Identifying Significant Cost-Influencing Factors for Sustainable Development in Construction Industry Using Structural Equation Modelling

Abstract

Construction projects are typically conducted in a complex and dynamic environment in which the accumulation of many interrelated factors causes high uncertainty. Many factors may have negative effects on construction projects and thus cause project cost overruns. The aim of this study is to identify significant cost-influencing factors for sustainable development in construction. Considering the effects of economic and environmental factors on project cost is indeed a challenging task due to the shortage of appropriate methodology. This study examines the relationships between cost-influencing factors and construction project cost by using a structural equation model based on the generalized maximum entropy (GME) and Bayesian estimation methods. The advantages of GME and Bayesian methods are discussed, and results obtained from the statistical analysis are provided for illustration. The results can enhance cost performance through the identification and evaluation of the cost-influencing factors. The improved project performance is considered as an important step to transit into a sustainable development in construction. The sustainable development may greatly affect the emission reduction target of the industry.

Applications of Bayesian approaches in construction management research: a systematic review

“…In addition, Bayesian approaches were incorporated into other techniques or applied separately for different objectives, such as BIM (Hu and Castro-Lacouture, 2019), multi-agent systems (Karakas et al , 2013) and SEM (Zhao et al , 2020), which shows the great flexibility and application potential of Bayesian approaches.…”

Coping with Knowledge Inertia for Improving R&D Team Creativity by Using Structural Equation Modeling and Hierarchical Multiple Regression

“…where B is the matrix of path coefficients indicating the direct effects of endogenous variables including knowledge inertia, team cognitive conflict, and team creativity on each other, Γ is the matrix of path coefficients indicating the direct effects of exogenous variables including intentional unlearning capability on endogenous variables including knowledge inertia, team cognitive conflict, and team creativity, Λx is the matrix of the factor loading value of item X, and Λy is the matrix of the factor loading value of item Y. Followed by Ma [50] and Zhao et al [51], combined with the parameter setting SEM model in Figure 2, equations ( 1) to (3) can be expressed in the vector and matrix forms as 3, combined with the path coefficient and significance (p value), the results of the hypothesis verification can be summarized as follows.…”

Cost Overrun Causative Factors in Road Infrastructure Projects: A Frequency and Importance Analysis

“…Considering the countries belonging to the Oceania region, the fact of including a single study that meets the three inclusion/exclusion criteria for the Oceania region (Creedy et al [18]) is not as limiting as that observed for the America and Europe regions. Despite this, the top-15 factors shown in Table 11 could be compared with the findings of other existing studies related to cost overruns on construction projects in the Oceania region; which focus on projects in Australia [74,98] and New Zealand [99][100][101]. Doloi [98] examines the causes of cost overruns in Australian construction projects, where several of the most important reported causes show several coincidences with the top-15 of cost overruns in road projects with the highest Influence Index found in this study: 'inadequate project planning', 'poor site management and supervision', 'inadequate contractor's experience', 'failures in design', 'price variation of materials', 'project scope changes', 'financial difficulties of owner', 'design changes', 'economy issues', and others.…”