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| 空间相互作用模型中的目的地竞争效应 ——基于中国城市间铁路客流数据的实证研究 | |
| 引用本文： | 陶卓霖,戴特奇,郑清菁,梁进社.空间相互作用模型中的目的地竞争效应 ——基于中国城市间铁路客流数据的实证研究[J].地理科学,2017,37(2):181-189. |
| 作者姓名： | 陶卓霖 戴特奇 郑清菁 梁进社 |
| 作者单位： | 1.北京大学城市与环境学院,北京 100871 2.北京大学城市规划与设计学院,广东 深圳 518055 3.北京师范大学地理学与遥感科学学院,北京 100875 |
| 基金项目： | 国家自然科学基金项目(41401170)资助 |
| 摘 要： | 目的地竞争模型是空间相互作用领域的重要进展之一,但其有效性尚未得到一致认可,且缺乏基于中国的实证依据。基于中国2010年城市间铁路客流数据,采用目的地竞争模型进行实证分析,并与传统空间相互作用模型相比较,以检验目的地竞争模型在实际应用中的有效性。结果表明：① 空间结构对中国城市间铁路客流存在显著影响,目的地之间存在较强的竞争效应;② 目的地竞争模型的引入显著地减弱了距离衰减参数的空间自相关程度,较大程度上改善了传统空间相互作用模型的距离衰减参数标定偏误问题;③ 既有研究中在区域尺度下对传统空间相互作用模型（即重力模型）参数的标定及实证分析可能会存在偏误,目的地竞争模型这一改进模型具备应用价值。 |
| 关 键 词： | 空间相互作用模型 重力模型 目的地竞争模型 空间结构 距离衰减参数 |
| 收稿时间： | 2016-01-19 |
| 修稿时间： | 2016-10-25 |
Competing Effects Among Destinations in Spatial Interaction Models:An Empirical Study Based on Intercity Railway Passenger Data of China |
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| Zhuolin Tao,Teqi Dai,Qingjing Zheng,Jinshe Liang.Competing Effects Among Destinations in Spatial Interaction Models:An Empirical Study Based on Intercity Railway Passenger Data of China[J].Scientia Geographica Sinica,2017,37(2):181-189. | |
| Authors: | Zhuolin Tao Teqi Dai Qingjing Zheng Jinshe Liang |
| Institution: | 1.College of Urban and Environmental Sciences, Peking University, Beijing 100871,China 2.School of Urban Planning and Design, Peking University, Shenzhen 518055, Guangdong, China 3.School of Geography, Beijing Normal University, Beijing 100875, China |
| Abstract: | Spatial interaction model is an important research field. Existing studies indicate spatial structure of destinations has a significant impact on spatial flow. Thus, traditional spatial interaction models suffer model misspecification problem because the absence of spatial structure variable. Among the modified models introduced to solve the misspecification problem, the competing destinations model is the most widely-used one.The competing destinations modelassumes that the travelers’ destinations selecting process adopts a hierarchical information processing strategy.Based on this strategy, the spatial decision process is divided into two stages. In the first stage, travelers select a destinations cluster containing a set of destinations; in the second stage, travelers select an individual destination from the cluster selected in the first stage. The competing destinations model has been empirically applied in numerous studies in foreign countries.However, the empirical conclusions with respect to the validity of the competing destinations model are still far from agreement. Moreover, none empirical study of this model has been conductedin China. This study applies the competing destinations model based on intercity railway passenger data in 2010 in China, and test its validity by comparing it with traditional spatial interaction models. The estimations of the competing destinations model as well as the traditional spatial interaction model are conducted by the maximum likelihood method, which is calculated by a new method distinguishing from existing studies, i.e. the Particle Swarm Optimization (PSO) algorithm. The conclusions can be drawn as follows. 1) Spatial structure has a significant impact on intercity railway passenger flow of China, and there exists a significant competing effect among destinations both in the system-wide estimation results and in the origin-specific estimation results. The system-wide distance-decay parameter estimated in the competing destinations model (-1.165) is more negative than in the traditional spatial interaction model (-1.108). In the other hand, 124out of a total number of 177 (the ratio is 70% ) origin-specific distance-decay parameter estimationsare more negative in the competing destinations model than in the traditional spatial interaction model, while 140 out of 177 (79%) origin-specific destinations accessibility indicator estimations are negative in the competing destinations model. These characteristics have not ever been reported in Chinese context in existing studies. 2) The competing destinations model reduces the spatial autocorrelation among distance-decay parameters, thus significantly corrects the misspecification problem of traditional spatial interaction models. These results illustrate that the competing destinations model performs significantly better than the traditional spatial interaction model, and thus the improvements by the competing destinations model are empirically valid in Chinese context. 3) The parameters estimation and empirical analysis of traditional spatial interaction models (i.e. gravity model) in existing literature may be biased, while the competing destinations model is an efficient improvement and can play an important part in empirical analysis. |
| Keywords: | spatial interaction models gravity model competing destinations model spatial structure distance-decay parameter |
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