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Erschienen in: Innovative Infrastructure Solutions 9/2023

Open Access 01.09.2023 | Technical Paper

Safety performance evaluation of construction projects in Egypt

verfasst von: Zeinab Abdalfatah, Emad Elbeltagi, Mohammed Abdelshakor

Erschienen in: Innovative Infrastructure Solutions | Ausgabe 9/2023

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Abstract

In Egypt, the construction industry employs about 20% of the total work force in the local market. The health and safety (H&S) performance evaluation is adopted mainly to control H&S risks in construction sites. As such, there is a need to measure the safety performance in construction sites in a way that is proactive rather than just relying on interactive procedures. The main goal of this study is to develop an indicator to evaluate safety performance on construction sites. This is achieved through two basic steps. First, factors that affect safety performance in construction projects are determined by reviewing literature and conducting personal interviews. A total of 47 factors were collected. Then, a questionnaire was conducted to determine the most important factors that affect the H&S of construction projects in Egypt. The incentives and safety training were among the most important factors. Second, an index to evaluate safety performance has been developed. The purpose of this evaluation is to create a determinate through which construction sites safety could be assessed. The proposed model will be a useful tool to assist project managers and safety inspectors to assess safety performance in construction sites and thus help build safety regulations.

Introduction

There is a critical need to increase worker safety on construction sites because the construction sector is one of the most vulnerable sectors in the world due to its dynamic, complex, and decentralized nature [27]. Researchers have been working harder for years to make it safer for people to conduct various jobs. These efforts have different forms include creating and enforcing a series of safety laws regulating different industries and the design and manufacture of safety equipment and protection systems. Research shows that the main causes of accidents affecting construction safety are related to the unique nature of this industry, human behavior, difficult work site conditions, and poor safety management, resulting in unsafe working methods, equipment, and procedures [1].
Construction projects are influenced by their size, duration, environment, uncertainty, complexity, deadlines, financial intensity, organizational structures, and other factors [17, 25, 35]. The dynamic, transient, and dispersed nature of construction sites necessitates frequent inspections [27]. However, in a market-driven culture, completing projects with the needed quality in the shortest possible time and at the lowest possible cost is more important than safety [36]. Despite significant progress in recent decades, prevention tactics have failed to ensure safety performance, many workers continue to be injured, and safety precautions are not taken seriously [12, 22]. Mouleeswaran [34] found occupational safety in the construction industry in developing countries is very poor, due to lack of safety regulations and standards, data related to construction site safety, safety training, safety promotion, and documented safety regulations. The nature of the construction industry, site circumstances, human behavior, and site mismanagement are among the most prominent issues in the Egyptian construction industry that lead to unsafe work environment, according to El-Safty et al. [12]. Smith et al. [45] stated that performance indicators for construction sites are needed to evaluate the overall safety performance.
So, there is a need to measure and assess safety performance. Mostly, safety elements are of general nature and cannot be measured easily, such as safety regulation, safety policy, safety promotion, inspection of hazardous conditions, maintenance equipment, high risk times, individual efficiency, and management behavior. These are important public safety elements, but must be coordinated in a way that can be measured in order to use the implementation of safety elements as a potential predictor of safe work environment [9].
Traditionally, safety precautions are evaluated after an injury has occurred, which focuses on factors such as accident rates and compensation. The issue here is that the injury has already hit, and there is no power to prevent it. In recent years, there has been a shift away from safety measures that rely entirely on retrospective data or lagging indicators, such as accident rates (AR), as well as safety climate measures and site inspections, which are referred to as “leading indicators” [34]. In that regard, Umair et al. (2021) developed a safety management system that integrates all factors affecting safety into one framework as those factors are interrelated with each other.
Several methodologies and models for assessing occupational health and safety risks have been identified in the literature [14, 21, 31, 51]. Risk analysis and assessment methods are divided into three categories [31]: qualitative, quantitative, and hybrid (qualitative and semi-quantitative) methods. The qualitative techniques are built on the analytical estimating processes and the competence of safety managers. The quantitative methodologies, on the other hand, a risk is viewed as a quantity that can be measured and described by a mathematical relationship using data from actual incidents that have occurred on a worksite. While the hybrid techniques are complex, because of their ad hoc nature, thus limiting their widespread adoption. Among those techniques found in the literature is the use of the quantification of occupational hazards [6, 37]. Also, the research conducted by Baradan and Usmen [7] used the probability (frequency) and intensity of accidents to assess H&S. A risk assessment model (RAM) has been developed to assist safety professionals’ assessing workers understand of risks that exist in their work trades [16]. Based on historical data regarding the risk levels of various sorts of work, the RAM can offer a quantitative risk assessment. The work of Gürcanli and Müngen [18] proposed a method for assessment of the risks that workers are exposed to at construction sites using fuzzy rule-based safety analysis to deal with uncertainty and insufficient data. In another effort, Rozenfeld et al. [39] developed a method used to assess risks, “construction job safety analysis” (CJSA), which can predict fluctuating safety risk levels and estimate the probability that a risk event occur. In a recent attempt, Qi et al. [37] presented a quantitative analysis of construction safety performance in three regions in China. They used nonparametric data envelopment analysis (DEA) for evaluating construction safety performance. This study was only limited for the period between the years 2003 and 2019 where the data were collected.
There are many ways of analyzing and evaluating occupational health and safety risks that have been studied in developed countries. None of these models have been made to suite developing countries such as Egypt. According to a study of the Egyptian construction sector [22], Egyptian contractors used less formal safety procedures, and the cost of accident insurance was set independently of the contractor’s safety record. Frequency and severity measures are the only metrics used to assess the safety performance of the construction industry as a whole (Egyptian Labor Law, 1981). Frequency measurement depends on the number of accidents. On the other hand, the severity measure depends on the number of workdays lost.
Most of the previously described techniques are applied retroactively to understand the reasons and decrease the number of accidents, but the outcomes for evaluating safety performance are constrained by shortcomings in accident reporting and in the investigation and analysis of accident causes [15]. Although using the outcomes of these indicators have some benefits, because they are reactive and come after the incident, their use does not improve safety results [3].
In summary, the above-discussed methods have significant drawbacks in terms of measuring safety performance in construction sites. Given these shortcomings, the purpose of this work is to develop an indicator to assess quantitatively the safety performance in construction sites. The factors that affect construction safety are first identified and then a mathematical model is developed to assess the safety performance using the analytic hierarchy process (AHP). The primary contribution of this study is the development of a safety performance assessment model that can be used by construction companies as a proactive tool to help improve their safety performance by reducing the fatalities and injuries on construction sites.

Research methodology

In this study, a serial method is used in the research design. The first step is to collect and analyze literature studies to gather factors that affect safety on construction sites. After that, a questionnaire survey was conducted to determine the most important factors among the collected factors from the literature that affect the safety performance of construction sites in Egypt. Interviews, mail, and email messages were used to conduct the questionnaire survey. To analyze the questionnaire, the relative importance index was first used to determine the importance of each factor.
An exploratory factor analysis was then performed on the collected responses to reduce the number of factors and analyze them well. Then, the analytic hierarchy process (AHP) is used to determine the weights of the most important factors in order to develop a model to assess safety performance. An index for evaluating the safety performance in construction sites is developed. Finally, the developed model is tested and validated.

Factors affecting safety performance

The construction workplace safety is complex, with numerous factors influencing it. To identify the factors affecting safety performance in construction sites, an in-depth literature review was carried out. As such, 59 factors that affect safety performance in construction sites are compiled. Then, those collected factors were reviewed. with five experts from the construction industry whose experience exceeds 10 years in semi-structured interviews to add any factors that could be related to the nature of the construction industry in Egypt or to remove any factors that do not apply to the Egyptian environment. Also, factors that have the same meaning were combined into one factor. Finally, 47 factors were identified (Table 1) for further analysis. Then, these factors were examined by preparing a survey questionnaire in which various construction safety professionals (including owners, managers, engineers, supervisors, etc.) participated. The purpose of this questionnaire is to identify the most important factors that affect the safety performance of construction projects in Egypt.
Table 1
Factors affecting safety performance in construction projects
Code
Factor
Code
Factor
Code
Factor
F1
Incentives
F17
Safety budget
F33
Accident rate (frequency and severity)
F2
Safety training
F18
Cost of accidents (injury and prevention costs)
F34
Injury (death) rate/type
F3
Provision of safety clothing and equipment
F19
Return of investment (ROI) on safety
F35
First aid rate
F4
Issue of safety booklet
F20
Project cost
F36
Safety and accident investigation/inspection
F5
Trade union involvement
F21
Quality
F37
Lessons learned
F6
Site safety representative
F22
Construction and design errors
F38
Company reputation
F7
worker co-operation on safety
F23
Equipment
F39
Company size
F8
Safety poster display
F24
Production pressure
F40
Client’s control
F9
Planned and organized site (layout)
F25
Work overload
F41
Involvement of subcontractors
F10
Wage
F26
Working time
F42
Number of employees/crew size
F11
Job satisfaction
F27
Schedule delay
F43
Management commitment
F12
Peer pressure (workmate’s influence)
F28
Work environment
F44
Communication and information
F13
Safety experience
F29
Exposure to hazard / unsafe work situation
F45
Safety control mechanisms
F14
Learning
F30
Supervisor’s behavior and effectiveness
F46
Safety programs
F15
Skill /quality of workers
F31
Worker’s behavior and attitude
F47
Development of emergency plan and procedures
F16
Worker age
F32
Personal responsibility for safety
  
For more explanation and discussion, the collected factors are grouped into 11 groups as presented below.
Motivation (Factors F1, F10, F11, and F12): Incentives towards the job for a worker in the construction industry include wages first [11, 18, 26, 32]. Also, work satisfaction can be enhanced by permanent support, financial reward and praise from the administration, which are among the incentives [32, 33]. Also, peer pressure is among the factors that affect safety performance of individuals and the group [33].
Competency (Factors F2, F13, F14, F15, and F16): The level of safety awareness is raised through training, which begins by guiding workers to become more familiar with the work they do [11, 20, 26]. This also gives experience in safety, represented by knowledge of safety issues, understanding, mastery, and implementing safety-related regulations [23, 32]. Also, learning through training increases the efficiency of workers and has a positive impact on their behavior in the field of safety [32, 33].
Safety investment (Factors F17, F18, and F19): To increase safety measures, a budget should be allocated for purchasing and maintaining safety equipment, covering the salaries of safety personnel, and other aspects of safety programs [26, 32, 33]. This increase in cost does not mean a loss, however risk reduction may lead to an investment increase [32].
Cost and productivity (Factors F20, F21, and F22): Often, project costs are reduced by reducing the safety budget. This solution leads to higher risk exposure. Also, accidents in construction sites increase as a result of rework that does not conform to quality [32].
Safety resources and equipment (Factors F3, F4, F6, F8, and F23): Safety resources must be provided to protect workers from potential hazards in construction sites [11, 23, 33]. It includes personal protective equipment and clothing, safety barriers and fences, safety posters, safety booklets, and any other facilities that help protect workers [29]. Not only this but also it provides the necessary protection when using work equipment [22, 32].
Work pressure (Factors F24, F25, F26, and F27): One of the factors significantly affecting the occurrence of accidents is the time delay [32, 33]. Under production pressure and increased working time leads to deterioration of safety conditions [32, 33].
Work condition (Factors F9, F28, and F29): Construction activities take place in a rapidly changing environment and under evolving site conditions. This change results in many factors that affect safety and exposure to hazard [11, 32]. To reduce this danger, the site must be planned and organized [11, 33].
Attitude and behavior (Factors F7, F30, F31, and F32): One of the main causes of construction accidents is the unsafe actions of workers [13, 32, 33, 49]. Therefore, all employees must cooperate and participate in creating a safe work environment, in addition to taking responsibility for improving safety performance [26, 29, 33].
Lessons learned from accidents (Factors F33, F34, F35, F36, and F37): In general, lessons learned from accidents help companies improve the effectiveness of safety procedures [32, 33]. Also, accident rates used in evaluating the level of safety [22, 32]. To reduce these rates, safety inspections of unsafe behavior of workers and working conditions are carried out.
Organization (Factors F5, F38, F39, F40, F41, and F42): Small construction companies have higher accident rate than large companies [23, 32]. This is because of their limited ability to carry out health and safety work, and there is insufficient awareness of safety. The accident rate is directly related to the number of subcontractors and the total number of workers [29, 32, 33].
Safety programs and management (Factors F43, F44, F45, F46, and F47): When senior management is clearly involved in safety, this increases safety performance, where the participation of management is a key element in safety programs, along with commitment of subcontractors, and workers participation [11, 22, 23]. Also, the mutual relations among participants affect project safety through communication, cooperation, risk management, and control and monitoring mechanisms [11, 20, 26].

Questionnaire survey

A questionnaire survey is conducted to determine the most important factors that affect safety performance of construction projects in Egypt. The questionnaire consists of two parts:
The first part is to collect data about the survey participants. Respondents were asked to provide general data such as: years of experience in the construction industry, company category (size of company), job title (owner, consultant, contractor, etc.), and nature of work (place of work). This part is mandatory to ensure accurate answers without any liability whatsoever.
The second part includes a list of the factors affecting safety performance in the construction industry as presented in Table 1. To measure the degree of impact on safety performance on a construction project, respondents are asked, based on their experience, to rate each factor using a 1–5 Likert scale, where “1” means unimportant, “2” less important, “3” moderate, “4” important, and “5” very important.
Attention was paid to distributing the questionnaire in different regions of Egypt, especially in large cities and cities that have large construction projects. Among these cities are Cairo, the 10th of Ramadan, the 6th of October, Assiut, Aswan, Alexandria, and Giza. The questionnaire was written in both English and Arabic to ensure that all of the questions were clear.

Simple size

This research-targeted construction companies for building works, foundation works, large facility works, metal construction works, and specialized complementary works. All construction companies were targeted (regardless of their size), from the seventh grade (small size companies) to the first grade (large size companies) according to the classification of the Egyptian Federation of Building and Construction Contractors (EFBCC). According to the Egyptian Engineers Syndicate’s registry for the year 2021, the number of civil engineers is 800,000.
Identifying the proper sample size is important for the reliability and credibility of the survey. There will be a loss of significant study findings if the sample size is too small. However, if it's too big, it will waste time and money. Equation (1) is used to calculate the sample size that best represents the targeted population [11].
$${\varvec{n}}=\frac{{{\varvec{n}}}^{,}}{1+\frac{{{\varvec{n}}}^{,}-1}{{\varvec{N}}}}$$
(1)
where: n is the sample size from finite population; N is the total population (800,000 civil engineers) and n' can be calculated using Eq. 2.
$${{\varvec{n}}}^{,}=\frac{{{\varvec{Z}}}^{2}*{{\varvec{S}}}^{2}}{{{\varvec{V}}}^{2}}$$
(2)
where: V is standard error of sample population assumed 0.05. \({{\varvec{S}}}^{2}\) Is the standard error variance of population elements which is defined as \({{\varvec{S}}}^{2}\) = P (1 − P) and it is maximum at P = 0.5 and Z is the confidence coefficient equals 1.645 at 90% confidence. Applying both equations, the sample size is determined to be 271. The number of responses to the questionnaire, which contains 47 factors (Table 1), was 245 respondents, less than the required sample size. It is, therefore, necessary to measure the adequacy of the sample size before analyzing the data.
The Kaiser–Meyer–Olkin (KMO) test (Eq. 3) is a measure implemented to measure the adequacy of the sample size. In other words, the suitability of the data for analysis [42].
$${{\varvec{K}}{\varvec{M}}{\varvec{O}}}=\frac{{\sum }_{{\varvec{i}}\ne {\varvec{j}}}{{\varvec{R}}}_{{\varvec{i}}{\varvec{j}}}^{2}}{{\sum }_{{\varvec{i}}\ne {\varvec{j}}}{{\varvec{R}}}_{{\varvec{i}}{\varvec{j}}}^{2}+{\sum }_{{\varvec{i}}\ne {\varvec{j}}}{{\varvec{U}}}_{{\varvec{i}}{\varvec{j}}}^{2}}$$
(3)
where: \({{\varvec{R}}}_{{\varvec{i}}{\varvec{j}}}\) is the correlation matrix, and \({{\varvec{U}}}_{{\varvec{i}}{\varvec{j}}}\) is the partial covariance matrix.
The range of KMO values is 0 to 1. KMO values between 0.8 to 1.0 show that the sample is adequate, values between 0.7 to 0.79 are middling, values between 0.6 to 0.69 are mediocre and values less than 0.6 indicate that the sample is not adequate [42]. According to the KMO scale of sampling adequacy, the value of the KMO statistic was 0.944, which indicates that the sample size is adequate.

Data collection and analysis

After collecting the responses from the participants, the collected data are analyzed. The demographics of the survey respondents are presented in Fig. (1). First, for the workplace (Fig. 1a), the results show that the questionnaire covered all workplaces, and the largest percentage was for those who are working in construction sites (63% for site and supervision). Sites are the most accident-prone places. Figure 1b shows companies’ grades (company size) based on the FEBCC classification. Since the size of the company is one of the factors affecting occupational safety and health. As far as possible, the questionnaire was distributed to different companies to cover different company sizes. The results show that 57% of the respondents are from large companies (first, second and third grades). such companies are the highest in implementing health and safety regulations and plans [28].
Third, regarding participants’ years of experience, Fig. (1-c) shows that 42% of the participants (have more than 10 years of experience. Accordingly, the result of this questionnaire is highly reliable. Finally, Fig. (1-d) shows the participants’ job titles. The results show the all-project parties who are in charge of the work and responsible for safety participated in the questionnaire.
The collected data were then analyzed by calculating the relative importance index (RII) to determine the most important factors, as shown in the following subsection.

Factors ranking using the relative importance index (RII)

The RII is calculated to determine each factor’s level of importance. The RII is calculated using Eq. (4) [41].
$${\varvec{R}}{\varvec{I}}{\varvec{I}}=\frac{{{\varvec{w}}}_{{\varvec{i}}}{{\varvec{x}}}_{{\varvec{i}}}}{{\varvec{A}} {\varvec{N}}}$$
(4)
where wi is the five-point priority scale (1 to 5), xi is the frequency of the priority scale, A is the greatest priority value (i.e., 5), and N is the total number of responses. The RII values are reported at five key levels [34]: High “H” (0.8 ≤ RII ≤ 1), High–Medium “H–M” (0.6 ≤ RII < 0.8), Medium “M” (0.4 ≤ RII < 0.6), Medium–Low “M–L” (0.2 ≤ RII < 0.4), and Low “L” (0 ≤ RII < 0.2) [34]. Factors that are ranked “M-L” and “L” are not taken into consideration [10].
The analysis’s findings are listed in Table 2, where 10 factors only are ranked as L or M-L and removed. Those factors are (F4) issue of safety booklet, (F5) trade union involvement, (F12) peer pressure (workmate’s influence), (F19) return of investment in safety, (F24) production pressure, (F25) work overload, (F26) working time, (F27) schedule delay, (F40) client’s control, and (F42) number of employees/crew size. As such, based on this analysis, 37 factors are considered important.
Table 2
Ranking safety factors using the RII
Code
Factors
RII
Importance
F1
Incentives
0.779
H-M
F2
Safety training
0.776
H-M
F3
Provision of safety clothing and equipment
0.809
H
F4
Issue of safety booklet
0.398
M-L
F5
Trade union involvement
0.397
M-L
F6
Site safety representative
0.620
H-M
F7
Workers’ cooperation on safety
0.561
M
F8
Safety poster display
0.602
H-M
F9
Site planning and organization (layout)
0.824
H
F10
Wages value
0.515
M
F11
Job satisfaction
0.507
M
F12
Peer pressure (workmate's influence)
0.399
M-L
F13
Safety experience
0.81
H
F14
Education level
0.48
M
F15
Skill/quality of workers
0.815
H
F16
Worker age
0.484
M
F17
Safety budget
0.821
H
F18
Cost of accidents (injury and prevention costs)
0.502
M
F19
Return of investment in safety
0.399
M-L
F20
Project cost
0.443
M
F21
Quality
0.539
M
F22
Construction and design errors
0.544
M
F23
Equipment
0.587
M
F24
Production pressure
0.398
M-L
F25
Work overload
0.397
M-L
F26
Working time
0.399
M-L
F27
Schedule delay
0.389
M-L
F28
Work environment
0.798
H-M
F29
Exposure to hazard/unsafe work situation
0.587
M
F30
Supervisor’s behavior and effectiveness
0.801
H
F31
Worker's behavior and attitude
0.620
H-M
F32
Personal responsibility for safety
0.811
H
F33
Accident rate (frequency and severity)
0.563
M
F34
Injury (death) rate/type
0.524
M
F35
First aid training
0.515
M
F36
Safety and accident investigation/inspection
0.838
H
F37
Lessons learned
0.578
M
F38
Company reputation
0.516
M
F39
Company size
0.508
M
F40
Client's control
0.394
M-L
F41
Involvement of subcontractors
0.504
M
F42
Number of employees/crew size
0.393
M-L
F43
Management commitment
0.804
H
F44
Communication and information
0.765
H-M
F45
Safety control mechanisms
0.584
M
F46
Safety programs
0.630
H-M
F47
Development of emergency plan and procedures
0.522
M
Due to the large number of factors (37 factors) resulting from the RII analysis, there is a need for another analysis to limit the very important and related factors to a smaller number to facilitate their analysis and give realistic and correct results. So, exploratory factor analysis (EFA) is used.

Exploratory factor analysis (EFA)

EFA is a popular statistical data analysis technique for reducing the number of factors in a set of data and figuring out how they relate to one another. It is used to figure out how many very important factors may be derived from a list of factors [50]. For this paper, a statistical package for the social sciences (SPSS) was employed. EFA begins by forming a matrix of correlations among factors. This matrix shows the Pearson’s correlation coefficients for each pair of factors. Only factors with correlations greater than 0.3 but less than 0.9 are chosen [10]. If the correlation is less than 0.3 and thus means that such factor has weak influence (not important). On the other hand, if the correlation is greater than 0.9 and thus means that this factor is highly correlated with other factors, and most probably is a duplicate of some other factor.
Additionally, the population correlation matrix is not an identity matrix, according to the Bartlett Test of Sphericity, which has a result of 666.00 and a significance level of 0.00. The data gained from the Bartlett Test of Sphericity and the Kaiser–Meyer–Olkin (KMO) measure of sample adequacy, which were mentioned previously; support the use of the EFA and the possibility of condensing these factors into a smaller set [44].
EFA is performed with all the 37 factors for the first iteration, and nineteen factors are eliminated: F6, F7, F11, F14, F16, F20, F21, F22, F31, F33, F35, F36, F37, F38, F39, F41, F45, F46, F47. A second cycle is done to confirm that the residual factors are inside the limit range. After the second iteration, six factors are eliminated: F8, F10, F18, F23, F29, and F34. Finally, F44 has also been removed from the third iteration. A fourth iteration is carried out to guarantee that no further data crosses the thresholds. The final factors are listed, as shown in Table 3.
Table 3
Correlations matrix
Factor
F1. Incentives
F2. Safety training
F3. Provision of safety clothing and equipment
F9. Site planning and organization (layout)
F13. Safety experience
F15. Skill/quality of workers
F17. Safety budget
F28. Work environment
F30. Supervisor’s behavior and effectiveness
F32. Personal responsibility for safety
F43. Management commitment
F1. Incentives
1
          
F2. Safety training
.547
1
         
F3. Provision of safety clothing and equipment
.497
.671
1
        
F9. Site planning and organization (layout)
.377
.471
.592
1
       
F13. Safety experience
.452
.563
.579
.568
1
      
F15. Skill/quality of workers
.468
.440
.530
.503
.521
1
     
F17. Safety budget
.457
.473
.433
.428
.543
.404
1
    
F28. Work environment
.390
.480
.406
.450
.383
.444
.388
1
   
F30. Supervisor’s behavior and effectiveness
.404
.498
.480
.474
.495
.514
.418
.517
1
  
F32. Personal responsibility for safety
.304
.441
.342
.381
.401
.367
.450
.536
.458
1
 
F43. Management commitment
.479
.499
.473
.536
.444
.503
.469
.559
.557
.484
1

Most important factors description

Based on previous analysis, the highly influential 11 factors affecting safety on construction sites are identified. To ensure the success of safety practices on construction sites, those factors must be understood. In general, an effective safety program can be measured by the absence of worker injuries or damaged equipment, machinery, or tools, no harm to the environment, maintaining a company’s safety record, and increasing productivity. Table 4 presents and explains those factors and their influence on the success of safety programs.
Table 4
Descriptions and sources of construction safety factors
Factor
Description
Selected references
Incentives
Workers who behave positively and safely at work are given promotions and praise
[20, 23]
Safety training
The extent to which all skilled and non-skilled employees are trained and made aware of workplace hazards
[19, 24]
Provision of safety clothing and equipment
To reduce injuries, it must be ensured that all workers are given the required safety clothing and appropriate personal protective equipment. Also, care must be taken to maintain them on an ongoing basis
[4, 49]
Site planning and organization (layout)
To reduce the risks exposed to the site, the site must be planned and organized (operating the site) in terms of the tools and equipment used, the available resources, and the methods used in the work procedures
[11]
Safety experience
Workers who have experience with work accidents tend to attribute the cause of the accident to the environment. Worker safety training must be completed in order to provide the necessary safety capabilities. Among them are knowing which label is used to indicate bad habits, educating workers about the benefits of safe work practices, or providing detailed information or guidance
[11]
Skill/quality of worker
For a successful safety program, there is a need for a suitable worker in a suitable job, to take advantage of workers’ ability to identify safety risks using their experience and skill and to make appropriate decisions
[47, 49]
Safety budget
Safety procedures affect project budget in ways such as monetary rewards, work injury costs, worker changes, the cost of increased working time, changes in insurance premiums, and legal costs
[48]
Work environment
Location, the environment, and operating at night all have a significant impact on safety performance. As a result, the organization continuously adapts to the demands placed on it by the environment, to maintain a safe work environment
[11]
Supervisor’s behavior and effectiveness
Managers must provide enough supervision to protect workers from work risks as part of a sound safety policy. Supervisors should provide workers with tasks that are compatible with their abilities, praise them when they complete tasks safely, communicate with them, and address any emerging safety issues
[13, 46]
Personal responsibility for safety
Safety should be everyone’s responsibility. So, managers must delegate authority and transfer responsibility to workers at lower levels of authority in order to complete activities safely
[2, 40]
Management commitment
The management must be committed to apply safety procedures in order to obtain an effective safety program. This includes issuing written safety rules, providing adequate safety equipment and clothing, handling complaints promptly, conducting regular safety meetings and training, visiting the work site regularly, and following the same safety regulations
[2, 46]

Assessing safety performance

The most important 11 factors obtained from the previous analysis will be used to measure safety performance in construction sites. To measure the safety performance, too steps are needed: (1) determining the relative weights of the factors as they are not equally weighted; and (2) measuring the availably of these factors in a given construction site.

Identifying safety factors weights

The analytical hierarchy process (AHP) was utilized to find the weights of the 11 factors affecting safety performance. Developing the hierarchy of the problem at hand is the initial step in applying the AHP. Finding the relative importance of the elements at each level is the second stage. In order to obtain better results and to ease the pairwise comparison process, the eleven factors that affect safety performance were divided into main factors and sub-factors [29, 30], as shown in Fig. 2. The main factors are project level (PL) and organizational level (OL).
To determine the relative weights of the factors, a questionnaire is developed and sent to construction safety experts. Each expert is asked to rank each component on a scale of importance in relation to the others (pairwise comparisons) in light of the objective. For example, one question is asked as, “how safety experience is preferred when compared with work environment in satisfying safety at project level”. A scale of one to nine [43] is used for these pairwise comparisons, one means that both factors are equally preferred, while nine indicates that one factor is greatly preferred over the other. In this study, the opinions of 20 safety experts, whose experience are ranging from 5 to 20 years, were solicited.
As such, the geometric average of the respondents’ responses is computed in order to create the pairwise comparison matrix. For example, Table 5 presents the pairwise comparison matrix for the PL’s five components. Following the creation of the pairwise comparison matrix, the evaluation criteria’s priority weights are calculated in two steps. First, normalize the pairwise comparison matrix using Eq. (5). After that, using Eq. (6) to create the weights [8], the normalized pairwise matrix and weights are displayed in Table 6.
Table 5
The pairwise comparison matrix
 
Safety experience
Skill/quality of worker
Work environment
Supervisor’s behavior and effectiveness
Personal responsibility for safety
Safety experience
1
3
1
7
6
Skill/quality of worker
0.33
1
0.5
5
4
Work environment
1
2
1
5
5
Supervisor’s behavior and effectiveness
0.143
0.2
0.2
1
0.25
Personal responsibility for safety
0.167
0.25
0.2
4
1
Table 6
The normalized pairwise comparison matrix
 
Safety experience
Skill/quality of worker
Work environment
Supervisor’s behavior and effectiveness
Personal responsibility for safety
Sub- total
Priority weights
Safety experience
0.375
0.555
0.314
0.301
0.497
2.043
0.375
Skill/quality of worker
0.124
0.185
0.157
0.215
0.331
1.0123
0.185
Work environment
0.375
0.370
0.314
0.215
0.414
1.689
0.314
Supervisor’s behavior and effectiveness
0.0537
0.037
0.063
0.043
0.021
0.217
0.043
Personal responsibility for safety
0.063
0.046
0.063
0.172
0.083
0.427
0.083
$${{\varvec{a}}}_{{\varvec{i}}{\varvec{j}}}^{\mathbf{*}}=\frac{{{\varvec{a}}}_{{\varvec{i}}{\varvec{j}}}}{{\sum }_{{\varvec{i}}=1}^{{\varvec{n}}}{{\varvec{a}}}_{{\varvec{i}}{\varvec{j}}}}\mathrm\quad{ For \;all }\;j = 1, 2, \dots ,\mathrm{ n}$$
(5)
$${{\varvec{w}}}_{{\varvec{i}}{\varvec{j}}}=\frac{{\sum }_{{\varvec{j}}=1}^{{\varvec{n}}}{{\varvec{a}}}_{{\varvec{i}}{\varvec{j}}}^{\mathbf{*}}}{{\varvec{n}}}\mathrm\quad{For\; all }\;i = 1, 2, \dots ,\mathrm{ n}$$
(6)
It is important to check the pairwise comparisons' consistency. As a result, the λmax value is calculated as 5.298. The consistency index (CI) is then calculated using the value of λmax shown below [8]:\({\varvec{C}}{\varvec{I}}=\boldsymbol{ }\frac{{{\varvec{\lambda}}}_{{\varvec{m}}{\varvec{a}}{\varvec{x}}}-{\varvec{n}}}{{\varvec{n}}-1}=0.0745\)
The consistency ratio (CR) is calculated by Eq. (7), where the RI changes depending on how many evaluation criteria are used and equals 1.12 for 5 criteria. The consistency of judgments is satisfactory because the CR is 0.066, which is less than 0.1. The priority weights of the 11 factors are displayed in Table 7.
Table 7
Factors’ priority weights
Factors
Weight
Safety experience
0.116
Skill/quality of worker
0.155
Work environment
0.072
Supervisor’s behavior and effectiveness
0.017
Personal responsibility for safety
0.063
Incentives
0.031
Safety training
0.073
Provision of safety clothing and equipment
0.079
Site planning and organization (layout)
0.217
Safety budget
0.136
Management commitment
0.041
$${\varvec{C}}{\varvec{R}}= \frac{{\varvec{C}}{\varvec{I}}}{{\varvec{R}}{\varvec{I}}}$$
(7)
The pair-wise comparison matrices for the OL factors and for the main factors were developed the same way. Finally, the weights of all the 11 factors were calculated as presented in Table 7. “The site planning and organization (layout)” factor was ranked as the most important factor affecting safety performance with the highest weight of 0.217. This agrees with El-Nagar et al. [11] findings, which considered that organizational factors are the most important factors, especially those that can cover management practices to make any improvements or changes to construction safety.

Safety factors’ level of implementation

In order to assess how well construction projects perform in terms of safety, it is necessary to score each of the 11 factors based on how much is level of implementation of a given factor. As such, each factor’s level of implementation is measured on a scale ranging from 0 to 1 [5, 11]. Such scoring is based on certain criteria that reflect the level of implementation (availability or existence) of a given factor. Here, an analysis is made of the factors affecting the safety performance of a construction site to facilitate its assessment and the degree of its level of implementation.
Safety experience: The experience and background of the workers’ safety training were assessed. Based on the number of training courses obtained as shown in Table 8.
Table 8
Safety experience evaluation
Number of training courses
0
2
3
4
5
Safety experience value
0
0.25
0.50
0.75
1
Skill/quality of worker: The efficiency of a worker is evaluated as presented in Table 9 and through which skill /quality of workers value can be obtained.
Table 9
Evaluation of safety factors
Evaluation score
0
0.5
1
Skill/quality of worker
(Worker efficiency)
Weak
Moderate
Excellent
Work environment
(Provide requirements tonight)
No
Sometimes
Always
Supervisor’s behavior and effectiveness
(Supervisor efficiency)
Weak
Moderate
Excellent
Personal responsibility for safety
(Commitment)
Weak
Moderate
Excellent
Incentive
(Motivation strategies)
No
Sometimes
Always
Provision of safety clothing and equipment
(Commitment)
Weak
Moderate
Excellent
Site planning and organization
(Site-level coordination)
Weak
Moderate
Excellent
Safety budget
(Budget)
Unrecognized
In some projects
Always
Management commitment
(Commitment)
Weak
Moderate
Excellent
Work environment: To ensure safety, night work and workplace are evaluated (Table 9).
Supervisor’s behavior and effectiveness: The competency of the safety supervisor is evaluated as shown in Table 9. Through that supervisor’s behavior and effectiveness value can be obtained.
Personal responsibility for Safety: Everyone from the top to the bottom of the hierarchical levels involved understands that preventing accidents is everyone’s duty. As such, commitment of personal responsibility for safety is evaluated (Table 9).
Incentives: The motivation strategies (reward) provided by the company management can be used to evaluate this factor (Table 9).
Provision of safety clothing and equipment: The administration’s commitment to provide the necessary safety equipment and clothing is used to evaluate this factor (Table 9).
Site planning and organization (layout): Coordination at the site, “including the location and equipment employed,” is used for evaluating site (Table 9).
Safety budget: Company’s budget that covers safety-related requirements is used to evaluate this factor (Table 9).
Management commitment: The management’s commitment to implement, manage, and maintain safety is used to evaluate this factor (Table 9).
Safety training: The use of safety clothing and equipment is taught to employees. Additionally, project managers and supervisors are trained in safety. Periodic training is used to evaluate this factor (Table 10).
Table 10
Periodic training
Periodic training
No
Only
employees
Employees and newly recruits
Employees, newly recruits, and supervisors
Employees, newly recruits, supervisors,
and managers
Safety training value
0
0.25
0.5
0.75
1

Evaluating construction site safety

Having the safety evaluation factors’ weights identified and the safety factors scored based on their level of implementation, the safety performance in construction (SPC) sites could be measured or evaluated (Eq. 8).
$${\varvec{SPC}} = \sum {\varvec{W}}_{{\varvec{i}}} \times {\varvec{A}}_{{\varvec{i}}} \quad{\text{for }}\;i{ } = { }1,{ } \ldots ..,{ }n$$
(8)
where:\({{\varvec{W}}}_{{\varvec{i}}}\): factor i priority weight (Table 7, determined from the AHP analysis); \({{\varvec{A}}}_{{\varvec{i}}}\): factor i score as per its level of implementation (existence) (Tables 810); and n is the number of assessing factors (11 factors in this study). For example, Table 11 illustrates this process for some criteria. Based on total score obtained, a safety performance assessment could be identified as per the classification presented in Table 12 [34].
Table 11
Example of safety performance evaluation
Performance factor
Implementation level
Value
Criteria weight
Score
Giving incentives to workers
Sometimes
0.5
0.031
0.0155
Provide safety training for employees
All
1
0.073
0.073
Provide safety clothing and equipment
Weak
0
0.079
0
Work on site planning and organization
Moderate
0.5
0.217
0.1085
Safety budget
Always
1
0.136
0.136
The management’s commitment to implementing, managing, and maintaining safety
Excellent
1
0.041
0.041
Total (OL)
   
0.374 (37.4%)
Table 12
Safety performance levels
SPC (%)
0–20%
 > 20%-40%
 > 40%-60%
 > 60%-80%
 > 80%-100%
Safety performance
level
Extremely unsafe
Unsafe
Moderately unsafe
Safe
Extremely safe

Case study

A bridge construction project was studied to determine its safety performance. The bridge is located in Aswan city, south of Egypt with a length of 555.0 m and height 7.0 m. The project site was visited, and the safety performance assessment list was completed by the project manager. Table 13 shows the project manager’s assessment of safety factors, the weight of each factor as determined previously from the AHP analysis, and the final safety performance score.
Table 13
Case study results
Performance criteria
Evaluation
Value
Criteria weight
Score
Number of safety training courses
3
0.50
0.116
0.058
Worker efficiency
Moderate
0.50
0.155
0.0775
Provide requirements work environment (Location, weather conditions, working at night)
No
0
0.072
0
Supervisor efficiency
Moderate
0.50
0.017
0.0085
Everyone accountable to safety
Weak
0
0.063
0
Giving incentives to workers
Sometimes
0.50
0.031
0.0155
Provide safety training for employees
Employees, newly recruits, and supervisors
0.75
0.073
0.05475
Provide safety clothing and equipment
Excellent
1
0.079
0.079
Work on site planning and organization
Excellent
1
0.217
0.217
Safety budget
In some projects
0.50
0.136
0.068
The management’s commitment to implement, manage, and maintain safety
Moderate
0.50
0.041
0.0205
Total (SPC)
   
0.59875

Case study results and discussion

Based on the results presented in Table 13, the safety performance level of the project (0.59875) was rated as moderately unsafe. Despite such evaluation, it is very close to being safe (0.6). A construction safety management evaluation form is proposed for use by project managers (Table 13). This form shows the eleven main factors (including incentives, safety training, and the provision of safety equipment and clothing). The bridge construction project manager believes that the evaluation form provides a comprehensive view of safety management. It is also easy-to-use and be used to check what is needed to improve safety performance on site. Such model is particularly useful for the construction industry in Egypt because there is currently no such simple and quick tool to help project owners and managers to assess safety in construction sites. Also, the proposed model could help to detect failure in the management and application of safety. In addition, this model serves as a tool to discover faults in the implementation of the most important factors affecting safety performance from the point of view of safety experts.
After evaluating the safety performance in the case study, the results showed that the number of training courses in the field of safety must be increased for all employees in order to spread safety awareness for all project workers who bear the responsibility for safety. Also, in order to address the safety issues associated with diverse construction activities, safety staff must be adequately trained and experienced, and to select workers with sufficient experience to perform the required work. Also, providing work requirements in a safe environment is especially important when working at night. The administration should also focus more on implementing and inspecting safety laws.

Study limitations

This research attempted to adequately develop a practical model for assessing safety performance in construction sites in Egypt. Even though the proposed approach via application on a case study project was successful, this research still has some limitations that need to be addressed in future research. First, the respondents that replied to the survey were not precisely distributed over the different regions of Egypt. Such geographical location limitation may prevent the generalization of the developed safety performance assessment model. Second, another limitation concerns the respondents’ type of project. Thus, might cause the developed model to be biased to a given project type. Accordingly, to maintain the generality of the developed model, it was necessary to ensure that the respondents are working in all types of construction projects. Third, the developed model even though working well with the case study presented, more case studies should have been experimented with to make sure its ability to work accurately with different types of projects. Accordingly, further investigations might be required. In addition, measuring the implementation level (existence) of safety performance factors needs more investigation among construction practitioners to ensure its accuracy in assessing safety performance.

Conclusions

Creating a safety performance index for Egyptian construction projects is the goal of this study in an effort to raise construction safety. Forty-seven factors affecting safety performance have been identified. A questionnaire survey was carried out in order to identify the most important factors influencing the safety of Egyptian construction projects. The relative importance index and the exploratory factor analysis were used to identify the most important factors affecting safety performance and resulted in identifying 11 factors. Among those factors are incentives, the provision of safety clothing and equipment, and the work environment. Then, the AHP method is used to determine the relative weights of the identified factors in order to develop a mathematical model to assess safety performance in construction sites. Based on the AHP analysis, organizational factors have higher weights than project related factors. Therefore, more attention should be paid to these factors. The sub-factor skill /quality of worker was found to be one of the most important factors affecting safety.
On many construction sites, management has little interest in organizing training sessions for employees, managers, or supervisors on safety policies and procedures with no or little periodic reviews of training requirements. Therefore, there is a need for strong awareness, which may be done in various ways including displaying safety posters and banners, instructing employees on how to use safety equipment and clothing, and holding meetings to discuss safety measures. The proposed model was then applied on a case study project to assess the safety performance level on a bridge construction site. The results revealed that the level of supervision and accountability for safety were low. As such, safety plans should be reviewed and updated on a regular basis to reflect changing site conditions, rather than relying on their validity at the start. Discussing the results of the case study with site personnel shows their satisfaction with the developed model and its ability to assess the safety performance in the construction site.

Declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

Our article does not contain any studies with human participants.
For this study no informed content is required.
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://​creativecommons.​org/​licenses/​by/​4.​0/​.
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Metadaten
Titel
Safety performance evaluation of construction projects in Egypt
verfasst von
Zeinab Abdalfatah
Emad Elbeltagi
Mohammed Abdelshakor
Publikationsdatum
01.09.2023
Verlag
Springer International Publishing
Erschienen in
Innovative Infrastructure Solutions / Ausgabe 9/2023
Print ISSN: 2364-4176
Elektronische ISSN: 2364-4184
DOI
https://doi.org/10.1007/s41062-023-01181-y

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