Next Article in Journal
The Vicious Circle of Working Hours, Sleep, and Recovery in Expert Work
Next Article in Special Issue
Job Satisfaction and Perceived Health in Spanish Construction Workers during the Economic Crisis
Previous Article in Journal
A Physiologically-Based Pharmacokinetic Modeling Approach Using Biomonitoring Data in Order to Assess the Contribution of Drinking Water for the Achievement of an Optimal Fluoride Dose for Dental Health in Children
Previous Article in Special Issue
A Critical Review of the Use of Virtual Reality in Construction Engineering Education and Training
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Using Interpretative Structural Modeling to Identify Critical Success Factors for Safety Management in Subway Construction: A China Study

1
School of Civil Engineering, Southeast University, Nanjing 211189, China
2
School of Civil Engineering, Lanzhou University of Technology, Lanzhou 730050, China
3
School of Construction Management and Real Estate, Chongqing University, Chongqing 400045, China
4
Institute of Engineering Management, Hohai University, Nanjing 211100, China
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2018, 15(7), 1359; https://doi.org/10.3390/ijerph15071359
Submission received: 10 April 2018 / Revised: 26 June 2018 / Accepted: 26 June 2018 / Published: 28 June 2018
(This article belongs to the Special Issue Improving Safety, Health, and Wellbeing in Construction)

Abstract

:
With the rapid development of urbanization in China, a vast number of subway projects are under construction and planned in many cities. However, the complexities of the environment in subway construction inherently bring about many uncertainties and risk factors. Understanding the inherent properties of the critical success factors (CSFs) will contribute significantly to the subway construction. From this perspective, this paper aims to identify the CSFs for safety management in subway construction. This study screened preliminary CSFs through a literature review and in-depth interviews with experts in China. Based on the data gathered and subsequently analyzed from the questionnaire surveys, a final total of 24 CSFs were identified. Then, interpretative structural modeling was employed to ascertain the interrelations among them. The result showed that the factors concerning the engineering survey and design not only occupy relatively higher scores in the questionnaire survey but also contribute significantly latent impacts on other factors. In addition, the creation of a reasonable schedule and the investment of the safety measures were also found to have a fundamental impact on the safety management of subway construction. This research guided the safety managers in determining the most important safety factors they must face and provided them valuable information that could promote safety performance and decrease the number of accidents over the course of subway construction.

1. Introduction

One of the major objectives and tasks for the 13th Five-Year Plan (2016–2020) period in China is to increase the urbanization level from the current 56.1 to 60%. In order to deal with urbanization pressures such as increasing traffic volume and growing demands for land, a vast number of subway projects are under construction and planned in many cities. As a result, as of 31 December 2017, up to 44 cities in China had been approved for the construction of subway systems, and 35 cities had already been operating subway systems. However, the complexity of the environment in subway construction inherently leads to many uncertainties and risk factors, which may lead to accidents [1]. Additionally, subway construction through dense urban areas increases the safety risks on nearby drainage systems, water supply systems, and gas pipelines [2]. Subway construction involves complicated and high-risk construction work. For example, a section of a tunnel collapsed suddenly on 15 November 2008, causing 21 fatalities and 24 injuries [3]. Therefore, it is extremely important to identify the risk factors for safety management in subway construction, which could promote safety performance and decrease the number of accidents.
Safety is the system property or quality, which is necessary and sufficient to ensure that the following construction activities. [4]. According to Hollnagel, most socio-technical systems are intractable, and performance variability is inevitable [5]. Consequently, resilience engineering was employed to enhance the ability of a complex socio-technical system to adapt or absorb disturbance, disruption, and change. [6]. Hollnagel presented the four abilities that characterize resilient systems, which have been widely adopted by resilience engineering researchers: anticipating, monitoring, responding, and learning [5]. A philosophy of safety management, e.g., Safety II, demonstrates the purpose of safety management is the ability to succeed under varying conditions, so that the number of intended and acceptable outcomes is as high as possible [4]. This means that safety is managed by what it achieves (successes, things that go right). In order to do this, safety management cannot only be reactive, it must also be proactive. Currently, safety management in construction projects is divided by different phases. Realizing the influence of design work in subway safety management, Seo and Choi introduced the concept of a safety impact assessment to achieve “design-for-safety” in the design phase [7]. An event tree analysis was applied to quantify the risk at the preliminary design stage in underground construction [8]. Ding et al. developed a safety risk identification system, which aims to assess pre-construction safety risks based on construction drawings [9]. Reducing or eliminating safety risks in the design has been a common trend with great potential in subway projects. Research can also be found in the construction phase. For example, Haslam et al. revealed that front line managers and supervisors are the key individuals in accidents through the investigation of 100 individual construction accidents [10].
Since the beginning of modern project management in 1960s, academic researchers have sought to identify a definitive list of Critical Success Factors (CSFs), the key things that project managers must get right in order to deliver a successful product [11]. Previous studies have identified many CSFs for construction project implementation, planning processes, and project risk management [12,13]. Aksorn and Hadikusumo identified 16 CSFs of safety factors and found that management support was the most effective factor [14]. Additionally, Ng et al. tested and validated 31 safety factors to evaluate a contractor’s safety performance at the organization level and the project level [15]. Mahmoudi et al. developed a framework that includes seven main factors and 120 sub factors for the improvement of safety in construction projects and validated the relative importance of the factors [16]. Twenty-five factors affecting construction site safety were identified and summarized into five main factors, consisting of: organizational poor safety awareness of top management, lack of training, poor safety awareness of project managers, reluctance to input resources for safety, and reckless operations [17]. Besides these, Rosa et al. utilized the Functional Resonance Analysis Method (FRAM) to assess risk in sustainable construction and adopted the Analytic Hierarchy Process to reduce the subjectivity in the evaluation of FRAM variability [18]. After an extensive literature review in the field of Resilience Engineering, Patriarca et al. summarized the research in Resilience Engineering and extracted relevant research factors using Factor Analysis and Multi-Dimensional Scaling. [19]. Meanwhile, safety risk factors from contractors and subcontractors [20], safety incentives [21,22], worker’s fatigue-management [23], safety training [17,24,25], safety inspections and job hazard analyses [26,27,28], safety climate [29,30,31], accident and near-miss investigations [32,33,34], and emergency response plans [28,35] were identified as factors influencing the relative effectiveness of CSFs for safety management in the construction phase.
Most prior studies concentrated on exploring CSFs for safety management in construction, with fewer studies aiming to consider the interrelationships among the CSFs in subway construction. To address this knowledge gap, a method for ascertaining the interrelations among CSFs was proposed. The objective of this paper is to provide a reasonable method to identify the CSFs for safety management in subway construction in order to enhance safety performance. The research objectives include: (1) determining the CSFs for safety management in subway construction; and (2) evaluating the relative importance of CSFs as well as the interrelations among them. The paper is organized and presented in the following structure: Section 2 elaborates on the preliminary screening of factors for safety management in subway construction. A final list of factors is determined through the questionnaire survey method and ISM (Interpretative Structural Modeling) is introduced in Section 3. Section 4 applies this method to identify the most important factors and demonstrates the interrelationships among the factors. Based on the result from Section 4, a further discussion about the findings is conducted in Section 5. Finally, Section 6 draws the overall conclusions.

2. Preliminary Screening of Factors for Safety Management in Subway Construction

The research goal of this paper is to explore the CSFs for safety management in subway construction in order to enhance safety management performance. To achieve this purpose, collecting the factors was a critical process of the research, which provided a foundation for the following analysis. This paper puts emphasis on extracting common elements for safety management factors from the activities and processes in subway construction.
In order to establish a comprehensive list of factors, the factors for safety management in subway construction should be considered from different views. As a construction project always starts with planning and design, followed by a construction stage, decisions made upstream have inherent influences on other stages [36]. Other researchers also found that design work is contributory to lifecycle safety performance in the construction industry [37,38,39]. Therefore, the influencing factors of planning and design should be considered for safety management in subway construction.
The following two typical options were adopted for the selection of factors. First, a literature review was used to identify the original factors. Second, preliminary factors were selected based on in-depth interviews with experts. Code of construction safety management is a significant part in literatures, which is summary of construction safety management after years’ experience. Therefore, code reading and review is an effective way to acquire factors (see Table 1). Though codes from different counties and regions slightly distinguish in contents and forms, safety management work has something in common.
According to the literature review, 28 related original factors were found. There were some similarities between the 28 related original factors, so in-depth interviews were then conducted to ensure the reliability of those dimensions and factors. There were some similarities among the 28 related original factors. As a consequence, the experts came to the consensus that the original factors should be reduced to 24 preliminary factors. Finally, a summary of 24 factors are presented in Table 2, which could be grouped into five dimensions based on their properties and attributes: engineering survey and design, construction safety management measures, construction sites security measures, workers’ safety behavior, and guarantee and supervision mechanism.

3. Research Methodology

3.1. The In-Depth Interviews

In-depth interviewing is a qualitative research technique, which conducting intensive individual interviews with a small number of respondents to explore their perspectives on a particular idea, program, or situation [44]. In order to ensure the reliability of the preliminary screening of factors, five experienced experts who were engaged in long-term safety management works in subway construction in authoritative enterprises were invited to revise the initial list of factors. All five of experts had over 10 years of working experience and participated in more than three subway construction projects. Considering there were some similarities between the 28 related original factors, the experts came to the consensus that the original factors should be reduced to 24 preliminary factors. Questionnaire survey was refined based on the feedback from the in-depth interviews.

3.2. Questionnaire Survey

Questionnaire surveys, is widely used method for extracting or identifying key factors [41,45]. The questionnaire was designed to test the preliminary CSFs for safety management in subway construction, in particular from the angle of reasonability and operability. The questionnaire passed the validity and reliability test before being sent out. The survey was conducted in May–August 2017, Six hundred survey questionnaires were distributed to professionals (project employers, contractors, designers, supervisors, and government regulators). They are the main actors in the subway construction process and have a significant influence on safety management. In the first part of the questionnaire, respondents’ personal information was collected, including job title, age, gender, education level, working experience in the subway construction, and other related personal information. In the second part, they were asked to make their own judgments on the CSFs for safety management according to experience in subway construction. A five-point Likert scale was used for data collection about the preliminary CSFs (where 1—can be ignored or not important; 2—slightly important; 3—important; 4—very important; and 5—extremely important).
In total, 600 questionnaires were distributed and 182 of them were collected from project employers, contractors, designers, contractors, and government regulators. Table 3 presents the profile of the data collected via the questionnaires. Among them, over 60% of the respondents have more than 10 years of subway construction safety management experience. Twenty-one questionnaires were discarded and 161 valid questionnaires remained. The 21 questionnaires were found to be invalid due to a significant amount of missing or incomplete data (missing data > 10%) and a very high proportion of same answers. The respondent rate was 26.8%, consistent with the criterion of 20–30% for questionnaire surveys in the construction industry [46,47]. Therefore, this sample was adequate for data analysis.

3.3. Interpretative Structural Modeling (ISM)

Interpretative structural modeling (ISM) was first proposed by Warfield in 1973, with the aim of analyzing complex systems [48]. Wang et al. applied this method to classify the nine kinds of accident causes into five layers, with definitive relationships between different layers [49]. Tian et al. established the structure of the risk factors at the workplace and reflected the hierarchical relationships of factors [50]. Song et al. made use of ISM to determine the interrelations among vulnerability factors of an urban rail transit system [51]. Considering that subway constructions are continuously affected by many factors, the reason for selecting ISM is that it is a well-established methodology for identifying relationships among specific items, and is frequently used to provide a fundamental understanding of complex situations as well as to put together a course of action for solving a problem [52,53].
The ISM process is an interactive process in which a group of both directly related and different elements are organized into an all-inclusive systematic framework [54]. In virtue of the structural relationships diagram, it is easy to visualize the interrelationships between various elements [55]. The steps of ISM development is described below [56,57]:
Step 1: Identify the system factors set. A set of variables affecting the system is defined. The factors for safety management in subway construction were generated using literature review, in-depth interviews, and questionnaire surveys, as shown in Table 2.
Step 2: Construct the adjacency matrix. The adjacency matrix is employed to demonstrate the relationships among the factors in ISM, a i j is the adjacency value of the factor i to j ( i = 1 ,   2 ,   ,   n ;   j = 1 ,   2 ,   ,   n ). A panel of seven experts was invited to participate in making the adjacency matrix, consisting of three professors from Southeast University and four senior managers in Nanjing Metro Co., Ltd. (Nanjing, China). These experts all had more than 10 years of work experience, which could make the judgments more credible and reliable. Before making the judgments, several experts were consulted to ensure that the questions were properly phrased and established. In the process of constructing the adjacency matrix, direct relationships among factors were obtained from the judgments of the experts with the question: does the factor i have an impact on j? As a result, four rounds of discussion were carried out to reach an agreement were about the interrelations. The adjacency matrix is formed by the following three principles:
(1)
For the relationships a ij , if i has an impact on j , a ij = 1 ; if not, a ij = 0 and vice versa.
(2)
If there are strong mutual influences between i and j , then a ij and a ji equals 1, if the degree of mutual influence is different between them, then the larger equals 1, the smaller equals 0.
(3)
When i = j , then a i j = a j i = 0 .
The adjacency matrix A is as follows:
A = [ a 11 a 12 a 21 a 22 a 1 n a 2 n a n 1 a n 2 a n n ] n × n
Step 3: Generate the reachability matrix. The reachability matrix is used to represent the extent to which different nodes in a directed graph can reach (i.e., indirect influence) each other through certain channels.
Let
E = [ 1 0 0 1 0 0 0 0 1 ] n × n
be a n × n identity matrix, the adjacency matrix A and the unit matrix E leads to a new matrix A 1 , and the square of the new matrix A 1 can be calculated by using the Boolean rules ( 0 + 0 = 0 ,   0 + 1 = 1 ,   1 + 1 = 1 ,   0 × 0 = 1 ,   0 × 1 = 0 ,   1 × 1 = 1 ), the result is as follows: A 2 = ( A 1 ) 2 = ( A + I ) 2 = A 2 + A + I . Through sequential calculations, the reachability matrix R can be calculated by the formula:
( A + E ) ( A + E ) 2 ( A + E ) 3 ( A + E ) r = ( A + E ) r + 1 = R
R = [ R 11 R 12 R 21 R 22 R 1 n R 2 n R n 1 R n 2 R n n ] n × n
where R = ( A + E ) r is the reachability matrix of adjacency matrix A .
Step 4: The analysis of the reachability matrix. According to the reachability matrix, the reachability sets and antecedent sets of every factor must be determined. In the i th row R i of reachability matrix R , if R ij = 1 ( j = 1 ,   2 , ,   n ) , then the element R ij is put into the reachable set, which is expressed as S i . Meanwhile, in the j th column R j of reachability matrix R , if R ij = 1   ( i = 1 ,   2 , ,   n ) , then the element R ij is put into the antecedent sets, which is expressed as B j . The intersection of these sets, S i B j , is derived for all the factors. If S i B j = S i , and then the highest level of factors L 1 is identified. The column and row corresponding to L 1 are removed from matrix R . By the same decision rules, L 2 ,   L 3 ,   ,   L K can be identified. The last step is to establish the hierarchy model of ISM using each level of L .
Step 5: Draw the ISM relationships diagram. In accordance with the results of partitioning the reachability matrix, the top-level factor is positioned at the top of the hierarchy and the second level factor is placed just below the top level. This process is repeated until the bottom level factors are placed at the lowest position in the hierarchy.

3.4. Overall Research Methodology

A flowchart of the overall methodology combining the questionnaire survey method and the ISM process adopted here is presented in Figure 1. First, literature review and in-depth interviews methods were used to identify the preliminary factors. Secondly, the final list of factors was then determined through the questionnaire survey method. Then, the ISM was employed to evaluate the relative importance of each factor properly and the interrelations among them.

4. Result Analysis

4.1. Result Analysis of Questionnaire Survey

4.1.1. Reliability Analysis

Reliability analysis was performed on the 161 valid questionnaires, with the results indicating a high reliability (Cronbach’s α = 0.847). Shen et al. noted that the threshold value of Cronbach’s α for a reliable questionnaire is 0.70 [58].

4.1.2. Mean Value and Ranking of the Factors

The scores and rankings of the 24 factors were examined by descriptive statistics (Table 4). If the factor mean value is above 3, it means that it passed the verification. It was found that all 24 factors were critical as they all have mean values above 3. The mean values for these 24 factors range from a minimum of 3.16 (F22) to a maximum of 4.67 (F3). More than half (54%) of the factors’ mean values are over 4.00 (13 factors). This indicates that most of the factors are very important and can be used as CSFs for safety management in subway construction in China. Of the top five factors with the highest mean values, two belong to the dimension of engineering survey and design (D1). The result shows that engineering survey and design for safety management could strongly influence subway construction safety.
Based on the questionnaire survey data gathered and the comprehensive analysis of the data, 24 factors were identified as the CSFs for safety management in subway construction. After calculating and analyzing the questionnaire survey data, it was found that the total effects of the dimension layers on safety management in subway construction ranged from 3.57 to 4.27. Given that four out of the 10 top factors were located in the engineering survey and design dimension (Figure 2), it is believed that the role of the engineering survey and design phase in subway construction is a vital factor of successful safety management. Surveying surrounding buildings and municipal pipelines (F3, 4.67), safety training (F7, 4.62), design scheme constructability review (F5, 4.59), ensuring the investment of the safety measures (F23, 4.54), and the foreman’s safety attitude (F17, 4.53) were identified as the most important factors for safety management in subway construction; these were the top five factors, indicating that these factors played vital roles in safety management.

4.2. Result Analysis of ISM

The adjacency matrix and reachability were obtained as per the steps and rules discussed in ISM methodology Section 3.2. Figure 3 graphically presents these relationships, in which nodes represent the safety factors, arrows indicate their interrelations, and the arrow points to the affected node. It is clear that 31 pairs of direct relationships exist among the factors and no bidirectional relationship exists. Only one node (F24) is isolated from the other nodes, and the nodes F6, F7, F17, and F20 exhibit the strongest relationships. However, the indirect interrelations among the safety factors and how these factors influence subway construction remain obscure from this picture.
According to Figure 3, the adjacency matrix A was simultaneously generated based on the relationships among the factors. A reachability matrix M was used to represent the extent to which different nodes in a directed graph can reach each other through certain channels. The feature of transformation means that if there is one channel through which factor F i can reach F j directly, there is also one channel through which F j can reach F k . Therefore, there must be two channels through which F i can reach F k . The calculation process was implemented in Matlab (2018a) and the final result is presented in Table 5. All of the indirect impacts are reflected in the reachability matrix as 1* and the original interrelations are expressed as 1 in Table 5.
According to Step 4 for the level partitioning of matrix M in Section 3.2, the reachability sets and antecedent sets of every factor should be determined. The reachability set is composed of all of the related factors that F i can reach (on which F i has an impact), which are shown in the second column of Table 6. The antecedent set is the set composed of all of the factors that can reach F i , which are shown in the third column. The last column is the intersection set, which contains the common factors in the reachability and antecedent sets. In Table 6, factors F10, F16, F19, F20, and F24 were found at level 1 and subsequently removed before the next partition. The process was repeated for four times until all factors were well arranged.
In accordance with the results of partitioning the reachability matrix, the reachability matrix was rearranged, and the hierarchical structural structure diagram for the safety factors was drawn as a five-layer hierarchy, shown in Figure 4. A relationship between two factors is shown by an arrow which points from a higher-level variable to a lower-level variable. Several observations could be drawn from Figure 4. First, this model is not symmetric. Second, factor F24 is entirely independent and has no relationship with the other factors. Third, factors F1, F2, F3, F11, F21, and F23 are at the deepest layer of the structure. Factors F10, F16, F19, and F20 are at the surface layer of the structure. The rest of the factors are in the middle; moreover, factors F15, F17, and F18 have bidirectional relationships.

5. Discussion

Knowing what safety factors influence and how these factors influence subway construction is necessary to promote and improve safety performance level. With the assistance of in-depth interviews and questionnaire survey, a final total of 24 CSFs was identified. Through the analysis of all of the indicator scores, shown in Table 3, it was discovered that the dimension of engineering survey and design (D1) achieved the top score. Consistent with the current studies concerning subway construction safety [59,60], the engineering survey and design dimension (D1) is believed to be the key factor influencing subway construction accidents in China. In addition, four out of the 10 top indicators were located in the engineering survey and design dimension (Figure 2).
Surveying surrounding buildings and municipal pipelines (F3), design scheme constructability review (F5), engineering geological condition analysis, and the disturbance of groundwater (F1) ranked first, third, eighth, and ninth, respectively. Considering that subway constructions through dense urban areas increase the unpredictability of tasks and the relationships of this unpredictability to safety, the above factors represent the crucial tasks in subway construction [2]. The management measures dimension (D2) plays the second most important role in the subway construction safety. Related factors such as safety training (F7) and a reasonable schedule (F11) also obtained higher scores in the final list of factors. Obviously, only with sufficient safety training (F7) can employees work more efficiently and handle unexpected situations more flexibly. While creating a reasonable schedule (F11) is the most important way to guarantee a safe working environment, the stress of meeting the schedule leads to increased safety risks, resulting in increased accidents in subway construction [61]. As the fundamental determinants of human performance, the foreman’s safety attitude (F17) is influenced the safety climate of construction teams [43], which is also a critical factor for decreasing the accidents in subway construction. Moreover, it is worth noting that the factor of ensuring the investment of the safety measures (F23) ranked fourth in the identified 24 factors. It is generally recognized that insufficient safety investment is the immediate cause of accidents [62]. Therefore, safety investment should be strengthened to guarantee safety procedures and a safe operating environment [61].
The ISM model (Figure 4) revealed the contextual relationship of identified CSFs and helped develop a hierarchical model. Figure 4 reveals some valuable insights into the relative importance of CSFs as well as the interdependencies among them. In Figure 4, all of the factors associated with subway construction can be classified into five levels. The majority of engineering survey and design factors, such as the disturbance of groundwater (F1), engineering geological condition analysis (F2), and surveying of surrounding buildings and municipal pipelines (F3), are at the deepest hierarchy of the mode, meaning that these factors contribute significantly latent impacts on other dimension factors. The finding is consistent with the studies from Suraji et al. [63] and Haslam et al. [10]. It was found that essential planning and design work are the essential factors, which could bring out inappropriate site conditions and construction operations. Designers can mitigate safety hazards by designing barriers, selecting alternative techniques, and increasing the resilience of the project [64]. In addition, creating a reasonable schedule (F11), establishing a project safety leading group (F21), and ensuring the investment of the safety measures (F23) are also at the bottom of the ISM structure, indicating that they have a fundamental impact on subway construction safety. Consequently, more attention should be paid to these factors.
Five superficial factors in the upper level have a direct impact on subway construction safety: the supervision of special operations (F10), guaranteeing temporary power use safety (F16), workers’ safety awareness (F19), workers’ potential safety hazard insight (F20), and emergency rescue measures (F24). Once an accident occurs, emergency rescue measures would be undertaken by the experienced project managers according to the accident type and characteristics. Therefore, F24 is isolated from the other factors. These factors will directly affect subway construction safety and cannot influence other factors. Moreover, it is worth noting that workers’ potential safety hazard insight (F20) is influenced by five factors in the middle levels, which means the abilities of the workers to find the potential safety hazards without warning have the most significant impact on reducing accidents in construction [43,65].
The factors in the middle levels ( L 2 , L 3 , and L 4 ) are influenced by the lower levels and indirectly influence the safety management of subway construction, thus playing a role in connecting the levels above and below. In addition, it could be distinctly observed that safety procedure and policy (F6) has the maximum number of relationships, as it is influenced by factors F11, F21, and F21, and directly influences factors F7, F9, and F12, indicating that this factor plays vital roles in effectively reducing the occurrence of accidents in subway construction. It is recommended that the establishment of appropriate safety procedure and policy is essential in protecting workers from workplace hazards [35].
The Resilience-based Early Warning Indicators (REWI) method was applied to provide early warning to avoid major accidents and to improve the organization’s resilience through the selected set of Contributing Success Factors [66]. The REWI indicators are not static, and provide proactive monitoring and successive evaluating of safety critical activities over time. However, the relationships among the various systematic indicators are not considered. By comparison, the proposed approach in this research was not only to identify CSFs of safety management in subway construction, but also to understand the relationships between different CSFs.

6. Conclusions

The promotion of safety management in subway construction is complex, as it involves many uncertainties and a mass of risk factors. Understanding the inherent properties of the CSFs for safety management in subway construction is conducive to retaining a high level of safety performance. This paper provides a comprehensive list of CSFs influencing subway construction safety management in China, based on literature review, in-depth interviews, and questionnaire survey. After calculating and analyzing the questionnaire survey data, it was found that the engineering survey and design phase in subway construction is a vital factor of successful safety management. In addition, surveying surrounding buildings and municipal pipelines, safety training, design scheme constructability review, ensuring the investment of the safety measures, and foreman’s safety attitude were identified as the most important factors for safety management in subway construction; these were the top five factors, indicating that these factors played vital roles in safety management.
Many researchers have tried to identify critical safety factors to effectively prevent construction accidents, while minimal efforts have been made to investigate the relationships and interactions among the CSFs in subway construction. To address this knowledge gap, the interrelations among factors are illustrated by utilizing the proposed ISM method. As the ISM model analysis shows, the engineering survey and design factors, such as surveying surrounding buildings and municipal pipelines, the disturbance of groundwater, and engineering geological condition analysis not only occupy relatively higher scores in the questionnaire survey but are also located at the deepest hierarchy of the interpretative structural model. In addition, the factors of creating a reasonable schedule and ensuring the investment of the safety measures occupy relatively higher scores and are also located at the bottom of the ISM structure. As such, more attention should be paid to these factors. It is also concluded that the factor of workers’ potential safety hazard insight is a critical superficial factor in the upper level, which will directly affect subway construction safety.
In general, this research contributed to the improvement of subway construction safety management in China. This research guided the participants in determining the most important safety factors to be addressed and provided them with valuable insights into the perception of and knowledge about subway construction safety. Although this study obtained very useful findings regarding safety management in subway construction, more factors should be gathered from construction sites to avoid deviations. Moreover, the research has been raised based on the factors, and their interaction regularity is not quantitatively analyzed, which should be clarified by further research. Meanwhile, subway construction involves many activities and these activities involve many processes, and it is encouraged to apply the proposed approach to analyze the particular activities in future research.

Author Contributions

P.L. contributed to the questionnaire design and the research framework. Q.L. was responsible for the ISM model section. J.B. assisted in literature review and data analysis. X.X. and L.S. did all the work of this paper together under the leadership of Q.L.

Funding

This research was funded by National Natural Science Foundation of China, grant number 51578144.

Acknowledgments

The authors’ special thanks go to all experts and survey participants of the paper. This work was supported by the National Natural Science Foundation of China (51578144) and the Postgraduates’ Science and Innovation Foundation of Jiangsu Province (grand No. KYLX_0206).

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Ding, L.; Zhang, L.; Wu, X.; Skibniewski, M.J.; Yu, Q. Safety management in tunnel construction: Case study of Wuhan metro construction in China. Saf. Sci. 2014, 62, 8–15. [Google Scholar] [CrossRef]
  2. Choi, H.H.; Cho, H.N.; Seo, J.W. Risk Assessment Methodology for Underground Construction Projects. J. Constr. Eng. Manag. 2004, 130, 258–272. [Google Scholar] [CrossRef]
  3. Zhou, Z.; Irizarry, J. Integrated Framework of Modified Accident Energy Release Model and Network Theory to Explore the Full Complexity of the Hangzhou Subway Construction Collapse. J. Manag. Eng. 2016, 32, 5016013. [Google Scholar] [CrossRef]
  4. Hollnagel, E. Safety-I and Safety-II: The Past and Future of Safety Management; Ashgate Publishing Company: Farnham, UK, 2014. [Google Scholar]
  5. Hollnagel, E. Prologue: The Scope of Resilience Engineering; Ashgate Publishing, Ltd.: Surrey, UK, 2011. [Google Scholar]
  6. Hollnagel, E. Safety-II in Practice: Developing the Resilience Potentials; Routledge: New York, NY, USA, 2017. [Google Scholar]
  7. Seo, J.W.; Choi, H.H. Risk-Based Safety Impact Assessment Methodology for Underground Construction Projects in Korea. J. Constr. Eng. Manag. 2008, 134, 72–81. [Google Scholar] [CrossRef]
  8. Hong, E.S.; Lee, I.M.; Shin, H.S.; Nam, S.W.; Kong, J.S. Quantitative risk evaluation based on event tree analysis technique: Application to the design of shield TBM. Tunn. Undergr. Space Technol. 2009, 24, 269–277. [Google Scholar] [CrossRef]
  9. Ding, L.Y.; Yu, H.L.; Li, H.; Zhou, C.; Wu, X.G.; Yu, M.H. Safety risk identification system for metro construction on the basis of construction drawings. Autom. Constr. 2012, 27, 120–137. [Google Scholar] [CrossRef]
  10. Haslam, R.A.; Hide, S.A.; Gibb, A.G.; Gyi, D.E.; Pavitt, T.; Atkinson, S.; Duff, A.R. Contributing factors in construction accidents. Appl. Ergon. 2005, 36, 401–415. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  11. Marais, M.; Du Plessis, E.; Saayman, M. A review on critical success factors in tourism. J. Hosp. Tour. Manag. 2017, 31, 1–12. [Google Scholar] [CrossRef]
  12. Zwikael, O.; Globerson, S. From Critical Success Factors to Critical Success Processes. Int. J. Prod. Res. 2006, 44, 3433–3449. [Google Scholar] [CrossRef]
  13. Ling, F.Y.Y.; Sui, P.L.; Wang, S.Q.; Lim, H.H. Key project management practices affecting Singaporean firms’ project performance in China. Int. J. Proj. Manag. 2009, 27, 59–71. [Google Scholar] [CrossRef]
  14. Aksorn, T.; Hadikusumo, B.H.W. Critical success factors influencing safety program performance in Thai construction projects. Saf. Sci. 2008, 46, 709–727. [Google Scholar] [CrossRef]
  15. Ng, S.T.; Cheng, K.P.; Skitmore, R.M. A framework for evaluating the safety performance of construction contractors. Build. Environ. 2005, 40, 1347–1355. [Google Scholar] [Green Version]
  16. Mahmoudi, S.; Ghasemi, F.; Mohammadfam, I.; Soleimani, E. Framework for Continuous Assessment and Improvement of Occupational Health and Safety Issues in Construction Companies. Saf. Health Work 2014, 5, 125–130. [Google Scholar] [CrossRef] [PubMed]
  17. Tam, C.M.; Zeng, S.X.; Deng, Z.M. Identifying elements of poor construction safety management in China. Saf. Sci. 2004, 42, 569–586. [Google Scholar] [CrossRef]
  18. Rosa, L.V.; Haddad, A.N.; Carvalho, P.V. Assessing risk in sustainable construction using the Functional Resonance Analysis Method (FRAM). Cogn. Technol. Work 2015, 17, 1–15. [Google Scholar] [CrossRef]
  19. Patriarca, R.; Bergström, J.; Di, G.; Costantino, F. Resilience Engineering: Current status of the research and future challenges. Saf. Sci. 2018, 102, 79–100. [Google Scholar] [CrossRef]
  20. Sun, Y.; Fang, D.; Wang, S.; Dai, M.; Lv, X. Safety Risk Identification and Assessment for Beijing Olympic Venues Construction. J. Manag. Eng. 2008, 24, 40–47. [Google Scholar] [CrossRef]
  21. Wanberg, J.; Harper, C.; Hallowell, M.R.; Rajendran, S. Relationship between Construction Safety and Quality Performance. J. Constr. Eng. Manag. 2013, 139, 4013003. [Google Scholar] [CrossRef]
  22. Hallowell, M.R.; Hinze, J.W.; Baud, K.C.; Wehle, A. Proactive Construction Safety Control: Measuring, Monitoring, and Responding to Safety Leading Indicators. J. Constr. Eng. Manag. 2013, 139, 4013010. [Google Scholar] [CrossRef]
  23. Hinze, J.; Hallowell, M.; Baud, K. Construction-Safety Best Practices and Relationships to Safety Performance. J. Constr. Eng. Manag. 2013, 139, 4013006. [Google Scholar] [CrossRef]
  24. Fernández-Muñiz, B.; Montes-Peón, J.M.; Vázquez-Ordás, C.J. Safety management system: Development and validation of a multidimensional scale. J. Loss Prev. Process Ind. 2007, 20, 52–68. [Google Scholar] [CrossRef]
  25. Huang, X.; Hinze, J. Owner’s Role in Construction Safety. J. Constr. Eng. Manag. 2006, 132, 174–181. [Google Scholar] [CrossRef]
  26. Yung, P. Institutional arrangements and construction safety in China: An empirical examination. Constr. Manag. Econ. 2009, 27, 439–450. [Google Scholar] [CrossRef]
  27. Rajendran, S.; Gambatese, J.A. Development and Initial Validation of Sustainable Construction Safety and Health Rating System. J. Constr. Eng. Manag. 2009, 135, 1067–1075. [Google Scholar] [CrossRef]
  28. Priyadarshani, G.K.K.; Jayasuriya, S. Construction Safety Assessment Framework for Developing Countries: A Case Study of Sri Lanka. J. Constr. Dev. Ctries. 2013, 18, 33–51. [Google Scholar]
  29. Pousette, A.; Larsson, S.; Törner, M. Safety climate cross-validation, strength and prediction of safety behaviour. Saf. Sci. 2008, 46, 398–404. [Google Scholar] [CrossRef]
  30. Hon, C.K.H.; Chan, A.P.C.; Yam, M.C.H. Relationships between safety climate and safety performance of building repair, maintenance, minor alteration, and addition (RMAA) works. Saf. Sci. 2014, 65, 10–19. [Google Scholar] [CrossRef]
  31. Lyu, S.; Hon, C.K.H. Relationships among Safety Climate, Safety Behavior, and Safety Outcomes for Ethnic Minority Construction Workers. Int. J. Environ. Res. Public Health 2018, 15, 484. [Google Scholar] [CrossRef] [PubMed]
  32. Wu, H.H.; Chen, H.K.; Shieh, J.I. Evaluating Performance Criteria of Employment Service Outreach Program Personnel by DEMATEL Method; Pergamon Press, Inc.: Oxford, UK, 2010. [Google Scholar]
  33. Hinze, J.; Thurman, S.; Wehle, A. Leading indicators of construction safety performance. Saf. Sci. 2013, 51, 23–28. [Google Scholar] [CrossRef]
  34. Ghasemi, F.; Mohammadfam, I.; Soltanian, A.R.; Mahmoudi, S.; Zarei, E. Surprising Incentive: An Instrument for Promoting Safety Performance of Construction Employees. Saf. Health Work 2015, 6, 227–232. [Google Scholar] [CrossRef] [PubMed]
  35. Ismail, Z.; Doostdar, S.; Harun, Z. Factors influencing the implementation of a safety management system for construction sites. Saf. Sci. 2012, 50, 418–423. [Google Scholar] [CrossRef]
  36. Zou, Y.; Kiviniemi, A.; Jones, S.W. A review of risk management through BIM and BIM-related technologies. Saf. Sci. 2016, 97, 88–98. [Google Scholar] [CrossRef]
  37. Driscoll, T.R.; Harrison, J.E.; Bradley, C.; Newson, R.S. The Role of Design Issues in Work-Related Fatal Injury in Australia. J. Saf. Res. 2008, 39, 209–214. [Google Scholar] [CrossRef] [PubMed]
  38. Gambatese, J.A.; Behm, M.; Rajendran, S. Design’s role in construction accident causality and prevention: Perspectives from an expert panel. Saf. Sci. 2008, 46, 675–691. [Google Scholar] [CrossRef]
  39. Behm, M. Linking construction fatalities to the design for construction safety concept. Saf. Sci. 2005, 43, 589–611. [Google Scholar] [CrossRef]
  40. Moon, H.; Dawood, N.; Kang, L. Development of Workspace Conflict Visualization System Using 4D Object of Work Schedule; Elsevier Science Publishers B. V.: Amsterdam, The Netherlands, 2014. [Google Scholar]
  41. Yu, Q.Z.; Ding, L.Y.; Zhou, C.; Luo, H.B. Analysis of factors influencing safety management for metro construction in China. Accid. Anal. Prev. 2014, 68, 131. [Google Scholar] [CrossRef] [PubMed]
  42. Cheng, E.W.L.; Ryan, N.; Kelly, S. Exploring the perceived influence of safety management practices on project performance in the construction industry. Saf. Sci. 2012, 50, 363–369. [Google Scholar] [CrossRef]
  43. Li, Q.; Ji, C.; Yuan, J.; Han, R. Developing dimensions and key indicators for the safety climate within China ’ s construction teams : A questionnaire survey on construction sites in Nanjing. Saf. Sci. 2017, 93, 266–276. [Google Scholar] [CrossRef]
  44. Boyce, C.; Neale, P.; Pathfinder, I. Conducting In-Depth Interviews: A Guide for Designing and Conducting in-Depth Interviews for Evaluation Input; Pathfinder. Int.: Watertown, MA, USA, 2006. [Google Scholar]
  45. Li, S.; Wu, X.; Zhou, Y.; Liu, X. A study on the evaluation of implementation level of lean construction in two Chinese firms. Renew. Sustain. Energy Rev. 2017, 71, 846–851. [Google Scholar] [CrossRef]
  46. Zhao, X.; Singhaputtangkul, N. Effects of Firm Characteristics on Enterprise Risk Management: Case Study of Chinese Construction Firms Operating in Singapore. J. Manag. Eng. 2016, 32, 5016008. [Google Scholar] [CrossRef]
  47. Choudhry, R.M.; Fang, D.; Lingard, H. Measuring Safety Climate of a Construction Company. J. Constr. Eng. Manag. 2009, 135, 890–899. [Google Scholar] [CrossRef]
  48. Warfield, J.N. Toward Interpretation of Complex Structural Models. Syst. Man Cybern. IEEE Trans. 1974, SMC-4, 405–417. [Google Scholar] [CrossRef]
  49. Wang, C.L.; Chao, W.U.; Shu qing, L.I. Layer Analysis of Accident Causes Based on Interpretation Structure Model. Min. Res. Dev. 2004. [Google Scholar]
  50. Tian, Y.Q.; Hua, L.I.; Shang, X.G. Study on Affecting Factors of Risks at Workplace Based on ISM and AHP. China Saf. Sci. J. 2011, 21, 140–146. [Google Scholar]
  51. Song, L.; Li, Q.; List, G.F.; Deng, Y.; Lu, P. Using an AHP-ISM Based Method to Study the Vulnerability Factors of Urban Rail Transit System. Sustainability 2017, 9, 1065. [Google Scholar] [CrossRef]
  52. Thakkar, J.; Deshmukh, S.G.; Gupta, A.D.; Shankar, R. Development of a balanced scorecard: An integrated approach of Interpretive Structural Modeling (ISM) and Analytic Network Process (ANP). Int. J. Product. Perform. Manag. 2007, 56, 25–59. [Google Scholar] [CrossRef]
  53. Agarwal, A.; Shankar, R.; Tiwari, M.K. Modeling agility of supply chain. Ind. Mark. Manag. 2007, 36, 443–457. [Google Scholar] [CrossRef]
  54. Raj, T. Identification and modelling of barriers in the implementation of TQM. Int. J. Product. Qual. Manag. 2011, 8, 153. [Google Scholar] [CrossRef]
  55. Venkatesh, V.G.; Rathi, S.; Patwa, S. Analysis on supply chain risks in Indian apparel retail chains and proposal of risk prioritization model using Interpretive structural modeling. J. Retail. Consum. Serv. 2015, 26, 153–167. [Google Scholar] [CrossRef]
  56. Han, Y.; Geng, Z.; Zhu, Q.; Lin, X. Energy consumption hierarchical analysis based on interpretative structural model for ethylene production. Chin. J. Chem. Eng. 2015, 23, 2029–2036. [Google Scholar] [CrossRef]
  57. Han, Y.; Zhu, Q.; Geng, Z.; Xu, Y. Energy and carbon emissions analysis and prediction of complex petrochemical systems based on an improved extreme learning machine integrated interpretative structural model. Appl. Therm. Eng. 2017, 115, 280–291. [Google Scholar] [CrossRef]
  58. Shen, Y.; Koh, T.Y.; Rowlinson, S.; Bridge, A.J. Empirical Investigation of Factors Contributing to the Psychological Safety Climate on Construction Sites. J. Constr. Eng. Manag. 2015, 141, 4015038. [Google Scholar] [CrossRef] [Green Version]
  59. Xiahou, X.; Yuan, J.; Li, Q.; Skibniewski, M.J. Validating DFS concept in lifecycle subway projects in China based on incident case analysis and network analysis. J. Civ. Eng. Manag. 2018, 24, 53–66. [Google Scholar] [CrossRef] [Green Version]
  60. Hansen, D.C. Measuring and Improving Designer Hazard Recognition Skill. Master’s Thesis, University of Colorado at Boulder, Boulder, CO, USA, 2015. [Google Scholar]
  61. Zhang, G.; Thai, V. V Expert elicitation and Bayesian Network modeling for shipping accidents: A literature review. Saf. Sci. 2016, 87, 53–62. [Google Scholar] [CrossRef]
  62. Ma, Y.; Zhao, Q.; Xi, M. Decision-makings in safety investment: An opportunity cost perspective. Saf. Sci. 2016, 83, 31–39. [Google Scholar] [CrossRef]
  63. Suraji, A.; Duff, A.R.; Peckitt, S.J. Development of Causal Model of Construction Accident Causation. J. Constr. Eng. Manag. 2001, 127, 337–344. [Google Scholar] [CrossRef]
  64. Hollnagel, E. Risk + barriers = safety? Saf. Sci. 2008, 46, 221–229. [Google Scholar] [CrossRef]
  65. Pinto, A. QRAM a Qualitative Occupational Safety Risk Assessment Model for the construction industry that incorporate uncertainties by the use of fuzzy sets. Saf. Sci. 2014, 63, 57–76. [Google Scholar] [CrossRef]
  66. Knut, Ø.; Kviseth, T.R. Guideline for implementing the REWI method. In Resilience Based Early Warning Indicators; SINTEF: Trondheim, Norway, 2012. [Google Scholar]
Figure 1. Flowchart of the methodology.
Figure 1. Flowchart of the methodology.
Ijerph 15 01359 g001
Figure 2. The top ten ranked factors through questionnaire survey analysis.
Figure 2. The top ten ranked factors through questionnaire survey analysis.
Ijerph 15 01359 g002
Figure 3. Relationships among factors.
Figure 3. Relationships among factors.
Ijerph 15 01359 g003
Figure 4. Interpretative structural model.
Figure 4. Interpretative structural model.
Ijerph 15 01359 g004
Table 1. Codes of construction safety management in different countries or regions.
Table 1. Codes of construction safety management in different countries or regions.
Country/RegionCodeAbbreviation
China MainlandStandard for construction safety assessment of metro engineering (GB 50715-2011)GB 50715
Code for risk management of underground works in urban rail transit (GB50652-2011)GB 50652
Code for Construction company safety manage criterion (GB50656-2011)GB 50656
Standard for construction safety inspection (JGJ59-2011)JGJ59
Hong KongFactories and Industrial Undertakings Ordinance (FIUO-Cap.59)FIUO
Occupational Safety and Health Ordinance (OSHO-Cap.509)OSHO
JapanConstruction Occupational Health and Safety Management System (COHSMS)COHSMS
Guidelines & COHSMS External System Evaluation
SingaporeThe Factories (Building Operations and Work of Engineering Construction) RegulationsBOWES
Code of practice for safety management system for construction worksites (Singapore standard CP79:1999)CP79
Table 2. The preliminary list of factors.
Table 2. The preliminary list of factors.
DimensionsFactorsDescriptionSource
Engineering survey and design (D1)The disturbance of groundwater (F1)Analyzes the disturbance of the groundwater table by subway constructionGB 50715, GB 50652
Engineering geological condition analysis (F2)Analyzes the main impact of soil physical properties, mechanical properties, and soil distribution during the construction processGB 50715, GB 50652
Survey surrounding buildings and municipal pipelines (F3)Detects the impact of surrounding buildings and complex municipal pipelines on subway construction.GB 50715, GB 50652
Construction drawing examination (F4)Construction drawing in the early stages serves as the foundation for an effective construction programGB 50652, GB 50656
Design scheme constructability review (F5)Checks the rationality and security of the design scheme against the constructability of the subway constructionMoon et al. (2014) [40],
Construction safety management measures (D2)Safety procedure and policy (F6)Determines whether there are proper safety procedures and policies for guiding team workers’ safety behaviorFIUO, CP79, BOWES
Safety training (F7)A vital factor of a successful safety program is to periodically train and educate all employees to enhance their skills and knowledge about safety at workJGJ59, FIUO, BOWES, CP79
Safety technical disclosure (F8)Disclose all information about the drawings, designs, and safety to the constructors before the constructionGB 50652, JGJ59, FIUO
Safety checks on construction site (F9)Safety risk identification and analysis on construction site during subway constructionGB50652, JGJ59, FIUO, BOWES, CP79
Supervision of special operation (F10)Special operators must be provided with necessary occupational training and related certificatesGB 50715, JGJ59
Creating a reasonable schedule (F11)Avoid the occurrence of accidents caused by rushing to meet the construction scheduleYu et al. (2014) [41]
Holding regular safety consultations and meetings (F12)Participation in regular safety consultations and meetings to discuss work safetyCheng et al. (2012) [42]
Construction sites security measures (D3)Personal protective equipment (F13)Determines whether there is enough proper and available equipment to protect team workers from injury when at workGB 50656, CP79
Machinery’s safety state (F14)Assesses the conditions of construction machines and toolsGB 50715, JGJ59
Workplace’s safety situation (F15)Addresses the situation of potential safety hazards, safety accidents, or injuries in the workplaceJGJ59, CP79
Guaranteeing temporary power use safety (F16)Determines whether there are proper safety procedures to guarantee temporary power use safetyGB 50715, JGJ59, CP79
Workers’ safety behavior (D4)Foreman’s safety attitude (F17)Addresses the foreman’s attitudes toward safety problems and attitudes to promote the workers’ safety skill and knowledge within the construction teamsLi et al. (2017) [43]
Foreman’s competence (F18)Addresses the foreman’s experience and competence in dealing with safety problems within his construction teamLi et al. (2017) [43]
Workers’ safety awareness (F19)Addresses attitudes to hazards, risks, and the possibility of personal injury in the workplace.Yu et al. (2014) [41]
Workers’ potential safety hazard insight (F20)Assesses capabilities to find or identify the potential safety hazard without warningAksorn et al. (2008) [14]
Guarantee and supervision mechanism (D5)Establishing project safety leading group (F21)Defines the organizational structure and labor division of safety supervision in subway constructionGB 50715, GB 50656, FIUO
Safety promotional activities (F22)Includes safety promotion activities through many mediums such as campaigns, publications, competitions, and contestsYu et al. (2014) [41]
Ensuring the investment of the safety measures (F23)Determines whether the contractor’s safety measures fee is used for subway constructionYu et al. (2014) [41]
Emergency rescue measures (F24)The emergency response plan involves making a plan to follow in the case of a critical situation or severe accidentGB 50656, JGJ59, FIUO, COHSMS, CP79
Table 3. Profile of the data collected from the questionnaires.
Table 3. Profile of the data collected from the questionnaires.
Respondents’ CharacteristicsDescriptionN%
Project employers (N = 46)Senior manager2758.7
Project manager1941.3
Contractors (N = 61)Senior manager2337.7
Project manager2845.9
Safety engineer1016.4
Designers (N = 17)Geotechnical engineer423.5
Designer1376.5
Supervisors (N = 24)Chief supervision engineer1354.2
Safety supervision engineer1145.8
Government regulators (N = 13)Leader1184.6
Staff215.4
Years of experience (N = 161)<52314.3
5–93622.4
10–157445.9
>152817.4
Regions (N = 161)Nanjing6037.2
Shanghai4528.0
Beijing2213.7
Others3421.1
Table 4. Scores and ranking of the factors.
Table 4. Scores and ranking of the factors.
DimensionFactorMeanStandard DeviationRankGroup MeanGroup RankVerification
Engineering survey and design (D1)F14.310.6294.271Pass
F24.370.878Pass
F34.670.961Pass
F43.390.7620Pass
F54.590.813Pass
Construction safety Management Measures (D2)F63.900.78144.122Pass
F74.620.502Pass
F84.171.0511Pass
F94.430.867Pass
F103.591.1317Pass
F114.490.836Pass
F123.640.7116Pass
Construction sites security measures (D3)F134.071.21123.754Pass
F143.480.6618Pass
F154.240.7410Pass
F163.210.6123Pass
Workers’ safety behavior (D4)F174.530.7053.973Pass
F184.010.8513Pass
F193.880.6315Pass
F203.470.9819Pass
Guarantee and Supervision Mechanism (D5)F213.271.22223.575Pass
F223.160.9824Pass
F234.540.824Pass
F243.321.1521Pass
Table 5. Reachability matrix.
Table 5. Reachability matrix.
FactorF1F2F3F4F5F6F7F8F9F10F11F12F13F14F15F16F17F18F19F20F21F22F23F24
F110011001*00001*0000001*0000
F201011001*00001*0000001*0000
F300101001*00001*0000001*0000
F40001000100001*0000001*0000
F50000100100001*0000001*0000
F60000011011*011*1*1*1*1*1*1*1*1*000
F7000000100100101*11*1*1*1*0000
F800000001000010000001*0000
F9000000001000011011*1*1*0000
F10000000000100000000000000
F110000011*01*1*11*1*1*1*1*1*1*1*1*0000
F12000000000001001*011*1*1*0000
F13000000000000100000010000
F14000000000000010000010000
F15000000000000001011*1*10000
F16000000000000000100000000
F17000000000000001*01111*0000
F1800000000000000101*11*10000
F19000000000000000000100000
F20000000000000000000010000
F210000011*01*1*01*1*1*1*1*1*1*1*1*1100
F22000000000000001*011*1*1*0100
F230000011*01*1*01*1*1*1*1*1*1*1*1*0010
F24000000000000000000000001
Table 6. Level partition of reachability matrix.
Table 6. Level partition of reachability matrix.
FactorReachability SetAntecedent SetIntersection Set
L 1 = { F 10 , F 16 , F 19 , F 20 , F 24 }
F11, 4, 5, 8, 13, 2011
F22, 4, 5, 8, 13, 2022
F33, 5, 8, 13, 2033
F44, 8, 13, 201, 2, 44
F55, 8, 13, 201, 2, 3, 55
F66, 7, 9, 12, 13, 14, 15, 16, 17, 18, 19, 20, 216, 11, 21, 236, 21
F77, 10, 13, 15, 16, 17, 18, 19, 20, 6, 7, 11, 21, 237
F88, 13, 201, 2, 3, 4, 5, 88
F99, 14, 15, 17, 18, 19, 206, 9, 11, 21, 239
F10106, 7, 10, 11, 16, 21, 2310
F116, 7, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 201111
F1212, 15, 17, 18, 19, 206, 11, 12, 21, 2312
F1313, 201, 2, 3, 4, 5, 6, 7, 8, 11, 13, 21, 2313
F1414, 206, 9, 11, 14, 21, 2314
F1515, 17, 18, 19 206, 7, 9, 11, 12, 15, 17, 18, 21, 22, 2315, 17, 18
F16166, 7, 11, 16, 21, 2316
F1715, 17, 18, 19, 206, 7, 9, 11, 12, 15, 17, 18, 21, 22, 2315, 17, 18
F1815, 17, 18, 19, 206, 7, 9, 11, 12, 15, 17, 18, 21, 22, 2315, 17, 18
F19196, 7, 9, 11, 12, 15, 17, 18, 19, 21, 22, 2319
F20201, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15, 17, 18, 20, 21, 22, 2320
F216, 7, 9, 12, 13, 14, 15, 16, 17, 18, 19, 20, 232121
F2215, 17, 18, 19, 20, 2221, 2222
F236, 7, 9, 12, 13, 14, 15, 16, 17, 18, 19, 20, 232323
F24242424
L 2 = { F 13 , F 14 , F 15 , F 17 , F 18 }
F11, 4, 811
F22, 4, 5, 822
F33, 5, 833
F44, 81, 2, 44
F55, 81, 2, 3, 55
F66, 7, 9, 12, 13, 14, 15, 17, 18, 216, 11, 21, 236, 21
F77, 13, 15, 17, 186, 7, 11, 21, 237
F88, 131, 2, 3, 4, 5, 88
F99, 14, 15, 17, 186, 9, 11, 21, 239
F116, 7, 9, 11, 12, 13, 14, 15, 17, 181111
F1212, 15, 17, 186, 11, 12, 21, 2312
F13131, 2, 3, 4, 5, 6, 7, 8, 11, 13, 21, 2313
F14146, 9, 11, 14, 21, 2314
F1515, 176, 7, 9, 11, 12, 15, 17, 18, 21, 22, 2315, 17
F1717, 186, 7, 9, 11, 12, 15, 17, 18, 21, 22, 2317, 18
F1815, 186, 7, 9, 11, 12, 15, 17, 18, 21, 22, 2315, 18
F216, 7, 9, 12, 13, 14, 15, 17, 18, 232121
F2215, 17, 18, 2221, 2222
F236, 7, 9, 12, 13, 14, 15, 17, 18, 232323
L 3 = { F 7 , F 8 , F 9 , F 12 , F 22 }
F11, 4, 811
F22, 4, 5, 8 22
F33, 5, 833
F44, 81, 2, 44
F55, 81, 2, 3, 55
F66, 7, 9, 12, 216, 11, 21, 236, 21
F776, 7, 11, 21, 237
F881, 2, 3, 4, 5, 88
F996, 9, 11, 21, 239
F116, 7, 9, 11, 121111
F12126, 11, 12, 21, 2312
F216, 7, 9, 12, 232121
F222221, 2222
F236, 7, 9, 12, 232323
L 4 = { F 4 , F 5 , F 6 }
F11, 411
F22, 4, 522
F33, 533
F441, 2, 44
F551, 2, 3, 55
F66, 216, 11, 21, 236, 21
F116, 111111
F216, 212121
F236, 232323
L 5 = { F 1 , F 2 , F 3 , F 11 , F 21 , F 23 }
F1111
F2222
F3333
F11111111
F21212121
F23232323

Share and Cite

MDPI and ACS Style

Liu, P.; Li, Q.; Bian, J.; Song, L.; Xiahou, X. Using Interpretative Structural Modeling to Identify Critical Success Factors for Safety Management in Subway Construction: A China Study. Int. J. Environ. Res. Public Health 2018, 15, 1359. https://doi.org/10.3390/ijerph15071359

AMA Style

Liu P, Li Q, Bian J, Song L, Xiahou X. Using Interpretative Structural Modeling to Identify Critical Success Factors for Safety Management in Subway Construction: A China Study. International Journal of Environmental Research and Public Health. 2018; 15(7):1359. https://doi.org/10.3390/ijerph15071359

Chicago/Turabian Style

Liu, Ping, Qiming Li, Jing Bian, Liangliang Song, and Xiaer Xiahou. 2018. "Using Interpretative Structural Modeling to Identify Critical Success Factors for Safety Management in Subway Construction: A China Study" International Journal of Environmental Research and Public Health 15, no. 7: 1359. https://doi.org/10.3390/ijerph15071359

APA Style

Liu, P., Li, Q., Bian, J., Song, L., & Xiahou, X. (2018). Using Interpretative Structural Modeling to Identify Critical Success Factors for Safety Management in Subway Construction: A China Study. International Journal of Environmental Research and Public Health, 15(7), 1359. https://doi.org/10.3390/ijerph15071359

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop