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Article

From Diversity to Engagement: The Mediating Role of Job Satisfaction in the Link Between Diversity Climate and Organizational Withdrawal

by
Yuvaraj Dhanasekar
and
Kaliyaperumal Sugirthamani Anandh
*
Department of Civil Engineering, Faculty of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur 603203, Tamil Nadu, India
*
Author to whom correspondence should be addressed.
Buildings 2025, 15(13), 2368; https://doi.org/10.3390/buildings15132368
Submission received: 5 June 2025 / Revised: 24 June 2025 / Accepted: 4 July 2025 / Published: 5 July 2025
(This article belongs to the Special Issue Advances in Safety and Health at Work in Building Construction)
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Abstract

Marked by a highly diverse workforce, the Indian construction industry faces ongoing challenges in fostering employee engagement and minimizing organizational withdrawal. This study examines the role of diversity climate in influencing psychological and physical withdrawal behaviors among construction professionals, assessing job satisfaction as a mediating variable. Grounded in Social Exchange Theory, the research employed a quantitative survey approach, gathering responses from 318 professionals across the sector. Partial least squares structural equation modeling (PLS-SEM) was used to test the hypothesized relationships. Results indicate that reduced psychological (β = –0.462, f2 = 0.465, p < 0.01) and physical withdrawal (β = –0.311, f2 = 0.194, p < 0.05) are associated with more positive perceptions of the diversity climate. Furthermore, this relationship is partially mediated by job satisfaction, with diversity climate positively influencing job satisfaction (β = 0.618, p < 0.001), which in turn reduces withdrawal tendencies (indirect effect on psychological withdrawal β = −0.094, p < 0.01 and physical withdrawal β = −0.068, p < 0.01). These results show that encouraging a supportive diversity climate not only helps but is also absolutely necessary for enhancing job satisfaction, lowering withdrawal behavior, and retaining trained talent. The findings offer concrete evidence that construction firms and policymakers should prioritize inclusive human resource strategies that directly improve project outcomes, reduce attrition, and enhance workforce engagement in the Indian construction sector.

1. Introduction

The construction industry significantly impacts employment and infrastructure development, making it a vital contributor to national economies. The sector in India employs over 71 million people and contributes about 9% of the nation’s GDP [1,2]. The sector is projected to experience substantial growth, with forecasts estimating an 8.8% compound annual growth rate between 2025 and 2029, reaching a value of INR 39.10 trillion by 2029. Government initiatives, accelerated urbanization, and increased foreign investment are the primary factors driving this growth. The sector is being influenced by a growing demand for affordable housing, advancements in construction technology, and a growing emphasis on sustainable and green building practices [3]. However, the industry struggles with issues such as labor shortages, high turnover rates, and difficulties in retaining skilled professionals [4]. The project-based nature and rigorous working conditions of the sector aggravate these problems, frequently causing employee job dissatisfaction and withdrawal actions [5,6].
Workplace diversity has become a critical focus in organizational research, particularly in heterogeneous industries like construction. Recent global trends underscore a growing recognition of the value that equality, diversity, and inclusion contribute to organizational effectiveness and societal progress [7]. Diversity refers to the wide range of differences among employees within a specific context, such as race, ethnicity, gender, age, religion, disability, and sexual orientation [8,9]. The construction industry, which relies on a diverse workforce [10], can notably benefit from the various perspectives and experiences of individuals from all backgrounds. Despite the advantages of diversity being well acknowledged, the construction sector still struggles to completely embrace inclusiveness [11], particularly in India. Currently, in India, women make up only 12% of the construction workforce, with 1.4% in technical and managerial positions and fewer than 2% in leadership roles [12]. Similar trends of underrepresentation are seen internationally, with the construction sector in the United States and Australia primarily constituted of white males, and Indigenous or minority groups are significantly marginalized [13]. Systemic barriers, such as gender bias in hiring, inadequate infrastructure support on sites, unequal pay, and restricted access to leadership positions, are responsible for the underrepresentation of women. These barriers are further reinforced by social norms that perceive construction as a male-dominated profession [14]. A recent study conducted by the CII-ILO found that 90% of male professionals acknowledge the sector’s need for increased female participation [15].
Beyond gender differences, India’s construction sector is characterized by significant fragmentation and linguistic diversity; migrant and regional workers often collaborate on projects together. While this diversity introduces valuable skills and perspectives, it also generates communication barriers that reduce operational efficiency. Empirical research shows that language-related misinterpretation directly lowers labor productivity by 15–20% and increases on-site injuries and error risk [16]. These breakdowns are characterized by delayed issue reporting, misinterpreted instructions, and an overreliance on non-verbal signals, which collectively erode morale and exacerbate withdrawal tendencies.
A growing body of research highlights that managing workforce diversity effectively can help address skills shortages and catalyze enhanced productivity, innovation, and organizational competitiveness [17,18]. This is where the concept of diversity climate (DC) becomes particularly relevant.
DC refers to employees’ perceptions of how much their organization values diversity and supports inclusivity [19]. A positive DC creates an inclusive environment, allowing employees to feel valued, respected, and empowered to express their unique talents [20] and perceive less discrimination [21]. This, in turn, has been shown to positively influence various employee outcomes, including job satisfaction (JS), commitment, and employee performance [22], while reducing turnover intention and absenteeism. On the contrary, a negative DC can create a feeling of alienation among employees, especially those belonging to marginalized groups, leading to decreased JS, motivation, and engagement, ultimately leading to organizational withdrawal (OW) [23]. For instance, LGBTQ+ employees in non-inclusive settings are 40% more likely to leave their jobs within two years [24].
OW, encompassing behaviors such as absenteeism, intentions to leave, and actual turnover, poses significant challenges for organizations, especially in industries like construction, where labor shortages and project delays can have extensive consequences. It refers to an employee’s psychological and physical disengagement from their work and the organization [25]. Understanding the factors that influence OW is crucial for developing strategies to enhance employee retention and organizational effectiveness.
Several complicated mechanisms drive the relationship between DC and organizational outcomes. Recent research indicates that JS is a significant mediator in this setting. JS is a critical metric for evaluating employees’ perceptions of their work environment and their function within the organization. It is defined as a positive emotional state that arises from evaluating one’s job or job experiences [26]. High levels of JS are associated with positive work attitudes and behaviors, including increased organizational commitment and reduced turnover intentions [22,27]. Therefore, fostering a positive DC can enhance JS, thereby mitigating the risk of OW.
Despite the well-established link between DC and employee outcomes, the specific mechanisms through which DC affects OW in the Indian construction context remain underexplored. This gap in research is of particular significance in view of India’s unique construction workforce, which is influenced by linguistic diversity, high levels of internal migration, and persistent gender imbalances [12,16]. This study provides an empirical extension within the Indian AEC sector, with a focus on construction professionals, whereas most prior research on DC has focused on Western countries. In a novel way, it examines the mediating role of JS in transforming DC perceptions into fewer withdrawal behaviors. This perspective provides novel insights for creating diversity-sensitive HR policies that are tailored to the unique needs of the Indian construction sector. Based on the social exchange theory (SET), which posits that employees respond to favorable organizational treatment with good attitudes and behaviors [22], this study uses a quantitative survey method to collect responses from construction professionals across India. The study has two primary objectives. First, to examine the direct impact of DC perceptions on the OW dimensions of construction professionals in India, and second, to investigate the mediating role of JS in this relationship. Exploring this mediation seeks to provide insights into how a positive DC can enhance JS and, in turn, reduce OW behaviors. This research contributes to the growing literature on diversity management by highlighting its practical implications for improving employee retention and organizational performance in the Indian construction sector.

2. Theoretical Background

2.1. Diversity Climate Perceptions and Organizational Withdrawal

DC, referring to employees’ shared perceptions of the level to which their organization supports diversity, has been extensively studied for its impact on various organizational outcomes [28,29,30]. Previous research has identified that a positive DC enhances JS, organizational commitment, and employee engagement and reduces turnover intention [29,31]. Conversely, negative perceptions of DC, particularly among underrepresented groups, are associated with lower levels of satisfaction and engagement [32], often resulting in increased turnover or withdrawal behaviors.
OW is a significant concern for organizations, encompassing both physical (e.g., absenteeism, turnover) and psychological (e.g., daydreaming, reduced effort) disengagement from work [33,34,35]. While physical withdrawal (PW) involves observable actions that remove employees from the workplace, psychological withdrawal (PSW) signifies mental detachment despite physical presence. Organizational factors such as inadequate communication, lack of recognition, and limited development opportunities, together with individual characteristics like work/life imbalance and stress management capabilities, significantly contribute to the development and escalation of the withdrawal behaviors [36,37,38,39].
Previous research in various sectors demonstrates that a positive DC significantly reduces employee turnover intentions [31,40,41]. Inclusive workplaces foster increased employee commitment and engagement [29]. According to Jolly and Self [42], diverse workplaces provide valuable resources for employees, reducing their likelihood of leaving. Conversely, a negative DC breeds discrimination and exclusion, particularly among minority groups, leading to increased turnover intentions [43]. These findings underscore the crucial role of a supportive DC in mitigating negative perceptions, enabling a sense of belonging, and ultimately retaining valuable talent within organizations.
Based on the literature study, the following hypotheses were proposed.
H1: 
DC perception is negatively related to the PSW behavior of construction professionals.
H2: 
DC perception is negatively related to the PW behavior of construction professionals.

2.2. Diversity Climate Perceptions and Job Satisfaction

Research indicates that environments that support and retain a multicultural workforce enhance positive work attitudes, including JS [44]. JS refers to the level of contentment that an employee experiences with the work environment and workplace conditions [45]. Organizations that actively advocate for diversity-oriented policies and inclusive workplace environments augment employees’ sense of belonging and engagement, resulting in heightened JS [46]. A healthy DC mitigates workplace disparities by cultivating an environment in which employees, irrespective of their ethnic backgrounds, experience equitable treatment, equal chances, and respect from others [47].
Employees who feel valued and included are more likely to develop affective commitment towards their organization, exhibit greater levels of motivation, and increase overall JS [48,49]. This is especially pronounced for individuals from under-represented groups, as an inclusive DC reduces the negative effects of workplace discrimination, improves career advancement opportunities, and fosters psychological safety [50]. In addition, organizations with robust diversity cultures exhibit effective leadership and impartial HR practices, which collectively enhance employee involvement and satisfaction [51].
In general, when employees believe their firm is genuinely committed to diversity and inclusion, they tend to feel more satisfied with their jobs. This increased satisfaction leads to greater organizational commitment and a lower likelihood of intention to leave [31]. Thus, creating a strong and positive DC is not just the right thing to do; it is also a smart strategy for improving employee satisfaction and boosting overall organizational performance.
Based on the above, the following hypothesis was framed.
H3: 
DC perception positively influences JS among construction professionals.

2.3. Job Satisfaction and Organizational Withdrawal

JS serves as a vital predictor of numerous organizational outcomes, such as employee turnover and withdrawal behaviors. Numerous studies have proven that higher levels of JS are associated with lower intentions to quit [52] and with lower absenteeism at work [37]. Employees who experience higher levels of JS are more likely to feel appreciated, engaged, and devoted to their organization, which reduces their desire to withdraw [53]. In particular, JS reduces PSW, including disengagement and reduced mental involvement, as well as PW behaviors like absenteeism and turnover [54]. This is because JS provides a sense of connection and belonging inside the workplace, reducing the negative emotions and feelings of dissatisfaction that can lead to withdrawal [55]. In settings such as the construction industry, where job stress, along with job demand, is common, promoting JS is increasingly important for reducing such withdrawal behavior.
Therefore, it is hypothesized that:
H4: 
JS negatively influences PSW among construction professionals.
H5: 
JS negatively influences PW among construction professionals.

2.4. Job Satisfaction as a Mediator

JS plays an important role in mediating the relationship between DC and OW dimensions, shaping how perceptions of inclusion and fairness translate into employee retention behaviors. The relationship between JS and reduced OW has been consistently demonstrated in research. For instance, Lee et al. [56] identified that dissatisfaction is the primary driver of employee turnover. Rubenstein et al. [57] emphasized in a meta-analysis that JS is a critical factor in reducing turnover, thereby validating its role as an intermediary between workplace perceptions and withdrawal outcomes. Moreover, a positive DC enhances employees’ sense of belonging, which, in turn, increases JS and reduces turnover intentions [58,59]. Kaur et al. [40] empirically established that inclusion and JS sequentially mediate the relationship between DC and turnover intention. Based on this, the following hypotheses were framed.
H6: 
JS mediates the relationship between DC perceptions and PSW among construction professionals.
H7: 
JS mediates the relationship between DC perceptions and PW among construction professionals.

2.5. Theoretical Support: Social Exchange Theory

SET offers a strong basis for understanding the relationship between DC perceptions, OW dimensions, and JS by emphasizing the reciprocal nature of social interactions in the workplace [60]. SET posits that organizational relationships are influenced by the exchange of valued resources, both tangible (e.g., rewards, career opportunities) and intangible (e.g., trust, fairness, respect), which subsequently affect employee attitudes and behaviors [61,62]. A positive DC indicates that a company is committed to fairness and inclusivity, increasing employee loyalty and job satisfaction. According to SET, when employees who experience fairness and inclusivity develop positive affective ties to the organization, leading to increased job engagement, reduced absenteeism, and lower turnover intentions [63]. In contrast, employees who perceive a weak DC marked by unfairness, exclusion, or discrimination may feel undervalued and unsupported, which would cause discontent and withdrawal behaviors like low commitment, absenteeism, and intent for job search [64]. This aligns with SET’s assertion that imbalanced or negative interactions reduce employees’ willingness to make positive contributions to the company, which finally results in psychological and physical withdrawals [65]. Thus, SET provides a strong theoretical foundation for understanding how DC influences OW through JS as a mediator, reinforcing the importance of fostering inclusive and equitable workplace environments.
Figure 1 represents the conceptual model, which proposes that DC perceptions affect the OW dimensions, with JS mediating the relationship. H1 and H2 indicate the direct effect of DC perceptions on the OW dimensions. Similarly, H3 represents the direct effect of DC perceptions on JS, while H4 and H5 represent the effect of JS on the OW dimensions. H6 and H7 represent the mediating effect of JS.

3. Methodology

The current study collected responses through a quantitative survey involving construction professionals working full-time in private construction firms across different regions of India. The professionals included both on-site and office roles. This approach efficiently collects data from large and diverse samples, allowing robust statistical analyses to uncover significant relationships [6,66].

3.1. Sample and Data Collection

Target samples were obtained through referrals using snowball sampling, a nonprobability method utilized in construction management research [67,68]. A total of 400 professionals were selected using this procedure, and 318 answered the questionnaires. This yielded a response rate of 79.5%, above the 68% average [69]. Respondents encompass a spectrum of professional positions within the Indian construction sector, such as Senior Project Managers, Engineering Managers, Project Managers, Site Engineers, Design Engineers, Detailing Engineers, BIM Modelers, and Quality Control Engineers. Hair et al. [70] suggest that a sample size of at least 150 is adequate for models with up to seven constructs, each containing more than three items. Given this, the 318 responses were sufficient for structural equation modeling. Among them, 213 were male and 105 were female. The higher proportion of females (33%) is primarily due to the inclusion of office-based roles where female participation is higher. The gender distribution is consistent with the emerging employment trends in private-sector construction firms, as over 60% of respondents were from office environments. The inclusion of a broader demographic was further facilitated by the snowball sampling approach, which provided access to closely connected networks within these domains.
Most participants were aged 29 to 38 (56.6%), with those aged 18–28 (30.5%) following in that order. In addition, the sample was educationally diverse, with 69.5% of the participants possessing undergraduate degrees, while the remaining 19.2%, 7.2%, and 4.1% held postgraduate qualifications, diplomas, or doctorates. A mature and experienced sample was indicated by the fact that 67.3% of the participants had 6 to 15 years of industry experience. Additionally, the participants were dispersed across various work environments, with 61% of them employed in offices, 25.8% on construction sites, and 13.2% in both contexts.
Figure 2 depicts the demographic profile of the survey respondents.
The Institutional Ethics Committee approved the ethical considerations (EC No.:8776/IEC/2024). The study’s purpose, data nature, and intended use were disclosed to the respondents. The study followed the guidelines established by Podsakoff et al. [71] to mitigate common method bias (CMB) by guaranteeing confidentiality, affirming that no responses were correct or incorrect, and reverse-scoring specific items. CMB was not a significant issue, as Harman’s single-factor test showed that a single factor explained just 33.5% of the variance, less than the 50% threshold [72].

3.2. Measures

A composite 21-item scale, combining measures from the Diversity Perceptions Scale by Mor Barak et al. [73] and the Marginalized-Group-Focused Diversity Climate Scale (MGF-DCS) by Sakr et al. [23], was used to assess DC perceptions. The scale evaluates four dimensions: Fairness (5 items), Inclusion (5 items), Interpersonal Valuing (5 items), and Anti-discrimination (6 items). Sample items include “Pay and benefits are distributed equitably across all employee groups, regardless of background” and “Layoff decisions are made without bias, considering only job performance and organizational needs”. Participants rated their agreement using a 5-point Likert scale ranging from 1 (Strongly Disagree) to 5 (Strongly Agree), with higher scores indicating a more favorable perception of the DC.
OW dimensions, PSW and PW, were assessed using the withdrawal behavior scale developed by Erdemli [74]. The scale consists of nine PSW items and seven PW items, with ratings ranging from 1 (Never) to 5 (Always). The items of the original scale were modified to fit the context of the construction industry. Sample items include “Being occupied with irrelevant things during working hours” and “Constantly checking the time”.
A six-item scale created by Brayfield and Rothe [75] was used to measure JS. Sample items include “I am satisfied with the work I do” and “I am satisfied with the opportunities that exist in this organization for advancement (promotion)”. A 5-point Likert scale ranging from 1 (Strongly Disagree) to 5 (Strongly Agree) was used to measure the level of satisfaction. Despite the fact that JS was modeled as a single latent construct in the SEM analysis, the items employed in this study indicate distinct and significant aspects of satisfaction, such as satisfaction with work content, supervision, remuneration, co-worker relationships, and career advancement opportunities. This multi-item approach enables a more comprehensive representation of JS, even when analyzed as a unified construct.
A pilot study was conducted initially to assess the reliability, relevance, and clarity of the modified questionnaire before the full-scale launch of the survey. This involves 85 construction professionals. The feedback received from professionals helped refine several items across all constructs to better align with the professional setting and vocabulary. The internal consistency metrics derived from the pilot study demonstrated adequate reliability for all constructs employed in the research.
The complete list of the questionnaire items of all constructs used in the study is presented in Table 1.

4. Analysis

The study employed SPSS V23.0 for descriptive statistics and correlation analysis and SmartPLS V3.2.9 for instrument validation and hypothesis testing. PLS-SEM is a statistical method effective at handling complex models characterized by a higher number of observed indicators, multiple latent constructs, and mediating or moderating variables. This is particularly relevant for studies with small to medium sample sizes, where traditional covariance-based SEM may be inappropriate [67]. It reduces unexplained variance in dependent variables while enhancing explained variance from independent variables [70]. The PLS-SEM procedure has two phases: evaluating the measurement model and assessing the structural model to analyze and interpret research findings.

4.1. Descriptive Statistics and Correlation Matrix

Table 2 summarizes the descriptive data, including mean, standard deviation (SD), and correlation matrix. The mean values indicate that DC (M = 3.634), PSW (M = 2.886), and PW (M = 2.798) exhibit moderate levels, while JS (M = 3.746) is relatively higher. A strong negative correlation is observed between DC and both PSW (r = −0.783, p < 0.01) and PW (r = −0.665, p < 0.01), suggesting that a positive DC reduces withdrawal behaviors. Additionally, JS is positively associated with DC (r = 0.736, p < 0.01) but negatively correlated with PSW (r = −0.807, p < 0.01) and PW (r = −0.762, p < 0.01), indicating that higher JS is linked to lower withdrawal tendencies. Furthermore, a strong positive relation prevails between PSW and PW (r = 0.811, p < 0.01), suggesting a close relationship between the two withdrawal dimensions.

4.2. Measurement Model

The assessment of the measurement model, as presented in Table 3, demonstrates that the constructs exhibit strong psychometric properties. All standardized outer loadings exceed the recommended threshold of 0.70, indicating that the items effectively measure their respective constructs. Furthermore, the variance inflation factor (VIF) values are well below the critical value of 5, suggesting the absence of multicollinearity issues among the items. Reliability and validity assessments demonstrated that composite reliability (CR) estimates, average variance extracted (AVE) values, and Cronbach’s alpha (CA) coefficients were all above the thresholds of 0.7, 0.5, and 0.7, respectively, signifying strong internal consistency and convergent validity [70].
The discriminant validity results, assessed using the Fornell & Larcker criteria shown in Table 4, demonstrate that the square root of the AVE (indicated along the diagonal) for each construct exceeds the correlations between constructs, establishing distinctiveness among them [76].

4.3. Structural Model

The structural model was analyzed using a two-step approach to test hypotheses and evaluate model metrics such as coefficient of determination (R2), effect size (f2), and predictive relevance (Q2) [70]. The first step involved assessing the standardized path coefficients using the PLS algorithm in SmartPLS V3.2.9. The second step utilized bootstrapping with 5000 resamples to calculate p-values, t-values, and confidence intervals for each path coefficient. The Standardized Root Mean Square Residual (SRMR) was 0.0754, the d_ULS was 0.632, the d_G was 0.928, and the Normed Fit Index (NFI) was 0.914, all showing a satisfactory model fit. These values conform to established criteria, with an SRMR below 0.08 and an NFI of 0.90 signifying a satisfactory model fit [77].
Table 5 summarizes the findings, indicating the strength and direction of the relationships between constructs and the significance of the tested hypotheses.
The results indicate that DC perceptions have a significant negative effect on both PSW (β = −0.462, t = 2.718, p < 0.01) and PW (β = −0.311, t = 2.172, p < 0.05), thereby confirming the hypotheses H1 and H2. This implies that on their respective scales, PSW is expected to decrease by around 0.462 units and PW by roughly 0.311 units for every one-unit improvement in the perception of DC by a construction professional. In simple terms, enabling a more inclusive workplace directly results in reduced levels of both psychological and physical disengagement. Furthermore, the results confirm H3, indicating a robust positive relationship between DC and JS (β = 0.618, t = 5.518, p < 0.001). This strong coefficient implies that a one-unit increase in perceived DC is associated with a substantial 0.618-unit increase in JS, underscoring the profound positive impact of inclusivity on employee contentment. These findings indicate that construction professionals’ satisfaction levels are increased and withdrawal behaviors are diminished when they hold a favorable opinion of DC.
JS was found to negatively influence both PSW (β = −0.406, t = 2.330, p < 0.05) and PW (β = −0.342, t = 2.707, p < 0.01), supporting H4 and H5. Specifically, a one-unit increase in JS is associated with a decrease of approximately 0.406 units in PSW and 0.342 units in PW, demonstrating the direct role of JS in mitigating disengagement. The study also assessed the mediating role played by JS in the relationships between DC and both PSW and PW. Mediation is considered statistically significant when the indirect effect of an independent variable on a dependent variable through a mediator is significant [78]. As illustrated in Table 5, the relationship between DC and PSW (β = −0.094, t = 2.653, p < 0.01) and between DC and PW (β = −0.068, t = 2.617, p < 0.01) is mediated by JS, supporting the hypotheses H6 and H7. These indirect effects suggest that a positive DC enhances JS, which then consequently reduces both PSW and PW behaviors. For instance, the positive influence of DC on JS indirectly contributes to a 0.094-unit reduction in PSW and a 0.068-unit reduction in PW. While the indirect effects are statistically significant, they are smaller than the direct effects, indicating that the mediation partially explains the link between DC and withdrawal behaviors. These findings highlight that DC primarily reduces withdrawal directly but is also mediated by its positive influence on JS, indicating that while JS partially mediates these relationships, its contribution is meaningful. The structural model, including path coefficients and p-values, is presented in Figure 3.
To evaluate the model’s in-sample predictive power, the coefficient of determination (R2) was analyzed for the endogenous constructs. The R2 values for PSW (R2 = 0.323) and PW (R2 = 0.287) suggest moderate levels of predictive accuracy, while the value for JS (R2 = 0.542) indicates substantial predictive strength [79]. Specifically, DC perceptions and JS within the model help to explain over 32.3% of the variation in PSW and 28.7% of the difference in PW among construction professionals. Moreover, DC perceptions explain more than half (54.2%) of the variance in JS, suggesting a quite significant explanatory power for this relation. Furthermore, the effect size (f2) was examined to determine the contribution of each exogenous variable to the R2 values of the endogenous variables [80]. As shown in Table 4, the effect of DC on JS (f2 = 0.734) was large, while its effect on PSW (f2 = 0.465) and PW (f2 = 0.194) ranged from strong to moderate, respectively. These findings highlight the substantial influence of DC perceptions on JS and withdrawal dimensions.
The predictive relevance of the model (out-of-sample) was further assessed using the Stone–Geisser Q2 index obtained through a blindfolding procedure [81]. All Q2 values for the endogenous variables—PSW (Q2 = 0.271), PW (Q2 = 0.145), and JS (Q2 = 0.412), were greater than zero, indicating that the model exhibits strong predictive relevance.
Diagnostic tests carried out as part of the model evaluation process verified the validity and stability of the findings. Under bootstrapping with 5000 resamples, all path coefficients remained consistently statistically significant. VIF values for every predictor construct were below the recommended threshold of 5 [70], indicating no multicollinearity issues. These findings reinforce the robustness of the model and the reliability of its conclusions.

5. Discussion

The current study provides valuable insights into the interplay between DC perceptions, OW dimensions, and JS within the construction sector. Grounded with SET, the results highlight the critical role of DC perceptions in shaping organizational outcomes, particularly within the Indian construction sector.
The results indicate that DC perceptions have a substantial negative effect on PSW and PW dimensions. This implies that a positive DC can decrease the likelihood of OW among construction professionals. This finding aligns with previous research that confirmed a negative relationship between DC perceptions and turnover intentions and OW [40,41,82]. A positive DC develops a feeling of belonging and inclusion among the employees, thereby reducing the feeling of alienation and isolation, which are key contributors to withdrawal behaviors [83]. In the predominantly male-dominated construction sector, where project sites often involve employees from diverse linguistic and cultural backgrounds [84], a strong DC can bridge these differences and create a more cohesive work environment. In addition, employees are more likely to trust their organization and colleagues when they perceive an equitable and inclusive environment, which leads to increased commitment and reduced withdrawal [82]. The increased inclusion of underrepresented groups, such as female professionals, has been shown to augment their satisfaction levels and mitigate their intention to exit the organization [85].
Furthermore, the stronger negative impact of DC perceptions on PSW compared to PW provides new evidence that diversity initiatives primarily address employees’ psychological and emotional disengagement rather than their perceptions of PW. This is because diversity initiatives are designed to promote an inclusive and supportive workplace, catering to employees’ emotional and belonging needs. As a result, these initiatives are more effective in mitigating PSW, which is closely associated with employees’ emotional engagement, than PW, which is influenced by a broader range of factors, including job demands, work/life balance, personal circumstances, etc. [5,86]. Additionally, in the Indian context, where cultural norms emphasize maintaining harmony and respecting authority [87], employees are more likely to engage in PSW and suppress negative emotions rather than resorting to visible PW.
The study also found the partial mediating role of JS in the relationship between DC perceptions and PSW and PW. This suggests that fostering a diverse workplace can improve JS, which lowers the risk of people leaving the organization. This is in line with previous studies that have highlighted the mediating role played by JS in the relationship between DC perceptions and staff withdrawal [40,88]. Higher levels of JS are more likely to be experienced by employees when they feel included, respected, and treated equitably. This, in turn, can buffer against the adverse consequences of workplace stressors, including heavy workloads, extended working hours, and safety concerns, which are common in the construction sector [5,86], thereby reducing their intention to leave the organization. Additionally, a positive DC can improve communication and collaboration among employees from various backgrounds, resulting in a more engaging work experience, better problem-solving, and innovation, ultimately increasing JS and reducing withdrawal [89].
The mediating role of JS can be further understood by SET [61]. A positive DC indicates that the organization is dedicated to creating an equitable and inclusive workplace and values the employees’ contributions. This develops a sense of trust and reciprocity, encouraging employees to reciprocate with positive attitudes and behaviors, such as increased JS and reduced withdrawal [60].
Overall, this study supports McKay et al.’s [29] assertion that a positive DC reduces negative workplace behaviors and increases employee retention. It also aligns with Nishii’s [47] emphasis on the vital role of perceived fairness and inclusivity in attaining favorable organizational outcomes. While earlier studies have mainly focused on corporate or educational settings [19,90], this research extends the DC framework to the Indian construction industry, addressing a vital research gap. Furthermore, the results strengthen the research conducted by Jaiswal and Dyaram [91], which identified DC as an important indicator of employee well-being. Despite these contributions, the partial mediation effect of JS implies that the relationship between DC and OW may also be explained by other factors, such as leadership styles and perceived organizational support. In order to give a more thorough understanding of workplace withdrawal behaviors, future research could examine these factors.

6. Implications

The findings of this study offer policymakers, managers, and construction organizations in India a variety of practical insights to promote a positive DC and reduce OW. The findings highlight how an inclusive workplace not only reduces withdrawal behaviors but also significantly enhances JS, hence improving employee engagement and reducing turnover intention. Organizations should prioritize implementing equitable and transparent human resource (HR) policies, particularly in recruitment, performance evaluation, and conflict resolution. This ensures fairness, which is essential for a positive DC and helps to improve JS. Professionals who experience fair treatment develop more value and belonging, which directly boosts their satisfaction level and helps to lower their desire to leave the organization. Regular diversity training programs should be introduced to create awareness and reduce unconscious bias across teams. Such initiatives create inclusive environments where diverse perspectives are encouraged and respected. This not only boosts morale but also helps professionals feel more valued, which is critical in high-pressure engineering roles that demand collaboration, decision-making, and clear communication.
Given the significant proportion of men working in Indian construction, it is imperative to design focused initiatives encouraging women’s involvement and retention. Policies on workplace safety, adaptable working schedules, and nondiscriminatory career opportunities directly address barriers faced by underrepresented groups, thereby promoting gender balance, improving JS, and lowering turnover. These initiatives primarily benefit managers and engineers, particularly by creating a more inclusive leadership pipeline and fostering a more diverse and skilled workforce for project delivery.
Further, with India’s linguistically and culturally diverse population, it is crucial that construction firms invest in communication mechanisms to facilitate cooperation among heterogeneous groups. Multilingual training programs, inclusive team-building activities, and cross-cultural seminars help to close current cultural gaps and foster belonging. These measures not only enhance team cohesion but also directly assist construction managers and employees in effectively fulfilling their engineering and coordination responsibilities.
Government agencies and professional bodies can also help encourage organizations to implement and maintain diversity-friendly practices by providing incentives such as certifications, awards, or tax benefits. Finally, organizations should provide support systems like counselling or mentor programs to reduce workplace stressors and mitigate PSW among employees. These programs directly improve the capacity of professionals to effectively manage projects and teams by addressing their emotional well-being, which in turn enhances JS and empowers them to remain engaged and committed to their duties. This comprehensive approach is essential for the Indian construction industry to retain skilled personnel and improve overall organizational performance.

7. Limitations and Future Directions

While providing valuable insights into the dynamics of DC, OW dimensions, and JS, the present study has some limitations. The cross-sectional design and regional emphasis of the study might restrict the generalizability and causal interpretation of the results. Although CMB is not an issue in the study, social desirability bias may still be a concern due to the self-reported data. Additionally, although effective at reaching diverse and underrepresented professionals in the industry, especially women in office-based professions, snowball sampling remains a non-probabilistic technique that can restrict the statistical representativeness of the sample. Future works should rectify these limitations by employing longitudinal designs to learn about the long-term effects and extend the scope to other regions and sectors within and beyond India. The use of mixed-method approaches, which incorporate qualitative techniques such as focus groups or interviews, would provide a more sophisticated understanding of the lived experiences of employees. Further, exploring the effects of specific JS components may reveal which aspects most strongly influence withdrawal behaviors. Including additional variables, like perceived organizational politics, organizational support, and leadership styles as mediators or moderators, could provide deeper insights into the mechanisms influencing DC and OW. Investigating additional outcomes, including employee commitment, performance, and engagement, would also achieve a more comprehensive understanding of the organizational significance of DC. Future studies should additionally consider demographic factors into account as control or moderating variables to capture possible subgroup variations and enhance the validity of the findings.

8. Conclusions

This study highlights the vital role of DC perceptions in mitigating OW dimensions among construction professionals in India. Conforming to social exchange theory, the results indicate that a positive DC promotes inclusivity, belonging, and trust, thereby minimizing alienation and withdrawal behaviors. Additionally, the partial mediating role of JS underscores its importance in buffering workplace stressors, enhancing workforce sustainability, and promoting employee retention. By bridging linguistic and cultural differences, a robust DC enables a cohesive work environment, particularly in the male-dominated construction sector. The findings imply that an inclusive and encouraging workplace could assist in reducing psychological and physical withdrawal activities, therefore stressing the need for diversity management in the construction industry. Future studies should look at other mediating factors, including perceived organizational support or leader inclusivity, and investigate the generalizability of these results across several organizational environments and occupational groups within the construction sector.

Author Contributions

Conceptualization, Y.D.; methodology, Y.D. and K.S.A.; software, Y.D.; validation, Y.D. and K.S.A.; formal analysis, Y.D.; investigation, Y.D.; resources, Y.D.; data curation, Y.D.; writing—original draft preparation, Y.D.; writing—review and editing, K.S.A.; supervision, K.S.A. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
AVEAverage variance extracted
CACronbach’s alpha
CRComposite reliability
CMBCommon method bias
DCDiversity climate
f2Effect size
JSJob satisfaction
NFINormed fit index
OWOrganizational withdrawal
PSWPsychological withdrawal
PWPhysical withdrawal
PLS-SEMPartial least squares structural equation modeling
Q2Predictive relevance
R2Coefficient of determination
SETSocial exchange theory
SEMStructural equation modeling
SPSSStatistical package for social sciences
SRMRStandardized Root Mean Square Residual
VIFVariance inflation factor

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Buildings 15 02368 g001
Figure 1. Conceptual model.
Figure 1. Conceptual model.
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Figure 2. Demographic profile (N = 318).
Figure 2. Demographic profile (N = 318).
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Figure 3. Structural model.
Figure 3. Structural model.
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Table 1. List of questionnaire items.
Table 1. List of questionnaire items.
ConstructItem CodeItem Description
DC—FairnessA1Promotion decisions are based solely on job performance and qualifications, without regard for factors like race, gender, or age.
A2Pay and benefits are distributed equitably across all employee groups, regardless of background.
A3My organization ensures that all employees have equal access to professional development opportunities.
A4I often feel that my contributions are overlooked compared to those of my colleagues from different backgrounds. (Reverse-coded)
A5Layoff decisions are made without bias, considering only job performance and organizational needs.
DC—InclusionB1My organization actively seeks to create a sense of belonging for all employees, regardless of their background.
B2Employees from diverse backgrounds are involved in key decision-making processes.
B3My organization promotes the inclusion of employees from all backgrounds in social and work-related activities.
B4There are clear initiatives in place to support the inclusion of employees from underrepresented groups (e.g., women, minorities).
B5I believe that my organization values the unique contributions of all employees, regardless of their background.
DC—Interpersonal ValuingC1My colleagues and I openly share ideas and perspectives, regardless of our differences.
C2Employees in my organization respect and appreciate the cultural differences of their colleagues.
C3I feel comfortable interacting with colleagues from different cultural or social backgrounds.
C4I occasionally feel that my ideas are dismissed because of my background. (Reverse-coded)
C5Managers actively seek input from employees of different demographic groups in problem-solving and decision-making.
DC—Anti-discriminationD1The organization has clear procedures in place for reporting and addressing incidents of discrimination.
D2Managers are committed to eliminating any forms of bias and discrimination within the workplace.
D3The organization responds quickly and effectively to any incidents of discrimination.
D4I sometimes worry that reporting discrimination may lead to negative consequences for me. (Reverse-coded)
D5I feel safe from discrimination in my workplace.
D6There is a culture of intolerance towards discrimination, which is reinforced by the organization’s leadership.
PSWPSW1I often find myself occupied with irrelevant things at work.
PSW2I frequently surf the web or use the internet for non-work purposes.
PSW3I put effort into looking busy, even when I’m not actually working.
PSW4I often chat with colleagues about non-work-related topics.
PSW5I constantly check the time, waiting for the workday to end.
PSW6I put in less effort than what is normally expected of me at work.
PSW7I spend time making long personal calls during work hours.
PSW8I often talk about wanting to leave the company.
PSW9I frequently ask others to do tasks that are my responsibility.
PWPW1I take leave or sick days even when I am not actually sick.
PW2I arrive late for work without a valid reason.
PW3I leave work early without obtaining permission.
PW4I avoid participating in important meetings or company events (e.g., performance reviews, group meetings).
PW5I do not return to the office or site after completing off-site work early.
PW6I take longer breaks than I am allowed.
PW7I often disappear from the worksite or office without informing anyone.
JSJS1I am satisfied with the work I do.
JS2I am satisfied with my supervisor.
JS3I am satisfied with the relations I have with my co-workers.
JS4I am satisfied with the pay I receive for my job.
JS5I am satisfied with the opportunities that exist in this organization for advancement (promotion).
JS6All things considered; I am satisfied with my current job situation.
Table 2. Descriptive statistics and correlation matrix of the variables.
Table 2. Descriptive statistics and correlation matrix of the variables.
VariableMeanSDDCPSWPWJS
DC3.6341.1351
PSW2.8860.985−0.783 **1
PW2.7981.04−0.665 **0.811 **1
JS3.7461.2520.736 **−0.807 **−0.762 **1
** Correlation is significant at the 1% level.
Table 3. Measurement model.
Table 3. Measurement model.
ConstructItemOuter LoadingsVIFCArho_aCRAVE
DCA10.8612.7500.8960.9270.9810.714
A20.9213.228
A30.7901.942
A40.8442.680
A50.8152.515
B10.9113.126
B20.8052.504
B30.8372.243
B40.7761.640
B50.8302.311
C10.8121.951
C20.8452.132
C30.8062.051
C40.8111.982
C50.8652.253
D10.8772.864
D20.9223.352
D30.7881.892
D40.8842.731
D50.8672.615
D60.8542.401
PSWPSW10.8162.0200.9030.9280.9570.717
PSW20.9152.971
PSW30.8732.350
PSW40.8412.226
PSW50.8272.332
PSW60.8112.172
PSW70.9133.237
PSW80.8922.560
PSW90.9113.138
PWPW10.8732.5770.8960.9150.9440.707
PW20.8251.922
PW30.8182.148
PW40.9223.156
PW50.7481.867
PW60.8652.366
PW70.8232.030
JSJS10.8012.1220.8780.8900.9360.708
JS20.7872.133
JS30.8342.443
JS40.8512.677
JS50.8912.984
JS60.8792.352
Table 4. Discriminant validity.
Table 4. Discriminant validity.
ConstructDCPSWPWJS
DC0.845
PSW−0.7830.846
PW−0.6650.8110.840
JS0.736−0.807−0.7620.841
Table 5. Structural model outcomes.
Table 5. Structural model outcomes.
HypothesisPathsβSDT-StatisticsR2f2Q2Decision95% Confidence Interval
H1DC → PSW−0.4620.172.718 **0.3230.4650.271Supported−0.795, −0.129
H2DC → PW−0.3110.142.172 *0.2870.1940.145Supported−0.592, −0.030
H3DC → JS0.6180.1125.518 ***0.5420.7340.412Supported0.398, 0.838
H4JS → PSW−0.4060.1742.330 *---Supported−0.748, −0.064
H5JS → PW−0.3420.1262.707 **---Supported−0.590, −0.094
H6DC → JS → PSW−0.0940.0352.653 **---Supported−0.163, −0.024
H7DC → JS → PW−0.0680.0262.617 **---Supported−0.119, −0.017
* Significance at the 5% level ** Significance at the 1% level *** Significance at the 0.1% level.
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Dhanasekar, Y.; Anandh, K.S. From Diversity to Engagement: The Mediating Role of Job Satisfaction in the Link Between Diversity Climate and Organizational Withdrawal. Buildings 2025, 15, 2368. https://doi.org/10.3390/buildings15132368

AMA Style

Dhanasekar Y, Anandh KS. From Diversity to Engagement: The Mediating Role of Job Satisfaction in the Link Between Diversity Climate and Organizational Withdrawal. Buildings. 2025; 15(13):2368. https://doi.org/10.3390/buildings15132368

Chicago/Turabian Style

Dhanasekar, Yuvaraj, and Kaliyaperumal Sugirthamani Anandh. 2025. "From Diversity to Engagement: The Mediating Role of Job Satisfaction in the Link Between Diversity Climate and Organizational Withdrawal" Buildings 15, no. 13: 2368. https://doi.org/10.3390/buildings15132368

APA Style

Dhanasekar, Y., & Anandh, K. S. (2025). From Diversity to Engagement: The Mediating Role of Job Satisfaction in the Link Between Diversity Climate and Organizational Withdrawal. Buildings, 15(13), 2368. https://doi.org/10.3390/buildings15132368

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