| DC 欄位 |
值 |
語言 |
| DC.contributor | 營建管理研究所 | zh_TW |
| DC.creator | 林秉緯 | zh_TW |
| DC.creator | Bing-wei Lin | en_US |
| dc.date.accessioned | 2009-7-22T07:39:07Z | |
| dc.date.available | 2009-7-22T07:39:07Z | |
| dc.date.issued | 2009 | |
| dc.identifier.uri | http://ir.lib.ncu.edu.tw:444/thesis/view_etd.asp?URN=963205011 | |
| dc.contributor.department | 營建管理研究所 | zh_TW |
| DC.description | 國立中央大學 | zh_TW |
| DC.description | National Central University | en_US |
| dc.description.abstract | 近年來建築工程趨向大型化與複雜化，使得工程專案面臨之不確定性因素日益複雜，因此於投資專案前須對其風險加以掌握及了解，降低對專案與公司財務之衝擊，而本研究參考財務理論中評估風險影響之工具β，以其理論概念建立一適用於評估工程風險之風險係數，藉以了解個別投資專案受到風險影響之程度。本研究風險係數係以線性迴歸來評估專案報酬率變動相對於市場報酬率變動之敏感程度，其迴歸係數可反映專案報酬率與市場報酬率兩者間關係強度，而此迴歸係數即為所求之風險係數，若係數愈大表示專案面臨風險愈大，反之風險愈小。
本研究藉由案例蒐集取得推求風險係數所需數據，共蒐集67筆可供分析使用之案例，其專案類型為集合住宅。其次，本研究風險係數之推估考量到專案只能於完工後得到一個報酬率之問題，故本研究以相似專案之報酬率與其對應之市場報酬率來推求風險係數，而萃取相似專案之方式係採用案例式推理，利用專案各工項成本佔合約總價之比例與其它相關資訊等共18項因子來界定專案間相似程度，並用相似度演算法由資料庫中萃取相似度95%以上案例來推估風險係數。
本研究由蒐集案例中篩選出A、B、C三個專案來推估其風險係數，並說明其運用方式，而推估結果A專案之風險係數為0.49；B專案為0.95；C專案為1.18，由此知各專案面臨風險程度以A專案最小；B專案介於兩專案間；C專案最大。此外，本研究假設三個專案完工後之實際報酬率與當初評估之預期報酬率差異不大，因此A專案評估之報酬率為8.83%；B專案為8.13%；C專案為5.52%。若將評估之報酬率與風險係數結合一起評估專案，可知投資A專案所獲取之報酬最高且風險最小，因此投資A專案為較佳選擇。本研究所推估之風險係數能幫助決策者了解各專案風險程度，作為公司評估專案時另一項參考依據，若再搭配其他專案評估方法一起運用，將有助於決策者於專案評估時做更詳細之判斷。
| zh_TW |
| dc.description.abstract | Fast, precisely, and automatically estimating investment risks for construction projects is usually what managers intend to achieve. Using well-known construction and management techniques, residential construction projects usually encounter relatively less uncertainty and are relatively easier to derive their risk status. This study develops a method to (1) define the market risk of residential construction project; and then (2) determine the risk coefficient of an input project based on 18 features of the project. Data collection follows the data sampling of 95% confidential level, 10% of error, and 20-80 proportion. As a result, detailed information of randomly-selected 67 residential projects were collected, normalized, and analyzed. The estimation model combines the regression and case based reasoning (CBR) techniques to yield the coefficient for each project. The findings conclude that the risk coefficient exists and is highly related to inflation of construction materials in recent years.
| en_US |
| DC.subject | 案例式推理 | zh_TW |
| DC.subject | 風險係數 | zh_TW |
| DC.subject | 評估風險 | zh_TW |
| DC.subject | 建築工程 | zh_TW |
| DC.subject | CBR | en_US |
| DC.subject | residential project | en_US |
| DC.subject | risk estimation | en_US |
| DC.subject | risk coefficient | en_US |
| DC.title | 建築工程專案投資風險推估之研究 | zh_TW |
| dc.language.iso | zh-TW | zh-TW |
| DC.title | Estimating Investment Risk for Residential Construction Projects | en_US |
| DC.type | 博碩士論文 | zh_TW |
| DC.type | thesis | en_US |
| DC.publisher | National Central University | en_US |