Using principal component analysis to identify latent factors affecting cost and time overrun in public construction projects

成本超支 排名(信息检索) 范围(计算机科学) 施工管理 鉴定(生物学) 多样性(控制论) 质量(理念) 风险分析(工程) 不可预见费 过程管理 施工前服务 项目管理 运营管理 业务 工程类 项目策划 计算机科学 项目管理三角形 建筑业 建筑工程 系统工程 土木工程 哲学 植物 认识论 机器学习 人工智能 生物 程序设计语言
作者
Simon Wyke,Søren Munch Lindhard,Jesper Kranker Larsen
出处
期刊:Engineering, Construction and Architectural Management [Emerald Publishing Limited]
卷期号:31 (6): 2415-2436 被引量:11
标识
DOI:10.1108/ecam-02-2022-0189
摘要

Purpose Cost and time are two of the primary benchmarks in which construction projects are measured. A variety of factors, however, affect cost and time on construction projects, as identified in previous research. This has led to a need for better understanding how factors affecting cost and time overruns on public construction projects can be managed more efficiently. The purpose of this paper is to address these issues. Design/methodology/approach In this study 26 factors affecting cost and time overruns on construction projects were identified, through qualitative interviews with project managers from Danish governmental agencies and through a literature review. Through principal component analyses the 26 factors were subsequently narrowed down to four primary latent factors. Findings The identified four latent factors affecting cost and time overruns on public construction projects were lack of quality management, lack of project pre-planning, lack of user management and lack of project management. Originality/value Previous research has focussed on increasing knowledge by identifying and ranking factors affecting time and cost performance. This has led to the identification of an overwhelming number of factors to use for managing construction projects. The present research reduced the number of factors by clustering them into key latent factors responsible for most of the deviation in performance, narrowing the scope of construction cost and time management into a few tangible key focus areas. This supports and improves fast decision-making that is necessary in a changeable environment such as construction.
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