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養(yǎng)老地產(chǎn)選址影響因素研究

發(fā)布時(shí)間:2018-01-11 07:07

  本文關(guān)鍵詞:養(yǎng)老地產(chǎn)選址影響因素研究 出處:《深圳大學(xué)》2016年碩士論文 論文類型:學(xué)位論文


  更多相關(guān)文章: 養(yǎng)老地產(chǎn) 選址 影響因素 層次分析


【摘要】:在我國(guó),社會(huì)人口老齡化正變得越來(lái)越嚴(yán)重,如何養(yǎng)老已經(jīng)成為重要的社會(huì)問(wèn)題。建設(shè)專門的養(yǎng)老機(jī)構(gòu)供老人集中居住,并提供相應(yīng)的服務(wù),進(jìn)而解決養(yǎng)老問(wèn)題是值得借鑒的國(guó)外經(jīng)驗(yàn)。建設(shè)養(yǎng)老機(jī)構(gòu),選址是第一步,也是項(xiàng)目成功開(kāi)發(fā)的關(guān)鍵一步。養(yǎng)老機(jī)構(gòu)/地產(chǎn)作為地產(chǎn)行業(yè)的一個(gè)細(xì)分,目前國(guó)內(nèi)外都已對(duì)其進(jìn)行了較深入的研究。如何設(shè)定具有地區(qū)特色的養(yǎng)老地產(chǎn)選址指標(biāo),是本文研究的主要內(nèi)容。本研究按如下步驟展開(kāi):首先,確定養(yǎng)老地產(chǎn)選址的影響因素。通過(guò)文獻(xiàn)分析、調(diào)查訪談和專家咨詢,初步確定養(yǎng)老地產(chǎn)選址的影響因素:地理環(huán)境、生活便利性和成本費(fèi)用。在此基礎(chǔ)上,設(shè)計(jì)老年人對(duì)各因素重要性判定的測(cè)量量表,通過(guò)進(jìn)一步實(shí)證研究檢驗(yàn)量表的信度和效度,得到最終的測(cè)量量表。其次,進(jìn)行數(shù)據(jù)的收集分析以及選址模型的建立。通過(guò)在深圳及全國(guó)范圍內(nèi)隨機(jī)發(fā)放206份調(diào)查問(wèn)卷,確定老人在選擇養(yǎng)老地點(diǎn)時(shí)對(duì)各因素的重視程度,調(diào)研結(jié)論有:⑴地理環(huán)境因素中,環(huán)境景觀與地理位置因素重要性遠(yuǎn)高于周邊土地用途和面積規(guī)模因素;⑵生活便利性因素中,交通狀況和醫(yī)療條件重要性遠(yuǎn)高于商業(yè)完善性和人口因素;⑶對(duì)于成本費(fèi)用,每個(gè)因素都有約九成受訪者表示非常關(guān)注。然后利用層次分析法計(jì)算出每個(gè)指標(biāo)的綜合權(quán)重值,建立養(yǎng)老地產(chǎn)選址模型。最后,通過(guò)新豐、大鵬、貝嶺居三個(gè)實(shí)際案例對(duì)養(yǎng)老地產(chǎn)選址模型進(jìn)行驗(yàn)證分析,大鵬項(xiàng)目被選為最優(yōu)方案。結(jié)合三個(gè)項(xiàng)目的特點(diǎn),提出如下建議:大鵬項(xiàng)目定位為養(yǎng)生養(yǎng)老社區(qū),新豐項(xiàng)目定位為全齡混合社區(qū),貝嶺居項(xiàng)目定位為醫(yī)養(yǎng)機(jī)構(gòu)綜合體。
[Abstract]:In China, population aging society is becoming more and more serious, how pension has become an important social problem. The construction of pension institutions specifically for the elderly to live together, and provide the corresponding services, and to solve the pension problem is foreign experiences. The construction of pension institutions, the location is the first step, but also a key step the success of the project. The development of pension institutions / real estate as a subdivision of the real estate industry, both at home and abroad have been deeply studied in this paper. How to set the location of the local characteristics of the endowment real estate index, is the main content of this paper. This research is as follows: first, determine the impact of pension real estate location factors. Through literature analysis, interviews and expert consultation, preliminary determine the influence factors of endowment real estate location: geographical environment, life convenience and cost. On this basis, the design of the elderly Measurement scale of people to judge the importance of various factors, through further empirical research to test the reliability and validity of the scale, get the final measurement table. Secondly, the data collection and analysis. Through the construction of the location model in Shenzhen and nationwide randomly distributed 206 copies of the questionnaire, to determine the importance of each factor the old man in the selection of the support point, research conclusions are: the geographical environment factors, environment landscape and geographical factors of importance is much higher than the surrounding land use area and scale factors; the life convenience factors, traffic conditions and medical conditions are more important than commercial integrity and demographic factors; the cost for each. Approximately 90% of the respondents said the factors are very concerned. Then use AHP to calculate the comprehensive weight of each index value, the establishment of pension real estate location model. Finally, through the new Feng, Dapeng, beilingju three actual cases of endowment real estate location model analysis, Dapeng project was selected as the optimal solution. According to the characteristics of the three projects, put forward the following suggestions: Dapeng project positioning for health retirement community, Xinfeng project positioning for the whole age mixed community, beilingju project location for medical care institutions complex.

【學(xué)位授予單位】:深圳大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2016
【分類號(hào)】:TU984.12;D669.6;F299.23

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