 11 coastal provincial-level regions of China from 2000 to 2019 as the study area, entropy-Topsis model and super-efficiency SBM model are used to measure China's marine fishery economic resilience and efficiency respectively, and the Haken models are used to describe their synergistic evolution characteristics. The results show that: (1) Marine fishery economic efficiency, as the order parameter of synergistic evolution, dominates the sustainable development of China's marine fishery economy. With the high-quality transformation of China's marine economy, the role of resilience is becoming more and more prominent. (2) There is a significant spatio-temporal difference in the synergistic evolution of marine fishery economic resilience and efficiency, the polarization pattern still exists, the inter-regional cooperation is insufficient, and the synergistic evolution tends to evolve from the primary stage to the advanced stage and from single polarization to multi-polarization. (3) On the whole, the synergistic evolution of China's marine fishery economic resilience and efficiency shows a positive effect, but the synergistic evolution of Tianjin and Shanghai has a bias effect due to the factors such as policy choice and industrial structure, resulting in a mismatch development with low economic level but high coordination value of marine fishery economy. (4) During the study period, the synergistic evolution showed the characteristics of fluctuation and rise, and the synergistic evolution was divided into four types by cluster analysis. Shandong and Fujian were developing in the high-level synergistic stage (0.824-0.964); Tianjin, Shanghai, Zhejiang and Guangxi were in the higher-level synergistic stage (0.784-0.823); Liaoning, Jiangsu, Guangdong and Hainan were in the intermediate synergistic stage (0.502-0.771); and Hebei was in the primary synergistic stage (0.411). The synergistic effect of resilience and efficiency shows that China should cultivate a endogenous power, construct a diversified industrial system under the existing industrial foundation and technological level, and strengthen economic resilience on the premise of maintaining economic and efficient operation, to promote the sustainable development of marine fishery economy.

Key words: marine fishery, economic resilience, economic efficiency, synergistic evolution

韩增林, 朱文超, 李博. 中国海洋渔业经济韧性与效率协同演化研究[J]. 地理研究, 2022, 41(2): 406-419.

HAN Zenglin, ZHU Wenchao, LI Bo. Synergistic analysis of economic resilience and efficiency of marine fishery in China[J]. GEOGRAPHICAL RESEARCH, 2022, 41(2): 406-419.

图/表 7

表1

海洋渔业经济韧性指标体系

目标层	准则层	指标层	指标解释	指标权重
海洋渔业经济韧性	抵抗恢复能力0.3188	X₁海洋渔业产值（+）	表征海洋渔业经济规模,海洋渔业产值越高则产业规模越大,则对冲击的抵御能力越强。	0.1119
		X₂海洋灾害直接经济损失（-）	表征海洋灾害对沿海地区破坏程度,海洋灾害直接经济损失越大,对危机的抵御能力越低。	0.0207
		X₃工业废水直接入海量（-）	表征海洋环境污染现状,工业废水直接入海量越大,对海洋渔业经济的环境压力越大。	0.0226
		X₄海水养殖结构指数（+）	表征海洋渔业养殖结构多样化水平,数值越大,海水养殖结构多样化程度越高。	0.0665
		X₅沿海地区渔民人均全年收入（+）	表征渔民对风险抵抗能力,收入越高,则对经济风险的抵抗能力越强。	0.0971
	适应调整能力0.272	X₆沿海地区人均湿地面积（+）	表征适应灾害的冗余空间,沿海湿地能够调节近海养殖地生态平衡,为海洋渔业提供冗余空间适应调节灾害的冲击。	0.0719
		X₇海洋渔业从业人员（+）	表征海洋渔业人力资本,充足的人力资源有利于增强海洋渔业经济的韧性。	0.1231
		X₈海水产品占水产品产量比例（+）	表征海洋渔业产出水平,通过计算海水养殖产量、海洋捕捞产量和远洋渔业产量的总和占水产品总产量比例所得。	0.0168
		X₉海洋机动渔船年末拥有量（+）	表征海洋渔业生产能力,具有规模的机动渔船能够保障地区海洋渔业的养殖、捕捞等生产能力和为生产提供运输、冷藏和加工等服务能力,增加海洋渔业的适应和调整能力。	0.0136
		X₁₀海水加工品占水产加工品比例（+）	表征海洋渔业加工能力,通过计算海水加工品总量占水产加工品总量比例所得,反映海洋渔业的加工生产能力和生产调整能力。	0.0466
	创新转型能力0.4092	X₁₁水产推广机构数（+）	表征海洋渔业地方技术投入,通过水产推广机构推广新技术,促进海洋渔业技术革新。	0.1401
		X₁₂创新人员投入（+）	以大专及以上教育水平水产技术人员数量表征创新人员投入,优质的人才储备有利于海洋渔业经济知识更新和推广。	0.1068
		X₁₃海洋科技课题数（+）	表征海洋渔业研发能力,海洋科技课题投入越大,科技促进海洋渔业经济创新作用越强。	0.0931
		X₁₄创新财政支持力度（+）	以技术推广经费表征地方政府对于海洋渔业创新转型的支持力度。	0.0692

表1

表2

图1

图2

表3

2000—2019年变量分析结果

模型假设	运动方程	参数信息	模型结论
$q 1$ =EF	$q 1$ =1.624579^* $q 1 (t - 1)$ +2.5053^ $q 1 (t - 1) q 2 (t - 1)$ +0.198	$γ 1$ =0.6246; $γ 2$ =-0.02701; a=2.5053;b=0.0523	运动方程成立;满足模型假设;EF为序参量
$q 2$ =RES	$q 2$ =0.97299^*1 $q 2 (t - 1)$ +0.05231^ $q 1 (t - 1) q 2 (t - 1)$ +0.001	$γ 1$ =0.6246; $γ 2$ =-0.02701; a=2.5053;b=0.0523	运动方程成立;满足模型假设;EF为序参量

表3

图3

表4

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指标类型	一级指标	二级指标
投入指标	资源投入	海水养殖面积
	资源投入	海水鱼苗数量
	资本投入	海洋渔船数量
	资本投入	水产技术推广经费
	劳动力投入	海洋渔业从业人员
产出指标	期望产出	海洋渔业产值
	期望产出	海水产品产量
	非期望产出	海水养殖排污总量

年份	2000年	2009年	2019年	2000—2019年
辽宁	较高级协同（0.801）	中级协同（0.527）	中级协同（0.551）	中级协同（0.502~0.771）
天津	较高级协同（0.772）	较高级协同（0.824）	较高级协同（0.816）	较高级协同（0.783~0.823）
河北	中级协同（0.776）	初级协同（0.137）	初级协同（0.251）	初级协同（0~0.411）
山东	高级协同（0.868）	高级协同（0.851）	高级协同（0.859）	高级协同（0.824~1）
江苏	初级协同（0.205）	较高级协同（0.634）	高级协同（0.926）	中级协同（0.502~0.771）
上海	中级协同（0.655）	中级协同（0.524）	较高级协同（0.822）	较高级协同（0.783~0.823）
浙江	中级协同（0.751）	高级协同（0.859）	高级协同（0.957）	较高级协同（0.783~0.824）
福建	中级协同（0.794）	高级协同（0.862）	高级协同（0.861）	高级协同（0.824~1）
广东	初级协同（0.460）	中级协同（0.481）	中级协同（0.445）	中级协同（0.502~0.771）
广西	较高级协同（0.840）	较高级协同（0.667）	较高级协同（0.742）	较高级协同（0.783~0.823）
海南	较高级协同（0.819）	中级协同（0.504）	中级协同（0.566）	中级协同（0.502~0.771）