由於運用特徵價格模型探討影響不動產價格之變數，國內外相關之文獻數量甚為豐富，但對於影響議價空間比率之變數，較少有研究者探討，由於議價空間比率影響賣方及買方之訂價或出價策略與對成交價格之預期，另對於估價人員採用市場比較法時，僅得待售案例時之情況調整亦有所幫助，故本研究試圖從蒐集相關不動產成交案例，探討有關影響其議價空間比率之變數。
因本研究之資料範圍鎖定成屋且透過仲介成交之案件，故透過與仲介經紀從業人員之訪談並與文獻回顧相關理論作相互印證，廣納可能之變數，並搜集台北市、縣成屋實際委託價格及交易資訊。將訪談蒐集所得之交易價格資料及變數，運用Excel 及SPSS統計軟體，透過敘述統計、相關係數分析、折線圖分析、特徵估價法之多元廻歸模型等方法，分析影響議價空間比率之因素，及其影響之程度。
實證結果發現：影響議價空間比率之顯著變數如下：
（一）區位變數有：樹林、林口、新莊為正相關，議價空間比率顯著較高，大安區為負相關，議價空間比率相對較低。
（二）成交時間變數有：97年第四季因金融風暴，該季議價空間比率顯著較高。
（三）物件個別屬性變數有：是否1樓、屋齡、平均委託單價與議價空間比率為正相關，透天產品與議價空間比率為負相關，透天產品議價空間比率顯著較低。
（四）總體因素變數有：北市北縣拍賣移轉件數與議價空間比率為正相關，北縣市買賣移轉件數與議價空間比率為負相關。
本研究建議買賣交易人或投資者應針對交易標的所在區位、交易時間點、標的物個別條件以及總體指標需深入了解，賣方在訂價或買方在出價斡旋時，將更能提高交易成功之機率。物件位於相對偏遠地區，由於條件相對較差，賣方在開價上需預留較大議價空間，並有讓價準備，而買方可多收集相關成交資訊，以減少因資訊不充足而支付較高之價格貼水。
另外，當市場上發生重大事件導致房屋市場變動時，此時仲介角色更具挑戰性， 應提供賣方相關分析資訊，協助使其提早瞭解市場變動情況，避免損失加劇。對於一樓產品，買賣雙方價格認知差異較大，應提供相近條件之成交行情，若是店面或商用產品，可再提供租金收益資訊，易使雙方對於價格較有共識，並促進交易價格之合理性。
而不動產估價師執行台北縣、市之估價案件時，若採用市場比較法，收集之比較案例為待售尚未成交之物件，可參考各區位議價空間比率之平均數，再評估上述顯著變數之正負相關性，酌予上下調整，以增進待售價格情況調整之精確度。 / Although there are abundant sources of references regarding the use of Hedonic pricing models to study the relationship between real estate pricing variables and real estate price volatility, relatively few were dedicated to the research of price concession variables. Price concession variables determine sellers' asking prices and buyers' bid prices, or the expected deal price of a bid/ask strategy and even provide useful indications to real estate evaluators taking the market comparison approach when there are no actual deals to compare. Therefore, in this research we aimed to collect samples of actual real estate deals made to determine the variables that affect degrees of price concession by analyzing the degrees of price concession in proportion to bid/ask prices.
In this research, we confined our area of study to completed constructions transacted through real estate agencies. Through interviews with real estate agents and reviews of past theoretical references, we attempted to gather all possible variables from the time buyers and sellers approach real estate agencies to the time a deal is made; we also gathered data of bid prices, asking prices and deal prices of completed constructions situated in the various administration districts within Taipei City and Taipei County. Interview results, pricing data and the possible variables we had identified were analyzed using Excel and SPSS; our statistical analysis included descriptive statistics, correlation analysis, line charts and multiple regression of the Hedonic pricing model. The purpose of our analyses was to determine factors that influence the degree of price concession as well as the extent of such influence.
Our research results found the following variables that significantly influence the degree of price concession:
(1) Location variable: Shulin, Linko and Hsinchuang districts are positively correlated, suggesting a higher degree of price concession; Daan district is negatively correlated, suggesting a lower degree of price concession.
(2) Timing variable: The degree of price concession during the fourth quarter of 2008 was significantly higher because of the global financial crisis.
(3) Object-specific variables: Whether the property is situated on the first floor and aging variables are positively correlated to the degree of price concession; whether the property is an independent house is negatively correlated to the degree of price concession, suggesting a lower degree of price concession for independent house properties.
(4) Macro factors: The number of court auctions in Taipei City and County is positively correlated to the degree of price concession; the number of property sales in Taipei City and County are negatively correlated to the degree of price concession.
Through this research, we advise that property buyers, sellers and investors should gain further insights into the location, timing, characteristics and the overall environment relating to the properties they wish to close deals for. These insights will help buyers and sellers set bid/ask prices that are more likely to close deals, thereby reducing the cost of prolonged negotiations. Properties located in remote areas are have a disadvantage; sellers should reserve more room for negotiation and be prepared to make price concessions, while buyers should gather more information related to the deal of similar properties to avoid paying higher premiums due to lack of information.
Furthermore, the role of real estate agencies becomes more challenging in the occurrence of major events which cause volatility within the real estate market. Real estate agents should provide sellers the relevant data analysis to facilitate early anticipation of market changes, thereby preventing further losses. For properties located on the first floor, since there are relatively wider discrepancies between sellers' and buyers' expectations, real estate agents should provide more information related to the deals of similar properties to reconcile their differences. If the properties are for retail or commercial purposes, real estate agents may also provide information on rental or revenue to reconcile the understanding between buyers and sellers and give more rationality to deal prices.
For real estate evaluators attempting to evaluate properties situated in Taipei City and County using the market comparison approach but lacking deal references, they may consider taking the average degree of price concession across all administrative districts and adjust upwards or downwards based on correlations to the above significant variables and produce a more accurate indicator for the properties pending sale.
| Identifer | oai:union.ndltd.org:CHENGCHI/G0096923006 |
| Creators | 邱千惠, Chiou, Daisy |
| Publisher | 國立政治大學 |
| Source Sets | National Chengchi University Libraries |
| Language | 中文 |
| Detected Language | English |
| Type | text |
| Rights | Copyright © nccu library on behalf of the copyright holders |
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