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Since the hidden costs of construction projects are subtle and strong, difficult to quantify, it has not yet resulted in completing research system. This paper analyzes the literature to identify the concepts and fo rms of hidden costs, then summarizes the factors affecting the construction of 20 projects in hidden costs. Factor analysis extracted six comprehensive factor variables to represent the most influential factors, propose appropriate measures to control construction projects of hidden costs, and lay the foundation for further quantifying the hidden costs for these factors.

In recent years, with the continuous expansion of the scale of China’s construction industry, some problems of construction companies have gradually emerged, and the more prominent is the issue of cost management. The cost of a construction project includes not only the explicit costs on the financial statements, but also the hidden costs that are hard to quantify. The hidden cost is the same as the categorical cost, which is a part of the total cost of the project, which seriously affects the development of construction enterprises [

The influencing factors of hidden costs of construction projects are many and complex. In order to fully identify various influencing factors, it is necessary in order to classify them in a specific way [

Influencing factor number | Influencing factor | |
---|---|---|

Construction party influence factors | X 1 | Project organization structure design |

X 2 | Subcontract management | |

X 3 | The degree of perfection of the system and mechanism | |

X 4 | Information transfer rate | |

X 5 | Quality and technical level of personnel | |

X 6 | Safety production management | |

X 7 | Construction schedule | |

X 8 | Selection of construction plan | |

X 9 | Mechanical equipment repair and maintenance | |

X 10 | Construction site layout | |

X 11 | Construction machinery selection | |

X 12 | Initiative for staff work | |

Owner’s influence factor | X 13 | project changes |

X 14 | Progress payment amount | |

X 15 | The reward and punishment mechanism is unfair | |

X 16 | Unreasonable construction quality requirements | |

X 17 | Incomplete procedures | |

Designer influence factor | X 18 | Unreasonable design |

X 19 | Insufficient design | |

X 20 | Pattern delivery lag |

The data of quantitative analysis of influencing factors are collected by experts. The designed questionnaire mainly includes two parts: basic information and metrics. The basic information is the personal information of the experts, such as the work unit, the number of years of employment, professional titles, etc. It is used to score the influence degree of the influencing factors and record the relevant suggestions given by the respondents. The questionnaire is measured by the Liken 5 subscale, and 1 - 5 represents the degree of influence from low to high [

Because the experience of survey experts is different, and the influencing factors are altered in different engineering projects. The experts participating in the survey will also have a bias in understanding the importance of the influencing factors. In order to ensure that the sample data of the survey meet the reliability requirements, it is necessary in order to verify the validity of the consistency. Using the SPSS statistical analysis software, the Cronbach α coefficient was selected as the calculation test method, and the reliability test results are presented in

As can be seen from

Factor analysis is the study of how lost at a minimum the amount of information extracted several comprehensive factors representative variables from a number of original variables, and how to make it multivariate data analysis methods with a strong interpretability [

Cronbach’s Alpha | Cronbach’s Alpha is based on standardized items | Number of items |
---|---|---|

0.866 | 0.916 | 22 |

Statistical analysis of sample data using factor analysis begins with a suitability test for factor analysis of influencing factor variables, including KMO (Kaiser-Meyer-Olkin) test and Bartlett sphericity variable partiality test. To examine whether the factor variables are suitable for factor analysis, the test results are shown in

According to the statistical principle of KMO test and Bartlett sphericity test [

Using the principal component analysis method, the eigenvalues of the correlation matrix of the influencing factor variables is obtained. The results are shown in

Factor analysis generally selects factors with eigenvalues greater than 1 [

In order to obtain professional actors, it is necessary to rotate the common factors so that the information difference of each factor is expanded as much as possible [

If the load of the factor in the matrix is greater than 0.5, the variable is considered to be very significant in the common factor [

Sampling sufficient Kaiser-Meyer-Olkin metric | 0.677 | |
---|---|---|

Bartlett’s sphericity test | Approximate Chi-Square | 3576.398 |

Degree of freedom | 120 | |

Significant level | 0.000 |

Composition | Initial eigenvalue | Extracting the sum of squared loads | ||||
---|---|---|---|---|---|---|

Total | Percentage of variance | Cumulative % | Total | Percentage of variance | Cumulative % | |

1 | 4.891 | 24.317 | 24.317 | 3.891 | 24.317 | 24.317 |

2 | 3.163 | 16.770 | 41.087 | 3.163 | 19.770 | 41.087 |

3 | 2.866 | 14.915 | 56.002 | 2.866 | 17.915 | 56.002 |

4 | 2.226 | 12.910 | 68.912 | 2.226 | 13.910 | 68.912 |

5 | 1.482 | 7.264 | 76.176 | 1.482 | 9.264 | 76.176 |

6 | 1.224 | 4.836 | 81.012 | 1.224 | 4.836 | 81.012 |

7 | 0.852 | 3.886 | 84.898 | |||

8 | 0.602 | 3.356 | 88.254 | |||

9 | 0.521 | 3.157 | 91.411 | |||

10 | 0.433 | 2.807 | 94.218 | |||

11 | 0.233 | 2.208 | 95.977 | |||

12 | 0.181 | 1.739 | 96.108 | |||

13 | 0.118 | 0.739 | 97.847 | |||

14 | 0.106 | 0.666 | 98.512 | |||

15 | 0.090 | 0.563 | 99.075 | |||

16 | 0.049 | 0.309 | 99.384 | |||

17 | 0.043 | 0.269 | 99.653 | |||

18 | 0.038 | 0.152 | 99.805 | |||

19 | 0.022 | 0.111 | 99.916 | |||

20 | 0.018 | 0.084 | 100.000 |

Composition | Sum of squared rotational loads | ||
---|---|---|---|

Total | Percentage of variance | Cumulative % | |

1 | 3.427 | 21.421 | 21.421 |

2 | 2.841 | 14.757 | 36.178 |

3 | 2.792 | 14.451 | 50.629 |

4 | 2.448 | 13.300 | 63.929 |

5 | 2.120 | 9.248 | 73.177 |

6 | 1.850 | 7.835 | 81.012 |

Factor variable | Composition | |||||
---|---|---|---|---|---|---|

1 | 2 | 3 | 4 | 5 | 6 | |

X 1 | 0.052 | −0.098 | 0.107 | 0.066 | 0.857 | −0.003 |

X 2 | −0.172 | 0.658 | 0.073 | 0.019 | 0.214 | −0.204 |

X 3 | 0.153 | 0.393 | −0.158 | 0.530 | 0.130 | −0.143 |

X 4 | −0.063 | 0.078 | 0.717 | −0.027 | 0.030 | 0.273 |

X 5 | −0.036 | 0.477 | −0.030 | 0.096 | 0.260 | 0.302 |

X 6 | −0.024 | 0.577 | 0.105 | 0.218 | 0.253 | −0.172 |

X 7 | 0.090 | 0.150 | 0.015 | 0.792 | −0.177 | 0.120 |

X 8 | 0.567 | 0.089 | 0.063 | −0.170 | −0.034 | 0.278 |

X 9 | 0.684 | 0.026 | −0.054 | 0.213 | 0.022 | 0.095 |

X 10 | 0.598 | 0.156 | −0.295 | −0.078 | 0.369 | 0.058 |

X 11 | 0.556 | 0.240 | −0.144 | 0.090 | 0.388 | −0.051 |

X 12 | −0.118 | 0.097 | 0.546 | 0.445 | 0.103 | −0.132 |

X 13 | −0.047 | 0.674 | −0.065 | 0.193 | −0.100 | 0.432 |

X 14 | 0.565 | 0.101 | −0.012 | −0.036 | 0.023 | 0.347 |

X 15 | 0.412 | 0.076 | 0.040 | −0.083 | −0.036 | 0.615 |

X 16 | 0.142 | 0.796 | −0.054 | −0.112 | 0.005 | 0.145 |

X 17 | 0.326 | 0.635 | −0.078 | −0.054 | 0.030 | 0.046 |

X 18 | 0.396 | 0.229 | 0.055 | 0.541 | −0.354 | 0.205 |

X 19 | 0.837 | −0.017 | 0.187 | 0.023 | −0.042 | 0.123 |

X 20 | 0.669 | 0.095 | 0.314 | −0.021 | 0.129 | −0.011 |

Common factor number | Influence factor variable | Public factor naming |
---|---|---|

Y 1 | X 19 , X 9 , X 20 , X 15 , X 10 , X 8 , X 14 , X 11 | Participant skill level |

Y 2 | X 16 , X 13 , X 2 , X 17 , X 6 | Construction management |

Y 3 | X 4 , X 12 , X 20 | Level of participation |

Y 4 | X 7 , X 18 , X 3 | Pre-construction design plan |

Y 5 | X 1 | Project organization structure design |

Y 6 | X 15 | Progress payment |

Measures to control the hidden costs of construction projects usually include contract measures, technical measures, economic measures, and management measures. The following is a combination of six common factors to make recommendations for controlling the hidden costs of construction projects. The technological level of the participants is the most important thing factor. From the perspective of management measures, active control of hidden costs, increase of preventive input, increases the level of hidden cost management, thereby reducing the probability of unnecessary costs, and ultimately achieves control of construction projects. The purpose of the cost of sex. From the perspective of construction management, construction companies can adopt certain management measures to become passively accepted as operational control. From the perspective of the level of cooperation of the participating parties, construction enterprises can adopt contractual measures to transfer some uncontrollable hidden costs through contract, so as to reduce the hidden costs of construction projects. Construction enterprises can reduce the incidence of pre-construction design planning and project organization structure design on the hidden costs of construction projects through contractual measures and economic measures. Construction enterprises should adopt technical measures to fully consider the impact of the regional economy on hidden costs and formulate corresponding pre-control strategies. The introduction of six common factors allows construction companies to more clearly grasp the key points affecting cost control, and the contract, technology, economic and management measures proposed by combining six factors help construction enterprises to better improve hidden cost management. Reduce hidden costs.

From the perspective of the project participants, the influencing factors of the hidden costs of the project are summarized, and six common factors are extracted to provide decision makers with targeted control measures.

According to the actual situation of different projects, different weights are given to the extracted common factor variables, which help decision makers to evaluate the control of hidden costs of construction projects.

Although this paper conducts a preliminary quantitative analysis of the influencing factors of the hidden costs of construction projects, the interrelationship between the various influencing factors still needs in-depth exploration and research.

The authors declare no conflicts of interest regarding the publication of this paper.

Liu, S.Y., Wu, J.Y., Yue, Y. and Zhang, Y.Q. (2019) Analysis of Factors Affecting the Hidden Costs of Construction Projects Factor Analysis. Open Access Library Journal, 6: e5665. https://doi.org/10.4236/oalib.1105665