發(fā)布時(shí)間：2018-03-30 19:52

  本文選題：住宅租金　切入點(diǎn)：空間分異　出處：《云南財(cái)經(jīng)大學(xué)》2013年碩士論文

【摘要】：通過(guò)幾十年的發(fā)展，昆明市房地產(chǎn)住宅市場(chǎng)已經(jīng)成為了成熟的市場(chǎng)。房地產(chǎn)住宅市場(chǎng)包括了住宅銷售市場(chǎng)與住宅租賃市場(chǎng)，與住宅銷售市場(chǎng)相比，住宅租賃市場(chǎng)發(fā)展較晚，發(fā)展到現(xiàn)在仍存在較多問(wèn)題待解決。這些問(wèn)題的出現(xiàn)引起了社會(huì)的關(guān)注，問(wèn)題主要有市場(chǎng)管理不當(dāng)、法律法規(guī)不完善、租金定價(jià)混亂等。房租與房?jī)r(jià)一樣，與地理區(qū)位有著密切的聯(lián)系，由于區(qū)位因素在空間分布上的不均衡，使得房租在空間上呈現(xiàn)差異性特征，這就導(dǎo)致租金的確定有較多影響因素。為了解決租金定價(jià)難這一問(wèn)題，幫助住建部門更好的管理租金，本文運(yùn)用ArcGIS軟件中的地統(tǒng)計(jì)模塊，對(duì)昆明市住宅租金進(jìn)行空間分析、建立空間模型，同時(shí)探索著把特征價(jià)格理論應(yīng)用于昆明市的住宅租賃市場(chǎng)，并結(jié)合具體城市構(gòu)建特征價(jià)格模型研究住宅租金的空間分異，，主要工作及結(jié)論如下： 研究了住宅價(jià)格空間分異理論與特征價(jià)格模型，在理論研究的基礎(chǔ)上以昆市主城區(qū)包括了五華區(qū)、盤龍區(qū)、西山區(qū)、官渡區(qū)等4個(gè)行政區(qū)的研究區(qū)域內(nèi)的住宅租賃市場(chǎng)為研究對(duì)象進(jìn)行了實(shí)證研究。運(yùn)用地理信息系統(tǒng)中的空間插值技術(shù)（Krigring插值法），得到了昆明市住宅租金等值線圖，發(fā)現(xiàn)昆明市住宅租金分布呈典型的扇形分布模式。租金以翠湖為中心向四周不規(guī)律的降低，在北市區(qū)、滇池旅游度假區(qū)、佴家灣與高新區(qū)出現(xiàn)了租金的次中心，盤龍江對(duì)租金影響顯著。通過(guò)聚類分析按照租金的高低把樓盤分為了五個(gè)等級(jí)，發(fā)現(xiàn)低租金的樓盤主要分布在城市的外緣區(qū)域，高租金樓盤主要分布在城市中心。 并以昆明市主城區(qū)為研究區(qū)域，選擇了12個(gè)住宅特征作為模型的自變量，對(duì)研究區(qū)內(nèi)的486個(gè)有效樣本進(jìn)行了特征價(jià)格模型分析，得出了影響租金的特征因素，并按照行政區(qū)劃分了子市場(chǎng)，進(jìn)一步分析得出住宅租金的影響因素，得出了區(qū)位因素、建筑因素與鄰里因素是影響住宅租金的重要因素。
[Abstract]:Through decades of development, the real estate housing market in Kunming has become a mature market. The real estate housing market includes the residential sales market and the residential rental market. Compared with the residential sales market, the residential rental market develops relatively late. Up to now, there are still many problems to be solved. The emergence of these problems has aroused the attention of the society. The main problems are improper market management, imperfect laws and regulations, confusion in rent pricing, etc. Rent is the same as house prices. There is a close relationship with geographical location. Because of the imbalance of location factors in spatial distribution, the rent is different in space, which leads to a lot of factors affecting the determination of rent. In order to solve the problem of difficult rent pricing, In this paper, we use the geostatistics module in ArcGIS software to analyze the housing rent in Kunming, and establish a spatial model. At the same time, we explore the application of the characteristic price theory to the residential rental market in Kunming. Based on the characteristic price model of specific cities, this paper studies the spatial differentiation of residential rent. The main work and conclusions are as follows:. This paper studies the spatial differentiation theory and the characteristic price model of housing price. On the basis of the theoretical research, the main urban area of Kunming includes Wuhua District, Panlong District, and Xishan District. The residential rental market in Guandu District and other administrative regions is studied as an empirical study object. By using the spatial interpolation technique in GIS, the contour map of housing rent in Kunming is obtained, which is based on the Krigring interpolation method. It is found that the rent distribution of residential buildings in Kunming is a typical sector pattern. The rent decreases irregularly in the center of Cuihu Lake. In the north urban area, Dianchi tourist Resort Zone, Yangjiawan and Hi-Tech Zone, there are sub-centers of rent in Yangjiawan and Hi-tech Zone. Panlongjiang has a significant impact on rent. According to the cluster analysis, the real estate is divided into five grades according to the level of rent. It is found that the low-rent buildings are mainly distributed in the outer edge of the city, and the high-rent buildings are mainly distributed in the center of the city. Taking the main urban area of Kunming as the study area, 12 residential features are selected as independent variables of the model, 486 effective samples in the study area are analyzed with the feature price model, and the characteristic factors affecting the rent are obtained. The sub-market is divided according to the administrative region, and the influence factors of housing rent are further analyzed, and the location factor, the building factor and the neighborhood factor are the important factors that affect the housing rent.
【學(xué)位授予單位】：云南財(cái)經(jīng)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：F299.23

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