Boosting Coordination and Employee Motivation in Mega-Project Sustainable Performance Through Quality Relationships: The Key Role of Quality Management System

Abstract

Coordination and employee motivation play vital roles in a mega-project’s sustainable performance, particularly in the construction industry. With increasing demands from stakeholders and employees in the construction sector, sustainable performance has emerged as a priority. However, the importance of quality relationships and quality management systems is often overlooked. This research addresses this gap by establishing a predictive model for sustainable performance. Data from 261 respondents in Pakistan’s construction industry were collected, and hypotheses were tested using partial least squares structural equation modeling. The results indicate that coordination and employee motivation exert a positive impact on sustainable performance. Furthermore, quality relationships partially mediate the relationship between coordination and sustainable performance and between employee motivation and sustainable performance. Additionally, quality management systems significantly moderate the relationship between coordination and sustainable performance, whereas the relationship between employee motivation and sustainable performance is insignificant. This study provides valuable insights for project coordinators, project managers, and policymakers on enhancing the stability of construction projects in emerging economies through quality relationships and quality management systems.

1. Introduction

Mega-projects in the construction sector face particular challenges [1] and involve many professionals, such as consultants, construction managers, contractors, designers, subcontractors, and specialists. Therefore, sustainability plays an essential role in mega-projects [2]. Mega-projects are major infrastructure projects that provide crucial public services, facilitating the production of everyday goods, social goods, and economic growth; they constitute the backbone of modern society [3,4].

However, industrial activities involve waste generation, environmental contamination, resource scarcity, and worsening environmental conditions [5]. These challenges complicate project management and require collaboration and coordination (COR) until the project is accomplished [6]. Mega-projects pose several difficulties and barriers to project management [7]. First, significant financial outlays, protracted construction, and uncontrollable events may occur throughout execution. Second, lengthy designed lifecycles and intricate construction processes demand high-level construction methods and quality. Due to the large number of parties involved and the requirement for cross-professional work, significantly higher levels of cross-functional coordination and collaboration efforts are required within mega-projects compared to typical projects. Therefore, the sustainable performance of mega-projects is a key concern for governments, users, and communities.

Due to their complexity, mega-projects provide valuable opportunities for applying theories and approaches to sustainable innovation. However, as the concept of performance is intricately linked to project stakeholders and remains unclear, determining the failure or success of the project remains challenging [8]. Therefore, mega-project sustainable performance (MSF) includes social, environmental, and economic aspects [4]. Effective COR between multiple contractual partners plays a determining role in the success of construction projects [9]. COR refers to the alignment, convergence, and harmonization of various stakeholders in any sector with numerous objectives [9]. Therefore, efficient and cohesive COR among agencies, consultants, owners, contractors, project management teams, suppliers, and users during the project implementation is essential to avoid issues leading to project failure [10].

The COR process seeks to enhance project delivery and increase efficiency by addressing the interconnectedness of project tasks and parties involved [11]. Uncertainties in the mega-project lifecycle impede teamwork, influencing the MSF. Moreover, employee motivation (EM) refers to the level of enthusiasm and commitment that the employees bear toward the project. To successfully coordinate a project, employee motivation should be upkept. Hence, predicting and managing EM is a key aspect of project COR [12]. Good coordination facilitates smooth project execution and ensures that all teams can work together effectively [13].

However, predicting EM and performance involves several difficulties, such as defining the characteristics of employee performance and identifying the elements affecting employee performance. Motivation in the workplace is defined as the direction of focus, mobilization of effort, and persistence of effort through time [14]. Most studies investigating motivation in the construction sector are flawed; for instance, most motivation theories focus only on an individual’s motivation and overlook the social context in which behaviors are carried out, limiting the generalizations that can be established [15]. While COR and EM are crucial factors in project performance, studies exploring how these elements interact to influence the long-term sustainability of mega-projects are scarce. This suggests a need for further research on the efficacy of COR and EM in contributing to MSF, which represent complex and resource-intensive endeavors with significant economic, social, and environmental impacts.

In recent years, numerous studies have focused on EM and COR separately by using different methods [16,17,18]. Surprisingly, the relationship between COR, EM, and their relationship with MSF by analyzing quality relationship (QR) in construction projects has largely been overlooked. To the best of our knowledge, little research has been conducted on this complex phenomenon, and no studies have examined how the quality management system (QMS) moderates the influences of COR and EM on MSF in the context of construction industries. To address this important research gap, the current study aims to improve sustainable performance by analyzing the effects of COR and EM on QR and MSF.

The current study’s framework was developed to address these initiatives. Therefore, this study aims to determine the following: (i) effective methods for managers to proactively address the COR and EM issues in mega-projects; (ii) whether QMS moderates the relationships between COR, EM, and MSF; and (iii) whether QR plays a mediating role in the connection between COR, EM, and MSF. This study examines the hypothesized relationship between COR, EM, and QR and aims to measure MSF using the suggested indicators. Moreover, QMS has been introduced as a novel moderating component in the interplay between COR, EM, and MSF, offering novel insight into a previously unexplored research area.

2. Materials and Methods, Literature Review, and Hypotheses Development

2.1. Coordination and Mega-Project Sustainable Performance

Mega-projects require the coordination of a variety of activities, involving continuous COR throughout the implementation processes. Most of these activities require support, such as frequent meetings among different stakeholders, to enhance the progress of a project with better satisfaction [8]. Therefore, a relational corporation is suggested to mean that COR is carried out by sharing purposes, mutual respect, and information. Moreover, COR factors in construction projects can be identified as part of a process, including resource priorities for essential tasks, comprehensive procurement planning, and identifying task components and dependencies like plans [19]. The COR processes include official COR, plans, meetings, procedures, rules, schedules, informal contacts, telephone, relational COR, and in-person interactions [20]. Construction projects are usually characterized by high ambiguity, inter-organizational, and complex interdependence of activities, highlighting the importance of communication [21]. Based on the debate above, our first hypothesis is as follows:

H1. 

Coordination has a significant and positive effect on the mega-project’s sustainable performance.

2.2. Employee Motivation and Mega-Project Sustainable Performance

In construction subcontractor employees, target setting, workforce needs, and incentives and rewards were identified as factors promoting constructive motivated behavior [22]. Notably, EM can enhance the sustainable performance of mega-projects. A comprehensive evaluation of the literature from disciplines other than construction revealed that efficacy, commitment, identification, and cohesion are effective at both levels [23]. These emotional attachments have been correlated with different motivational states, such as emotional connection to the organization [24]. Therefore, EM can enhance the sustainable performance of mega-projects. According to the above discussion, a second hypothesis is proposed:

H2. 

Employee motivation has a significant and positive effect on mega-project sustainable performance.

2.3. Coordination and Quality Relationship

COR is derived from effective communication, shared goals, common knowledge, and respect among team members [25]. The benefits of performing tasks and the inherent advantages of encouraging positive behaviors were identified as sources of increased job satisfaction [25]. QR here refers to the trust between the developer and the customer, as well as the dedication to upholding their working relationship over the long term [26]. Most successful collaborative partnerships provide compelling evidence of the crucial role of QR in upholding long-lasting, high-quality alliances. For example, Toyota’s ability to use cutting-edge technology and Chrysler’s ability to survive can be attributed to the strong bonds with their business partners [27]. QR is a crucial relational quality that enables partners to forge and grow normative links, which can lessen uncertainty in a close relationship and its unfavorable impacts [28]. According to the above discussion, a third hypothesis is proposed:

H3. 

Coordination has a significant and positive effect on quality relationship.

2.4. Employee Motivation and Quality Relationship

An individual’s response to various conditions determines motivation, which manifests in many ways [14]. Therefore, manager exchange illustrates the impact of a dyadic leader–follower connection on an employee’s motivation [29]. QR affects a result; relationships with business partners are crucial for enhancing performance [30]. The resulting balance of capital and skills decreases transaction costs dramatically and increases efficiency. Leonidou et al. [31] proposed that strong relationships are built by reducing opportunistic actions and conflicts, improving communication efficiency, adaptation, and managing cultural distance. Therefore, the workplace should be managed to improve the quality of partnerships. According to the above discussion, a fourth hypothesis is proposed:

H4. 

Employee motivation exerts a significant and positive effect on quality relationship.

2.5. The Mediating Role of Quality Relationship

This study presents three relationships to examine the mediating function of QR: (I) the effects of QR on COR and employee motivation; (ii) the effects of QR on the sustainable performance of mega-projects; and (iii) the mechanism of QR in converting COR and EM to MSF. Achieving these sustainability goals requires coordination among multiple stakeholders, such as suppliers, contractors, and project managers. However, determining the mechanism underlying the effects of COR on sustainable performance remains challenging. A key factor is the caliber of the connections between these stakeholders. Due to its partial win–lose interest and the short-term structure of corporate relationships, construction is a harsh atmosphere [32]. An ideal relationship between participants in mega-projects is rare. According to Pryke [33], relationship management is a core competency in the construction industry, and the consistency of relationships is a critical component of sustainable performance. Regarding how QR affects a result, relationships with business partners play an essential role in enhancing performance [30]. The resulting balance of capital and skills decreases transaction costs dramatically and increases efficiency. When a firm’s allies become a better basis for learning, the influence of quality collaborations in new environments leads to a positive result [34]. Thus, the quality of partnerships should be fostered by efficient workplace management. According to the above discussion, the following hypotheses are proposed:

H5. 

Quality relationship has a significant and positive effect on construction mega-projects’ sustainable performance.

H6a. 

Quality relationship mediates the association between coordination and mega-project sustainable performance.

H6b. 

Quality relationship mediates the association between employee motivation and mega-project sustainable performance.

2.6. The Moderating Role of the Quality Management System

QMS might affect the association between COR, EM, and MSF. Therefore, management responsibilities and motivational aspects should be considered when studying the effect of COR and EM on MSF. Poor management is common in the construction industry. Systematic management is also essential for the successful implementation of construction projects [35]. To avoid interruptions in activities, the roles and duties of each mega-project team participant should be well defined. A complex temporary multi-organizational structure is frequently established during the mega-project development process that constantly faces differences between two layers of goals: the participating organizations’ long-term aims and the project’s operational phase, and the construction project’s temporary purposes [36]. Dynamic management systems must be developed by main contractors to promote the COR of activities and monitor the actions of their representatives [37]. Therefore, the QMS facilitates the mega-project’s success. QMS was initially designed to fulfill the needs of stakeholders and is necessary to ensure that the project outcomes follow the corresponding requirements. Desmond [38] reported that poor staff does not lead to poor quality, but bad management does. Considering the importance of QMS on sustainable performance, the following hypothesis was proposed:

H7a. 

A quality management system moderates the relationship between coordination and mega-project sustainable performance.

H7b. 

A quality management system moderates the relationship between employee motivation and mega-project sustainable performance.

3. Research Methodology

3.1. Measures and Validation

The survey data from practitioners in the construction industry were gathered using questionnaires. In the first stage, a questionnaire was prepared to identify factors from the related literature. The final questionnaire was distributed among the construction workers in Pakistan. The comprehensive questionnaire comprised two sections. Demographic data about the respondents, including their age, degree of education, job title, and work experience, were included in the questionnaire’s first section. The second component of the questionnaire was further divided into five subsections, as shown in Appendix A. The first subsection of the questionnaire focused on the questions related to factors affecting project COR, including planning (PF), resource handling and record documentation (RDF), teamwork and leadership (TLF), value engineering and facilitating (EFF), and communication (CF). The constructs for this section were based on previous research by Alaloul et al. [39].

In the second section, the measures defined by Raoufi and Fayek [23] were used to determine the association between different components of EM, such as efficacy (EF), commitment (CM), identification (ID), and cohesion (CO). The third section included four items related to QMS, which were based on studies from Yen et al. [40]. In the fourth section, QR was calculated using four items, according to the methods of Sharma [41]. Finally, MSF was calculated using three dimensions: environmental performance (ENP), social performance (SCP), and economic performance (ECP). The environmental MSF was measured using three items; social MSF was measured using four items, and economical MSF was measured using three items. The constructs for this part were derived from Ali et al. [4]. The questionnaire used closed-end questions to obtain the respondents’ opinions using a 5-point Likert scale from 1 (strongly disagree) to 5 (strongly agree). The questionnaire and construct item details are provided below in Appendix A.

3.2. Data Collection and Sampling

The identification of factors from the literature provides the basis for the preliminary questionnaire. The questionnaire was designed to facilitate understanding and feasibility. Four construction professionals and three university professors examined the questionnaire’s design and structure to ensure that the questionnaire was easy to comprehend. Moreover, the importance of each factor in the context of Pakistan’s construction industry was evaluated. Eventually, a final questionnaire was developed with the updated list of factors, which was used to collect information from the respondents. The results were analyzed to determine the fundamental relationships and relative importance among the elements, supporting the subsequent analysis of COR, EM, and MSF.

The final survey questionnaire was distributed by email, personal visits, and other social media applications among 750 randomly selected construction experts. The sample included workers in Pakistan’s construction industry. Data were retrieved from government archives, online databases, and organizational records, which were publicly accessible. Help from the parties involved regular updates in construction and follow-up emails and phone calls in case of insufficient response time. The data collection process took five months to complete, starting in October 2023 and ending in March 2024. Assuming that every participant in a study fits inside a narrow enough sample insight, Elton and Yamane [42] presented the method below to determine the proper sample size.

$$\mathrm{n}={\displaystyle \frac{N}{1+N{e}^2}}$$

where n = sample size, N = population size, and e = margin of error. Academics have repeatedly applied this formula, demonstrating its usefulness and validity [43]. A total of 750 workers satisfied the research inclusion criteria (relevant employment experience). Therefore, the margin of error affects the findings’ dependability, which in turn affects how widely the research’s conclusions may be implemented. As the margin of error grows, the reliability of the results declines. Nevertheless, this study’s 5% margin of error was acknowledged by earlier researchers [43]. The sample size was as follows:

$$\mathrm{n}={\displaystyle \frac{750}{1+750({0.05)}^2}}={\displaystyle \frac{750}{1+750\left(0.0025\right)}=260.86\cong 261}$$

Therefore, to bolster the previously mentioned circumstances, a representative sample size of 261 was utilized in this study. Considering the lack of significant difference between the two approaches, selecting a larger sample size would seem desirable [44]. Finally, 261 responses were received, representing a 37.28% response rate, exceeding the 20% response rate, which is considered good [45]. The demographic information is shown in Figure 1. The distribution of respondents based on education, organization position, and experience is displayed in Figure 1. Respondents were required to have more than ten years of experience in the construction industry. In addition, most respondents were engineers who held master’s and Ph.D. degrees in the construction field. Therefore, the collected data were deemed adequate for perception analysis. Furthermore, the survey questionnaire included a cover letter outlining the study purpose and ensuring the privacy of the respondents. In this research, data were collected from different institutions such as PWD (Public Work Department), NESPAK (National Engineering Service Pakistan), NHA (National Highway Authority), and some other construction companies in Pakistan. Most of the respondents were civil engineers. The respondents included chief executive officers (CEOs), project managers (PMs), site engineers (SEs), designer engineers (DEs), project coordinators (PCs), planning engineers (PEs), and quality surveyors (QSs) in the construction industry. The participants had adequate expertise and skills to clarify the relationships in this research.

4. Results\Data Analysis

In this work, smart-PLS version 4 and partial least squares structural equation modeling (PLS-SEM) were employed for analysis. PLS-SEM is an effective technique for analyzing complex models, particularly with complex interactions between the variables. This method facilitates the identification and modeling of the direct and indirect impacts of variables. The primary goal of this study is to identify endogenous variables, those influenced by other variables in the model contribute the least to the overall variance. By doing so, the researchers aim to improve the model’s predictive accuracy and reduce noise, enhancing the clarity and reliability of the results. This approach is particularly useful in structural equation modeling with complex relationships. PLS-SEM can simultaneously handle structural and measurement models [46]. Thus, PLS-SEM was used to test the proposed model. As described by Hair et al. [46], the structural and measurement models were explicitly approximated to ensure accurate results.

4.1. Measurement Model

The investigation revealed that all constructs satisfied the standards for dependability (composite reliability (CR) and Cronbach’s alpha), which have been advocated by multiple scholars working in a variety of fields [47]. The average variance extracted (AVE) and factor loading values were used to determine convergent validity; the results indicated that all items had factor loading values exceeding 0.7 on their respective constructs. However, as previously demonstrated in survey-based studies, AVE values were higher than 0.5 [46]. Therefore, convergent validity was established in our research. The authors employed the HTMT and Fornell–Larcker approach to examine discriminant validity. The findings demonstrated that both constructs’ inter-correlation values were lower than those of the AVE square root. Additionally, the HTMT values were less than 0.9, as suggested by Hair et al. [46].

Table 1. Factor loading, CR, AVE, HTMT, standard deviation.

Construct	Factor Loading Range	Cronbach’s Alpha	CR	AVE	Mean	HTMT Below 0.9	Std. Deviation
PF	0.846–0.905	0.890	0.923	0.971	3.675	yes	1.217
RDF	0.750–0.869	0.767	0.866	0.683	4.035	yes	1.094
TLF	0.737–0.899	0.866	0.910	0.717	4.266	yes	0.825
EFF	0.833–0.899	0.897	0.928	0.764	4.256	yes	0.874
CF	0.834–0.896	0.892	0.925	0.756	4.268	yes	0.786
EF	0.741–0.887	O.801	0.874	0.699	4.186	yes	0.894
CM	0.812–0.850	0.783	0.874	0.698	4.275	yes	0.830
ID	0.811–0.844	0.773	0.869	0.688	3.778	yes	1.181
CO	0.808–0.883	0.792	0.879	0.707	4.296	yes	0.788
QR	0.785–0.877	0.861	0.906	0.706	4.235	yes	0.775
QMS	0.807–0.875	0.865	0.908	0.712	4.246	yes	0.783
ENP	0.760–0.868	0.855	0.902	0.698	4.367	yes	0.691
SCP	0.820–0.881	0.783	0.839	0.691	4.362	yes	0.866
ECP	0.743–0.853	0.840	0.812	0.732	3.886	yes	0.978

and

Table 2. Fornell–Larcker criterion test.

	CF	CM	CO	EF	EFF	ID	PF	ENP	QMS	QR	SCP	ECP	RDF	TLF
CF	0.870
CM	0.669	0.835
CO	0.748	0.701	0.841
EF	0.621	0.657	0.603	0.836
EFF	0.687	0.754	0.765	0.664	0.874
ID	0.727	0.762	0.754	0.672	0.687	0.829
PF	0.665	0.760	0.663	0.812	0.836	0.710	0.869
ENP	0.736	0.622	0.745	0.549	0.789	0.730	0.700	0.835
QMS	1.00	0.669	0.748	0.621	0.745	0.727	0.665	0.736	0.844
QR	0.833	0.692	0.780	0.639	0.633	0.720	0.681	0.739	0.834	0.840
SCP	0.625	0.753	0.688	0.653	0.754	0.822	0.702	0.620	0.652	0.672	0.826
ECP	0.792	0.744	0.812	0.650	0.798	0.799	0.696	0.761	0.792	0.782	0.741	0.847
RDF	0.725	0.653	0.788	0.753	0.654	0.722	0.802	0.720	0.552	0.572	0.800	0.745	0.812
TLF	0.692	0.544	0.712	0.550	0.698	0.799	0.796	0.661	0.592	0.582	0.641	0.737	0.711	0.832

provide the specifics of the findings as mentioned.

However, common method bias (CMB) is a serious problem that may impact assessments of construct reliability and validity. Researchers claim that gathering information for exogenous and endogenous components from diverse sources may significantly reduce the risk of process bias [48]. Consequently, the authors gathered data from different sources over a long period. Harman’s single factor test was employed to verify the absence of CMB [49].

4.2. Assessment of Structural Model

Collinearity statistics is essential for formative outer and inner models. The variance inflation factor (VIF) among exogenous constructs is a severe issue in Smart-PLS utilizing inner VIF values [46]. This research revealed that all of the exogenous latent constructs’ inner VIFs were less than 3.3. As a result, no collinearity was found in this study. Moreover, $R^2$ is a function of the variance described in the endogenous variables and reflects the model’s predictive power. An $R^2$ value of 0.19 is considered low, 0.33 is moderate, and 0.67 is considered substantial. In this study, the $R^2$ of MSF was 0.627, reflecting a moderate variance in the exogenous latent construct [46]. The model is expected to forecast by using the $Q^2$ Stone-Geisser value determined by blindfolding procedures [50]. The criterion of the Stone-Geissor $Q^2$ indicates that the model must be capable of predicting endogenous latent variable indicators. The outcome indicates a $Q^2$ value of 0.546 for the model, indicating predictive validity, as evidenced by the value exceeding zero.

The proposed study model contained second-order formative constructs, COR, and EM. Weights of first-order reflective constructs were estimated by Petter et al. [51], revealing their significance as CF = 0.367, EFF = 0.305, PF = 0.132, RDF = 0.196, TLF = 0.343, CM = 0.348, CO = 0.421, EF = 0.374 and ID = 0.204, p < 0.001. The VIF was also examined for multicollinearity. The lower VIF values, CF = 2.217, EFF = 1.351, PF = 1.090, RDF = 1.427, TLF = 2.160, CM = 1.293, CO = 1.560, EF = 1.617, and ID = 1.230 of all first-order constructs for COR and EM confirmed its validity [46]. Finally, the goodness of fit (GOF) was determined using the following formula:

$$\mathrm{GOF}=\sqrt{R^2\times AVE}$$

The PLS models’ global validation cutoff values range from 0 to 1, resulting in GOF large 0.36, medium 0.25 and small 0.1 [52]. The model’s GOF was determined to be 0.646, indicating a high capacity for prediction and good data fit; furthermore, our SRMR value was also in a reasonable range. Moreover, as shown in Figure 2, QR mediates the link between the exogenous constructs COR, EM, and MSF. Additionally, the authors tested the moderating variable QMS, the relationship between COR, EM, and MSF. COR and EM have a more significant impact on MSF (β = 0.240), (β = 0.037) in the construction industry. Thus, the findings support H1 and H2. The research also showed that COR and EM significantly affect QR (β = 0.460 and β = 0.298, respectively), which supports hypotheses H3 and H4. Moreover, QR also significantly impacted MSF (β = 0.330), supporting hypothesis H5.

Table 3. Hypothesis assessment.

	Path Relationship	β Value	T Statistics	p Values	Decision
H1	COR -> MSF	0.240	2.639	0.003	Supported
H2	EM -> MSF	O.037	2.764	0.000	Supported
H3	COR -> QR	O.460	5.763	0.000	Supported
H4	EM -> QR	O.298	3.842	0.000	Supported
H5	QR -> MSF	0.330	4.643	0.000	Supported
Mediation Analysis
H6a	COR -> MSF COR -> QR -> MSF	0.240 0.152	2.639 3.899	0.009 0.000	Partial Mediation
H6b	EM -> MSF EM -> QR -> MSF	0.037 0.096	2.764 3.182	0.000 0.002	Partial Mediation
Moderation Analysis
H7a	QMS*COR -> MSF	0.153	2.583	0.010	Supported
H7b	QMS*EM -> MSF	−0.198	2.907	0.004	Not Supported

and Figure 2 display the results of all hypotheses.

4.3. Importance–Performance Map Analysis (IPMA)

The importance–performance map analysis (IPMA) is a useful systematic tool that expands the traditional route coefficient estimates in a more diagnostic way and graphically illustrates the discrepancy between the variables’ performance and importance. The primary objective of IPMA is to determine which antecedents work well but are not very important and vice versa [47]. In our model, MSF is a dependent construct that is predicted by the following four antecedents: COR, CM, QR, and QMS. COR achieved an importance value of 0.385 and a performance value of 80.098, as shown in Figure 3 and

Table 4. Importance–performance results.

Construct	Importance	Performance
COR	0.385	80.098
CM	0.147	79.854
QR	0.328	81.451
QMS	0.229	81.632

. Similarly, the importance values of QR, QMS, and CM were 0.328, 0.229, and 0.147, with performance values of 81.451, 81.632, and 79.854, respectively. Comparing COR with QR, QMS, and CM, COR exhibited a higher importance value, while QMS achieved a higher performance value than QR, COR, and CM. In the ceteris paribus situation, an increase in QR, QMS, and CM performance by one unit leads to a 0.328-, 0.229-, and 0.147-unit improvement in MSF performance.

Similarly, a one-unit increase in COR performance was found to lead to a 0.385-unit improvement in MSF performance. Therefore, the construction industry in Pakistan should focus on QR, QMS, and CM, along with COR. To produce more observable and quantifiable results, QMS first ensures consistent procedures, quality control, and ongoing improvements. Second, QMS frequently includes more standardized frameworks that are directly measurable and amenable to improvement. However, despite its importance, coordination (COR) is frequently impacted by softer factors like interpersonal dynamics and communication, which are more difficult to quantify and control.

4.4. Mediation and Moderation Analysis

Mediation refers to the process in which the effects of an antecedent construct are transmitted to an outcome construct through a mediating construct [53]. In this study, the mediating construct QR was hypothesized to mediate the effects of COR and EM on MSF. First, COR and EM were confirmed to exert direct and significant effects on MSF, and QR was hypothesized to act as a mediator (H6a, H6b). Constructive relationships that are marked by mutual respect, trust, and good communication can facilitate COR efforts and produce longer-term results. Consequently, QR plays a mediating role in the relationship between COR and MSF. Accordingly, enhancing the QR can amplify the benefits of COR, ultimately assisting in the timely and sustainable completion of mega-projects. Moreover, good connections based on mutual respect, trust, and efficient communication improve EM over time. This suggests that the quality of these connections acts as a mediator, enhancing the relationship between EM and the MSF. As a result, cultivating strong bonds within the team can enhance EM, improving mega-project sustainability.

Construction companies may motivate their workforce to meet sustainability targets and ensure that projects are executed successfully, ethically, and efficiently by placing a high priority on QR. The authors found that QR played a significant mediating role between COR, EM, and MSF, as shown in Table 3. Thus, this study also supports hypotheses 6a and 6b of mediation. Considering that both direct and indirect effects pointed in the same direction, the mediation effects were found to be complementary [53]. Finally, the authors assessed the moderating effect of QMS on MSF (H7a, H7b). Data showed that QMS significantly strengthens the link between COR and MSF (β = 0.153, p < 0.010). Similarly, the effect of QMS on the association between EM and MSF was found to be insignificant (β = −0.198, p < 0.004). Figure 4 demonstrates that QMS enhances MSF in the construction sector when stakeholders or managers find higher QMS rather than low QMS. The moderating effect test is shown in Figure 4 and Figure 5.

5. Discussion

This study was conducted to explore the impact of COR and EM on MSF by using the PLS-SEM method. The introduction of QMS between COR and MSF was positive (0.153), indicating that QMS plays a significant role in this relationship. Additionally, the introduction of QMS between EM and MSF was unfavorable (−0.198), indicating that QMS did not play a significant role in this relationship. EM is an individual trait that enhances an individual’s motivation level. In contrast, QMS is related to managing the quality of construction work and represents a different phenomenon, explaining the lack of positive moderation. Therefore, while examining the effect of COR on MSF, managerial duties were found to be just as essential as motivating considerations. The mediation analysis procedure developed by Baron and Kenny [54] has been used by researchers. Table 3 illustrates a significant direct and indirect impact between EM and MSF, indicating that QR exerts a partial mediation. Moreover, the relationship between COR and MSF is significant directly or indirectly, suggesting that QR exhibits a partial mediation effect.

The finding sheds light on COR and EM and is significant for MSF. Effective COR involves seamless teamwork and organized efforts, along with high EM, and significantly enhances the long-term success and sustainability of mega-projects. Good teamwork and employee motivation lead to better project outcomes, such as meeting environmental, social, and economic goals. This positive and significant relationship highlights the importance of fostering collaboration and motivation within teams to achieve sustainable performance in complex, resource-intensive mega-projects. Furthermore, QR is a key mediating variable that enhances the COR and EM for enhancing MSF. The cohesion-related factors (beta 0.421) have the most significant influence on EM regarding the relative importance of the four EM factors. Moreover, the communication-related factors (beta 0.367) have the most significant influence on COR regarding the relative importance of other COR factors. It can be regarded as the most crucial indicator affecting MSF. These factors should be analyzed to evaluate their impact on MSF to achieve better COR and EM in construction projects. Project coordinators and project managers should be involved in the project’s planning to overcome this problem [55].

Project professionals have the expertise, qualification, experience, and knowledge of construction techniques. Their participation in the mega-project in the pre-construction phase could improve project COR and EM, thereby boosting the possibility of sustainable performance of mega-projects. In the pre-construction phase, effective planning, clear communication, and strategic decision-making by these key stakeholders can establish a strong foundation for COR and EM by setting clear goals and fostering a collaborative environment. A streamlined COR and motivated employees improve resource utilization, reduce delays, and enhance adherence to sustainability goals, such as minimizing environmental impact and ensuring long-term economic and social benefits. Ultimately, the proactive involvement of project managers and policymakers in this early stage creates a positive ripple effect, driving the project toward successful and sustainable outcomes. The communication-related factors and cohesion-related factors are crucial elements for all participants and are pivotal for the success of the mega-project. In addition to cohesion-related factors and communication-related factors, COR and EM are also influenced by the other model factors. This effect has been verified by evaluating relationships.

6. Conclusions and Implication

6.1. Conclusions

Previous studies have confirmed the importance of COR and EM in the construction industry and other fields. The study’s findings from the conceptual model’s calculation support the hypothesis. The findings of the PLS-SEM study revealed that COR and EM directly impacted mega-projects and suggested that the four most important factors were communication and cohesion, teamwork and leadership, efficacy, and commitment-related factors with maximum standardized path coefficient. The conceptual model’s GOF index was calculated at 0.646, indicating that the conceptual model has sufficient validity and reliability, matching the data supported by the PLS-SEM. However, the study also indicated that these factors impact MSF and influence COR and EM in construction mega-projects. The findings of the standardized conceptual model assist project coordinators and project managers in identifying areas to improve for enhanced COR and EM.

6.2. Theoretical Implications

This study offers important new insights into a number of crucial areas related to mega-projects. Firstly, the study clarifies how efficient coordination between various stakeholders improves project outcomes, reduces delays, and maximizes resource utilization, thereby enriching our understanding of COR processes. Secondly, this research also clarifies the importance of EM in boosting output and achieving project objectives. This research offers useful techniques to improve labor productivity by identifying elements that drive motivation, such as clear communication, acknowledgment, and career growth possibilities. Moreover, this study also investigates the sustainability of mega-projects, emphasizing the importance of incorporating social, economic, and environmental factors into project development and implementation. This strategy supports global sustainability objectives while ensuring sustainability for future generations.

The study also explores the mediating effect of QR, demonstrating how robust, trust-based interactions among project participants can lead to high-quality project performance. These connections promote cooperation, lessen friction, and ease the exchange of information, all of which promote project success in its final stages. Finally, the moderating function of QMS is investigated, demonstrating how strong QMS frameworks amplified the benefits of CM and COR on project results. The QMS improved project performance by ensuring that quality requirements were regularly met by implementing defined processes and continuous improvement activities. These theoretical contributions provide construction industry workers a direction and a comprehensive understanding of the dynamics involved in managing mega-projects.

6.3. Practical Implications

This research provides solutions to problems in the construction industry. Firstly, the results emphasize the importance of setting up robust COR mechanisms. To reduce inefficiencies and prevent delays, project managers and leaders can use advanced project management tools and communication platforms to enable smooth COR among different stakeholders. The results imply that investments in motivational techniques can lead to appreciable gains in project performance regarding EM. Construction companies require proactive efforts in rewarding and acknowledging worker achievements and should offer opportunities for professional growth while promoting a positive work environment. Such initiatives can increase productivity and job satisfaction, ultimately leading to project success. Multiple teams and subcontractors are involved in mega-projects, and recognizing and rewarding key contributions can improve morale and productivity. For example, acknowledging employees who excel in safety practices or those who contribute innovative solutions to coordination issues can boost team collaboration and project success.

Secondly, the construction companies are encouraged to incorporate sustainability ideas into their project planning and execution processes by focusing on sustainable performance. Moreover, blockchain and AI can enhance transparency, security, and accountability within mega-projects by enabling immutable records of transactions, contracts, and project milestones. Such measures can reduce fraud, improve stakeholder collaboration, and streamline project management processes. AI-powered tools can also improve risk management by identifying potential issues in real time, thereby improving project outcomes and sustainability. Furthermore, by integrating BIM, project teams can streamline coordination efforts, improve accuracy, and minimize errors, making it an essential tool for managing mega-projects. Using sustainable materials, prioritizing energy efficiency first, and implementing green building methods will not only improve environmental results but also boost the company’s reputation and draw in eco-aware clients. Utilizing sustainable materials such as low-carbon cement could enhance energy efficiency. Moreover, LEED-certified projects are designed to be energy-efficient, use sustainable materials, and reduce waste. These could improve project sustainable outcomes.

The study also emphasizes the importance of QR in the accomplishment of project success. Practitioners should concentrate on developing solid, trustworthy relationships with suppliers, subcontractors, and clients, among other project participants. Transparent communication, cooperative problem-solving, and consistent involvement of stakeholders can help achieve this. Finally, the moderating role of QMS implies that QMS frameworks should be adopted and strictly implemented by construction companies. Organizations can ensure that project outcomes meet or surpass quality standards by following established quality practices and always seeking improvement. This will increase client satisfaction and provide a competitive advantage.

6.4. Limitations and Future Research

Nevertheless, the limitations of the present study should be acknowledged. First, this study’s conclusions are based on a questionnaire survey conducted in Pakistan, and the results cannot be extended to other countries. Researchers from other countries may conduct a similar study to examine the contribution of QR and QMS to the relationship between COR, CM, and MSF and to compare the contributions of QR and QMS in various nations. Further research is needed to explore the complex relationship between COR, EM, and sustainable performance in mega-projects, thereby identifying complexities specific to the construction sector. Examining how modern technologies like blockchain and artificial intelligence might improve stakeholder COR and communication is an interesting direction to pursue. Mega-project dependability and efficiency may be revolutionized by applying these technologies to project management procedures. Finally, analyzing the efficacy of diverse QMSs in diverse mega-project categories and cultural settings can provide a more comprehensive understanding of appropriate methodologies. The most flexible and effective quality management strategies can be found through comparative studies that examine the performance of QMS in various organizational and geographic contexts. These studies also offer a comprehensive framework for improving mega-project outcomes internationally.