Assessing Egyptian construction projects performance using principal component analysis

被引:18
|
作者
Marzouk, Mohamed Mahdy [1 ]
Gaid, Emad Fayez [2 ]
机构
[1] Cairo Univ, Dept Struct Engn, Fac Engn, Cairo, Egypt
[2] Orascom Construct, Cairo, Egypt
关键词
Key performance indicators (KPIs); Exploratory factor analysis (EFA); Overall performance; Performance assessment model; Principal component analysis (PCA);
D O I
10.1108/IJPPM-06-2017-0134
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Purpose The construction sector is a major contributor to the Egyptian economy and gross domestic products, plus considered as one of its fastest-growing sectors. Various deficiencies such as low productivity, delays, cost overrun, poor quality, etc. have plagued the construction sector, leading to undesirable project performance across Egypt and several other countries. One of the best methods to measure and improve performance evaluation and consequently a step toward industry improvement is key performance indicators (KPIs). The paper aims to discuss this issue. Design/methodology/approach A questionnaire survey was conducted to identify the importance index for 35 KPIs. The KPIs were identified and selected based on an extensive literature review and one on one interview with expert construction professionals. Moreover, exploratory factor analysis method has been used to analyze and determine the inter-relationships between the set of indicators. Findings Seven indicators that have the highest importance indicator were selected to create project overall performance indicator assessment models to consistently measure the performance of different construction projects. Seven equations are introduced reflecting the output of the research while considering both organization size and project type. Practical implications The proposed evaluation assessment models can be used to: evaluate the relative success of projects; indicate the areas of strengths and weaknesses in performance and establish company benchmarking. Three projects were selected to validate the performance evaluation models. Originality/value This paper provides mathematical assessment models for evaluating overall construction project performance in Egypt, taking into consideration organization size and project type. Previously published research works on the subject matter are quite limited, and frequently deal with only one or two selected aspects.
引用
收藏
页码:1727 / 1744
页数:18
相关论文
共 50 条
  • [41] The use of principal component analysis for the construction of the Water Poverty Index
    de Senna, Larynne Dantas
    Maia, Adelena Goncalves
    Freire de Medeiros, Joana Darc
    RBRH-REVISTA BRASILEIRA DE RECURSOS HIDRICOS, 2019, 24
  • [42] KERNEL PRINCIPAL COMPONENT ANALYSIS FOR THE CONSTRUCTION OF THE EXTENDED MORPHOLOGICAL PROFILE
    Fauvel, M.
    Chanussot, J.
    Benediktsson, J. A.
    2009 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-5, 2009, : 1094 - +
  • [43] Analyzing delay causes in Egyptian construction projects
    Marzouk, Mohamed M.
    El-Rasas, Tarek I.
    JOURNAL OF ADVANCED RESEARCH, 2014, 5 (01) : 49 - 55
  • [44] Assessing the integration of electricity markets using principal component analysis: Network and market structure effects
    Evans, Lewis
    Guthrie, Graeme
    Videbeck, Steen
    CONTEMPORARY ECONOMIC POLICY, 2008, 26 (01) : 145 - 161
  • [45] Assessing prescription drug abuse using functional principal component analysis (FPCA) of wastewater data
    Salvatore, Stefania
    Roislien, Jo
    Baz-Lomba, Jose A.
    Bramness, Jorgen G.
    PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, 2017, 26 (03) : 320 - 326
  • [46] Feature Extraction of Hyperspectral Image Using Principal Component Analysis and Folded-Principal Component Analysis
    Deepa, P.
    Thilagavathi, K.
    2015 2ND INTERNATIONAL CONFERENCE ON ELECTRONICS AND COMMUNICATION SYSTEMS (ICECS), 2015, : 656 - 660
  • [47] Using software to monitor performance in construction projects
    Christian, J
    Cariappa, A
    COMPUTER TECHNIQUES FOR CIVIL AND STRUCTURAL ENGINEERING, 1999, : 229 - 233
  • [48] Comparative Performance Analysis of Three Algorithms for Principal Component Analysis
    Landqvist, Ronnie
    Mohammed, Abbas
    RADIOENGINEERING, 2006, 15 (04) : 84 - 90
  • [49] Predictive model for construction labour productivity using hybrid feature selection and principal component analysis
    Ebrahimi, Sara
    Kazerooni, Matin
    Sumati, Vuppuluri
    Fayek, Aminah Robinson
    CANADIAN JOURNAL OF CIVIL ENGINEERING, 2022, 49 (08) : 1366 - 1378
  • [50] Texture analysis of images using Principal Component Analysis
    Bharati, MH
    MacGregor, JF
    PROCESS IMAGING FOR AUTOMATIC CONTROL, 2001, 4188 : 27 - 37