شاخص ضریب اطمینان املاک و مستغلات در برنامه کاربردی وب مبتنی بر GIS و SPSS
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|17562||2007||7 صفحه PDF||سفارش دهید|
نسخه انگلیسی مقاله همین الان قابل دانلود است.
هزینه ترجمه مقاله بر اساس تعداد کلمات مقاله انگلیسی محاسبه می شود.
این مقاله تقریباً شامل 3507 کلمه می باشد.
هزینه ترجمه مقاله توسط مترجمان با تجربه، طبق جدول زیر محاسبه می شود:
- تولید محتوا با مقالات ISI برای سایت یا وبلاگ شما
- تولید محتوا با مقالات ISI برای کتاب شما
- تولید محتوا با مقالات ISI برای نشریه یا رسانه شما
پیشنهاد می کنیم کیفیت محتوای سایت خود را با استفاده از منابع علمی، افزایش دهید.
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : International Journal of Project Management, Volume 25, Issue 2, February 2007, Pages 171–177
Real estate confidence index, as an efficient and effective information-oriented measure, is being studied and applied to the China’s real estate market. It not only assists government with the macro control of real estate market, but also guides investment and consumption. In order to assure the accuracy and real time of the RECI, more factors should be considered and an efficient system based on IT is needed. This paper presents a set of real estate confidence indices via considering synthetically efficient demand and supply, latent demand and latent supply on the basis of domestic and overseas research status and establishes relevant mathematical models at all levels. Then a Web GIS and SPSS WebAPP-based indices-issued system model is constructed. The relevant key techniques are analyzed, and the functions of the model are discussed. Otherwise, according to current conditions, the application of the system is conceived.
Real estate confidence index (RECI) can reflect and measure the running status, booming degree and equilibrium degree of the real estate market (REM). It is one of important means of macro control of the REM and is also the main component of information-oriented warning systems for the REM  and . RECI is a widely studied research topic. For example, Research Centre for Real Estate at Texas A&M University in US has been compiling Texas RECI (TRECI) since the second quarter of 1999 . The Hong Kong Polytechnic University has also compiled their real estate index (BRE Index) . However, these existing indices are regularly issued and mainly applied through Internet or Intranet. Difficulties have been experienced in the process of data collection, compiling and releasing of indices. For example, data collection is often not in time, which results in index issued late. If the original data used for compiling the indices are not released, users will only know about the indices and cannot verify them. In addition, data collected in previous studies were primarily based on questionnaires. RECI developed upon these data reflects mainly latent demand of residential property, without taking into account other important factors such as current effective demand and supply (D&S), and latent supply  and . RECI should be a set of indices involving the confidence of consumers and the confidence of investors and governments in the REM, which reflect synthetically the current status and development trend of the REM. Thus the effective D&S index and the latent supply index should be implicated in RECI, as well as the latent demand index. In this study, a new RECI system is developed by integrating data of latent supply, current effective demand and supply, as well as latent demand. At the same time, through the use of Web GIS and SPSS WebAPP technologies, data collection and analysis, the dissemination of indices are effectively conducted using these online technologies. The subsequent sections of this paper described how the RECI is developed and used to support decision making processes in the real estate market. Specifically, the second section presents how the RECI system is established based on efficient D&S, latent demand and latent supply, and main models for confidence indices are constructed, including a composite index model, monomial index models and other models. Weighting coefficients of monomial indices and sub-indices are also determined. In Section 3, the key techniques constructing RECIs-release systems are analyzed. Section 4 presents the model of RECIs-release systems based on Web GIS and SPSS WebAPP (W-S) and describes the functions of the system. An application of the system is discussed in Section 5. Finally, Section 6 concludes the study.
نتیجه گیری انگلیسی
In China’s real estate market, real estate confidence indices are being studying and used widely. A set of accurate and real-time RECIs can guide the healthy development of real estate market. This paper compiles a set of real estate confidence indices through synthetically considering the effective D&S, latent demand and latent supply, and constructs a Web GIS-and-SPSS WebAPP-based indices-issued system model, which may effectively and efficiently establish and release RECIs, analyze them via using GIS. The implementation of the model is conceived. It is expected that the research can provide an efficient means for the information-oriented mechanism of China real estate market.