Investigating the Latent Factors of Quality of Work-Life Affecting Construction Craft Worker Job Satisfaction

Shan, Yongwei; Imran, Hamza Ali; Lewis, Phil; Zhai, Dong

doi:10.1061/(asce)co.1943-7862.0001281

Cited by 27 publications

(35 citation statements)

References 48 publications

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“…The independent sample t-test has been commonly used to examine whether the mean values of a specific variable from two independent groups are significantly consistent, or whether they are significantly different [16,52]. The one-way ANOVA (analysis of variance) is usually used to check whether the mean values of a specific variable from more than two independent groups are significantly different [8].…”

Section: Mean Analysismentioning

confidence: 99%

“…All the professionals came from the China Construction Industry Association (CCIA) and were experienced in prefabrication, which ensured the authority and reliability of this study. The five-point Likert scale method was used to measure the degree of significance of factors [52], in which "1" refers to "negligible", "2" "insignificant", "3" "average", "4" "significant" and "5" "most important". To ensure the reliability and validity of the survey, the questionnaire was distributed to the professionals who were experienced in project management.…”

Section: Factors Affecting the Capital Cost Of Prefabricationmentioning

confidence: 99%

“…The independent sample t-test has been commonly used to examine whether the mean values of a specific variable from two independent groups were significantly different [16,52,59]. Table 4 suggests that there exists deviation between experienced and inexperienced respondents (Figure 3).…”

Section: T-testmentioning

confidence: 99%

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Factors Affecting the Capital Cost of Prefabrication—A Case Study of China

Xue

Zhang

et al. 2017

Sustainability

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Abstract:As a sustainable construction method, prefabrication has become popular in many nations. However, there are many challenges for prefabrication, especially in terms of cost. Previous studies have revealed that higher capital cost was the most important barrier to the implementation of prefabrication. Thus, the objective of this study is to explore and evaluate the critical factors affecting the capital cost of prefabrication and examine how cost management may be affected by the "experience", "corporate responsibility", and "participant function" as a fix independent factors. To achieve the research objective, semi-structured interviews were conducted with 11 experts for the development of the questionnaire. Then, a questionnaire survey was conducted to investigate the significance of 49 factors related to prefabrication capital cost. The survey results revealed that "Specification and standards for prefabricated building design", "Related experience of manager", and "Rationality of precast component split" were the most critical factors. In addition, "experience", "corporate responsibility", and "participant function" had significant impact on the evaluation of capital cost factors. The findings can facilitate developing a benchmark framework for exploring the factors affecting the capital cost of prefabrication in China.

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Section: Mean Analysismentioning

confidence: 99%

Section: Factors Affecting the Capital Cost Of Prefabricationmentioning

confidence: 99%

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Factors Affecting the Capital Cost of Prefabrication—A Case Study of China

Xue

Zhang

et al. 2017

Sustainability

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“…EFA was performed on the data set to extract the latent factors underlying a large number of variables [44,78]. Principal component analysis (PCA) is the most extensively used method and was used in this case [79].…”

Section: Exploratory Factor Analysismentioning

confidence: 99%

“…A component with an eigenvalue of less than 1 is considered less important and can be ignored. Meanwhile, the total variance % should reach 40% [78]. Furthermore, the slope was taken into account.…”

Section: Extraction Of Initial Factorsmentioning

confidence: 99%

Capital Cost Optimization for Prefabrication: A Factor Analysis Evaluation Model

Xue

Zhang

et al. 2018

Sustainability

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Abstract:High capital cost is a significant hindrance to the promotion of prefabrication. In order to optimize cost management and reduce capital cost, this study aims to explore the latent factors and factor analysis evaluation model. Semi-structured interviews were conducted to explore potential variables and then questionnaire survey was employed to collect professionals' views on their effects. After data collection, exploratory factor analysis was adopted to explore the latent factors. Seven latent factors were identified, including "Management Index", "Construction Dissipation Index", "Productivity Index", "Design Efficiency Index", "Transport Dissipation Index", "Material increment Index" and "Depreciation amortization Index". With these latent factors, a factor analysis evaluation model (FAEM), divided into factor analysis model (FAM) and comprehensive evaluation model (CEM), was established. The FAM was used to explore the effect of observed variables on the high capital cost of prefabrication, while the CEM was used to evaluate comprehensive cost management level on prefabrication projects. Case studies were conducted to verify the models. The results revealed that collaborative management had a positive effect on capital cost of prefabrication. Material increment costs and labor costs had significant impacts on production cost. This study demonstrated the potential of on-site management and standardization design to reduce capital cost. Hence, collaborative management is necessary for cost management of prefabrication. Innovation and detailed design were needed to improve cost performance. The new form of precast component factories can be explored to reduce transportation cost. Meanwhile, targeted strategies can be adopted for different prefabrication projects. The findings optimized the capital cost and improved the cost performance through providing an evaluation and optimization model, which helps managers to evaluate cost management level of prefabrication and explore key inducers for high capital cost.

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