Structuring the prediction model of project performance for international construction projects: A comparative analysis

2009 ◽  
Vol 36 (2) ◽  
pp. 1961-1971 ◽  
Author(s):  
Du Y. Kim ◽  
Seung H. Han ◽  
Hyoungkwan Kim ◽  
Heedae Park
Keyword(s):  
Comparative Analysis ◽  
Prediction Model ◽  
Construction Projects ◽  
Project Performance ◽  
International Construction

Determining the relationship between conflict factors and performance of international construction projects

2014 ◽  
Vol 21 (4) ◽  
pp. 369-382 ◽  
Author(s):  
Eyad Zouher Al-Sibaie ◽  
Ali Mohammed Alashwal ◽  
Hamzah Abdul-Rahman ◽  
Umi Kalsum Zolkafli
Keyword(s):  
Internal Control ◽  
Construction Projects ◽  
Project Performance ◽  
Project Managers ◽  
Path Modeling ◽  
Content Type ◽  
Team Members ◽  
International Construction ◽  
Two Factors ◽  
And Performance

Purpose – Conflict was recognized as a major cause of inefficiency and limited performance of construction projects. Factors pertaining to conflict in construction are vast; however, there have been less recognition of these factors in international construction projects. The purpose of this paper is to provide in-depth understanding of conflict in this context and analyze how it influences project performance. Design/methodology/approach – A questionnaire survey was used to collect data from 161 professionals working in Malaysian companies, which are undertaking construction projects overseas. Findings – Analyzing the data using factor analysis revealed six new factors of conflict: external, internal, control-related, knowledge-related, mismanagement, and social conflicts. Further analysis of the data using partial least squares-path modeling (PLS-PM) affirmed a significant relationship between project performance and two factors of conflict only: internal and social. The results also showed that conflict contributes to about 27 percent of the variance in project performance. Originality/value – This paper provided a clear picture for project managers and team members about specific aspects of conflict and how to mitigate them to attain better performance of international construction projects.

Project performance prediction model linking agility and flexibility demands to project type

2021 ◽  
Author(s):  
Marco Aurélio Oliveira ◽  
Luiz V. O. Dalla Valentina ◽  
André Hideto Futami ◽  
Osmar Possamai ◽  
Carlos Alberto Flesch
Keyword(s):  
Prediction Model ◽  
Performance Prediction ◽  
Project Performance

scholarly journals FUZZY MULTI-CRITERIA DECISION MAKING MODEL FOR SUBCONTRACTOR SELECTION IN INTERNATIONAL CONSTRUCTION PROJECTS

2015 ◽  
Vol 22 (2) ◽  
pp. 210-234 ◽  
Author(s):  
Serdar ULUBEYLI ◽  
Aynur KAZAZ
Keyword(s):  
Construction Projects ◽  
Decision Criterion ◽  
Practical Application ◽  
Human Judgment ◽  
Qualitative And Quantitative ◽  
International Construction ◽  
Weak Points ◽  
Initial Idea ◽  
Decision Making Model ◽  
Selection Of

A general contractor’s ability to select proper subcontractors in foreign projects is a key competitive advantage. Toward this aim, a subcontractor selection model (CoSMo) was developed in this study. As a computational approach, the fuzzy sets method was employed because it can model human judgment by means of linguistic values, combining qualitative and quantitative decision criteria into an aggregate measure. Although the algorithm may be complex for easy acceptance by industrial practitioners, this disadvantage was minimized through a computer-supported system. In order to gain a better understanding of the current practice of CoSMo, a real world construction project was conducted. As a result, it was observed that CoSMo has high practical application and can be used as an advisory system by satisfying principal contractor’s requirements to reduce the risk involved in the selection of a subcontractor. Moreover, it gives an initial idea of how subcontractors perform on each decision criterion and allows the main contractor to understand the picture on the strong and weak points of each bidder and thereby to take conscious decisions.

scholarly journals SIMILARITY ASSESSMENT OF COUNTRIES TO FACILITATE LEARNING FROM INTERNATIONAL CONSTRUCTION PROJECTS

2017 ◽  
Vol 4 (1) ◽  
Author(s):  
Beste Ozyurt ◽  
Gozde Bilgin ◽  
Irem Dikmen ◽  
M. Talat Birgonul
Keyword(s):  
Construction Projects ◽  
Online Questionnaire ◽  
Political Condition ◽  
Similarity Assessment ◽  
International Construction ◽  
Related Information ◽  
Financial Condition ◽  
Governance Systems ◽  
Construction Experience ◽  
The Right

Companies’ ability to learn from projects is a source of competitive advantage in project-based industries. Learning from experiences in international markets is particularly important for global contractors so that the right bidding strategy can be developed, effective project governance systems can be established, and similar mistakes are not repeated. In this study, we assert that countries can be clustered according to their similarity so that experiences gained in these markets can be transferred and adapted to forthcoming projects. Thus, similarity factors to be used for clustering of countries can be identified, and a methodology can be developed to store, retrieve and reuse country-related information in international construction projects. In this paper, we report the factors identified for similarity assessment of countries to be used to facilitate learning from projects. As a result of literature review, interviews with experts and an online questionnaire administered to company professionals who have international construction experience, 12 factors have been identified for clustering of countries. As a result of ranking analysis; factors of “development level of and culture in the construction industry”, “political condition of the country” and “financial condition of the country” are obtained as the most important factors. The identified factors will be explained and how the clustering of countries can help companies to extract valuable information from previous experiences will be discussed.

scholarly journals Investigating Rework: Insights from the Malaysian Construction Industry

2021 ◽  
Vol 14 ◽  
pp. 1-9
Author(s):  
Jeffrey Boon Hui Yap ◽  
Shi Min Tan
Keyword(s):  
Quality Management ◽  
Construction Industry ◽  
Construction Projects ◽  
Poor Quality ◽  
Project Performance ◽  
Statistical Techniques ◽  
Cost Overruns ◽  
Delivery Performance ◽  
Communication Design ◽  
Design Changes

Construction practitioners recognise that rework is undesirable due to the detrimental effects. While rework literature has examined rework causation factors in construction projects, the problem continues to plague the industry resulting in poor delivery performance. To better understand this phenomenon and given the scarcity of Malaysian-based rework study, a questionnaire survey involving 130 Malaysian construction practitioners (consultants, contractors and clients) were undertaken to obtain feedback about nature, implications, causes and solutions for rework. Data were analysed using descriptive statistical techniques to prioritise the variables studied. From the analyses, rework is a causal factor for delays and cost overruns, higher wastage and productivity inhibitor. The findings revealed the leading causes of rework are poor quality management, improper planning, lack of communication, design changes and poor subcontractor management. Some practical rework minimisation approaches are also suggested to better manage and prevent rework towards enhanced project performance.

scholarly journals Impact of the Lean Start up Method on Project Performance Indicators

2020 ◽  
pp. 80-82
Author(s):  
Ekaterina Pavlovna Burmistrova
Keyword(s):  
Project Management ◽  
Comparative Analysis ◽  
Performance Indicators ◽  
Project Performance ◽  
Start Up ◽  
Lean Startup

The article considers the Lean Startup method, highlights and reveals its features. Also, its provides a comparative analysis of this method with other approaches to project management. Special attention is paid to revealing the influence of the Lean Startup method on project performance indicators.

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