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Ecological Compensation Assessment from the Perspective of Spatial Game: A Case Study of the Watershed Ecological Compensation in Anhui Section of the Huaihe River Basin, China
XING Qinfeng, E-mail: xqinfeng@163.com |
Received date: 2022-02-20
Accepted date: 2022-12-20
Online published: 2023-10-23
Supported by
The Estimation and Action Logic of Ecological Compensation System in Huaihe River Basin of Anhui Province(2022CX072)
The ecological environment has been the favorite subject of ecological security with the aim of ecological restoration, development and utilization. Therefore, a spatial game model was constructed according to the theory of spatial production and the spirit of game theory. Then the methods of Factor Analysis and Multivariate Analysis were used to verify the actual situation of watershed ecological compensation satisfaction in Anhui section of the Huaihe River Basin. The results show that: (1) Government management is still the dominant player in the spatial game, and the satisfaction of both market governance and social governance have significant impacts on its overall satisfaction; and (2) To improve the satisfaction of the spatial game, it is necessary to strengthen its cost control, face up to the status and role of its behavior subjects, and accurately recognize its target groups. The results of this study are helpful for deepening our understanding of watershed ecological compensation, and three viewpoints obtained based on the research results are: creating a new pattern of multiple collaborative constructions, highlighting the new implications of cost co-governance and consolidating the new demand of benefit sharing.
XING Qinfeng , ZHANG Mengxue . Ecological Compensation Assessment from the Perspective of Spatial Game: A Case Study of the Watershed Ecological Compensation in Anhui Section of the Huaihe River Basin, China[J]. Journal of Resources and Ecology, 2023 , 14(6) : 1138 -1147 . DOI: 10.5814/j.issn.1674-764x.2023.06.003
Table 1 Indicator operation assignment table |
Indicator name | Indicator definition | Indicator description | Indicator assignment |
---|---|---|---|
Gender | Constant | Gender involves two parameters: Male, female | “Male”=“1”; “Female”=“0” |
Age | Constant | Age involves four parameters: “0-18 years old ”, “19-35 years old ”, “36-60 years old”, “61 years old and over” | “0-18 years old”=“1”; “19-35 years old”=“2”; “36-60 years old”=“3”; “61 years and older”=“4” |
Education | Constant | Education involves six observation parameters: “Primary school and below”, “junior high school”, “high school”, “university and above” | “Primary school and below”= “1”; “Junior high school”= “2”; “High School”=“3”; “University and above”=“4” |
Satisfaction of “the spatial game of watershed ecological compensation” | Y0 | Y0 measured by independent variable Y and X | - |
Satisfaction of “market governance” | Y1 | Y1 involves five observation indicators and they are measured by the Likert scale as follows: Satisfaction of compensation object identification (Y11), Satisfaction of trading market (Y12), Satisfaction of performance evaluation (Y13), Satisfaction of contractual relationship (Y14), Satisfaction of legal environment (Y15) | “Very dissatisfied” = “1”; “Relatively dissatisfied” = “3”; “Satisfied” = “5”; “Relatively satisfied” = “7”; “Very satisfied” = “9” |
Satisfaction of “government management” | Y2 | Y2 involves four observation indicators and they are measured by the Likert scale as follows: Government payment means satisfaction (Y21), Negative externalities taxation satisfaction (Y22), Compensation object control satisfaction (Y23), Compensation efficiency measurement satisfaction (Y24) | |
Satisfaction of “social governance” | Y3 | Y3 involves three observation indicators and they are measured by the Likert scale as follows: Multiple participation satisfaction (Y31), Regional collaborative satisfaction (Y32), Social capital integration satisfaction (Y33) | |
Satisfaction of “behavior subjects” | X1 | - | |
Satisfaction of “cost control” | X2 | - | |
Satisfaction of “target group” | X3 | - |
Table 2 Factor analysis of the spatial game of watershed ecological compensation |
Y1 a=1.018, b=19.145% | Y2 a=1.287, b=28.275% | Y3 a=1.017, b=15.648% | ||||||
---|---|---|---|---|---|---|---|---|
Factor | Load capacity | Commonality | Factor | Load capacity | Commonality | Factor | Load capacity | Commonality |
Y11 | 0.647 | 0.636 | Y21 | 0.759 | 0.671 | Y31 | 0.721 | 0.651 |
Y12 | 0.702 | 0.689 | Y22 | 0.662 | 0.687 | Y32 | 0.657 | 0.673 |
Y13 | 0.705 | 0.697 | Y23 | 0.718 | 0.659 | Y33 | 0.639 | 0.651 |
Y14 | 0.695 | 0.628 | Y24 | 0.729 | 0.651 | - | ||
Y15 | 0.677 | 0.642 | ||||||
c=66.068% |
Note: a is the factor characteristic value, b is the factor contribution rate, and c is the factor cumulative contribution rate. |
Table 3 Multiple regression analysis of the spatial game of watershed ecological compensation |
Variable name | Model 1 | Model 2 | Model 3 | Model 4 |
---|---|---|---|---|
X1 | 0.469** | 0.346** | 0.364* | |
X2 | 0.487** | 0.448* | ||
X3 | 0.349*** | |||
Gender (female =0) | 0.373*** | 0.376** | 0.381* | 0.378*** |
Age | ||||
Under 18 years old (reference) | ||||
19 to 35 years old | 0.229* | 0.345** | 0.342*** | 0.351** |
36 to 60 years old | 0.348** | 0.265 | 0.275* | 0.257** |
Over 60 years old | 0.275 | 0.286 | 0.267 | 0.228 |
Education level | ||||
Primary school and below (reference) | ||||
Junior high school | ‒0.207 | 0.209 | 0.215 | 0.221 |
High school | 0.229 | 0.231** | 0.258* | 0.269 |
University and above” | 0.342** | 0.469* | 0.421** | 0.321* |
F value | 6.121* | 7.647* | 7.523** | 6.604*** |
Adjusted R2 | 0.232 | 0.247 | 0.243 | 0.261 |
Sample size | 5591 | 5591 | 5591 | 5591 |
Note: *P<0.1, **P<0.05, ***P<0.01. |
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