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### 竞争型公共设施区位决策——概念、选址原则及模型构建

1. 南京信息工程大学地理与遥感学院, 江苏 南京 210044
• 收稿日期:2016-01-04 修回日期:2016-05-10 出版日期:2016-10-20 发布日期:2020-09-07
• 作者简介:

作者简介：宋正娜（1980-）,女,山东潍坊人,讲师,博士,主要从事城市发展与区域规划、福利地理学相关研究。E-mail:songzhengna@163.com

• 基金资助:
国家自然科学基金项目（41201170、41301104）、南京信息工程大学大学生实践创新训练计划项目(201410300146)资助

### Competitive Public Facilities Location Decision: Concept, Location Selection Principle and Model Construction

Song Zhengna()

1. School of Geography and Remote Sensing, Nanjing University of Information Science & Technology, Nanjing 210044, Jiangsu, China
• Received:2016-01-04 Revised:2016-05-10 Online:2016-10-20 Published:2020-09-07
• Supported by:
National Natural Science Foundation of China(41201170, 41301104), College Students Practice Innovation Training Program of NUIST(201410300146)

Abstract:

Competitive public facilities are both public-welfare and competitive, among them the comprehensive hospitals are most representative. Their location decision is relatively more complicated. This study aims to solve the problem that how to seek the optimal locations of such facilities. First of all, this study puts forward the concept of “competitive public facilities” which had been not defined systematically and normatively, pointed out that “the spatial equilibrium to coordinate the efficiency and equity” is the basic principle in location selection of competitive public facilities, and summarized a series of location requirements that they are to abide by the spatial interaction between the supply and demand, to limit the extreme travel cost from the settlement to the nearest facilities, to minimize the weighted total travel cost, to restrain the facility scale threshold, and to distinguish appropriately in spatial distribution between the higher level competitive public facilities and the ones. Secondly, gravity P median model was constructed with the probability distribution to replace the proximity rule by embedding the improved Huff probability model in the classic P median model. In such new model, the facility scale factor was introduced to solve facilities location and scale simultaneously, and then two factors were constrained that they are the biggest travel cost from some settlement to the corresponding nearest facility as well as the minimum facility scale. The objective function and a series of constraints just been mentioned can guarantee to realize the multiple targets including the spatial equity—efficiency, quality of service fairness and scale efficiency. Finally, the model was applied to the empirical test as to the comprehensive hospitals location decisions in Wuxi urban district, the results showed that: 1) The optimal facilities distribution is more balanced, and new hospitals locations form three layers that are the main core, secondary core and outer layers, which can comprise reasonable structure with more appropriate division, meanwhile the scale configuration of hospitals is in conformity with the population distribution on the whole. 2) The spatial equity of the optimal locations calculated with the new model shows bigger advantage, since a class of related indicators are improved that they are the Gini coefficient of available service resources quantity potentially for residents and other such indexes. 3) And at the same time, it is decreased properly that is the weighted average travel time from the settlements to all the hospitals, which can achieve the collaborative layout and spatial mismatch among the hospitals and the community health service organizations. In addition, it is important to note that this study focuses on the discussion of theory and approach, rather than the application with the intact model. Futhermore, when the new model is applied to the actual planning and location selection, concerned parameters and constraints should be adjusted appropriately by planning situation. All in all, the above study can support certain decision basis for future public facilities distribution adjustment or new town construction, meanwhile can enrich the concerned research about public facilities location allocation both here and abroad.

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