基于PSR模型的我国体育场地公共服务承载力评价与空间特征

Evaluation of Public Service Carrying Capacity and Spatial Characteristics of Sports Ground in China Based on PSR Model

利用第六次全国体育场地普查数据,基于压力—状态—响应(PSR)模型构建我国体育场地公共服务承载力评价指标体系,在熵权法赋予各具体指标客观权重的基础上,采用TOPSIS算法计算体育场地资源承载力指数,并使用环境与气候区位系数进行修正,综合评估我国省域体育场地公共服务承载力水平,继而运用探索性空间数据分析(ESDA)方法呈现我国总体与省域场地资源状态的空间动态特征。研究显示:(1)区位系数修正前的承载力指数由于在指标体系所包含的压力、状态与响应三者系统层面上的权重不同,而呈现出西部最高、东部次之、中部最低的状态,其承载力指数的全局空间特征表现为正向的聚集效应,而省域聚集状态则表现为低—低类型聚集区占主导地位,新疆与广东则分别处于西部与东部的承载力指数高值中心,但其影响力并未辐射至低值聚集的中部地区;(2)区位系数修正后的承载力指数相对水平基本与修正前一致,其中吉林与辽宁存在明显的区位优势,而重庆与四川存在明显的区位劣势,省域之间的最终承载力指数相差较大,最高水平的地区为西藏,其余排名前8的省份依次为江苏、上海、青海、新疆、广东、浙江、山东,最低水平的省份为贵州,其最终承载力指数的全局与局域空间特征表现出与修正前相似的空间聚集性,但是省域空间依赖性有所提升。针对上述特征,提出以下建议:我国体育场地的公共服务建设应在拓宽多元供给渠道与运营方式的同时,提高各社会系统资源之间的共享、开放水平与利用率,在因地制宜地发挥省域区位优势的基础上,实现区域性群众需求的精准供给。

Using the census data of the sixth national sports venues,the evaluation index system for public service capacity of sports venues in China was constructed based on the pressure-state-response(PSR)model. Based on the objective weights given by the entropy method to each specific indicator,the TOPSISalgorithm was used to calculate the index of carrying capacity of sports ground resources was revised,and the environmental and climate location coefficientswere used to modify the comprehensive assessment of the level of public service capacity of provincial sports grounds in China. Then,the overall and provincialsite resource status was presented using the method of exploratory spatial data analysis(ESDA)and spatial dynamic characteristics. The research showed that:1)The bearing capacity index before the correction of location coefficients is different from the weights on the three systems in terms of the pressure,status,and re-sponse included in the indicator system,and it shows the highest in the west,the second in the east,and the lowest in the middle;The global spatial characteris-tics of the bearing capacity index show a positive aggregation effect,while the provincial aggregation status shows that the low-low type aggregation area domi-nates,and Xinjiang and Guangdong are respectively located in the high value center of the western and eastern bearing capacity index. However,its influencehas not been radiated to the low-lying central regions. 2)The relative level of the bearing capacity index after the revised location coefficient is basically thesame as that before the correction. Among them,Jilin and Liaoning have obvious regional advantages,while Chongqing and Sichuan have obvious location disad-vantages,and the final bearing capacity index between provinces is quite different. The highest level is Tibet,and the remaining top eight provinces are Jiangsu,Shanghai,Qinghai,Xinjiang,Guangdong,Zhejiang,and Shandong. The lowest level is Guizhou;the overall capacity and local spatial characteristics of the finalbearing capacity index The spatial clustering similar to that before the correction was released,but the spatial dependence of the province was improved. In re-sponse to the above characteristics,the following suggestions are made:The construction of public services in sports venues in China should expand the diversityof supply channels and modes of operation while increasing the sharing and opening levels and utilization ratios among various social system resources,and give play to provincial locations in accordance with local conditions. On the basis of advantages,we can realize the accurate supply of regional people’s needs.