營建工程現場之人力配置決策模式; PREDICTING ALLOCATION OF ON-SITE SUPERVISORY MANPOWER FOR CONSTRUCTION PROJECTS

NCUIR > Engineering College > Graduate Institute of construction engineering > Electronic Thesis & Dissertation > Item 987654321/3044

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/3044

Title:	營建工程現場之人力配置決策模式;PREDICTING ALLOCATION OF ON-SITE SUPERVISORY MANPOWER FOR CONSTRUCTION PROJECTS
Authors:	黃俊維;Huang-Jhun Wei
Contributors:	營建管理研究所
Keywords:	營建管理;決策模式;案例式推理;人力資源配置;營造現場;Allocation;Supervisory manpower;Overhead;On-site;Human resource management;Cost;CBR
Date:	2006-11-03
Issue Date:	2009-09-21 12:03:53 (UTC+8)
Publisher:	國立中央大學圖書館
Abstract:	營建工程之人事費用支出向來即為營造公司主要爭議之一，且其人力配置亦無一明確規範可遵循，近年來已有許多研究利用各式研究方法尋求最佳化之人事成本控制，以便於公司之財務規劃；而營建業為一經驗導向之傳統產業，台灣之營造公司對於人事費用之控制亦常根據過往之案例經驗及學術之研究，營建業間接成本與工地管理人員成本隨著專案的大小而有所變動。一般來說，其範圍約介於總工程成本的1%至10%之間，為成本預估之重要影響因素，故若能正確的估計成本和工地管理人員配置為影響專案工程利潤的重要關鍵。若無法準確估算工程之利潤，則可能導致人力配置不符實際施工需求，造成工程品質管控問題或增加公司人事費用。本研究蒐集台灣近16年來共79筆工程案例，經過統計分析，篩選適用案例66筆，並利用案例式推理(Case Based Reasoning, CBR)理論建立專案工程人力配置預測之模式，以期根據工程各項性質，預估工程之利潤且考量工期長短，進而依據產值估算工程所須管理人員數目及其配置情形，提供適合之管理人員決策之參考依據。 In the highly competitive construction industry of Taiwan, a slightly inaccurate estimation of a project can easily cause loss of the bid, especially in erroneously estimating costs and allocation of on-site supervisory manpower that usually offsets the profit gained from the project and even jeopardizes the management processes of the project. This research developed a model based on mathematical regression and case-based reasoning to predict costs and allocation of on-site supervisory manpower for construction projects. It is founded on laborious processes of data collections and analyses by matching statistical assumptions, and includes construction projects of residential buildings, industrial office buildings, commercial buildings and industrial construction. The model quantifies the costs and allocation of on-site supervisory manpower for both owners and contractors before initiating or bidding their projects. Findings confirm that the variation degree of prediction by the model presents the accuracy rate at 88.47%. Construction projects with characteristics of non-crashing schedule, floor area less than 35,000 m2, height less than 50 meters, and single site are accurately predicted.
Appears in Collections:	[Graduate Institute of construction engineering] Electronic Thesis & Dissertation

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