Investigating the Underpinning Criteria of Employees’ Social Sustainability and Their Impact on Job Satisfaction in the U.A.E. Construction Sector

Abstract

The construction sector holds a paramount position in the economic landscape of any country, serving as its foundational pillar. This sector, characterized by its diverse and dynamic environment, is crucial in job creation across various domains, including transportation, real estate, manufacturing, trade, warehousing, wholesale, and leasing services. Employing about one quarter of the global workforce, its significance is undeniable. Despite its pivotal role, the construction sector grapples with significant mental health and social sustainability challenges. Reports in recent years indicate that approximately one in four individuals worldwide experiences various forms of mental disorders. A study by the Global Burden of Disease in 2010 revealed that around 400 million people globally suffer from depression with projections suggesting that depression could be the leading cause of employee mortality by 2030. This underscores the critical need to address mental health and well-being issues in this sector. While the existing literature has presented numerous studies and reliable scales linking employee mental health and well-being to factors such as job satisfaction, productivity, absenteeism, and low turnover rates, these studies often operate in isolation, concentrating on specific aspects of mental health. This study views mental health and well-being as essential parts of defining social sustainability as a comprehensive concept. Moreover, limited research has been conducted to assist organizations in decision making and facilitate efforts to enhance the social sustainability of employees in the construction sector, highlighting a noticeable research gap. To address this gap, our study adopted a comprehensive mixed-methods approach, incorporating semi-structured interviews, surveys, and structural equation modeling to identify the underpinning criteria that define the social sustainability of employees. This study accordingly incorporated the identified criteria to evaluate the relationship and impact of these factors on employees’ job satisfaction, ultimately contributing to the assurance of social sustainability for employees within the construction sector in the UAE. This holistic approach seeks to establish the intricate relationship between employees’ job satisfaction and their mental health, providing valuable insights for guiding organizational decisions and fostering improvements in employee social sustainability in the construction sector generally and the UAE construction sector in particular.

1. Introduction

The construction sector is regarded as the backbone of the economy of most countries, with the ability to create jobs across different sectors such as transportation, real estate, manufacturing, trade, warehousing, wholesale, and leasing services. The sector is considered the single largest industry globally with a net worth exceeding four trillion dollars in the year 2004. Moreover, the sector alone employs about one quarter of the world’s workforce [1]. However, despite the importance of the sector, grave issues of mental health and social sustainability have been reported over the years. Reports by the Centers for Disease Control and Prevention (CDC) have shown that workers in the construction sector are at a high risk of suicide and mental health issues due to uncertain factors such as the uncertainty of seasonal work, demanding schedules, and workplace health and safety risks [2]. This is a significant problem that needs to be addressed.

To add to this, the recent COVID-19 pandemic has not only shaken the world in general but affected the global workforce and the construction sector in particular, which has caused significant problems in terms of unemployment, mental health issues of employees, and work–life balance. At the same time, the literature has reported on several issues related to mental health; such issues result in an adverse effect on the population globally with increases in the numbers of cases of depression, anxiety, and suicide each year [3]. This results in several failures in the industry, such as low productivity and performance and costs of illness, absenteeism, staff turnover, and onsite accidents, as evident in the UK, where about 80 million days are lost every year to mental health illnesses that cost the country between GBP 1 and 2 billion each year [4].

At this point, it can be established that the issue of mental health carries significant importance to communities’ well-being and the success of a nation. This is also evident from the initiatives taken by the World Health Organization (WHO), over the years; i.e., in 1991, the UN’s calls for the improvement of mental health care; 1993—the World Bank exposing the alarming burden of mental health problems; 1995—Harvard University creating awareness about the complexity of mental disorders; 1996—the World Health Organization launching a global program, ‘Nations for Mental Health’. The latter program adopts a three-step approach envisaged to put mental health as a significant factor in nations’ success on the political agenda [5].

However, still, alarming estimates show that one in four of the world’s population suffers from a different form of mental disorder. In addition, the Global Burden of Disease report from 2010 claims that about 400 million people suffer from depression [6]. Furthermore, the global burden of mental health in terms of economic strain and financial costs is staggering. For example, the United States in 2014 had to spend USD 239 billion on mental health and substance abuse treatment with the costs of human suffering incalculable [7]. The global economic impact of mental health problems such as depression and anxiety disorders are estimated to be USD 1 trillion per year in loss of productivity, according to a report conducted by the WHO [8]. It is evident from these figures that mental health has been neglected for far too long. It is crucial for the overall well-being of individuals, societies, and countries and can help ensure social sustainability. Thus, in 2015, the inclusion of mental health and psychosocial well-being as an integral part of the sustainable development goals (SDGs) came as a promising effort to promote this grave issue in a unified global agenda. The universal nature of the SDGs commits world leaders to prioritize and promote mental health and well-being.

Hence, it is important to understand the concept of mental health in general, and that of employee mental health and well-being specifically, in the construction sector. Although the literature has reported on reliable scales that have been proposed over the years that have linked the concept of employee mental health and well-being with job satisfaction, higher productivity, lower absenteeism, and lower turnover rates [6,9,10], these scales tend to work in isolation and focus on only certain aspects of mental health. Ref. [11] examined the mental health challenges faced by manual and trade workers in the construction industry, highlighting the higher prevalence of anxiety, depression, and suicides compared with the general population. It identified key causes, such as poor work–life balance and job insecurity, and outlined the effects, including suicidality and poor work performance. The review also assessed the effectiveness of interventions, revealing mixed results, and suggested areas for further research and improved practices to address mental health issues in this sector. Moreover, ref. [12] presented how different levels of stress and mental health issues exist for different occupations based on the work pace and skills required; construction workers and architects tend to show higher stress levels, as indicated in Figure 1.

The figure, therefore, indicates that architects belong to the high-skill discretion with a high pace of work, but they tend to have a higher risk of stress and mental health issues associated with their work. Similarly, construction workers fall into the low-skill discretion category that demands a high pace; thus, they also tend to have a higher risk of stress and mental health issues.

However, little or no research has been conducted to support and monitor the organizations in working on enhancing the social sustainability and mental health of employees in the construction sector, thus indicating a research gap.

Similarly, the adverse impact of mental health on the construction sector of the United Arab Emirates is no different from that of other developing and developed nations, where about 42 percent of the workforce experiences some degree of stress with the inability to maintain a good work–life balance [13,14]. This study, therefore, focuses on the United Arab Emirates, which is a land with a diverse workforce that hosts a large number of migrant workers [15]. In addition, the UAE government has a compelling vision for the future with several initiatives like the national program for happiness and positivity for its diverse workforce.

Thus, the primary objective of this study is to discern a foundational set of criteria defining social sustainability, specifically in the context of employee mental health and well-being within the construction sector of the United Arab Emirates. To achieve this aim, it is imperative to cultivate a comprehensive understanding of conceptual evolution.

This study will accordingly incorporate the identified criteria to evaluate the relationship and impact of these factors on employees’ job satisfaction, ultimately contributing to the assurance of social sustainability for employees within the construction sector in the UAE.

2. Social Sustainability

Sustainable development has become a widely embraced benchmark for obtaining a competitive advantage on a global scale, having been endorsed by nations, communities, and organizations. The discourse on sustainability has expanded beyond environmental considerations to encompass economic and social dimensions. While the literature extensively discusses sustainability, the incorporation of social sustainability within organizational frameworks is still in its nascent stages [7].

In a broader context, the United Nations has defined social sustainability as “the process of creating sustainable environments that enhance well-being (comprising both physical and mental health) by comprehending the needs of individuals in the spaces they reside and work”. When viewed through the lens of corporate environments, social sustainability extends its purview to encompass various factors, including but not limited to human rights, fair labor practices, living conditions, health and safety standards, wellness initiatives, diversity, equity, work–life balance, empowerment, engagement, and organizational commitment [8].

Consequently, by embracing the definition and components of social sustainability, numerous studies have presented a comprehensive conceptualization that intertwines social sustainability with mental health and well-being. This implies that safeguarding the mental health and well-being of an individual is crucial for ensuring their social sustainability, as illustrated in Figure 2.

Hence, the present study posits that ensuring social sustainability necessitates the comprehensive consideration of mental health and well-being. Consequently, this research will employ the interchangeability of terms, treating social sustainability and mental health and well-being as a unified conceptual framework.

Over time, the concept of mental health has undergone evolution across various theoretical frameworks. Despite the dynamic nature of this concept, a persistent assumption endorsed by scientists and researchers is the distinction between mental health and mental illness [16,17]. As articulated by [18], mental health and mental illness are posited as orthogonal constructs, residing on two separate yet interconnected continua, as shown in Figure 3 below.

The depicted figure articulates a theoretical framework involving two continua: one representing the spectrum of mental health presence and absence, and the other an orthogonal continuum delineating the presence and absence of mental illness. In the first quadrant (clockwise), an individual characterized by high mental health and low mental illness is categorized as flourishing. However, in the fourth quadrant, an individual with high mental health and high mental illness is also termed as flourishing albeit with occasional instances of mental illness. This underscores the distinction between the concepts of mental health and mental illness, emphasizing that the absence of mental illness does not automatically imply the presence of mental health. Consequently, this study concentrates solely on the concept of mental health and the underlying criteria influencing the mental health of employees within an organizational context.

Mental health and well-being have emerged as pivotal concepts crucial for community welfare and a nation’s success in achieving social sustainability. Throughout history, the concept of mental health has evolved into three distinct theories: the pathogenic approach, the salutogenic approach, and the complete state approach [19]. The pathogenic approach, rooted in the Greek term pathos, denoting suffering or empathetic emotion, initially defined health as the absence of illness. Subsequently, in 1979, the salutogenic approach was introduced, perceiving health as the presence of positive emotions, capabilities, behavior, and cognitive processes. Lastly, the complete state model, derived from the word hale signifying wholeness, was introduced [20]. Since then, the theory of mental health as a holistic state of an individual’s well-being has garnered acceptance among researchers, as shown in

Table 1. Mental health definition.

Year	Definition
1958	The existing behavioral and social scientific vision of mental health is not merely the absence of mental illness but the presence of something positive
1980’s	The concept of mental health as subjective well-being was first introduced, where the presence of mental health was termed as flourishing and the absence of mental health was considered as languishing in life
1985	Mental health in terms of emotional well-being can be defined as the presence and absence of positive feelings in one’s life.
1989	The concept of mental health as a symptom of positive feelings and functioning of life
1988	There is more to mental health than just psychological well-being and positive functioning, therefore proposing the concept of social well-being
	The degree of mental health can be accessed using subjective well-being such as subjective happiness, self-confidence, and morale.
1999	The US Surgeon General, David Satcher, conceived of mental health as “a state of successful performance of the mental function, resulting in productive activities, fulfilling relationships with people, and the ability to adapt to change and to cope with adversity”
2004	“a state of well-being in which the individual realizes his or her abilities, can cope with the normal stresses of life, can work productively and fruitfully, and can make a contribution to his or her community”

This acknowledgment is exemplified by the World Health Organization’s [21] definition in its seminal report in 2002, which characterizes mental health as “a state of well-being in which every individual realizes his or her potential, can cope with the normal stresses of life, can work productively and fruitfully, and can contribute to his or her community”.

Hence, drawing upon the insights gleaned from the historical evolution of mental health, as encapsulated in Table 1, and aligning with the comprehensive perspective of the World Health Organization, which encompasses subjective well-being (encompassing emotional, psychological, and social dimensions), the definition emphasizing an individual’s capacity to function positively and productively is adopted as the framework for this study.

Thus, keeping in mind that social sustainability focuses on creating a place that promotes well-being and mental health through creating an environment where the individual realizes his or her potential when the needs of people from the places they live and work are met [8]. Thus, for this study, the holistic definition of social sustainability and mental health and well-being will be adopted.

Furthermore, an examination of the provided table underscores the enduring significance attributed to mental health over the past decade. Despite this recognition, current estimates indicate that one in four individuals globally is afflicted by various forms of mental disorder. The Global Burden of Disease 2010 report asserts that approximately 400 million people worldwide suffer from depression [9]. Moreover, a report by the World Health Organization (WHO) indicates a staggering global economic impact of mental health issues, such as depression and anxiety disorders, amounting to an estimated annual loss of 1 trillion US dollars in productivity [13]. Additionally, the report delineates that neuropsychiatric or mental health conditions contribute to 28% of disability-adjusted life-years, as illustrated in Figure 4, in comparison to various other non-communicable diseases.

Regrettably, despite the alarming global prevalence of mental health issues, there has been a pervasive lack of commitment from leaders and policymakers. As indicated by source [21], it took a decade of incremental progress for mental health concerns to gain global recognition. Key milestones in this journey include UN calls for improvement in mental health care in 1991; Alarming Burden of Mental Health Exposed in 1993, and the Complexity of Mental disorders in developing countries in 1995. In A Nation is Born (1996) the WHO decided to promote mental health as a global agenda in collaboration with the United Nations (UN) by proposing a global program dedicated to improving the mental health and well-being of the world’s population. This program was called ‘Nations for Mental Health’. Finally, in 2015, the inclusion of mental health and psychosocial well-being as an integral part of the Sustainable Development Goals (SDGs) 2015 marked a promising effort to establish the construct as a unified global agenda [23]. The universal scope of SDGs mandates world leaders to prioritize and promote mental health and well-being, fostering a new perspective and vision globally.

However, despite ongoing efforts by governments and international organizations to enhance mental health, numerous global challenges persist. Primary among these is the literacy challenge, involving the recognition of mental health issues as a critical concern, particularly in underdeveloped and developing countries where the concept remains stigmatized. Furthermore, an inadequate allocation of resources, both nationally and internationally, compared to other diseases poses a significant barrier to addressing global mental health issues. Additionally, the absence of valid and reliable definitions, models, and measurement tools for quantitative assessment at individual and population levels, applicable across diverse cultures and settings, presents a substantial challenge for global implementation. This challenge is categorized into seven dimensions: conceptual, social, economic, human rights, political, health system, and international/national policy [24].

Hence, it is imperative to delineate the foundational criteria influencing employees’ social sustainability within the construction sector. This entails examining the relationship between employees’ social sustainability and job satisfaction to propose a comprehensive measurement scale.

3. Employees’ Social Sustainability

The literature reports on several studies that investigated the impact of different criteria on employees’ job satisfaction and mental health and well-being ensuring social sustainability. However, the limitation of these studies was their narrow focus on only one or a limited number of criteria, thus failing to provide a complete measurement and definition of employees’ social sustainability in the organization. Therefore, this study conducted an extensive literature review that identified the underpinning criteria of employees’ social sustainability and classified them into four categories: organizational factors, personal factors, social factors, and environmental factors.

3.1. Organizational Factors

The current discussion explores the varied domain of organizational factors and their complicated interplay with employees’ social sustainability in a variety of work contexts. These organizational characteristics, which denote crucial structural and functional aspects inherent in the organizational fabric, have a perceptible influence on individuals’ psychological well-being. The concept of organizational factors spans a wide range of characteristics, including the structure of the organization, operational policies, and functional beliefs. Following a thorough review of the literature, it is clear that organizational structure emerges as a significant driver of employee mental health and well-being. Several studies [25,26,27,28] have demonstrated that organizational structure has a significant impact on a variety of elements of psychological well-being, ranging from depression and anxiety to job satisfaction. The hierarchical structure, communication channels, knowledge management, and organizational justice all contribute to the psychological well-being of employees. Moreover, the flexible work system within which work is undertaken emerges as an influential factor. The shift system, as elucidated by [29], has a distinct relationship with sleep quality, thereby having an impact on mental health. Similarly, the flexibility of work systems and the nature of work timings [30,31,32] unveil a nexus between employee well-being, work–life balance, and job satisfaction.

Further, the discourse navigates the domain of work design, elucidating its cardinal role in shaping employee mental health. A robustly designed work structure, encompassing facets such as job fit, autonomy, challenge, and meaningfulness, has been shown to positively correlate with employee engagement and well-being [28,33,34,35]. The role of management involvement and support is also underscored [31,32], with leadership styles and the competencies of supervisors impacting the psychological welfare of employees. In addition to structural and functional dimensions, organizational well-being is underscored as a vital underpinning of employee mental health. Criteria encompassing growth opportunities, the timely payment of salaries, welfare schemes, appraisal protocols, and training further reinforce the relationship between organizational factors and employee well-being [27,28,36].

From the literature, the varied range of organizational factors that have an impact on the employees’ job satisfaction and mental health ensuring social sustainability is presented in

Table 2. Organizational factors.

Organizational Factors	Criteria	Authors
	Organization structure, management involvement and awareness, flexible or fixed work systems, work design (job control)—how much control they have over project, team, resources, and time selection, person–job fit (the job meets the goals and skills set of the employee), timely payment of salaries, role ambiguity/ role clarity, role conflict—working different roles that requires different outcome, training and development, salary satisfaction	[25,26,27,28,29,30,31,32,33,34,35,36]

below:

In summary, a complicated tapestry of organizational elements, including organizational structure, work design, management participation, and several other dimensions, converges to significantly influence employees’ social sustainability. While existing studies have provided interesting perspectives into individual aspects of these factors, a thorough explication of their interrelationships is an ongoing research gap that calls for additional research. However, the limitation of the scale is its dependence on the organizational factors alone, whereas the construct of employee well-being (satisfaction, performance, and mental health) can be defined by considering multiple factors such as personal, environmental, and social.

3.2. Personal Factors

The literature underscores the dual impact of external and personal factors on employees’ social sustainability. While external factors are significant, personal attributes also hold substantial influence over an individual’s decisions, behaviors, and relationships. Consequently, personal factors wield a pronounced effect on an individual’s overall well-being, extending to their professional life. The study by [37] further categorizes individual personal factors into demographics (e.g., age, education, past experience, level of academic achievements, individual culture), personality traits (such as work motivation, intrinsic motivation, optimism, trait anxiety, hostility), and situational factors (including sleep quality, emotional exhaustion, contract type, work–life balance, spousal support, job demand, and job satisfaction).

Explorations into the impact of demographics on employee mental health have been noted in several studies. Notably, ref. [35] demonstrated the significant role of both organizational and personal factors (e.g., personality, gender, age, education) in influencing employee well-being and mental health. Likewise, ref. [33] echoed this sentiment by highlighting the influence of age and generational shifts on employee well-being, especially in the context of happiness goals. Similarly, ref. [31] utilized a two-step hierarchical regression model, identifying personal factors like marital status, marital satisfaction, age, number of children, and parents’ residence as determinants of employee mental health. Moreover, ref. [28] focused on the construction industry and found factors such as level of academic achievements, experience, age, individual culture, and motivation to be significant contributors. Despite these insights, a limitation exists in the tendency of these studies to concentrate on a singular facet of an individual’s life.

Personality traits have emerged as influential determinants of job performance, productivity, satisfaction, and turnover intention [38]. Likewise, ref. [39] adopted a quantitative approach to investigate the interplay between work motivation, job stress, and employee well-being, revealing the positive association between intrinsic work motivation, job satisfaction, and negative correlation with depression. Similarly, ref. [40] delved into multilevel analyses, revealing that trait anxiety and hostility were significant contributors to individual mental health, while job control exerted a multilevel influence. The same was witnessed throughout the literature where [41] identified factors like minimal risk, workplace concern, activity concern, and emotional stress as pivotal contributors to IT professionals’ mental health and well-being. Likewise, ref. [42] found positive affectivity and intrinsic motivation to protect employees from work-related depression with emotional exhaustion acting as a mediating factor.

The significance of sleep quality on an employee’s well-being is evident, particularly in high-risk industries. In their study [43], Lim et al. established a link between sleep quality, shift systems, and employee health and well-being, with poor sleep quality associated with adverse impacts on work performance, turnover intention, job satisfaction, and increased depression, anxiety, and stress [44]. It should be noted that the Pittsburgh Sleep Quality Index (PSQI) is a widely used scale for measuring sleep quality.

The impact of job contracts on mental health has garnered attention with non-permanent forms of employment deemed detrimental to employee well-being. In their studies, refs. [45,46,47] further supported this claim, highlighting the adverse effects of precarious employment on mental health. The delicate balance between work and personal life, and the role of spousal support, have also been emphasized as significant determinants of employee mental health along with job demand, control, and job satisfaction emerging as substantial determinants of employee mental health and well-being [30,31,48]. The interplay between these factors has been explored with research indicating their considerable impact. Notably, job satisfaction, role clarity, role ambiguity, work-related stress, life stress, growth opportunities, and career anchors contribute to mental health and well-being. Longitudinal studies [9,36] have further underscored the interaction between low job control, high-demand jobs, and their negative impact on employee well-being.

Thus, the varied range of personal factors identified from the literature that have an impact on the employees’ job satisfaction and mental health ensuring social sustainability is presented in

Table 3. Personal factors.

Personal Factors	Criteria	Authors
	Self-efficacy, work motivation, burnout, emotional exhaustion, personal accomplishment/depersonalize, sleep quality, contract type, work–life balance, age, personality type, marital status, family type	[9,30,31,33,35,37,38,39,40,41,42,43,44,45,46,47,48]

below:

Although personal and organizational factors have a primary impact on the employee’s mental health, the effect of these factors is mediated by social and environmental factors. Therefore, to define the comprehensive nature of the EMW, the social and environmental factors must be identified which the previous studies above fail to include in their research.

3.3. Social Factors

Individual lives comprise two intertwined domains: the organizational domain and the personal domain. Consequently, social factors and support within both these domains are fundamental for a harmonious and effective life [49]. Research by [27,31] has underscored the significance of interpersonal relationships, group dynamics, peer support, leadership style, supervisor acknowledgment, and organizational commitment as crucial factors affecting employee mental health and overall well-being in the workplace. For instance, a study by [50] delved into the correlation between social support (frequency of support from colleagues, supervisors, friends, and family) and employee well-being, revealing that social support is inversely associated with depression and exerts a substantial influence on employee health and well-being.

Similarly, ref. [51] conducted an inquiry into the link between employees’ perception of their supervisors’ emotional intelligence (EI) and individual and group satisfaction. The study’s findings highlighted that the perception of a supervisor’s EI significantly and positively impacts job and group satisfaction, subsequently influencing workgroup attachment. Moreover, an encompassing review by [9] explored the social determinants of mental health, categorizing them into life-course, community-level, and country-level contexts. The research underscored various factors such as unemployment, job security, short-term contracts, job control, job demand, and spousal support, which affect employee well-being and mental health. The recommendations derived from these findings offer actionable insights to mitigate the impact of social inequalities on mental health.

Furthermore, concerning adverse experiences, studies by [52,53] have indicated the detrimental effects of workplace bullying, harassment, and violence on employee mental health and overall well-being. Likewise, ref. [54]’s investigation revealed that exposure to workplace bullying was associated with anxiety, depression, stress, and mental health issues. These studies also suggest that peer, supervisor, and organizational support can act as mediators, exerting a positive influence on individual mental health and well-being.

Thus,

Table 4. Social factors.

Social Factors	Criteria	Authors
	Social support, association with supervision/employee perception of supervisors/leadership style/competencies of supervisors, spousal support, job demand—physical and psychological demand of the job, self-organizational commitment, organization culture, pay equity, gender equality	[27,31,49,52,53,54]

presents the range of social factors identified through the literature that have an impact on employees’ job satisfaction and mental health ensuring social sustainability.

It can be concluded at this point that personal and organizational along with social factors have a significant impact on employee well-being. Although the studies have identified relevant factors of employee well-being, they fail to consider the effect of external factors such as environmental, organizational arrangement, and site/off-site work on the well-being of an employee. As indicated by [55], the external environment and organizational arrangements have an impact on the mood and motivation of an employee.

3.4. Environmental Factors

Numerous scholarly investigations have emphasized the pivotal role of the work environment in shaping employees’ social sustainability. In their study, Sarode and Shirsath highlighted that elements like lighting, noise, color, and air quality within the work environment exert an influence on employee productivity, health, well-being, job satisfaction, and morale [56]. Employing a descriptive approach, the study synthesized secondary data from various sources such as websites, journals, and books. The findings demonstrated the tangible impact of the working environment on employee well-being, underscoring the significance for organizations to consider this factor. Similarly, Han and Hyun (2019) employed a quantitative methodology to delve into the effects of nature-based solutions (NBSs) on customer and employee morale as well as mental health. The research affirmed that a green indoor and outdoor environment significantly contributes to mental well-being [57]. Furthermore, refs. [58,59] underscored the importance of organizational arrangements and the overall working environment as integral components influencing employee well-being. Job security emerges as another vital determinant impacting employee mental health, thereby shaping both individual well-being and the organization’s broader brand image. Moreover, ref. [60] conducted a longitudinal study involving 5400 UK National Health Service employees, employing a self-rated mental health questionnaire (12-item version of the General Health Questionnaire). The study revealed that increased workload in the preceding year adversely affected employee mental health, while those who received training, promotions, and job security exhibited better mental well-being. This perspective aligns with the findings of [61,62], who explored the relationship between perceived job security and health. These studies collectively ascertain that job security holds a central role in subjective, physical, and psychological well-being.

Thus, the varied range of environmental factors identified from the literature that ensures employees’ social sustainability is presented in

Table 5. Environmental factors.

Environmental Factors	Criteria	Authors
	Working environment and condition (lighting, noise, color, and air quality), work stress/workload, and job security/safety	[56,57,58,59,60,61,62]

below:

In a nutshell, the literature reports on the number of organizational, personal, social, and environmental factors as the underpinning criteria that define employees’ social sustainability as presented in

Table 6. Underpinning criteria.

Themes	Criteria	Authors
Organizational Factors	Organization structure, management involvement and awareness, flexible or fixed work systems, work design (job control)—how much control they have over project, team, resources, and time selection, person–job fit (the job meets the goals and skills set of the employee), timely payment of salaries, role ambiguity/ role clarity, role conflict—working different roles that require different outcomes, training and development, salary satisfaction	[25,26,27,28,29,30,31,32,33,34,35,36]
Personal Factors	Self-efficacy, work motivation, burnout, emotional exhaustion, personal accomplishment/depersonalize, sleep quality, contract type, work–life balance, age, personality type, marital status, family type	[9,30,31,33,35,37,38,39,40,41,42,43,44,45,46,47,48]
Social Factors	Social support, association with supervision/employee perception of supervisors/leadership style/competencies of supervisors, spousal support, job demand—physical and psychological demands of the job, self-organizational commitment, organization culture, pay equity, gender equality	[27,31,49,52,53,54]
Environmental Factors	Working environment and conditions (lighting, noise, color, and air quality), work stress/workload, and job security/safety	[56,57,58,59,60,61,62]

below.

The findings of the literature and the factors identified are aligned with Maslow’s hierarchy of needs, as this theory offers an organized perspective on the demands of employees, ranging from self-actualization to fundamental physiological requirements. This study can demonstrate how addressing many levels of employee needs—such as safety (environmental factors), belonging (social factors), and esteem (organizational factors)—contributes to overall well-being [63].

This study, therefore, aims to incorporate the identified criteria to evaluate the relationship and impact of these factors on employees’ job satisfaction, ultimately contributing to the assurance of social sustainability for employees as shown in theoretical framework in Figure 5 within the construction sector in the UAE.

4. Methodology

This study adopts a mixed-methods approach to identify the underpinning criteria of employees’ social sustainability and its impact on job satisfaction, ultimately contributing to the assurance of social sustainability for employees within the construction sector in the UAE following the methodological steps below:

4.1. Qualitative Study

The purpose of this study is to validate and tailor the criteria according to the construction sector that was used to develop the questionnaire survey by targeting stakeholders from the construction industry, using semi-structured interviews. Moreover, the interviews aid in understanding the current practices and challenges related to the successful implementation of employees’ social sustainability in the industry. In addition, it also allows for identifying the decision criteria that play a significant role in making strategic decisions.

The semi-structured interview questions were divided into five sections. The set of questions in Section I intends to inquire about the interviewees’ profiles and backgrounds. Section 2 asked the participants about their organizational profiles. Section 3 was intended to determine their role, responsibility, and the experience they have gained as an expert. Section 4 focuses on determining their knowledge of social sustainability, current practices, and challenges they faced in its implementation. Finally, Section 5 aimed to present the list of underpinning criteria of employee mental health and well-being identified from the literature to the interviewees to gain their insights for validating and tailoring the criteria to the construction sector. At the beginning of the interview, the interviewers explained the confidentiality requirements and area of research to the participants. The interviewees in Section 1 and Section 2 discussed their profiles and roles in the construction organization.

4.2. Quantitative Study

The primary objective of the survey was to assist the research in discerning the factors or criteria that wield a substantial relationship and impact on employees’ social sustainability through the application of structural equation modeling. The findings of this survey aim to lay a foundation for subsequent studies to adopt these identified criteria and contribute to the improvement of employee well-being. A ten-minute online survey was disseminated via different social media outlets such as LinkedIn and WhatsApp, employing a combination of snowballing and convenience sampling, targeting a diverse array of participants within the construction sector in the UAE.

The survey comprised three sections. Section I focused on gathering participants’ profiles, delving into aspects such as their position, total years of experience, marital status, contract type, and income. Section II solicited participants to rate their satisfaction levels, social sustainability, and mental health and well-being on a 5-level Likert scale, providing insights into their perceived social sustainability within the organization. Following this, Section III prompted participants to rank their level of agreement concerning 27 criteria of social sustainability, utilizing a 5-level Likert scale. These criteria were further disaggregated into indicators/items, which were designed to assess participants’ agreement levels with the impact of these criteria and sub-criteria on their social sustainability. This approach aimed to eliminate potential biases, and the survey questions were phrased positively, encouraging participants to respond impartially and candidly, thus contributing to the reliability of the collected data as shown in

Table 7. Social sustainability criteria and indicators.

Dimensions	Indicators/Items	Label
Organization Structure	Choose the statement that defines the structure of your organization.	OS1
	Choose the statement that defines the ‘managerial style’ of your organization.	OS2
	Choose the statement that defines the ‘environment’ of your organization.	OS3
Management Involvement and Awareness	The management is often involved and aware of any changes/activities going on in the organization at the functional level (employer level).	MI1
	The management often intervenes to promote social sustainability (employee health and well-being).	MI2
	The management address any issues the employee is facing.	MI3
Flexible or Fixed Work Systems	My supervisor seeks my opinions while planning my shifts/work schedules.	FW1
	I am allowed to reschedule my tasks, meetings, and other work-related involvements.	FW2
	Work requirements are not rigid, and flexibility is displayed to accommodate the requests.	FW3
Work Design (Job Control)	I have full control over my project selection.	WD1
	I have full control over setting the timeline and milestones of my project.	WD2
	I have full control over selecting the team and resources for my project.	WD3
Person–Job Fit	All things considered, this job suits me, and it is what I like to do.	JF1
	I feel that my needs and goals are met in this job.	JF2
	I can use my skills, knowledge, and competencies in this job.	JF3
Timely Payment of Salaries	My organization pays me in a timely manner.	TP1
	Overtime payments are given as per policy and in a timely manner.	TP2
	Benefits and bonuses are given as per the policy.	TP3
Role Ambiguity/Role Clarity	I have clear and well-defined goals and objectives for my job	.RA1
	I feel certain how much authority I have on the job.	RA2
	The job description is clear concerning what has to be done.	RA3
Role Conflict	I must do things that need to be done differently under different situations.	RC1
	I work with two or more groups who operate differently.	RC2
	I do things that might be accepted by one person but not by others.	RC3
Training and Development	My organization ensures possibilities for employees to develop professional competences.	TD1
	My organization constantly encourages employees to enhance their competences to meet the changing market.	TD2
	My organization develops employees’ personal competencies such as leadership skills, communication skills, etc.	TD3
Salary Satisfaction	I am satisfied with my salary in terms of the market.	SS1
	I am satisfied with the benefits provided to me by my organization in comparison to others in the market.	SS2
	My organization increases pay to depend upon the economic conditions such as inflation or the introduction of VAT or addition of job demands.	SS3
Self-Efficacy (Personal Accomplishment/Depersonalize)	I can always manage to solve difficult problems if I try hard enough by remaining calm.	SE1
	It is easy for me to stick to my aims and accomplish my goals.	SE2
	I feel satisfied with how I perform and with my accomplishments.	SE3
Work Motivation	How would you describe your type of motivation for your work and organization?	WM1
	My organization ensures the employees are well motivated.	WM2
Burnout/Emotional Exhaustion	I do not feel burnout or fatigue due to my job at the end of the week.	B1
	I generally feel relaxed and optimistic.	B2
	I do not feel emotionally drained due to my job at the end of the week.	B3
Sleep Quality	How would you rate your sleep quality?	SQ1
	On average during the past month, how long has it taken you to fall asleep?	SQ2
	Sleep duration	SQ3
Contract Type	I am satisfied with the contract I have with my organization.	CT1
	My contract type does not affect my performance.	CT2
	My contract type does not affect my commitment and loyalty to my organization.	CT3
Work–Life Balance	My job does not harm my family and social life.	WLB1
	My job does not require me to think about the work requirements while I am at home.	WLB2
	I can balance both work and family requirements successfully.	WLB3
Spousal Support	My family members understand my work pressure and offer support while I work on my office work from home.	S1
	Members of my family or spouse always seem to make time for me if I need to discuss work stress.	S2
	If my job gets very demanding, someone in my family or my spouse will take on extra household responsibilities and childcare.	S3
Job Demand	My job is not physically very demanding.	JD1
	My job is not psychologically very demanding.	JD2
	I don’t feel burdened due to the requirements of my job.	JD3
Social Support	My supervisor has my back and supports me in any way possible.	SO1
	My colleagues have my back and support me in any way possible.	SO2
	My organization values my contribution and appreciates any extra effort from me.	S03
Association with Supervision/Employee Perception of Supervisors/Leadership Style/Competencies of Supervisors	Morale building: my supervisor behaves in ways that gain respect, trust, and confidence of others and transmit a strong sense of mission to them.	AS1
	Inspirational motivation: my supervisor provides meaning and challenge to others’ work, communicates a vision with fluency and confidence, increases others’ optimism and enthusiasm, and gives pep talks to energize others.	AS2
	Individualized consideration: my supervisor pays special attention to each individual’s needs and abilities for achievement and growth by acting as a coach or mentor and makes each individual feel valued.	AS3
Self-Organizational Commitment	I am emotionally attached to this institution and have no intention to join another organization at the moment.	SOC1
	I recommend this institution to my friends and all other prospective employees.	SOC2
	My continuance with this organization is not based on my current necessities and needs only.	SOC3
Organizational Culture	My organization values diversity.	C1
	Bullying/Harassment/Discrimination are not welcomed in my organization.	C2
	Social cohesion—a sense of belonging— is common in my organization.	C3
Working Environment and Condition (Lighting, Noise, Color, and Air Quality)	There is sufficient green space (e.g., trees/plants) in my organization.	WE1
	Perceived air pollution—my organization ensures clean air.	WE2
	Perceived noise—my organization ensures that low noise levels are maintained to increase productivity.	WE3
Work Stress/Workload	My manager ensures employees are given appropriate amounts of work that don’t put them under too much stress/pressure.	WW1
	My supervisor assigns me tasks after discussing with me the workload I have.	WW2
	My manager ensures I am not given more work than that defined in my job description.	WW3
Job Security/Safety	My organization provides the necessary working equipment for employees and ensures the workplace fulfils all safety requirements	JSS1
	My organization’s environment gives me a feeling of safety and security and I feel satisfied with my future prospects within the organization.	JSS2
	My organization ensures market conditions such as inflation or global issues such as the COVID-19 pandemic do not affect employees’ morale by taking strategic measures.	JSS3
Pay Equity	I am paid equally in comparison to others holding similar jobs in the organization.	PE1
	I am paid equally in comparison to others with similar skills in the market.	PE2
	I am given similar incentives and benefits in comparison to others with similar skills in the market.	PE3
Gender Equality	My organization ensures equal personal development opportunities for employees without any gender bias.	GE1
	My organization ensures equal opportunities for all candidates during the selection process without any gender bias.	GE2
	My organization ensures equal benefits for all candidates during the selection process without any gender bias.	GE3

below.

Thus, this study aims to determine the criteria that have an impact on the satisfaction and subjective well-being (social sustainability and EMW) of employees in construction-sector organizations, therefore ensuring their social sustainability in the organization. For this purpose, this study adopts exploratory structural equation modeling (ESEM) proposed by [64] in 2013, which allows it to cater to the non-ignorable cross-loadings between the criteria.

4.3. Exploratory Structural Equation Modeling (ESEM)

Exploratory structural equation modeling (ESEM) is a statistical technique that combines aspects of both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) within the framework of structural equation modeling (SEM). SEM is a statistical method used to test and estimate complex relationships between observed and latent variables [64].

In traditional SEM, researchers specify a theoretical model with a set of hypothesized relationships between latent and observed variables. Confirmatory factor analysis (CFA) is then used to test the fit of the specified model to the data. In contrast, exploratory factor analysis (EFA) is a technique used to uncover the underlying structure of a set of variables without a pre-specified model. ESEM allows for a more flexible and data-driven approach. Instead of strictly adhering to a pre-specified model (as in CFA), ESEM allows for the exploration of the data to identify the most appropriate factor structure. This can be particularly useful when researchers do not have a well-defined theory guiding their model or when the true structure of the data is not known. The key features encompass model flexibility, allowing for a blend of factor structure exploration and hypothesis testing. It accommodates cross-loadings, permitting variables to load on multiple factors, providing a more realistic representation of relationships. Researchers can use model fit indices to assess how well their chosen model fits the data, aiding in overall adequacy evaluation. ESEM is particularly useful for complex data structures or when researchers aim to explore underlying factor structures with a balanced approach between confirmatory and exploratory modeling [65].

A number of studies have adopted ESEM, such as [66], which used exploratory structural equation modeling (ESEM) to assess the factor structure and measurement invariance of the Farsi version of the Children’s Eating Attitudes Test (F-ChEAT) among Iranian preadolescents. ESEM allowed for testing whether the factor structure was consistent across gender and age groups. The 5-factor, 15-item ESEM model demonstrated excellent fit and meaningful comparability, validating the tool for assessing disordered eating symptoms in this population. Similarly, ref. [67] adopted ESEM to clarify the factor structure of the Anxiety Sensitivity Index-3 (ASI-3) for a sample of 300 Korean college students. The study compared CFA, ESEM, bifactor-CFA, and bifactor-ESEM models where the results showed that the bifactor-ESEM model provided the best fit with a strong global factor explaining most of the variance. The global factor was also associated with distress intolerance, supporting its criterion-related validity. This study supports a bifactor-ESEM structure for the ASI-3 among Korean students.

The structured methodology based on qualitative and quantitative measures facilitates the examination of the relationship among the identified underpinning criteria of employees’ social sustainability.

5. Results and Analysis

This section elucidates the outcomes of the mixed-methods approach utilized in this study. Qualitative analysis was employed to identify the underpinning criteria of employees’ social sustainability through an extensive literature review, which was subsequently validated through semi-structured interviews conducted with experts in the construction industry. Additionally, the section encompasses the findings of the quantitative analysis, which involved the development of a survey instrument. The survey was designed to identify significant criteria influencing employee mental health and well-being, utilizing structural equation modeling for analysis.

5.1. Semi-Structured Interviews

Semi-structured interviews were utilized as a methodological tool to investigate the existing practices and challenges in the implementation of policies aimed at enhancing the social sustainability of employees by targeting 10 experts from the construction sector.

Profile of Interviewees—The interviewees were selected as experts within the industry, each possessing considerable experience in roles such as Head of the HR Department, CFO (Chief Financial Officer), and General Manager. The participants’ professional backgrounds spanned from 5 to 32 years within the construction sector, as detailed in

Table 8. Participants’ profiles.

Code	Title	Years of Experience
P1	Chief Financial Officer (CFO)	24
P2	Director of National Capabilities	20
P3	Head of HR Department	20
P4	Head of HR Department	13
P5	Head of HR Department	19
P6	Head of Quality & Materials Management	15
P7	General Manager	21
P8	HR Executive	5
P9	Regional CHO	32
P10	Senior Group Human Resources Manager	15

.

The participants were asked about their organization and whether their organization had an occupational health/organizational health department. All the interviewees responded positively to the question; participant 3 highlighted that “Though we don’t have a dedicated Health dept., we have a program, call it Mariah. It’s for coaching and the purpose is to… make good health for the employees or to solve the problems”.

Moreover, we asked the interviewees what services their organization offered as part of social sustainability. The responses of all the participants were similar in that they highlighted the common practices of offering medical insurance and wellness programs. Interviewee P1 stated, “We take care of the health of each one, we are giving medical insurance to families also. So, all the colleagues are comfortable, they are not worried about their families. Also, whenever they are sick we pushed them to take kids or family, wife, to hospital… as only happy people can be a good employee”. Moreover, Interviewee P9 also stressed the benefits of organization services by saying, “Yeah, we do have only medical insurance and we try to organize sports league to tune and so we as the team can participate and take care of their health. This all is offered to maintain employee relations”.

Thus, it may be interpreted here that organizational support plays an important role in social sustainability and EMW.

Moreover, to gain insight from their experience, the interviewees were asked about the most difficult challenge they faced in their entire experience as a supervisor/HR manager. The interviewees highlighted several challenges they have faced. As discussed by interviewee P4: “I think probably the most difficult challenge is that sometimes…well often you must be nimble. It’s a diverse environment and you don’t always get to see a lot of long-range plans and you must be nimble and able to react quickly”. Moreover, Interviewee P8 also highlighted, “Being in HR and being in the construction industry, I would say that change management… anywhere when you try to bring the change so that’s very difficult for us”.

The construction sector, especially in the UAE, comprises a diverse workforce, and the sector itself is dynamic. Thus, from the view of interviewees, the major challenge is ‘change management’, and the response to the dynamic nature must be quick.

Furthermore, to understand their knowledge of mental health and experience with the concept, the interviewees were asked if they have experienced issues of mental health and well-being during their professional career and the current practices their organization adopts for the social sustainability of employees. All the participants agreed that though they came across such cases, however, there has been a fear among employees to share information with their employer that ultimately harms the employee’s health. Interviewee P8’s response highlights this fear: “Almost all of my career, the organizations I have worked had a closed environment. So, you know people would not approach you for their problems or the issues that they probably would be facing personally, or professionally, so I have not come across any such case. You know mental health… we used to have training for them. We used to have sessions or seminars. You know actually to deal with these issues. There used to be regular updates and everything. We used to have training for them because you know mental safety is very important in our industry. If they’re not mentally satisfied anymore, it’s very difficult for them to perform their job. So, for them by rules, we had to plan their CRM, so they take a training program which they have to undergo for yearly renewal”. The same was supported by interviewee P1, who said, “Like two to three people are able to express these things, not all our so much expressive to talk about their personality, but I know I can observe also because I’m from this team like social. Social issues I know even I know the melting issues also even sometimes I’m able to understand so I sometimes self-initiated. I understand and I talk to people. Otherwise, people come even I know some of the psychiatrist here. I immediately refer to those psychiatrists also and people take advice and feel comfortable”.

In conclusion, the findings from the interviews resonate with the existing literature, highlighting a common reluctance among employees to openly discuss issues related to mental health and well-being. This underscores the organizational responsibility to ensure the social sustainability of employees by implementing supportive measures that foster an environment conducive to mental well-being.

Furthermore, to understand the issues of successful implementation of social sustainability in construction, the interviewees were asked about their opinion in terms of the challenges and enablers of social sustainability in the industry. From the responses, a lot of similarities were found, where the major issues highlighted were lack of budget, organizational culture for acceptance, conflict with organization vision, risk, and return of investment. Interviewee P3 states, “Well, no doubt the budget is the first. We don’t have a lot of budget for training courses and everything”. Moreover, interviewee P4 agreed: “I think probably you know one of the challenges we face is that it is resources…. We have a very diverse population that we serve in several areas, so it’s not just the… dependence of the staff and so we cover a broad range of clientele, and you know, the people that we bring to serve that population…. they may not always have the necessary expertise that may be needed with such a diverse population, so I would say, yeah, one of the challenges is when you have such a diverse population its being able to match it up with a diversity of resources that’s appropriate for the challenges”. P8 and P6 had similar responses that highlighted change management and the acceptance of organizational culture. Interviewee P7 highlighted the lack of risk taking due to fear of budget limitations and change management.

Therefore, to encapsulate the insights gleaned from the interviewees regarding challenges encountered in the successful implementation of social sustainability, an online Word Cloud generator was employed. The resulting Figure 6 visually represents the challenges discussed by the interviewees.

The generated word cloud visually represents the words that exhibited the highest frequency of adoption during the interviews. Notably, words such as “monitoring”, “budget”, “organization”, “employees”, “health insurance”, “social sustainability”, “ROI”, and “budget” were recurrent in the discussions. This prominence indicates that interviewees placed particular emphasis on these terms throughout their conversations.

Moreover, to explore the current practices of social sustainability by government and organization, the interviewees were first asked, What are the initiatives and policies (if any) by the government that commit your organization to social sustainability? All the interviewees agreed that there are policies by the Ministry of Labor such as WPS, health insurance, fixed hours per week, and annual leave that the organization must be obliged to provide. However, often there are reports on the organizations that have been misusing and manipulating the timesheets and WPS system. Thus, they highlighted the biggest issue is the ‘lack of monitoring’ and proposed that there is a need in the industry for a monitoring framework that allows the Ministry of Labor to ensure the organizations follow their corporate social responsibility, work toward the social sustainability of its employees, and incentivize the organization to fulfill their responsibilities. The findings can be seen from the response of interviewee P2: “Actually, the law is existing there in UAE also, but the implementation and the justification is a separate thing… MOHRE has started to educate the laborers about the basic laws and their rights… but the gap which I feel is that with between that system and MOHRE, I don’t know whether it is interconnected or not connected that should be connected with each other that once the employee arrives within UAE, he should be entitled for monitoring his time and attendance…there should be a system… So, there should be a monitoring system by government”. In addition, interviewee P4 stated: “Well, there I mean, I think that the government certainly sets what is the floor of what we, you know at least how we offer it. Making sure that people are qualified for their positions and so forth, and then what we offer… I don’t know that there is a lot. Intervention, monitoring, or prescription… You know, with respect to the government, I think we have a lot of flexibility in what we can offer overall and so we wouldn’t find you know anything presently that the government has asked us to do that would serve as an impediment to what we want to do”.

Thus, it can be concluded here that the government has policies in place for social sustainability. However, there is a lack of monitoring to ensure the successful implementation of social sustainability.

Finally, the interviewees have been presented with the list of underpinning criteria for employees’ social sustainability identified from the literature as shown in Table 6 in Section 3. They were asked to choose the criteria that they perceived to be relevant to the mental health and social sustainability of the employees. It was found that most of the criteria found in the literature were perceived to be relevant by the experts. Moreover, the interviewees were asked to tailor the criteria to the construction sector, where all the interviewees agreed that the criteria presented were suitable for the construction sector and suggested merging a few of the criteria such as self-efficacy (Personal Accomplishment/Depersonalization) and Burnout/Emotional Exhaustion. This stage helps the study by validating and tailoring the criteria of EMW that were adopted for the survey development.

5.2. Survey Development

This section discusses the findings of the quantitative analysis with the aid of surveys by adopting structural equation modeling to determine the significant criteria of employees’ social sustainability in the targeted audience, i.e., employees in the construction sector.

Demographic profile—The survey targeted employees working in the construction sector including blue- and white-collar employees. The assumption behind the selection of participants was the dynamic nature of the sector that has an impact on the mental health and social sustainability of employees working in the construction sector. A sample of 530 responses was collected from which 506 responses were retained after removing missing values and outliers from the sample data. The demographic profile of the 506 participants was summarized and tabulated in

Table 9. Demographic profile. Source: Authors.

Demographic Characteristics		%
Gender	Female	33.8
	Male	66.2
Position	Entry Level	21.1
	Mid-level	24.6
	Senior Level	32.3
	Managerial Position	22
Years of Experience	1–5	13.7
	5–10	30.06
	10–15	26.24
	15 and above	30.
Education Level	Diploma/High School	13.7
	Graduate	42.5
	Postgraduate	37.4
	Doctoral	6.4
Marital Status	Single	40.9
	Married	56.8
	Divorced	1.3
	Widowed	01
Self-Income	2000–4999 AED	40.7
	5000–9999 AED	18.5
	10,000–14,999 AED	13.5
	15,000–19,999 AED	7.9
	20,000–24,999 AED	9.4
	24,999 and above	10
Contract Type	Open-ended contract (Permanent)	4.8
	Limited-duration contract	24.6
	Contract to perform a specified task.	18.5
	No formal employment contract	52.1
Working Style	Shift system	28.3
	Fixed hours	52.2
	Flexible timings	18.3
	Work from home (Flexible option)	1.2
Sleep Duration	>7 h	19.4
	6–7 h	42.3
	5–6 h	28.1
	<5 h	10.3

.

The table illustrates that the gathered data predominantly reflect employees occupying middle to senior-level positions both at construction sites and in office spaces within the construction sector. The sample predominantly comprises individuals with supervisory roles, line managers, and both on-site and off-site office employees. The data exhibit a balanced distribution across demographic criteria such as gender, position, years of experience, education level, income, etc., without displaying any significant skewness.

Initially, participants were requested to assess their satisfaction and subjective well-being (mental health) using a scale ranging from 1 (Extremely Dissatisfied) to 5 (Extremely Satisfied), as illustrated in Figure 7a,b.

The observations gleaned from Figure 5 indicate a prevailing satisfaction among the majority of participants regarding their jobs and organization. Additionally, participants tended to self-evaluate their subjective well-being as ‘Good’.

Finally, to identify the appropriateness of data collected for factor analysis, the study focuses on determinants such as sample size with Kaiser–Meyer–Olkin (KMO) and Bartlett’s test for sphericity as suggested by [68], where according to [69], the sample size must be 100 or greater, so that the study fulfills the requirements of sample size. The results found indicated a perfectly adequate KMO sampling of 0.943, which is greater than the minimum acceptance value of 0.5 as suggested by [70]. In addition, the test conducted shows Bartlett’s test is significant (chi-square with a degree of freedom (df) 2926 = 17,414.093 with a significance value = 0.000). These findings present a reasonable basis for proceeding to the next stage as it indicates that the data are suitable for factor analysis and dimension reduction.

5.3. Exploratory Structural Equation Modeling

The ESEM method was adopted to allow this study to determine the criteria that have an impact on satisfaction and subjective well-being (employee mental health and well-being) in construction-sector organizations.

Initially, exploratory factor analysis (EFA) based on PCA with Varimax rotation was applied, and criteria with factor loadings below 0.5 were excluded. The analysis yields 11 factors out of 27 criteria related to organizational and social influences on employees’ social sustainability, excluding less impactful personal factors. The factors were interpreted based on the understanding of the criteria of employee’s social sustainability as shown in

Table 10. Exploratory factor analysis.

Factors Interpretation	Criteria	Component
		1	2	3	4	5	6	7	8	9	10	11
Organizational Support (OS)	AS1	0.744
	AS3	0.718
	SC1	0.696
	AS2	0.683
	SC2	0.659
	SC3	0.637
	WW2	0.552
	WW3	0.550
	WW1	0.549
Work–Life Balance (WLB)	WLB3		0.706
	JD3		0.689
	B3		0.688
	WLB1		0.653
	SQ1		0.644
	WLB2		0.636
	B2		0.632
	B1		0.617
Equity Factor	SS1			0.753
	PE2			0.689
	SS3			0.682
	PE3			0.674
	SS2			0.656
	PE1			0.591
	CT1			0.517
Work Control (WC)	WD2				0.747
	FW2				0.717
	WD1				0.709
	WD3				0.706
	FW1				0.681
	FW3				0.666
Gender Equality (GE)	GE1					0.799
	GE2					0.783
	GE3					0.750
Work Environment (WE)	WE2						0.795
	WE1						0.726
	WE3						0.673
Spousal Support (SS)	SO1							0.804
	SO2							0.794
	SO3							0.789
Training and Development (TD)	TD3								0.755
	TD1								0.725
	TD2								0.669
Contract Type (CT)	CT3									0.681
	CT2									0.600
	MI1									0.573
	TP1									0.530
Role Conflict (RC)	RC3										0.774
	RC1										0.754
	RC2										0.728
Job Demand (JD)	JD1											0.907
	JD2											0.518

below.

Thus, the exploratory factor analysis aids the study in identifying the model of social sustainability as shown in Figure 8. The model allows to determine the impact of employee’s social sustainability criteria on the satisfaction and subjective well-being (employee mental health and well-being) in the UAE construction sector.

The subsequent validation of the measurement model involves assessing the goodness of fit.

Validation of Measurement Model—The study computed the goodness of fit for the model. However, to achieve an acceptable goodness of fit, modifications were made to the structural equation model (SEM). Factors deemed unsuitable, including role conflict, spousal support, job demand, and gender equality, were subsequently removed from the model. This adjustment is aimed at refining the SEM to ensure it adequately represents the relationships within the data, enhancing the overall fit of the model.

Following the modifications to the structural equation model (SEM), the analysis achieved acceptable goodness-of-fit values, indicating the model’s appropriateness. The standardized root means square error (SRMSR) is reported as 0.0547, the goodness-of-fit index (GFI) is 0.7350, the adjusted goodness of fit index (AGFI) is 0.6946, and the Bentler comparative fit index (CFI) is 0.8510. These values collectively suggest a reasonable fit for the model.

Furthermore,

Table 11. SEM path list.

Path			Estimate	Standard Error	Pr > |t|
OS_Factor	→	AS1	0.83350	0.01924	<0.0001
OS_Factor	→	AS3	0.84275	0.01837	<0.0001
OS_Factor	→	SC1	0.80169	0.02215	<0.0001
OS_Factor	→	AS2	0.81336	0.02110	<0.0001
OS_Factor	→	SC2	0.64379	0.03509	<0.0001
OS_Factor	→	SC3	0.77830	0.02424	<0.0001
OS_Factor	→	WW1	0.80149	0.02217	<0.0001
OS_Factor	→	WW2	0.79960	0.02234	<0.0001
OS_Factor	→	WW3	0.79513	0.02274	<0.0001
WLB_Factor	→	WLB1	0.78088	0.02531	<0.0001
WLB_Factor	→	WLB2	0.61665	0.03810	<0.0001
WLB_Factor	→	WLB3	0.72671	0.02981	<0.0001
WLB_Factor	→	B1	0.73839	0.02886	<0.0001
WLB_Factor	→	B2	0.76235	0.02688	<0.0001
WLB_Factor	→	B3	0.78794	0.02470	<0.0001
WLB_Factor	→	SQ1	0.63972	0.03647	<0.0001
Equity_Factor	→	SS1	0.74940	0.02822	<0.0001
Equity_Factor	→	SS2	0.78647	0.02512	<0.0001
Equity_Factor	→	SS3	0.71756	0.03080	<0.0001
Equity_Factor	→	PE1	0.76091	0.02727	<0.0001
Equity_Factor	→	PE2	0.77895	0.02575	<0.0001
Equity_Factor	→	PE3	0.80516	0.02352	<0.0001
WC_Factor	→	WD1	0.81986	0.02219	<0.0001
WC_Factor	→	WD2	0.87500	0.01751	<0.0001
WC_Factor	→	WD3	0.75594	0.02761	<0.0001
WC_Factor	→	FW1	0.69651	0.03238	<0.0001
WC_Factor	→	FW2	0.73639	0.02921	<0.0001
WC_Factor	→	FW3	0.67813	0.03379	<0.0001
WE_Factor	→	WE1	0.66840	0.03694	<0.0001
WE_Factor	→	WE2	0.80691	0.02751	<0.0001
WE_Factor	→	WE3	0.85402	0.02487	<0.0001
TD_Factor	→	TD1	0.90200	0.01586	<0.0001
TD_Factor	→	TD2	0.87481	0.01779	<0.0001
TD_Factor	→	TD3	0.83761	0.02071	<0.0001
CT_Factor	→	CT1	0.86021	0.02299	<0.0001
CT_Factor	→	CT2	0.72507	0.03185	<0.0001
CT_Factor	→	CT3	0.61854	0.03952	<0.0001
Satisfaction	→	ST1	0.71951	0.03417	<0.0001
Satisfaction	→	ST2	0.77215	0.03062	<0.0001
Satisfaction	→	ST3	0.62697	0.04050	<0.0001
OS_Factor	→	Satisfaction	0.72982	0.03701	<0.0001
WLB_Factor	→	Satisfaction	0.71952	0.03984	<0.0001
Equity_Factor	→	Satisfaction	0.67295	0.04307	<0.0001
WC_Factor	→	Satisfaction	0.68366	0.04194	<0.0001
WE_Factor	→	Satisfaction	0.50101	0.05643	<0.0001
TD_Factor	→	Satisfaction	0.64036	0.04494	<0.0001
CT_Factor	→	Satisfaction	0.74707	0.04157	<0.0001
MHealth & Well-being	→	MH1	0.76869	0.03189	<0.0001
MHealth & Well-being	→	MH2	0.76853	0.03190	<0.0001
MHealth & Well-being	→	MH3	0.80167	0.03008	<0.0001
Satisfaction	→	MHealth & Well-being	0.65443	0.04539	<0.0001

provides details on the fit of the model concerning indicators and constructs, offering a comprehensive view of how well the SEM aligns with the observed data. This information aids in validating the model and assessing its reliability for further analysis.

The obtained results demonstrate the significance of all indicators, each with a p-value below 0.05 and substantial factor loadings, indicating their relevance to the employee’s job satisfaction and social sustainability (mental health and well-being) in the structural equation model (SEM). The SEM analysis reveals a dependency of employee satisfaction on various social sustainability factors, including organizational support, work–life balance, equity factor, work control, work environment, training and development, and contract type. Additionally, the SEM enables the investigation of relationships between endogenous dimensions (satisfaction) and exogenous dimensions (mental health and well-being).

In further validation, this phase of the analysis aims to test the reliability and validity of the factors listed in

Table 12. Cronbach’s alpha, AVE and composite reliability (CR) scores.

Path	Correlation with Total	Cronbach’s α	CR	AVE	CFA Standardized Parameter Estimate
OS_Factor		0.937	0.938	0.627
AS1	0.812131				0.8335
AS3	0.811009				0.8427
SC1	0.783343				0.8016
AS2	0.774801				0.8133
SC2	0.635945				0.6437
SC3	0.746378				0.7783
WW1	0.764836				0.8014
WW2	0.767629				0.7996
WW3	0.763844				0.7951
WLB_Factor		0.883	0.885	0.525
WLB1	0.721527				0.78088
WLB2	0.576956				0.61665
WLB3	0.699861				0.72671
B1	0.666911				0.73839
B2	0.723411				0.76235
B3	0.721563				0.78794
SQ1	0.597826				0.63972
Equity_Factor		0.895	0.895	0.588
SS1	0.713608				0.7494
SS2	0.729672				0.78647
SS3	0.673369				0.71756
PE1	0.70348				0.76091
PE2	0.731053				0.77895
PE3	0.754649				0.80516
WC_Factor		0.891	0.893	0.583
WD1	0.745093				0.81986
WD2	0.799756				0.875
WD3	0.675178				0.75594
FW1	0.677558				0.69651
FW2	0.720279				0.73639
FW3	0.651264				0.67813
WE_Factor		0.817	0.822	0.609
WE1	0.595499				0.6684
WE2	0.726765				0.80691
WE3	0.692545				0.85402
TD_Factor		0.904	0.905	0.76
TD1	0.834037				0.902
TD2	0.802074				0.87481
TD3	0.794035				0.83761
CT_Factor		0.804	0.782	0.55
CT1	0.592301				0.86021
CT2	0.721637				0.72507
CT3	0.642416				0.61854
Satisfaction		0.741	0.75	0.502
ST1	0.566578				0.71951
ST2	0.660012				0.77215
ST3	0.481252				0.62697
MHealth and Wellbeing		0.822	0.823	0.608
MH1	0.647843				0.76869
MH2	0.690478				0.76853
MH3	0.694938				0.80167

. This involves conducting confirmatory factor analysis (CFA) followed by SEM. The reliability of each construct is assessed using Cronbach’s alpha (α) and composite reliability (CR), both gauging internal consistencies. While Cronbach’s alpha may underestimate true reliability in some cases, CR is considered a more consistent measure. For both indices, a value of 0.5 and above is deemed acceptable, as illustrated in Table 12. This step ensures the robustness and trustworthiness of the constructs before proceeding with subsequent analyses.

As seen in Table 12, it is evident that the composite reliabilities are all above 0.70 with the lowest value for satisfaction being 0.75. Despite this being the lowest value, it still falls within the acceptable range. As both Cronbach’s alpha and composite reliability values meet the specified criteria, the measurement instrument in this study is deemed reliable. Moreover,

Table 13. Discriminant validity.

	OS	WLB	Equity	WC	WE	TD	CT	JD
OS		0.65061 <0.0001	0.67071 <0.0001	0.61044 <0.0001	0.64318 <0.0001	0.66264 <0.0001	0.62891 <0.0001	0.47585 <0.0001
WLB			0.59296 <0.0001	0.62243 <0.0001	0.46176 <0.0001	0.53540 <0.0001	0.58139 <0.0001	0.59160 <0.0001
Equity				0.55247 <0.0001	0.46076 <0.0001	0.56565 <0.0001	0.62665 <0.0001	0.40539 <0.0001
WC					0.43766 <0.0001	0.46478 <0.0001	0.54393 <0.0001	0.38463 <0.0001
WE						0.46072 <0.0001	0.50852 <0.0001	0.31519 <0.0001
TD							0.49950 <0.0001	0.40502 <0.0001
CT								0.42119 <0.0001
JD

below also shows that there is a significant correlation between all eight factors.

The study’s adoption of a mixed-methods approach, incorporating interviews, surveys, and quantitative analysis, particularly employing exploratory structural equation modeling (ESEM), proves instrumental in accurately identifying the presentation and structure of the underlying criteria of employee social sustainability. These eight factors serve as an umbrella, influencing both employee satisfaction and mental health and well-being, as depicted in the path diagram in Figure 6.

The findings from the SEM analysis can be utilized in the future development of a decision-support tool for organizations which would enable informed decision making regarding employees’ social sustainability criteria. This will aid in the enhancement and assurance of social sustainability for employees within the organization. This signifies the practical application and potential utility of the study’s insights for organizational decision-makers in fostering a socially sustainable work environment.

6. Discussion and Conclusions

The study undertakes a thorough exploration of employees’ social sustainability, beginning with a literature review that traces the evolution of mental health definitions. It encompasses the transition from defining mental health as the absence of disease to considering it within the context of well-being and, ultimately, social sustainability. The literature review highlights the global initiatives, evolving concepts, and measurement scales, culminating in the identification of 27 criteria for social sustainability within the realm of employee mental health and well-being (EMW), which was categorized into four groups. To validate and refine these findings, the study employs a mixed-methods approach involving semi-structured interviews and survey development. This methodology aims to determine the significant criteria impacting EMW, subsequently utilizing exploratory structural equation modeling for a quantitative analysis. The interviews further contribute by shedding light on current practices and challenges in implementing employees’ social sustainability policies within organizations.

However, the study has several limitations. First, restricted data access during the COVID-19 pandemic limits the study to accommodate the representation of workers at the construction site. Second, while the study identifies criteria impacting employees’ social sustainability, it does not account for demographic differences, which future research could examine for their effect on model fit. Additionally, the conceptual framework emphasizes human-related issues, such as work environment and work–life balance, without addressing economic and environmental factors, which could be included in future research.

Looking ahead, the identified significant criteria for social sustainability in the UAE construction sector can serve as a foundation for the development of a decision-support tool. This tool can assist organizations in optimizing decision criteria, considering multiple objectives, and guiding decision-makers toward investments that enhance the social sustainability of their employees. For their practical applications, this study, therefore, proposes the adoption of a hybrid framework based on the AHP and the fuzzy MOORA method as an efficient and robust technique to develop a decision support tool that will enable the organization to take strategic decisions to ensure employees’ social sustainability. However, social sustainability in the organization is a dynamic construct that changes over time. The lack of dynamic nature of the classic decision support tool will only allow the organization to re-evaluate their decision quarterly or annually. Therefore, to monitor and ensure the continuous successful implementation of employees’ social sustainability practices, the study proposes the adoption of technologies such as IoT and blockchain to complement the decision-support tool.

Moreover, future work could explore the application of fuzzy neural networks (FNNs) as in [71] to improve social sustainability in the construction sector by analyzing complex mental health data and supporting decision making amid uncertainty. FNNs could help predict the long-term impacts of interventions on employee well-being, allowing for proactive, personalized mental health support and more sustainable workforce planning. The study thus not only provides insights into the present state of employees’ social sustainability but also offers a practical pathway for future organizational decision making in the context of employee well-being.