Identifying,evaluating and prioritizing the causes of occupational accidents in the construction industry using fuzzy AHP and fuzzy TOPSIS

Abstract

BACKGROUND:

The construction industry is one of the most dangerous industries in terms of occupational accidents. Understanding the various factors that affect work-related injuries and deaths in the industry can help develop prevention strategies, improve safety performance and reduce accidents.

OBJECTIVES:

This applied qualitative study was carried out in several steps to investigate, evaluate and prioritize the causes of occupational accidents in the construction industry.

METHODS:

In order to extract the most important criteria in construction accidents, the opinions of safety experts and the qualitative Delphi method were used. The Fuzzy Analytic Hierarchy Process (FAHP) was used to determine the weights of selected criteria and finally, the Fuzzy TOPSIS technique was used to rank the causes of occupational accidents in the construction industry.

RESULTS:

According to the results, governance, occupational, organizational, individual, and environmental factors were the most determinative options for the cause of construction accidents. Prioritizing the causes of occupational accidents in the construction industry using Fuzzy AHP and Fuzzy TOPSIS showed that governance and environmental factors were the most effective and least effective factors in construction accidents, respectively.

CONCLUSIONS:

According to the criteria, and based on fuzzy TOPSIS technique, governance factors were determined to be the primary option for occupational accidents in the construction industry. The results of this study indicate that in addition to organizational factors, individual factors, and environmental factors, the government must also play a role in legislation, law enforcement, implementation, and organization of safety training programs.

Keywords

Construction safety accidents AHP-TOPSIS work construction

1 Introduction

In terms of occupational accidents, the characteristics of the construction industry make it one of the most dangerous industries. The rate of occupational injuries and workers’ accident in construction locations is the highest compared to all other workplaces [1]. Therefore, workers in the construction industry are exposed to more risks and injuries compared to other industries, due to the dynamic and innovative nature of activities, and large changes in working conditions [2]. These accidents in addition to the economic and social damage to individuals and industry, also lead to the imposition of various costs on society [3]. Despite many efforts to reduce accidents and injuries caused by these accidents, this industry still has a large share of injuries and workplace accidents in Iran [4]. Studies have also shown that in other countries, this industry is one of the most dangerous and high-risk industries, it also provides a wide source of information to prevent similar accidents in the future [5, 6]. Therefore, there is a need to develop an appropriate strategy to reduce accident rates in these projects. This information can be used in the development of safety promotion programs in the construction industry and reduce the rate of accidents, injury damage. There are many factors involved in construction accidents [7]. Research also shows that the cause of most occupational accidents is a combination of unsafe behavior and conditions and multiple causes [8]. The prevention and management of accidents can be accomplished by understanding these factors. Therefore, understanding the various factors affecting work-related injuries and deaths in the construction industry is helpful in planning prevention strategies and priorities, and also helps to improve safety performance and reduce accidents. This knowledge can be used to develop better working conditions and environments in the construction industry [9].

Given that the construction industry has a higher rate of accidents than other industries, understanding the causes of occupational accidents in this industry is an important step to preparedness, management, and prevention of accidents. Due to a large number of efficient factors in construction accidents, the criteria for selecting these factors must be defined using Delphi method. In the next step, the importance of each of these criteria should be considered. In other words, the criteria should be weighed using paired comparison of criteria, to determine the most important criteria. In the next step, based on the specified criteria and available options (effective factors in construction accidents), the most important criteria in controlling and preventing occupational accidents in the construction industry can be identified. Therefore, this study aimed to identify, evaluate and prioritize the causes of occupational accidents in the construction industry using a combination of Delphi, AHP, and FTOPSIS methods.

2 Method

The design and implementation of this qualitative and practical study were carried out in several steps. Due to the fact that the causes of occupational accidents in the construction industry are not well defined and prioritized, the Delphi technique was used in this study. The steps of this study are outlined below.

Identify the evaluation criteria

In this step, effective criteria were selected using Delphi method. Delphi is one of the methods of extracting or screening decision criteria, which is used to identify and screen criteria in this study. The Delphi method was proposed by Dalkey and Helmer about 50 years ago [10]. Delphi is an effective and highly flexible technique for reaching consensus or predicting future events. When there is no comprehensive knowledge about a specific problem, it is useful to use Delphi as a research method. The goal of the Delphi method is to use questionnaires and a group of experts to reach the most reliable agreement on a specific topic based on their feedback [11]. According to the Delphi study, if the participants are homogeneous, 15-10 samples are sufficient for Delphi [10]. In order to maintain the validity of the research when the number of interviewees decreased during the research process, 30 experts were selected as the Delphi method.

The steps of the Delphi method were: (1) Identify the criteria using review the studies, (2) Identify the panel members.

Due to the lack of appropriate criteria to assess the causes of occupational accidents, with review of the literature [12], a list of criteria were collected.

Identify the panel members

The Delphi technique was start with select the member of the panel of experts. This panel member was any individual with relevant knowledge and experience. The Delphi method in this study was based on an expert team composed of 12 faculty member with relevant experience, 7 HSE managers, and 11 safety officers.

Sending the questionnaire to the expert, repeat the questionnaire and control the feedback on the results obtained from the previous rounds

The Delphi method is an iterative process for receiving feedback and using a series of questionnaires to collect expert judgments. The method is based on a series of continuous questionnaires with controlled feedback [13]. Each subsequent questionnaire is based on the results of the previous step. The process stops when the research question is answered. In this study to collect opinions of the specialists about the causes of occupational accidents in the construction industry, an open-ended question was designed to identify and determining the main criteria in occupational accidents in the construction industry and asked the experts to list at least six important criteria. The answers were reviewed and consulted, and grouped with findings of literature and sources. In this step, irrelevant answers were eliminated and the final criteria were determined.

Determining the relative weights of each criterion using the fuzzy AHP

In this step, a pairwise comparison matrix was used to determine the relative importance of the factors determined by the Delphi method. The AHP method is one of the well-known multi-criteria decision making methods. It was developed by Saaty in the 1970s. The classical type of this method takes into account the definitive judgments of decision makers and includes the opinions of experts, but does not reflect people’s vague thoughts [14].

The fuzzy set theory makes the comparison process more flexible and also explain experts ’preferences [14]. Several methods have been proposed to apply the fuzzy hierarchical analysis process. In this study, Chang’s proposed method was used to apply AHP as a triangular fuzzy data [15]. For this purpose, the pairwise comparison questionnaire was used. The advantage of this method is the subjective and objective factors in the evaluation process [16, 17].

The fuzzy AHP is described in the steps below.

Adjusting the pairwise comparison questionnaire based on the determined criteria in the Delphi method

In this questionnaire, the panel of experts was asked to compare the criteria using fuzzy triangular numbers in Table 1 and based on Saaty’s scale for pairwise comparison in AHP [15].

Table 1
Saaty’s 9-point scale for pairwise comparison in AHP

Linguistic Fuzzy number Scale of fuzzy number

Equal importance 1 (1,1,1)

Weak advantage 2 (1,2,3)

Not bad 3 (2,3,4)

Preferable 4 (3,4,5)

Good 5 (4,5,6)

Fairly good 6 (5,6,7)

Very good 7 (6,7,8)

Absolute 8 (7,8,9)

Perfect 9 (8,9,10)

Linguistic	Fuzzy number	Scale of fuzzy number
Equal importance	1	(1,1,1)
Weak advantage	2	(1,2,3)
Not bad	3	(2,3,4)
Preferable	4	(3,4,5)
Good	5	(4,5,6)
Fairly good	6	(5,6,7)
Very good	7	(6,7,8)
Absolute	8	(7,8,9)
Perfect	9	(8,9,10)

Calculating the weight of first-class indicators

Determining the relative importance using the fuzzy hierarchical analysis process

Triangular fuzzy numbers were used to judge the importance of each criterion by pairwise comparison based on a standardized comparison scale with nine levels (1 means equally important, and 9 means extremely important). Pairwise comparisons based on n criteria can be summarized in (n × n) evaluation matrices A. Each element aij of matrix A (ij = 1, 2, …, n) is the quotient of weights of the criteria, which are as follows: $\overset{⌣}{A} = {{\tilde{a}}_{ij}} = [\begin{matrix} {\tilde{a}}_{11} & \dots & {\tilde{a}}_{1 n} \\ ⋮ & ⋱ & ⋮ \\ {\tilde{a}}_{1 n} & \dots & {\tilde{a}}_{mn} \end{matrix}]$

Consistency test

The testing process could be divided into three steps:

Since there are many determinants of the comparison matrix, a consistency test between the paired comparison matrices is required. The testing process can be divided into three steps:

Calculate the consistency index, Consistency index is usually defined: $CI = \frac{λ_{max} - n}{n - 1}$

Compare the CI with the average random consistency index RI (Table 2)

Calculate the consistency ratio CR $(CR = \frac{CI}{RI})$ . If CR < 0.10, the matrix was considered satisfactory consistency, or the value of the elements in judgment matrix needs to be modified

Table 2

Random consistency index

n	1	2	3	4	5	6	7	8	9	10
RI	0	0	0.58	0.90	1.12	1.24	1.32	1.41	1.45	1.49

In the next step, the Delphi method and expert opinions were used to determine the comparison criteria. For this purpose, an open ended questionnaire was sent to a panel of experts. Common criteria were extracted, scored, and grouped, and similar comments were placed in homogeneous subgroups.

Fuzzy TOPSIS method was presented by Chen in 2000, as one of the multi-criteria decision making methods. This method is based on the best choice, that is, the distance from the positive ideal solution is the smallest, and the distance from the negative ideal solution is the largest.

Steps of fuzzy TOPSIS method

Form a decision matrix

The decision matrix is composed of criteria (obtained using the Delphi method) and options. In this method, each matrix unit evaluates options according to criteria. After the decision matrix was formed, experts were asked to respond according to the Likert scale.

Compute the normalized fuzzy decision matrix.

The normalized fuzzy decision matrix is $\tilde{R} = {[{\tilde{r}}_{ij}]}_{mn}$ , where

${\tilde{r}}_{ij} = (\frac{a_{ij}}{c_{j}^{*}}, \frac{b_{ij}}{c_{j}^{*}}, \frac{c_{ij}}{c_{j}^{*}}) and c_{j}^{*} = \max_{i} {c_{ij}} (benefit criteria)$ ${\tilde{r}}_{ij} = (\frac{a_{j}^{-}}{c_{ij}}, \frac{a_{j}^{-}}{b_{ij}}, \frac{a_{j}^{-}}{a_{ij}}) and c_{j}^{-} = \min_{i} {a_{ij}} (cost criteria)$

Calculate the weighted normalized fuzzy decision matrix.

Compute Fuzzy positive and negative ideal solutions (FPIS and FNIS) are calculated as follows:

$A^{*} = ({\tilde{υ}}_{1}^{*}, {\tilde{υ}}_{2}^{*}, \dots, {\tilde{υ}}_{n}^{*}) where {\tilde{υ}}_{j}^{*} = \max_{i} {υ_{ij 3}};$ $A^{-} = ({\tilde{υ}}_{1}^{-}, {\tilde{υ}}_{2}^{-}, \dots, {\tilde{υ}}_{n}^{-}) where {\tilde{υ}}_{j}^{-} = {min}_{i} {υ_{ij 1}} .$

Compute the distance of each option with the ideal solution according to the following equation: $d_{i}^{+} = \sum_{j = 1}^{n} d ({\tilde{p}}_{ij}, {\tilde{p}}_{j}^{+}), with i = 1, \dots, m .$ $d_{i}^{-} = \sum_{j = 1}^{n} d ({\tilde{p}}_{ij}, {\tilde{p}}_{j}^{-}), with i = 1, \dots, m .$

$d_{i}^{+}$ and d^- are the distance of alternative from positive and negative ideals.

Calculate the proximity coefficient using the following equation ${CC}_{i} = \frac{d_{i}^{-}}{d_{i}^{+} + d_{i}^{*}}$

Excel were used for data processing. Then, using MATLAB software, the mean and coefficients of each matrix of pairwise comparisons were calculated.

3 Results

The first step was to use literature and data review and then use the Delphi method to extract a list of common causes of occupational accidents in the construction industry. The extracted primary options are shown in Table 3. In another study session, given that some options were conceptually the same, similar options were placed in the same subgroups. Finally, the number of effective options was reduced to 5, as shown in Table 4. The options selected at this step were re-sent to the experts for pairwise comparison. Finally, the fuzzy analytic hierarchy process was used to analyze the weight of each option.

Table 3
Causes of occupational accidents in the construction industry

•Age •Poor management and employee commitment •Improper recording •Absence, deficiency or weakness in rules and regulations •Variety of risks

•Level of education •Inadequate physical conditions (heat and cold stress, inadequate lighting, excessive noise, etc.) •Temporary job

•Number of dependents •Educational weaknesses •Variety of tasks

•work experience •Inadequate investment in safety •Weak supervision •Highrisk environment

•Accident history •shortages, lack of or too expensive safety equipment

•Risk perception •Simultaneous activities

Table 4

Effective options in occupational accidents in the construction industry

Extracted options	Number	Percentage
Governance factors	20	100
Organizational factors	19	95
Occupational factors	18	90
Individual factors	14	70
Environmental factors	12	60

The inconsistency rate in this study was 0.067, which is below the acceptable level. The criteria obtained using the Delphi method, in order to prioritize the effective factors in accidents, are shown in Table 5. According to Table 5, cost has the highest relative weight, equal to 0.249.

Table 5

Effective criteria in prioritizing cause of accidents using Delphi method

Criteria	Priority	Relative weight
Durability of the effect	4	0.186
Effective and fast impact	5	0.158
Executability	2	0.209
Cost	1	0.249
Comprehensiveness	3	0.198

The fuzzy TOPSIS method was used to prioritize the cause of accidents in construction industry. The results of proximity coefficient, distance from positive and negative ideals and promising the effective factors in occupational accidents using fuzzy TOPSIS method are shown in the Table 6. Prioritizing the causes of occupational accidents in the construction industry using fuzzy AHP and fuzzy TOPSIS showed that governance and environmental factors were the most effective and least effective factors in construction accidents, respectively.

Table 6

Relative weight, coefficients of evaluation matrices and weight vectorof the options

Options weight	Relative	Separation from positive ideal	Separation from negative ideal
Governance factors	0.278	0.239	0.65
Organizational factors	0239	0.334	0.556
Occupational factors	0.209	0.375	0.517
Individual factors	0.157	0.376	0.516
Environmental factors	0.117	0.414	0.479

4 Discussion

Accidents are inevitable in various occupations, and lead to financial losses and irreparable losses in all aspects. Studies have shown that most accidents are caused by a combination of multiple reasons, as well as one or more unsafe behaviors and unsafe conditions. In order to improve safety performance and reduce accidents, the main causes of accidents must be investigated. This knowledge can be used to develop better working conditions and environments in the construction industry [18]. So far, several studies conducted about the causes of occupational accidents in the construction industry, which can be referred to: Individual factors [12 , 19–24], safety policies [25], management factors [22 , 26–29], organizational conditions [24, 28], unsafe working conditions [26], inadequate supervision [20], organizational factors [12 , 23], governance factors such as legislation [24 , 30–33].

Analyze the causes of accidents shows that several factors may be involved in an accident, which may be very different. These factors are likely to significantly increase the risk of accidents, and thus lead to work related accidents. Some of these factors, such as individual, occupational, and organizational factors, are less well known and more complex. In this case, conventional methods of identifying the problems are not useful, and it is necessary to use other methods used to identify and control. Analyzing the causes of accidents also helps to determine the cause-and-effect relationships that lead to accidents. Therefore, this study was conducted to identify, evaluate and prioritize the causes of occupational accidents in the construction industry.

The research results show that, based on the Delphi method and expert opinions, the most important factor in occupational accidents was governance factor. Governance factors include weak rules and regulations, lack of or too expensive safety equipment, on which 100% of experts agreed. Various studies have shown that the lack of safety regulations in the construction industry also has a negative impact on enforcement. Consequently, it leads to more vulnerability of workers in this industry. Inadequate policy-making also leads to inefficient safety standards and poor environmental conditions [32]. Generally, rules and regulations play an important role in reducing work-related accidents and injuries. Therefore, most accidents stem from the rules and regulations, unsafe behaviors of workers, sense of insecurity at work, unsafe equipment conditions and environmental factors. Appropriate regulations and proper monitoring play an important role in reducing work-related accidents and injuries.

Research by Tam et al. show that in order to reduce occupational accidents and injuries in the construction industry, the government should play a more critical role in regulations and safety training programs [33]. Mohamed’s study also showed that weak regulations as well as non-enforcement of regulations in the construction industry are an important problem in this industry [32]. The study by Garrett et al. Also noted that federal or local programs play an important role in the success of safety programs in the construction industry [34]. Research by Adeyemo and Smallwood also shows that by enforcing authorities to develop and implement appropriate regulations, accidents and injuries on construction sites can be reduced [30].

Organizational factors was the next criterion with 95% of expert’s agreement. Organizational factors include poor management and employer commitment, weak training, and insufficient investment in safety. Various studies have also shown that organizational factors are one of the main factors in construction accidents. The studies also shows that organizational factors account for 53% of occupational accidents [35]. Organizational factors play an important role in preventing occupational accidents. Pay attention to occupational safety and health, take preventative measures, adequate training of employees, as well as provide adequate supervision are the duty of organizations [36]. The study by Mohammadfam et al. showed that personal, professional, and organizational factors can be used as positive indicators for predicting and evaluating employee safety performance [37].

90% of experts agree with the occupational factors in the construction industry. Multiple studies have shown that the nature of the industry leads to fatal accidents, occupational injuries and losses [38]. Construction environments are characterized and described by many job factors such as constant changes in the work environment, high work rotation, unsuitable working conditions, exposure to different climatic conditions, a high number of unskilled workers, temporary workers, intermittent and seasonal work [31, 39]. characteristics have led to many accidents in the industry, such as falls, slips, exposure to various chemicals, electric shocks, collisions, manual handling, etc. [40, 41]. HU and his colleagues believe that the behavior of workers is the most important factor affecting the risk of falling from heights in the construction industry. They also believe that other influencing factors are the safety behavior of managers and contractors, the use of personal protective equipment, the physical condition of workers, and the working environment [42].

Individual factors received 70% of the experts’ agreement. In order to achieve higher safety in the organization, management and employees must perform their tasks in parallel. Liu also showed that individual factors such as high-risk behaviors of workers are the most important cause of occupational injuries in the construction industry [43]. The study by Vosoughi et al. also showed that personal and organizational factors are the most important cause of injury caused by the fall in Iranian construction industry [23]. Mohammadfam et al. also believed that personal and organizational factors are the most important causes of construction accidents [12]. The study by Cheng et al. also showed that the factors affecting occupational accidents in small construction companies included safety and health management skills, employer and managers’ attitudes toward safety measures and compliance with occupational safety rules and regulations in Taiwan [24].

Research has shown that the most important measure to prevent accidents and damage is to determine the factors that lead to accidents and damage. The research examined various parameters and explained the causes of various accidents. However, the causes of occupational accidents in the construction industry have not been fully studied. Understanding the various factors affecting work-related injuries and deaths in the construction industry and using the proposed model in this study for this purpose is helpful in setting prevention strategies and priorities.

5 Conclusion

Findings from the present study based on Delphi technique, on the importance of criteria such as cost, durability of the effect, executability, effective and fast impact, and comprehensiveness. According to these criteria, and based on fuzzy TOPSIS technique, governance factors were determined to be the primary option for occupational accidents in the construction industry. The results of this study show that in addition to organizational factors, personal factors, and environmental factors, the government must also play a role in legislation, law enforcement, implementation, and organize safety training programs. Lack of supervision will also have a negative impact on the implementation of the law and increase the vulnerability of workers in the industry.

Conflict of interest

None to report.

Footnotes

Acknowledgments

This study was supported by the Hamadan University of Medical Sciences, Iran (grant no. 9804042567).

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•Age	•Poor management and employee commitment	•Improper recording	•Absence, deficiency or weakness in rules and regulations	•Variety of risks
•Level of education		•Inadequate physical conditions (heat and cold stress, inadequate lighting, excessive noise, etc.)		•Temporary job
•Number of dependents	•Educational weaknesses			•Variety of tasks
•work experience	•Inadequate investment in safety		•Weak supervision	•Highrisk environment
•Accident history			•shortages, lack of or too expensive safety equipment
•Risk perception		•Simultaneous activities