Evaluation and Driving Force Analysis of Marine Sustainable Development based on the Grey Relational Model and Path Analysis

doi:10.5814/j.issn.1674-764x.2020.06.004

Abstract

Abstract:

With the rapid development of the marine economy, the demand for marine resources development and the pressure on marine environmental protection are gradually increasing. It is critical to evaluate and analyze the driving forces of marine sustainable development in order to promote the coordinated development of the marine economy, resources and environment. Taking Jiangsu Province of China as an example, this paper constructs an evaluation index system for marine sustainable development from the three aspects of marine economy, resources and environment, and calculates the weight of the variation coefficient for each indicator. Based on the grey relational model, the average value of the relational degree, calculated by the average value method of correlation coefficients and the weighting method, is then used to evaluate the status of marine sustainable development in this province. The comprehensive index model is used to analyze the dynamic trend of the evolution of marine sustainable development. The driving forces of marine sustainable development are analyzed by the path analysis method combined with the average values of the grey relational degree for each indicator. This analysis found that the marine sustainable development in 2016 and 2012 was good, the situation in 2007 was bad, and the remaining years were intermediate. Compared with the previous years, the optimal conditions of 2008 and 2012 were obvious. The main driving factors of marine sustainable development are cargo throughput of coastal ports, economic losses caused by storm surges in coastal areas, the area of marine nature reserves in coastal areas, coastal wind power generation capacity, and marine biodiversity.

Key words: marine sustainable development, coefficient of variation method, grey relational model, composite index model, path analysis

GAO Sheng, ZHAO Lin, SUN Huihui, CAO Guangxi, LIU Wei. Evaluation and Driving Force Analysis of Marine Sustainable Development based on the Grey Relational Model and Path Analysis[J]. Journal of Resources and Ecology, 2020, 11(6): 570-579.

Figures/Tables 11

References 24

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Grade	Ⅴ	Ⅳ	Ⅲ	Ⅱ	Ⅰ
Evaluation indicator value	[0, 0.2)	[0.2, 0.4)	[0.4, 0.6)	[0.6, 0.8)	[0.8, 1.0]
State	Very bad	Bad	Neutral	Good	Very good

Grade	Ⅴ	Ⅳ	Ⅲ	Ⅱ	Ⅰ
Evaluation indicator value	[0, 0.2)	[0.2, 0.4)	[0.4, 0.6)	[0.6, 0.8)	[0.8, 1.0]
State	Very bad	Bad	Neutral	Good	Very good

System layer	Indicator layer	Unit	Coefficient of variation weight
Marine economy	Added value of marine industry (X₁)	×10⁸ yuan	0.0460
	Gross marine product of coastal areas (X₂)	×10⁸ yuan	0.0488
	The proportion of marine GDP to coastal GDP (X₃)	%	0.0120
	Proportion of marine secondary industry in marine GDP in coastal areas (X₄)	%	0.0074
	Proportion of marine tertiary industry in marine GDP in coastal areas (X₅)	%	0.0083
	Number of employed personnel involved in the sea (X₆)	×10⁴ person	0.0138
	Passenger traffic volume in coastal areas (X₇)	×10⁴ person	0.0770
Marine resources	Cargo throughput of coastal ports (X₈)	×10⁴ t	0.0419
	Per capita water resources in coastal areas (X₉)	m³ person^-1	0.0273
	Mariculture area in coastal area (X₁₀)	×10⁴ ha	0.0093
	Coastal wind power generation capacity (X₁₁)	×10⁴ kW	0.0758
	Coastal wetland area (X₁₂)	×10⁴ ha	0.0288
	Area of marine nature reserves in coastal areas (X₁₃)	×10⁴ ha	0.1950
	Marine biodiversity (X₁₄)		0.0548
Marine environment	Economic losses caused by storm surges in coastal areas (X₁₅)	×10⁸ yuan	0.2351
	Industrial wastewater discharge in coastal areas (X₁₆)	×10⁴ t	0.0110
	Standard rate of industrial wastewater discharge in coastal areas (X₁₇)	%	0.0011
	Industrial waste gas emissions in coastal areas (X₁₈)	×10⁸ m³	0.0242
	Industrial smoke (dust) emission in coastal areas (X₁₉)	×10⁸ m³	0.0073
	Disposal capacity of industrial solid waste in coastal areas (X₂₀)	×10⁴ t	0.0583
	Comprehensive utilization of industrial solid waste in coastal areas (X₂₁)	×10⁴ t	0.0165

System layer	Indicator layer	Unit	Coefficient of variation weight
Marine economy	Added value of marine industry (X₁)	×10⁸ yuan	0.0460
	Gross marine product of coastal areas (X₂)	×10⁸ yuan	0.0488
	The proportion of marine GDP to coastal GDP (X₃)	%	0.0120
	Proportion of marine secondary industry in marine GDP in coastal areas (X₄)	%	0.0074
	Proportion of marine tertiary industry in marine GDP in coastal areas (X₅)	%	0.0083
	Number of employed personnel involved in the sea (X₆)	×10⁴ person	0.0138
	Passenger traffic volume in coastal areas (X₇)	×10⁴ person	0.0770
Marine resources	Cargo throughput of coastal ports (X₈)	×10⁴ t	0.0419
	Per capita water resources in coastal areas (X₉)	m³ person^-1	0.0273
	Mariculture area in coastal area (X₁₀)	×10⁴ ha	0.0093
	Coastal wind power generation capacity (X₁₁)	×10⁴ kW	0.0758
	Coastal wetland area (X₁₂)	×10⁴ ha	0.0288
	Area of marine nature reserves in coastal areas (X₁₃)	×10⁴ ha	0.1950
	Marine biodiversity (X₁₄)		0.0548
Marine environment	Economic losses caused by storm surges in coastal areas (X₁₅)	×10⁸ yuan	0.2351
	Industrial wastewater discharge in coastal areas (X₁₆)	×10⁴ t	0.0110
	Standard rate of industrial wastewater discharge in coastal areas (X₁₇)	%	0.0011
	Industrial waste gas emissions in coastal areas (X₁₈)	×10⁸ m³	0.0242
	Industrial smoke (dust) emission in coastal areas (X₁₉)	×10⁸ m³	0.0073
	Disposal capacity of industrial solid waste in coastal areas (X₂₀)	×10⁴ t	0.0583
	Comprehensive utilization of industrial solid waste in coastal areas (X₂₁)	×10⁴ t	0.0165

Year	Grey relational degree of correlation coefficient average method	Grey relational degree of weighting method	Average value of grey relational degree	Rank
2016	0.7146	0.5881	0.6513	1
2012	0.5782	0.6246	0.6014	2
2014	0.6345	0.5259	0.5802	3
2015	0.6273	0.521	0.5741	4
2013	0.6097	0.5382	0.5739	5
2011	0.5383	0.4455	0.4919	6
2010	0.5487	0.4323	0.4905	7
2008	0.4590	0.4941	0.4766	8
2009	0.4571	0.3834	0.4203	9
2006	0.4474	0.3634	0.4054	10
2007	0.4069	0.3632	0.3850	11