Purpose
The purpose of this paper is to develop a model for complex interconnected structure of various factors interacting with delay in order to identify the most important factors influencing and influenced by delay based on their interrelations.
Design/methodology/approach
Reviewing literature and interviewing with local experts selected from the Iranian construction industry, top 58 delay factors were identified and categorized into six major groups. The interrelations among these factors were, then, modeled using the system dynamics (SD) approach. The resulting causal loop diagrams obtained from SD were used subsequently for identifying the most significant factors influencing and influenced by delay through the Decision Making Trial and Evaluation Laboratory (DEMATEL) method. The impact of factors on each other was finally determined based on the opinions of 63 experts selected from the Iranian community of consultants, contractors, and clients.
Findings
According to the analysis, eight out of the 58 factors were identified as the most influencing factors on delay, and nine factors were found to be the most influenced factors by delay in the field of delay analysis. The study also concluded that factors related to labors are the most important and influential factors. In addition, factors related to client were the most influencing factors and external-related factors were the least important ones. At the end, some recommendations to reduce variation of delay in the construction projects are presented as well.
Originality/value
Considering the interconnected structure of the factors, the paper identifies the most important factors interacting with time delay in construction projects.
Purpose
This paper aims to model different causal relations among factors interacting with labour productivity in order to recognize the most important factors influencing and influenced by it.
Design/methodology/approach
Top 60 factors affecting labour productivity were determined and grouped into 5 major groups by reviewing previous research and interviewing relevant experts. The interactions of factors were modelled using system dynamics (SD) approach. The resulting causal loop diagrams obtained from SD were then applied for identifying the most crucial factors influencing and influenced by labour productivity through the decision-making trial and evaluation laboratory (DEMATEL) method. The impact of factors on each other was finally determined based on the opinions of 63 experts selected from the Iranian construction industry.
Findings
The results indicated that factors such as fatigue, lack of labour motivation and lack of skill are the most influencing, and factors such as schedule delay and inflation in the cost of execution are the most influenced by labour productivity. In the end, a set of recommendations to improve construction labour productivity was also presented.
Originality/value
The main contribution of the study is proposing a novel method which is capable of providing insights into how causes and effects of construction labour productivity are interrelated. Furthermore, the proposed method makes this study distinct from previous research in the light of prioritizing factors and offering recommendations according to the interrelationships among factors.
PurposeThis study aims at introducing a claim management model based on building information modeling (BIM) for claims that can be visualized in BIM models.Design/methodology/approachBased on the results of a questionnaire survey, 10 claims were identified as claims that can be visualized in BIM models (named hard claims in this study). Then, a BIM-based claim management model was developed and used in a case study.FindingsA BIM-based claim management model is represented. The claim management process through this model consists of four steps: (1) extracting project information, identifying conditions prone to claim and storing them into a relational database, (2) automatically connecting the database to building information model, (3) simulation of the claims in building information model and (4) final calculations and report.Practical implicationsThe proposed model can provide benefits to parties involved in a claim, such as early identification of potential claims, large space for data storage, facilitated claim management processes, information consistency and improved collaboration.Originality/valueThere are a few studies on providing solutions to claim management based on BIM process. Hence, the original contribution of this paper is the attempt to set a link between BIM and claim management processes.
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