The Influence of Managers’ Safety Perceptions and Practices on Construction Workers’ Safety Behaviors in Saudi Arabian Projects: The Mediating Roles of Workers’ Safety Awareness, Competency, and Safety Actions

Abstract

Improving construction site safety remains a critical challenge in Saudi Arabia’s rapidly growing construction sector, where high accident rates and diverse labor forces demand evidence-based managerial interventions. This study investigated the influence of Managers’ Safety Perceptions and Practices (MSP) on Workers’ Safety Behaviors (WSB) in the Saudi construction industry, emphasizing the mediating roles of Workers’ Safety Awareness (WSA), Safety Competency (WSC), and Safety Actions (SA). The conceptual framework integrates these three mediators to explain how managerial attitudes and practices translate into frontline safety outcomes. A quantitative, cross-sectional design was adopted using a structured questionnaire distributed among construction workers, supervisors, and project managers. A total of 352 from 384 valid responses were collected, and the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS 4. The findings revealed that MSP does not directly influence WSB but has significant indirect effects through WSA, WSC, and SA. Among these, WSC emerged as the most powerful mediator, followed by WSA and SA, indicating that competency is the most critical driver of safe worker behavior. These results provide robust empirical support for a multidimensional mediation model, highlighting the need for managers to enhance safety behaviors not merely through supervision but through fostering awareness and competency, providing technical training, and implementing proactive safety measures. Theoretically, this study contributes a novel and integrative framework to the occupational safety literature, particularly within underexplored Middle Eastern construction contexts. Practically, it offers actionable insights for safety managers, industry practitioners, and policymakers seeking to improve construction safety performance in alignment with Saudi Vision 2030.

1. Introduction

The construction industry is a cornerstone of global economic development, contributing approximately 13% of global GDP and employing over 220 million workers worldwide [1]. Despite its economic importance, it remains one of the most labor-intensive and high-risk sectors worldwide, with safety performance recognized as a critical factor affecting both operational continuity and workforce well-being, particularly in rapidly developing countries such as Saudi Arabia [2,3,4,5]. The industry continues to experience persistently high rates of accidents and fatalities due to unsafe practices, inconsistent training, and insufficient safety oversight [6,7,8,9]. It still faces persistent challenges related to unsafe work behaviors, limited worker training, and inconsistent enforcement of safety protocols [10,11,12]. Practically, the Saudi Arabian construction sector presents unique challenges that amplify the need for a deeper understanding of these safety dynamics. The workforce is largely composed of migrant laborers who often face language barriers, limited formal training, and exposure to extreme environmental conditions [13,14,15,16]. Despite regulatory frameworks, many construction firms lack coherent safety systems that integrate managerial practices with ongoing behavioral monitoring.

The influence of management on safety outcomes in construction environments has gained increasing attention in current research. Managers’ safety perceptions, defined as their attitudes, beliefs, and practices toward safety, are foundational to fostering a culture of prevention and accountability [17,18,19,20,21]. A safety-conscious leadership approach enhances communication, improves compliance, and positively influences how workers perceive and respond to potential hazards on site [22,23,24]. Managers’ commitment to safety—reflected through leadership practices, communication, and resource allocation—has been shown to influence the development of a positive safety climate [25,26,27,28]. When frontline supervisors and managers prioritize safety, their behavior sets a tone that is often mirrored by workers, resulting in better adherence to safety guidelines and lower incident rates. Conversely, managerial neglect or inconsistent practices can foster a culture of risk-taking, exposing workers to avoidable hazards [29,30,31]. However, this relationship is not always direct or linear, and understanding the mechanisms through which managerial influence translates into workers’ safety behavior (WSB) remains underdeveloped in literature.

The influence of managerial safety practices on workers’ behavior tends to be shaped by mediating factors, such as employees’ safety awareness and their level of competency [32,33]. Safety awareness refers to an individual’s recognition of hazards and their understanding of safe practices [34], while safety competency involves the practical knowledge and technical skills required to execute tasks safely [35]. Both constructs are essential for translating safety knowledge into action, especially in high-risk environments like construction sites. In addition to awareness and competency, safety actions such as training programs, proactive safety, toolbox talks, hazard drills, and feedback mechanisms may play a critical role in shaping a strong safety culture [36,37]. Proactive safety initiatives that emphasize learning, employee involvement, and continuous improvement have been shown to significantly enhance safety performance [38,39,40]. These actions, when executed consistently and supported by management, can reduce the frequency and severity of accidents. The current body of knowledge lacks integrated models that explain how MSP affects WSB through mediating constructs such as workers’ safety awareness (WSA), workers’ safety competency (WSC), and safety actions (SA).

Alsulami et al. [7] highlighted how emotionally intelligent managers foster positive safety climates and reduce stress-related errors, while Elosta and Alzubi [21] emphasized transformational leadership and perceived employer responsibility as key drivers of workers’ safety commitment. Pourmazaherian and Musonda [41] and Rahman et al. [42] both underscored safety competency as a critical mediator that translates training into behavioral safety outcomes, stressing the need for strategic alignment between training and performance goals. Additionally, the literature identifies structured supervisory practices and consistent safety communication as central to operationalizing safety culture. Al-Bayati et al. [28] emphasized the role of frontline supervisors in enforcing managerial intent through proactive engagement, validating the mediating role of Safety Actions (SA). Mosly and Makki [6] and Alqahtani et al. [13] showed how workers’ safety awareness is shaped by managerial communication strategies, particularly in culturally diverse and multilingual environments. Studies by Amirah et al. [43] and Alshehri et al. [44] supported the use of structured safety actions and competency-based systems as pathways linking safety culture to behavioral outcomes. Finally, Cheng et al. [45] offered a forward-looking view, suggesting that evolving managerial approaches, including digitized and behavior-based safety systems, can further enhance safety performance in complex, technology-driven construction settings.

Despite the breadth of existing studies addressing safety leadership, competency, and communication, most prior studies tend to focus on isolated variables or theoretical reviews, lacking a comprehensive, data-driven model that captures the complex interplay among managerial intent, worker perception, and behavioral outcomes. This study addresses that gap by empirically testing a multi-path mediation framework using structural equation modeling, tailored specifically to the socio-cultural and operational dynamics of Saudi construction projects.

The purpose of this study was to examine how managers’ perceptions of safety influence workers’ safety behaviors in the Saudi construction sector, with a focus on the mediating roles of workers’ safety awareness, competency, and safety actions. The findings are useful for construction professionals, particularly project managers, safety officers, and policymakers—seeking to enhance safety outcomes on construction sites. By understanding the mechanisms through which managerial attitudes influence safety performance, stakeholders can develop more effective and targeted strategies to enhance hazard recognition, ensure compliance with safety protocols, and foster a proactive safety culture. This contributes to fewer workplace accidents, improved worker well-being, and stronger organizational safety performance across the construction industry.

2. Key Dimensions Influencing WSB

Understanding the mechanisms through which workplace safety is cultivated requires examining both managerial influences and worker-level dimensions. In high-risk environments such as construction, Managers’ Safety Perceptions and Practices (MSP) serve as the foundation for developing key safety dimensions, including Workers’ Safety Awareness (WSA), Workers’ Safety Competency (WSC), and the implementation of Safety Actions (SA). These dimensions, in turn, play a direct role in shaping Workers’ Safety Behaviors (WSB)—both compliance-based and proactive. The following subsections explore how MSP influences each safety dimension and how, collectively, these dimensions impact the safety behaviors of workers on-site.

2.1. Managers’ Safety Perceptions and Practices (MSP)

Managers’ Safety Perceptions and Practices (MSP) are fundamental to shaping safety dimensions at the worker level. MSP includes managerial attitudes toward safety, their commitment to enforcing safety policies, and their role in setting behavioral expectations. When managers demonstrate high safety commitment, such as through site visits, risk communication, and visible compliance with safety procedures, they positively influence the development of Workers’ Safety Awareness (WSA), Workers’ Safety Competency (WSC), and the implementation of Safety Actions (SA) [7,21,28]. In other words, managers influence WSA by communicating hazards and reinforcing risk anticipation; WSC by investing in worker training and supporting decision-making skills; and SA through the enforcement of structured safety activities such as toolbox talks, inspections, and feedback systems. In turn, these enhanced dimensions contribute to positive Workers’ Safety Behaviors (WSB) by fostering both compliance and proactive practices [43]. Conversely, a lack of visible managerial engagement in safety often results in worker complacency and increased unsafe acts.

2.2. Workers’ Safety Awareness (WSA)

Workers’ Safety Awareness (WSA) refers to an individual’s ability to identify workplace hazards, understand safety procedures, and anticipate risks before they escalate into accidents. It is a cognitive construct that shapes how workers interpret and respond to safety instructions, influencing both compliance-based and proactive safety behaviors [41,43]. Safety awareness plays a foundational role in the development of workers’ safety behaviors (WSB). Employees who are more informed about the potential consequences of unsafe practices are significantly more likely to follow established safety protocols, wear protective equipment, and avoid risk-taking behaviors [46]. Awareness also influences proactive behaviors such as hazard reporting, participating in safety meetings, and advising co-workers on proper practices [47].

2.3. Workers’ Safety Competency (WSC)

Workers’ Safety Competency (WSC) refers to the practical ability of workers to perform their tasks safely, guided by their technical knowledge, situational judgment, and familiarity with safety protocols. Competency enables workers not only to follow instructions but also to make informed safety decisions, respond to hazards, and take initiative in dynamic work environments [42,48]. Safety competency has been widely linked to improvements in Workers’ Safety Behaviors (WSB), particularly in industries like construction, where the operating environment is often unpredictable and hazardous. Competent workers are more likely to engage in both compliance behaviors (e.g., proper use of personal protective equipment) and proactive behaviors (e.g., hazard reporting and mentoring peers), thereby strengthening safety culture and performance outcomes.

2.4. Safety Actions (SA)

Safety Actions (SA) refer to the structured set of preventive, corrective, and supportive measures implemented on construction sites to reduce hazards and improve safety performance. These include routine site inspections, hazard assessments, emergency drills, safety incentive programs, and reactive interventions such as incident investigations and corrective actions [49]. Safety Actions are critical in shaping workers’ safety behaviors (WSB) by reinforcing expected standards, reducing ambiguity in safety procedures, and enhancing accountability among site personnel. The effectiveness of SA lies not only in their design but also in their consistent implementation and alignment with organizational safety values [50,51]. Research suggests that when safety actions are embedded into day-to-day workflows and supported by managerial engagement, workers demonstrate higher adherence to protocols, improved hazard perception, and more proactive behavior [44]. In environments where safety actions are visible, regularly practiced, and well-communicated, workers are more likely to perceive safety as an organizational priority and adapt their behaviors accordingly. For example, companies that implement daily toolbox talks, enforce PPE usage, and publicly recognize safe performance tend to experience fewer incidents and higher compliance levels [52].

3. Theoretical Framework of Managerial Perceptions and Worker Safety Behavior in the Construction Sector

The proposed theoretical framework aims to explain how Managers’ Safety Perceptions and Practices (MSP) influence Workers’ Safety Behaviors (WSB) through three mediating constructs: Workers’ Safety Awareness (WSA), Workers’ Safety Competency (WSC), and Safety Actions (SA). This framework is grounded in empirical safety research and aligns with organizational behavior theories emphasizing the role of leadership and system reinforcement in shaping worker outcomes.

Safety awareness and competency are two key worker-level mechanisms mediating the impact of managerial safety engagement. As argued by Alshehri et al. [44] and Pourmazaherian and Musonda [41], awareness enables workers to recognize risks and take preventive action, while competency ensures they possess the knowledge and skills necessary to carry out tasks safely. These mediators are especially important in Saudi Arabia’s construction industry, which is characterized by a multinational workforce with varying safety backgrounds. Complementing these individual factors, Safety Actions (SA)—such as safety inspections, hazard communication, and incentive systems—operationalize managerial priorities and reinforce safety performance [43,44]. Together, these mediators bridge the gap between managerial perceptions and workers’ behavior, making the model particularly relevant for guiding targeted safety interventions in high-risk, culturally diverse construction environments. Figure 1 summarizes this model, with MSP as the independent variable, WSB as the dependent variable, and WSA, WSC, and SA as the mediating variables.

The conceptual research framework (Figure 1) illustrates the hypothesized relationships among five key constructs: Managers’ Safety Perceptions and Practices (MSP), Workers’ Safety Awareness (WSA), Workers’ Safety Competency (WSC), Safety Action (SA), and Workers’ Safety Behavior (WSB). In this model, MSP is posited to have both a direct effect on WSB and indirect effects mediated through WSA, WSC, and SA.

The direct pathway from MSP to WSB represents the influence of managerial attitudes, decisions, and enforcement of safety practices on workers’ observable safety behavior. Additionally, MSP is hypothesized to influence WSA, WSC, and SA, which in turn contribute to WSB. WSA reflects the extent to which workers are informed and aware of workplace hazards and safety protocols. WSC captures the workers’ practical ability and knowledge to perform tasks safely, while SA refers to the specific actions taken by workers to maintain safety during operations.

Each of the three mediating constructs—WSA, WSC, and SA—is also directly linked to WSB, indicating that improvements in awareness, competency, and safety actions are expected to enhance workers’ safety behavior. This framework allows for testing both direct and indirect relationships between managerial influence and worker outcomes, offering a structured basis for understanding how safety culture is transmitted from management to frontline workers in the construction industry.

Based on the presented literature and the developed research framework, the following hypotheses are developed:

Hypothesis (H1).

Managers’ Safety Perceptions and Practices (MSP) have a positive influence on Workers’ Safety Behaviors (WSB).

Hypothesis (H2).

Managers’ Safety Perceptions and Practices (MSP) have a positive impact on Workers’ Safety Awareness (WSA)

Hypothesis (H3).

Managers’ Safety Perceptions and Practices (MSP) positively influence Workers’ Safety Competency (WSC).

Hypothesis (H4).

Managers’ Safety Perceptions and Practices (MSP) positively impact Safety Actions (SA).

Hypothesis (H5).

Workers’ Safety Awareness (WSA) has a positive effect on Workers’ Safety Behaviors (WSB).

Hypothesis (H6).

Workers’ Safety Competency (WSC) positively influences Workers’ Safety Behaviors (WSB).

Hypothesis (H7).

Safety Actions (SA) have a positive effect on Workers’ Safety Behaviors (WSB).

4. Research Methodology

This section presents a comprehensive overview of the research methodology developed to investigate the influence of Managers’ Safety Perceptions and Practices (MSP) on Workers’ Safety Behavior (WSB) in the construction industry, with Workers’ Safety Awareness (WSA), Workers’ Safety Competency (WSC), and Safety Actions (RSA) serving as mediating variables. The section begins by outlining the design framework and the process of developing the data collection tool. It further explains the characteristics of the study population and the sampling approach employed to recruit suitable respondents. Measures taken to ensure the instrument’s validity and reliability are also discussed. Moreover, this section presents the statistical methods used for data analysis, such as descriptive statistics, normality and multicollinearity assessments, and the application of Structural Equation Modeling (SEM). The section concludes by addressing the ethical protocols followed during the course of the study.

4.1. Research Design and Instruments

This study adopts a cross-sectional research design, utilizing a survey methodology to collect data from construction managers and workers in Saudi Arabia. By employing a quantitative approach, this study ensures objectivity in hypothesis testing, allowing for the identification of causal relationships between variables and the validation or refutation of theoretical frameworks [53]. This approach allows for the systematic collection of numerical data, which is instrumental in addressing complex conceptual issues through structured measurement tools, such as validated questionnaires and standardized scales.

The questionnaire collects data using a 5-point Likert scale, allowing employees to provide feedback on their safety-related perceptions, behaviors, and awareness. The questionnaire is divided into six sections. Section A consists of questions concerning the demographic profile of the respondents, including age, gender, job title, years of experience, education level, and department. The respondents include construction workers, supervisors, and project managers, ensuring a comprehensive representation of different roles within the construction sector.

Section B consists of questions measuring the independent variable, Managers’ Safety Perceptions and Practices (MSP), which reflects managers’ attitudes, commitment, and enforcement of safety policies that influence workers’ adherence to safety practices. Section C includes items related to the dependent variable, Workers’ Safety Behavior (WSB), which assesses workers’ adherence to safety protocols, risk-avoidance behaviors, and proactive engagement in maintaining a safe work environment. Sections D and E contain statements regarding the mediator variables, Workers’ Safety Awareness (WSA) and Workers’ Safety Competency (WSC), which refer to workers’ ability to recognize hazards, understand safety regulations, and apply safety knowledge in their tasks. Lastly, Section F includes statements measuring the mediator variable, Safety Actions (SA), which focuses on structured safety interventions, including preventive, reactive, and supportive measures that reinforce workplace safety culture.

The Managers’ Safety Perceptions and Practices (MSP) is the independent variable of the study. The measurement of Managers’ Safety Perceptions and Practices (MSP) in this study was adapted from studies by Neal and Griffin [54] and Liu et al. [55]. The measurement of the Workers’ Safety Behavior (WSB), the dependent variable of the study, was adapted from the studies of Neal and Griffin [54] and the study of Zhang et al. [56]. The mediator variables in the study, Workers’ Safety Awareness (WSA), adapted from Yılmaz [57] and Kim et al. [58]; Workers’ Safety Competency (WSC), adapted from Pourmazaherian and Musonda [41] and Olokede and Ukpere [59]; and Safety Actions (SA), adapted from studies of Hofmann and Morgeson [60] and Mori et al. [61]. To ensure the suitability and cultural relevance of these measurement instruments within the study context, a systematic cultural adaptation process was undertaken. This involved a thorough review of the wording and phrasing of all items to ensure conceptual equivalence and linguistic clarity, taking into consideration cultural and organizational specificities relevant to the Saudi Arabian construction sector.

Prior to the full-scale distribution, the questionnaire was pilot-tested with a small group of construction professionals to evaluate its clarity, relevance, and overall usability. Feedback from this pilot phase led to minor revisions to improve the question wording and format, enhancing the reliability of the instrument.

4.2. Population and Sampling Strategy

In this study, the target population consists of individuals actively engaged in the construction industry in the Kingdom of Saudi Arabia, including construction workers, site supervisors, safety officers, and project managers. These participants represent various construction environments such as residential, commercial, and infrastructure projects. According to the General Organization for Social Insurance (GOSI), approximately 2.54 million individuals were employed in the Saudi construction sector as of the first quarter of 2023, with the majority being expatriate labor [62]. Accordingly, this study applies the widely accepted formula developed by Krejcie and Morgan [63] to determine an appropriate sample size based on the total population. Based on this population size, a sample of 384 respondents is deemed sufficient to achieve a 95% confidence level with a 5% margin of error [63]. This sample size ensures the study’s findings are representative of the broader construction workforce, thereby enhancing the generalizability and statistical robustness of the analysis.

Given the large-scale and geographically distributed nature of the construction workforce in Saudi Arabia, this study adopts a convenience sampling technique to enable practical and time-efficient data collection. Convenience sampling is particularly suitable for studies involving sizable, heterogeneous, and mobile populations, where random sampling may not be feasible due to logistical and operational constraints [64]. In this study, convenience sampling was selected primarily because Saudi Arabia is a vast country, making it challenging to ensure equal opportunities for every potential participant. Moreover, this study deliberately targeted workers and managers directly involved in site-based construction activities, excluding employees working in office-based or off-site roles to ensure that the data reflected safety behaviors within the actual construction environment. While we acknowledge that convenience sampling may introduce selection bias and limit the generalizability of the findings, this approach enabled us to select participants most relevant to the study objectives. Accordingly, the results should be interpreted with caution, and future research employing more representative sampling techniques is encouraged to enhance external validity.

4.3. Data Collection and Ethical Considerations

The data for this study were collected using a self-administered structured questionnaire distributed directly to construction workers, site supervisors, and project managers across residential, commercial, and infrastructure projects in Saudi Arabia. Distribution occurred during workplace interactions, scheduled site visits, toolbox meetings, and safety briefings. This method was chosen for its practicality, ensuring participants could complete the survey at a convenient time without interfering with ongoing project activities.

Ethical approval for this study was obtained from the relevant academic authority prior to the start of data collection. Participation in the study was entirely voluntary. All participants received an informed consent form explaining the purpose of the research, the procedures involved, and the confidentiality of their responses. The form also clarified that participants had the right to withdraw from the study at any time without any negative consequences. All responses were collected anonymously, and the data were securely stored and used solely for academic research purposes.

4.4. Validity and Reliability

To establish the construct validity and reliability of the research instrument, a pilot test was carried out before the main data collection phase. A sample of 100 participants was used to pre-test the questionnaire. The data from this phase were used exclusively to validate the instrument and were excluded from the final analysis. Construct validity was assessed using Pearson’s correlation coefficient, which evaluates the strength and significance of the relationship between each item and its corresponding construct. This method is recommended for testing the validity of instruments that rely on ordinal or interval scales, such as Likert-type responses [64,65]. Items with high and statistically significant correlations with their respective latent constructs were considered valid indicators.

The internal consistency is measured using Cronbach’s Alpha (α), Composite Reliability (CR), and standardized factor loading value. Cronbach’s Alpha is the most widely accepted indicator for measuring the coefficient, which quantifies the extent to which multiple items measuring a concept are correlated with one another. A Cronbach’s Alpha value of 0.70 or above is generally considered acceptable for social science research [65], indicating that the instrument reliably captures the intended constructs. Cronbach’s Alpha was computed for each key variable.

4.5. Data Analysis Techniques

The responses gathered through the questionnaire were examined using both descriptive and inferential statistical approaches to evaluate the association between the dimensions of Managers’ Safety Perceptions and Practices (MSP), Workers’ Safety Awareness (WSA), Workers’ Safety Competency (WSC), Safety Actions (SA), and Workers’ Safety Behaviors (WSB).

4.5.1. Descriptive Analysis

Descriptive statistics were employed to portray the demographic profile of participants and to provide an overall summary of patterns across the study’s core variables. This includes the computation of central tendency (mean) and variability (standard deviation) measures for individual items and broader constructs derived from the questionnaire. The mean offers insight into the average tendency of responses for each variable, whereas the standard deviation illustrates the extent to which responses deviate from the mean, indicating the level of agreement or divergence among participants.

4.5.2. Normality Analysis

Assessing normality is a foundational step in quantitative analysis, particularly when using parametric tests that assume data follow a normal distribution. Skewness and kurtosis are commonly used to evaluate distribution characteristics. Skewness reflects the asymmetry of the dataset, while kurtosis measures the concentration or flatness of the distribution in comparison to a normal curve. For data to be deemed approximately normal, both skewness and kurtosis values should lie within ±2, a range supported in the literature for moderate sample sizes [55]. Values falling outside this interval may indicate substantial deviations, potentially requiring data transformation or the use of non-parametric alternatives.

4.5.3. Multicollinearity Analysis

To safeguard the accuracy and interpretive clarity of regression-based analyses, particularly those within the structural equation modeling (SEM) framework, multicollinearity must be assessed. This phenomenon occurs when independent variables are strongly correlated with one another, thereby obscuring their individual contributions to the dependent variable and compromising model reliability [44].

To detect multicollinearity, this study examined the Variance Inflation Factor (VIF) and Tolerance scores. The VIF measures how much the variance of a regression coefficient is increased due to multicollinearity, while Tolerance is its reciprocal. As noted by Hair et al. [64], VIF values exceeding 5.0 (or 10.0 under stricter criteria) and Tolerance values under 0.20 signal the presence of problematic multicollinearity. This analysis was applied to all adaptive leadership variables to confirm that multicollinearity does not distort the structural model’s results, thereby strengthening the validity and credibility of the findings.

4.5.4. Structural Equation Modeling (SEM)

To test the study’s hypotheses and assess the conceptual framework, Partial Least Squares Structural Equation Modeling (PLS-SEM) was utilized. This method is well-suited for evaluating models with complex interrelations among latent variables and observed indicators. The analysis was conducted using SmartPLS version 4.0, which facilitates the assessment of both the measurement and structural components of the model. This statistical approach enables a comprehensive examination of how specific adaptive leadership traits, such as emotional intelligence, flexibility, and collaborative capacity, impact the effectiveness of crisis management functions, including preparedness, response, recovery, and organizational learning.

5. Results and Discussion

This section presents the findings of the data analysis conducted to examine the relationships between Managers’ Safety Perceptions and Practices (MSP), Workers’ Safety Behaviors (WSB), and the mediating roles of Workers’ Safety Awareness (WSA), Workers’ Safety Competency (WSC), and Safety Actions (SA) in the construction sector in Saudi Arabia. The section begins by presenting the response rate from the distributed questionnaires, followed by descriptive statistics for the key study variables. This provides a general overview of participants’ perceptions regarding managerial safety practices and their corresponding safety-related behaviors and competencies on construction sites. The subsequent sections assess the measurement model to verify the internal consistency reliability, convergent validity, and discriminant validity of each construct and its indicators. Finally, the structural model is tested to evaluate the hypothesized direct and indirect (mediated) relationships among MSP, WSB, WSA, WSC, and SA, offering empirical insights into how managerial perceptions and practices shape safety outcomes among workers in the Saudi construction industry.

5.1. Response Rate

A total of 384 questionnaires were distributed to construction professionals, including workers, supervisors, and project managers, across various projects in Saudi Arabia, utilizing a convenience sampling technique. Out of these, 352 completed questionnaires were returned and deemed valid for analysis, resulting in a response rate of approximately 91.7%. This exceeds the commonly accepted benchmark for survey-based research [44], demonstrating that the collected data is both adequate in quantity and reliable in quality for proceeding with analysis using the PLS-SEM approach.

5.2. Demographic Data of the Respondents

To develop a clear understanding of the sample population, demographic information was collected through the questionnaire. This section outlines the main characteristics of the respondents, such as gender, age group, level of education, and length of work experience. A comprehensive summary of these demographic details is presented in

Table 1. Respondent demographic profile.

No.	Respondent Profile	Category	Frequency	Percentage (%)
1	Gender	Male	310	88.1%
		Female	42	11.9%
		Total	352	100.0%
2	Age	20–30 years old	82	23.3%
		31–40 years old	134	38.1%
		41–50 years old	84	23.9%
		Above 50 years old	52	14.8%
		Total	352	100.0%
3	Qualification/Education Level	Diploma	36	10.2%
		Bachelors	168	47.7%
		Masters	110	31.3%
		PhD/DBA	38	10.8%
		Total	352	100.0%
4	Length of Service	Below 1 year	34	9.7%
		1–5 years	141	40.1%
		5–10 years	98	27.8%
		Above 10 years	79	22.4%
		Total	352	100.0%

.

The majority of the participants were male (88.1%), with females comprising only 11.9% of the sample. It is important to acknowledge that the sample included a relatively low proportion of female respondents (11.9%), which reflects both the broader gender imbalance in the Saudi Arabian construction sector and the cultural and regulatory context that shapes workforce composition. In Saudi Arabia, construction remains a traditionally male-dominated industry, with limited female participation due to cultural norms, occupational segregation, and the nature of site-based construction activities. While this reflects the current workforce reality, it limits the ability to draw comprehensive conclusions regarding gender-related differences in safety perceptions. Future studies are encouraged to incorporate more targeted approaches to include female construction employees, where possible, to explore this dimension more thoroughly. The respondents were fairly well-distributed across different age groups. The largest segment fell within the 31–40 years age bracket (38.1%), followed by those aged 41–50 years (23.9%) and 20–30 years (23.3%). A smaller percentage (14.8%) was above 50 years of age. These figures suggest that the workforce is composed primarily of experienced mid-career individuals, with a balance between younger and older workers.

In terms of educational attainment, nearly half of the respondents held a bachelor’s degree (47.7%), while 31.3% had completed a master’s degree. Workers with a diploma accounted for 10.2%, and 10.8% had earned a PhD or DBA. Regarding work experience, 40.1% of participants had been employed in the construction sector for 1–5 years, followed by 27.8% with 5–10 years of experience. Those with over 10 years of service represented 22.4%, while only 9.7% had been employed for less than a year. This indicates that the majority of the respondents were not novices but had substantial field experience, which is vital when examining behavioral outcomes such as safety compliance and engagement with safety practices.

5.3. Reliability and Validity Results

The PLS-SEM analysis was conducted in order to assess the reliability and validity of the observed indicators used to reflect the latent constructs. Internal consistency was examined through Cronbach’s Alpha and Composite Reliability (CR), while convergent validity was determined by the Average Variance Extracted (AVE). Furthermore, to confirm that each construct is conceptually distinct, discriminant validity was evaluated using the Fornell–Larcker criterion and cross-loadings [64]. This phase ensures that the measurement instruments are both psychometrically robust and theoretically aligned. The results for reliability and validity are presented in

Table 2. Reliability and validity analysis.

Construct	Items (Indicators)	Indicators of Reliability	Reliability		Validity
		Factor Loading >0.70	Compost Reliability CR >0.70	Cronbach’s Alpha >0.70	Convergent Validity AVE >0.50
Managers’ Safety Perceptions and Practices (MSP)	MSP1	0.829	0.934	0.911	0.738
	MSP2	0.875
	MSP3	0.867
	MSP4	0.867
	MSP5	0.856
Workers’ Safety Awareness (WSA)	WSA1	0.803	0.908	0.874	0.664
	WSA2	0.816
	WSA3	0.812
	WSA4	0.837
	WSA5	0.806
Workers’ Safety Competency (WSC)	WSC1	0.839	0.948	0.934	0.751
	WSC2	0.888
	WSC3	0.880
	WSC4	0.848
	WSC5	0.862
	WSC6	0.883
Safety Actions (SA)	SA1	0.843	0.938	0.918	0.753
	SA2	0.875
	SA3	0.884
	SA4	0.828
	SA5	0.906
Workers’ Safety Behavior (WSB)	WSB1	0.855	0.934	0.918	0.670
	WSB2	0.826
	WSB3	0.729
	WSB4	0.794
	WSB5	0.852
	WSB6	0.831
	WSB7	0.836

. These findings collectively affirm that the constructs in the model were measured with precision, consistency, and theoretical alignment, providing a solid basis for the structural modeling phase to follow.

Indicator Reliability: Indicator reliability was first assessed to ensure that each item sufficiently reflects its underlying latent variable. Following the standard thresholds suggested by Hair et al. [64], outer loadings of 0.70 or higher are considered indicative of strong item reliability. As shown in Table 2, all indicators exceeded this threshold, with loadings ranging from 0.729 to 0.906 across all constructs. These results confirm that the individual items reliably measure their intended constructs. For instance, the items measuring MSP (ranging from 0.829 to 0.875) and WSC (ranging from 0.839 to 0.888) demonstrated particularly high loadings, underscoring their strength in capturing perceptions of managerial safety practices and workers’ safety-related competencies, respectively.

Internal Consistency Reliability: To evaluate the consistency of the items within each construct, both Composite Reliability (CR) and Cronbach’s Alpha were computed. Composite Reliability was prioritized as it accounts for the individual loading of each item, offering a more precise estimate of reliability [64]. All five constructs demonstrated CR values well above the recommended cutoff of 0.70, with scores ranging from 0.908 to 0.948. This indicates that the sets of items within each construct are internally consistent and cohesively measure the same underlying concept. Similarly, Cronbach’s Alpha values ranged from 0.874 (WSA) to 0.934 (WSC), further supporting the high internal consistency of the constructs. These results affirm the reliability of the scales used to measure both managerial and worker-level safety constructs within the context of Saudi construction projects.

Convergent Validity: Convergent validity was assessed through the Average Variance Extracted (AVE), which indicates the extent to which the items of a given construct share common variance. According to the criteria set forth by Hair et al. [64], AVE values should exceed 0.50 to be considered acceptable. All constructs met this requirement, with AVE scores ranging from 0.664 (WSA) to 0.753 (SA). These results suggest that each construct captures a substantial portion of the variance in its respective indicators. Notably, the constructs Safety Actions and Workers’ Safety Competency exhibited high AVE values (0.753 and 0.751, respectively), indicating a strong degree of item convergence around these core safety behaviors and competencies.

5.4. Normality and Multi-Collinearity Test Results

In accordance with the guidelines proposed by Hair et al. [66], skewness values ranging between ±3 and kurtosis values within ±10 are considered acceptable for SEM analysis. As shown in

Table 3. The assessment of normality.

Variable	Skewness	Kurtosis
Managers’ Safety Perceptions and Practices (MSP)	−0.622	−0.768
Workers’ Safety Behavior (WSB)	−0.701	0.135
Workers’ Safety Awareness (WSA)	−1.020	−0.925
Workers’ Safety Competency (WSC)	−0.785	0.518
Safety Actions (SA)	−0.617	−0.063

, all items met these criteria, confirming that the dataset is sufficiently normal and suitable for further analysis using the PLS-SEM technique. Also, Figure 2 shows the normal distribution based on the skewness.

The figure illustrates the distribution patterns of the five core study variables—Managers’ Safety Perceptions and Practices (MSP), Workers’ Safety Behavior (WSB), Workers’ Safety Awareness (WSA), Workers’ Safety Competency (WSC), and Safety Actions (SA), based on their respective skewness values. All variables exhibit moderate skewness values, falling within the acceptable range of −1 to +1, suggesting that the data are approximately normally distributed. Notably, WSA displays the most pronounced negative skew (−1.020), indicating a tendency for responses to cluster toward higher agreement levels. Conversely, WSC and WSB show slight left skewness, but remain well within acceptable bounds, suggesting symmetry in distribution. MSP and SA are the least skewed, reflecting a relatively balanced response pattern. The bell-shaped curves further confirm that none of the variables deviate significantly from normality, supporting the appropriateness of applying parametric statistical techniques such as PLS-SEM in the subsequent analysis.

Table 4. Tolerance and (VIF) results.

Variable	Tolerance	VIF
Managers’ Safety Perceptions and Practices (MSP)	0.711	3.15
Workers’ Safety Awareness (WSA)	0.639	2.54
Workers’ Safety Competency (WSC)	0.615	2.87
Safety Actions (SA)	0.561	2.15

presents the results of the multicollinearity test. The analysis includes both Tolerance and Variance Inflation Factor (VIF) values to evaluate whether the constructs exhibit any problematic intercorrelations that might distort the structural model estimates. According to Hair et al. [66], tolerance values greater than 0.20 and VIF values below 5.0 are indicative of acceptable levels of collinearity. As shown in the table, all variables meet these recommended thresholds. MSP recorded a tolerance value of 0.711 and a VIF of 3.15, while WSA had a tolerance of 0.639 and a VIF of 2.54. WSC also fell within the acceptable range, with a tolerance of 0.615 and a VIF of 2.87. Lastly, SA had the lowest VIF at 2.15 and a corresponding tolerance of 0.561. These results confirm that multicollinearity is not a concern in this model, as none of the variables approach critical values that would compromise regression estimates.

5.5. Assessment of Descriptive Analysis

This section presents the descriptive statistics for all constructs measured in this study, specifically reporting the mean and standard deviation for each item included in the research instrument. These measures provide a useful overview of how respondents perceive key safety-related aspects in the workplace and help assess the quality of the collected data before conducting more advanced statistical analyses such as Structural Equation Modeling (SEM).

5.5.1. Assessment of Managers’ Safety Perceptions and Practices (MSP)

This construct was measured through several items that reflect different managerial roles in fostering a safe working environment. The descriptive results presented in

Table 5. Managers’ safety perceptions and practices (MSP).

No.	Item	Mean	Std. Deviation	Relative Importance
MSP1	Supervisor’s emphasis on safety contributes to improved safety behavior among workers.	4.33	0.741	High
MSP2	Management support for safety training encourages adherence to safe work practices.	4.25	0.585	High
MSP3	Strict enforcement of safety policies by managers leads to increased compliance with safety rules.	4.11	0.693	High
MSP4	Timely and appropriate management response to safety concerns encourages reporting and adherence to safety protocols.	4.18	0.788	High
MSP5	A strong safety culture, promoted by management, leads to a greater prioritization of safe behaviors among employees.	3.86	0.568	High

reflect respondents’ strong agreement on the importance of Managers’ Safety Perceptions and Practices (MSP) in influencing safety behaviors among construction workers. All five items scored within the “High” relative importance category, with mean values ranging from 3.86 to 4.33. The highest-rated item, “Supervisor emphasis on safety contributes to improved safety behavior among workers” (M = 4.33, SD = 0.741), underscores the critical role that direct supervisory involvement plays in reinforcing safe conduct on-site. Similarly, strong support was observed for the role of managerial backing in safety training (M = 4.25), which indicates that when managers actively promote and invest in training, workers are more likely to comply with safety procedures and standards.

Further, items related to policy enforcement and responsiveness also received high agreement. Respondents rated “Strict enforcement of safety policies” (M = 4.11) and “Timely and appropriate response to safety concerns” (M = 4.18) as significant contributors to worker compliance and safety adherence. These findings suggest that managerial consistency and follow-through are perceived as key motivators for safe behavior. While the item “A strong safety culture promoted by management” had the lowest mean score (M = 3.86), it still reflected a high level of importance, indicating that although workers value cultural reinforcement of safety, it may not always be as visible or consistently practiced. Overall, the analysis highlights that proactive managerial engagement—through supervision, policy enforcement, training, and communication—is viewed as fundamental in shaping a safe working environment in the Saudi construction sector.

5.5.2. Assessment of Workers’ Safety Behavior (WSB)

The descriptive analysis of Workers’ Safety Behavior (WSB), given in

Table 6. Workers’ safety behavior (WSB).

No.	Item	Mean	Std. Deviation	Relative Importance
WSB1	The required personal protective equipment (PPE) is consistently worn during all tasks.	4.11	1.011	High
WSB2	All safety procedures are strictly followed during work activities.	4.31	0.635	High
WSB3	Unsafe conditions or hazards are reported to the supervisor immediately.	4.17	0.789	High
WSB4	Coworkers are encouraged to adhere to safety protocols.	3.85	0.812	High
WSB5	Participation in workplace safety training programs is maintained.	3.74	0.912	High
WSB6	Volunteering for safety initiatives or committees is demonstrated in the workplace.	4.19	1.021	High
WSB7	Accountability for maintaining safety standards during work is observed.	3.69	0.789	High

, reveals consistently high levels of safety engagement among construction workers, as reflected in the mean scores across all seven items. The highest mean (4.31) corresponds to strict adherence to safety procedures during work activities, suggesting that compliance with formal safety protocols is strongly embedded within the workforce. This is closely followed by the consistent use of personal protective equipment (PPE), with a mean of 4.11, indicating that workers recognize the importance of protective gear in reducing injury risks. Additionally, the prompt reporting of unsafe conditions (mean = 4.17) highlights a proactive safety culture, where hazard communication is practiced regularly, aligning with good safety management principles.

Other items also demonstrate relatively high levels of perceived safety behavior. Encouraging coworkers to follow safety protocols (mean = 3.85) and maintaining participation in safety training programs (mean = 3.74) reflect a shared sense of responsibility and continued learning. Interestingly, volunteering for safety initiatives (mean = 4.19) received a high score despite being a discretionary behavior, which indicates a level of intrinsic motivation among some workers to support safety beyond mandatory actions. However, accountability for safety (mean = 3.69) scored slightly lower, suggesting that while workers largely engage in safe practices, there may be room to strengthen individual responsibility and ownership of safety outcomes. Overall, the results reflect a generally positive safety behavior trend, with opportunities for reinforcing peer influence and accountability mechanisms.

5.5.3. Assessment of Workers’ Safety Awareness (WSA)

The results summarized in

Table 7. Workers’ safety awareness (WSA).

No.	Item	Mean	Std. Deviation	Relative Importance
WSA1	The required personal protective equipment (PPE) is consistently worn during tasks.	3.85	1.011	High
WSA2	All safety procedures are strictly followed while performing work activities.	4.01	0.635	High
WSA3	Unsafe conditions or hazards are reported to the supervisor without delay.	4.22	0.789	High
WSA4	Participation in workplace safety training programs is actively maintained.	3.96	0.812	High
WSA5	Volunteering for safety initiatives or committees occurs within the workplace.	3.78	1.012	High

provide an overview of workers’ perceived safety awareness in the Saudi construction sector. The overall findings suggest a high level of awareness, as reflected in the consistently strong mean values across all five items. The highest mean score (M = 4.22, SD = 0.789) was recorded for the item stating that “unsafe conditions or hazards are reported to the supervisor without delay,” indicating that hazard recognition and prompt communication are well established among the workforce. This result highlights an encouraging level of responsiveness and a culture where safety concerns are likely to be taken seriously and addressed swiftly.

Additionally, the item concerning the strict following of safety procedures during work activities also scored highly (M = 4.01, SD = 0.635), suggesting that workers not only understand but also apply procedural knowledge in practice. Meanwhile, consistent use of personal protective equipment (PPE) received a slightly lower, but still high, mean score (M = 3.85, SD = 1.011), pointing to generally positive compliance, albeit with some variation across respondents. Notably, participation in safety training (M = 3.96) and volunteering for safety initiatives (M = 3.78) further reflect strong engagement with organizational safety culture. However, the higher standard deviation in these two items may signal varying levels of opportunity or motivation to participate in such programs. Overall, the results indicate a solid foundation of safety awareness, with room for targeted interventions to enhance consistency and expand proactive engagement across all employees.

5.5.4. Assessment of Workers’ Safety Competency (WSC)

The descriptive statistics in

Table 8. Workers’ safety competency (WSC).

No.	Item	Mean	Std. Deviation	Relative Importance
WSC1	Sufficient training has been provided to perform job tasks safely.	4.12	0.662	High
WSC2	Proper use of personal protective equipment (PPE) is well understood.	4.16	0.863	High
WSC3	Confidence is demonstrated in handling emergency situations at work.	3.88	0.786	High
WSC4	Safety training has enhanced the ability to assess workplace risks.	3.83	0.963	High
WSC5	Machinery and equipment are operated in a safe manner.	3.91	0.778	High
WSC6	Correct procedures for hazardous work tasks are well understood.	4.08	1.25	High

provide a comprehensive overview of Workers’ Safety Competency (WSC) among construction employees in Saudi Arabia. All six items received high mean scores, ranging from 3.83 to 4.16, indicating a generally strong perception of competency among the respondents. The highest-rated item, “Proper use of personal protective equipment (PPE) is well understood” (M = 4.16, SD = 0.863), suggests that most workers are confident in their ability to use PPE effectively—an essential aspect of daily construction safety. Similarly, the item “Sufficient training has been provided to perform job tasks safely” also scored highly (M = 4.12, SD = 0.662), reflecting a positive assessment of initial and ongoing safety training initiatives.

Other items, such as “Confidence is demonstrated in handling emergency situations at work” (M = 3.88, SD = 0.786) and “Safety training has enhanced the ability to assess workplace risks” (M = 3.83, SD = 0.963), while still rated as high in importance, showed slightly lower mean scores. This may indicate variability in practical exposure to emergency situations or inconsistency in the quality or retention of training content. Notably, “Correct procedures for hazardous work tasks are well understood” received a strong mean (M = 4.08) but had the highest standard deviation (SD = 1.25), suggesting a wider disparity in responses, possibly due to differences in job roles, training access, or individual experience. Overall, the results demonstrate a robust level of perceived competency, but also highlight the importance of reinforcing advanced hazard-specific training and ensuring consistency across the workforce to close any remaining gaps in safety preparedness.

5.5.5. Assessment of Safety Actions (SA)

The data presented in

Table 9. Safety actions (SA).

No.	Item	Mean	Std. Deviation	Relative Importance
SA1	Regular safety inspections and audits are conducted by the organization.	3.77	1.114	High
SA2	Safety drills and emergency response exercises are held frequently.	4.42	1.025	High
SA3	Corrective actions are promptly taken by management when accidents occur.	4.23	0.963	High
SA4	Incentives or rewards are provided for adherence to safety protocols.	3.98	1.032	High
SA5	Safety warning signs and hazard communication materials are clearly visible in the workplace.	4.36	0.789	High

reflect respondents’ perceptions of Safety Actions (SA) implemented in their construction workplaces. Overall, the results demonstrate a high level of agreement across all five items, with mean scores ranging from 3.77 to 4.42, indicating that safety actions are generally perceived as actively practiced and institutionally supported. Notably, the highest mean score (M = 4.42, SD = 1.025) was recorded for the item “Safety drills and emergency response exercises are held frequently,” suggesting that organizations are placing significant emphasis on preparing workers for emergency situations—an essential component of reactive and preparedness-based safety strategies.

Similarly, high mean values were observed for “Safety warning signs and hazard communication materials are clearly visible in the workplace” (M = 4.36) and “Corrective actions are promptly taken by management when accidents occur” (M = 4.23), indicating that visible communication and timely managerial responses are critical components of the safety culture in the sampled projects. While still rated as high in importance, the item “Regular safety inspections and audits are conducted” had the lowest mean (M = 3.77), implying a potential area for improvement. Variability in responses, as shown by the standard deviations (ranging from 0.789 to 1.114), also suggests differing implementation levels across sites.

5.6. Hypotheses Testing

5.6.1. Direct Hypotheses

To address the primary objectives of the research and answer the formulated research questions, the hypothesized direct relationships were examined using structural equation modeling. This analysis was carried out in SmartPLS, relying on the estimation of path coefficients, accompanied by standard errors, t-values, and p-values, which were calculated through a bootstrapping procedure with 5000 iterations. This stage of the structural model assessment provides empirical insight into the direction, strength, and statistical significance of the proposed direct pathways. The findings help clarify the role of managerial safety practices in shaping various worker-related safety outcomes within the construction industry. A detailed summary of the results, including path coefficients and significance levels for each direct hypothesis, is presented in

Table 10. Structural model assessment for the direct effect hypotheses.

	Path Coefficient	Standard Deviation	T Statistics	p Values **	Decision
H1	0.049	0.051	0.957	0.338	Not Supported
H2	0.686	0.032	21.644	0.000	Supported
H3	0.458	0.048	9.437	0.000	Supported
H4	0.520	0.046	11.259	0.000	Supported
H5	0.121	0.044	2.733	0.006	Supported
H6	0.764	0.038	20.003	0.000	Supported
H7	0.057	0.042	1.360	0.174	Not Supported

Notes: Significant level at ** = p < 0.05.

.

H1. 

Managers’ Safety Perceptions and Practices (MSP) have a positive influence on Workers’ Safety Behaviors (WSB).

The direct path from MSP to WSB was not statistically significant (β = 0.049, t = 0.957, p = 0.338), indicating that managerial safety perceptions and practices do not have a significant direct effect on workers’ safety behavior. This suggests that while managers may influence safety outcomes, their impact on behavior is likely mediated by other factors such as awareness, competence, or proactive actions. As a result, H1 is not supported. This finding aligns with earlier research by Liu et al. [55] and Kim et al. [58], which suggests that the impact of managerial safety commitment is often mediated by internal worker factors such as awareness and competency. This finding highlights the complexity of safety behavior, which may not be directly shaped by managerial attitudes alone but rather through indirect pathways. While the non-significant direct effect of Managers’ Safety Perceptions and Practices (MSP) on Workers’ Safety Behavior (WSB) may suggest a full mediation mechanism through the identified mediators, alternative explanations should also be considered. These include potential measurement limitations associated with the use of self-reported data, which may be influenced by social desirability bias, as well as the omission of other relevant variables, such as organizational culture, peer influence, or external regulatory pressures, which could independently affect workers’ safety behavior.

H2. 

Managers’ Safety Perceptions and Practices (MSP) have a positive impact on Workers’ Safety Awareness (WSA)

The analysis revealed a strong and statistically significant effect of MSP on WSA (β = 0.686, t = 21.644, p < 0.001). This suggests that positive managerial safety practices—such as clear communication, visible commitment, and safety leadership—are highly effective in raising workers’ awareness of safety issues. Therefore, H2 is supported, reinforcing the idea that awareness is largely shaped by the tone and practices set by management. These findings reinforce the view of Al-Bayati et al. [28] and Amirah et al. [43], who argue that safety actions must be coupled with awareness and competency-building to produce consistent behavioral change.

H3. 

Managers’ Safety Perceptions and Practices (MSP) positively influence Workers’ Safety Competency (WSC).

A significant positive relationship was also found between MSP and WSC (β = 0.458, t = 9.437, p < 0.001), supporting H3. This result implies that managerial behaviors, such as providing safety training, guidance, and technical support, significantly enhance workers’ self-perceived competence in managing occupational risks and performing tasks safely. This supports the work of Pourmazaherian and Musonda [41,48], who demonstrated that competence is a primary driver of safety performance, especially when combined with organizational support.

H4. 

Managers’ Safety Perceptions and Practices (MSP) positively impact Safety Actions (SA).

The direct path from MSP to SA was statistically significant (β = 0.520, t = 11.259, p < 0.001), thus supporting H4. This suggests that managers play a crucial role in motivating workers to engage in proactive safety behaviors, such as reporting hazards or participating in safety drills. When safety is visibly prioritized by management, it appears to foster a more action-oriented safety culture among workers. These findings reinforce the view of Al-Bayati et al. [28] and Amirah et al. [43], who argue that safety actions must be coupled with awareness and competency-building to produce consistent behavioral change.

H5. 

Workers’ Safety Awareness (WSA) has a positive effect on Workers’ Safety Behaviors (WSB).

The path from WSA to WSB was also significant (β = 0.121, t = 2.733, p = 0.006), supporting H5. This indicates that increased awareness of risks and safety procedures contributes positively to safer behavioral practices. Although the effect size is smaller compared to the other relationships, it nonetheless confirms that awareness plays an important role in shaping worker behavior.

H6. 

Workers’ Safety Competency (WSC) positively influences Workers’ Safety Behaviors (WSB)

The strongest direct effect on WSB was observed from WSC (β = 0.764, t = 20.003, p < 0.001), providing robust support for H6. This finding underscores that safety behavior is most strongly influenced by workers’ own perceptions of their skills, capabilities, and confidence in handling workplace hazards. This pathway highlights the need for continuous training and competence development as a critical component of behavioral safety strategies.

H7. 

Safety Actions (SA) have a positive effect on Workers’ Safety Behaviors (WSB).

Although the path from SA to WSB showed a positive coefficient (β = 0.057), the relationship was not statistically significant (t = 1.360, p = 0.174), leading to the rejection of H7. This suggests that while safety actions are a visible part of safety culture, their direct influence on behavior may be limited unless reinforced by deeper cognitive factors such as awareness and competency. Alternatively, this result could imply that safety actions function more effectively as mediators rather than direct predictors of behavior.

Overall, the analysis confirms the significant influence of MSP on WSA, WSC, and SA, and highlights that WSC, in particular, is a dominant predictor of WSB. The lack of a direct effect from MSP to WSB suggests the presence of full or partial mediation, which will be further explored in the mediation analysis. These findings provide important implications for construction safety management by emphasizing the critical role of indirect pathways in translating managerial practices into frontline safety behavior.

5.6.2. Mediating Hypotheses

To examine the mediating mechanisms through which Managers’ Safety Perceptions and Practices (MSP) influence Workers’ Safety Behavior (WSB), this study tested three indirect effect hypotheses corresponding to the parallel mediators proposed in the conceptual model: Workers’ Safety Awareness (WSA), Workers’ Safety Competency (WSC), and Safety Actions (SA). This approach was adopted to avoid the overlapping influence of the mediators and to accurately identify the unique contribution of each mediating variable in the pathway from MSP to WSB. The results of the structural model assessment for the mediating hypotheses are summarized in

Table 11. Structural model assessment for the mediating hypotheses.

	Path Coefficient	Standard Deviation	T Statistics	p Values **	Decision
H8	0.291	0.053	5.511	0.000	Supported
H9	0.381	0.043	8.802	0.000	Supported
H10	0.268	0.043	6.223	0.000	Supported

Notes: Significant level at ** = p < 0.05.

.

H8. 

Workers’ Safety Awareness (WSA) mediates the relationship between Managers’ Safety Perceptions and Practices (MSP) and Workers’ Safety Behaviors (WSB).

The results presented in the table indicate that Safety Actions (SA) significantly mediate the relationship between Managers’ Safety Perceptions and Practices (MSP) and Workers’ Safety Behavior (WSB). The indirect effect coefficient was 0.268, with a t-value of 6.223 and a p-value of 0.000, confirming strong statistical significance at the 0.01 level. This finding aligns with the observations of Mosly and Makki [6] and Yılmaz [57], who noted that increased safety awareness leads to greater adherence to safety procedures, particularly when management models safety engagement. Similarly, Alsulami et al. [7] emphasized the role of managerial influence on safety-related perceptions and communication as key determinants of awareness in high-risk environments like construction.

H9: 

Workers’ Safety Competency (WSC) mediates the relationship between Managers’ Safety Perceptions and Practices (MSP) and Workers’ Safety Behaviors (WSB).

Workers’ Safety Competency (WSC) also demonstrated a significant mediating effect, with a higher indirect effect of 0.381 (t = 8.802, p < 0.001). This suggests that competency serves as a particularly strong behavioral pathway. Workers who perceive themselves as capable and trained are more likely to engage in safe practices. Among the three mediators tested, WSC exhibited the strongest mediating influence, underscoring the central role of skill development and technical preparedness in promoting safe behavior in construction environments. This outcome is consistent with previous studies by Pourmazaherian and Musonda [41] and Neal and Griffin [54], which found that competency significantly enhances workers’ ability to assess risks and act safely under pressure.

H10. 

Safety Actions (SA) mediate the relationship between Managers’ Safety Perceptions and Practices (MSP) and Workers’ Safety Behaviors (WSB).

Safety Actions (SA) was likewise found to significantly mediate the relationship between MSP and WSB, with an indirect effect of 0.268 (t = 6.223, p < 0.001). The importance of such actions is supported by Al-Bayati et al. [28] and Alqahtani et al. [13]. This finding supports the idea that managerial emphasis on active safety participation—such as encouraging hazard reporting and engaging in preventive measures—can effectively motivate workers to adopt safe behavioral practices. Although its indirect effect is slightly lower than that of WSA and WSC, SA still plays a meaningful and statistically significant mediating role.

When comparing the three mediators, Workers’ Safety Competency (WSC) emerged as the most influential pathway, followed by Workers’ Safety Awareness (WSA) and then Safety Actions (SA). This ordering suggests that while all three mechanisms are important, the behavioral impact of managerial practices is most strongly realized when they contribute to enhancing workers’ capabilities. Awareness and proactive actions are also essential, but may be less impactful without a foundation of competency.

These results emphasize the multidimensional nature of safety behavior and confirm that effective safety leadership must simultaneously foster knowledge, skills, and active engagement. The findings also highlight the need for integrated safety programs that address all three dimensions—awareness, competency, and action—to achieve sustained behavioral change in the construction sector. In conclusion, the mediation results provide robust empirical support for the theoretical model and reinforce the importance of indirect mechanisms in translating managerial safety perceptions into effective safety behavior on-site. These insights offer valuable implications for construction safety policy, training design, and leadership development aimed at improving safety outcomes in high-risk work environments.

6. Limitations of the Study

This study offers important insights into the role of managerial perceptions in shaping safety practices and behaviors within the construction industry in Saudi Arabia. However, its scope is naturally limited in ways that should be considered when interpreting the findings. The research was conducted exclusively within the Saudi construction sector, which has unique cultural, regulatory, and operational characteristics. It was limited to the construction industry, which has a high requirement for work safety due to its high-risk nature and complex work environments. As such, while the results provide valuable guidance within this context, they may not be directly transferable to all national or industry settings where workplace dynamics and safety cultures differ.

Nevertheless, many of the behavioral mechanisms and managerial influences identified in this study—such as the impact of safety awareness and competency on safety behavior—are likely to be relevant in neighboring Gulf countries such as the UAE, Qatar, and Kuwait, which share similar construction practices, labor structures, and regulatory frameworks. In addition, while the study presents a meaningful behavioral model linking managerial intention, employee perception, and safety outcomes, it does not account for all external pressures that may influence safety behavior, such as economic constraints, project deadlines, or subcontractor practices. Moreover, this study did not account for certain organizational and project-specific factors such as organization size, project type (e.g., infrastructure versus residential), and the presence of third-party safety audits, which may influence safety behaviors and should be considered in future research.

The data were also self-reported, which, despite mitigation efforts, may reflect subjective perceptions more than observed actions. In addition, the cross-sectional design of this study provides valuable insights into the associations between the examined variables; it inherently limits the ability to make definitive causal inferences. Future research utilizing longitudinal or experimental approaches is encouraged to further explore and substantiate these relationships. These limitations highlight the need for future research to validate the model across different sectors, regions, and the use of mixed methods to build a more comprehensive understanding of safety behavior in diverse construction settings.

7. Conclusions

This study examined the influence of managers’ safety perceptions and practices (MSP) on construction workers’ safety behaviors (WSB) in Saudi Arabia, with particular focus on the mediating roles of workers’ safety awareness (WSA), safety competency (WSC), and safety actions (SA). The study adopted a quantitative research approach, using a structured questionnaire distributed to a diverse sample of construction professionals across multiple sites in Saudi Arabia. This resulted in 183 valid responses collected through a non-probability convenience sampling approach. To ensure the instrument’s robustness, its validity and reliability were established through expert evaluation, analysis of factor loadings, Average Variance Extracted (AVE), Composite Reliability (CR), and Cronbach’s Alpha. The dataset was subjected to descriptive statistical analysis, with assessments of normality based on skewness and kurtosis, and multicollinearity was evaluated using Variance Inflation Factors (VIF), all indicating acceptable thresholds. Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed to examine the structural relationships among the study variables. The principal findings are outlined below:

• The direct path from MSP to Workers’ Safety Behavior (WSB) was found to be statistically insignificant, indicating that managerial attitudes and practices alone do not directly shape on-site worker behaviors.
• MSP was found to have strong, positive, and statistically significant effects on Workers’ Safety Awareness (WSA), Workers’ Safety Competency (WSC), and Safety Actions (SA).
• Workers’ Safety Competency (WSC) showed the strongest direct impact on Workers’ Safety Behavior (WSB), highlighting the importance of technical knowledge and skills in shaping safe work practices.
• Workers’ Safety Awareness (WSA) also showed a significant positive effect on WSB, though the impact was smaller. This indicates that cognitive understanding of hazards contributes to safe behavior but may require reinforcement through skill development.
• In contrast, Safety Actions (SA) did not have a statistically significant direct influence on WSB, suggesting that visible safety practices such as inspections and drills may not be sufficient unless workers internalize safety values.
• Workers’ Safety Awareness (WSA) significantly mediated the relationship between MSP and WSB, indicating that managerial commitment enhances behavioral safety by first shaping workers’ cognitive understanding of hazards and protocols.
• Workers’ Safety Competency (WSC) demonstrated the strongest mediating effect, reinforcing its central role in enabling safe behavior through technical proficiency and confidence.
• Additionally, Safety Actions (SA) also showed a statistically significant indirect effect, highlighting that visible safety initiatives—such as drills, audits, and hazard signage—serve as motivational and structural reinforcements when embedded within a strong managerial safety culture.

In summary, this study highlights the critical role of managerial perceptions in shaping safer work environments and offers practical guidance for improving safety culture and outcomes across the Saudi construction sector.